Complete Mitochondrial Genome Sequence Analysis Revealed Double Matrilineal Components in Indian Ghungroo Pigs

Complete Mitochondrial Genome Sequence Analysis Revealed Double Matrilineal Components in Indian Ghungroo Pigs | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Complete Mitochondrial Genome Sequence Analysis Revealed Double Matrilineal Components in Indian Ghungroo Pigs Pranab Jyoti Das, Satish Kumar, Manasee Choudhury, Seema Rani Pegu, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4561770/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Jan, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract This research aimed to characterize the mitochondrial genome of the Ghungroo (GH) pig, a notable breed in India, along with its crossbred varieties, to elucidate their matrilineal components, evolutionary history, and implications for conservation. Seven pigs (5 GH, 2 crossbred, namely Rani and Asha) were sequenced for complete mitochondrial genome, while 24 pigs (11 GH, 6 Rani, and 7 Asha) were sequenced for the complete D-loop of the mitochondrial genome. The genome size of these pigs was determined to be 16690 bp. Analysis of the mitochondrial sequences and phylogenetics uncovered two distinct matrilineal components within the GH population, a phenomenon also observed in its crossbred counterparts, Rani and Asha. Phylogenetic analysis demonstrated a clear clustering of GH sequences into two clades, indicating the presence of two independent maternal lineages. Haplotype analysis revealed 10 different haplotypes, with some sequences shared among GH, Rani, and Asha, while others differed due to varying matrilineal origins. Furthermore, examination of tRNA genes and nucleotide composition offered insights into genetic diversity within these pigs. The findings suggest that geographical isolation and historical events likely contributed to the emergence of distinct maternal lineages within the GH breed. This study underscores the significance of mitochondrial DNA analysis in uncovering hidden genetic diversity within seemingly uniform populations. The molecular insights gained into the genetic makeup of GH pigs could aid in designing effective breeding programs for conservation efforts and highlight its significance in understanding the broader context of pig domestication in India. Biological sciences/Genetics Biological sciences/Molecular biology Indian Ghungroo pig Mitochondrial genome D-loop Double Matrilineal Phylogeny Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Pigs ( Sus scrofa) are one of the most ancient domesticated, socioeconomically valued and widely distributed livestock species across the world (Bharati et al. 2022 ). The process of pig domestication occurred independently in various regions from its wild ancestors, with evidence suggesting occurrences in western Asia around 8500 BC (Ervynck et al. 2001 ; Conolly et al. 2011 ), in China around 6500 BC (Cucchi et al. 2011 ), and in Southeast Asia and Europe approximately 9000 years ago (Giuffra et al. 2000 ; Larson et al. 2010 ). India is recognised as one of the centres for the domestication of pigs and domestic pigs potentially originating from Indian wild boars separate from European and other Asiatic lineages (Das et al. 2024 ). The genomic analyses revealed distinct mitochondrial haplotypes in Indian pig populations that were present in wild boar populations of India, but not in pigs from Europe and the East, indicating a localized event for domestication (Larson et al. 2010 ). Pig farming holds significant importance in the livelihood of rural tribal communities (Bharati et al. 2022 ). India possesses a rich diversity of pig genetic resources, with significant variations among populations. Fourteen indigenous pig breeds, documented in the country's breed database, contribute significantly to the socioeconomic upliftment of rural poor pig farmers. Among these breeds, the Ghungroo (GH) stands out as one of the most prolific pig breeds, primarily found in West Bengal and Assam which has the potential to be used in various breeding programmes. This is the first registered pig breed of India exhibits distinctive features such as a black coat, a characteristic bulldog-like face, a cylindrical body shape, and large, drooping ears [Fig. 1 (a-b)] (Banik et al. 2012 ; Bharati et al. 2023 ). The northeastern region of India, particularly Assam, emerges as a key hub for pig production, with GH and Doom being the predominant indigenous breeds traditionally raised in low-input backyard farming systems. These indigenous breeds possess inherent traits such as early sexual maturity, adaptability to harsh climate and management conditions and requirement of low input, disease resistance, strong maternal instincts, and desirable meat quality makes them the best enterprise for the weaker sections of society and the progressive farmers as well (Bharati et al. 2022 ). However, to enhance growth and reproductive performance, breeds like Hampshire and Duroc have been introduced and crossbred with GH, resulting in varieties like Rani and Asha. Notably, these crossbred varieties retain the maternal genetic heritage of GH (Bharati et al. 2021 ). Mammalian mitochondrial DNA genome (mtDNA) is a double-stranded molecule, composed of an H (heavy) strand and an L (light) strand and is approximately 16.5 kb in size that varies with the species viz . cattle 16.34 Kb, goat 16.64 Kb; sheep 16.61 Kb; buffalo 16.36 Kb and in pig 16.69 Kb (Hu and Gao 2016; De et al. 2019 ; Niu et al. 2019 ; Siddiki et al. 2019 ; Arbizu et al. 2022 ). MtDNA encodes crucial proteins of the electron transport chain. The location of genes varies in different species but most genes are located on the H-strand and only one or two genes are located on the L-strand. The mtDNA also has 22 tRNAs and 2 rRNAs that are involved in mtDNA transcript production and processing. Its maternal inheritance pattern and faster base substitution evolutionary rate allow for the investigation of evolutionary relationships within and between species (Avise 2000 ). Of the mtDNA genome, the control region i.e. D-loop was used for investigating the genetic population structure of closely related animals in restricted areas (Ghivizzani et al. 1993 ; Alves et al. 2003 ). The complete mtDNA of GH and its crossbreds, along with the assessment of matrilineal components and genetic diversity, represents a vital step towards conservation and genetic improvement. The earlier reports mainly focused on small fragments of mtDNA, however, the present study aimed to characterize the complete mtDNA of Indian GH pigs and its crossbred varieties, tracing domestication patterns based on maternal lineages. Phylogenetic analyses will shed light on relationships among GH and its crossbreds and to what extent they were affected by the modern commercial breeds (Duroc, Yorkshire and Landrace) in maternal lineage, thus providing valuable insights into the multiple matrilinear components and evolutionary history of GH pigs. 2. Methods and Materials 2.1. Ethics Statement All experiments conducted in this study adhered to the guidelines set forth by the animal ethics committee of the institute, with approval no. NRCP/CPCSEA/1658/IAEC-20/2018. Blood collection from the animals was performed with supreme care to minimize discomfort or harm. 2.2. Animals and Sampling This study focused on the indigenous pig breed GH and its crossbreds found in the Bengal and Assam regions of India. A total of five GH pigs were used for the characterisation of the complete mtDNA genomic sequence and 11 GH pigs were used for the characterization of the complete D-loop sequence of the mitochondrial genome. Additionally, crossbred varieties, namely Asha and Rani, with maternal components of GH, were included in the study. Seven animals from the Asha variety and six from the Rani variety were used for complete D-loop sequence analysis, while one animal each from Rani and Asha crossbreds was employed for complete mitogenome sequencing. Rani (Fig. 1 d) is a crossbred pig variety developed by crossing ♀ GH and ♂Hampshire pigs, with 50% blood of each breed (Bharati et al. 2021 ). Asha (Fig. 1 c), on the other hand, is a crossbred pig variety obtained by crossing ♀ Rani with the terminal sire ♂ Duroc, thereby maintaining mitochondrial inheritance from GH pigs exclusively. Blood samples of 5 ml each were collected from the anterior vena cava using a sterile needle and BD vacutainer, and then stored at -20°C until DNA extraction. 2.3. DNA extraction Genomic DNA was extracted from the blood samples using the standard phenol-chloroform method (Sambrook and Russel 2001 ; Kumar et al. 2024 ). The quality of extracted genomic DNA was checked on agarose gel electrophoresis and the DNA samples without any smearing and having intact bands were used for further study. The purity and concentration of DNA were determined using a NanoDrop spectrophotometer, with samples having an A260/A280 ratio falling between 1.7 to 1.9 considered suitable for downstream applications. The DNA samples having good quality and purity were stored at -20°C until further use. 2.4. PCR amplification of mitochondrial genome: The primers sequences, amplification temperatures and product size along with the amplification conditions were similar to our earlier study (Das et al. 2024 ). Briefly, 30 pairs of overlapping primers were used for the amplification of the complete mtDNA of GH and its crossbreds. The PCR was carried out in a 25 µl reaction mixture having 2.5 µl of 10X PCR buffer (with Mg 2+ ), 0.5 µl of forward and reverse primer each (10 pm/µl), 0.5 µl of dNTPs (10 mM), 0.2 µl Taq polymerase (1 unit), 1 µl DNA samples (50 ng/µl), and 19.8 µl of NFW. The PCR condition was conducted in a thermocycler (Applied Biosystems) involving an initial denaturation at 95°C for 7 min, followed by 30 cycles of denaturation at 95°C for 30 s, annealing at 58–59°C for 30 s, and extension at 72°C for 30 s followed by a 5 min final extension at 72°C. The PCR products were then analyzed by 2% agarose gel electrophoresis. The PCR products showing intact specific bands and without any smearing was used for downstream works and processed for sequencing. 2.5. Sequencing of amplicon and structure analysis mitogenome The purified PCR products were subjected to Sanger sequencing using 3500 Series Genetic Analyzers (Applied Biosystems). Sanger Sequencing not only sequences individual DNA fragments sequentially, but also guarantees full coverage of the reference genome. This is achieved through the utilization of overlapping fragments, effectively eliminating any gaps and ensuring a comprehensive 100% coverage of the targeted sequence (Hagemann 2015 ). The obtained sequences from Sanger sequencing were trimmed and edited using DNAstar and Megalign software. The annotation of complete mtDNA sequences was finalized using MITOS2 tools in the Galaxy webserver Platform (Al Arab et al. 2017 ; Donath et al. 2019 ; Afgan et al. 2022 ). The circular structure of the complete mitogenome was constructed using Proksee Server (Grant et al. 2023 ). The structure of the tRNA sequence identified in the complete mitogenome was predicted using the tRNAscan-SE 2.0 web server (Chan et al. 2021 ). The Nucleotide frequencies, G + C content, and A + T content of mitogenome were determined using EditSeq of Laser gene (DNA STAR Inc.). The skewness of protein-coding genes in the mitogenomes was calculated using the formula: GC skew = (G − C) / (G + C) and AT skew = (A − T) / (A + T) (Nguyen et al. 2017 ). 2.6. Phylogenetic Analysis and Genetic Distance Analysis Phylogenetic analysis, using the complete mtDNA sequences of pigs generated in this study, was conducted, along with sequences from Indian wild boars and African warthog (AWH) downloaded from NCBI GenBank for comparison. The nucleotide sequences were aligned using the MUSCLE algorithm (Edgar 2004 ) of MEGA 11 (Tamura et al. 2021 ). The substitution model utilized for the alignment was thoroughly assessed, and the Hasegawa-Kishino-Yano (HKY) model, which yielded the lowest Bayesian information criterion (BIC) score, was selected as the most suitable for both alignment and phylogenetic analysis. Detailed information regarding each model, including their respective BIC, AICc values, Maximum Likelihood value (lnL), and the number of parameters, is provided in Supplementary Table 1. Subsequently, the aligned sequences were employed to construct a phylogenetic tree using the maximum likelihood (ML) method with 1000 bootstrap replications in MEGA 11, aimed at elucidating the matrilineal components in GH and its crossbred pig varieties. Apart from the complete mitogenome sequence, complete D-loop sequences were also used for the phylogenetic and genetic distance analysis. For this purpose, the complete D-loop sequences of European pig breeds, which contributed to the development of crossbred varieties of GH pigs, were retrieved from the NCBI GenBank. The list of sequences used for the phylogenetic analysis is provided in Supplementary Tables 2a & 2b. The nucleotide sequences were aligned using the MUSCLE package of MEGA 11 employing the HKY + G model as the best fit, which accounts for varying nucleotide frequencies and differing rates of transitions and transversions. Details of each substitution model are provided in Supplementary Table 3. The analysis encompassed 28 nucleotide sequences and a total of 1330 positions in the final dataset. These aligned sequences were used to construct a phylogenetic tree via the ML method with 1000 bootstrap replications. Furthermore, genetic distances among the sequences were calculated utilizing the maximum composite likelihood (MCL) model in MEGA 11 (Kumar et al. 2018 ; Tamura et al. 2021 ). The phylogenetic tree constructed in MEGA was visualized using the FigTree v.1.4.4 software (Rambaut 2010 ). The genetic distances among the sequences were calculated using the MCL model in MEGA 11 (Kumar et al. 2018 ; Tamura et al. 2021 ). The AWH was selected as an outgroup for phylogenetic tree analysis because it is well known to be different from Eurasian wild boars and this particular type of pig has been commonly employed in past phylogenetic investigations of pigs (Larson et al. 2005 ; Lucchini et al. 2005 ; Yu et al. 2013 ). The haplotypes were identified from sequences of complete mitogenome and complete D-loop sequences using DnaSP v.6 (Rozas et al. 2017 ). The network of haplotype was generated by the minimum spanning network method (epsilon = 0) using PopART v.1.7 (Leigh and Bryant 2015 ). The nucleotide diversity, no. of segregating sites, Tajima's D value and haplotype frequency were also analysed using DnaSP v.6 (Rozas et al. 2017 ). 3. Results and Discussion This study was done to characterise the mitochondrial genome of GH and its crossbreds. The complete mitogenome and D-Loop sequences were used for phylogenetic analysis and genetic distance estimation and to access the matrilineal components in these pigs. The D-loop region of the mitochondrial genome has high mutation rate and variable than any other region of the nuclear or mitochondrial genome (Nicholls and Minczuk 2014) and thus important region for the phylogenetic analysis and evolution of animal breeds (Chen et al. 2011). Sequencing and submission of complete mtDNA Genome The entire mtDNA of 5 GH and one each of the Rani and Asha crossbred varieties were amplified using 30 pairs of overlapping primers and sequenced by Sanger sequencing. All the fragments, including the D-loop , 2 rRNA, 22 tRNA, 13 coding genes, and repeat regions, were aligned to obtain the complete mtDNA genome of each pig and the sequences were deposited into the NCBI GenBank database and assigned accession numbers MT501674, MZ703184, OM617468, OM634652, MZ647672 for GH breed; ON706057 for Rani; and ON715893 for Asha. Apart from the complete mtDNA genome, complete D-loop sequences were amplified and sequenced using Sanger sequencing from GH, Asha and Rani pigs. The sequences were trimmed and edited using DNAstar and Megalign software and these sequences were submitted to NCBI GenBank database and received the accession numbers for GH ( OP185718, OP185719, OP185720, OP185721, OP185722 , and OP185723 ); Asha ( ON934748, ON934749, ON934750, ON934751, ON934752, and ON934753 ) and Rani ( OP352470, OP352471, OP352472, OP352473, and OP352474 ). The base composition of the mtDNA genome The complete mtDNA of all the GH and its crossbred viz . Rani and Asha were found to be of size 16690 bp and for all the mitogenome, viz . GH, Asha and Rani, the approximate base composition was 34.7% for Adenine (A), 25.8% for Thymine (T), 13.3% for Guanine (G) and 26.17% for Cytosine(C), while the G+C content was, 39.5% for all the breeds studied. The composition of different nucleotide base compositions of the mitochondrial genome is depicted in Table 1, which shows that the majority of the nucleotides in the mitogenomes were AT-rich with 60.52 % of total bases. The nucleotide composition and organization of the mitogenome of GH and its crossbreds was similar to other pigs viz . Min pig (Niu et al. 2019). The size of the mitogenome in these pigs was comparable with the earlier reports of pigs in Asian as well as European pig breeds (Kim et al. 2002; Yu et al. 2013; De et al. 2019; Thom et al. 2021; Das et al. 2024). The nucleotide composition in mtDNA of I Pig was 34.66% for A, 26.24% for C, 13.35%, for G and 25.75% for T, the A+T content was 60.41% (Nguyen et al. 2017) while in Indian wild boar was 26.25, 13.40, 25.79 and 34.56 % for C, G, T and A, respectively and A+T content was 60.35 (Das et al. 2024). Annotation of Complete Mitogenome: The mitogenome has one non-coding control region viz . displacement loop ( D-loop ), 22 transfer RNAs (tRNAs), 2 ribosomal RNAs (rRNAs), and 13 protein-coding genes which were similar to other pig mitogenomes (Bich Vo 2018). The typical circular structure of the mitogenome of GH, Asha and Rani is depicted in Fig. 2(a-c) which depicts the H and L strands, position of all the genes, tRNAs, rRNAs and D-loop along with GC content and Skewness of GC or AT. The annotation of the complete mitogenome of the GH breed is shown in Table 2. The D-loop was 1254 bp long and located between tRNA-Pro and tRNA-Phe having repeat regions. The two rRNAs viz . 12S and 16S rRNAs were 960 and 1570 bp, respectively. The size of tRNAs was varied from 59 ( tRNA-Ser-1) to 75 bp ( tRNA-Leu, tRNA-Asn) in size. The mitogenome had a total of 6 overlaps among all the genes ranging from 1 to 43 bp long. Additionally, there were 11 non-coding spaces ranging from 1-32 bp in length. The protein-coding genes had a total sequence length of 11,409 bp ranging from 204 ( ATP8 ) to 1821 ( ND5 ), which is 68.36 % of the total mitogenome. The H-strand of the mitogenome consists of all the protein-coding genes, tRNAs, rRNAs and D-loop , except the ND6 gene and 8 tRNAs ( tRNA-Ala, tRNA-Asn, tRNA-Cys, tRNA-Tyr, tRNA-Ser, tRNA-GLU, tRNA-Pro ) which were encoded on L-strand (Fig. 2). Consistent with our findings, the length of 13 protein-coding genes ranged from 204 bp to 1,821 bp, and a total of 11,413 bp in I pig (Nguyen et al. 2017). Furthermore, studies in various pig populations (Wang et al. 2016; Nguyen et al. 2017; Bich Vo 2018), birds (Liu et al. 2021), and humans (Taanman 1999) have identified one protein-coding gene and eight tRNA genes encoded on the L-strand. In contrast, prior research on the mitochondrial DNA (mtDNA) of wild and domestic pigs revealed only one protein-coding gene ( ND6 ) and seven tRNA genes ( tRNAGln, tRNAAla, tRNAAsn, tRNACys, tRNAPro, tRNATyr, tRNAGlu ) encoded on the L-strand (Jadav et al., 2019). However, another study indicated two protein-coding genes ( COX3 , ND6 ) and two tRNA genes ( tRNAPro, tRNAGlu ) on the L-strand (Singh et al. 2016). Notably, the complete mitochondrial genome of Daweizi and Ningxiang pigs revealed that all mitochondrial genes were encoded on the L-strand, except for three tRNA genes ( tRNAIle, tRNAAsp , tRNALeu ), which were encoded on the H-strand (Xu et al. 2015b, a). The arrangement and orientation of genes in the present study align with earlier reports on vertebrate and pig mitogenomes (Nguyen et al. 2017; Bich Vo 2018; Sarvani et al. 2018; De et al. 2019; Kumar Jadav et al. 2019). Each protein-coding gene begins with the start codon ATG, except for ND4L , which starts with GTG, while ND3, ND2 , and ND5 start with ATA. The termination codons in six protein-coding genes ( ND3, COX2, COX3, ND1, ND2 and ND4 ) were incomplete and were subsequently completed by the addition of 3’ A residues to the mRNA during post-transcriptional polyadenylation. The annotation and codon sequences in our study are consistent with those found in the mitogenomes of other pig breeds from India and South-East Asia like I, Nicobari ((Yu et al. 2013; Nguyen et al. 2017; Bich Vo 2018; De et al. 2019; Kumar Jadav et al. 2019). In contrast to our findings, Singh et al. (2016) reported that all protein-coding genes had ATG as the start codon except for ND3, ND4, ND5, ND1, and ND2, which started with ATA. In the mitochondrial genome of Daweizi pig, ND2, ND3, and ND5 began with ATA, ND4L with GTG, and ND6 with ATT, while the remaining proteins initiated with ATG (Xu et al. 2015a). In Swedish pig breeds, the start codon for ND2 and ND4L was ATT and GTG, respectively (Ursing and Arnason 1998). The nucleotide composition bias in mitogenome was estimated by GC and AT skews, and it showed that all genes on H stand coding for protein and rRNA were negatively GC-skewed and positively AT-skewed, which denoted cytosine and adenine biasedness. The most cytosine bias was observed in ATPase 8 (-0.52), while the least cytosine bias was observed in 16S rRNA (-0.11). In contrast, the 12S rRNA and 16S rRNA genes had the most adenine bias (0.25), while the COX1 gene had no bias for AT content, which means that its adenine content is equal to the thymine content. The ND6 gene was the only gene coded in the L strand that was positively skewed for GC content (0.55), whereas it was negatively skewed for AT content (-0.36) (Table 2). The AT content of the D-loop was 57.81 %, whereas the GC skew and AT skew were found to be -0.26 and 0.14, respectively. The AT content of the D-loop (57.81 %) was lesser than that of the I pig (60.09 %), Ningxiang pig (60.52 %) and Wild pig (60.65 %) (Nguyen et al. 2017; Kumar Jadav et al. 2019). The AT content, AT skew, and GC skew were used to determine the nucleotide composition behaviour of mitochondrial genomes as well as related to phylogenetics (Hassanin et al. 2005; Wei et al. 2010). The nucleotide composition bias within the mitogenome was assessed using GC and AT skews, revealing that all genes on the H strand encoding for proteins and rRNA exhibited negative GC-skew and positive AT-skew, indicating a bias towards cytosine and adenine. Among these, ATPase8 displayed the highest cytosine bias (-0.52), while 16S rRNA showed the least (-0.11). Conversely, 12S rRNA and 16S rRNA exhibited the highest adenine bias (0.25), while COX1 showed no bias in AT content, implying equal adenine and thymine content. Notably, the ND6 gene, the sole gene encoded on the L strand, demonstrated positive GC skew (0.55) and negative AT skew (-0.36) (Table 2). The AT content of the D-loop was determined to be 57.81%, with corresponding GC and AT skews of -0.26 and 0.14, respectively. This AT content was lower than that observed in I pig (60.09%), Ningxiang pig (60.52%), and Wild pig (60.65%) (Nguyen et al. 2017; Kumar Jadav et al. 2019). Utilizing AT content, AT skew, and GC skew aids in understanding the nucleotide composition patterns within mitochondrial genomes and their relevance to phylogenetics (Hassanin et al. 2005; Wei et al. 2010). Structure of tRNA The mitogenome of GH and its crossbred had 22 tRNA genes encoded for 22 tRNAs which consists of 2 tRNAs for Leucine and Serine amino acids while one tRNA for each of the other amino acids. All the tRNAs except eight were encoded on the H strand. The tRNA structure predicted by the tRNAscan-SE server revealed that all the tRNAs have typical cloverleaf structures except Ser-I which was devoid of D-arm. The structure and number of tRNAs in our study were similar to earlier reports in pigs (Nguyen et al. 2017). The structure of all the tRNAs is depicted in Fig. 3. Phylogenetic analysis and Double matrilineal within Ghungroo pigs The aligned complete mitochondrial genome sequence of GH and its crossbred pigs identified 27 polymorphic sites (Table 3), with one insertion and one deletion in the rRNA region of the Rani mitogenome. Out of these polymorphic sites, other than the insertion and deletion, 9 were found in the control region of the D-loop while 2 in the rRNA region, 3 each in ND4L and ND5 gene, 2 each in COX1 and COX2 gene, and one each in ND4, ND6, ATP6 and Cytb . Apart from complete mitogenomes, a complete D-loop region was also sequenced and aligned and a total of 18 polymorphic sites were observed in 1254 bp long D-loop (Table 4 and Supplementary Table 5). The phylogenetic analysis from the complete mitogenome sequence of GH and its crossbred was done using the AWH sequence as an outgroup. The phylogenetic analysis showed that different sequences of GH breeds were clustered in two different clades indicating two independent maternal lineages existing within GH. In one clade GH sequences were clustered with Rani crossbred while in other clade GH sequences were clustered with the Asha crossbred variety (Fig 4). The presence of GH in two different clades indicated that GH breeds indicated the different matrilineal components within GH breeds and this may be the reason for their grouping in different clades. This hypothesis stands good if we see the position of Asha and Rani crossbreds, both crossbreds have mitochondrial inheritance of GH breed, Rani was clustered in one clade while Asha is in another clade which indicated that Rani crossbred which was used in this study may have developed from GH which have similar matrilineal components while Asha was developed from GH which have different matrilineal components. The haplotype analysis using a complete mitogenome also shows the same result (Fig. 5b, Supplementary Table 4b). To further validate the results of double matrilineal components in GH with complete mitogenome samples, another phylogenetic analysis was conducted on the complete D-loop sequences of GH, Rani and Asha. We have also downloaded the complete D-loop sequences of Hampshire, Duroc and Landrace for phylogenetic analysis to see whether any influence of paternal mitochondrial components was present in Rani and Asha. Similar to the results of complete mitogenome analysis, GH and its crossbreds Rani and Asha were clustered in two distinct clades (Fig 6). It was clearly indicated that some of the GH, Rani and Asha were clustered together in one clade while the rest of GH, Rani and Asha were clustered in another clade. It may be due to the fact that the animals within the same clade have the same matrilineal components while animals between the two clades have different matrilineal components. The European breeds which were used to produce crossbreds have clustered separately in the third clade which shows that GH crossbreds have no effect on the matrilineal components of European breeds, signifying European breeds were used as sire components only and no mitochondrial inheritance was found in crossbreds from these European breeds. In order to further explore the genetic differentiation of the population, the haplotype analysis was performed and a median-joining network profile was generated (Fig. 5a). The haplotype network has a correlation with the results of the phylogenetic tree. There was a total of 125 polymorphic or variable sites, including 102 singleton sites and 23 parsimony informative sites. The number of haplotypes generated from complete D-loop sequences was 10 with haplotype diversity 0.720 ± 0.079. It was found that GH, Asha and Rani shared a single haplotype (Fig 5a and Supplementary Table 4a) which is obvious due to the same matrilineal components within them. It was also evident that GH and crossbreds had another separate haplotype which may be due to the different matrilineal components within them as evident from the phylogenetic analysis. The nucleotide diversity measured 0.01333, while Tajima's D was -2.10929. These values suggest non-neutral evolution, potentially indicating an abundance of rare alleles, suggestive of positive selection or a selective sweep (Eckshtain-Levi et al. 2018). The pairwise genetic distance between GH, GH crossbreds and European breeds and AWH was calculated using the maximum composite likelihood model (Tamura et al. 2004) based on complete D-loop sequences and presented in Table 5. The animals used for distance calculation were one from each haplogroup as depicted in supplementary table 4a. The analysis showed that the genetic distance between GH having different matrilineal components was more (0.7%) than the distance between GH and Asha (0.1-0.2 %) or Rani (0.2 %) crossbreds. As crossbreds Rani and Asha were developed from the GH matrilineal components, the genetic distance based on the D-loop should be negligible but a significant genetic distance was found between two GH and some of the Rani and Asha while with others it was negligible. It may be because Rani and Asha may have matrilineal components different from the GH for which distance was calculated. The genetic distance between GH and its crossbreds against European breeds revealed that the highest distance was between GH and Hampshire (1.9 %) followed by Landrace (1.7%) and Duroc (1.3%). The results of genetic distance corroborated with the phylogenetic tree. Furthermore, after placing all the GH and its crossbreds in one group, European pigs in 2 nd group and AWH in 3 rd group, the genetic distance between the GH and European group was found to be 1.24 % while between GH and AWH group was 6.24 % while the distance between European and AWH was 7.1 %. Our study corroborates with the earlier reports where the genetic distance between Indian wild boar and domestic pigs was 3.29 % (Das et al. 2024) and 3.5 % (Laxmivandana et al. 2022) and European wild boars and domestic breeds were 1.16 % (Kim et al. 2002). The study first time used the complete mtDNA genome of GH and its crossbred varieties namely Rani and Asha pigs. The mtDNA genome sequencing was performed for GH pigs from different locations in their breeding tract from West Bengal to Assam. The study discovered that within the GH breed, a wide genetic diversity is present and it may have two subspecies, with exact same morphological characters, which is not possible to identify phenotypically. Genetic measures like sequencing and phylogenetic analysis of mtDNA have given the tools to identify the matrilineal components of GH pig and identification of such distinct clusters within a breed made possible. The complete mtDNA genome as well as complete D-loop sequences revealed the double matrilineal components within GH breeds. Moreover, the crossbred commercial varieties namely Rani (♀GH x ♂Hampshire) and Asha (♀Rani x ♂Duroc) where GH has been used as the maternal lineages also showed similar differentiation. The Rani and Asha were also differentiated into two different clusters confirming the double matrilineal components within the GH population. The complete mitochondrial genome data of five GH pigs as well as complete D-loop sequences of 11 pigs of this breed clearly validate that GH pig has maintained two different mitochondrial inheritances. Analogous patterns of gene flow parallel to these two maternal inheritances can also be seen in Rani and Asha, crossbred animals developed using GH as the maternal lineage. In this connection, the phylogenetic analysis of the complete mitochondrial genome as well as complete D-loop sequences of Rani and Asha, validated the vertical inheritance of two mitochondrial genomes of GH subspecies among these breeds (Fig. 4 & Fig. 6). The GH pigs having two different matrilineage footprints might have encountered unusual natural/artificial selection pressure in the past, which led to the evolution of two distinct subspecies within the breed without affecting their phenotypic characters. The geographical isolation between Assam and West Bengal due to the Sankosh River, a tributary of the Brahmaputra River may be one of the reasons for the introduction of mitochondrial inheritance within GH from a related different ancestor. Therefore, from the study, it can be inferred that GH pigs have experienced a silent mitochondrial inheritance within the breed, which has changed their genetic framework but did not alter the phenotypic attributes of the animal. This is the first study which revealed the two different matrilineal components within the same breed. As GH is distributed in a wide range of West Bengal and Assam states of India and wide variation is present in this breed but phenotypically all are the same. The double matrilineal components within GH may be due to their origination from not a single ancestor but from closely related maternal ancestors. The eight pig breeds of Shandong province of China had lower divergence and shared the same haplotype because of the possibility that they stemmed from closely related maternal ancestors, if not from a common ancestor (Wang et al. 2010). The Dapulian Black and Laiwu Black breeds had independent maternal lineage but other indigenous pigs have extensive gene flow with other breeds (Wang et al. 2010). The neighbour-joining tree analysis identified two distinct clades among individual pigs, with a Chinese domestic breed showing a scattered distribution across multiple breeds (Niu et al. 2023). The commercial European breeds like Landrace, Hampshire and Duroc were clustered together in a separate clade independent of Indian pigs. Our findings align with earlier studies indicating a distinct phylogenetic separation between Indian pigs and European-American and Asian pig clades (Kumar Jadav et al. 2019). The separate matrilineage observed in Indian wild boars may stem from the differentiation of wild boar populations that originated from Island South East Asia (ISEA) and subsequently migrated to the Indian subcontinent before further dispersal to East Asia and eventually across Eurasia (Larson et al. 2005). Additionally, (Larson et al. 2010) reported that modern Indian domestic pigs have ancestral ties to local wild boar populations distinct from those found in Asia and Europe. Multiple domestication centres have been identified, including four for Chinese Native Pigs (Cai et al. 2019) and six for native pigs in East Asia (Larson et al. 2005). The GH pig is the most prolific pig breed in India and shows a wide range of variability in terms of reproductive and productive performance (Boro et al. 2021) which may be linked to the two different genetic subpopulations of GH having different maternal lineages. The absence of a structured breeding program for indigenous pig breeds like GH has contributed to a decline in their population (Subalini et al. 2010). Consequently, it becomes crucial to characterize the mitochondrial DNA (mtDNA) of GH and its crossbred counterparts to assess genetic diversity and maternal lineages within these pigs. This information is pivotal for designing appropriate breeding programs aimed at conserving this significant pig breed. In contrast to many species where domestication has been one of the major causes for drastic change in their morphological parameters, in this study it has been particularly uncovered that GH pig due to multiple expansion events though maintaining two different maternal lines in their genome has experienced no phenotypic changes in their morphology. The mitochondrial genomic data of GH pigs having two matrilineage, annotated in this study, could be fine-tuned as a powerful tool to trace the origin of pig domestication, conserve their indigenous germplasm and identify the purity as well as elucidate the lineage of other nondescript pigs. 4. Conclusion This study aimed to identify the molecular breed signatures of GH pigs through an integrative analysis of mtDNA expression and D-loop sequence data of GH pigs from different locations and their crossbred species (Rani and Asha). As evidenced by the mitochondrial genomic data GH pigs of this region have undergone multiple domestication events and have been carrying two different maternal lineages in their genome from the past, which is also apparent in their crossbred species. The study also underscores that GH pigs have undergone silent mitochondrial inheritance in their breed, without affecting their morphological attributes. The study identified two unique maternal legacies, which might be useful for their genotypic identification and thus work as an input for designing and implementing genetic strategies to conserve this important indigenous pig breed of India. Abbreviations ICAR Indian Council of Agricultural Research NRCP National Research Centre on Pig CPCSEA Committee for the Purpose of Control and Supervision of Experiments on Animals IAEC Intuitional Animal Ethic committee NFW Nuclease Free Water PCR Polymerase Chain Reaction NCBI National Center for Biotechnology Information H strands Heavy Strand L strands Light Strand D loop-Displacement loop Temp Temperature GH Ghungroo Declarations Competing interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Compliance with Ethical Standards All experiments conducted in this study adhered to the guidelines set forth by the animal ethics committee of the institute, with approval no. NRCP/CPCSEA/1658/IAEC-20/2018. Blood collection from the animals was performed with supreme care to minimize discomfort or harm. It is confirmed that authors complied with the ARRIVE guidelines. Funding This study was supported by Indian Council of Agricultural Research-National Research Centre on Pig Institutional Project Grant no. IXX13503 to Pranab Jyoti Das. Author Contribution Conceptualization: Pranab Jyoti Das, Satish Kumar; Methodology: Pranab Jyoti Das, Satish Kumar; Formal Analysis and investigation: Pranab Jyoti Das, Satish Kumar, Manasee Choudhury; Writing original Manuscript: Satish Kumar, Pranab Jyoti Das; Review and Editing: Pranab Jyoti Das, Satish Kumar, Seema Rani Pegu, Meera K, Rajib Deb, Sunil Kumar; Supervision and Resources: Pranab Jyoti Das, Santanu Banik, Vivek Kumar Gupta; All authors revised and approved the final version of the manuscript. Acknowledgements The authors are thankful to the Director, Indian Council of Agricultural Research-National Research Centre on Pig for providing infrastructural facilities to carry out this project. Data Availability The complete mitogenome sequences with gene annotation and complete D-loop sequences has been submitted to the NCBI GenBank. The details of accession numbers of all the sequence data utilized in this study can be found in the Supplementary Table 2. 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J Anim Sci Biotechnol 4:. https://doi.org/10.1186/2049-1891-4-9 Tables Table 1: Nucleotide base composition of the mitochondrial genome of Ghungroo and its crossbred pigs Breed/Crossbred Total Base A (n, %) G (n, %) T (n, %) C (n, %) % A+T % G+C MT501674, GH 1 16690 5792, 34.7 2221, 13.31 4309, 25.82 4368, 26.17 60.52 39.48 MZ703184, GH 2 16690 5792,34.7 2221, 13.31 4309, 25.82 4368, 26.17 60.52 39.48 OM617468, GH 3 16690 579034.69 2222, 13.31 4307, 25.81 4371, 26.19 60.5 39.5 OM634652, GH 4 16690 579234.7 2220, 13.3 4310, 25.82 4368, 26.17 60.53 39.47 MZ647672, GH 5 16690 579234.7 2221, 13.31 4309, 25.82 4368, 26.17 60.52 39.48 ON706057, Rani 16690 578934.69 2222, 13.31 4308, 25.81 4371, 26.19 60.5 39.5 ON715893.1, Asha 16690 579234.7 2219, 13.3 4310, 25.82 4369, 26.18 60.53 39.47 Table 2: A nnotation of the complete mtDNA genome of Indian Ghungroo and its crossbreds Gene Name Strand Start End Bases Space(+)/ Overlap(-) Start codon Stop codon Anti Codon GC skew AT Skew D-loop H 1 1254 1254 0 -0.26 0.13 tRNA-Phe H 1255 1324 70 0 GAA 12S rRNA H 1325 2284 960 0 -0.15 0.25 tRNA-Val H 2285 2352 68 0 TAC 16S rRNA H 2353 3922 1570 0 -0.11 0.25 tRNA-Leu H 3923 3997 75 0 TAA ND1 H 4000 4954 955 2 ATG T-- -0.42 0.14 tRNA-Ile H 4955 5023 69 0 GAT tRNA-Gln L 5021 5093 73 -3 TTG tRNA-Met H 5095 5164 70 1 CAT ND2 H 5165 6206 1042 0 ATA T-- -0.49 0.24 tRNA-Trp H 6207 6274 68 0 TCA tRNA-Ala L 6281 6348 68 6 TGC tRNA-Asn L 6350 6424 75 1 GTT tRNA-Cys L 6457 6522 66 32 GCA tRNA-Tyr L 6522 6587 66 -1 GTA COX1 H 6589 8133 1545 1 ATG TAA -0.2 0 tRNA-Ser L 8137 8207/8205 71 3 TGA tRNA-Asp H 8213 8280 68 5 GTC COX2 H 8281 8968 688 0 ATG T-- -0.31 0.12 tRNA-Lys H 8969 9035 67 0 TTT ATP8 H 9037 9240 204 1 ATG TAA -0.52 0.19 ATP6 H 9198 9878 681 -43 ATG TAA -0.46 0.11 COX3 H 9878 10661 784 -1 ATG T-- -0.31 0.04 tRNA-Gly H 10662 10730 69 0 TCC ND3 H 10731 11076 346 0 ATA T-- -0.46 0.15 tRNA-Arg H 11078 11146 69 1 TCG ND4L H 11147 11443 297 0 GTG TAA -0.33 0.01 ND4 H 11437 12814 1378 -7 ATG T-- -0.48 0.12 tRNA-His H 12815 12883 69 0 GTG tRNA-Ser-1 H 12884 12942 59 0 GCT tRNA-Leu H 12943 13012 70 0 TAG ND5 H 13013 14833 1821 0 ATA TAA -0.46 0.15 ND6 L 14817 15344 528 -17 ATG TAA 0.55 -0.36 tRNA-GLU L 15345 15413 69 0 TTC Cytb H 15418 16557 1140 4 ATG AGA -0.39 0.09 tRNA-Thr H 16558 16625 68 0 TGT tRNA-Pro L 16626/25 16689 64 0 TGG Table 3. Polymorphic sites of complete mitochondrial genome sequence of Ghungroo and its crossbreds. Nucleotide positions are numbered according to the reference sequence GenBank ON706057. Sequences identical to the first sequence (GH1) are denoted by dots (.). GH: Ghungroo Breed name/Sample 2 1 3 2 4 0 2 7 8 2 9 3 4 5 1 6 9 1 7 0 3 7 5 3 1 1 7 5 1 5 0 9 1 6 3 0 2 4 9 6 2 8 2 5 6 7 2 4 7 5 7 9 8 4 6 8 8 8 5 9 9 4 8 2 1 1 1 50 1 1 1 7 2 1 1 3 8 4 1 2 2 1 1 1 3 9 7 1 1 3 9 8 8 1 4 1 9 7 1 5 2 19 1 6 0 3 5 MT501674.1 GH 1 C T C A T G A G A - A G A G A T T T T G A T G G C A T MZ703184.1 GH 2 . . . . . . . . . - . . . . . . . . . . . . . . . . . MZ647672.1 GH 5 . . . . . . . . . - . . . . . . . . . . . . . . . . . OM634652.1 GH 4 T C T G C A G A G - . . . . . . . . . T . A A T T G C OM617468.1 GH 3 T C T G C A G A G - . . G A G C C C C T G A A T T G . ON706057.1 Rani T C T G C A G . G T - A G A G C C C C T G A A T T G . ON715893.1 Asha T C T G C A G A G - . . . . . . . . . T . . A T . . C D-loop rRNA rRNA COX1 COX2 ATP6 ND4L ND4 ND5 ND6 Cytb Table 4. Polymorphic sites of complete D-loop sequence of Ghungroo and its crossbred. Nucleotide positions are numbered according to the reference sequence GenBank OP185718. Sequences identical to the first sequence (Concensus) are denoted by dots (.). GH: Ghungroo Breed/Sample 93 213 240 278 293 451 483 511 691 703 714 743 753 761 772 773 802 1175 consensus C T C T G C G G A G C G A G T G T G MT501674 GH1 . C T C A T . . G A . . G . . . . A MZ703184 GH2 . C T C A T . . G A . . G . . . . A OM617468 GH3 . . . . . . . . . . . . . . . . . . OM634652 GH4 . . . . . . . . . . . . . . . . . . MZ647672 GH5 . C T C A T . . G A . . G . . . . A OP185718 GH6 . C T C A T . . G A . . G . . . . A OP185719 GH7 . . . . . . . . . . . . . A . . . . OP185720 GH8 . . . . . . . . . . . . . . . . . . OP185721 GH9 . C T C A T . . G A . . G . A . C A OP185722 GH10 . C T C A T . . G A . . G . . . . A OP185723 GH11 . . . . . . . . . . . . . . . A . . ON715893 Asha1 . . . . . . . . . . . . . . . . . . ON934748 Asha2 . C T C A T A . G A . . G . . . . A ON934749 Asha3 . C T C A T A . G A . . . . . . . . ON934750 Asha4 . . . . . . . . . . . . . . . . . . ON934751 Asha5 . . . . . . . . . . . . . . . . . . ON934752 Asha6 . . . . . . . . . . . A . . . . . . ON934753 Asha7 . . . . . . . . . . . . . . . . . . ON706057 Rani1 . . . . . . . . . . . . G . . . . . OP352470 Rani2 . . . . . . . . . . . . G . . . . . OP352471 Rani3 A C T C A T . . G A . . G . . A . A OP352472 Rani4 . C T C A T . C G A . . G . . . . . OP352473 Rani5 . . . . . . . . . . . . G . . A . . OP352474 Rani6 . . . . . . . . . . A . G . . . . . Table 5: Estimates of Pair Distances of Ghungroo and its crossbreds with European breeds, Percent identity in the upper triangle, and Percent Divergence in the lower triangle based on mtDNA D-loop sequences by the maximum composite likelihood method. IDENTITY D I V E R G E N C E 1 2 3 4 5 6 7 8 9 10 11 12 1 99.5 98.7 99.7 89.9 98.4 98.5 98.4 98.6 98.5 98.6 98.6 AM040628 Duroc 2 0.5 98.0 99.2 88.9 97.9 97.9 97.9 97.9 97.8 97.9 97.8 AY429460 Hampshire 3 1.3 1.9 98.2 90.9 99.3 99.4 99.3 99.9 99.8 99.8 99.8 MT501674 GH1 4 0.3 0.8 1.7 89.3 98.0 98.0 98.0 98.1 98.0 98.1 98.0 NC_000845 Landrace 5 9.4 11.2 9.1 10.4 90.7 90.7 90.7 90.7 90.5 90.7 90.6 NC_008830 African Warthog 6 1.7 2.2 0.7 2.2 9.2 99.9 100.0 99.2 99.4 99.1 99.3 OM617468 GH3 7 1.6 2.1 0.6 2.1 9.1 0.1 99.9 99.3 99.3 99.2 99.4 ON706057 Rani1 8 1.7 2.2 0.7 2.2 9.2 0.0 0.1 99.2 99.4 99.1 99.3 ON715893 Asha1 9 1.4 2.0 0.1 1.8 9.2 0.8 0.7 0.8 99.8 99.8 99.8 ON934748 Asha2 10 1.5 2.2 0.2 2.0 9.4 0.6 0.7 0.6 0.2 99.6 99.8 ON934749 Asha3 11 1.5 2.0 0.2 1.9 9.2 0.9 0.8 0.9 0.2 0.4 99.7 OP352471 Rani3 12 1.5 2.1 0.2 1.9 9.3 0.7 0.6 0.7 0.2 0.2 0.3 OP352472 Rani4 1 2 3 4 5 6 7 8 9 10 11 12 Additional Declarations No competing interests reported. Supplementary Files SupplementaryTable1.docx SupplementaryTable2.docx SupplementaryTable3.docx SupplementaryTable4.docx SupplementaryTable5.docx Cite Share Download PDF Status: Published Journal Publication published 17 Jan, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 05 Aug, 2024 Reviews received at journal 28 Jul, 2024 Reviews received at journal 25 Jul, 2024 Reviewers agreed at journal 17 Jul, 2024 Reviewers agreed at journal 15 Jul, 2024 Reviewers invited by journal 15 Jul, 2024 Editor assigned by journal 15 Jul, 2024 Editor invited by journal 13 Jun, 2024 Submission checks completed at journal 12 Jun, 2024 First submitted to journal 11 Jun, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Das","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFElEQVRIiWNgGAWjYDCCAxAqgbEBRLIxMPCDuQXEaWFsAGmRBOs1IEILEAN1AbUYgEXwaOG7ffbYh5877PKYZyQff/CgzM7e+PzqxA8PDBjk+cUOYNUieS4veWbvmeRixhlpiQ0J55ITt914u1kC6DDDmbMTsGoxOMNjzMDbxpzYOCPHsCGxjTnB7MbZDSAtCQa3cWth/NtWD9NSb2884+zmH4S0MPO2HYZpOcy4gb93G15bJM/wJTPLth0vZux5ljgj4dzxxBk3eLdZJBhI4PQL3xnew4xv26rzDNuTD3z8UVZtz99/dvPNHxU28vzS2LUwMPBAKMMJMAUSYIYEDuVIWuT5D0AF4IxRMApGwSgYBRAAAOnvaE/0rm49AAAAAElFTkSuQmCC","orcid":"","institution":"ICAR-National Research Centre on Pig","correspondingAuthor":true,"prefix":"","firstName":"Pranab","middleName":"Jyoti","lastName":"Das","suffix":""},{"id":318433682,"identity":"41090677-30c7-429b-99f4-4c1b70db8392","order_by":1,"name":"Satish Kumar","email":"","orcid":"","institution":"ICAR-National Research Centre on Pig","correspondingAuthor":false,"prefix":"","firstName":"Satish","middleName":"","lastName":"Kumar","suffix":""},{"id":318433683,"identity":"b6f21d42-bd06-4450-9a58-261ee216f4c1","order_by":2,"name":"Manasee Choudhury","email":"","orcid":"","institution":"ICAR-National Research Centre on Pig","correspondingAuthor":false,"prefix":"","firstName":"Manasee","middleName":"","lastName":"Choudhury","suffix":""},{"id":318433684,"identity":"25a38b50-3704-4c7c-acc5-87d302d9f9a7","order_by":3,"name":"Seema Rani Pegu","email":"","orcid":"","institution":"ICAR-National Research Centre on Pig","correspondingAuthor":false,"prefix":"","firstName":"Seema","middleName":"Rani","lastName":"Pegu","suffix":""},{"id":318433685,"identity":"cc77f947-885e-4592-9daf-d6ff90958df9","order_by":4,"name":"Meera K","email":"","orcid":"","institution":"ICAR-National Research Centre on Pig","correspondingAuthor":false,"prefix":"","firstName":"Meera","middleName":"","lastName":"K","suffix":""},{"id":318433686,"identity":"a4e4441e-119c-449a-b6a4-5171dcaa5ffb","order_by":5,"name":"Rajib Deb","email":"","orcid":"","institution":"ICAR-National Research Centre on Pig","correspondingAuthor":false,"prefix":"","firstName":"Rajib","middleName":"","lastName":"Deb","suffix":""},{"id":318433687,"identity":"9af97fe7-35b6-4faa-87f5-165d90ef274a","order_by":6,"name":"Sunil Kumar","email":"","orcid":"","institution":"ICAR-National Research Centre on Pig","correspondingAuthor":false,"prefix":"","firstName":"Sunil","middleName":"","lastName":"Kumar","suffix":""},{"id":318433688,"identity":"5ff9e54c-edd7-4d32-acb2-7d4cf9d1dae0","order_by":7,"name":"Santanu Banik","email":"","orcid":"","institution":"ICAR-National Research Centre on Pig","correspondingAuthor":false,"prefix":"","firstName":"Santanu","middleName":"","lastName":"Banik","suffix":""},{"id":318433689,"identity":"323cc808-1973-4216-91f7-4399777fc955","order_by":8,"name":"Vivek Kumar Gupta","email":"","orcid":"","institution":"ICAR-National Research Centre on Pig","correspondingAuthor":false,"prefix":"","firstName":"Vivek","middleName":"Kumar","lastName":"Gupta","suffix":""}],"badges":[],"createdAt":"2024-06-11 06:41:54","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4561770/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4561770/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-81205-4","type":"published","date":"2025-01-17T15:57:04+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":59220156,"identity":"a8de2145-6d50-4492-8492-39bcd526cf20","added_by":"auto","created_at":"2024-06-27 20:35:22","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":557966,"visible":true,"origin":"","legend":"\u003cp\u003eImages of Adult (a) Ghungroo Boar (b) Ghungroo Sow (c) Asha Crossbred (d) Rani crossbred pigs\u003c/p\u003e","description":"","filename":"F1.png","url":"https://assets-eu.researchsquare.com/files/rs-4561770/v1/5d03029d028f1293cbdd36db.png"},{"id":59219976,"identity":"839a6f5d-b3c0-4362-8438-398f920d82b5","added_by":"auto","created_at":"2024-06-27 20:27:21","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":324512,"visible":true,"origin":"","legend":"\u003cp\u003eCircular structure of Complete mitochondrial genome of a) Ghungroo b) Rani and c) Asha pigs\u003c/p\u003e","description":"","filename":"F2.png","url":"https://assets-eu.researchsquare.com/files/rs-4561770/v1/f4260fd5e06dbd48d15d287b.png"},{"id":59219978,"identity":"dbe07b3e-7c6c-4e80-aeb4-23ee348ac58f","added_by":"auto","created_at":"2024-06-27 20:27:22","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":240158,"visible":true,"origin":"","legend":"\u003cp\u003etRNA structure of all 22 tRNAs found in the complete mitogenome of GH and its crossbreds\u003c/p\u003e","description":"","filename":"F3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4561770/v1/d74a641480b716468dbfe2c8.jpg"},{"id":59220151,"identity":"a33b3cbb-6508-4336-ae27-bbc920a312de","added_by":"auto","created_at":"2024-06-27 20:35:21","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":28796,"visible":true,"origin":"","legend":"\u003cp\u003ePhylogenetic tree generated using complete mitogenome sequences of GH and its crossbreds using ML methods in Mega and Visualise using FigTree. African Warthog was used as an outgroup.\u003c/p\u003e","description":"","filename":"f4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4561770/v1/7c26f35f386369d638a2e03a.jpg"},{"id":59220303,"identity":"464fd1b0-a2da-4fa3-ad6b-c3b2ae888441","added_by":"auto","created_at":"2024-06-27 20:43:21","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":59307,"visible":true,"origin":"","legend":"\u003cp\u003eMedian Joining Haplotype Network created with PopArt showing the genetic relationships between all individuals using a) Complete \u003cem\u003eD-loop\u003c/em\u003esequences b) Complete mitogenome sequences. Colours represent different pig populations, mutational steps between haplotypes are shown as numbers across connection lines. Each haplogroup is represented by a circle, with the area of the circle proportional to the haplogroup's frequency.\u003c/p\u003e","description":"","filename":"f5.png","url":"https://assets-eu.researchsquare.com/files/rs-4561770/v1/ff6db1c2094c1e13b65b7acf.png"},{"id":59220304,"identity":"2149a1f4-e945-4cad-a103-1cab1e24db31","added_by":"auto","created_at":"2024-06-27 20:43:22","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":84390,"visible":true,"origin":"","legend":"\u003cp\u003ePhylogenetic tree generated using complete D Loop sequences of GH and its crossbreds using ML methods in Mega and Visualise using FigTree\u003cstrong\u003e \u003c/strong\u003ea) Radial representation b) rectangular representation\u003c/p\u003e","description":"","filename":"f6.png","url":"https://assets-eu.researchsquare.com/files/rs-4561770/v1/7a8bfc4dec442f179afb3429.png"},{"id":74284508,"identity":"92ab5288-5cb5-4b64-9680-c944f442da38","added_by":"auto","created_at":"2025-01-20 16:08:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3082389,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4561770/v1/43b1f923-af14-4625-9bd9-15febde10d15.pdf"},{"id":59220153,"identity":"119811e4-864d-4414-9d1d-139f7c95bdf8","added_by":"auto","created_at":"2024-06-27 20:35:22","extension":"docx","order_by":20,"title":"","display":"","copyAsset":false,"role":"supplement","size":23531,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4561770/v1/e516ecc1a3c03031d2cb69e0.docx"},{"id":59220155,"identity":"4816f01c-8568-4ed7-ac71-d97117f523f4","added_by":"auto","created_at":"2024-06-27 20:35:22","extension":"docx","order_by":21,"title":"","display":"","copyAsset":false,"role":"supplement","size":18471,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable2.docx","url":"https://assets-eu.researchsquare.com/files/rs-4561770/v1/f54f5644d0d5362e9b13c816.docx"},{"id":59219986,"identity":"5e19cf1e-c702-496e-aa28-cfdefa5b9cb5","added_by":"auto","created_at":"2024-06-27 20:27:22","extension":"docx","order_by":22,"title":"","display":"","copyAsset":false,"role":"supplement","size":23581,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable3.docx","url":"https://assets-eu.researchsquare.com/files/rs-4561770/v1/33f91c49bf0ca5c281f2fb4a.docx"},{"id":59219981,"identity":"8b01b307-5a80-4fc1-a077-a18bbf2fb9a0","added_by":"auto","created_at":"2024-06-27 20:27:22","extension":"docx","order_by":23,"title":"","display":"","copyAsset":false,"role":"supplement","size":14347,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable4.docx","url":"https://assets-eu.researchsquare.com/files/rs-4561770/v1/6e77a26e3947d68e4d7e8623.docx"},{"id":59219984,"identity":"c7a4d0a6-fa52-4ff8-b404-7773e0c2877c","added_by":"auto","created_at":"2024-06-27 20:27:22","extension":"docx","order_by":24,"title":"","display":"","copyAsset":false,"role":"supplement","size":17994,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable5.docx","url":"https://assets-eu.researchsquare.com/files/rs-4561770/v1/8e7655a4f19b3e10814e77cb.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Complete Mitochondrial Genome Sequence Analysis Revealed Double Matrilineal Components in Indian Ghungroo Pigs","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003ePigs (\u003cem\u003eSus scrofa)\u003c/em\u003e are one of the most ancient domesticated, socioeconomically valued and widely distributed livestock species across the world (Bharati et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The process of pig domestication occurred independently in various regions from its wild ancestors, with evidence suggesting occurrences in western Asia around 8500 BC (Ervynck et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Conolly et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), in China around 6500 BC (Cucchi et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), and in Southeast Asia and Europe approximately 9000 years ago (Giuffra et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Larson et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). India is recognised as one of the centres for the domestication of pigs and domestic pigs potentially originating from Indian wild boars separate from European and other Asiatic lineages (Das et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The genomic analyses revealed distinct mitochondrial haplotypes in Indian pig populations that were present in wild boar populations of India, but not in pigs from Europe and the East, indicating a localized event for domestication (Larson et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePig farming holds significant importance in the livelihood of rural tribal communities (Bharati et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). India possesses a rich diversity of pig genetic resources, with significant variations among populations. Fourteen indigenous pig breeds, documented in the country's breed database, contribute significantly to the socioeconomic upliftment of rural poor pig farmers. Among these breeds, the Ghungroo (GH) stands out as one of the most prolific pig breeds, primarily found in West Bengal and Assam which has the potential to be used in various breeding programmes. This is the first registered pig breed of India exhibits distinctive features such as a black coat, a characteristic bulldog-like face, a cylindrical body shape, and large, drooping ears [Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e(a-b)] (Banik et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Bharati et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The northeastern region of India, particularly Assam, emerges as a key hub for pig production, with GH and Doom being the predominant indigenous breeds traditionally raised in low-input backyard farming systems. These indigenous breeds possess inherent traits such as early sexual maturity, adaptability to harsh climate and management conditions and requirement of low input, disease resistance, strong maternal instincts, and desirable meat quality makes them the best enterprise for the weaker sections of society and the progressive farmers as well (Bharati et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, to enhance growth and reproductive performance, breeds like Hampshire and Duroc have been introduced and crossbred with GH, resulting in varieties like Rani and Asha. Notably, these crossbred varieties retain the maternal genetic heritage of GH (Bharati et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMammalian mitochondrial DNA genome (mtDNA) is a double-stranded molecule, composed of an H (heavy) strand and an L (light) strand and is approximately 16.5 kb in size that varies with the species \u003cem\u003eviz\u003c/em\u003e. cattle 16.34 Kb, goat 16.64 Kb; sheep 16.61 Kb; buffalo 16.36 Kb and in pig 16.69 Kb (Hu and Gao 2016; De et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Niu et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Siddiki et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Arbizu et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). MtDNA encodes crucial proteins of the electron transport chain. The location of genes varies in different species but most genes are located on the H-strand and only one or two genes are located on the L-strand. The mtDNA also has 22 tRNAs and 2 rRNAs that are involved in mtDNA transcript production and processing. Its maternal inheritance pattern and faster base substitution evolutionary rate allow for the investigation of evolutionary relationships within and between species (Avise \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Of the mtDNA genome, the control region \u003cem\u003ei.e. D-loop\u003c/em\u003e was used for investigating the genetic population structure of closely related animals in restricted areas (Ghivizzani et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Alves et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe complete mtDNA of GH and its crossbreds, along with the assessment of matrilineal components and genetic diversity, represents a vital step towards conservation and genetic improvement. The earlier reports mainly focused on small fragments of mtDNA, however, the present study aimed to characterize the complete mtDNA of Indian GH pigs and its crossbred varieties, tracing domestication patterns based on maternal lineages. Phylogenetic analyses will shed light on relationships among GH and its crossbreds and to what extent they were affected by the modern commercial breeds (Duroc, Yorkshire and Landrace) in maternal lineage, thus providing valuable insights into the multiple matrilinear components and evolutionary history of GH pigs.\u003c/p\u003e"},{"header":"2. Methods and Materials","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Ethics Statement\u003c/h2\u003e \u003cp\u003e All experiments conducted in this study adhered to the guidelines set forth by the animal ethics committee of the institute, with approval no. NRCP/CPCSEA/1658/IAEC-20/2018. Blood collection from the animals was performed with supreme care to minimize discomfort or harm.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Animals and Sampling\u003c/h2\u003e \u003cp\u003eThis study focused on the indigenous pig breed GH and its crossbreds found in the Bengal and Assam regions of India. A total of five GH pigs were used for the characterisation of the complete mtDNA genomic sequence and 11 GH pigs were used for the characterization of the complete \u003cem\u003eD-loop\u003c/em\u003e sequence of the mitochondrial genome. Additionally, crossbred varieties, namely Asha and Rani, with maternal components of GH, were included in the study. Seven animals from the Asha variety and six from the Rani variety were used for complete D-loop sequence analysis, while one animal each from Rani and Asha crossbreds was employed for complete mitogenome sequencing. Rani (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003ed) is a crossbred pig variety developed by crossing ♀ GH and ♂Hampshire pigs, with 50% blood of each breed (Bharati et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Asha (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003ec), on the other hand, is a crossbred pig variety obtained by crossing ♀ Rani with the terminal sire ♂ Duroc, thereby maintaining mitochondrial inheritance from GH pigs exclusively. Blood samples of 5 ml each were collected from the anterior vena cava using a sterile needle and BD vacutainer, and then stored at -20\u0026deg;C until DNA extraction.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. DNA extraction\u003c/h2\u003e \u003cp\u003eGenomic DNA was extracted from the blood samples using the standard phenol-chloroform method (Sambrook and Russel \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Kumar et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The quality of extracted genomic DNA was checked on agarose gel electrophoresis and the DNA samples without any smearing and having intact bands were used for further study. The purity and concentration of DNA were determined using a NanoDrop spectrophotometer, with samples having an A260/A280 ratio falling between 1.7 to 1.9 considered suitable for downstream applications. The DNA samples having good quality and purity were stored at -20\u0026deg;C until further use.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. PCR amplification of mitochondrial genome:\u003c/h2\u003e \u003cp\u003eThe primers sequences, amplification temperatures and product size along with the amplification conditions were similar to our earlier study (Das et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Briefly, 30 pairs of overlapping primers were used for the amplification of the complete mtDNA of GH and its crossbreds. The PCR was carried out in a 25 \u0026micro;l reaction mixture having 2.5 \u0026micro;l of 10X PCR buffer (with Mg\u003csup\u003e2+\u003c/sup\u003e), 0.5 \u0026micro;l of forward and reverse primer each (10 pm/\u0026micro;l), 0.5 \u0026micro;l of dNTPs (10 mM), 0.2 \u0026micro;l \u003cem\u003eTaq\u003c/em\u003e polymerase (1 unit), 1 \u0026micro;l DNA samples (50 ng/\u0026micro;l), and 19.8 \u0026micro;l of NFW. The PCR condition was conducted in a thermocycler (Applied Biosystems) involving an initial denaturation at 95\u0026deg;C for 7 min, followed by 30 cycles of denaturation at 95\u0026deg;C for 30 s, annealing at 58\u0026ndash;59\u0026deg;C for 30 s, and extension at 72\u0026deg;C for 30 s followed by a 5 min final extension at 72\u0026deg;C. The PCR products were then analyzed by 2% agarose gel electrophoresis. The PCR products showing intact specific bands and without any smearing was used for downstream works and processed for sequencing.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Sequencing of amplicon and structure analysis mitogenome\u003c/h2\u003e \u003cp\u003eThe purified PCR products were subjected to Sanger sequencing using 3500 Series Genetic Analyzers (Applied Biosystems). Sanger Sequencing not only sequences individual DNA fragments sequentially, but also guarantees full coverage of the reference genome. This is achieved through the utilization of overlapping fragments, effectively eliminating any gaps and ensuring a comprehensive 100% coverage of the targeted sequence (Hagemann \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The obtained sequences from Sanger sequencing were trimmed and edited using DNAstar and Megalign software. The annotation of complete mtDNA sequences was finalized using MITOS2 tools in the Galaxy webserver Platform (Al Arab et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Donath et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Afgan et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The circular structure of the complete mitogenome was constructed using Proksee Server (Grant et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The structure of the tRNA sequence identified in the complete mitogenome was predicted using the tRNAscan-SE 2.0 web server (Chan et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The Nucleotide frequencies, G\u0026thinsp;+\u0026thinsp;C content, and A\u0026thinsp;+\u0026thinsp;T content of mitogenome were determined using EditSeq of Laser gene (DNA STAR Inc.). The skewness of protein-coding genes in the mitogenomes was calculated using the formula: GC skew = (G\u0026thinsp;\u0026minus;\u0026thinsp;C) / (G\u0026thinsp;+\u0026thinsp;C) and AT skew = (A\u0026thinsp;\u0026minus;\u0026thinsp;T) / (A\u0026thinsp;+\u0026thinsp;T) (Nguyen et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Phylogenetic Analysis and Genetic Distance Analysis\u003c/h2\u003e \u003cp\u003ePhylogenetic analysis, using the complete mtDNA sequences of pigs generated in this study, was conducted, along with sequences from Indian wild boars and African warthog (AWH) downloaded from NCBI GenBank for comparison. The nucleotide sequences were aligned using the MUSCLE algorithm (Edgar \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) of MEGA 11 (Tamura et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The substitution model utilized for the alignment was thoroughly assessed, and the Hasegawa-Kishino-Yano (HKY) model, which yielded the lowest Bayesian information criterion (BIC) score, was selected as the most suitable for both alignment and phylogenetic analysis. Detailed information regarding each model, including their respective BIC, AICc values, Maximum Likelihood value (lnL), and the number of parameters, is provided in Supplementary Table\u0026nbsp;1. Subsequently, the aligned sequences were employed to construct a phylogenetic tree using the maximum likelihood (ML) method with 1000 bootstrap replications in MEGA 11, aimed at elucidating the matrilineal components in GH and its crossbred pig varieties.\u003c/p\u003e \u003cp\u003eApart from the complete mitogenome sequence, complete \u003cem\u003eD-loop\u003c/em\u003e sequences were also used for the phylogenetic and genetic distance analysis. For this purpose, the complete \u003cem\u003eD-loop\u003c/em\u003e sequences of European pig breeds, which contributed to the development of crossbred varieties of GH pigs, were retrieved from the NCBI GenBank. The list of sequences used for the phylogenetic analysis is provided in Supplementary Tables\u0026nbsp;2a \u0026amp; 2b. The nucleotide sequences were aligned using the MUSCLE package of MEGA 11 employing the HKY\u0026thinsp;+\u0026thinsp;G model as the best fit, which accounts for varying nucleotide frequencies and differing rates of transitions and transversions. Details of each substitution model are provided in Supplementary Table\u0026nbsp;3. The analysis encompassed 28 nucleotide sequences and a total of 1330 positions in the final dataset. These aligned sequences were used to construct a phylogenetic tree via the ML method with 1000 bootstrap replications. Furthermore, genetic distances among the sequences were calculated utilizing the maximum composite likelihood (MCL) model in MEGA 11 (Kumar et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Tamura et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe phylogenetic tree constructed in MEGA was visualized using the FigTree v.1.4.4 software (Rambaut \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The genetic distances among the sequences were calculated using the MCL model in MEGA 11 (Kumar et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Tamura et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The AWH was selected as an outgroup for phylogenetic tree analysis because it is well known to be different from Eurasian wild boars and this particular type of pig has been commonly employed in past phylogenetic investigations of pigs (Larson et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Lucchini et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Yu et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The haplotypes were identified from sequences of complete mitogenome and complete \u003cem\u003eD-loop\u003c/em\u003e sequences using DnaSP v.6 (Rozas et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The network of haplotype was generated by the minimum spanning network method (epsilon\u0026thinsp;=\u0026thinsp;0) using PopART v.1.7 (Leigh and Bryant \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The nucleotide diversity, no. of segregating sites, Tajima's D value and haplotype frequency were also analysed using DnaSP v.6 (Rozas et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results and Discussion","content":"\u003cp\u003eThis study was done to characterise the mitochondrial genome of GH and its crossbreds. The complete mitogenome and \u003cem\u003eD-Loop\u003c/em\u003e sequences were used for phylogenetic analysis and genetic distance estimation and to access the matrilineal components in these pigs.\u0026nbsp;The \u003cem\u003eD-loop\u003c/em\u003e region of the mitochondrial genome has high mutation rate and variable than any other region of the nuclear or mitochondrial genome (Nicholls and Minczuk 2014) and thus important region for the phylogenetic analysis and evolution of animal breeds (Chen et al. 2011).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Sequencing and submission of complete mtDNA Genome\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe entire mtDNA of 5\u0026nbsp;GH\u0026nbsp;and one each of the Rani and Asha crossbred varieties were amplified using 30 pairs of overlapping primers and sequenced by Sanger sequencing. All the fragments, including the \u003cem\u003eD-loop\u003c/em\u003e, 2 rRNA, 22 tRNA, 13 coding genes, and repeat regions, were aligned to obtain the complete mtDNA genome of each pig and the sequences were deposited into the NCBI GenBank database and assigned accession numbers \u003cem\u003eMT501674, MZ703184, OM617468, OM634652, MZ647672\u003c/em\u003e for\u0026nbsp;GH\u0026nbsp;breed; \u003cem\u003eON706057\u0026nbsp;\u003c/em\u003efor Rani; and \u003cem\u003eON715893\u0026nbsp;\u003c/em\u003efor Asha. Apart from the complete mtDNA genome, complete \u003cem\u003eD-loop\u003c/em\u003e sequences were amplified and sequenced using Sanger sequencing from\u0026nbsp;GH, Asha and Rani pigs. The sequences were trimmed and edited using DNAstar and Megalign software and these sequences were submitted to NCBI GenBank database and received the accession numbers for\u0026nbsp;GH\u0026nbsp;(\u003cem\u003eOP185718, OP185719, OP185720, OP185721, OP185722\u003c/em\u003e, and \u003cem\u003eOP185723\u003c/em\u003e); Asha (\u003cem\u003eON934748, ON934749, ON934750, ON934751, ON934752,\u003c/em\u003e and \u003cem\u003eON934753\u003c/em\u003e) and Rani (\u003cem\u003eOP352470, OP352471, OP352472, OP352473,\u003c/em\u003e and \u003cem\u003eOP352474\u003c/em\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;The base composition of the mtDNA genome\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe complete mtDNA of all the\u0026nbsp;GH\u0026nbsp;and its crossbred\u0026nbsp;\u003cem\u003eviz\u003c/em\u003e. Rani and Asha were found to be of size 16690 bp and for all the mitogenome,\u0026nbsp;\u003cem\u003eviz\u003c/em\u003e.\u0026nbsp;GH, Asha and Rani, the approximate base composition was 34.7% for Adenine (A), 25.8% for Thymine (T), 13.3% for Guanine (G) and 26.17% for Cytosine(C), while the G+C content was, 39.5% for all the breeds studied.\u0026nbsp;The composition of different nucleotide\u0026nbsp;base compositions of the mitochondrial genome is depicted in Table 1,\u0026nbsp;which shows that the majority of the nucleotides in the mitogenomes were AT-rich with 60.52 % of total bases. The nucleotide composition and organization of the mitogenome of GH and its crossbreds was similar to other pigs\u0026nbsp;\u003cem\u003eviz\u003c/em\u003e. Min pig (Niu et al. 2019). The size of the mitogenome in these pigs was comparable with the earlier reports of pigs in Asian as well as European pig breeds (Kim et al. 2002; Yu et al. 2013; De et al. 2019; Thom et al. 2021; Das et al. 2024).\u0026nbsp;The nucleotide composition in\u0026nbsp;mtDNA of I Pig was 34.66% for A, 26.24% for C, 13.35%, for G and 25.75% for T, the A+T content was 60.41% (Nguyen et al. 2017) while in Indian wild boar was 26.25, 13.40, 25.79 and 34.56 % for C, G, T and A, respectively and A+T content was 60.35 (Das et al. 2024).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Annotation of Complete Mitogenome:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe mitogenome has one non-coding control region\u0026nbsp;\u003cem\u003eviz\u003c/em\u003e. displacement loop (\u003cem\u003eD-loop\u003c/em\u003e), 22 transfer RNAs (tRNAs), 2 ribosomal RNAs (rRNAs), and 13 protein-coding genes which were similar to other pig mitogenomes (Bich Vo 2018). The typical circular structure of the mitogenome of\u0026nbsp;GH, Asha and Rani is depicted in Fig. 2(a-c) which depicts the H and L strands, position of all the genes, tRNAs, rRNAs and \u003cem\u003eD-loop\u003c/em\u003e along with GC content and Skewness of GC or AT. The annotation of the complete mitogenome of\u0026nbsp;the GH\u0026nbsp;breed is shown in Table 2. The \u003cem\u003eD-loop\u003c/em\u003e was 1254 bp long and located between \u003cem\u003etRNA-Pro\u003c/em\u003e and \u003cem\u003etRNA-Phe\u003c/em\u003e having repeat regions. The two rRNAs\u0026nbsp;\u003cem\u003eviz\u003c/em\u003e. 12S and 16S rRNAs were 960 and 1570 bp, respectively. The size of tRNAs was varied from 59 (\u003cem\u003etRNA-Ser-1)\u0026nbsp;\u003c/em\u003eto 75 bp (\u003cem\u003etRNA-Leu, tRNA-Asn)\u0026nbsp;\u003c/em\u003ein size. The mitogenome had a total of 6 overlaps among all the genes ranging from 1 to 43 bp long. Additionally, there were 11 non-coding spaces ranging from 1-32 bp in length. The protein-coding genes had a total sequence length of 11,409 bp ranging from 204 (\u003cem\u003eATP8\u003c/em\u003e) to 1821 (\u003cem\u003eND5\u003c/em\u003e), which is 68.36 % of the total mitogenome. The H-strand of the mitogenome consists of all the protein-coding genes, tRNAs, rRNAs and \u003cem\u003eD-loop\u003c/em\u003e, except the \u003cem\u003eND6\u003c/em\u003e gene and 8 tRNAs (\u003cem\u003etRNA-Ala, tRNA-Asn, tRNA-Cys, tRNA-Tyr, tRNA-Ser, tRNA-GLU, tRNA-Pro\u003c/em\u003e) which were encoded on L-strand (Fig. 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsistent with our findings, the length of 13 protein-coding genes ranged from 204 bp to 1,821 bp, and a total of 11,413 bp in I pig (Nguyen et al. 2017). Furthermore, studies in various pig populations (Wang et al. 2016; Nguyen et al. 2017; Bich Vo 2018), birds (Liu et al. 2021), and humans (Taanman 1999) have identified one protein-coding gene and eight tRNA genes encoded on the L-strand. In contrast, prior research on the mitochondrial DNA (mtDNA) of wild and domestic pigs revealed only one protein-coding gene (\u003cem\u003eND6\u003c/em\u003e) and seven tRNA genes (\u003cem\u003etRNAGln, tRNAAla, tRNAAsn, tRNACys, tRNAPro, tRNATyr, tRNAGlu\u003c/em\u003e) encoded on the L-strand (Jadav et al., 2019). However, another study indicated two protein-coding genes (\u003cem\u003eCOX3\u003c/em\u003e, \u003cem\u003eND6\u003c/em\u003e) and two tRNA genes (\u003cem\u003etRNAPro,\u003c/em\u003e\u003cem\u003etRNAGlu\u003c/em\u003e) on the L-strand (Singh et al. 2016). Notably, the complete mitochondrial genome of Daweizi and Ningxiang pigs revealed that all mitochondrial genes were encoded on the L-strand, except for three tRNA genes (\u003cem\u003etRNAIle, tRNAAsp\u003c/em\u003e, \u003cem\u003etRNALeu\u003c/em\u003e), which were encoded on the H-strand (Xu et al. 2015b, a). The arrangement and orientation of genes in the present study align with earlier reports on vertebrate and pig mitogenomes (Nguyen et al. 2017; Bich Vo 2018; Sarvani et al. 2018; De et al. 2019; Kumar Jadav et al. 2019).\u003c/p\u003e\n\u003cp\u003eEach protein-coding gene begins with the start codon ATG, except for \u003cem\u003eND4L\u003c/em\u003e, which starts with GTG, while \u003cem\u003eND3, ND2\u003c/em\u003e, and \u003cem\u003eND5\u003c/em\u003e start with ATA. The termination codons in six protein-coding genes (\u003cem\u003eND3, COX2, COX3, ND1, ND2 and ND4\u003c/em\u003e) were incomplete and were subsequently completed by the addition of 3\u0026rsquo; A residues to the mRNA during post-transcriptional polyadenylation. The annotation and codon sequences in our study are consistent with those found in the mitogenomes of other pig breeds from India and South-East Asia like I, Nicobari ((Yu et al. 2013; Nguyen et al. 2017; Bich Vo 2018; De et al. 2019; Kumar Jadav et al. 2019). In contrast to our findings, Singh et al. (2016) reported that all protein-coding genes had ATG as the start codon except for ND3, ND4, ND5, ND1, and ND2, which started with ATA. In the mitochondrial genome of Daweizi pig, ND2, ND3, and ND5 began with ATA, ND4L with GTG, and ND6 with ATT, while the remaining proteins initiated with ATG (Xu et al. 2015a). In Swedish pig breeds, the start codon for ND2 and ND4L was ATT and GTG, respectively (Ursing and Arnason 1998).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The nucleotide composition bias in mitogenome was estimated by GC and AT skews, and it showed that all genes on H stand coding for protein and rRNA were negatively GC-skewed and positively AT-skewed, which denoted cytosine and adenine biasedness. The most cytosine bias was observed in ATPase 8 (-0.52), while the least cytosine bias was observed in \u003cem\u003e16S rRNA\u003c/em\u003e (-0.11). In contrast, the 12S rRNA and \u003cem\u003e16S rRNA\u003c/em\u003e genes had the most adenine bias (0.25), while the \u003cem\u003eCOX1\u003c/em\u003e gene had no bias for AT content, which means that its adenine content is equal to the thymine content. The \u003cem\u003eND6\u003c/em\u003e gene was the only gene coded in the L strand that was positively skewed for GC content (0.55), whereas it was negatively skewed for AT content (-0.36) (Table 2). The AT content of the \u003cem\u003eD-loop\u003c/em\u003e was 57.81 %, whereas the GC skew and AT skew were found to be -0.26 and 0.14, respectively. The AT content of the \u003cem\u003eD-loop\u003c/em\u003e (57.81 %) was lesser than that of the I pig (60.09 %), Ningxiang pig (60.52 %) and Wild pig (60.65 %) (Nguyen et al. 2017; Kumar Jadav et al. 2019). The AT content, AT skew, and GC skew were used to determine the nucleotide composition behaviour of mitochondrial genomes as well as related to phylogenetics (Hassanin et al. 2005; Wei et al. 2010).\u003c/p\u003e\n\u003cp\u003eThe nucleotide composition bias within the mitogenome was assessed using GC and AT skews, revealing that all genes on the H strand encoding for proteins and rRNA exhibited negative GC-skew and positive AT-skew, indicating a bias towards cytosine and adenine. Among these, ATPase8 displayed the highest cytosine bias (-0.52), while 16S rRNA showed the least (-0.11). Conversely, 12S rRNA and 16S rRNA exhibited the highest adenine bias (0.25), while COX1 showed no bias in AT content, implying equal adenine and thymine content. Notably, the ND6 gene, the sole gene encoded on the L strand, demonstrated positive GC skew (0.55) and negative AT skew (-0.36) (Table 2). The AT content of the \u003cem\u003eD-loop\u003c/em\u003e was determined to be 57.81%, with corresponding GC and AT skews of -0.26 and 0.14, respectively. This AT content was lower than that observed in I pig (60.09%), Ningxiang pig (60.52%), and Wild pig (60.65%) (Nguyen et al. 2017; Kumar Jadav et al. 2019). Utilizing AT content, AT skew, and GC skew aids in understanding the nucleotide composition patterns within mitochondrial genomes and their relevance to phylogenetics (Hassanin et al. 2005; Wei et al. 2010).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Structure of tRNA\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe mitogenome of GH and its crossbred had 22 tRNA genes encoded for 22 tRNAs which consists of 2 tRNAs for Leucine and Serine amino acids while one tRNA for each of the other amino acids. All the tRNAs except eight were encoded on the H strand. The tRNA structure predicted by the tRNAscan-SE server revealed that all the tRNAs have typical cloverleaf structures except Ser-I which was devoid of D-arm. The structure and number of tRNAs in our study were similar to earlier reports in pigs (Nguyen et al. 2017). The structure of all the tRNAs is depicted in Fig. 3.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Phylogenetic analysis and Double matrilineal within Ghungroo pigs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe aligned complete mitochondrial genome sequence of\u0026nbsp;GH\u0026nbsp;and its crossbred pigs identified 27 polymorphic sites (Table 3), with one insertion and one deletion in the rRNA region of the Rani mitogenome. Out of these polymorphic sites, other than the insertion and deletion, 9 were found in the control region of\u0026nbsp;\u003cem\u003ethe D-loop\u003c/em\u003e while 2 in the rRNA region, 3 each in\u0026nbsp;\u003cem\u003eND4L\u003c/em\u003e and\u0026nbsp;\u003cem\u003eND5\u003c/em\u003e gene, 2 each in\u0026nbsp;\u003cem\u003eCOX1\u003c/em\u003e and\u0026nbsp;\u003cem\u003eCOX2\u003c/em\u003e gene, and one each in\u0026nbsp;\u003cem\u003eND4, ND6, ATP6\u003c/em\u003e and\u0026nbsp;\u003cem\u003eCytb\u003c/em\u003e. Apart from complete mitogenomes, a complete\u0026nbsp;\u003cem\u003eD-loop\u003c/em\u003e region was also sequenced and aligned and a total of 18 polymorphic sites were observed in 1254 bp long\u0026nbsp;\u003cem\u003eD-loop\u003c/em\u003e (Table 4 and Supplementary Table 5).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe phylogenetic analysis from the complete mitogenome sequence of GH and its crossbred was done using\u0026nbsp;the AWH\u0026nbsp;sequence as an outgroup. The phylogenetic analysis showed that different sequences of\u0026nbsp;GH\u0026nbsp;breeds were clustered in two different clades\u0026nbsp;indicating two independent maternal lineages existing within\u0026nbsp;GH.\u0026nbsp;In one clade\u0026nbsp;GH\u0026nbsp;sequences were clustered with Rani crossbred while in other clade\u0026nbsp;GH\u0026nbsp;sequences were clustered with the Asha crossbred variety (Fig 4). The presence of\u0026nbsp;GH\u0026nbsp;in two different clades indicated that\u0026nbsp;GH\u0026nbsp;breeds indicated the different matrilineal components within\u0026nbsp;GH\u0026nbsp;breeds and this may be the reason for their grouping in different clades. This hypothesis stands good if we see the position of Asha and Rani crossbreds, both crossbreds have mitochondrial inheritance of GH breed, Rani was clustered in one clade while Asha is in another clade which indicated that Rani crossbred which was used in this study may have developed from GH which have similar matrilineal components while Asha was developed from GH which have different matrilineal components. The haplotype analysis using a complete mitogenome also shows the same result (Fig. 5b, Supplementary Table 4b).\u003c/p\u003e\n\u003cp\u003eTo further validate the results of double matrilineal components in GH with complete mitogenome samples, another phylogenetic analysis was conducted on the complete \u003cem\u003eD-loop\u003c/em\u003e sequences of GH, Rani and Asha. We have also downloaded the complete \u003cem\u003eD-loop\u003c/em\u003e sequences of Hampshire, Duroc and Landrace for phylogenetic analysis to see whether any influence of paternal mitochondrial components was present in Rani and Asha. Similar to the results of complete mitogenome analysis, GH and its crossbreds Rani and Asha were clustered in two distinct clades (Fig 6). \u0026nbsp;It was clearly indicated that some of the GH, Rani and Asha were clustered together in one clade while the rest of GH, Rani and Asha were clustered in another clade. It may be due to the fact that the animals within the same clade have the same matrilineal components while animals between the two clades have different matrilineal components. The European breeds which were used to produce crossbreds have clustered separately in the third clade which shows that GH crossbreds have no effect on the matrilineal components of European breeds, signifying European breeds were used as sire components only and no mitochondrial inheritance was found in crossbreds from these European breeds.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn order to further explore the genetic differentiation of the population, the haplotype analysis was performed and a median-joining network profile was generated (Fig. 5a). The haplotype network has a correlation with the results of the phylogenetic tree. There was a total of 125 polymorphic or variable sites, including 102 singleton sites and 23 parsimony informative sites. The number of haplotypes generated from complete \u003cem\u003eD-loop\u003c/em\u003e sequences was 10 with haplotype diversity 0.720 \u0026plusmn; 0.079. It was found that GH, Asha and Rani shared a single haplotype (Fig 5a and Supplementary Table 4a) which is obvious due to the same matrilineal components within them. It was also evident that GH and crossbreds had another separate haplotype which may be due to the different matrilineal components within them as evident from the phylogenetic analysis. The nucleotide diversity measured 0.01333, while Tajima\u0026apos;s D was -2.10929. These values suggest non-neutral evolution, potentially indicating an abundance of rare alleles, suggestive of positive selection or a selective sweep (Eckshtain-Levi et al. 2018).\u003c/p\u003e\n\u003cp\u003eThe pairwise genetic distance between GH, GH crossbreds and European breeds and AWH was calculated using the maximum composite likelihood model (Tamura et al. 2004) based on complete \u003cem\u003eD-loop\u003c/em\u003e sequences and presented in Table 5.\u0026nbsp;The animals used for distance calculation were one from each haplogroup as depicted in\u0026nbsp;supplementary table 4a. The analysis showed that the genetic distance between GH having different matrilineal components was more (0.7%) than the distance between GH and Asha (0.1-0.2 %) or Rani (0.2 %) crossbreds. As crossbreds Rani and Asha were developed from the\u0026nbsp;GH\u0026nbsp;matrilineal components, the genetic distance based on \u003cem\u003ethe D-loop\u003c/em\u003e should be negligible but a significant genetic distance was found between two GH and some of the Rani and Asha while with others it was negligible. It may be because Rani and Asha may have matrilineal components different from the GH for which distance was calculated. The genetic distance between GH and its crossbreds against European breeds revealed that the highest distance was between GH and Hampshire (1.9 %) followed by Landrace (1.7%) and Duroc (1.3%). The results of genetic distance corroborated with the phylogenetic tree. Furthermore, after placing all the GH and its crossbreds in one group, European pigs in 2\u003csup\u003end\u003c/sup\u003e group and AWH in 3\u003csup\u003erd\u003c/sup\u003e group, the genetic distance between the GH and European group was found to be 1.24 % while between GH and AWH group was 6.24 % while the distance between European and AWH was 7.1 %. Our study corroborates with the earlier reports where the genetic distance between Indian wild boar and domestic pigs was 3.29 % (Das et al. 2024) and 3.5 % (Laxmivandana et al. 2022) and European wild boars and domestic breeds were 1.16 % (Kim et al. 2002).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe study first time used the\u0026nbsp;complete mtDNA genome of GH and its crossbred varieties namely Rani and Asha pigs. The mtDNA genome sequencing was performed for GH pigs from different locations in their breeding tract from West Bengal to Assam. The study discovered that within\u0026nbsp;the GH\u0026nbsp;breed, a wide genetic diversity is present and it may have two subspecies, with exact same morphological characters, which is not possible to identify phenotypically. Genetic measures like sequencing and phylogenetic analysis of mtDNA have given the tools to identify the matrilineal components of\u0026nbsp;GH\u0026nbsp;pig and identification of such distinct clusters within a breed made possible. The complete mtDNA genome as well as complete\u0026nbsp;\u003cem\u003eD-loop\u003c/em\u003e sequences revealed the double matrilineal components within\u0026nbsp;GH\u0026nbsp;breeds. Moreover, the crossbred commercial varieties namely Rani\u0026nbsp;(♀GH\u0026nbsp;x ♂Hampshire)\u0026nbsp;and Asha\u0026nbsp;(♀Rani x ♂Duroc)\u0026nbsp;where\u0026nbsp;GH\u0026nbsp;has been used as the maternal\u0026nbsp;lineages also showed similar differentiation. The Rani and Asha were also differentiated into two different clusters confirming the double matrilineal components within the\u0026nbsp;GH\u0026nbsp;population. \u0026nbsp;The complete mitochondrial genome data of five\u0026nbsp;GH\u0026nbsp;pigs as well as complete\u0026nbsp;\u003cem\u003eD-loop\u003c/em\u003e sequences of 11 pigs of this breed clearly validate that\u0026nbsp;GH\u0026nbsp;pig has maintained two different mitochondrial inheritances. Analogous patterns of gene flow parallel to these two maternal inheritances can also be seen in Rani and Asha, crossbred animals developed using\u0026nbsp;GH\u0026nbsp;as the maternal lineage. In this connection, the phylogenetic analysis of the complete mitochondrial genome as well as complete\u0026nbsp;\u003cem\u003eD-loop\u003c/em\u003e sequences of Rani and Asha, validated the vertical inheritance of two mitochondrial genomes of\u0026nbsp;GH\u0026nbsp;subspecies among these breeds (Fig. 4 \u0026amp; Fig. 6). The\u0026nbsp;GH\u0026nbsp;pigs having two different matrilineage footprints might have encountered unusual natural/artificial selection pressure in the past, which led to the evolution of two distinct subspecies within the breed without affecting their phenotypic characters. The geographical isolation between Assam and West Bengal due to the Sankosh River, a tributary of the Brahmaputra River may be one of the reasons for the introduction of mitochondrial inheritance within\u0026nbsp;GH\u0026nbsp;from a related different ancestor. Therefore, from the study, it can be inferred that\u0026nbsp;GH\u0026nbsp;pigs have experienced a silent mitochondrial inheritance within the breed, which has changed their genetic framework but did not alter the phenotypic attributes of the animal.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis is the first study which revealed the two different matrilineal components within the same breed. As GH is distributed in a wide range of West Bengal and Assam states of India and wide variation is present in this breed but phenotypically all are the same. The double matrilineal components within GH may be due to their origination from not a single ancestor but from closely related maternal ancestors. The eight pig breeds of Shandong province of China had lower divergence and shared the same haplotype because of\u0026nbsp;the possibility that they stemmed from closely related maternal ancestors, if not from a common ancestor (Wang et al. 2010).\u0026nbsp;The Dapulian Black and Laiwu Black breeds had independent maternal lineage but other indigenous pigs have extensive gene flow with other breeds (Wang et al. 2010).\u0026nbsp;The neighbour-joining tree analysis identified two distinct clades among individual pigs, with a Chinese domestic breed showing a scattered distribution across multiple breeds (Niu et al. 2023). The commercial European breeds like Landrace, Hampshire and Duroc were clustered together\u0026nbsp;in a separate clade independent of Indian pigs. Our findings align with earlier studies indicating a distinct phylogenetic separation between Indian pigs and European-American and Asian pig clades (Kumar Jadav et al. 2019). The separate matrilineage observed in Indian wild boars may stem from the differentiation of wild boar populations that originated from Island South East Asia (ISEA) and subsequently migrated to the Indian subcontinent before further dispersal to East Asia and eventually across Eurasia (Larson et al. 2005). Additionally, (Larson et al. 2010) reported that modern Indian domestic pigs have ancestral ties to local wild boar populations distinct from those found in Asia and Europe. Multiple domestication centres have been identified, including four for Chinese Native Pigs (Cai et al. 2019) and six for native pigs in East Asia (Larson et al. 2005).\u003c/p\u003e\n\u003cp\u003eThe GH pig is the most prolific pig breed in India and shows a wide range of variability in terms of reproductive and productive performance (Boro et al. 2021) which may be linked to the two different genetic subpopulations of GH having different maternal lineages. The absence of a structured breeding program for indigenous pig breeds like GH has contributed to a decline in their population (Subalini et al. 2010). Consequently, it becomes crucial to characterize the mitochondrial DNA (mtDNA) of GH and its crossbred counterparts to assess genetic diversity and maternal lineages within these pigs. This information is pivotal for designing appropriate breeding programs aimed at conserving this significant pig breed. In contrast to many species where domestication has been one of the major causes for drastic change in their morphological parameters, in this study it has been particularly uncovered that GH pig due to multiple expansion events though maintaining two different maternal lines in their genome has experienced no phenotypic changes in their morphology. The mitochondrial genomic data of GH pigs having two matrilineage, annotated in this study, could be fine-tuned as a powerful tool to trace the origin of pig domestication, conserve their indigenous germplasm and identify the purity as well as elucidate the lineage of other nondescript pigs.\u003c/p\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eThis study aimed to identify the molecular breed signatures of GH pigs through an integrative analysis of mtDNA expression and \u003cem\u003eD-loop\u003c/em\u003e sequence data of GH pigs from different locations and their crossbred species (Rani and Asha). As evidenced by the mitochondrial genomic data GH pigs of this region have undergone multiple domestication events and have been carrying two different maternal lineages in their genome from the past, which is also apparent in their crossbred species. The study also underscores that GH pigs have undergone silent mitochondrial inheritance in their breed, without affecting their morphological attributes. The study identified two unique maternal legacies, which might be useful for their genotypic identification and thus work as an input for designing and implementing genetic strategies to conserve this important indigenous pig breed of India.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eICAR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIndian Council of Agricultural Research\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNRCP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNational Research Centre on Pig\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCPCSEA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCommittee for the Purpose of Control and Supervision of Experiments on Animals\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIAEC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIntuitional Animal Ethic committee\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNFW\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNuclease Free Water\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePCR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePolymerase Chain Reaction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNCBI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNational Center for Biotechnology Information\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eH strands\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHeavy Strand\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eL strands\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLight Strand\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eloop-Displacement loop\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTemp\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTemperature\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGhungroo\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompliance with Ethical Standards\u003c/h2\u003e \u003cp\u003eAll experiments conducted in this study adhered to the guidelines set forth by the animal ethics committee of the institute, with approval no. NRCP/CPCSEA/1658/IAEC-20/2018. Blood collection from the animals was performed with supreme care to minimize discomfort or harm. It is confirmed that authors complied with the ARRIVE guidelines.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis study was supported by Indian Council of Agricultural Research-National Research Centre on Pig Institutional Project Grant no. IXX13503 to Pranab Jyoti Das.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization: Pranab Jyoti Das, Satish Kumar; Methodology: Pranab Jyoti Das, Satish Kumar; Formal Analysis and investigation: Pranab Jyoti Das, Satish Kumar, Manasee Choudhury; Writing original Manuscript: Satish Kumar, Pranab Jyoti Das; Review and Editing: Pranab Jyoti Das, Satish Kumar, Seema Rani Pegu, Meera K, Rajib Deb, Sunil Kumar; Supervision and Resources: Pranab Jyoti Das, Santanu Banik, Vivek Kumar Gupta; All authors revised and approved the final version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eThe authors are thankful to the Director, Indian Council of Agricultural Research-National Research Centre on Pig for providing infrastructural facilities to carry out this project.\u003c/span\u003e \u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe complete mitogenome sequences with gene annotation and complete D-loop sequences has been submitted to the NCBI GenBank. The details of accession numbers of all the sequence data utilized in this study can be found in the Supplementary Table 2.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAfgan E, Nekrutenko A, Gr\u0026uuml;ning BA, et al (2022) The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2022 update. Nucleic Acids Res 50:. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/nar/gkac247\u003c/span\u003e\u003cspan address=\"10.1093/nar/gkac247\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl Arab M, H\u0026ouml;ner zu Siederdissen C, Tout K, et al (2017) Accurate annotation of protein-coding genes in mitochondrial genomes. 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J Anim Sci Biotechnol 4:. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/2049-1891-4-9\u003c/span\u003e\u003cspan address=\"10.1186/2049-1891-4-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1: Nucleotide base composition of the mitochondrial genome of Ghungroo and its crossbred pigs\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"bottom\"\u003e\n \u003cp\u003eBreed/Crossbred\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.578947368421053%\" valign=\"top\"\u003e\n \u003cp\u003eTotal Base\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.578947368421053%\" valign=\"bottom\"\u003e\n \u003cp\u003eA (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"bottom\"\u003e\n \u003cp\u003eG (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"bottom\"\u003e\n \u003cp\u003eT (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"bottom\"\u003e\n \u003cp\u003eC (n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.526315789473685%\" valign=\"bottom\"\u003e\n \u003cp\u003e% A+T\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"bottom\"\u003e\n \u003cp\u003e% G+C\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"bottom\"\u003e\n \u003cp\u003eMT501674, GH 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.578947368421053%\" valign=\"top\"\u003e\n \u003cp\u003e16690\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.578947368421053%\" valign=\"top\"\u003e\n \u003cp\u003e5792, 34.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e2221, 13.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e4309, 25.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e4368, 26.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.526315789473685%\" valign=\"top\"\u003e\n \u003cp\u003e60.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\"\u003e\n \u003cp\u003e39.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"bottom\"\u003e\n \u003cp\u003eMZ703184, GH 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.578947368421053%\" valign=\"top\"\u003e\n \u003cp\u003e16690\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.578947368421053%\" valign=\"top\"\u003e\n \u003cp\u003e5792,34.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e2221, 13.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e4309, 25.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e4368, 26.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.526315789473685%\" valign=\"top\"\u003e\n \u003cp\u003e60.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\"\u003e\n \u003cp\u003e39.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"bottom\"\u003e\n \u003cp\u003eOM617468, GH 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.578947368421053%\" valign=\"top\"\u003e\n \u003cp\u003e16690\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.578947368421053%\" valign=\"top\"\u003e\n \u003cp\u003e579034.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e2222, 13.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e4307, 25.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e4371, 26.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.526315789473685%\" valign=\"top\"\u003e\n \u003cp\u003e60.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\"\u003e\n \u003cp\u003e39.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"bottom\"\u003e\n \u003cp\u003eOM634652, GH 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.578947368421053%\" valign=\"top\"\u003e\n \u003cp\u003e16690\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.578947368421053%\" valign=\"top\"\u003e\n \u003cp\u003e579234.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e2220, 13.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e4310, 25.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e4368, 26.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.526315789473685%\" valign=\"top\"\u003e\n \u003cp\u003e60.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\"\u003e\n \u003cp\u003e39.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"bottom\"\u003e\n \u003cp\u003eMZ647672, GH 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.578947368421053%\" valign=\"top\"\u003e\n \u003cp\u003e16690\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.578947368421053%\" valign=\"top\"\u003e\n \u003cp\u003e579234.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e2221, 13.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e4309, 25.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e4368, 26.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.526315789473685%\" valign=\"top\"\u003e\n \u003cp\u003e60.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\"\u003e\n \u003cp\u003e39.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"bottom\"\u003e\n \u003cp\u003eON706057, Rani\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.578947368421053%\" valign=\"top\"\u003e\n \u003cp\u003e16690\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.578947368421053%\" valign=\"top\"\u003e\n \u003cp\u003e578934.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e2222, 13.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e4308, 25.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e4371, 26.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.526315789473685%\" valign=\"top\"\u003e\n \u003cp\u003e60.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\"\u003e\n \u003cp\u003e39.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" valign=\"bottom\"\u003e\n \u003cp\u003eON715893.1, Asha\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.578947368421053%\" valign=\"top\"\u003e\n \u003cp\u003e16690\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.578947368421053%\" valign=\"top\"\u003e\n \u003cp\u003e579234.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e2219, 13.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e4310, 25.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e4369, 26.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.526315789473685%\" valign=\"top\"\u003e\n \u003cp\u003e60.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.421052631578947%\" valign=\"top\"\u003e\n \u003cp\u003e39.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eA\u003c/strong\u003e\u003cstrong\u003ennotation of the complete mtDNA genome of Indian Ghungroo and its crossbreds\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"669\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003eGene Name\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eStrand\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003eStart\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003eEnd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003eBases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003eSpace(+)/\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;Overlap(-)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\n \u003cp\u003eStart codon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\n \u003cp\u003eStop codon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\n \u003cp\u003eAnti Codon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\n \u003cp\u003eGC skew\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\n \u003cp\u003eAT Skew\u003c/p\u003e\u0026nbsp;\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003eD-loop\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e1254\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e1254\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\n \u003cp\u003e-0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003etRNA-Phe\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e1255\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e1324\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\n \u003cp\u003eGAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003e12S rRNA\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e1325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e2284\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e960\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\n \u003cp\u003e-0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003etRNA-Val\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e2285\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e2352\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\n \u003cp\u003eTAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003e16S rRNA\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e2353\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e3922\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e1570\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\n \u003cp\u003e-0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003etRNA-Leu\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e3923\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e3997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n 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width=\"9.687034277198212%\"\u003e\n \u003cp\u003e5021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e5093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e-3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\n \u003cp\u003eTTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003etRNA-Met\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n 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width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003etRNA-Trp\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e6207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e6274\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\n \u003cp\u003eTCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003etRNA-Ala\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e6281\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e6348\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\n \u003cp\u003eTGC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003etRNA-Asn\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e6350\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e6424\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\n 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width=\"8.79284649776453%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\n \u003cp\u003eGCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003etRNA-Tyr\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e6522\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e6587\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\n \u003cp\u003eGTA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003eCOX1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e6589\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e8133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e1545\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n 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width=\"6.855439642324888%\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\n \u003cp\u003eTGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003etRNA-Asp\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e8213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n 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width=\"9.985096870342772%\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e9037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e9240\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\n \u003cp\u003eATG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\n \u003cp\u003eTAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\n \u003cp\u003e-0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003eATP6\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e9198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e9878\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e681\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e-43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\n \u003cp\u003eATG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\n \u003cp\u003eTAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\n \u003cp\u003e-0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003eCOX3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e9878\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e10661\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e784\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\n \u003cp\u003eATG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\n \u003cp\u003eT--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\n \u003cp\u003e-0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003etRNA-Gly\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e10662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e10730\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\n \u003cp\u003eTCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003eND3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e10731\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e11076\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e346\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\n \u003cp\u003eATA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\n \u003cp\u003eT--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\n \u003cp\u003e-0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003etRNA-Arg\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e11078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e11146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\n \u003cp\u003eTCG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003eND4L\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e11147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e11443\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\n \u003cp\u003eGTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\n \u003cp\u003eTAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\n \u003cp\u003e-0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003eND4\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e11437\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e12814\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e1378\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e-7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\n \u003cp\u003eATG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\n \u003cp\u003eT--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\n \u003cp\u003e-0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003etRNA-His\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e12815\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e12883\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\n \u003cp\u003eGTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003etRNA-Ser-1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e12884\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e12942\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\n \u003cp\u003eGCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003etRNA-Leu\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e12943\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e13012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\n \u003cp\u003eTAG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003eND5\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e13013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e14833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e1821\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\n \u003cp\u003eATA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\n \u003cp\u003eTAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\n \u003cp\u003e-0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003eND6\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e14817\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e15344\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e528\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e-17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\n \u003cp\u003eATG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\n \u003cp\u003eTAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\n \u003cp\u003e-0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003etRNA-GLU\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e15345\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e15413\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\n \u003cp\u003eTTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003eCytb\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e15418\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e16557\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e1140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\n \u003cp\u003eATG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\n \u003cp\u003eAGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\n \u003cp\u003e-0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003etRNA-Thr\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e16558\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e16625\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\n \u003cp\u003eTGT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.412816691505217%\"\u003e\n \u003cp\u003e\u003cem\u003etRNA-Pro\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.985096870342772%\"\u003e\n \u003cp\u003eL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.687034277198212%\"\u003e\n \u003cp\u003e16626/25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.581222056631892%\"\u003e\n \u003cp\u003e16689\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.855439642324888%\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.922503725782414%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.79284649776453%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.451564828614009%\"\u003e\n \u003cp\u003eTGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.004470938897168%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.302533532041728%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e Polymorphic sites of complete mitochondrial genome sequence of Ghungroo and its crossbreds. Nucleotide positions are numbered according to the reference sequence GenBank ON706057. Sequences identical to the first sequence (GH1) are denoted by dots (.). GH: Ghungroo\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"630\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.19047619047619%\" valign=\"bottom\"\u003e\n \u003cp\u003eBreed name/Sample\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.761904761904762%\" valign=\"bottom\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.015873015873016%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.6984126984126986%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8095238095238093%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9682539682539684%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.19047619047619%\" valign=\"bottom\"\u003e\n \u003cp\u003eMT501674.1 GH 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.761904761904762%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.015873015873016%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.6984126984126986%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8095238095238093%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9682539682539684%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.19047619047619%\" valign=\"bottom\"\u003e\n \u003cp\u003eMZ703184.1 GH 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.761904761904762%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.015873015873016%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.6984126984126986%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8095238095238093%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9682539682539684%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.19047619047619%\" valign=\"bottom\"\u003e\n \u003cp\u003eMZ647672.1 GH 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.761904761904762%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.015873015873016%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.6984126984126986%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8095238095238093%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9682539682539684%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.19047619047619%\" valign=\"bottom\"\u003e\n \u003cp\u003eOM634652.1 GH 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.761904761904762%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.015873015873016%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.6984126984126986%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8095238095238093%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9682539682539684%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.19047619047619%\" valign=\"bottom\"\u003e\n \u003cp\u003eOM617468.1 GH 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.761904761904762%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.015873015873016%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.6984126984126986%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8095238095238093%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9682539682539684%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.19047619047619%\" valign=\"bottom\"\u003e\n \u003cp\u003eON706057.1 Rani\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.761904761904762%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.015873015873016%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.6984126984126986%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8095238095238093%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9682539682539684%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.19047619047619%\" valign=\"bottom\"\u003e\n \u003cp\u003eON715893.1 Asha\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.761904761904762%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.015873015873016%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.6984126984126986%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8095238095238093%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.857142857142857%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9682539682539684%\" valign=\"bottom\"\u003e\n \u003cp\u003e. \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.19047619047619%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.714285714285715%\" colspan=\"9\" valign=\"bottom\"\u003e\n \u003cp\u003eD-loop\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.714285714285714%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003erRNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.714285714285714%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003erRNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.714285714285714%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eCOX1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.714285714285714%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eCOX2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.761904761904762%\" valign=\"bottom\"\u003e\n \u003cp\u003eATP6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.571428571428571%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003eND4L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8095238095238093%\" valign=\"bottom\"\u003e\n \u003cp\u003eND4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.571428571428571%\" colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003eND5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9682539682539684%\" valign=\"bottom\"\u003e\n \u003cp\u003eND6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\" valign=\"bottom\"\u003e\n \u003cp\u003eCytb\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u0026nbsp;\u003c/strong\u003ePolymorphic sites of complete D-loop sequence of Ghungroo and its crossbred. Nucleotide positions are numbered according to the reference sequence GenBank OP185718. Sequences identical to the first sequence (Concensus) are denoted by dots (.). GH: Ghungroo\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"96%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.157894736842106%\" valign=\"bottom\"\u003e\n \u003cp\u003eBreed/Sample\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e240\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e293\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e451\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e483\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e511\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e691\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e703\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e743\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e753\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\" valign=\"bottom\"\u003e\n \u003cp\u003e761\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e772\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e773\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e802\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e1175\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.157894736842106%\" valign=\"bottom\"\u003e\n \u003cp\u003econsensus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.157894736842106%\" valign=\"bottom\"\u003e\n \u003cp\u003eMT501674 GH1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.157894736842106%\" valign=\"bottom\"\u003e\n \u003cp\u003eMZ703184 GH2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.157894736842106%\" valign=\"bottom\"\u003e\n \u003cp\u003eOM617468 GH3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.157894736842106%\" valign=\"bottom\"\u003e\n \u003cp\u003eOM634652 GH4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.157894736842106%\" valign=\"bottom\"\u003e\n \u003cp\u003eMZ647672 GH5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.157894736842106%\" valign=\"bottom\"\u003e\n \u003cp\u003eOP185718 GH6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.157894736842106%\" valign=\"bottom\"\u003e\n \u003cp\u003eOP185719 GH7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.157894736842106%\" valign=\"bottom\"\u003e\n \u003cp\u003eOP185720 GH8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.157894736842106%\" valign=\"bottom\"\u003e\n \u003cp\u003eOP185721 GH9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.157894736842106%\" valign=\"bottom\"\u003e\n \u003cp\u003eOP185722 GH10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.157894736842106%\" valign=\"bottom\"\u003e\n \u003cp\u003eOP185723 GH11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.157894736842106%\" valign=\"bottom\"\u003e\n \u003cp\u003eON715893 Asha1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.157894736842106%\" valign=\"bottom\"\u003e\n \u003cp\u003eON934748 Asha2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.157894736842106%\" valign=\"bottom\"\u003e\n \u003cp\u003eON934749 Asha3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.157894736842106%\" valign=\"bottom\"\u003e\n \u003cp\u003eON934750 Asha4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.157894736842106%\" valign=\"bottom\"\u003e\n \u003cp\u003eON934751 Asha5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.157894736842106%\" valign=\"bottom\"\u003e\n \u003cp\u003eON934752 Asha6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.157894736842106%\" valign=\"bottom\"\u003e\n \u003cp\u003eON934753 Asha7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.157894736842106%\" valign=\"bottom\"\u003e\n \u003cp\u003eON706057 Rani1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.157894736842106%\" valign=\"bottom\"\u003e\n \u003cp\u003eOP352470 Rani2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.157894736842106%\" valign=\"bottom\"\u003e\n \u003cp\u003eOP352471 Rani3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.157894736842106%\" valign=\"bottom\"\u003e\n \u003cp\u003eOP352472 Rani4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.157894736842106%\" valign=\"bottom\"\u003e\n \u003cp\u003eOP352473 Rani5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.157894736842106%\" valign=\"bottom\"\u003e\n \u003cp\u003eOP352474 Rani6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1578947368421053%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.2631578947368425%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.2105263157894735%\" valign=\"bottom\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5: \u0026nbsp;\u003c/strong\u003eEstimates of Pair Distances of Ghungroo and its crossbreds with European breeds, Percent identity in the upper triangle, and Percent Divergence in the lower triangle based on mtDNA D-loop sequences by the maximum composite likelihood method.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"643\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIDENTITY\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"13\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eD\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eI\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eV\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eE\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eR\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eG\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eE\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eE\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e99.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e98.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e99.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e89.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e98.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e98.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e98.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e98.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e98.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e98.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e98.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAM040628 Duroc\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e98.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e99.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e88.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e97.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e97.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e97.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e97.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e97.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e97.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e97.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAY429460 Hampshire\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e98.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e90.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e99.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e99.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e99.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e99.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e99.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e99.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e99.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMT501674 GH1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e89.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e98.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e98.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e98.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e98.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e98.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e98.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e98.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNC_000845 Landrace\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e90.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e90.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e90.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e90.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e90.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e90.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e90.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNC_008830 African Warthog\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e99.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e99.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e99.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e99.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e99.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOM617468 GH3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e99.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e99.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e99.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e99.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e99.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eON706057 Rani1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n 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\u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Indian Ghungroo pig, Mitochondrial genome, D-loop, Double Matrilineal, Phylogeny","lastPublishedDoi":"10.21203/rs.3.rs-4561770/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4561770/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis research aimed to characterize the mitochondrial genome of the Ghungroo (GH) pig, a notable breed in India, along with its crossbred varieties, to elucidate their matrilineal components, evolutionary history, and implications for conservation. Seven pigs (5 GH, 2 crossbred, namely Rani and Asha) were sequenced for complete mitochondrial genome, while 24 pigs (11 GH, 6 Rani, and 7 Asha) were sequenced for the complete \u003cem\u003eD-loop\u003c/em\u003e of the mitochondrial genome. The genome size of these pigs was determined to be 16690 bp. Analysis of the mitochondrial sequences and phylogenetics uncovered two distinct matrilineal components within the GH population, a phenomenon also observed in its crossbred counterparts, Rani and Asha. Phylogenetic analysis demonstrated a clear clustering of GH sequences into two clades, indicating the presence of two independent maternal lineages. Haplotype analysis revealed 10 different haplotypes, with some sequences shared among GH, Rani, and Asha, while others differed due to varying matrilineal origins. Furthermore, examination of tRNA genes and nucleotide composition offered insights into genetic diversity within these pigs. The findings suggest that geographical isolation and historical events likely contributed to the emergence of distinct maternal lineages within the GH breed. This study underscores the significance of mitochondrial DNA analysis in uncovering hidden genetic diversity within seemingly uniform populations. The molecular insights gained into the genetic makeup of GH pigs could aid in designing effective breeding programs for conservation efforts and highlight its significance in understanding the broader context of pig domestication in India.\u003c/p\u003e","manuscriptTitle":"Complete Mitochondrial Genome Sequence Analysis Revealed Double Matrilineal Components in Indian Ghungroo Pigs","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-27 20:27:16","doi":"10.21203/rs.3.rs-4561770/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-05T08:26:48+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-28T13:24:23+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-25T08:49:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"225562913795623112168202102139783706595","date":"2024-07-17T09:58:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"303422943802159979368037113772117984196","date":"2024-07-16T02:41:49+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-15T09:49:34+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-15T09:48:46+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-06-13T10:03:21+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-12T13:38:19+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-06-11T06:40:36+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3116256e-94aa-4c0e-a137-675dd60d81e3","owner":[],"postedDate":"June 27th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":33670396,"name":"Biological sciences/Genetics"},{"id":33670397,"name":"Biological sciences/Molecular biology"}],"tags":[],"updatedAt":"2025-01-20T15:59:39+00:00","versionOfRecord":{"articleIdentity":"rs-4561770","link":"https://doi.org/10.1038/s41598-024-81205-4","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-01-17 15:57:04","publishedOnDateReadable":"January 17th, 2025"},"versionCreatedAt":"2024-06-27 20:27:16","video":"","vorDoi":"10.1038/s41598-024-81205-4","vorDoiUrl":"https://doi.org/10.1038/s41598-024-81205-4","workflowStages":[]},"version":"v1","identity":"rs-4561770","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4561770","identity":"rs-4561770","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}