Genetic diversity among three camel populations reared in Egypt using mitochondrial COX-3 gene

Genetic diversity among three camel populations reared in Egypt using mitochondrial COX-3 gene | 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 Research Article Genetic diversity among three camel populations reared in Egypt using mitochondrial COX-3 gene Sekena H Abdel-Aziem, Dalia M Mabrouk, Heba A Abd El-Kader, Sally S Alam, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4032390/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Maintaining genetic diversity among native Egyptian breeds is important towards genetic resource conservation. Examining the mitochondrial genome in different or within breeds can be helpful in determining the genetic variety of populations. This study examined the mitochondrial COX-3 gene of Egyptian Camelus dromedaries using bioinformatics and phylogenetic analysis, revealing two distinct haplotypes based on single nucleotide polymorphisms at positions 280 and 325. These two haplotypes' amplified PCR products were uploaded to GenBank/NCBI with accession numbers OP994029 and OP994030 with protein id = WHO17331.1" and WHO17330.1, respectively. Comparison of nucleotide and amino acid sequences of the Egyptian camel populations' three-dimensional COX-3 structure showed how closely related these two haplotypes are genetically. Haplotype 1 was more predominant and found in Baldi and Sudani populations whereas haplotype 2 was more abundant in Maghrebi population. The two polymorphic sites have diversity and theta (per site): Theta (W: 0.00208); high variety of haplotypes (Hd: 0.667). These two haplotypes are the most genetically distant from camels in the Camelidae family, according to phylogenetic study. Based on the nucleotide sequences A + T and C + G have frequencies between 51.15% and 48.85%, respectively. The two non-synonymous SNPs caused the P94S amino acid substitution in the coiled region while I109V substitution located in the strand, which was neutral. Analysis of amino acid substitutions via protein prediction showed that the two amino acids were semi-conserved in which the resultant amino acid has different properties from the original amino acid and can affect the protein structure. The protein stability diminished according to the I-Mutant and MUpro tools. I109V nSNP and increased for P94S nSNP. This finding suggested that COX-3 gene variability in camels is important to preserve this genetic resource and creating future breeding programmes, conservation strategies that will increase camel production. Camelus dromedarius COX-3 gene Mitochondrial DNA nonsynonymous SNP homology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Introduction Based on archaeological evidence, the one-humped camel (Camelus dromedarius) originated in the southeast of the Arabian Peninsula (Almathen et al., 2021). As a result of its remarkable tolerance to harsh desert circumstances, this type of livestock is unique (Al Askar et al., 2020 ). Ancient trade routes have dispersed dromedary camels throughout semi-arid and desert areas of Africa, the Arabian Peninsula, and southwest Asia (Bahbahani & Almathen, 2022 ). Camels in Egypt are belonged to Camelus dromedaries’ family, which is often referred to as the Arabian camel (Sallam, 2020 ). The total number of camels recorded in Egypt was 119,885 (Ashour & Abdel-Rahman, 2022 ). There are five breeds of camel reared in Egypt which are used for many purposes. The Maghrabi breed is reared for meat and milk production, Falahi or Baladi for transportation and agricultural operations, Sudani and Somali breeds for riding and racing purposes and the Mowallad breed which is a hybrid between Falahi and Maghrabi (Abdel-Aziem et al., 2022 ). The evaluation of genetic diversity is essential for managing genetic resources for long-term preservation and application. Animal biodiversity management relies heavily on the characterization of genetic variety both within and between breeds and populations. This aspect has very important role especially in countries with negative population growth as in Egypt (Faye, 2020 ). The mitochondrial genome (mtDNA) is an uniparentally inherited marker system, has the characteristics of a high evolution rate with no recombination and it has shown to be highly informative for determining the degree of their genetic variability, which is essential in defining conservation priorities for regional breed's specific programs (Di Lorenzo et al., 2016 ). The length of the dromedary camel mitochondrion is about 16.6 kb. It consists of 22 tRNA gene, two rRNAs genes, 13 protein-coding genes and non-coding control region. The 13 protein-coding genes are cytochrome c oxidases (COX) 1, 2 and 3; NADH dehydrogenases (ND) 1, 2, 3, 4, 4L, 5 and 6; ATP synthases (ATP) 6A and 8; and cytochrome b (CytB) (Alaqeely et al.,2021). Little is known about COX-3 gene in camel, although it is an important component of the respiratory chain and is conserved among species. The camel genome's SNPs are essential for the development of beneficial features (Ali et al., 2019 ). Before doing additional laboratory research, computational methods can be used to first filter potentially harmful SNPs that may alter susceptibility to diseases (Venkata et al., 2022). Geneticists and breeders may find it helpful to combine the DNA-sequencing-based approach with silico tools (PROVEAN, I-Mutant, SIFT, MUpro, and Polyphen-2) to find unknown SNPs that may have an impact on the structure and biological function of a protein (Ali et al., 2022 ). Therefore, in the current study, mtDNA COX-3 gene was analyzed to better understand the genetic diversity among native Egyptian camel breeds and to explore the effect of nsSNPs on COX-3 protein structure and function. Materials and methods Ethics approval and consent to participate: This study has been authorised by the Ethics of Medical Research Committee, National Research Centre, Al Buhouth St. Dokki – Cairo, Egypt, number 12440723. The Collection of Samples and extracting DNA : Blood samples from Sudani and Falahi (Baladi) camels were collected from the camel market in Berkash, Giza, Egypt, whilst samples from Maghrabi camels were provided by King Mariout Research Station.Phenol/chloroform procedure previously described by Wajid et al. (2014) was used to isolate genomic DNA from blood samples. Thermo Scientific, USA's NanoDrop spectrophotometer was used to quantify the extracted DNA, which was then kept at -20°C until needed. For the purpose of amplifying the COX-3 mitochondrial area, a 50 μl PCR reaction mixture including 10X buffer (containing 15 mM MgCl2), 10 mM dNTPs mix, 10 pmol of universal primers (Cui et al., 2007), and 5 U Taq DNA Polymerase was utilised. The used primer: F: ccagtgatgacgggacgttg R: TAGATGTGAAGTGGAATTTC PCR amplification and sequencing: 35 cycles of denaturation at 95°C for 30s, annealing at 55°C for 30s, extension at 72°C for 45s, and final extension at 72°C for 7 minutes were used to carry out the amplification. The first denaturation was place at 95°C for 5 minutes. Using a DNA purification kit (ExoSap-IT, USB Corporation) and following the manufacturer's instructions, the amplified products were filtered to remove any remaining primers and dNTPs. The sequencing of the COX-3 amplified products was done in Macrogen Incorporation by using an automated DNA sequencer ABI 3730XL (Seoul, South Korea). Sequence data analysis: The MEGA11.0 program's Clustal W method was used to align the COX-3 sequences from 90 examined camels with the GenBank-available Camelus sequence (Tamura et al., 2013). Furthermore, MEGA11.0 was used to determine sequence composition and genetic differentiation. Moreover, ExPASy (http://web.expasy.org/translate) was used to generate an analysis of the translated protein of the COX-3 gene sequences of the camels that were examined. Estimation of genetic diversity: Polymorphic sites (S), number of haplotypes (H), haplotype diversity (Hd), nucleotide diversity (π), average number of nucleotide differences (K), and standard deviations (SD) were used to calculate the degree of genetic diversity using DNASP v5.10. These parameters were identified within and among all populations (Librado & Rozas, 2009). Neutrality tests The neutrality tests, including Fu’s F s (Fu, 1997) and Tajima’s D (Tajima, 1989). Tajima's D is negative, the population is growing (due to bottlenecks or selective sweeps), there is an excess of low-frequency polymorphisms compared to expectations, and purifying selection is taking place (Al-Jumaili et al., 2020). Positive Tajima's D denotes low frequencies of high frequency polymorphisms, which could account for declining population size or counteract selection. Similarly, Tajima's D test is less potent than Fu's Fs test (Ramos-Onsins & Rozas, 2002). Phylogenetic Analysis Using MEGA X (version 2020), the neighbor-joining (NJ) tree for tested camel breed sequences and the phylogenetic tree connecting our camels to other camel breeds worldwide were built. Applications (Kumar et al., 2016). Our camel's COX-3 sequences were compared to Camelus dromedaries' reference sequences:(Arabian camel), camelus bactrianus (Mongolian camel MH109977.1 ), Lama glama (South American camelid NC_012102.1 ), and other species as Bubalus bubalis (water buffaloMT186736.1) and Bos taurus (cattle MN714218.1) , that were downloaded from the NCBI database. 3D Structure Prediction of COX 3 gene fragment The 3D tertiary structure of COX-3 mDNA from camels reared in Egypt was predicted by software known as the Protein Homology Analogy Recognition Engine (Phyre2). Identification Tools for SNP The bioinformatics programmes NovelSNPer, BLASTn, BLASTx, and Bio-edit v 7.2.6 were used to analyse the sequencing data. Prediction of the deleterious nsSNPs Four different in silico SNP prediction algorithms (PREDICT SNP , Sorting intolerance from tolerance (SIFT), polymorphism phenotyping v2 (PolyPhen-2), and protein variation effect analyzer (PROVEAN) were used to predict the deleterious effects of nsSNPs. Six prediction programmes were utilised in the development of the PredictSNP tool, a consensus SNP classifier (MAPP, PhD-SNP, PolyPhen-1, PolyPhen-2, SIFT and SNAP) to give a more reliable and alternate prediction. If the score falls between -1 and 0, the mutations are considered neutral, and if the score falls between 0 and 1, they are considered detrimental. SIFT determine whether the function of proteins is affected in any way via an amino acid substitution. The SIFT method is based on sequence homology, and nsSNPs may be deleterious if the score is equivalent to or lower than 0.05. The PolyPhen-2 server is an evolutionary conservation system for sequences and structures that is focused on categorising the deleterious effects of amino acid change. It has a value between 0 (tolerable) and 1 (deleterious). The PROVEAN service finds nonsynonymous variants and returns a pairwise sequence alignment (PSA) score. An amino acid variant is considered to have a negative effect on protein function if its PROVEAN score is less than or equal to 2.5, while a variant with a value greater than or equal to 2.5 is considered to have a neutral effect. Protein stability prediction: The MUpro and I-Mutant tools were utilised to predict modifications in the protein stability due to single-site mutations. MUpro predicts only whether or not the change will cause destabilization, without providing an actual ddG value while I-Mutant provides the ddG value(kcal/mol). I-Mutant 3.0 produces a DDG value based on the tertiary structure or protein sequence, which is predicted to be as follows: If ddG is less than or equal to 0.5 kcal/mol, it is mostly unstable; if ddG is greater than or equal to 0.5 kcal/mol, it is neutral. Accession numbers for nucleotide sequences: The sequences produced from this investigation were deposited in GenBank with these numbers. OP994029 and OP994030 with protein id= WHO17331.1 and WHO17330.1. Table 1: Prediction tools used in the analysis. Prediction tool URL Type Reference I-Mutant 2.0 ( https://folding.biofold.org/cgi-bin/i-mutant2.0 ) machine learning method (SVM) ( Capriotti et al.,2005 ) MutPred http://mutpred.mutdb.org/ evolutionary conservation and structure-based ( Klein & Power, 2007 ) PhD-SNP http://snps.biofold.org/phd-snp/phd-snp.html machine learning method (SVM) ( Doss et al., 2008) PolyPhen-2 http://genetics.bwh.harvard.edu/pph2/index.shtml evolutionary conservation and structure-based ( Spencer et al., 2009 ) PROVEAN http://provean.jcvi.org/ evolutionary conservation-based ( Kumar et al., 2014 ) SIFT http://sift.jcvi.org/ evolutionary conservation-based ( Ohashi & Tokunaga, 2001 ) SNAP https://www.rostlab.org/services/SNAP/ machine learning method (neural-network), protein sequence and structure-based ( Carvalho & Mesquita, 2013 ) PredictSNP 1.0 http://loschmidt.chemi.muni.cz/predictsnp Consensus tool ( Esaki et al., 2012 ) Results The tested samples of the COX-3 gene PCR amplification produced a 524-bp DNA fragment of camel breeds reared in Egypt ( Fig. 1 ). The amplified fragments of the COX-3 gene from the three different breeds were sequenced and aligned with sequences of other dromedarius in the database NCBI/Bankit/GenBank DNA Sequencing: The FASTA format was generated for the PCR-sequenced products following outsourcing; before outsourcing, the required steps for data processing were taken. Tools for Single-Nucleotide Polymorphism Identification : The sequencing analysis of 524 bp fragments from camel COX-3 gene (Fig.2) was discovered to be polymorphic by comparison with the camelus species sequence (GenBank: Acc. no. OP994029 and OP994030). Two polymorphic sites (Fig. 3) (2 transitions) 280: C>T and 325: A>G were segregating into two detected haplotypes and A + T and C + G's predicted frequencies fell within the range of 51.15% and 48.85%, respectively. Diversity of haplotypes (genes) Hd=0.6671±0.056. A pairwise nucleotide diversity (π) of 0.00254±0.001 was computed, and the average number of differences among all haplotype pairs was equal k =1.33333±0.063. Among the three investigated populations (Baladi, Maghrabi and Sudani), The ranges of Hd and π were found to be 0.376 and 0.797, and 0.001 and 0.002, respectively. Sequence conservation ©: 0.996, Tajima's (D):1.89306, Fu's (Fs): 1.530, the divergence time (T): 6.734 and the Transition/Transversion bias ( R ): 359.575 were calculated. Nucleotide BLAST (BLASTn) The sequence alignments of the two detected haplotypes 1 (OP994029) and 2 (OP994030) with sequences of C. bactrianus (MH109977.1, 93%), Lama glama (NC_012102.1, 84%), Bubalus bubalis (MT186736.1, 80%) and Bos taurus (MN714218.1, 79%) are similar. The only difference in alignment sequences of the 2 detected haplotypes was recorded with sequences of C. dromedarius at identity 99 and 99.6%, ( Fig. 4 ). Novel SNPer Table 2 provides the variation results as reported by NovelSNPer concerning the types of SNPs and alterations in amino acids. Table 2. NovelSNPer detailed output file with transcript variation per line Name Start End Allele Refallele AA Ref AA Type SNP var1 280 280 C T Proline Serine SNP Novel var1 325 325 A G Isoleucine Valine SNP Novel BLASTx Figure 6 displays the comprehensive output of codon variation produced by the BLASTx algorithm. Sequences (seq1 , seq2) altered the codon CCA to CCT by substituting nucleotide bases (C & T) at position 280 in the reference sequence (Fig. 5). Similarly, the codon sequence (ATT> GTT) was altered when the nucleotide base "A" at position 325 was changed to G (Fig. 3). Proline changed to serine due to the nucleotide triplet variation from CCA to CCT (CA > CT allele), while isoleucine changed to valine due to the nucleotide triplet variation from ATT to GTT (AT > GT allele). NCBI GenBank SNPs were discovered in nucleotide sequences including the CA and AT alleles, which were uploaded to the NCBI GenBank with the accession numbers OP994029 and OP994030, respectively. Estimating Evolutionary Distances The majority of commonly employed techniques for estimating the distance between two sequences mainly estimate it by counting the number of nucleotide changes that take place in between. Table 3 displays the number of base substitutions made at each position between sequences. The MCL model was used to conduct the analysisn (Tamura et al., 2004). Reliability differences between the examined breeds were shown by the number of base changes per site between sequences. The findings revealed that Egyptian haplotypes 1 and 2 had the fewest nucleotide substitutions per site and the smallest genetic distance (0.004). This result showed that both had a closer relationship with each other than they do with their parents.Conversely, though, there is a genetic distance between Egyptian haplotype 2 and C. dromedarius (0.000), while Egyptian haplotype 1 showed a closer evolutionary distance to C. dromedarius (0.004). The two Egyptian haplotypes showed the same genetic distance with C. bactrianus (0.071). The genetic distances between Egyptian haplotypes 1 and 2 with Lama glama were 0.221 and 0.228, respectively. Meanwhile, the distance between Egyptian haplotypes and Bubalus bubalis is 0.331and 0.341, respectively whereas the genetic distance between Egyptian haplotypes and Bos taurus were 0.345, 0.344, respectively. Table 3: Estimates of evolutionary divergence between sequences Phylogenetic constriction A phylogenetic tree was constructed for three breeds in this work. Phylogenetic data declared that sequences of camels from Egypt (Fig. 6) showed the highest homology with other previously reported sequences in C. dromedarius (KX554934.1, >100%) with query coverage 100% whereas Egyptian camel sequences showed a >99% homology with C. bactrianus (MH109977.1), with query coverage 99%, the Egyptian camels showed >83% homology with Lama glama (NC_012102.1) with query coverage 99%, >80% homology with Bubalus bubalis (MT186736.1) with query coverage 99% and the lowest similarity with Bos taurus (MN714218.1, >79%) and query coverage 100%. These records were obtained from a genomic sequence and were predicted by automated computer analysis. As shown in Fig.6, graphical alignment indicates the locus of COX-3 fragment supplied sequences for all breeds. Prediction of protein The partial (mitochondrion) part which is found in the sequence of the amplified COX-3 gene fragments produced by the ExPASy programme (http://web.expasy.org/translate) in the tested camels showed 174 amino acids (Fig. 7 & 8) with two non-synonymous mutations that resulted in proline to serine (P94S) and Isoleucine to Valine (I109V). The 3D tertiary structure of COX-3 mDNA from camels reared in Egypt was planned via the software known as the Protein Homology Analogy Recognition Engine (Phyre2). The results revealed that the single highest scoring template modelled the sequence with 12.5% confidence, and 35 amino acid residues, or 20% of the sequence, were detected at 29%. In the three-dimensional (3D) model of the COX-3 protein, the expected secondary structure is made up of 41% disordered regions, 9% beta strands, and 21% α-helix structure. The coiled sections are shown by the faint colour. The level of confidence in the prediction is shown by the "SS confidence" line (Fig.9), where red indicates a high level and blue a low one. Functional framework of nsSNPs on the COX-3 protein's 3D structure Verification Tools for SNPs Predict SNP was used to assess the possible effects on protein structure and function of an amino acid alteration caused by non-synonymous SNPs (nsSNPs) in the COX-3 gene. The results of six programmes (MAPP, PhD-SNP, PolyPhen-1, PolyPhen-2, and SNAP software) that employ various prediction techniques are combined in this method. SNPs (S94P) and (V109I) were found to be predicted as neutral based on the data (Table 4). PROVEAN and polyphen-2 were used to assess The prospective impacts on protein structure and function of an amino acid alteration caused by nsSNPs (C280T and A325G SNPs) in the COX-3 gene. The information showed that the SNPs proline to serine (P94S) and Isoleucine to Valine (I109V) were determined to be neutral (Table 4). Table 4: Analysis of COX-3 gene nsSNPs using PredictSNP Software Tools for SNP Validation and Verification It was crucial to accurately validate the variants following SNP identification, and additional in silico methods were employed for this purpose. PROVEAN Scores The PROVEAN tool filters variant sequences to find nonsynonymous variants that are functionally significant (Table 5). Two SNPs were shown to be harmful and one to be neutral by the PROVEAN analysis. A score of ≤ -2.5 on PROVEAN represented a detrimental impact on an amino acid variation, whereas a score of > -2.5 suggested a neutral impact. Table (5) Prediction and scores generated by the PROVEAN tool Variant PROVEAN Score Prediction (Cutoff = 2.5) P94s 5.333 Neutral I109V -0.333 Neutral PolyPhen-2 In this study, the variations at positions 94 (proline to serine), was determined to be most likely benign, with a 0.002 score (sensitivity: 0.99; specificity: 0.30). Additionally, with a score of 0.049 (sensitivity: 0.94; specificity: 0.83), the mutation at position 109 (isoleucine to valine) was determined to be benign. According to Figures 10 and 11, the variants categorised as benign had numerical values of 0 and 1. Shown are 75 amino acids surrounding the mutation position (marked with a black box) I-Mutant The I-Mutant method was used in the current investigation to ascertain whether the SNPs discovered would raise or lower the COX-3 protein's stability (Table 6). The results demonstrated that the protein was more stable and that the SNPs (C→T) that changed the amino acid from proline to serine had a free-energy value >-0.5 kcal/mol, indicating that they were mostly stable. The other transitional alteration (A→G), on the other hand, changed the amino acid from isoleucine to valine. Its free-energy value was less than 0.5 kcal/mol, indicating that it was mostly unstable and that the protein's stability had diminished. Table 6: Protein stability reports generated by I-Mutant. Position Wild-Type Amino Acid New Amino Acid after Mutation Stability Reliability Index pH Temperature 94 109 P I S V increased decrease 1 7 7 7 25 25 MUpro The results of this investigation for mutations located at positions 94 (P→S) indicated that the protein's stability was increased by the amino acid change. Although the protein stability decreased with mutation 109 (I→V), Sorting Intolerant from Tolerant (SIFT) This method produced scores for the amino acid residue, with values ranging from 0 to 1. For SNPs, the cutoff value for tolerance was ≥0.05, and for tolerance, it was 0.05 or less. Because the change was tolerated, it was determined that the amino acid substitutions at positions 94 (proline to serine) and 109 (isoleucine to valine) affected the protein's function. These modifications got a score of 1.01 in this investigation.. The results summary validated by different computational tools has been presented in the Table 7. Table 7. Validation of results obtained from different bioinformatical tools. Mutation Provean PolyPhen-2 I-mutant Mupro SIFT P94S Neutral Benign Increased Increase stability Affected protein function I109V Neutral Benign Decrease Decrease stability Affected protein function P94S substitution Replacement of amino acids Proline in its natural state is a semi-conservative amino acid found in the coil region that is semi-sensitive to mutation, as shown in P94S (Fig. 12). I109V substitution The natural amino acid, issoleucine, is a semi-conservative amino acid found in the Strand region with semi-sensitivity to mutation, as demonstrated by the amino acid replacement V109I (Fig. 13). Discussion Genetic diversity is a measure of species' capacity for evolution. Populations with higher genetic diversity are predicted to be more resilient to environmental changes than populations with lower genetic diversity. These changes include disease, invasive species, habitat loss, overharvesting, and climate change (Kardos, 2021). The 524 bp mtDNA COX-3 gene was analyzed in this work to determine the genetic diversity and inter-population relationships of dromedary camels obtained from three populations in Egypt. According to the present findings, the camel COX-3 gene's promoter region has a high AT content (approximately 46.7% vs. 51.15%) and relatively scarce GC bases. These characteristics are similar to those of other camel κ-casein gene reports that have been published previously, (Pauciullo et al., 2013; Mutery et al., 2021), and they appear to be the same in other species (Beati et al., 2013). Furthermore, two polymorphisms (2 transitions) were found in COX-3 , which separated into two haplotypes (hap1 includes Baladi and Sudani populations with accession number OP994029, and hap2 includes Maghrebi populations with accession number OP994030). The haplotype diversity (0.667) and nucleotide diversity (0.00254) of the polymorphisms suggested that there were low variations across the types of dromedary camels as evidenced by the moderate to high very low nucleotide diversity (0.00254) and haplotype diversity (0.667). These variety indicators may indicate a markedly reduced selection pressure on camels relative to other animals that are farmed more intensively for a particular purpose (Alaqeely et al., 2021). In this study, two methodologies are typically used to detect the historical evolution of the population. The difference between pairs of sequences in the sample is analyzed using mismatch analysis, and the history of population growth is assumed to be represented by the distinct unimodal curve. The negative and notably differing Tajima's D and Fu's Fs values are seen as evidence of historical population increase. The Tajima's D and Fu's Fs values in this study were positive and did not reach statistical significance (P>0.1) which may point to a decline in the size of the population and/or balanced selection (Ming et al., 2021). These results agree with the low effective population size and decreased genetic variety found in wild Bactrian camels(Yadamsurenet al., 2012; Charruau, 2012). Taken together with the other two findings, it indicated that camel populations have stayed relatively steady and have not experienced population growth in the recent past. This is likely due to the population's resistance to the changes in living conditions, which will require more research to confirm. In BLASTN investigation of three Egyptian camel breeds (Baladi, Maghrebi, and Sudani) against a nucleotide database, functional annotation of COX-3 revealed height homology to the Arabian dromedary camel with the length of the gene was 524 bp (KX554934.1>100%), (Daloii et al., 2016), 489 bp of Camelus bactrianus (MH109977.1>93%) ( Ming et al., 2013), 436 bp of Lama glama (NC_012102.1>99%) (Westbury et al., 2016), 414bp of Bubalus bubalis (MT186736.1>80%) (Sun et al., 2020), 415 bp of Bos taurus (MN714218.1, >79%) (Xia et al., 2020). The phylogenetic analysis demonstrated that camel dromedaries belonged to a unique mitochondrial lineage with little genetic variation from other camel breeds. The results showed that the genetic distances between the Sudani and Baladi breeds (haplotype 1) were quite similar, which might be explained by their respective geographic positions. This could provide a plausible explanation for the observed high haplotype sharing rate amongst breeds. Additionally, the data showed that there is no pairwise genetic difference between the haplotypes of the Sudani and Baladi populations. The Baladi and Sudani breeds were declared to have the greatest genetic distance from each other, indicating a closer relationship and shared ancestry between the two breeds. The bootstrap value of 1000%, which serves as a baseline for assessing the phylogenetic tree's accuracy, is consistent with this finding (Dharmayant, 2011). These results are closely related to those of (Abdel-Aziem et al. (2022)), which reported that Maghrebi was divided into a single cluster, Baldi and Sudani breeds showed genetic diversity and resemblance. Many studies used molecular markers, such as microsatellites (Manee et al. 2019), microsatellites and start codon targeted (SCoT) markers (Al-soudy et al. 2018), mitochondrial ATP6 and ATP8 gene sequences (Li et al. 2017), or mitochondrial sequence variations (Ming et al. 2017; Ming et al. 2021) to estimate evolutionary relationships and genetic diversity as well as phylogenetic analyses between breeds. This result revealed that the variation in two DNA sequences of nucleotides at locations 280 (CCA / TCA) and 325 (ATT /GTT) determined to be SNPs that are not synonymous (nsSNPs), and so correlated with the conversion of proline into serine, an amino acid and (Isoleucine to Valine) at positions 94 and 109, respectively. It has been suggested that COX genes had the fewest nonsynonymous alterations, suggesting that the Camelus lineage placed a strong evolutionary pressure on them (Mohandesan et al., 2017). Since single-base variations in the amino acid sequence of the protein they encode are known as nonsynonymous single nucleotide polymorphisms (nsSNPs), they have been extensively researched. nsSNP variations are linked to disease by removing the original functionality of individual proteins, such as stability and enzyme active sites. The technology for genotyping and DNA sequencing has advanced quickly, leading to the discovery of millions of SNPs. While some harmful nsSNPs are known to be connected to complicated or hereditary disorders, the majority of nsSNPs are benign or neutral and have no effect on protein function (Gong et al., 2021). It is very important to predict and recognize important variants that have a negative impact about the structure and function of proteins utilising a range of computational techniques. However, because each algorithm uses a different set of parameters for prediction, the current in silico techniques have certain flaws in their ability to predict harmful nsSNPs. Therefore, single algorithms should not be taken into account for accurate prediction of harmful nsSNPs. Various methods with various parameters and characteristics must be implemented in order to accurately predict harmful nsSNPs. A dependable result can be produced by a consensus result achieved using the majority of the tools (Rozario et al., 2021). In silico technologies were employed to predict the effect of the identified SNPs in the structure and function of proteins. In this study, the I-Mutant and MUpro tools showed that P94S nsSNP showed increase in the COX-3 protein stability whereas I109V nsSNP was found to decrease the protein stability. Because each prediction tool utilizes method with different feature, it is expected to obtain dissimilar outcomes. However, all the tools used in the present investigation supplied enough proof of the neutral effect concerning the P94S and I109V nsSNPs. Therefore, these nsSNPs are considered to have a little influence on the protein function and may be not associated with diseases. Conclusion The results presented in this work are the first reported on the genetic structure combined with an in-silico study (which highlighted the polymorphism of nucleotide and protein mutations) for the Egyptian dromedary populations. The degree of polymorphism revealed by the COX-3 markers provides important information on the genetic structure of Egyptian camel populations. Furthermore, identified two nsSNPs of COX-3 showed neutral effect by using multiple in silico tools. These results offer a filtered data saving time, effort and cost that required before further validating using experimental analysis. Declarations Ethics approval and consent to participate: This study has been authorised by the Ethics of Medical Research Committee, National Research Centre, Al Buhouth St. Dokki – Cairo, Egypt, number 12440723. The Collection of Samples and extracting DNA : PCR amplification and sequencing: 35 cycles of denaturation at 95°C for 30s, annealing at 55°C for 30s, extension at 72°C for 45s, and final extension at 72°C for 7 minutes were used to carry out the amplification. The first denaturation was place at 95°C for 5 minutes. Using a DNA purification kit (ExoSap-IT, USB Corporation) and following the manufacturer's instructions, the amplified products were filtered to remove any remaining primers and dNTPs. The sequencing of the COX-3 amplified products was done in Macrogen Incorporation by using an automated DNA sequencer ABI 3730XL (Seoul, South Korea). Sequence data analysis: The MEGA11.0 program's Clustal W method was used to align the COX-3 sequences from 90 examined camels with the GenBank-available Camelus sequence (Tamura et al., 2013 ). Furthermore, MEGA11.0 was used to determine sequence composition and genetic differentiation. Moreover, ExPASy ( http://web.expasy.org/translate ) was used to generate an analysis of the translated protein of the COX-3 gene sequences of the camels that were examined. Estimation of genetic diversity: Polymorphic sites (S), number of haplotypes (H), haplotype diversity (Hd), nucleotide diversity (π), average number of nucleotide differences (K), and standard deviations (SD) were used to calculate the degree of genetic diversity using DNASP v5.10. These parameters were identified within and among all populations (Librado & Rozas, 2009 ). Neutrality tests The neutrality tests, including Fu’s Fs (Fu, 1997 ) and Tajima’s D (Tajima, 1989 ). Tajima's D is negative, the population is growing (due to bottlenecks or selective sweeps), there is an excess of low-frequency polymorphisms compared to expectations, and purifying selection is taking place (Al-Jumaili et al., 2020 ). Positive Tajima's D denotes low frequencies of high frequency polymorphisms, which could account for declining population size or counteract selection. Similarly, Tajima's D test is less potent than Fu's Fs test (Ramos-Onsins & Rozas, 2002 ). Phylogenetic Analysis Using MEGA X (version 2020), the neighbor-joining (NJ) tree for tested camel breed sequences and the phylogenetic tree connecting our camels to other camel breeds worldwide were built. Applications (Kumar et al., 2016 ). Our camel's COX-3 sequences were compared to Camelus dromedaries' reference sequences: (Arabian camel), camelus bactrianus (Mongolian camel MH109977.1), Lama glama (South American camelidNC_012102.1), and other species as Bubalus bubalis (water buffaloMT186736.1) and Bos taurus (cattle MN714218.1), that were downloaded from the NCBI database. 3D Structure Prediction of COX 3 gene fragment The 3D tertiary structure of COX-3 mDNA from camels reared in Egypt was predicted by software known as the Protein Homology Analogy Recognition Engine (Phyre2). Identification Tools for SNP The bioinformatics programmes NovelSNPer, BLASTn, BLASTx, and Bio-edit v 7.2.6 were used to analyse the sequencing data. Prediction of the deleterious nsSNPs Four different in silico SNP prediction algorithms (PREDICT SNP, Sorting intolerance from tolerance (SIFT), polymorphism phenotyping v2 (PolyPhen-2), and protein variation effect analyzer (PROVEAN) were used to predict the deleterious effects of nsSNPs. Six prediction programmes were utilised in the development of the PredictSNP tool, a consensus SNP classifier (MAPP, PhD-SNP, PolyPhen-1, PolyPhen-2, SIFT and SNAP) to give a more reliable and alternate prediction. If the score falls between − 1 and 0, the mutations are considered neutral, and if the score falls between 0 and 1, they are considered detrimental. SIFT determine whether the function of proteins is affected in any way via an amino acid substitution. The SIFT method is based on sequence homology, and nsSNPs may be deleterious if the score is equivalent to or lower than 0.05. The PolyPhen-2 server is an evolutionary conservation system for sequences and structures that is focused on categorising the deleterious effects of amino acid change. It has a value between 0 (tolerable) and 1 (deleterious). The PROVEAN service finds nonsynonymous variants and returns a pairwise sequence alignment (PSA) score. An amino acid variant is considered to have a negative effect on protein function if its PROVEAN score is less than or equal to 2.5, while a variant with a value greater than or equal to 2.5 is considered to have a neutral effect. Protein stability prediction: The MUpro and I-Mutant tools were utilised to predict modifications in the protein stability due to single-site mutations. MUpro predicts only whether or not the change will cause destabilization, without providing an actual ddG value while I-Mutant provides the ddG value(kcal/mol). I-Mutant 3.0 produces a DDG value based on the tertiary structure or protein sequence, which is predicted to be as follows: If ddG is less than or equal to 0.5 kcal/mol, it is mostly unstable; if ddG is greater than or equal to 0.5 kcal/mol, it is neutral. Accession numbers for nucleotide sequences: The sequences produced from this investigation were deposited in GenBank with these numbers. OP994029 and OP994030 with protein id = WHO17331.1 and WHO17330.1. PolyPhen-2 In this study, the variations at positions 94 (proline to serine), was determined to be most likely benign, with a 0.002 score (sensitivity: 0.99; specificity: 0.30). Additionally, with a score of 0.049 (sensitivity: 0.94; specificity: 0.83), the mutation at position 109 (isoleucine to valine) was determined to be benign. According to Figs. 10 and 11, the variants categorised as benign had numerical values of 0 and 1. Author Contribution Sekena H Abdel-Aziem and Othman E Othman. conceived of the presented idea. Sally S Alam. developed the theory and performed the computations. Dalia M Mabrouk and Heba A Abd El-Kader. verified the analytical methods. Sekena H Abdel-Aziem. encouraged Othman E Othman. to investigate [a specific aspect] and supervised the findings of this work. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4032390","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":277436161,"identity":"d99410c3-c8f3-4d20-9519-3e1c60f29a88","order_by":0,"name":"Sekena H 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09:04:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":53521,"visible":true,"origin":"","legend":"\u003cp\u003eThe nucleotide sequence of 524-bp amplified fragment of COX3 gene SNPs at positions 280 and 325 in red\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4032390/v1/e2d40b468ddde88c86174ba9.png"},{"id":52497427,"identity":"9aa96732-2f1c-4a3e-9ba0-845cf8018250","added_by":"auto","created_at":"2024-03-12 08:56:20","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":103728,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe genotype \u003c/strong\u003eAT \u003cstrong\u003eof \u003c/strong\u003e\u003cem\u003eCOX-3 \u003c/em\u003e\u003cstrong\u003egene with A/G nucleotide at position\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4032390/v1/fe0209b3d5be1d139f024827.png"},{"id":52498302,"identity":"4f7ef3f3-29b6-4763-95b5-c06509017af8","added_by":"auto","created_at":"2024-03-12 09:04:20","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":185021,"visible":true,"origin":"","legend":"\u003cp\u003eQuery sequences producing alignments with the top 5 species\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4032390/v1/cf8873930b6bd93e7b24ad63.png"},{"id":52497435,"identity":"9a21b6c2-2698-4750-b224-1e6b8fd18bba","added_by":"auto","created_at":"2024-03-12 08:56:20","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":149414,"visible":true,"origin":"","legend":"\u003cp\u003eDetailed output of codons showing variations\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4032390/v1/4a464c46f7206cd7e9ddf543.png"},{"id":52497426,"identity":"2a683fef-6958-4b35-ac35-5e3ab1408eb1","added_by":"auto","created_at":"2024-03-12 08:56:20","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":11821,"visible":true,"origin":"","legend":"\u003cp\u003ePhylogenetic tree shows the genetic distances among the three Egyptian camel breeds (Maghrebi and Fellahi) and other organisms based on COX-3\u003cem\u003e \u003c/em\u003egene sequence\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-4032390/v1/efaa94bc38026da148229a2d.png"},{"id":52497432,"identity":"e9238cab-3117-4ff7-b324-e54a488f0839","added_by":"auto","created_at":"2024-03-12 08:56:20","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":25017,"visible":true,"origin":"","legend":"\u003cp\u003eThe predicted 3D tertiary structure of the Camel COX-3 reared in Egypt\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-4032390/v1/4ea28f08391a3ae36598c121.png"},{"id":52498297,"identity":"5574eb1b-6806-4d6b-894c-26d8c2a6287e","added_by":"auto","created_at":"2024-03-12 09:04:20","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":26640,"visible":true,"origin":"","legend":"\u003cp\u003eshows the amino acid for COX-3 protein in Egyptian camels\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-4032390/v1/d07d4d4c28ae2b0f72fb113a.png"},{"id":52498923,"identity":"e3197c5a-3770-4437-81ff-7f8b72429bbb","added_by":"auto","created_at":"2024-03-12 09:12:20","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":435172,"visible":true,"origin":"","legend":"\u003cp\u003eThe 3D model of COX-3 protein's secondary structure is made up of the α-helix (green), beta strands (blue), and disordered areas (?).\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-4032390/v1/ee11c3a5dfcf9560556424a9.png"},{"id":52498300,"identity":"ae5bfd45-59e0-4a08-98c6-34251d200ac6","added_by":"auto","created_at":"2024-03-12 09:04:20","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":86177,"visible":true,"origin":"","legend":"\u003cp\u003ePredict SNP P94S\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-4032390/v1/97288afe0da3d3f1ec65bac0.png"},{"id":52497429,"identity":"b6788fe6-2068-4352-8d4f-393bf9f85315","added_by":"auto","created_at":"2024-03-12 08:56:20","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":79625,"visible":true,"origin":"","legend":"\u003cp\u003ePredict SNP I109V\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-4032390/v1/16c48e998849795b95f9de90.png"},{"id":52498925,"identity":"66f101e0-e1e1-4df8-b03e-0cd64a8c28f6","added_by":"auto","created_at":"2024-03-12 09:12:20","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":163603,"visible":true,"origin":"","legend":"\u003cp\u003eThe natural amino acid proline was found in a coiled region, according to the phyre2 investigator's results.\u003c/p\u003e","description":"","filename":"12.png","url":"https://assets-eu.researchsquare.com/files/rs-4032390/v1/0ac2202edd1a5166580a51e1.png"},{"id":52499036,"identity":"902b4319-8037-4043-bc95-58c2b0cba589","added_by":"auto","created_at":"2024-03-12 09:20:20","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":154682,"visible":true,"origin":"","legend":"\u003cp\u003eThe phyre2 investigator's result revealed that the wild amino acid Isoleucinelocated in a Strandregion.\u003c/p\u003e","description":"","filename":"13.png","url":"https://assets-eu.researchsquare.com/files/rs-4032390/v1/154978891d7c1be49893f618.png"},{"id":52578929,"identity":"5a146b74-1818-4bcb-9da1-6e3da7b8037e","added_by":"auto","created_at":"2024-03-13 07:18:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2194118,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4032390/v1/f95e16f0-3df2-4152-9ef1-4fb554efd07c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Genetic diversity among three camel populations reared in Egypt using mitochondrial COX-3 gene","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBased on archaeological evidence, the one-humped camel (Camelus dromedarius) originated in the southeast of the Arabian Peninsula (Almathen et al., 2021). As a result of its remarkable tolerance to harsh desert circumstances, this type of livestock is unique (Al Askar et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Ancient trade routes have dispersed dromedary camels throughout semi-arid and desert areas of Africa, the Arabian Peninsula, and southwest Asia (Bahbahani \u0026amp; Almathen, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Camels in Egypt are belonged to Camelus dromedaries\u0026rsquo; family, which is often referred to as the Arabian camel (Sallam, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The total number of camels recorded in Egypt was 119,885 (Ashour \u0026amp; Abdel-Rahman, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). There are five breeds of camel reared in Egypt which are used for many purposes. The Maghrabi breed is reared for meat and milk production, Falahi or Baladi for transportation and agricultural operations, Sudani and Somali breeds for riding and racing purposes and the Mowallad breed which is a hybrid between Falahi and Maghrabi (Abdel-Aziem et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe evaluation of genetic diversity is essential for managing genetic resources for long-term preservation and application. Animal biodiversity management relies heavily on the characterization of genetic variety both within and between breeds and populations. This aspect has very important role especially in countries with negative population growth as in Egypt (Faye, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe mitochondrial genome (mtDNA) is an uniparentally inherited marker system, has the characteristics of a high evolution rate with no recombination and it has shown to be highly informative for determining the degree of their genetic variability, which is essential in defining conservation priorities for regional breed's specific programs (Di Lorenzo et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The length of the dromedary camel mitochondrion is about 16.6 kb. It consists of 22 tRNA gene, two rRNAs genes, 13 protein-coding genes and non-coding control region. The 13 protein-coding genes are cytochrome c oxidases (COX) 1, 2 and 3; NADH dehydrogenases (ND) 1, 2, 3, 4, 4L, 5 and 6; ATP synthases (ATP) 6A and 8; and cytochrome b (CytB) (Alaqeely et al.,2021). Little is known about COX-3 gene in camel, although it is an important component of the respiratory chain and is conserved among species. The camel genome's SNPs are essential for the development of beneficial features (Ali et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Before doing additional laboratory research, computational methods can be used to first filter potentially harmful SNPs that may alter susceptibility to diseases (Venkata et al., 2022). Geneticists and breeders may find it helpful to combine the DNA-sequencing-based approach with silico tools (PROVEAN, I-Mutant, SIFT, MUpro, and Polyphen-2) to find unknown SNPs that may have an impact on the structure and biological function of a protein (Ali et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Therefore, in the current study, mtDNA COX-3 gene was analyzed to better understand the genetic diversity among native Egyptian camel breeds and to explore the effect of nsSNPs on COX-3 protein structure and function.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study has been authorised by the Ethics of Medical Research Committee, National Research Centre, Al Buhouth St. Dokki \u0026ndash; Cairo, Egypt, number 12440723.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe Collection of Samples and\u003c/strong\u003e \u003cstrong\u003eextracting DNA\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBlood samples from Sudani and Falahi (Baladi) camels were collected from the camel market in Berkash, Giza, Egypt, whilst samples from Maghrabi camels were provided by King Mariout Research Station.Phenol/chloroform procedure previously described by Wajid et al. (2014) was used to isolate genomic DNA from blood samples.\u0026nbsp;Thermo Scientific, USA\u0026apos;s NanoDrop spectrophotometer was used to quantify the extracted DNA, which was then kept at -20\u0026deg;C until needed. For the purpose of amplifying the COX-3 mitochondrial area, a 50 \u0026mu;l PCR reaction mixture including 10X buffer (containing 15 mM MgCl2), 10 mM dNTPs mix, 10 pmol of universal primers (Cui et al., 2007), and 5 U Taq DNA Polymerase was utilised.\u003c/p\u003e\n\u003cp\u003eThe used primer:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eF: ccagtgatgacgggacgttg\u003c/p\u003e\n\u003cp\u003eR: TAGATGTGAAGTGGAATTTC\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePCR amplification and sequencing:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e35 cycles of denaturation at 95\u0026deg;C for 30s, annealing at 55\u0026deg;C for 30s, extension at 72\u0026deg;C for 45s, and final extension at 72\u0026deg;C for 7 minutes were used to carry out the amplification. The first denaturation was place at 95\u0026deg;C for 5 minutes. Using a DNA purification kit (ExoSap-IT, USB Corporation) and following the manufacturer\u0026apos;s instructions, the amplified products were filtered to remove any remaining primers and dNTPs. The\u0026nbsp;sequencing of the\u0026nbsp;COX-3\u0026nbsp;amplified products was done in Macrogen Incorporation by using an automated DNA sequencer ABI 3730XL (Seoul, South\u0026nbsp;Korea).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSequence data analysis:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe MEGA11.0 program\u0026apos;s Clustal W method was used to align the COX-3 sequences from 90 examined camels with the GenBank-available Camelus sequence (Tamura et al., 2013). Furthermore, MEGA11.0 was used to determine sequence composition and genetic differentiation.\u0026nbsp;Moreover,\u0026nbsp;ExPASy (http://web.expasy.org/translate) was used to generate an analysis of the translated protein of the COX-3 gene sequences of the camels that were examined.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eEstimation of genetic diversity:\u003c/h3\u003e\n\u003cp\u003ePolymorphic sites (S), number of haplotypes (H), haplotype diversity (Hd), nucleotide diversity (\u0026pi;), average number of nucleotide differences (K), and standard deviations (SD) were used to calculate the degree of genetic diversity using DNASP v5.10.\u0026nbsp;These parameters were identified within and among all populations (Librado \u0026amp; Rozas, 2009).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNeutrality tests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe neutrality tests, including\u0026nbsp;Fu\u0026rsquo;s \u003cem\u003eF\u003c/em\u003es (Fu, 1997) and Tajima\u0026rsquo;s D (Tajima, 1989).\u0026nbsp;Tajima\u0026apos;s D is negative, the population is growing (due to bottlenecks or selective sweeps), there is an excess of low-frequency polymorphisms compared to expectations, and purifying selection is taking place\u0026nbsp;(Al-Jumaili et al., 2020).\u0026nbsp;Positive Tajima\u0026apos;s D denotes low frequencies of high frequency polymorphisms, which could account for declining population size or counteract selection. Similarly, Tajima\u0026apos;s D test is less potent than Fu\u0026apos;s Fs test\u0026nbsp;(Ramos-Onsins \u0026amp; Rozas, 2002).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhylogenetic Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing MEGA X (version 2020), the neighbor-joining (NJ) tree for tested camel breed sequences and the phylogenetic tree connecting our camels to other camel breeds worldwide were built. Applications\u0026nbsp;(Kumar et al., 2016).\u0026nbsp;Our camel\u0026apos;s COX-3 sequences were compared to Camelus dromedaries\u0026apos; reference sequences:(Arabian camel), camelus bactrianus (Mongolian camel\u0026nbsp;\u003ca href=\"https://www.ncbi.nlm.nih.gov/nucleotide/MH109977.1?report=genbank\u0026log$=nuclalign\u0026blast_rank=36\u0026RID=FA7DYR3E013\" target=\"lnkFA7DYR3E013\" title=\"Show report for MH109977.1\"\u003eMH109977.1\u003c/a\u003e), Lama glama (South American camelid\u003ca href=\"https://www.ncbi.nlm.nih.gov/nucleotide/NC_012102.1?report=genbank\u0026log$=nuclalign\u0026blast_rank=1\u0026RID=4ZV7RGTH016\" target=\"lnk4ZV7RGTH016\" title=\"Show report for NC_012102.1\"\u003eNC_012102.1\u003c/a\u003e), and other species as Bubalus bubalis (water buffaloMT186736.1) and Bos taurus (cattle MN714218.1) , that were downloaded from the NCBI database.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3D Structure Prediction of COX 3 gene fragment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe 3D tertiary structure of COX-3 mDNA from camels reared in Egypt\u0026nbsp;was predicted by software known as the Protein Homology Analogy Recognition Engine (Phyre2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIdentification Tools for SNP\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe bioinformatics programmes NovelSNPer, BLASTn, BLASTx, and Bio-edit v 7.2.6 were used to analyse the sequencing data.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrediction of the deleterious nsSNPs\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFour different in silico SNP prediction algorithms (PREDICT SNP ,\u0026nbsp;Sorting intolerance from tolerance (SIFT), polymorphism phenotyping v2 (PolyPhen-2), and protein variation effect analyzer (PROVEAN)\u0026nbsp;were used to predict the deleterious effects of nsSNPs.\u0026nbsp;Six prediction programmes were utilised in the development of the PredictSNP tool, a consensus SNP classifier (MAPP, PhD-SNP, PolyPhen-1, PolyPhen-2, SIFT and SNAP)\u0026nbsp;to give a more reliable and alternate prediction.\u0026nbsp;If the score falls between -1 and 0, the mutations are considered neutral, and if the score falls between 0 and 1, they are considered detrimental. SIFT determine whether the function of proteins is affected in any way via an amino acid substitution. The SIFT method is based on sequence homology, and nsSNPs may be deleterious if the score is equivalent to or lower than 0.05. The PolyPhen-2 server is an evolutionary conservation system for sequences and structures that is focused on categorising the deleterious effects of amino acid change. It has a value between 0 (tolerable) and 1 (deleterious). The PROVEAN service finds nonsynonymous variants and returns a pairwise sequence alignment (PSA) score. An amino acid variant is considered to have a negative effect on protein function if its PROVEAN score is less than or equal to 2.5, while a variant with a value greater than or equal to 2.5 is considered to have a neutral effect.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProtein stability prediction:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe MUpro and I-Mutant tools were utilised to predict modifications in the protein stability\u0026nbsp;due to single-site mutations. MUpro predicts only whether or not the change will cause destabilization, without providing an actual ddG value while I-Mutant provides the ddG value(kcal/mol).\u0026nbsp;I-Mutant 3.0 produces a DDG value based on the tertiary structure or protein sequence, which is predicted to be as follows: If ddG is less than or equal to 0.5 kcal/mol, it is mostly unstable; if ddG is greater than or equal to 0.5 kcal/mol, it is neutral.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAccession numbers for nucleotide sequences:\u003c/strong\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;The sequences produced from this investigation were deposited in GenBank with these numbers.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOP994029 and OP994030 with protein id= WHO17331.1 and WHO17330.1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ePrediction tools used in the analysis.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"714\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.126050420168067%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrediction tool\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.857142857142854%\"\u003e\n \u003cp\u003e\u003cstrong\u003eURL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.050420168067227%\"\u003e\n \u003cp\u003e\u003cstrong\u003eType\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.966386554621849%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.126050420168067%\"\u003e\n \u003cp\u003e\u003cstrong\u003eI-Mutant 2.0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.857142857142854%\"\u003e\n \u003cp\u003e\u003cstrong\u003e(\u003c/strong\u003ehttps://folding.biofold.org/cgi-bin/i-mutant2.0\u003cstrong\u003e)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.050420168067227%\"\u003e\n \u003cp\u003e\u003cstrong\u003emachine learning method (SVM)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.966386554621849%\"\u003e\n \u003cp\u003e\u003cstrong\u003e(\u003c/strong\u003eCapriotti et al.,2005\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.126050420168067%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMutPred\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.857142857142854%\"\u003e\n \u003cp\u003ehttp://mutpred.mutdb.org/\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.050420168067227%\"\u003e\n \u003cp\u003e\u003cstrong\u003eevolutionary conservation and structure-based\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.966386554621849%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;(\u003c/strong\u003eKlein \u0026amp;\u0026nbsp;Power, 2007\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.126050420168067%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhD-SNP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.857142857142854%\"\u003e\n \u003cp\u003ehttp://snps.biofold.org/phd-snp/phd-snp.html\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.050420168067227%\"\u003e\n \u003cp\u003e\u003cstrong\u003emachine learning method (SVM)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.966386554621849%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;(\u003c/strong\u003eDoss et al., 2008)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.126050420168067%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePolyPhen-2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.857142857142854%\"\u003e\n \u003cp\u003ehttp://genetics.bwh.harvard.edu/pph2/index.shtml\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.050420168067227%\"\u003e\n \u003cp\u003e\u003cstrong\u003eevolutionary conservation and structure-based\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.966386554621849%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;(\u003c/strong\u003eSpencer et al., 2009\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.126050420168067%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePROVEAN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.857142857142854%\"\u003e\n \u003cp\u003ehttp://provean.jcvi.org/\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.050420168067227%\"\u003e\n \u003cp\u003e\u003cstrong\u003eevolutionary conservation-based\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.966386554621849%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;(\u003c/strong\u003eKumar et al., 2014\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.126050420168067%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSIFT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.857142857142854%\"\u003e\n \u003cp\u003ehttp://sift.jcvi.org/\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.050420168067227%\"\u003e\n \u003cp\u003e\u003cstrong\u003eevolutionary conservation-based\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.966386554621849%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;(\u003c/strong\u003eOhashi \u0026amp; Tokunaga, 2001\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.126050420168067%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSNAP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.857142857142854%\"\u003e\n \u003cp\u003ehttps://www.rostlab.org/services/SNAP/\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.050420168067227%\"\u003e\n \u003cp\u003e\u003cstrong\u003emachine learning method (neural-network), protein sequence and structure-based\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.966386554621849%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;(\u003c/strong\u003eCarvalho \u0026amp; Mesquita, 2013\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.126050420168067%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePredictSNP 1.0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.857142857142854%\"\u003e\n \u003cp\u003ehttp://loschmidt.chemi.muni.cz/predictsnp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.050420168067227%\"\u003e\n \u003cp\u003e\u003cstrong\u003eConsensus tool\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.966386554621849%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;(\u003c/strong\u003eEsaki et al., 2012\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Results","content":"\u003cp\u003eThe tested samples of\u0026nbsp;the COX-3 gene PCR amplification produced a 524-bp DNA fragment\u0026nbsp;of camel breeds reared in Egypt (\u003cstrong\u003eFig. 1\u003c/strong\u003e). The amplified fragments of the COX-3 gene from the three different breeds were sequenced and aligned with sequences of other dromedarius in the database NCBI/Bankit/GenBank\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDNA Sequencing:\u003c/strong\u003e The FASTA format was generated for the PCR-sequenced products following outsourcing; before outsourcing, the required steps for data processing were taken. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTools for Single-Nucleotide Polymorphism Identification\u003c/strong\u003e:\u003c/p\u003e\n\u003cp\u003eThe sequencing analysis of 524 bp fragments from camel COX-3 gene (Fig.2) was discovered to be polymorphic by comparison with the camelus species sequence (GenBank: Acc. no. OP994029 and OP994030). Two polymorphic sites (Fig. 3) (2 transitions) 280: C\u0026gt;T and 325: A\u0026gt;G were segregating into two detected haplotypes and A + T and C + G\u0026apos;s predicted frequencies fell within the range of 51.15% and 48.85%, respectively. Diversity of haplotypes (genes) Hd=0.6671\u0026plusmn;0.056. A pairwise nucleotide diversity (\u0026pi;) of 0.00254\u0026plusmn;0.001 was computed, and the average number of differences among all haplotype pairs was equal \u003cem\u003ek\u003c/em\u003e=1.33333\u0026plusmn;0.063. Among the three investigated populations (Baladi, Maghrabi and Sudani),\u0026nbsp;The ranges of Hd and \u0026pi; were found to be 0.376 and 0.797, and 0.001 and 0.002, respectively.\u0026nbsp;Sequence conservation \u0026copy;: 0.996, Tajima\u0026apos;s (D):1.89306,\u0026nbsp;Fu\u0026apos;s (Fs):\u0026nbsp;1.530,\u0026nbsp;the divergence time (T): 6.734 and\u0026nbsp;the Transition/Transversion bias (\u003cem\u003eR\u003c/em\u003e): 359.575 were calculated.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNucleotide BLAST (BLASTn)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sequence alignments of the two detected haplotypes 1 (OP994029) and \u0026nbsp;2 (OP994030) with sequences of C. bactrianus (MH109977.1, 93%), Lama glama (NC_012102.1, 84%), Bubalus bubalis (MT186736.1, 80%) and Bos taurus (MN714218.1, 79%) are similar. The only difference in alignment sequences of the 2 detected haplotypes was recorded with sequences of C. dromedarius at identity 99 and 99.6%, (\u003cstrong\u003eFig. 4\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNovel SNPer\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2 provides the variation results as reported by NovelSNPer concerning the types of SNPs and alterations in amino acids.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003eNovelSNPer detailed output file with transcript variation per line\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eName\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eStart\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eEnd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eAllele\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eRefallele\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eRef AA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eType\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eSNP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003evar1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e280\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e280\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eProline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eSerine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eSNP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eNovel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003evar1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eIsoleucine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eValine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eSNP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eNovel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eBLASTx\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFigure 6 displays the comprehensive output of codon variation produced by the BLASTx algorithm. Sequences (seq1 , seq2) altered the codon CCA to CCT by substituting nucleotide bases (C \u0026amp; T) at position 280 in the reference sequence (Fig. 5). Similarly, the codon sequence (ATT\u0026gt; GTT) was altered when the nucleotide base \u0026quot;A\u0026quot; at position 325 was changed to G (Fig. 3). Proline changed to serine due to the nucleotide triplet variation from CCA to CCT (CA \u0026gt; CT allele), while isoleucine changed to valine due to the nucleotide triplet variation from ATT to GTT (AT \u0026gt; GT allele).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNCBI GenBank\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSNPs were discovered in nucleotide sequences including the CA and AT alleles, which were uploaded to the NCBI GenBank with the accession numbers OP994029 and OP994030, respectively. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEstimating Evolutionary Distances\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe majority of commonly employed techniques for estimating the distance between two sequences mainly estimate it by counting the number of nucleotide changes that take place in between. Table 3 displays the number of base substitutions made at each position between sequences. The MCL model was used to conduct the analysisn\u0026nbsp;(Tamura et al., 2004).\u0026nbsp;Reliability differences between the examined breeds were shown by the number of base changes per site between sequences. The findings revealed that Egyptian haplotypes 1 and 2 had the fewest nucleotide substitutions per site and the smallest genetic distance (0.004). This result showed that both had a closer relationship with each other than they do with their parents.Conversely, though, there is a genetic distance between Egyptian haplotype 2 and C. dromedarius (0.000), while Egyptian haplotype 1 showed a closer evolutionary distance to C. dromedarius (0.004). The two Egyptian haplotypes showed the same genetic distance with C. bactrianus (0.071). The genetic distances between Egyptian haplotypes 1 and 2 with Lama glama were 0.221 and 0.228, respectively. Meanwhile, the distance between Egyptian haplotypes and Bubalus bubalis is 0.331and 0.341, respectively whereas the genetic distance between Egyptian haplotypes and Bos taurus were 0.345, 0.344,\u0026nbsp;respectively.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3:\u0026nbsp;\u003c/strong\u003eEstimates of evolutionary divergence between sequences\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\" alt=\"image\" width=\"909\" height=\"134\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ePhylogenetic constriction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA phylogenetic tree was constructed for three breeds in this work. Phylogenetic data declared that sequences of camels from Egypt (Fig. 6) showed the highest homology with other previously reported sequences in C. dromedarius (KX554934.1, \u0026gt;100%) with query coverage 100% \u0026nbsp;whereas Egyptian camel sequences showed a \u0026gt;99% homology with C. bactrianus \u0026nbsp;(MH109977.1), with query coverage 99%, the Egyptian camels showed \u0026gt;83% homology with Lama glama (NC_012102.1) with query coverage 99%, \u0026gt;80% homology with Bubalus bubalis (MT186736.1) with query coverage 99% and the lowest similarity with Bos taurus (MN714218.1, \u0026gt;79%) and query coverage 100%. These records were obtained from a genomic sequence and were predicted by automated computer analysis. As shown in Fig.6, graphical alignment indicates the locus of COX-3 fragment supplied sequences for all breeds. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrediction\u003cem\u003e\u0026nbsp;\u003c/em\u003eof protein\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe partial (mitochondrion) part which is found in the sequence of the amplified COX-3 gene fragments produced by the ExPASy programme (http://web.expasy.org/translate) in the tested camels showed 174 amino acids (Fig. 7 \u0026amp; 8) with\u0026nbsp;two non-synonymous mutations that resulted in\u0026nbsp;proline\u0026nbsp;to\u0026nbsp;serine\u0026nbsp;(P94S) and\u0026nbsp;Isoleucine\u0026nbsp;to\u0026nbsp;Valine\u0026nbsp;(I109V).\u003c/p\u003e\n\u003cp\u003eThe 3D tertiary structure of COX-3 mDNA from camels reared in Egypt was planned via the software known as the Protein Homology Analogy Recognition Engine (Phyre2). The results revealed that the single highest scoring template modelled the sequence with 12.5% confidence, and 35 amino acid residues, or 20% of the sequence, were detected at 29%.\u003c/p\u003e\n\u003cp\u003eIn the three-dimensional (3D) model of the COX-3 protein, the expected secondary structure is made up of 41% disordered regions, 9% beta strands, and 21% \u0026alpha;-helix structure. The coiled sections are shown by the faint colour. The level of confidence in the prediction is shown by the \u0026quot;SS confidence\u0026quot; line (Fig.9), where red indicates a high level and blue a low one.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunctional framework of nsSNPs on the COX-3 protein\u0026apos;s 3D structure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVerification Tools for SNPs\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePredict SNP was used to assess the possible effects on protein structure and function of an amino acid alteration caused by non-synonymous SNPs (nsSNPs) in the COX-3 gene. The results of six programmes (MAPP, PhD-SNP, PolyPhen-1, PolyPhen-2, and SNAP software) that employ various prediction techniques are combined in this method. SNPs (S94P) and (V109I) were found to be predicted as neutral based on the data (Table 4). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePROVEAN and polyphen-2 were used to assess\u0026nbsp;The prospective impacts on protein structure and function of an amino acid alteration caused by nsSNPs (C280T and A325G SNPs) in the COX-3 gene. The information showed that\u0026nbsp;the SNPs\u0026nbsp;proline\u0026nbsp;to\u0026nbsp;serine\u0026nbsp;(P94S) and\u0026nbsp;Isoleucine\u0026nbsp;to\u0026nbsp;Valine\u0026nbsp;(I109V) were determined to be neutral (Table 4).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u003c/strong\u003e 4: Analysis of COX-3 gene nsSNPs using PredictSNP Software\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cimg 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Z2QlEaU6bOSbBrCP4PVG6l2pRkIOGfJIVZsmybaISldUYoJyrpqoEaypAecmakkTnyj3WUOP48QgSJhvlOpipE5QClBPuPl61Bdlgyp7nYniImV4ILkU65Q6vF7XnI2V7tyTXFZFB1EKNoxRDU5RyRYNffExqrItotzVJj5RQrqhEsfRKE6KWhxDyj1WwXUlxqkM3Da5BJ7oWbP2LTeCLzu68SVIi+wWx5BKT8jztSj6zQWFkCuplIqbwCOm9TXw7ImHwQ90KHwJr754CVz2GkDvHuPg0sZ7q90h/svRT3WuPX8ydK4tHvif9+CeCaPhcXRce96D0HkfHN+LY/J1vBlePvwAWPPuhXDeAoAh56N/7/dgnPMj5/QYD5c0Sq8P2fYinPDHSdg5He646Bxo/e9iFvvEsD9pZLf5wNGR4gPoDkcG4s76GFRVC7GotRBxdoLYEW1YWG82cRoTGxIOQcwF9keVlkxszqActwbQ8cHrTFUysqlYPRTUEOd6uZpzfWeHiQbJi4RLXU7kDSFldw4alc/t8YclUvrNRWW+FvXopzOkbgFkddH+pNUJqrN6jhgGDx29HyyZNBgmqCnOZmIDHqcuZ0yG8/deCj1nyb9eUanrOwNxF9gfJet4Z1GOm39zUZmvRT35pT7TpbYncbyPuwP+2HgbPDb1tzA/Feiu7zM7Pgznfn8JnD93fKIOqzKg60w48quHYOCCOWrJRdLc8RsIN/c9Fj579TwYvYrdOWSsJokGJI93jsGr2x8aZaLhmddjBjWgG1zV40JovlcpvPzYpfAQWi7o9AS0q7kdVr3WB95q9Cj0rL8PbFh9FgxfivFH3wP3N20EX26eDFcunK1ViG4wuKQf1sHu/66EGbOGA75kwflnPgkHbekGv11GG5S7XxW+vpNpohmIO67rVMHhKSc+BiXffwUu+dPdees4OPvIcTDuR9vgiSeHwp/FHOAAXB9uYHK92TivX21siDR5/jICVHOuh9idQR6zR9Jlf/z5YhV/GokvUFcDEufPd3LV7Q/95uLMM89EG1rd8U2pY6f8y8fCPif/Tj2BG5/fDlcfWYH8ovk3w7TzDoI1l+WuNzt/GYze5w5o+sFjcMJfzoUff3glbL/26MhfXn4R/KVToU+zj+Dyf14Nx+TND9vZa90Y2OfuA+HvD/eEBlHdvPV3kX/+/PkFf3PhL9ssNIDK5fnkwqXipc1dUX6i8OoaB8Kad/rD8XdIm7d1b2hz9DXQW1zIeph3Rz/09YN2d5JeAle8Luk0OTkJJxZr3kXfi+/BP//9MLjw7DN0HZJNfbm5MS3cSKCDQ6apsy6BE+66EE54CWuh/SOciND4RJ5YYNwpJ+DE4kt47SW0vbseYL8T4I+nYCLXoxrSl3q0TlLO9Ep3B3W5OTOrDpyR6lCXlIe85JsEEKLiE+UeqQuLGolTX1es3HPNr4vrYJ+VTNRHpUWym2gE1+WB5qpKTVHtsM/FypKzvVKMd2PzKa5xCC2DqpWbr4Y+7rOSifokTr2JlUNEENejOkGlHt59MjYxsM+tk118k9wYTlHlPist1EigSrZofBOfxIiQTZS7quIM6rqVQeomK9GIGy6cW7YzMuo2hePDRr5JAIFaez/Yx404ljucmw71PjY4dxyglki5z0om6rtY7coo0WjBdXXgcjmdVRoHeJVYWdItKMV4N7Y4lfuVRPaR71JTlVCJwG1ho6jP9YniIyffnLK1G9T7D/XHEin3WWlB/Qlw/aPn48QiVEnfKIk8rlC8Tb6MuGTAqjm4ZH+kcqeFNKknyo1uaNIo1hgOjxRqzIbfv/MWfAmNoF2nSwGOuRsnFoCTh+lw+wc1YMHC6bDqfwEaNr0HLoBL4Xc4saDJw1MLZQLG6ydt3haa4ATlL1Ofgw17/Rh+0hyNzUdAq++vhL/gxELWJcrbqModVrVEyn1WFxOUuzJKNFr4ui6XVRveGnxfH5XilL6qRJBLlHNJCey4FFJuNGQj9UXVyk18ouwnZRP12aPqTeInFUFcT3NVubZXbWKgCOrlqMSQqkQa0nOdcZX4Jj6JkaFTb2JlnGJHuqgcE1Tu4qWvrNAbwXztm/oBhsOf//lP+OKLL+CfqvQGPx33ba3ftR24KVl219L5hPS58+1vX9q/bg3MpnfS+fzUStfAG7qdO9r+Bv6JE4v66Rht3/n2p5rzE3LN8ZUoN7wg6UYXJl+NcoGyXc3OxEpU8DcXtHJe0sKrOhWyym319i8B/r0WHKieGJfC9ahfp1b41OO1MXA6Tj5On/EnrBLg9enSk1g3DdHPJqdJnKlXzR9qD23PXQcn4sTj/OfQG+dyLWne5is4FSQCGy7Y49zOQVAtFjG4uqERsU+Ue6QuTFysUdf3k1ZRKUcqzdejmEi5K6NE36ODUI/6YnQqTu2rYmTUI1E/CTaXwkKLSAPOENXCIB7FSXx3KiZ2iWQiMVSPlxwsx8k52cC+cJMcwakg9USjdMFrqCEhbokaF2Ahm6iYnCbJMH1DkpXKoDP89rzH4c6S38PMAY/DzP7Yb88ObBfBnTgm24z+E+HGIyS3yxkTYUbfodCVg34Fd/SfhD7UQ36E4x/Bz3pcBGXtfg/T+94Od/R5HKaXXARw+DB4sN9UmK5t8umduVZ6a7xyNz4m0mKbiwlL0bifHKBwgNSQek7jRqiPb65Hon4SbC6VhRaVhNeSqsdy2I1w33kz4I/YRtdlM1NWNhBGo+3hvtQegmvxTa7bL0nERfMbYQL6H+J2B9B/oXpGxx5w+F4Ae+/fA4Ychobmv8WYmfBgn5kYcyf0w7Sysq4wpOdMuLnLnWh/GIY0HwQ3s9JWim8yxk9G2zVsK4PTf/YwTO75Ozidt2EQjOyNvmZYq9lv4Z7es2AStz/C1fRmPEK3mFWPtCh3VbGmDGVdOdcD41QgH0ep8mLVcHhq03aAmqfAH2jyAKXw2kJ6G0FOmnyslMnHOadAQ7RsWEefSnC2rjOompnzD2oJn5ViLNqcmVTqEmXQ8aRH4d6fPwn39sJ2xiWy7UfdAxN63QN9eXAJ3NhrNtx+Ujc45aQpMOGMEXBl99kwHm0TzrhU6wH0PUNs43vi9p50llsR9DldbOOwDWuLhiPHwXH7om/fjjAM31ACTpiG9ZzD/nE9H4PLDtWtO+QmGIv2e86eDUPrkAFBB/tUy8rOgsu6zYG7z9bWbSR0ID96e58mtrt6zIEbcL10fMoOGQmjcXxXj7lwV1eMpTptxuF4PJzDWd3hkq5z4fo2OGgzHu7sOh6ux/Gdp16OBvHdUYJjzL+jyyg4iY9PdxjURex3lDwOlxyMttbj4b+6jISTuOZZ6J8H17ahWDI4VYk07idxZ0w0LFETBUhU1eRcaZxJwnnhVRdci94AulaUMTZeU5Z/2Rj4wQ9GwxIeL4Ex++4LvadtgA3T+sAPbpkK087fF/0/gH1vXaL1NsLU83CMcWw/fxpsoNylWOe80TDGxZ83le20viW3aPx5D8Ia3sdo/W57KJ/ytO6YpeTno8PbTZMSDA7xLp+3P8pbRv4NuI37wuhbRqfqbeD9Sdg5Xnxhv3rD1FKy4fHoMAJXPAJ+xvsv+X59uI8b6Xhc2x/m4K3/tTim7dF9T8b3galrw/Ebc2vY7tG8bdjWToU+ul0hPrW/RRoTesXJMaYl+pyKi/rOx/eEi6jgby5o5kJ9HnglI4nAUXg7HY6rvzfA/3zGF4sEHACdr5wMf3Ft4DVwLtdB13Mvwav/A3Dg4ZPhZbJzTlxXKrul4JIVHqKfTU6TkInatFkr4CPYG1q3fxBePG+AGLkAieaySiOH09DYKkpxrOrhQWhiczE8yqhHftUoVsKCkoO9ck80QR2RchrXkEYGVo6haqR0555XgjUeYJNUjOG+OJ2yXQP9jW3OJ8qQ0t1pypVEcqWeU2liCI1ucid/yE0jPlEX67dFlYycrRpunMlLTmQJSl3XKExd0meVGq5WYhQnURw36oqSTzRJhukbQFWkEm8LqRZuVOMD6DHpHHhow3ZodOAw6FqDJh0nA/z1HLaf/ddPoUWr4fiWMlQIjercD1f+dR321sHCmfeJda8fwrY3zuGvPHWp/THMnPxz6DUZxxi3T51WUS0HjtigqsdEjo00cjglJ90I1/MWcqsy4qQUXpBKHafS4ip8o1gJ8sodVc6NTJWF18J3WrezdIXrWrYA2PgwnPfI2fBXfOMroP3nPwP4+9lwPtrP//s2OLzljXCm2xCuMwhubXsQrHn1bLgAYx7ftB+c2HUQ/GnBTHj3fwG+3DQTRr83CG5pQzE94MJHQ4wrcwC8j3b6xELGVLV/lwvgsP/+M/R7tAf0w/Ue1uYunLRoAsHHxR0zgP6H4PZvehD6T+kBUzfhXOngQRzmoDhulEa9SNXISiKKN7JHKoiKTZS9uPBh2J59fjFsoABkw+rL4GFUiUR9/0Z47XPuAnz+HNy4NLkurvXBa/CPfzWC42kC8vli+C98E0KfWryyjMO4Umi0RI4aBz32+zvMnHoWXDxtMrz//Y7w26PQv/xSmLl5P2h98lk4oTgOam2eDINf0K9g7ftjgHe6waBpz8FGnCDceFQNnKBMgeNwujNoGtqnL4DP6veCK3ACR/WP27cUXpneDS55cyXUajoe+iy/BF75An1fLICblneHK87qCLCmG1yKMZeu2QbNDh8Jp+Ab8ssPbwnw8SS4dEY3WA2NedW02bzlqjUObQxb3u0Kl82gtgA2fu/HcMQh6Gg7Ho7ddy0sRvvlK3G9B46H3jW6w2Va8/KZXWHxf7eE007s7o4Eqj8qge/Vhs/e6wJXPHsX1DikMWzF/pWzqC2ATbyuGnBy+5/DobASZpP9o61wyGE3w8mvrUJ/bdifah58JDT63lpY/apW5/NGgkp3d/60iU+UkK5sG28jxdEIO07j5uvRDZV7rEnIxE1j+S4DMSLuDaBrxRlT5ZvglJo1oaa2WrX6wrR16G9zFXww8U24a/pG2Dj9Lnjjgffhjz3qcy6Mmg07Rn0Kn322AIaO6ghj6Y146WpocvNn8Omnan/iSViEdTj+iTehiYt/8hfwMMXjpOGUUcPgWYq/+T/hjSdwU3TbwvaVwdKy9pgndT+Y2BVuWrhUYtwN+/T2Nr1/S3ak8v68RPNoj08I9num4UQA89GRsN9NEwRc/+hDYcDhC2S/nvsp/OKwsbhNR8JVC4ZiJdz+q4/kTzEa8/7R+p6FYU/MhhdK68HZNz8AXfD2wM1nQz35aIa3YenoQ2DAYc9K/IKW2B/Lkzh0wU26v+8/0AW3QbZt6SMDoAyPv9jLYMAjSyt4fnd+TPBlRze+BGlBfdG4xTGk3GMtMLmQVcgsBFctKgNVaSTEgUdMwokDtZ9Dm39fD/MmjIEp5GB/+FoUN/Q9piWg7Gm4fMKF0O6d9QD/fhhccsVkeLrkNEnT2rx+vjlcssJD3Rav7BHIL4JtEpx31wUwrvRL/krUossehIdPoQBpbt+kHja6kY2yvdKd+mSSHrnYQuoG5Is0xPKSb6RxP46RsKDkYK/cnQmVltRXAyt72Bc3sjvlvuZoL1JpslDl3KBSR1U6uAzKN+5LDKn4RKkTaniT2FyMdMINbV45IWjoU5f61BWVKgGxJWPiXDWwzynXZNVcFl6yzyl1XaMgV5cMJKLZtyhJ4rhRV5R8otz16rqVg6pIJd4WUi28/ct13J/zxadkxfuPYL+9cNJxiH5yQZ9K7HUgtDoirkA9HfmNFouMPoXNb8v+zH3pXph7+DCY3O9xmM6fcFCOixO4HhtIpclxCc3ZSLmvOdoLKuawUCPZnXIdHrJR7JHyjfsSw9GkYsAmdlFplYXXwndZD+threDAvbbDmtI57HvgE/mPUOlToh/iOTrgx/rJxY9x0rHXQfDT5lKDWtlh9eGHsA8c3kY+uThn/30AajbDiQAFEKg+hj65CDH06QXx5VdrpeN3sAt/pWr9x+MwG29LVuErwH5Qj9br0APCFlxM+rgU9t7/QpjU+2FoWXoe9J+nvwVRqMsNF1xTle9ai+tFKudEbRTIiIpNlL24cGHsO3R/qMURAA3rXKIxLrYr1OWvjCE1m8P5aHXr4Biu8STcPvMsuOjxs+BX8+/xn1qUnfwo3EefTPz8HjiPMziLKsEp++yHb6BbQg/+5KIfNPseQANaNxZc8HxveO0/+vHkY/7zT2om8sUrcMf7NLob/o6ThFp7d4P96WtOONGQTy46QgM8d00a4sRkb6z/xXvwCG3j+8PgqmmD4FGpojSCmrTOA2fDPT2xHYjXC75pP/z4ttD4e9vhH+txvZj7yBZ3vnkoSvLB3fDoX92nF7ReocM+tXG9q/D9AK73gxvgmhmDYEpZY1zXdli7/gnev8ee6QJDFmFfc+iYcO0EW2HrX0nR99e74DFcl3xK0REnDpKz/3/sA199uhyep+QVA+HKuddj/05Y/UVjaNoGI2rtB9/HYyD/oDMlyUr4/NEdlbvavE86PsffXF+VfHEL9USxp5qETJTPsU5lIIrQm7+iN659Azy7bRts3boVtrE+BD0aiL9eyUNw6d+bwaFzu8DYknps45TrL9WYttD+OoA31myEHQ3aQtsGG2HaBT/ECUpHGIlh8skCJbSEJhzfBJp0o33aAUsXYsT17aEtxTRoD13Untg+bG3btIUdy8bCD3/4Qzh0AD3H0RthOkpSn8uzrYJ5GN+laROOqdcEJ7hoKMtr3whr3gEYehLWorpt2uPRehOfa7FPCXSuyO73vRau71ScpKidJhS6nSFeat4Q1RwKb2BN9GFEYhu0TtuThsLcXzTjid+iYx6Cbb/R3G+hEbQlfKNj4JS2P9XErvGo3GOtwNei4tkIzU7kTgvXOEx/czGVP4WQTy04Kgc3q3HpUgoXz90A7e6U/B/U/6l+gkELEncjvoQtn5BRnYr7CwEtRNksYN8NxVUDps0aBCfe9SJ8hOP/bEifYFAQ5QblRjdOJnusAnW5OTOrDrhGUKknSgE6SjTxYU9jKVHDpRGoPPQqDs3gnmt+XVwH+6xkoj4qLfjOA1bquSYLp5qrKvVUpePVVUn2qONUWpzKjUNoyR1RF4yN9yNSiuEoiuVhUOmKcohIhPNprCSoahMDRbBdVHNIdOklUu6z0kKNBKpki8a3OEaEbKJicspdr65beZKV/LoQ7roF63Z4a6l+csFtAPwOnzQlRfdHR0EFP9L9GthjKkw/ej9YOvnn/MmFuhJZXI8NpNSh3KByrKQeL0g5lu484GXc/IINIZfTeeCUDV6lnij32MYdVWlxKvcrCVfnO96kyy0/2+HdFfrJBbcL4NZV6cRSWIQ++uRC2hUwyTudUgx9ctED/aRXwGSfrx2/g0HdzY09uvFsIV16BfSfUiKfWrSZBZPO/h2cFodHyhUph0ZepYVrQBvd0MSBjFOBw51yh/QsuOonLWBv3OcN9AlFzWPhqmZkp2oAp/6sF/9Qe8PnNIlrBK074LsiWQnHOJV6qP63FpfC8fUBVr0xGd7/VyNodXI3WTcvSZEvnoOL+ZMLbKgDnx4nNXCb6n4f/d+rDQ04UHJY5e6h/lebJ+snF/SpRje4ahFNSBTdNretSbbD+2925U8uLpmOOqM33P2xeDiacnmEcA1VkiPHwT1n94ea6/STCw6KofVSvq6fTdJ3BrbRkJob5ICOtuPhzh4DoNb6LnDlzAWAlw1ao2yuR2PRqVvXwv61r4BzajeGTVvvYjtHu5U4CSnBFTpeJVuUb84Wx/IwqLicJhGT+LiSKt81wb3Bo0ZvAos1JvL7N8GadzHgyTWwJvLjO17fpwr8Jn/572G//ZrBR4O2wJYtT+ObcBdPa3D9KJ7NYuP18TAac38TTO9XG/a7pzG8t2ULrPpDF65F/rhmYnuw7cA38JLXhPPeu5++Zqt+6vn6PPLrR4Pmi71gvCRI/LLboHbt5rBm0NbUvlN+FK82KZ+MkT6ZM+Jb/xrr0v4D/OonuF8XTmO7axJfnDHB1x4t8drjmypfmBxAfRJVukUuooK/uRDFVdPCq3cyZH0aLl8qP8q+9PwL1Z4kUQ/bOSXj4OUrxsGdrcjYEOrQv+K0/WN4DGUN/3bjP+GYVpJ0Dv9e4lNY/zpKYt00pAPDvbSLcaZrznsQFl1+M1yD/bJWdYG+PvrP7eslwNVglUYOFl/BqSARsnDKqENsWINFnE7Fm2xxDPdoHNxCyuTMAWcJ2871eBBsEiaqa2OVXnAzqqEe9cXo1AeRn/uiGiXqYsUtQ1ISWkQacAaswbGkvEwmqc+puNiSFx9DOa6GqjpZ3Y0cYlWf0xDqNe5Lx2moQeqW3FJJ8TaJyWmSDNM3JFkpXpeuXihbB9v+dx9o0fwiDipr/3uY0f/3MBBds//5KX/l6UcU3P5Q/ZJOqq4qr0AH2zcs5H9FamB9/eRCWwI2uJz4mEiLbS5Glk6dJeH2DikhNaReUA5QlXqibKUcVUbcatMhDyoHr4Xvuj6yvfc6rMFzcWAj+iIZwC/quq9FrYNP0X74IQN53WXH3gEP970DBsTb+N5mfEZtBEd27MIVz+j4EDzU67dwRqgexXTlOmd0fBge7PlbON2F5DAbPv5vgAPq4XpxVHZMMzgAtsHHq/AV4p/b8NrYDxpSoaOb828WKOjCzjNh5NEAz/z5POj3d/fJS8CtiuvRku+iOsCmx4QVb7yfatNlUIFC2EJKHWynntxTJg8fXgbD5z8HG2AfaH7ECOhIzmYjoFP9feTrUPMvhZdx8rF3/V4w+FCuousUlW5Z4rcWDKrrEq6/YDsem32PhV83o4Bu8OuSJ+H3J/Gfc+GUk3pB422TYeBqgONPvxSjNWvf5tCXR5fCj/cF+Gz7k7Dhq+3w/fod2Q5ll8LwXrNheFuA57j+YfzbjbJDb4Lbek6Byw+lIMda+Oxf+0Czgy7DelifJwv3QO8PVsBatDduSL/dKIM+dfRrUbSZkXL/Xyth8QrUts39JxcLt2/l7eyNEWUHj4TRZz8Glx4s65KaAOeeOgfuOvVyKPt8G3wFtaH2IWg+hD4x0SJpaGW6rrI2zf0nF5v+G/f9h23gZIppPR7uKKHfb6Dn1Wfhr3Ac/HRf+koUOXlrUZyqkGIj9S7VAB8dr7yMEwkuQPeg4nKaxJkkjRdeXQK9AXSNrq/ijHkFef0bZ/wG5p75DnzydBmcPla+isMpt7wISzl2Kbx4C0DLJvSpBjq63Qe9W2P+8hdhFFXmGFlHqE27VAZtTrge6yziOmXrXoS5s118vH0Sf/3AHlAXJwyL5s2lIPZzVYrhTu72S14J57341DzOc/VwoLE44FiJd5+c0JgMO3bUhcaHAYx6fpnEL1uE+9USmjQkHxWSOhzf9V7og/u+Y1l632kQx9eFJlxTjyfHt4TGDbAOx0q9uP6ysXXg98t2QN3uk+HjP+FxQzhXm8QXZ0zIVusxoRF1vFKXHeoT9S6Riv7mQtXNUiIjiaAzm9fGwoNrcVJQ+wR4tKPGpX9zge3RUzkdHp81F179n73xQpsML195AhxIX6H642ROmzrzEpi3jXwPwktXTOZ/Yvajd2+A0eSlZIK/SkV+aS+e19+7BBnQktqYR+jTigOg0+UY2/5w+MH/vAcPz3paA3T2xSqNHE5DY6uMKE4MlCbuqJGQg4ccEFS80uJ1cY9UOhoiyl5nipqHB5qrKrWkiU2UnHSTO/e8EqzxABulum2TOkEpQC3hRrF4owSnEkJ9ElU1OVcSzuSlhJNKE0NodJM7+UMuG2OJ1MX6bVElI4mo3MjhlBvFUi/K5W5weWU/a7oSOaSXUIrjRl1R8jkNy6CVg6q4unRDjQpz341rzIPfPvI8lNY6GWYOmAozD/khvLX0Kp4c1HjpAyilH273nwoz6tPfvCkXE7d+Ctv1B92+LNnxPmHzOtin4Xn8Y+5mX74N2/ENKL1F9nEONugxwAWns0oTnyg56Ua4HseJwSvDTrxzwxhVdqlSgFrCjWLxRgkcRotIxRdMlSXU455a5sAtK98CaHA+/6D7ED7ixBy4ddqfYX2tn7H9jz/eD9599UqY6DaE60yAa1/F3P0vwInHTDhn/22waNrv4E8wlycIe+9/Ngw5bDxcrzEPacyL038LT2uZXGrA5LkPwXv/cQr/APxBXO97r10B/Ky+9H18hm8EJ/SZBZPr4Rt4CYcH5/0ZavxYftA9meLfvhGeERdDyg0X/hikjjUpiSjeyC49Vm5sI1Grz1FXc5w80Ne+/vcteHkZmcfB8NV4PPdqAZ063ACDj6BPNLbDqr+P46SH/6STj5/cBB2pFjetS/Wa3eT/hSiocQ+8shlX0aofNP9eKbz+vPxugsJ4sYx+W4Ep//9suPfn/aDZfz8HV70wGzqePIW/DvUn+p3F8gX8W4zb6UfaxL/2g9b0Y+5eHaHBFwtgxIoa8OcXesMrXzSC4+hrUWin32iMoDf8Ky6BWZv3Q/scGP/TlgCbp8FdHwBsxMmI/KB7Ntz95AL+7cY4+lH3gbXhgzcvhSnwJNz17kqA+v3hHrQ3xUkIQ7skC978GitWwcbvtYTu9GPuOtvgA5w81KTvluF6n/y4Nhx79ly4m9b78VS4529Pwj1zFsDn9frDXWjn32Q8ezfU+KtMZA5tORfuOmw/+PxfvKYArYiEf0fREs7qMRfuxHX9FXNq1aoBz790Diz5759CN/pB94GNYdNHg+Bx3son4V28nr//xSqYygVcIVG+Vuiu58018YkS0uW95iXH0ShOilocQ8o9VsF1JcapDNw2uQR6A+iae0OYr1XcT5VvhjPq1oV69epBXadjl8GmmRfC4fM6w63d6+EErg9MePdMuHDmJs6Drm/COI4/A24eMh9+TV85a9MOrp99ERxB9ucbw4Su8+Aj+s2Fe7up66YRvYkva3MlzL/2ZjiT4od+BC3obyMaE7avHrQ7sxPcfDpt1zVQdia+sX73I9iIb7z5pvH0ltb1qdEb+Ky8TeSn6MT+ax53NZ8d0m87+G24990z5LicvhImvHEltKH8ho2hMx67M29bzvt+3ZyL4XA6fi/ovq/HfIxpAfPgoqEzAI+cr98Ga9Lx5ON9xptw75u/hrbsoxDd/yi+7VXzoewMOt4SP+F33dmer1Xm+iD4sqMbX4K0yG5xDKn0hMr/PxeOrPAgeZFwqcuJtIW0STpMF8hjzsH7MxOcocD+ODTfb5aO8yWIO9qftGohFrUWIs5OEDuiDQvrzSZOY2JDwiGIucD+qNKSic0ZlOPWADo+8b+/TBnZVKweCmqIc71czbkessNEg+RFwqUuJ/KGkLI7B43K5/b4wxJplf9/LjKIs5nY4K7rYl3fGYi7wP4oWcc7i3Lc383/cxE7Ulqh6zsiNcxB0qLj588Xu3PQqHxuH5A83jkGrzn7k0bDk8cnPxIe7Y8vkBqiVrxeFMcGV0A1KhzWm42Pxg79a1H8A/BZw+A5cmQg8Rn749BhYjMKUG4YB+D6sGByvdnk1IsNkfLh0mFmgGrO9eDd3eGSLgOg5vrOcAt/ciH4uDxIuuxP8ryJP43EF6irAcnj7Tq56vaH/p+L9u3pn+nb9Wx+YgC0nN8JVv6hBOqrzdhzeOmll6rK/3MhjW9eJQaFc2PI55T7rLRQI4HK2arxjQI5SmPlzacodZ1qqED20MUWVeI7LdQiRbQOeUgl0yndHdTl5sysOnBGqkNdUh7ykm8SQIiKT5R7pC4saiROfV2xcs81vy6ug31WMlEflRbJbqIRXJcHmqsqNUW1wz4XK0vO9kox3o3Np7jGIbQMqlZuvhr6uM9KJuqTOPUmVg4RQVyP6gSVenj3ydjEwD63TnbxTXJjOEWV+6y0UCOBKtmi8U18EiNCNlHuqoozqOtWBqmbrEQjbrhwbtnOyKjbFI4PG/kmAYSo+Fwsd+gubnGxeh+LqxQHqCVS7rOSifouVrsySjRacF0duFxOZ5XGAV4lVpZ0C0ox3o0tTuV+JZF95LvUVCVUENfDbeGuqM+VgTQxUATb5UZWUfbHEmlIp4UaCdS4SnwTn8SIkE1Uu84lA1bNwSX7I5U7LaS5fZN65CENuaQxHB4pLdw2xU6pE5QcdJMAQlR8ohrmNYRKptNQCZfiYB9bIuU+q8Y4yBy6iUYLX9flsmqjmxjZLoGEqESQS5RiRKXFqdw4hJbUF1UrN7cut25KEhP12aPqTeInFUFcT3NVubZXbWy4Aq4rGQCHwJuw5FVeA2WwSgypSqQ+PTaqxlXim/gkRoZOvYmVcYod6aJyTFC5i9f9ZbkqNHoHmWW3tvs3Qq45vhLlhhck3ejC5KtRLlC2q9mZWDkEi0k1RT65mKcjh5urxH8ZkDFXohJa0JEa5kWryAb51WjdYAhx2ArhN6dgQsZ+5KiQqFcBcsK4nBZApZNBh3xn6rmtYnIMggydI0sFb80Ki8hjVkJi2B8c835yQA6F6yEa4MskAsP6ggqJMCIVxvV0mJ+QkHt9R+6IwvUCPj2u43fQG0IctkJkHx+hsp9cTPlsho7yk7Na3nDdIFS+HnR/KgKnqzI5BiI6H3lVSBwf586gsDvUrejjtXA9RAMq/cnFV4/Hmyf7q8P8hAR/fWu+q5MuULhegNev2xHqpAvTeiN3ARL18hLtR6KyJnKB1JDGFSAnjOu4AvF6K4Zk+fTIgM2TsR85KiT2x7kzKOwOdSt9fccOVN4+qpt25KhAowRxmEo0zEOom9ifeHWpAoXrBXh/MD95fNKFaX8zVxPQgOx6aeT4xcfx6P/rD8cdd5y4DeNb5JVXXoFV+96HvQpc37EjdX3nnVz4nDg5g8JuXQs/2N2DXsbfrB6SChBxhliTaHggHa4BqWEeogd/vD8ZiRWrF8Vxh+rFmUHDk04eUmlcpgASJnUTiY7YrBINc8jxswEt/jhFipHl7o/i/ZIWGZKIu8D+KKnNKKde2h3V1UKJ6ztjfY7sehGpAJFofV6TkLUPTi4qw5TPZmovOi/+QKkrRbxVhfBlOMF3yJPQnbq+g+RFwqVuYn2pIatKNMwhx88GqoedjP1K70/3vX+uvW/G7K/kH9HMe33rMHNzMsh2O0soxNc33sJ6s8muh8SOKEAk7SBNouG5Yd4h5DErITHxeOUDxQE5FK6HaIAvw4FhPUGF2JpJKiBvHCPnI3Fe4v1xdVL1omEOOX42UL3YEzQeFSIzPQNxR/vjVdFh8njnJ64SiOpqoW98fceGhEOQYTqANIlPi8Mijv5XPzj22GN1ZBjfHosXL4b3eXKB5LkeHWLOvr4r8clFilRtfszqsBASHj2o42cNVg7zpIY5aJUQl2MgnKHA/jg0nzYnSkvVC4g72p+06n7t3PGJ4mKDV6pXhCfHDJLmnBXjUtebNBesV8CtAbI//jrgjGwqVk/K5MY5S9Cc6yHp9ppdLxcJl7ohkZTdOZRbz6VrOVc2mRgcOfuTRvO5XgWQ8Gh/4gJuw/j8BW8hNDvExQbviPfDObJJpBE5hiRiTq8waHgTmuHOoBy3BkjdZMFscuql01STxzsjQDXneojdEXnMOUic7k90/vMlllsvKpN/A5wjY3/SaB2uVwEkXOr6xMR+ibJofCHIn4jLMRDxfriAbOLN8HVy6gXEnA4Mmri+K0CcnSBRVurG68lHHMWk09SRHKYDghb9+saA5CTUqQakqFg90VzcFgV1+0O/uTj66KPRZhjfLkuXLi34m4tM9LKNr+8i/D8X0vjmVXNIdOkQn09jNz9wuU8LUe6xJm9xjEhQ7nrVRqBGXWxcSZZ8p4U02RZRbnRDkwZGKlCXmzOz6oBrBJV6ohSgo0QTH/Y0lhI1XBqBykOv4tAM7rnm18V1sM9KJuqj0oLvPGClnmuycKq5qlJPVTpeXZVkjzpOpcWp3DiEltwRdcHYeD8ipRiOolgeBpWuKIeIRDifxkqCqjYxUATbRTWHRJdeIuU+Ky3USKBKtmh8i2NEyCYqJqfc9RqbtJIs+U4LaW7fpB55SF1mrAKHR0oLynFGziVlCUoBOoqa84lKmFNtBKq61CwOVu6SqidS7rOSifoulu484GXc/IINIZfTeeCUDV6lnij32MYdVWlxKjcOoSURqzSpE5SSOJwWfA+qJvGTiiCup7ku1tWQgTQxUER00xwWGakxDFFDeq5TskXjWxwjw6DicspdT2ziStiRek6luX2TeuQhdZmxChzulDukwUjiVOqpH3s6wkYiKj5RCXOqjUCNTVJHlbuk6iHlGtpnm4sJyl0ZJZpfsEFzVeNt1QBttAw+tqpSoqg0l8rilZZEUK2idVQ5gZRc1JdIvTsTN8Ip93gguZTD6mrIQJoYJMbfNJdFRmqMU4IrdLxKtijfnC2O5WFQcTlNIibxcSVVvmsCTXKsWfu2G8HXHi3x2uObKl+YHEB9ElW6RS5WLCbVlOxPLhzxXwaoQjxVkQi1umG5+Pg4keslDLh048L4zYnTMxB3XDetQqJeAeLsBOzQAqh0MuiQyxNGWE8+suupRiSHLiBWIbE/6bCIPGYlJObuj9MkheshGpDYPk9c16mQCCNSYVxPh/kJCUW/vl16nJhxAmhZERL18pKxH059gdSQxgXQcNYE7HAF4vVWDB8n6UmNSA7TgaRCYn8y6jgKu0PdSl/fqbTE9nmiANV4lCDlyBuXIKobb0BCObCC9QI7sz8F0fDsemmo3k5c3+othIbnxrFDC2HETl/fceG0quSuNytB8LuXTMihsFsLYKHc6zsb582pm3JkxzlL0Jy4pNs7cuIyierGB4iVAzwSVV69QFwuENbnNG+9ZFieemmoXvL6pt9cGMZ3RdZvLjIRd/L61uG3/JsLhAPkQe+fxPjRJe40Faun6sUZcjXnxSA7TFQlGuZB6nJkZfdH8WU4wXfIk9ByX9w0PFGvABIe7Y9XJTYHyUsqPGnwih3dv3L3R/H+uE4G4s7aH1UnqDmHOYNy3BqA68NCyfVmk7de7IgCRNKOoPGIyQqLyGNOEe2HP1DiSVNuvXQZHvtOCFAt93rQcK6nw0JIeJ79Cav1hVTykgpPGdIFK7A/SubhyEDc0f54VXTod5PGBYir5BIKfePrOzak1UtWgJAKzzAkKcetAbI//gC56yEDDlfNRAO4jA5DL1fzXg+p8GS9/Eh4dF7i/ckokBrmkJPGBq3rPUHLvb41PDM9A3FH++NV0eHOHZ90nCsQtCjXdwZidgGxCt6adpNmUI5bA2R/kuctm4rVkzIhzvVyNed6yA5L1cuPhEfnxe8Xu3OoWD0p4zcgcZyS+o2u7wJIWLQ/vkBqiFqBcok0hg2ugCpGhP1wGdk4LymTY0giZhcQK/ayJhf0H2wYhmEYhmEYhmHsDJmTiy5dusC//Vu5P8eoVrzxxhvQsmXLanNcqtv+GgE799UXO/fVFzv31Rc794ajstcC5bdp0wb+v98iamPee+89aNasGdCcw807XL86jzdt2gT777+/H6f9e9q4uu2vjcPYnft8fhvvueP43Gf5bbznjtPnPu238Z47ttd7G7txZV//Kf+AAw4o/1+LcgkOG9s4xsY2jrHx7j1OU+z6Nq7a4zTFrm9jG8fYeM8d5/3kgn534QJJXauu482bN+f8VSf272nj6ra/Ng5jd+7db6/SfhvvueP43Gf5bbznjtPnPu238Z47ttd7G7txZV//Kd8+uUBsbOMYG9s4prqN0xS7vo2r9jhNsevb2MYxNt5zxxX+5KK668cff5z5F709Vavb/poGdef+66+/5nFF80x3f7XHffVVe9xXX7XHvanTyj4PUD59cpH3X4v617/+pRaDoEkX/YK+uhyX6ra/RsDOffXFzn31xc599cXOveGo7LVA+fSvReX9WhTNYMtvG+DxvvvAPrcsyfAVoy2B0fucC4+vzfK5FsUsHQ379H0cNmTGVa45snyh6fHI2WbaRrSXt21rH4dz9xkNS7J8rsUxu3x/v7u25BY6rsl27tQNmbEVa+G62TD13MLXcOq8cHzmduj5T5wTsY1e6uqEPGnlnO9d0BxZvqrR3OMs2fgYqy/r2si6hiQnX9PHrW/hXEmt5Lkjm1tv8a/X76Y5sny7on2j41je82LBx6Gc88LXReVauc83u6g5sny7ou1J5z75mmHP+d96o+vAH29s/vFWzmt0ypbzOE3XpfYtvQfbVc2R5atIc5Q7uaAPNuLExLj0BZgNw2DY2y/4B0vB+J0dl66GN3Bbysry+GlcuibEtLkKPn+oJ9SL/ZVZfzR2lBdPdD0LYPZf5EmQ/UtfgBGSXDgf92UOFK5fti6KqQL7+52N6fO1GxbA559/Dp999hl89t4DAP0Hw7TSb16fP7LDcb0ef4TPrm6b4/fj6LyUlU6Dwf0BHngPtwG34/P3JuJ2HAxj9ImJeWIAPKRjysc7lFE96kBXn0vtuRtGwM9uDU9ghbb3uxo78vmrwhgFuk78IFwPzw2DER3GwFJ0kA8PeG4+2W94zh97uobe6LCvP3fp+CW3/gxGRPEL6FydP01eSPgwjYA7p2/08WLTfF5Xca/X72LsyOf/7se4MXgc3TmQx9tgmFpaKB+T1J7px+Yeh+788LnFxyH5ycuP13z5lRgvvXVfOLj/nOzrcxePHfn83/mYz33y8Rqf+5x4HeOigJ/2MDwH0/l355796HXnXuILbF9Fx6VT8TXjp7AgXt95U/PH74Kxo1j1du14CYzpMAKGPece3wtg2MifQZ9pG9iPd/8a7fLJRufd16P3tmX43vad8N7W1Qd8z0vnUq6fv8IDZQNgMNYO609vz+41duTzlzd2lDu5oO9dxcnxeONfZkNZp77Qt/MbcJe+yH799QaYdkEtGDt6LNSqVQtq1qwJY5dp/PS+UPPWMTAW7eSrNXqpr0c+F9+Xa22Eadf9At/UzYFfXDcNNmLM0tHi59xaY2Epxky9bkCIWTYWap4/lWM5H7dD4vvii7psw4ZpfXC9Y/021Ize2FHLt7+OQseDXtToCbFl5y5Q9vc13r904U0w9PqhmI1+PT6yj+hfOgZqXUD7txTGnnITxtwEHfG4JLcft1VjxvwsiknsL+br8ZNjQzY8Pufj8ddzQW3M0kLbv7P7+92N+ZrFhfc3aA9dzpoDq0txjMeh1gV4Tul48fmUY8Hnt2Yff+7d8eBjMXoRng16YHwt1x4fc1wfnQ/NletzSeK8fI0T3jnQEpo00O1rUAIPbdsGg9vQWM5/lwf+AGWnyDn4+mvcdt508fONt0Vam5PwunhHrhWu9w2PTzHHjnz+XT+moygvhN7fpj0MhTdg9Vo93n9/GPry+Q/PP3INhVo7GvSAsQ90gZsWyrmnFta3Eda8g+eyaWPva/ubbbBtUglP5rnW9X+ALnNowiB+soU3pbyBoV58vWoMtez923VjRz7/dz2mxxMdR+9v0I6P4xo95rmPV8yXg89/COhTEyecmkuvH/QGI34cuvW11cfhBvd4Xehev+LnD3z+9a8/8ppS6PWOty/aH3qeeeGkbfDs9WGfytv/73LsyOf/rsdyGoPPPYbcuefXP3c+3PO3XDB87vvi6+ASrUfnnl5zv8a+O/ccj3537je65xU993SOp6512xO/vrr3ExV8fcXnmYe2DYa28fpwTd6fjt8FY0ex6u3SMf/BuQs0aej8bWEwvkY/VFIPx/L4dq/Rcn3oecdrzdXj97ad8b1tp/Deluu768uvry60x/d7c6L3ey52dx078vnLGzvyTi7ohbtw2wSL5raES/GE1TumC8DcRbDJ+wBGlrWHrVu3wqo/dIGR90xXHxa+uQzao33r2/dDl5vvhunr0L78Nmj2i5bwDNm3PgMtf9EMblteD3qMxBi83T+yB9QrWwZlJ5Gf2iq4v9tIWJQTgyvg9ZTBsjHN4JeHPSPxz7aEXx5xGywrtA2al685snzJhjFNmkDLmxfp+pbBoptvgPYnhW2jmNB3dnwAPHsDOm6AZ37Tlj+haDLS7e8zcMOTc2DRulSMz90E0y88Fd78wyqOX/WHN+HUC8Mxzz4XhZsjy7drGm9MGK9bBHOepCcQGcOTb8rx+k0TPhZlz+qxo3N/vezzphm/gV+W3Q+ryI7nY6TfP1d7GdzWcSTcwLl4jb1zKl6HqWPeZjA8c91IOHW//WA/bLct1+3xjWq1h754Du6escnbnJ8IsXidLsStOKxJwrarmyPLV3Uab2AYL1+E5xMnfXw94NPRO01gbM41n8rBVq9JS35jkfuYkOcWwOciOs/7+ceTa1SrCfQYhNfXI/jc5G2x3/Wxpa7XqtocWb5d03hjwjg+juumw/kd34T73w6P1/P1Mcc5DfHNaLc3YQ0/v9PzML5SHFNP/Kl9dI9Deg0hr3vOfOa6uXp+5Tk263kF7xV6jq1X8hAMbiPxtEj7d3VzZPl2TeONCePd+NzHjdbXpVP7TN+uao4s327XGvaAsX8AfM8nr9HuugiNdjT/a3Th97acnIqdC12aVq3X8Mo0R5avIs1R8JMLNyvJ1FJ8oB92PLSh8f7HQ2eYAy+4WT7W79y0McfVbdwCt1JnNeTo1gQaUX6DxtBCZ4AbVr8JcG07aM3128Dx1wK8uWYj5stfGXaovXWrr2HpmNpQu3Zz+NVsLMt2ipA6X38tJ57+mrTmXYDrT2gt6211PFwPb8Jq2j7a+a6NoTHZ92/E2yD1KT+/OsqL4y34ujW0u3YULKK/YixbBKOupeOEHvdXGOr6WXKwh+1HewPc3/03wPR+tL+nwSi/nRKTjP8Q1szuDJ2OqsP2Okd1gs6z18CHuj2dD2wk9kZ4Llx9zs+vjvLivjOlHbnlNDwWdDyw/eRXUHbfrVDSgPzkbAGN9qf41XgsAEadqnGnjgKYjROz0o3wAj4JdO7UDupQvdbt8JrQ60bPwddrV+NVcj0cj9fZjh11ofsDH8OvW7v64bi1HvwxfPLJJ/Dxm/fCm7ye82E6/xVTz/8OvO67j4ZOcx+Wv5pyefLT9TwXfvUT3TZsp91yPcwfrNdpvL+7UB0Vjd8VSsd57i+b++NI5/n6P13Jz0d0vN15Tjz/yMlJ1eOTk1Ofdf/uMJnO88cfw58O+xU0p/WMcX8dp1qorX8N88vulvNPpVx98ue9XlPrqULqqGj8t66FjuPaNTC3W2c4nh/3deH4MzvD3L+vxjw+Oah1oF2nMphDX1EtXQNvdu0E7fj4F34cUvb1J7bh9Tdu2lnOc97nFb3esl7vsvaHlDevgH8XqaOi8d+6Zp37+0dDdzrfeD7n+vNJ55nO/YeYh0l8/Ol6wHP/Cr6PoOd1f53Qu4Xcc/+nq+R887nX9w2NDqRzT/Xp9TX33NP7HYrfmdfXjTPOh9PK5sPk7nULxn3X6qhofFXXut0n8/P2J5/8CVro68Rt7lMlukTwvNY561boPO9h/vSCzqO8n8T8tS/ge1t9P9qgHXQqk8e51KfIUXCaXjv8XrTsXhhdxc5nZdRR0fi0OgpOLmgWkk+XPXoRzLv1TKhbty7Uq3cEXDR7HsxdvEn8mE9vpjgeGz3gXB49WKWOTAqCHUdsx43jMLHzjeyl0+HCevXgngPfhs2b34YJXSlM8yP19anr7NqX+jjItGteHnWUF+fW2+bE6+DmF5bDsudvhutObJs8DtTz8bFd+uiAHct/z8d1zcWbcX/nw3XkjeI5n2OpDlvEr3XFR/EkUX1//Auro7y470rxDjBkPv8HLa5N6l5P/LRfbn/5uuoEE94IcZs3T4Lu+CLEUb4uxYX6lMvroSj2u7h0/cjesAQmYf35Q+bxixjbOYz8daFkYBmcMZa+fkU2ycvdtiuhbbruLlZHReN3ieJB7XQvPReEY3llG/XTtvs4HrFdT0SizsY1b/JfLevq8ws/nw2YwV81jOPaDMZ1vDEBOt36IiznGlyW/W3P6QRzhk6Hj3Dsn7fIn+96RWdVVUdF479txXvhx33q+YwSYnvdozpB2VMvwrJX5kDZme2grqub93HI2Rjj6lItOh5ZORnPK9gogb4yM2OAXk/1LuTJp9TLvg6rgjoqGv9tKx+n9Lk/q674sclxdvE4xntsr3c0nvt5i2D54rlQdsbx/MkEx2ece/qjBKVKdqhLRrHnnvuShhjHIa4uDShvE0zvT+edzv8FMGOd+JffVg+u3nErbB6c/H1fVVBHReN3H20DV+L5evveTvx+jO24n/J4rQfdLy6DM297Uc4j3si/fMrF+N72DD1/h8PFc+LXd8q+Dub76wDbAyX+eSX/duw+6qhofFod5f7mIrstgxdHd4Lxr2+EjRu1vT4e4OJHYBn6cR38IJNYOmuyUur6PsXxcIf8tWc0vgCwnWoDtGhcV0+kxEj/WhiITy471r0I8/g3cc6uMX5ddaFxc4Bbnl8m61r+ItwCLaAxvhDk2wY3ztccWb640ebwdrU6Hq4dPQ7GvdtJ1pvatqc+lO/oLXv+lmh7eGtCv8t4OLcV9nn73XamYji3ETTu8hTMWyzfDdy4eB481aUxNMI+bU/muSinObJ8u6Ql9iPd4mMix2LgFHfub4f69W/Ha6suHH9GJ3gK32jwb1TiY+pq86dpt8CLy6kOvTmoD/1m0jEN9TfO7Kf1KEYbuvl6xX7ieLe6AuaVDYSBmddq1W2OLF9VacnrupAPB+6aT+esmwFDLn4KrqW/VDboDhPdc9n93fHFYhncXt+df42nwvq4StTC3FvOmAcD8XnL29Lr2k2aI8u3S1qh44iP1074wv/iOhpvhBefego68V+RMcmdczw3A5vPg3FP4WT0aHmMlvc4lFXq2K8/3/NKvuutLnS/370+TuRJiKtfVa8NR5Zvl7RCx2k3O/fLbqsPL56wESbS+xdXvwo1R5Zvt2t8fvrhpC6y4amR6yN1ztKv0eW8t+Vz7N9r7JnNkeWrSHPknVwU5NWX4dYunaBdQx0TDdtBpy63wsuv6nhnaHMlrJzwFnRu0AAaNOgMb01YCVe2QXvDJvhm7ykYNHwWbNb6HDMcL5RrAN76x+ZkjFRj2g5eCePf64z1ML7TW3ixXAlt1ffd0BbaXfMUblnqOCFtT7wWYIxs28s4YfIc0ASjcR9vX4HHpB1cO3cQtKTtX9QExuOT2z/Wp2I89aHkD/OgxcCWXLPlwBYw7w8laK2OyLG4Vo9vfO7rd78FxoM7pjRVTdMWrsQnkrc6ob9BS4wcD7d0x6MYHfP63SfCvGv0OtQ2oalerxm0PXc85hpVBnddUGs1CFo8tTHPuZNrAfQxJfH/gIF5Hlf1uw/MuJ6Mb5WGJTDxqRYwqBWdH3y8HjYPJtLjNUXbE+kVIvd5eOfI/7xi7AJ2p3P/6h3QeQzArfy6ou2Xs9RpFB1+Pwl6bUhruXpg5vVBJF6ji/3ethqT9z/Rox8oGYHS0lL+j0Wqy3GpbvtrBOzcV1/2xHO/4nb5A0C+NxeGYOe++mLP+YajstcC5Rf8T/QMwzAMY/dlM8z6ZQPoPOZaGGhvLqsZdu4NY1dikwvDMAxjD4S+zkLfm7avL1U/7Nwbxq7EJheGYRiGYRiGYRQFm1wYhmEYhmEYhlEUbHJhGIZhGIZhGEZRsMmFYRiGYRiGYRhFIfOfov3pT38Ka9euVYtB7LXXXrD//vtXm+NS3fbXCNi5r77Yua++2Lmvvti5NxyVvRYo/7jjjsueXJSUlOjIqM7cjzejetIGb4ZhGIZhVC+K8fpvX4syDMMwDMMwDKMo2OTCMAzDMAzDMIyiYJMLwzAMwzAMwzCKgk0uDMMwDMMwDMMoCja5MAzDMAzDMAyjKNjkwjAMwzAMwzCMomCTC8MwDMMwDMMwioJNLgzDMAzDMAzDKAo2uTAMwzAMwzAMoyjY5MIwDMMwDMMwjKJgkwvDMAzDMAzDMIqCTS6+UxbDqBo1oEaijUKrsmRUsPeaAhvV7FH/qCU6JkqnQA9fK+UzAqXL4N4aF8FF3O6FZaVZ9vnwoZoTLJmv/otgvju+lNdrGXyuQ6MqsxIm1WgLbbldA0/7c/80XOPtkzAqi5B7zWNb1LYFnu7VFibZY223YOVN7hy7cxZfD65F14XHzv3uTu65J/I8HySwc79HkHiOx3aTPsvnsyewa6Ay2ORiF1AyZQOUlZVhewVGwlA47iaaXuDE49ih6tsAj0IfuOSxeHoh/jSLJ/eBWT0fhQ1Y75URAEOPjSYrhvI5LBs8EV7vOQDGlt0HQ0a8DhMH08Qgto+FAT1nw+ibcqcXHy6YDa2mjIWxU1rB7AXi/3DyRGgy+CioySOjKrPypv4wfsQkWFG2Ap6Zgo+RwU/jSwS+SAzGx9OUZ9i+Ah80/XuRPcmWxx6BVRwzCZr3no0vN8iS2TC0xSTofwyHGFWYLY9dA/1Bzv2KtSNh1e10jltCfxpre2ZKB+gwZQic3kiTFDv3uzfZ5z7f80ESO/d7CKXrYWHPkfCMe7wPa1nYHmHXQOWwycUu5VjogBMCeGs1bCxdDa9ht3XTBrhsAE1bAMx6YqH/9GLxTcfB0J4lUKJjYSOsfku7yLHDaMJyA1Y1KkZNOGrafXDfNJokfAKfTFdzeZQug2ffGgDt7Almt+BHB3fQntLiAKgD62D9dHxT2b6O2BodAB2mr0dreeCk5PZVMLJf7ouRUdXYAsufgHCuGp0OY6adjuc+ovRpGN27OfQ9N2HNg5373Yf85z77+aA87NzvjmxZvSrz/OazF8augZ3BJhe7lMWwcDhKi6bQoFFTaI3d11bTdEInDdNXw2oU+jrUccNHwiu396BRRAPoPXgkxvWBhvaVqALQJGIsDICJcHWNi2A0TgzG8oTC8Tks6zUaZo8YAvcNO0htgYM6doPXe18NV/cGGNDvIPvUYjejzrlj4JmDH+GPt0fDEP0r1Y/ggJ4LYeFL+jdL+ksWrIL1qa9I1Dm3LzTvfRrm9odVU7pBS/7LVd+cv3IbVZf1k6/xX39If51h5eSh0Hxxf8h6u2Dnfvcn69xnPx8ksXO/J0ATzIUAw/vrNeC+ApfPnsSugcphk4tdwKzeDfU3EsfBUMBJwzD6rOFYuGHxSPU1hJn+Mwr5OtTIxXk+kTjmBvkaVU/6ShTVtK9F5UKTh6thYgucPNDXolrgJCPxewn5BGMIvtRk/u7imDM5776yi+EocJ9afAjz9XcY9z5mv7youmzh78jym4iyFXyO2/LXn+rA6bfjxJxfPPAFZgHAIM1IEr5CM+bcdTAJH4SThmHjF6X4u7hG1YM+ncIp48Fy7lcsHgTjj41/W7MSVgwfBG3zfgJp5373Jd+5z/d8kMbO/e4PPsdPk3Mo10BzGNqYroF89jR2DVQGm1zsAsJvLlJfY+KJgth/02IWQM+m0HTJQpyA6MShcR9AK/eTn1I0gN7TMA8nJ+iFhfYJRgr5ylOrg+vyqO7BrQCmvwarUn+tYDv8Az7J/IGf4D61gMeelU86FtOnGi9n/xDcqAIkv/5Upz328U3HcjrH9FUJ9wLT7wBYBc3hgAJ/lZLv4HaDH2V9F9eogtCnUwDNm+qXH+irb/GnU0tWwPgRbTM/tUhj5353I9+5L/B8kAc793sI6ce/I589wq6BnccmF1UG/Zek9Mfd9HWpku4doEE04Shb+yh/njFycRncwH9ti3MANq6mX22UQFP72C5FXaiLLzSv/+0THn3yt9dx2QTqNtJPH/RH3Gzv2Rqa5zt+9luL3ZCsrz/RJEL+gum+KkFfj1lY8I3mSphd4e/mG1WDOnAkPoeOX6BvAfy5l+HKBeNhUMeKTC3s3O9+5Dv3+Z4PZJiLnfvdF3qOD1952vISnveeHeBIfu7Psss4F7sGvgk18E1rmfaZWbNmQUlJ8mfDRrGgycBx8NqUDTDzXPrhdgr6p2bdvwg14hUo469LRdA/O9u4D7T2kwskzkHoU5HM2t+A+/G2x0D/dGzjiUDTCoBWMGDtxXAUPZkk7N1gSNmZkPurC+HDmy6CVR3vgzP52NPEZDTMxh79S1IXn7tn/QKjDd72HOifFOwP47nfAUauHSPfm6V/jrAxTirITP9ySPrHvhH0T1o+cvAzMIZfYEK9DlOczaia0BuJ02Ao/2MN0bln+2iA2904P3bud1fynfs8zwcZ2LnfzYmf4/M999s1kEMxXv9tcmHkZY+aXBg7xZ41uTAMwzAMoyIU4/XfvhZlGIZhGIZhGEZRsMmFYRiGYRiGYRhFwSYXhmEYhmEYhmEUBZtcGIZhGIZhGIZRFGxyYRiGYRiGYRhGUbDJhWEYhmEYhmEYRcEmF4ZhGIZhGIZhFAWbXBiGYRiGYRiGURRscmEYhmEYhmEYRlGwyYVhGIZhGIZhGEXBJheGYRiGYRiGYRSFGmWI9plZs2ZBSUmJjozqzP14M6onbfBmGIZhVA9av/yV9ozqTo127bT3zbFPLgzDMAzDMAzDKAo2uTAMwzAMwzAMoyjY5MIwDMMwDMMwjKJgkwvDMAzDMAzDMIqCTS4MwzAMwzAMwygKNrkwDMMwDMMwDKMo2OTCMAzDMAzDMIyiYJMLwzAMwzAMwzCKgk0uDMMwDMMwDMMoCja5MAzDMAzDMAyjKNjkwjAMwzAMwzCMomCTi++MxTCqRg2ocdNiHRMbYUqvlK10CvSgOGq9pmCEEttrjMJqyJJRPB61hCOUrPVUdz6E+TUugosS7V5YVoqu0mVwr7fNx8gMlsz3efPdsaa8Xsvgcx0aVZuVN7WFtjWkTfKPl5UwSW1ta1wDT9P1kEOIueaxLWrbAk/3iusYVZnccx+fd9eyzr+d+90de9xXcz5eAGe3bw//5tqDb6sD3yk9GOyj3lFjgrdhlPrPfm6r2rbClOH54o0Ym1zsMmhi0RD6TNchg7bBfWDWiFegrOwVGDm9D1zyGE0vYnsZvDJiKBxHk4djOsBI9A5dEE0kliyEoSgjOx4rYwM5CM4suw/u4zYEupFpxKlwVKPPYdngifB6zwEwtmwsDOg5G0bflDu9+HDBbGg1ZSyMndIKZi8Q/4eTJ0KTwUdBTR4ZVZktj10D/WESrChbASvWjoRVtz+NbxPojUd/GD9C7M9MwcfRYLHHbHnsEVg15RmMmQTNe8/GtxzIktkwtMUk6H8MhxhVmOxz3xL601jbM1M6QIcpQ+D0Rpqk2LnfvbHHvQGbN8Csk4fD+pdegh3ULvwJmzc+NxSOhwlimzUcXp+6IPwhV9n43OPw+o2zMWYCtPrdPPmD7jvzoO9BE+CGIzjEKIBNLnYJbmJRAiU91USULoSZONmQicGx0GEEwKwnFmL0aliN9pKDm3JY04NLAIYvxItdYqQvLF7AUwvoYE+AmXz+2LMwG6cXQ4YdhKOacNQ0nHBMo0nCJ/BJYqJXgNJl8OxbA6CdHePdgC2w/Al8RPRrKcNGp8OYaadDHez+6OAOYnO0OIDthdkCT9++KtQzqjD5z72n9GkY3bs59D23/DNv5353wh73Br7T2vABwEENoYGOha2w8EWARzrJRAPqdYQZIzqmYrLYClOmfhDyjILY5GKXMRJeKRsHPXRUmKbQFCchs/62mker/zYLl6/B6lKcgnTkzy5gIX9UuxgWDsdJyJQBOO0wcvkQXu79OrSa0g5oahH4HJb1Gg2zRwyB+3jSkeSgjt3g9d5Xw9W9AQb0O8g+tdgNWT/5mpyvR9Q5dww8c/AjbBsNQ2DFsNw3DnXO7QvNe5+GMf1h1ZRu0JL/etk356/cRtUl69w7Vk4eCs0X94est4x27nd/7HFfnaFJxCKAiQP1609DYcrH6kJWPzW04NeiGpxyDrT6XTf0D4TXb+wMx/KnFudA73oaYBTEJhe7hAbQe9oNOzEBwPjbH4WS4cfxbyxue6tE7Uj81Sj+SlQJ9Ghf/hy8OiKfWrSC1u3T0wL5BGMIvtRk/u7imDP1K1UXw1HgPrUIv+O49zH75UXVZR2sn74QVh2MbyLo6xGLB8H4YyfBSvpLZC99c4F2Ovdte+V+PQKir9CMOXcdTMIH7aRh2PQNS/g+tlH1yHfuHSthxfBB0DbvJ5B27ndf7HFv1IbeI/TrUNTuPRT6ljwMi2E9rH5+EbzeaLDafwnDLiZ7mp/ADZo745T1MOpigL9cCBm/wzCysMnF7kKj3jCzrIx/czGuOxlaQ1P+K0r4atQo+kpUzx7Qwf66ksknf3sdj09raJ7n+NQ9uBUu/wGfZP7AT3CfWgBNVOiTjsX0qcbL2T8EN6oAP4IDegI0b6pffGh0AHSAVbC+lN58dIAO7cVepz328c3I8gLnXr6H3Q1+lPV9bKMKku/cyxCWrIDxI9pmfmqRxs797oY97o0U9RtCCXwAqz8+AJqeDNCqYe2UXYZZyO8vOkPTrN9hGJnY5KIq0agD9MAnRPmBtn7FqXsHaMC/0XD/etRGWPjELIARHfwnH+6rUUN9vJHLh7AKjw+0qBt9nUk/fdAfcZc3+bDfWuyO1IEj8TExfoG+FShdDwuhORzQiN58LISFL+lfIL1dhrmshNkV/m6+UTXId+5luHLBeBjUsSJTCzv3ux/2uDfoX3YKX4Xa+OYimHXyidChXm3ocMKJMGy5/stR9KNvOBSa5v2609sw8XeHwlWn6GTEqBA2uahSxF9/Og6G9nwUxp1LUwW1T+8DDWs0hD7wKGwYFn2pSr8ahVML+0pUObQ6uK72iIPgzLUDoNVw+jrURTB6eDcYwj/uzib+rUXNc0+FbpR3LP1LUunfcBhViTrnDoGRb/XnrzO0PXYVjFxL37GvA6dPo79A0veqY3s29C/M8HevsZ/zfWwJMaog2eee2ALr3+pQ4E1lwM797ok97qs7taH3ZSfCrBL5GtMBvwN45DL54XaDUwbDIx/qbzEu/gAemXV+3q+pL35Qf3OB/ZzfYUiIkUGNMvqeTcSsWbOgpCT6Tr9Rbbkfb0b1pA3eDMMwjOpB65e/0p5R3anRrp32vjn2yYVhGIZhGIZhGEXBJheGYRiGYRiGYRQFm1wYhmEYhmEYhlEUbHJhGIZhGIZhGEZRsMmFYRiGYRiGYRhFwSYXhmEYhmEYhmEUBZtcGIZhGIZhGIZRFGxyYRiGYRiGYRhGUbDJhWEYhmEYhmEYRcEmF4ZhGIZhGIZhFAWbXBiGYRiGYRiGURRqlCHaZ2bNmgUlJSU6MgzDMAzDMAzDqBj2yYVhGIZhGIZhGEXBJheGYRiGYRiGYRQFm1wYhmEYhmEYhlEUbHJhGIZhGIZhGEZRsMmFYRiGYRiGYRhFwSYXhmEYhmEYhmEUBZtcGIZhGIZhGIZRFGxyYRiGYRiGYRhGUbDJhWEYhmEYhmEYRcEmF4ZhGIZhGIZhFAWbXBiGYRiGYRiGURRscmEYhmEYhmEYRlGwyYVhGIZhGIZhGEXBJheGYRiGYRiGYRQFm1wYhmEYhmEYhlEUbHJhGIZhGIZhGEZRsMmFYRiGYRiGYRhFwSYXhmEYhmEYhmEUBZtcGIZhGIZhGIZRFGxyYRiGYRiGYRhGUbDJhWEYhmEYhmEYRcEmF4ZhGIZhGIZhFAWbXBiGYRiGYRiGURRscmEYhmEYhmEYRlGwyYVhGIZhGIZhGEXBJheGYRiGYRiGYRQFm1wYhmEYhmEYhlEUbHJhGIZhGIZhGEZRsMmFYRiGYRiGYRhFwSYXhmEYhmEYhmEUBZtcGIZhGIZhGIZRBAD+H2DXMzvfuYQlAAAAAElFTkSuQmCC\" alt=\"image\" width=\"791\" height=\"167\"\u003e\u003c/p\u003e\n\u003cp\u003eTools for SNP Validation and Verification It was crucial to accurately validate the variants following SNP identification, and additional in silico methods were employed for this purpose.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePROVEAN Scores\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe PROVEAN tool filters variant sequences to find nonsynonymous variants that are functionally significant (Table 5). Two SNPs were shown to be harmful and one to be neutral by the PROVEAN analysis. A score of \u0026le; -2.5 on PROVEAN represented a detrimental impact on an amino acid variation, whereas a score of \u0026gt; -2.5 suggested a neutral impact.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable (5) Prediction and scores generated by the PROVEAN tool\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariant\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePROVEAN Score\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrediction (Cutoff = 2.5)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eP94s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e5.333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eNeutral\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eI109V\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e-0.333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eNeutral\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003ePolyPhen-2\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, the variations at positions 94 (proline to serine), was determined to be most likely benign, with a 0.002 score (sensitivity: 0.99; specificity: 0.30). Additionally, with a score of 0.049 (sensitivity: 0.94; specificity: 0.83), the mutation at position 109 (isoleucine to valine) was determined to be benign. According to Figures 10 and 11, the variants categorised as benign had numerical values of 0 and 1.\u003c/p\u003e\n\u003cp\u003eShown are 75 amino acids surrounding the mutation position (marked with a black box)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eI-Mutant\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe I-Mutant method was used in the current investigation to ascertain whether the SNPs discovered would raise or lower the COX-3 protein\u0026apos;s stability (Table 6). The results demonstrated that the protein was more stable and that the SNPs (C\u0026rarr;T) that changed the amino acid from proline to serine had a free-energy value \u0026gt;-0.5 kcal/mol, indicating that they were mostly stable. The other transitional alteration (A\u0026rarr;G), on the other hand, changed the amino acid from isoleucine to valine. Its free-energy value was less than 0.5 kcal/mol, indicating that it was mostly unstable and that the protein\u0026apos;s stability had diminished.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6:\u0026nbsp;\u003c/strong\u003eProtein stability reports generated by I-Mutant.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.149532710280374%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePosition\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWild-Type\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eAmino Acid\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.339563862928348%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNew Amino Acid\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eafter Mutation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.682242990654206%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eStability\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.39563862928349%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eReliability\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eIndex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003epH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.35514018691589%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTemperature\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.149532710280374%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e94\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e109\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.339563862928348%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eS\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.682242990654206%\" valign=\"top\"\u003e\n \u003cp\u003eincreased\u003c/p\u003e\n \u003cp\u003edecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.39563862928349%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.411214953271028%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.35514018691589%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e25\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e25\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eMUpro\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results of this investigation for mutations located at positions 94 (P\u0026rarr;S) indicated that the protein\u0026apos;s stability was increased by the amino acid change. Although the protein stability decreased with mutation 109 (I\u0026rarr;V),\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSorting Intolerant from Tolerant (SIFT)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis method produced scores for the amino acid residue, with values ranging from 0 to 1. For SNPs, the cutoff value for tolerance was \u0026ge;0.05, and for tolerance, it was 0.05 or less. Because the change was tolerated, it was determined that the amino acid substitutions at positions 94 (proline to serine) and 109 (isoleucine to valine) affected the protein\u0026apos;s function. These modifications got a score of 1.01 in this investigation..\u003c/p\u003e\n\u003cp\u003eThe results summary\u0026nbsp;validated by different computational tools has been presented in the\u0026nbsp;Table 7.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 7.\u0026nbsp;\u003c/strong\u003eValidation of results obtained from different bioinformatical tools.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMutation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.423076923076923%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eProvean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePolyPhen-2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eI-mutant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.23076923076923%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMupro\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.923076923076923%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSIFT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP94S\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.423076923076923%\" valign=\"top\"\u003e\n \u003cp\u003eNeutral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003eBenign\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\" valign=\"top\"\u003e\n \u003cp\u003eIncreased\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.23076923076923%\" valign=\"top\"\u003e\n \u003cp\u003eIncrease stability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.923076923076923%\" valign=\"top\"\u003e\n \u003cp\u003eAffected protein function\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eI109V\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.423076923076923%\" valign=\"top\"\u003e\n \u003cp\u003eNeutral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.461538461538462%\" valign=\"top\"\u003e\n \u003cp\u003eBenign\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.5%\" valign=\"top\"\u003e\n \u003cp\u003eDecrease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.23076923076923%\" valign=\"top\"\u003e\n \u003cp\u003eDecrease stability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.923076923076923%\" valign=\"top\"\u003e\n \u003cp\u003eAffected protein function\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eP94S substitution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eReplacement of amino acids Proline in its natural state is a semi-conservative amino acid found in the coil region that is semi-sensitive to mutation, as shown in P94S (Fig. 12).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eI109V substitution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe natural amino acid, issoleucine, is a semi-conservative amino acid found in the Strand region with semi-sensitivity to mutation, as demonstrated by the amino acid replacement V109I (Fig. 13).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eGenetic diversity is a measure of species' capacity for evolution. Populations with higher genetic diversity are predicted to be more resilient to environmental changes than populations with lower genetic diversity. These changes include disease, invasive species, habitat loss, overharvesting, and climate change (Kardos, 2021). The 524 bp mtDNA COX-3 gene was analyzed in this work to determine the genetic diversity and inter-population relationships of dromedary camels obtained from three populations in Egypt. \u003c/p\u003e\n\u003cp\u003eAccording to the present findings, the camel COX-3 gene's promoter region has a high AT content (approximately 46.7% vs. 51.15%) and relatively scarce GC bases. These characteristics are similar to those of other camel κ-casein gene reports that have been published previously, (Pauciullo et al., 2013; Mutery et al., 2021), and they appear to be the same in other species (Beati et al., 2013). Furthermore, two polymorphisms (2 transitions) were found in COX-3\u003cs\u003e,\u003c/s\u003e which separated into two haplotypes (hap1 includes Baladi and Sudani populations with accession number OP994029, and hap2 includes Maghrebi populations with accession number OP994030). The haplotype diversity (0.667) and nucleotide diversity (0.00254) of the polymorphisms suggested that there were low variations across the types of dromedary camels as evidenced by the moderate to high very low nucleotide diversity (0.00254) and haplotype diversity (0.667). These variety indicators may indicate a markedly reduced selection pressure on camels relative to other animals that are farmed more intensively for a particular purpose (Alaqeely et al., 2021).\u003c/p\u003e\n\u003cp\u003eIn this study, two methodologies are typically used to detect the historical evolution of the population. The difference between pairs of sequences in the sample is analyzed using mismatch analysis, and the history of population growth is assumed to be represented by the distinct unimodal curve. The negative and notably differing Tajima's D and Fu's Fs values are seen as evidence of historical population increase. The Tajima's D and Fu's Fs values in this study were positive and did not reach statistical significance (P\u0026gt;0.1) which may point to a decline in the size of the population and/or balanced selection (Ming et al., 2021). These results agree with the low effective population size and decreased genetic variety found in wild Bactrian camels(Yadamsurenet al., 2012; Charruau, 2012). Taken together with the other two findings, it indicated that camel populations have stayed relatively steady and have not experienced population growth in the recent past. This is likely due to the population's resistance to the changes in living conditions, which will require more research to confirm.\u003c/p\u003e\n\u003cp\u003eIn BLASTN investigation of three Egyptian camel breeds (Baladi, Maghrebi, and Sudani) against a nucleotide database, functional annotation of COX-3 revealed height homology to the Arabian dromedary camel with the length of the gene was 524 bp (KX554934.1\u0026gt;100%), (Daloii et al., 2016), 489 bp of Camelus bactrianus (MH109977.1\u0026gt;93%) ( Ming et al., 2013), 436 bp of Lama glama (NC_012102.1\u0026gt;99%) (Westbury et al., 2016), 414bp of Bubalus bubalis (MT186736.1\u0026gt;80%) (Sun et al., 2020), 415 bp of Bos taurus (MN714218.1, \u0026gt;79%) (Xia et al., 2020).\u003c/p\u003e\n\u003cp\u003eThe phylogenetic analysis demonstrated that camel dromedaries belonged to a unique mitochondrial lineage with little genetic variation from other camel breeds. The results showed that the genetic distances between the Sudani and Baladi breeds (haplotype 1) were quite similar, which might be explained by their respective geographic positions. This could provide a plausible explanation for the observed high haplotype sharing rate amongst breeds. \u003c/p\u003e\n\u003cp\u003eAdditionally, the data showed that there is no pairwise genetic difference between the haplotypes of the Sudani and Baladi populations. The Baladi and Sudani breeds were declared to have the greatest genetic distance from each other, indicating a closer relationship and shared ancestry between the two breeds. The bootstrap value of 1000%, which serves as a baseline for assessing the phylogenetic tree's accuracy, is consistent with this finding (Dharmayant, 2011). These results are closely related to those of (Abdel-Aziem et al. (2022)), which reported that Maghrebi was divided into a single cluster, Baldi and Sudani breeds showed genetic diversity and resemblance. Many studies used molecular markers, such as microsatellites (Manee et al. 2019), microsatellites and start codon targeted (SCoT) markers (Al-soudy et al. 2018), mitochondrial ATP6 and ATP8 gene sequences (Li et al. 2017), or mitochondrial sequence variations (Ming et al. 2017; Ming et al. 2021) to estimate evolutionary relationships and genetic diversity as well as phylogenetic analyses between breeds.\u003c/p\u003e\n\u003cp\u003eThis result revealed that the variation in two DNA sequences of nucleotides at locations 280 (CCA / TCA) and 325 (ATT /GTT) determined to be SNPs that are not synonymous (nsSNPs), and so correlated with the conversion of proline into serine, an amino acid and (Isoleucine to Valine) at positions 94 and 109, respectively. It has been suggested that COX genes had the fewest nonsynonymous alterations, suggesting that the Camelus lineage placed a strong evolutionary pressure on them (Mohandesan et al., 2017). Since single-base variations in the amino acid sequence of the protein they encode are known as nonsynonymous single nucleotide polymorphisms (nsSNPs), they have been extensively researched. nsSNP variations are linked to disease by removing the original functionality of individual proteins, such as stability and enzyme active sites. The technology for genotyping and DNA sequencing has advanced quickly, leading to the discovery of millions of SNPs. While some harmful nsSNPs are known to be connected to complicated or hereditary disorders, the majority of nsSNPs are benign or neutral and have no effect on protein function (Gong et al., 2021).\u003c/p\u003e\n\u003cp\u003eIt is very important to predict and recognize important variants that have a negative impact about the structure and function of proteins utilising a range of computational techniques. However, because each algorithm uses a different set of parameters for prediction, the current in silico techniques have certain flaws in their ability to predict harmful nsSNPs. Therefore, single algorithms should not be taken into account for accurate prediction of harmful nsSNPs. Various methods with various parameters and characteristics must be implemented in order to accurately predict harmful nsSNPs. A dependable result can be produced by a consensus result achieved using the majority of the tools (Rozario et al., 2021). In silico technologies were employed to predict the effect of the identified SNPs in the structure and function of proteins. In this study, the I-Mutant and MUpro tools showed that P94S nsSNP showed increase in the COX-3 protein stability whereas I109V nsSNP was found to decrease the protein stability. Because each prediction tool utilizes method with different feature, it is expected to obtain dissimilar outcomes. However, all the tools used in the present investigation supplied enough proof of the neutral effect concerning the P94S and I109V nsSNPs. Therefore, these nsSNPs are considered to have a little influence on the protein function and may be not associated with diseases.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe results presented in this work are the first reported on the genetic structure combined with an in-silico study (which highlighted the polymorphism of nucleotide and protein mutations) for the Egyptian dromedary populations. The degree of polymorphism revealed by the COX-3 markers provides important information on the genetic structure of Egyptian camel populations. Furthermore, identified two nsSNPs of COX-3 showed neutral effect by using multiple in silico tools. These results offer a filtered data saving time, effort and cost that required before further validating using experimental analysis.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eEthics approval and consent to participate:\u003c/h2\u003e \u003cp\u003eThis study has been authorised by the Ethics of Medical Research Committee, National Research Centre, Al Buhouth St. Dokki \u0026ndash; Cairo, Egypt, number 12440723.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eThe Collection of Samples and\u003c/h2\u003e \u003cp\u003e \u003cb\u003eextracting DNA\u003c/b\u003e:\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003ePCR amplification and sequencing:\u003c/h2\u003e \u003cp\u003e35 cycles of denaturation at 95\u0026deg;C for 30s, annealing at 55\u0026deg;C for 30s, extension at 72\u0026deg;C for 45s, and final extension at 72\u0026deg;C for 7 minutes were used to carry out the amplification. The first denaturation was place at 95\u0026deg;C for 5 minutes. Using a DNA purification kit (ExoSap-IT, USB Corporation) and following the manufacturer's instructions, the amplified products were filtered to remove any remaining primers and dNTPs. The sequencing of the COX-3 amplified products was done in Macrogen Incorporation by using an automated DNA sequencer ABI 3730XL (Seoul, South Korea).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSequence data analysis:\u003c/strong\u003e \u003cp\u003eThe MEGA11.0 program's Clustal W method was used to align the COX-3 sequences from 90 examined camels with the GenBank-available Camelus sequence (Tamura et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Furthermore, MEGA11.0 was used to determine sequence composition and genetic differentiation. Moreover, ExPASy (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://web.expasy.org/translate\u003c/span\u003e\u003cspan address=\"http://web.expasy.org/translate\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was used to generate an analysis of the translated protein of the COX-3 gene sequences of the camels that were examined.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEstimation of genetic diversity:\u003c/strong\u003e \u003cp\u003ePolymorphic sites (S), number of haplotypes (H), haplotype diversity (Hd), nucleotide diversity (π), average number of nucleotide differences (K), and standard deviations (SD) were used to calculate the degree of genetic diversity using DNASP v5.10. These parameters were identified within and among all populations (Librado \u0026amp; Rozas, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eNeutrality tests\u003c/strong\u003e \u003cp\u003eThe neutrality tests, including Fu\u0026rsquo;s Fs (Fu, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1997\u003c/span\u003e) and Tajima\u0026rsquo;s D (Tajima, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1989\u003c/span\u003e). Tajima's D is negative, the population is growing (due to bottlenecks or selective sweeps), there is an excess of low-frequency polymorphisms compared to expectations, and purifying selection is taking place (Al-Jumaili et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Positive Tajima's D denotes low frequencies of high frequency polymorphisms, which could account for declining population size or counteract selection. Similarly, Tajima's D test is less potent than Fu's Fs test (Ramos-Onsins \u0026amp; Rozas, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003ePhylogenetic Analysis\u003c/strong\u003e \u003cp\u003eUsing MEGA X (version 2020), the neighbor-joining (NJ) tree for tested camel breed sequences and the phylogenetic tree connecting our camels to other camel breeds worldwide were built. Applications (Kumar et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Our camel's COX-3 sequences were compared to Camelus dromedaries' reference sequences: (Arabian camel), camelus bactrianus (Mongolian camel MH109977.1), Lama glama (South American camelidNC_012102.1), and other species as Bubalus bubalis (water buffaloMT186736.1) and Bos taurus (cattle MN714218.1), that were downloaded from the NCBI database.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003e3D Structure Prediction of COX 3 gene fragment\u003c/strong\u003e \u003cp\u003eThe 3D tertiary structure of COX-3 mDNA from camels reared in Egypt was predicted by software known as the Protein Homology Analogy Recognition Engine (Phyre2).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eIdentification Tools for SNP\u003c/strong\u003e \u003cp\u003eThe bioinformatics programmes NovelSNPer, BLASTn, BLASTx, and Bio-edit v 7.2.6 were used to analyse the sequencing data.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003ePrediction of the deleterious nsSNPs\u003c/strong\u003e \u003cp\u003eFour different in silico SNP prediction algorithms (PREDICT SNP, Sorting intolerance from tolerance (SIFT), polymorphism phenotyping v2 (PolyPhen-2), and protein variation effect analyzer (PROVEAN) were used to predict the deleterious effects of nsSNPs. Six prediction programmes were utilised in the development of the PredictSNP tool, a consensus SNP classifier (MAPP, PhD-SNP, PolyPhen-1, PolyPhen-2, SIFT and SNAP) to give a more reliable and alternate prediction. If the score falls between \u0026minus;\u0026thinsp;1 and 0, the mutations are considered neutral, and if the score falls between 0 and 1, they are considered detrimental. SIFT determine whether the function of proteins is affected in any way via an amino acid substitution. The SIFT method is based on sequence homology, and nsSNPs may be deleterious if the score is equivalent to or lower than 0.05. The PolyPhen-2 server is an evolutionary conservation system for sequences and structures that is focused on categorising the deleterious effects of amino acid change. It has a value between 0 (tolerable) and 1 (deleterious). The PROVEAN service finds nonsynonymous variants and returns a pairwise sequence alignment (PSA) score. An amino acid variant is considered to have a negative effect on protein function if its PROVEAN score is less than or equal to 2.5, while a variant with a value greater than or equal to 2.5 is considered to have a neutral effect.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eProtein stability prediction:\u003c/strong\u003e \u003cp\u003eThe MUpro and I-Mutant tools were utilised to predict modifications in the protein stability due to single-site mutations. MUpro predicts only whether or not the change will cause destabilization, without providing an actual ddG value while I-Mutant provides the ddG value(kcal/mol). I-Mutant 3.0 produces a DDG value based on the tertiary structure or protein sequence, which is predicted to be as follows: If ddG is less than or equal to 0.5 kcal/mol, it is mostly unstable; if ddG is greater than or equal to 0.5 kcal/mol, it is neutral.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eAccession numbers for nucleotide sequences:\u003c/strong\u003e \u003cp\u003eThe sequences produced from this investigation were deposited in GenBank with these numbers.\u003c/p\u003e \u003cp\u003eOP994029 and OP994030 with protein id\u0026thinsp;=\u0026thinsp;WHO17331.1 and WHO17330.1.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003ePolyPhen-2\u003c/h2\u003e \u003cp\u003eIn this study, the variations at positions 94 (proline to serine), was determined to be most likely benign, with a 0.002 score (sensitivity: 0.99; specificity: 0.30). Additionally, with a score of 0.049 (sensitivity: 0.94; specificity: 0.83), the mutation at position 109 (isoleucine to valine) was determined to be benign. According to Figs.\u0026nbsp;10 and 11, the variants categorised as benign had numerical values of 0 and 1.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eSekena H Abdel-Aziem and Othman E Othman. conceived of the presented idea. Sally S Alam. developed the theory and performed the computations. Dalia M Mabrouk and Heba A Abd El-Kader. verified the analytical methods. Sekena H Abdel-Aziem. encouraged Othman E Othman. to investigate [a specific aspect] and supervised the findings of this work. All authors discussed the results and contributed to the final manuscript\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAl Askar H, Alhajeri BH, Almathen F, Alhaddad H (2020) Genetic Diversity and Population Structure of Dromedary Camel-Types. J. 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Austrian Academy of Sciences Press, Wien (Austria). p. 45\u0026ndash;54 .\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Camelus dromedarius, COX-3 gene, Mitochondrial DNA, nonsynonymous SNP, homology","lastPublishedDoi":"10.21203/rs.3.rs-4032390/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4032390/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMaintaining genetic diversity among native Egyptian breeds is important towards genetic resource conservation. Examining the mitochondrial genome in different or within breeds can be helpful in determining the genetic variety of populations. This study examined the mitochondrial COX-3 gene of Egyptian Camelus dromedaries using bioinformatics and phylogenetic analysis, revealing two distinct haplotypes based on single nucleotide polymorphisms at positions 280 and 325. These two haplotypes' amplified PCR products were uploaded to GenBank/NCBI with accession numbers OP994029 and OP994030 with protein id\u0026thinsp;=\u0026thinsp;WHO17331.1\" and WHO17330.1, respectively. Comparison of nucleotide and amino acid sequences of the Egyptian camel populations' three-dimensional COX-3 structure showed how closely related these two haplotypes are genetically. Haplotype 1 was more predominant and found in Baldi and Sudani populations whereas haplotype 2 was more abundant in Maghrebi population. The two polymorphic sites have diversity and theta (per site): Theta (W: 0.00208); high variety of haplotypes (Hd: 0.667). These two haplotypes are the most genetically distant from camels in the Camelidae family, according to phylogenetic study. Based on the nucleotide sequences A\u0026thinsp;+\u0026thinsp;T and C\u0026thinsp;+\u0026thinsp;G have frequencies between 51.15% and 48.85%, respectively. The two non-synonymous SNPs caused the P94S amino acid substitution in the coiled region while I109V substitution located in the strand, which was neutral. Analysis of amino acid substitutions via protein prediction showed that the two amino acids were semi-conserved in which the resultant amino acid has different properties from the original amino acid and can affect the protein structure. The protein stability diminished according to the I-Mutant and MUpro tools. I109V nSNP and increased for P94S nSNP. This finding suggested that COX-3 gene variability in camels is important to preserve this genetic resource and creating future breeding programmes, conservation strategies that will increase camel production.\u003c/p\u003e","manuscriptTitle":"Genetic diversity among three camel populations reared in Egypt using mitochondrial COX-3 gene","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-12 08:56:15","doi":"10.21203/rs.3.rs-4032390/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c53ab4b9-c92f-4fcf-9e53-6a12d644bf12","owner":[],"postedDate":"March 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-20T07:16:06+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-12 08:56:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4032390","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4032390","identity":"rs-4032390","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}