Molecular characterization and phylogeny based on ITS2 and 28S regions of rDNA of Microphallus sp. (Digenea: Microphallidae) parasitic in freshwater crabs of Manipur, India

Molecular characterization and phylogeny based on ITS2 and 28S regions of rDNA of Microphallus sp. (Digenea: Microphallidae) parasitic in freshwater crabs of Manipur, India | 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 Molecular characterization and phylogeny based on ITS2 and 28S regions of rDNA of Microphallus sp. (Digenea: Microphallidae) parasitic in freshwater crabs of Manipur, India Voleentina Devi Athokpam, Lalit Mohan Goswami, Veena Tandon This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4064777/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Freshwater crabs ( Potamiscus manipuriensis ), commonly consumed as local delicacies by the native people in the state of Manipur, were found to harbour metacercariae of Microphallus sp. (Family Microphyllidae), which were morphologically different from metacercariae of Microphallus indicus reported earlier from a different host ( Barytelphusa lugubris mansoniana ) in Meghalaya, another state in Northeast India. So, PCR-based molecular characterization of this metacercaria was done utilizing rDNA marker regions: larger subunit (LSU) or 28S and inter-transcribed spacer 2 (ITS2). Sequence and phylogenetic analyses confirmed that the taxon under study belonged to family Microphyllidae. The ITS2 secondary structure data analyses also confirmed the primary sequence analysis. The analysis also revealed sequence differences in one hundred and nineteen bases (with 38 transitions, 35 transversions and 46 indels) with regard to 28S, though ITS2 showed sequence differences in 25 bases (10 transitions, 7 transversions and 8 indels) between the present microphallid and M. indicus . crabs Potamiscus manipuriensis metacercaria Microphallidae rDNA Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction The trematode flukes of the family Microphallidae Travassos, 1920, occur as intestinal parasites in all groups of vertebrates, mainly the birds and mammals (Martorelli et al. 2004 ; Deblock 2008 ). In their complex life cycle, crustaceans serve as second intermediate host harbouring encysted metacercarial larval form which is the infective form (Yamaguti 1975 ; Heard and Overstreet 1983 ; Pung et al. 2002 ; Diaz et al. 2004). Significant contributions have been made to study the life cycles of microphallid and also for their identification using traditional methods (Overstreet et al. 1992 ; Kostadinova et al. 2006 ; Guk et al. 2008 ; Chung et al. 2010 ; Diaz and Cremonte 2010 ; Lee et al. 2010 ; Goswami et al. 2013 ). With the advent of molecular tools and technique in the recent years that utilize various regions of trematode rDNA, molecularly characterization has been increasing utilized supplementing morphological studies (Hillis and Dixon 1991 ). Trematode has complex life cycle with different larval stages completing in different intermediate host. These techniques using DNA-based PCR-amplification are useful in characterization at all larval stages (Dzikowski et al. 2004 ). They have been successfully used for species characterization and interpreting phylogenetic inter-relationships between various microphallid taxa (Tkach et al. 2003 ; Hust et al. 2004 ; Al-Kandari and Al-Bustan 2010 ; Pina et al. 2011 ; Goswami et al. 2013 ). The commonly edible freshwater crab species in mountainous ranges of Manipur, Northeast India, are reported to be naturally infected with metacercariae representing the genera Paragonimus and Microphallus (Singh and Singh 1997 ; Singh 2002 , 2003 ; Singh et al. 2006 ; Athokpam and Tandon 2015 ). The objective of the present study was to molecularly characterize the Microphallus sp. occurring in freshwater crabs in the region using ITS2 and 28S marker sequences and to compare it molecularly with M. indicus Indian isolate earlier reported from the crab host, Barytelphusa lugubris mansoniana , in the northeastern region of India by Goswami et al. ( 2013 ). The ITS2 secondary structure data were also analysed, so as to corroborate the species characterization. Material and methods Sample collection and morphology study Metacercariae of Microphallus sp. were recovered from the muscle tissue of the crab host, Potamiscus manipuriensis by the artificial digestion technique, collected from susceptible foci of Manipur, Northeast India (Tandon et al. 2007; Athokpam and Tandon 2015). Morphological analysis was carried out following the standard procedure as described elsewhere (Athokpam and Tandon 2014). Molecular study DNA extraction, PCR amplification and Sequencing Genomic DNA extraction was done from the metacercariae separated from a single crab host using QIAamp DNA Mini Kit (50) followings manufacturer’s instructions. The rDNA ITS2 and 28S regions were PCR amplified using the primers – for ITS2: [3S (forward): 5’- GGTACCGGTGGATCACTCGGCTCGTG-3’ and A28 ( reverse ) : 5’- GGGATCCTGGTTAGTTTCTTTTCCTCCGC-3’] (Bowles et al ., 1995) and for 28S: [Dig12 (forward): 5’-AAGCATATCACTAAGCGG-3’ and 1500R (reverse): 3’-GCTATCCTGAGGGAAACTTC-5’] (Tkach et al. 2000). PCR amplification was carried out following the standard protocol of White (1993) with minor modifications. The amplified products were stained with ethidium bromide and examined on 1.6% agarose gel in TAE buffer. They were purified with Genei Pure Quick PCR Purification Kit (Bangalore, Karnataka, India) and sequenced in both directions using mentioned PCR primers by DNA sequencing services provided by Macrogen, Seoul, Korea. Sequence analysis Similarity search for the sequences generated during the study was done using Basic Local Alignment Search Tool (BLAST) available at http://www.ncbi.nlm.nih.go v/blast . The multiple sequence alignment of the sequences generated from the studied metacercaria, with related sequences from family Microphallidae retrieved from GenBank (Table 1), was done using ClustalW of Bioedit software ( http://www. ebi.ac.uk/clustalw ). Also, the sequence identity analysis was carried out using Bioedit version 7.0.9.0 (Hall 1999). Phylogenetic tree construction The rDNA ITS2 sequences of various microphallids were annotated using the hidden Markov models (HMM) (Keller et al. 2009) available at http://its2.bioapps.biozentrum.uni-wuerzburg.de/.Phylogenetic analyses were done based on the distance-based Neighbour Joining (NJ) method and character-based Maximum likelihood (ML) of MEGA11 and also profile neighbour-joining (PNJ) implemented in ProfDistS (Wolf et al. 2008; Tamura et al. 2021). In addition to the sequence data set used in the analysis, the Clinostomum sequence was included as the outgroup taxon. Bootstrapping analysis was done for all the phylogenetic trees constructed. ITS2 secondary structure analysis The secondary structures of these annotated ITS2 sequences were predicted using mfold webserver that utilizes minimum free energy folding algorithms, and the most stable structures with highest negative free energy were selected (Zuker 2003). The predicted secondary structures were aligned using 4SALE (Seibel et al. 2006), and the output file of sequence-structure alignment was save in .xfasta format. Then, the file was imported into ProfDistS 0.9.9 and allowed to run using PNJ implemented in ProfDistS, with GTR as selected correction number, 1,000 numbers of bootstraps and Q_ITS2 selected for Ratematrix Q. So, the data of ITS2 predicted secondary structures was also used for phylogenetic analysis to corroborate the tree construction with the primary data. Results Morphology and morphometry Based on the morphological analysis, the metacercaria was identified as belonging to genus Microphallus (Family: Microphallidae Ward, 1901) and is describe as follows. Description (based on 5 specimens, Fig. 1a, b): Encysted form rounded in shape, thin-walled, 0.55–0.83 mm in diameter. Most of the adult organs developed in metacercarial stage; excysted metacercaria having globular body; tegument spinous, density of spines decreasing from anterior to posterior end; oral sucker subterminal; ventral sucker single, post equatorial; prepharynx present; pharynx well developed, muscular; oesophagus long, medium sized; intestinal caeca short, divergent just anterior to ventral sucker; testes two, postovarian, symmetrical, on each lateral side of body; seminal vesicle ovoid, intercaecal; ovary dextral to ventral sucker; vitellaria in two groups, each having cluster of 6–7 on lateral side of body, posterior or lateral to each testis; excretory pore terminal. Morphometric measurements of various body parts of the mounted metacercaria are given in Table 2. Molecular study Molecular characterization and analysis The selected marker regions were amplified and the generated sequences were deposited in GenBank [Accession numbers: KF738448, KF738451]. The amplicon size of ITS2 and 28S was 395 bp and 1002 bp in length, respectively. They were then compared with various Microphallidae taxa (a total of 28 accession numbers) retrieved from GenBank for analysis (Table 1). The metacercaria under the present study stands close to Microphallus spp, with high sequence identities of 92.8% (ITS2) with M. indicus and 91.6% (28S) with M. calidris (Tables 3, 4). The query sequences, when compared with M. indicus Indian isolate, revealed 25 nucleotide differences (with 10 transitions, 7 transversions and 8 indels) and 119 nucleotide differences (with 38 transitions, 35 transversions and 46 indels) for ITS2 and 28S, respectively (Table 5). Phylogenetic analysis Phylogenetic trees were constructed using the ITS2 and 28S data of microphallid taxa available in GenBank (Table 1). The ML and NJ phylogenetic trees constructed for marker genes depicted the same topology of taxa with minor differences. In the analysis of ITS2 sequences, the NJ tree is shown with sum of branch length = 0.97763611 (Fig. 2a), which was drawn on scale, branch lengths in the same units with those of evolutionary distances used to infer the phylogenetic tree. The ML tree with the highest log likelihood (-1571.3102) is shown (Fig. 2b), which was drawn to scale, with branch lengths measured in the number of substitutions per site. Similarly, for 28S sequence, the NJ tree with sum of branch length = 0.67117473 (Fig. 3a) and ML tree with the highest log likelihood (-4108.0370) (Fig. 3b) are shown. All the trees revealed that the present microphallid fluke clades with M. indicus , with significant bootstrap values of 98-100% (Figs.2a, b and 3a, b). In all trees, the outgroup, genus Clinostomum , formed a seperate clade. ITS2 RNA secondary structures analysis The ITS2 secondary structure of the presently studied Microphallus sp. shows the typical four-helix model with helix I and IV being short; helix III- the longest and showing UGG motifs and helix II showing U-U mismatch (Fig. 4). The Profile neighbour joining (ProfDistS) analysis of the ITS2 secondary sequences also showed the same topology as that shown by the primary sequence analysis (Fig. 5), the present metacercaria Microphallus sp. clading with M. indicus with significant bootstrap value (91%). Discussion Ward ( 1901 ) created the genus Microphallus with Microphallus opacus (Ward 1894) as its type species from intestine of Amia calva . Many species of the genus have been reported from various definitive hosts such as birds, shrew and mammals – M. abortivus Deblock 1974; M. bittii Prevot 1973; M. breviatus Deblock and Maillard 1975; M. crociduri Mikhail and Fahmy 1968; M. forresteri Kinsella and Deblock 1997; M. fusiformis Reimer 1963; M. gracile Baer 1944; M. hoffmanni Rebecq 1964; M. kenyensis Canaris 1971; M. kinsellai Canaris and Beblock 2000; M. longicaecum Chen 1956; M. minus Ochi 1928; M. minutum Johnston 1948; M. montanus Beljakova and Kulkina 1998; M. oblonga Ching 1965; M. orientalis Yurakhno 1968; M. pearsoni Deblock and Canaris 1997 and M. oblongus Ching 1965 (see Yamaguti, 1971 ; Global Names Index, 2010 ). Various Microphallus spp at their larval stages have been reported from crustaceans and molluscan hosts; these are M. ovatus Osborn 1919; M. progeneticus Sogandares-Bernal 1962; M. pachygrapsi Deblock and Cable 1966; M. scolectroma Deblock and Tran Van Ky 1966; M. papillornatus Deblock and Pearson 1969; M. pisodonphidis Reimer and Szuks 1973; M. tauricus Stenko 1973; M. helicicola Belopolskaya and Soboleva 1977; M. pseudopygmaeus Galaktionov 1980; M. triangulatus Galaktionov 1980; M. piriformes Galaktionov 1983; M. paragrapsi Smith 1983; M. fonti Overstreet, Heard and Lotz 1992 ; M. selector Kinsella and Deblock 1997 and M. sabanensis Diaz, Bashirullah and Hernandez 2004 (Anantaraman and Subramoniam 1976 ; Jayasree et al. 2001 ; Goswami et al. 2013 ). In India, so far, only few microphallid taxa have been identified, namely: Levinseniella indica Lal 1936; Basantisia ramai Pande 1938; Pseudospeloterma indicum Murhar 1960; Mehraformes jabalpurensis Bharadwaj 1963; Spelotrema narii Rao 1965; Microphallus indicus Mukherjee and Ghosh 1967; Megalatriotrema hispidum Rao 1969 and S. chauhani Gupta and Jahan 1975 (Yamaguti 1971 ; Global Names Index, 2010 ; Goswami et al. 2013 ). A variety of molecular techniques have increasingly been utilized for various taxonomic issues related to describing new species or strains, supplementing traditional methods for characterizing based on their morphological studies (Thompson et al. 2004 ; Olson and Tkach 2005 ; Otachi et al. 2015 ). These techniques can be used even from the larval stages in addition to the adult stage of a taxon (Jousson et al. 1998 ; Rathinam et al. 2012 ; Chomchoei et al. 2022 ). In the present study, the microphallid metacercarial form harbouring the crab host Potamiscus manipuriensis was identified based on both morphometric and molecular analysis. Microphallid species show a high degree of similarity in morphology between their larval and adult stages due to the precocious development of reproductive organs. Based on morphological study, the present metacercarial form was found to belong to the family Microphallidae Ward, 1901 , possessing the typical morphological features of the genus Microphallus (Yamaguti 1971 ; Deblock 2008 ). In India, about eight species from the family have been reported as infecting various mammals, reptiles, amphibians and birds, with their infective metacercaria stage in crustacean host (Yamaguti 1971 ; Patterson et al. 2010; Goswami et al. 2013 ). For all these eight microphallids species reported so far, identification is based on morphological study alone, except for M. indicus , for which molecular characterization supplemented the morphology-based criteria (Goswami et al. 2013 ). Athokpam and Tandon ( 2015 ) had reported the microphallid species recovered from crabs in Manipur region to be morphologically differ with smaller morphological parameters from M. indicus earlier reported from Meghalaya, another state in Northeast India. In the present study, the sequence comparison revealed that the Microphallus sp. differs from M. indicus Indian isolate, with 25 nucleotide differences for ITS2, and 119 nucleotide differences for 28S regions, showing transition, transversion and indels. Tkach et al. ( 2003 ) studied phylogenetic interrelationships of Microphalloidea taxa (representing the families Lecithodendriidae, Microphallidae, Pleurogenidae and Prosthogonimidae) using partial 28S sequences. In the public domain, data on molecular characterization using rDNA tools with phylogenetic analysis for various microphallid species are available (Hust et al. 2004 ; Al-Kandari and Al-Bustan 2010 ; Pina et al. 2011 ). In phylogenetic analysis based on rDNA ITS2 and 28S regions, our query sequence claded close to M. indicus and within the Microphallidae taxa, thus supplementing the morphology study, which were also supported by sequence identity analysis. The high bootstrap values thus confirmed the placing of Microphallus sp. under study within Microphallidae family; a bootstrap value greater than 70% gives reliable clading in a phylogenetic tree (Hillis and Bull 1993 ). The ITS2 secondary structures include additional morphological information that are not found in the primary sequence and thus help in reconstructing the complete tree of life (Caetano-Anollés 2002 ; Grajales et al. 2007 ). A four-domain secondary structure model for ITS2 proposed by Michot et al ( 1993 ) boosts its value as a marker for megasystematics (Schultz et al. 2005 ). So, ITS2 region has high nucleotide mutation but their conserve nature of secondary structure has made them highly useful in various evolutionary studies (Coleman 2003 ). It is, therefore, necessary to consider both sequence and structure when calculating their alignments and in phylogenetic analysis (Keller et al. 2010 ). Hence, the ITS2 rDNA primary sequence and secondary structures have been utilized in many taxonomic studies including those on digenean taxa (Coleman 2007 ; Shylla et al. 2011 ; Ghatani et al. 2012 ; Athokpam and Tandon 2014 ). In the present study, Profile neighbour joining analysis of the secondary structure and sequence information of studied Microphallus sp. revealed the same topology as NJ and ML phylogenetic trees, clading with M. indicus with significant bootstrap value (91%), thus confirming the results of primary sequence analysis. On the basis of morphological study, supplemented with molecular characterization, the presently studied microphallid metacercarial parasite occurring in Potamiscus crabs in Manipur region is identified as belonging to the genus Microphallus Ward, 1901 . Limited data on the infection status of genus Microphallus are available in the public domain. So, more extensive works need to carry out to focus on finding possible intermediate hosts, completing their life cycle and for systematic analysis. Declarations Acknowledgments VDA acknowledges University Grants Commission (UGC), Government of India for awarding her ‘Research Fellowship in Science for Meritorious Students’ and Council of Scientific & Industrial Research (CSIR), Government of India, for Senior Research Fellowship. Funding This work was supported by Department of Information Technology, Government of India under the “North-East Parasite Information and Analysis Centre (NEPIAC)” sanctioned to VT et al. [Sanction no.: DIT/R&D/BIO/ 15(13)/2008 dated Sep. 29, 2008]. VDA was awarded University Grants Commission (UGC) ‘Research Fellowship in Science for Meritorious Students’ and Council of Scientific & Industrial Research (CSIR) ‘Senior Research Fellowship’. The authors declare that no funds or other support were received during the preparation of this manuscript. Conflict of Interest There is no conflict of interest. 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MolBiolEvol https://doi.org/10.1093/molbev/msab120 Tandon V, Prasad PK, Chatterjee A, Bhutia PT (2007) Surface fine topography and PCR-based determination of metacercaria of Paragonimus sp. from edible crabs in Arunachal Pradesh, Northeast India. Parasitol Res 102:21–28. DOI: 10.1007/s00436-007-0715-4 Thompson RCA, Zarlenga DS, La Rosa G, et al (2004) Advances in the diagnosis and systematics of parasites of veterinary importance: new and exciting prospects. In: Gasser RB, Zarlenga DS (Eds) Molecular systematics and diagnosis. Vet Parasitol 125:69–72 Tkach VV, Littlewood DTJ, Olson PD, Kinsella JM, Swiderski Z (2003) Molecular phylogenetic analysis of the Microphalloidea Ward, 1901 (Trematoda: Digenea). Sys Parasitol 56(1):1–15. DOI: 10.1023/A:1025546001611 Tkach VV, Pawlowski J, Sharpilo VP (2000) Molecular and morphological differentiation between species of the Plagiorchis vespertilionis group (Digenea, Plagiorchiidae) occurring in European bats, with a re-description of P. vespertilionis (Müller, 1780). Sys Parasitol 47:9–22. DOI: 10.1023/A:1006358524045 Ward HB (1901) Notes on the parasites of lake fish III. On the structure of the copulatory organs in Microphallus nov. gen. Trans Am Microsc Soc 22:175–187 White BA (1993) PCR Protocols, current methods and applications, vol. 15. Totowa, New Jersey, Humana press, USA Wolf M, Ruderisch B, Dandekar T, Schultz J, Müller T (2008) ProfDistS: (profile-) distance based phylogeny on sequence-structure alignments. Bioinformatics 24:2401–2402. DOI: 10.1093/bioinformatics/btn453 Yamaguti S (1971) Synopsis of the digenetic trematodes of vertebrates, Vol 1, II Keigaku Publishers, Tokyo Japan, pp. 1–1074 Yamaguti S (1975) A synoptic review of life histories of digenetic trematodes with special reference to the morphology of their larval forms. Keigaku Publishers, Tokyo Japan, pp. 1–590 Zuker M (2003) Mfold web server for nucleic acid folding and hybridization prediction. Nucleic Acids Res 31:3406–3415. DOI: 10.1093/nar/gkg595 Tables Table 1. Microphallidae taxa sequences of rDNA used in the analysis with their respective GenBank accession numbers Sl. No. Parasite name Locality Genes ITS2 28S 1. Microphallus indicus India: Meghalaya FJ966111.1 FJ966109.1 2. Microphallus abortivus UK HM584174.1 AY220626.1 3. Microphallus calidris Russia HM584183.1 HM584125.1 4. Microphallus pseudopygmaeus Russia HM584198.1 HM584126.1 5. Microphallus pygmaeus Iceland HM584190.1 HM584133.1 6. Microphallus similis Russia HM584178.1 HM584138.1 7. Microphallus piriformes Iceland HM584181.1 HM584122.1 8. Microphallus primas UK - AY220627.1 9. Microphallus triangulates Russia HM584196.1 HM584139.1 10. Microphallus fusiformis UK - - 11. Microphallus turgidus USA - - 12. Microphallus sp. Russia HM584188.1 HM584140.1 13. Microphallus sp. Russia HM584175.1 - 14. Maritrema subdolum Russia HM584172.1 AF151926.1 15. Maritrema oocysta UK HM584170.1 AY220630.1 16. Maritrema eroliae Kuwait HQ650132.1 JF826247.1 17. Maritrema neomi Ukraine - AF151927.1 18. Maritrema arenaria UK - AY220629.1 Table 2. Morphometric measurements of the excysted metacercaria of Microphallus sp. Characters Range (mm) Mean ± SD Body length 0.423 – 0.522 0.461 ± 0.042 Body width (maximum) 0.369 – 0.495 0.434 ± 0.052 Oral sucker (diameter) 0.048 – 0.054 0.050 ± 0.005 Prepharynx length 0.003 – 0.018 0.009 ± 0.008 Pharynx: Length 0.018 – 0.021 0.020 ± 0.010 Width 0.021 – 0.024 0.022 ± 0.011 Oesophagus 0.069 – 0.090 0.083 ± 0.043 Ventral sucker (diameter) 0.027 – 0.048 0.038 ± 0.009 Ovary: Length 0.048 – 0.087 0.070 ± 0.019 Width 0.036 – 0.063 0.052 ± 0.012 Left testis: Length 0.060 – 0.105 0.080 ± 0.019 Width 0.063 – 0.108 0.083 ± 0.019 Right testis: Length 0.051 – 0.087 0.070 ± 0.018 Width 0.060 – 0.099 0.072 ± 0.018 Table 5 . Difference in nucleotide positions between Microphallus sp. under study and M. indicus , Indian isolate. A) ITS2 B) 28S (Ts –Transition; Tv – Transversion; Indel – Insertion/Deletion; * - Query sequence) (a) ITS2 Sl. No. Base position Microphallus sp. * M. indicus Differences Sr. No. Base position Microphallus sp.* M. indicus Differences 1. 8 T A Tv 13. 315 T G Tv 2. 28 T C Ts 14. 316 - T Indel 3. 100 A T Tv 15. 317 - A Indel 4. 142 A G Ts 16. 318 - A Indel 5. 153 - C Indel 17. 319 - T Indel 6. 154 - C Indel 18. 320 - G Indel 7. 237 A G Ts 19. 333 A T Tv 8. 248 T G Tv 20. 334 A C Tv 9. 251 T G Tv 21. 357 G A Ts 10. 265 T C Ts 22. 400 A G Ts 11. 295 - T Indel 23. 402 A G Ts 12. 297 G A Ts 24. 410 A G Ts 25. 412 A G Ts (b) 28S Sl. No. Base position Microphallus sp.* M. indicus Differences Sr. No. Base position Microphallus sp.* M. indicus Differences 1. 5 G C Tv 61. 225 - C Indel 2. 10 A - Indel 62. 235 - G Indel 3. 11 C - Indel 63. 242 - T Indel 4. 12 C - Indel 64. 249 - C Indel 5. 18 G T Tv 65. 256 - A Indel 6. 22 G T Tv 66. 257 - G Indel 7. 25 T - Indel 67. 258 A G Ts 8. 26 G - Indel 68. 259 G C Tv 9. 27 T - Indel 69. 261 C T Ts 10. 28 T - Indel 70. 267 T G Tv 11. 29 T - Indel 71. 268 C T Ts 12. 30 G - Indel 72. 270 G C Tv 13. 43 A T Tv 73. 274 A G Ts 14. 45 A T Tv 74. 275 A G Ts 15. 47 T G Tv 75. 276 C T Ts 16. 52 G C Tv 76. 278 G A Ts 17. 53 G - Indel 77. 280 - C Indel 18. 54 T - Indel 78. 281 - A Indel 19. 55 A - Indel 79. 282 - A Indel 20. 56 A - Indel 80. 283 - C Indel 21. 64 C T Ts 81. 284 - C Indel 22. 67 A - Indel 82. 291 C T Ts 23. 68 G - Indel 83. 292 - C Indel 24. 70 C T Tv 84. 294 G A Ts 25. 76 A - Indel 85. 297 C T Ts 26. 82 A C Tv 86. 300 C T Ts 27. 83 C T Ts 87. 301 G C Tv 28. 92 T A Tv 88. 302 G A Ts 29. 101 A C Tv 89. 304 G A Ts 30. 102 G A Ts 90. 305 T G Tv 31. 103 T G Tv 91. 306 G A Ts 32. 104 A T Tv 92. 307 G T Tv 33. 105 C T Ts 93. 308 G A Ts 34. 106 C A Tv 94. 309 G A Ts 35. 107 G C Tv 95. 312 - T Indel 36. 114 A C Tv 96. 317 G C Tv 37. 119 T G Tv 97. 320 - T Indel 38. 124 A G Ts 98. 321 - G Indel 39. 131 T G Tv 99. 322 - C Indel 40. 134 - G Indel 100. 342 - C Indel 41. 139 A G Ts 101. 347 T C Ts 42. 140 G A Ts 102. 348 - T Indel 43. 147 C A Tv 103. 370 - C Indel 44. 148 A C Tv 104. 389 - C Indel 45. 149 G A Ts 105. 406 - C Indel 46. 154 - G Indel 106. 411 C T Ts 47. 157 A C Tv 107. 441 T C Ts 48. 169 G A Ts 108. 442 T C Ts 49. 171 - G Indel 109. 443 C T Ts 50. 172 - T Indel 110. 444 - C Indel 51. 176 A C Tv 111. 454 T C Ts 52. 186 T G Tv 112. 494 - G Indel 53. 188 G T Tv 113. 515 A G Ts 54. 189 A G Ts 114. 822 C G Tv 55. 194 - G Indel 115. 825 A G Ts 56. 198 A C Tv 116. 877 C T Ts 57. 215 - T Indel 117. 888 T C Ts 58. 222 C G Tv 118. 947 T C Ts 59. 223 G C Tv 119. 949 T C Ts 60. 224 - G Indel Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 09 Apr, 2024 Editor invited by journal 01 Apr, 2024 Reviewers invited by journal 21 Mar, 2024 Editor assigned by journal 16 Mar, 2024 First submitted to journal 15 Mar, 2024 Editorial decision: Minor revisions needed 12 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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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-4064777","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":282339367,"identity":"aec4c200-4482-452b-a32d-e45c71f5c5d0","order_by":0,"name":"Voleentina Devi Athokpam","email":"data:image/png;base64,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","orcid":"https://orcid.org/0009-0000-1396-1271","institution":"G P Women's College","correspondingAuthor":true,"prefix":"","firstName":"Voleentina","middleName":"Devi","lastName":"Athokpam","suffix":""},{"id":282339368,"identity":"23043feb-424f-4164-a276-7f27d4bbd840","order_by":1,"name":"Lalit Mohan Goswami","email":"","orcid":"","institution":"Nowgong College","correspondingAuthor":false,"prefix":"","firstName":"Lalit","middleName":"Mohan","lastName":"Goswami","suffix":""},{"id":282339369,"identity":"0905b6ca-822c-425a-874f-c8b7475553f9","order_by":2,"name":"Veena Tandon","email":"","orcid":"","institution":"NASI, lucknow","correspondingAuthor":false,"prefix":"","firstName":"Veena","middleName":"","lastName":"Tandon","suffix":""}],"badges":[],"createdAt":"2024-03-10 11:54:49","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4064777/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4064777/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53388299,"identity":"6e3615e2-bb75-463e-9975-1adcbe2b9113","added_by":"auto","created_at":"2024-03-25 11:48:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1183426,"visible":true,"origin":"","legend":"\u003cp\u003eLight microscopy of the microphallid metacercaria.\u003c/p\u003e\n\u003cp\u003ea. Encysted metacercaria,\u003c/p\u003e\n\u003cp\u003eb. Line drawing of excysted metacercaria (camera lucida)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4064777/v1/b7bd806a318cc5da720d5d83.png"},{"id":53388995,"identity":"6c515a1b-e187-42cc-a014-3ce1a1bdc93b","added_by":"auto","created_at":"2024-03-25 11:56:25","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":238449,"visible":true,"origin":"","legend":"\u003cp\u003ePhylogenetic trees depicting the relationship between various microphallid taxa based on rDNA ITS2 sequence data. The numbers indicate the bootstrap values. (a) NJ tree, (b) ML tree\u003c/p\u003e\n\u003cp\u003e(*Query sequence generated during the study)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4064777/v1/dfb0ea30e9f7814f370226b6.png"},{"id":53388297,"identity":"c06a16f0-7137-46a1-8fa6-8a2132151d41","added_by":"auto","created_at":"2024-03-25 11:48:25","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":256411,"visible":true,"origin":"","legend":"\u003cp\u003ePhylogenetic trees depicting the relationship between various microphallid taxa based on 28S marker. The numbers indicate the bootstrap values. (a) NJ tree, (b) ML tree\u003c/p\u003e\n\u003cp\u003e(*Query sequence generated during the study)\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4064777/v1/76a154bb3189102d8f326f3f.png"},{"id":53388298,"identity":"a436bcfe-6ecc-46ba-9b25-5bdee960c4d8","added_by":"auto","created_at":"2024-03-25 11:48:25","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":631810,"visible":true,"origin":"","legend":"\u003cp\u003eInferred ITS2 secondary structure of \u003cem\u003eMicrophallus\u003c/em\u003esp. showing four-helix model\u003c/p\u003e\n\u003cp\u003e(dG = -93.50kcal/mol)\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4064777/v1/4033ae5228c5c5da1e9e28f8.png"},{"id":53388301,"identity":"57d3311d-7d17-4e3a-9d48-8de9455e4660","added_by":"auto","created_at":"2024-03-25 11:48:25","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":160329,"visible":true,"origin":"","legend":"\u003cp\u003ePhylogenetic tree depicting relationship between various microphallid based on ProfDistS of ITS2 region. (*Query sequence generated during the study)\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4064777/v1/ffa3caa70a7af1d83df45904.png"},{"id":53389483,"identity":"c6fd1f5a-db7c-421f-b2f7-74a5cd4a10e9","added_by":"auto","created_at":"2024-03-25 12:04:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2590162,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4064777/v1/548b6993-ebac-4895-9cc3-b64811c792c1.pdf"}],"financialInterests":"","formattedTitle":"Molecular characterization and phylogeny based on ITS2 and 28S regions of rDNA of Microphallus sp. (Digenea: Microphallidae) parasitic in freshwater crabs of Manipur, India","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe trematode flukes of the family Microphallidae Travassos, 1920, occur as intestinal parasites in all groups of vertebrates, mainly the birds and mammals (Martorelli et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Deblock \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). In their complex life cycle, crustaceans serve as second intermediate host harbouring encysted metacercarial larval form which is the infective form (Yamaguti \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e1975\u003c/span\u003e; Heard and Overstreet \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1983\u003c/span\u003e; Pung et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Diaz et al. 2004). Significant contributions have been made to study the life cycles of microphallid and also for their identification using traditional methods (Overstreet et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Kostadinova et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Guk et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Chung et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Diaz and Cremonte \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Lee et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Goswami et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWith the advent of molecular tools and technique in the recent years that utilize various regions of trematode rDNA, molecularly characterization has been increasing utilized supplementing morphological studies (Hillis and Dixon \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). Trematode has complex life cycle with different larval stages completing in different intermediate host. These techniques using DNA-based PCR-amplification are useful in characterization at all larval stages (Dzikowski et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). They have been successfully used for species characterization and interpreting phylogenetic inter-relationships between various microphallid taxa (Tkach et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Hust et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Al-Kandari and Al-Bustan \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Pina et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Goswami et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe commonly edible freshwater crab species in mountainous ranges of Manipur, Northeast India, are reported to be naturally infected with metacercariae representing the genera \u003cem\u003eParagonimus\u003c/em\u003e and \u003cem\u003eMicrophallus\u003c/em\u003e (Singh and Singh \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Singh \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2002\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Singh et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Athokpam and Tandon \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The objective of the present study was to molecularly characterize the \u003cem\u003eMicrophallus\u003c/em\u003e sp. occurring in freshwater crabs in the region using ITS2 and 28S marker sequences and to compare it molecularly with \u003cem\u003eM. indicus\u003c/em\u003e Indian isolate earlier reported from the crab host, \u003cem\u003eBarytelphusa lugubris mansoniana\u003c/em\u003e, in the northeastern region of India by Goswami et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The ITS2 secondary structure data were also analysed, so as to corroborate the species characterization.\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSample collection and morphology study\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMetacercariae of \u003cem\u003eMicrophallus \u003c/em\u003esp. were recovered from the muscle tissue of the crab host, \u003cem\u003ePotamiscus manipuriensis\u003c/em\u003e by the artificial digestion technique, collected from susceptible foci of Manipur, Northeast India (Tandon et al. 2007; Athokpam and Tandon 2015). \u003c/p\u003e\n\u003cp\u003eMorphological analysis was carried out following the standard procedure as described elsewhere (Athokpam and Tandon 2014).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMolecular study\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDNA extraction, PCR amplification and Sequencing\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eGenomic DNA extraction was done from the metacercariae separated from a single crab host using QIAamp DNA Mini Kit (50) followings manufacturer\u0026rsquo;s instructions. The rDNA ITS2 and 28S regions were PCR amplified using the primers \u0026ndash; for ITS2: [3S (forward): 5\u0026rsquo;- GGTACCGGTGGATCACTCGGCTCGTG-3\u0026rsquo; and A28\u003cstrong\u003e (\u003c/strong\u003ereverse\u003cstrong\u003e)\u003c/strong\u003e: 5\u0026rsquo;- GGGATCCTGGTTAGTTTCTTTTCCTCCGC-3\u0026rsquo;] (Bowles \u003cem\u003eet al\u003c/em\u003e., 1995) and for 28S: [Dig12 (forward): 5\u0026rsquo;-AAGCATATCACTAAGCGG-3\u0026rsquo; and 1500R (reverse): 3\u0026rsquo;-GCTATCCTGAGGGAAACTTC-5\u0026rsquo;] (Tkach et al. 2000). PCR amplification was carried out following the standard protocol of White (1993) with minor modifications. The amplified products were stained with ethidium bromide and examined on 1.6% agarose gel in TAE buffer. They were purified with Genei Pure Quick PCR Purification Kit (Bangalore, Karnataka, India) and sequenced in both directions using mentioned PCR primers by DNA sequencing services provided by Macrogen, Seoul, Korea. \u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSequence analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eSimilarity search for the sequences generated during the study was done using Basic Local Alignment Search Tool (BLAST) available at \u003cu\u003ehttp://www.ncbi.nlm.nih.go v/blast\u003c/u\u003e. The multiple sequence alignment of the sequences generated from the studied metacercaria, with related sequences from family Microphallidae retrieved from GenBank (Table 1), was done using ClustalW of Bioedit software (\u003cu\u003ehttp://www. ebi.ac.uk/clustalw\u003c/u\u003e). Also, the sequence identity analysis was carried out using Bioedit version 7.0.9.0 (Hall 1999). \u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePhylogenetic tree construction\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe rDNA ITS2 sequences of various microphallids were annotated using the hidden Markov models (HMM) (Keller et al. 2009) available at http://its2.bioapps.biozentrum.uni-wuerzburg.de/.Phylogenetic analyses were done based on the distance-based Neighbour Joining (NJ) method and character-based Maximum likelihood (ML) of MEGA11 and also profile neighbour-joining (PNJ) implemented in ProfDistS (Wolf et al. 2008; Tamura et al. 2021). In addition to the sequence data set used in the analysis, the \u003cem\u003eClinostomum\u003c/em\u003e sequence was included as the outgroup taxon. Bootstrapping analysis was done for all the phylogenetic trees constructed. \u003c/p\u003e\n\u003cp\u003e\u003cem\u003eITS2 secondary structure analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe secondary structures of these annotated ITS2 sequences were predicted using mfold webserver that utilizes minimum free energy folding algorithms, and the most stable structures with highest negative free energy were selected (Zuker 2003). The predicted secondary structures were aligned using 4SALE (Seibel et al. 2006), and the output file of sequence-structure alignment was save in .xfasta format. Then, the file was imported into ProfDistS 0.9.9 and allowed to run using PNJ implemented in ProfDistS, with GTR as selected correction number, 1,000 numbers of bootstraps and Q_ITS2 selected for Ratematrix Q. So, the data of ITS2 predicted secondary structures was also used for phylogenetic analysis to corroborate the tree construction with the primary data.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMorphology and morphometry\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on the morphological analysis, the metacercaria was identified as belonging to genus \u003cem\u003eMicrophallus \u003c/em\u003e(Family: Microphallidae Ward, 1901) and is describe as follows.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDescription\u003c/em\u003e (based on 5 specimens, Fig. 1a, b): Encysted form rounded in shape, thin-walled, 0.55\u0026ndash;0.83 mm in diameter. Most of the adult organs developed in metacercarial stage; excysted metacercaria having globular body; tegument spinous, density of spines decreasing from anterior to posterior end; oral sucker subterminal; ventral sucker single, post equatorial; prepharynx present; pharynx well developed, muscular; oesophagus long, medium sized; intestinal caeca short, divergent just anterior to ventral sucker; testes two, postovarian, symmetrical, on each lateral side of body; seminal vesicle ovoid, intercaecal; ovary dextral to ventral sucker; vitellaria in two groups, each having cluster of 6\u0026ndash;7 on lateral side of body, posterior or lateral to each testis; excretory pore terminal.\u003c/p\u003e\n\u003cp\u003eMorphometric measurements of various body parts of the mounted metacercaria are given in Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMolecular study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMolecular characterization and analysis \u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe selected marker regions were amplified and the generated sequences were deposited in GenBank [Accession numbers: KF738448, KF738451]. The amplicon size of ITS2 and 28S was 395 bp and 1002 bp in length, respectively. They were then compared with various Microphallidae taxa (a total of 28 accession numbers) retrieved from GenBank for analysis (Table 1). The metacercaria under the present study stands close to \u003cem\u003eMicrophallus \u003c/em\u003espp, with high sequence identities of 92.8% (ITS2) with \u003cem\u003eM. indicus\u003c/em\u003e and 91.6% (28S) with \u003cem\u003eM. calidris\u003c/em\u003e (Tables 3, 4). The query sequences, when compared with \u003cem\u003eM. indicus\u003c/em\u003e Indian isolate, revealed 25 nucleotide differences (with 10 transitions, 7 transversions and 8 indels) and 119 nucleotide differences (with 38 transitions, 35 transversions and 46 indels) for ITS2 and 28S, respectively (Table 5). \u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePhylogenetic analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e \u003c/em\u003ePhylogenetic trees were constructed using the ITS2 and 28S data of microphallid taxa available in GenBank (Table 1). The ML and NJ phylogenetic trees constructed for marker genes depicted the same topology of taxa with minor differences. In the analysis of ITS2 sequences, the NJ tree is shown with sum of branch length = 0.97763611 (Fig. 2a), which was drawn on scale, branch lengths in the same units with those of evolutionary distances used to infer the phylogenetic tree. The ML tree with the highest log likelihood (-1571.3102) is shown (Fig. 2b), which was drawn to scale, with branch lengths measured in the number of substitutions per site. Similarly, for 28S sequence, the NJ tree with sum of branch length = 0.67117473 (Fig. 3a) and ML tree with the highest log likelihood (-4108.0370) (Fig. 3b) are shown. All the trees revealed that the present microphallid fluke clades with \u003cem\u003eM. indicus\u003c/em\u003e, with significant bootstrap values of 98-100% (Figs.2a, b and 3a, b). In all trees, the outgroup, genus \u003cem\u003eClinostomum\u003c/em\u003e, formed a seperate clade.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eITS2 RNA secondary structures analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe ITS2 secondary structure of the presently studied \u003cem\u003eMicrophallus\u003c/em\u003e sp. shows the typical four-helix model with helix I and IV being short; helix III- the longest and showing UGG motifs and helix II showing U-U mismatch (Fig. 4). The Profile neighbour joining (ProfDistS) analysis of the ITS2 secondary sequences also showed the same topology as that shown by the primary sequence analysis (Fig. 5), the present metacercaria \u003cem\u003eMicrophallus \u003c/em\u003esp. clading with \u003cem\u003eM. indicus\u003c/em\u003e with significant bootstrap value (91%). \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eWard (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e1901\u003c/span\u003e) created the genus \u003cem\u003eMicrophallus\u003c/em\u003e with \u003cem\u003eMicrophallus opacus\u003c/em\u003e (Ward 1894) as its type species from intestine of \u003cem\u003eAmia calva\u003c/em\u003e. Many species of the genus have been reported from various definitive hosts such as birds, shrew and mammals \u0026ndash; \u003cem\u003eM. abortivus\u003c/em\u003e Deblock 1974; \u003cem\u003eM. bittii\u003c/em\u003e Prevot 1973; \u003cem\u003eM. breviatus\u003c/em\u003e Deblock and Maillard 1975; \u003cem\u003eM. crociduri\u003c/em\u003e Mikhail and Fahmy 1968; \u003cem\u003eM. forresteri\u003c/em\u003e Kinsella and Deblock 1997; \u003cem\u003eM. fusiformis\u003c/em\u003e Reimer 1963; \u003cem\u003eM. gracile\u003c/em\u003e Baer 1944; \u003cem\u003eM. hoffmanni\u003c/em\u003e Rebecq 1964; \u003cem\u003eM. kenyensis\u003c/em\u003e Canaris 1971; \u003cem\u003eM. kinsellai\u003c/em\u003e Canaris and Beblock 2000; \u003cem\u003eM. longicaecum\u003c/em\u003e Chen 1956; \u003cem\u003eM. minus\u003c/em\u003e Ochi 1928; \u003cem\u003eM. minutum\u003c/em\u003e Johnston 1948; \u003cem\u003eM. montanus\u003c/em\u003e Beljakova and Kulkina 1998; \u003cem\u003eM. oblonga\u003c/em\u003e Ching 1965; \u003cem\u003eM. orientalis\u003c/em\u003e Yurakhno 1968; \u003cem\u003eM. pearsoni\u003c/em\u003e Deblock and Canaris 1997 and \u003cem\u003eM. oblongus\u003c/em\u003e Ching 1965 (see Yamaguti, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e1971\u003c/span\u003e; Global Names Index, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003eVarious \u003cem\u003eMicrophallus\u003c/em\u003e spp at their larval stages have been reported from crustaceans and molluscan hosts; these are \u003cem\u003eM. ovatus\u003c/em\u003e Osborn 1919; \u003cem\u003eM. progeneticus\u003c/em\u003e Sogandares-Bernal 1962; \u003cem\u003eM. pachygrapsi\u003c/em\u003e Deblock and Cable 1966; \u003cem\u003eM. scolectroma\u003c/em\u003e Deblock and Tran Van Ky 1966; \u003cem\u003eM. papillornatus\u003c/em\u003e Deblock and Pearson 1969; \u003cem\u003eM. pisodonphidis\u003c/em\u003e Reimer and Szuks 1973; \u003cem\u003eM. tauricus\u003c/em\u003e Stenko 1973; \u003cem\u003eM. helicicola\u003c/em\u003e Belopolskaya and Soboleva 1977; \u003cem\u003eM. pseudopygmaeus\u003c/em\u003e Galaktionov 1980; \u003cem\u003eM. triangulatus\u003c/em\u003e Galaktionov 1980; \u003cem\u003eM. piriformes\u003c/em\u003e Galaktionov 1983; \u003cem\u003eM. paragrapsi\u003c/em\u003e Smith 1983; \u003cem\u003eM. fonti\u003c/em\u003e Overstreet, Heard and Lotz \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; M. \u003cem\u003eselector\u003c/em\u003e Kinsella and Deblock 1997 and \u003cem\u003eM. sabanensis\u003c/em\u003e Diaz, Bashirullah and Hernandez 2004 (Anantaraman and Subramoniam \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1976\u003c/span\u003e; Jayasree et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Goswami et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In India, so far, only few microphallid taxa have been identified, namely: \u003cem\u003eLevinseniella indica\u003c/em\u003e Lal 1936; \u003cem\u003eBasantisia ramai\u003c/em\u003e Pande 1938; \u003cem\u003ePseudospeloterma indicum\u003c/em\u003e Murhar 1960; \u003cem\u003eMehraformes jabalpurensis\u003c/em\u003e Bharadwaj 1963; \u003cem\u003eSpelotrema narii\u003c/em\u003e Rao 1965; \u003cem\u003eMicrophallus indicus\u003c/em\u003e Mukherjee and Ghosh 1967; \u003cem\u003eMegalatriotrema hispidum\u003c/em\u003e Rao 1969 and \u003cem\u003eS. chauhani\u003c/em\u003e Gupta and Jahan 1975 (Yamaguti \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e1971\u003c/span\u003e; Global Names Index, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Goswami et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA variety of molecular techniques have increasingly been utilized for various taxonomic issues related to describing new species or strains, supplementing traditional methods for characterizing based on their morphological studies (Thompson et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Olson and Tkach \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Otachi et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). These techniques can be used even from the larval stages in addition to the adult stage of a taxon (Jousson et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Rathinam et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Chomchoei et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In the present study, the microphallid metacercarial form harbouring the crab host \u003cem\u003ePotamiscus manipuriensis\u003c/em\u003e was identified based on both morphometric and molecular analysis.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eMicrophallid species show a high degree of similarity in morphology between their larval and adult stages due to the precocious development of reproductive organs. Based on morphological study, the present metacercarial form was found to belong to the family Microphallidae Ward, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e1901\u003c/span\u003e, possessing the typical morphological features of the genus \u003cem\u003eMicrophallus\u003c/em\u003e (Yamaguti \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e1971\u003c/span\u003e; Deblock \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). In India, about eight species from the family have been reported as infecting various mammals, reptiles, amphibians and birds, with their infective metacercaria stage in crustacean host (Yamaguti \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e1971\u003c/span\u003e; Patterson et al. 2010; Goswami et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). For all these eight microphallids species reported so far, identification is based on morphological study alone, except for \u003cem\u003eM. indicus\u003c/em\u003e, for which molecular characterization supplemented the morphology-based criteria (Goswami et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Athokpam and Tandon (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) had reported the microphallid species recovered from crabs in Manipur region to be morphologically differ with smaller morphological parameters from \u003cem\u003eM. indicus\u003c/em\u003e earlier reported from Meghalaya, another state in Northeast India. In the present study, the sequence comparison revealed that the \u003cem\u003eMicrophallus\u003c/em\u003e sp. differs from \u003cem\u003eM. indicus\u003c/em\u003e Indian isolate, with 25 nucleotide differences for ITS2, and 119 nucleotide differences for 28S regions, showing transition, transversion and indels.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eTkach et al. (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) studied phylogenetic interrelationships of Microphalloidea taxa (representing the families Lecithodendriidae, Microphallidae, Pleurogenidae and Prosthogonimidae) using partial 28S sequences. In the public domain, data on molecular characterization using rDNA tools with phylogenetic analysis for various microphallid species are available (Hust et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Al-Kandari and Al-Bustan \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Pina et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). In phylogenetic analysis based on rDNA ITS2 and 28S regions, our query sequence claded close to \u003cem\u003eM. indicus\u003c/em\u003e and within the Microphallidae taxa, thus supplementing the morphology study, which were also supported by sequence identity analysis. The high bootstrap values thus confirmed the placing of \u003cem\u003eMicrophallus\u003c/em\u003e sp. under study within Microphallidae family; a bootstrap value greater than 70% gives reliable clading in a phylogenetic tree (Hillis and Bull \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1993\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe ITS2 secondary structures include additional morphological information that are not found in the primary sequence and thus help in reconstructing the complete tree of life (Caetano-Anoll\u0026eacute;s \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Grajales et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). A four-domain secondary structure model for ITS2 proposed by Michot et al (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1993\u003c/span\u003e) boosts its value as a marker for megasystematics (Schultz et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). So, ITS2 region has high nucleotide mutation but their conserve nature of secondary structure has made them highly useful in various evolutionary studies (Coleman \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). It is, therefore, necessary to consider both sequence and structure when calculating their alignments and in phylogenetic analysis (Keller et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Hence, the ITS2 rDNA primary sequence and secondary structures have been utilized in many taxonomic studies including those on digenean taxa (Coleman \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Shylla et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Ghatani et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Athokpam and Tandon \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). In the present study, Profile neighbour joining analysis of the secondary structure and sequence information of studied \u003cem\u003eMicrophallus\u003c/em\u003e sp. revealed the same topology as NJ and ML phylogenetic trees, clading with \u003cem\u003eM. indicus\u003c/em\u003e with significant bootstrap value (91%), thus confirming the results of primary sequence analysis.\u003c/p\u003e \u003cp\u003eOn the basis of morphological study, supplemented with molecular characterization, the presently studied microphallid metacercarial parasite occurring in \u003cem\u003ePotamiscus\u003c/em\u003e crabs in Manipur region is identified as belonging to the genus \u003cem\u003eMicrophallus\u003c/em\u003e Ward, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e1901\u003c/span\u003e. Limited data on the infection status of genus \u003cem\u003eMicrophallus\u003c/em\u003e are available in the public domain. So, more extensive works need to carry out to focus on finding possible intermediate hosts, completing their life cycle and for systematic analysis.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVDA acknowledges University Grants Commission (UGC), Government of India for awarding her \u0026lsquo;Research Fellowship in Science for Meritorious Students\u0026rsquo; and Council of Scientific \u0026amp; Industrial Research (CSIR), Government of India, for Senior Research Fellowship.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Department of Information Technology, Government of India under the \u0026ldquo;North-East Parasite Information and Analysis Centre (NEPIAC)\u0026rdquo; sanctioned to VT et al. [Sanction no.: DIT/R\u0026amp;D/BIO/ 15(13)/2008 dated Sep. 29, 2008]. VDA was awarded University Grants Commission (UGC) \u0026lsquo;Research Fellowship in Science for Meritorious Students\u0026rsquo; and Council of Scientific \u0026amp; Industrial Research (CSIR) \u0026lsquo;Senior Research Fellowship\u0026rsquo;.\u003c/p\u003e\n\u003cp\u003eThe authors declare that no funds or other support were received\u0026nbsp;during the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere is no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVeena Tandon prepare the study framework, critically analysed the manuscript; Voleentina Devi Athokpam carried out specimen preparation, analysis and drafting of the manuscript; Lalit Mohan Goswami help during analysis and drafting. All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAl-kandari WY, Al-bustan SA (2010) Molecular identification of \u003cem\u003eProbolocoryphe uca\u003c/em\u003e (Sarkisian, 1957; Digenea: Microphallidae) from Kuwait Bay using ITS1 and ITS2 sequences. Parasitol. Res 106:1189\u0026ndash;1195. Doi: 10.1007/s00436-010-1778-1\u003c/li\u003e\n\u003cli\u003eAnantaraman S, Subramoniam T (1976) On a microphallid metacercaria occurring in the ovaries of the sand crabs \u003cem\u003eEmerita asiatica\u003c/em\u003e and \u003cem\u003eAlbunea symnista\u003c/em\u003e on the Madras coast. Proc. Indian Acad. Sci\u003cem\u003e.\u003c/em\u003e\u003cem\u003e B\u003c/em\u003e 84(5):192\u0026ndash;199\u003c/li\u003e\n\u003cli\u003eAthokpam VD, Tandon V (2015) A survey of metacercarial infections in commonly edible fish and crab hosts prevailing in Manipur, Northeast India. J Parasit Dis 39(3): 429\u0026ndash;440\u003c/li\u003e\n\u003cli\u003eAthokpam VD, Tandon V (2014): Morphological and molecular characterization of\u003cem\u003e Posthodiplostomum\u003c/em\u003e sp. (Digenea: Diplostomidae) metacercaria in the muscles of snakeheads (\u003cem\u003eChanna punctata\u003c/em\u003e) from Manipur, India. Helminthologia 51(2):141\u0026ndash;152. DOI: 10.2478/s11687-014-0221-z\u003c/li\u003e\n\u003cli\u003eBowles J, Blair D, Mcmanus DP (1995) A molecular phylogeny of the human schistosomes. Mol\u003cem\u003e \u003c/em\u003ePhylogenet Evol 4:103\u0026ndash;109\u003c/li\u003e\n\u003cli\u003eCaetano-Anoll\u0026eacute;s G (2002) Tracing the evolution of RNA structure in ribosomes. Nucleic Acids Res 30:2575\u0026ndash;2587. Doi: 10.1093/nar/30.11.2575\u003c/li\u003e\n\u003cli\u003eChomchoei N, Backeljau T, Segers B, Wongsawad C, Butboonchoo P, Nantarat N (2022) Morphological and molecular characterization of larval trematodes infecting the assassin snail genus \u003cem\u003eAnentome \u003c/em\u003ein Thailand. J Helminthol 96:e52\u003c/li\u003e\n\u003cli\u003eChung OS, Lee HJ, Sohn WM, Lee SH, Park IY, Oh AA, Chai JY, Seo M (2010) Discovery of \u003cem\u003eMaritrema jebuensis\u003c/em\u003e n. sp. (Digenea: Microphallidae) from the Asian shore crab, \u003cem\u003eHemigrapsus sanguineus\u003c/em\u003e, in Korea. Korean J Parasitol 48(4):335\u0026ndash;338. DOI: 10.3347/kjp.2010.48.4.335\u003c/li\u003e\n\u003cli\u003eColeman AW (2003) ITS2 is a double-edged tool for eukaryote evolutionary comparisons. Trends Genet 19:370\u0026ndash;375. DOI: 10.1016/s0168-9525(03)00118-5\u003c/li\u003e\n\u003cli\u003eColeman AW (2007) Pan-eukaryote ITS2 homologies revealed by RNA secondary structure. 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DOI: 10.1093/nar/gkg595\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Microphallidae taxa sequences of rDNA used in the analysis with their respective GenBank accession numbers\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"600\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.820299500831947%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSl. No.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.62063227953411%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eParasite name\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.62728785357737%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLocality\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.93178036605657%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGenes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.755102040816325%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eITS2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52.244897959183675%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e28S\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.833333333333333%\" valign=\"top\"\u003e\n \u003cp\u003e1.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eMicrophallus indicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eIndia: Meghalaya\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5%\" valign=\"top\"\u003e\n \u003cp\u003eFJ966111.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.333333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eFJ966109.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.833333333333333%\" valign=\"top\"\u003e\n \u003cp\u003e2.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eMicrophallus abortivus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eUK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5%\" valign=\"top\"\u003e\n \u003cp\u003eHM584174.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.333333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eAY220626.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.833333333333333%\" valign=\"top\"\u003e\n \u003cp\u003e3.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eMicrophallus calidris\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eRussia\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5%\" valign=\"top\"\u003e\n \u003cp\u003eHM584183.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.333333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eHM584125.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.833333333333333%\" valign=\"top\"\u003e\n \u003cp\u003e4.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eMicrophallus pseudopygmaeus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eRussia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5%\" valign=\"top\"\u003e\n \u003cp\u003eHM584198.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.333333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eHM584126.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.833333333333333%\" valign=\"top\"\u003e\n \u003cp\u003e5.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eMicrophallus pygmaeus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eIceland\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5%\" valign=\"top\"\u003e\n \u003cp\u003eHM584190.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.333333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eHM584133.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.833333333333333%\" valign=\"top\"\u003e\n \u003cp\u003e6.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eMicrophallus similis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eRussia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5%\" valign=\"top\"\u003e\n \u003cp\u003eHM584178.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.333333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eHM584138.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.833333333333333%\" valign=\"top\"\u003e\n \u003cp\u003e7.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eMicrophallus piriformes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eIceland\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5%\" valign=\"top\"\u003e\n \u003cp\u003eHM584181.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.333333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eHM584122.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.833333333333333%\" valign=\"top\"\u003e\n \u003cp\u003e8.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eMicrophallus primas\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eUK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.333333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eAY220627.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.833333333333333%\" valign=\"top\"\u003e\n \u003cp\u003e9.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eMicrophallus triangulates\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eRussia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5%\" valign=\"top\"\u003e\n \u003cp\u003eHM584196.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.333333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eHM584139.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.833333333333333%\" valign=\"top\"\u003e\n \u003cp\u003e10.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eMicrophallus fusiformis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eUK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.333333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.833333333333333%\" valign=\"top\"\u003e\n \u003cp\u003e11.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eMicrophallus turgidus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eUSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.333333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.833333333333333%\" valign=\"top\"\u003e\n \u003cp\u003e12.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eMicrophallus\u0026nbsp;\u003c/em\u003esp.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eRussia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5%\" valign=\"top\"\u003e\n \u003cp\u003eHM584188.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.333333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eHM584140.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.833333333333333%\" valign=\"top\"\u003e\n \u003cp\u003e13.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eMicrophallus\u0026nbsp;\u003c/em\u003esp.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eRussia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5%\" valign=\"top\"\u003e\n \u003cp\u003eHM584175.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.333333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.833333333333333%\" valign=\"top\"\u003e\n \u003cp\u003e14.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eMaritrema subdolum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eRussia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5%\" valign=\"top\"\u003e\n \u003cp\u003eHM584172.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.333333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eAF151926.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.833333333333333%\" valign=\"top\"\u003e\n \u003cp\u003e15.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eMaritrema oocysta\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eUK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5%\" valign=\"top\"\u003e\n \u003cp\u003eHM584170.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.333333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eAY220630.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.833333333333333%\" valign=\"top\"\u003e\n \u003cp\u003e16.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eMaritrema eroliae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eKuwait\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5%\" valign=\"top\"\u003e\n \u003cp\u003eHQ650132.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.333333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eJF826247.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.833333333333333%\" valign=\"top\"\u003e\n \u003cp\u003e17.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eMaritrema neomi\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eUkraine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.333333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eAF151927.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.833333333333333%\" valign=\"top\"\u003e\n \u003cp\u003e18.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eMaritrema arenaria\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eUK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.5%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.333333333333332%\" valign=\"top\"\u003e\n \u003cp\u003eAY220629.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Morphometric measurements of the excysted metacercaria of \u003cem\u003eMicrophallus\u003c/em\u003e sp.\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"539\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.44444444444444%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacters\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.814814814814815%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.77777777777778%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRange (mm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.074074074074074%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026plusmn;\u003c/strong\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.44444444444444%\"\u003e\n \u003cp\u003eBody length\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.814814814814815%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.77777777777778%\"\u003e\n \u003cp\u003e0.423 \u0026ndash; 0.522\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.074074074074074%\"\u003e\n \u003cp\u003e0.461\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026plusmn;\u0026nbsp;\u003c/strong\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.44444444444444%\"\u003e\n \u003cp\u003eBody width (maximum)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.814814814814815%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.77777777777778%\"\u003e\n \u003cp\u003e0.369 \u0026ndash; 0.495\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.074074074074074%\"\u003e\n \u003cp\u003e0.434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026plusmn;\u0026nbsp;\u003c/strong\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.44444444444444%\"\u003e\n \u003cp\u003eOral sucker (diameter)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.814814814814815%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.77777777777778%\"\u003e\n \u003cp\u003e0.048 \u0026ndash; 0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.074074074074074%\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026plusmn;\u0026nbsp;\u003c/strong\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.44444444444444%\"\u003e\n \u003cp\u003ePrepharynx length\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.814814814814815%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.77777777777778%\"\u003e\n \u003cp\u003e0.003 \u0026ndash; 0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.074074074074074%\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026plusmn;\u0026nbsp;\u003c/strong\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.44444444444444%\" rowspan=\"2\"\u003e\n \u003cp\u003ePharynx:\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.814814814814815%\"\u003e\n \u003cp\u003eLength\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.77777777777778%\"\u003e\n \u003cp\u003e0.018 \u0026ndash; 0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.074074074074074%\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026plusmn;\u0026nbsp;\u003c/strong\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.598870056497177%\"\u003e\n \u003cp\u003eWidth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.74576271186441%\"\u003e\n \u003cp\u003e0.021 \u0026ndash; 0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.468926553672315%\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.1864406779661%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026plusmn;\u0026nbsp;\u003c/strong\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.44444444444444%\"\u003e\n \u003cp\u003eOesophagus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.814814814814815%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.77777777777778%\"\u003e\n \u003cp\u003e0.069 \u0026ndash; 0.090\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.074074074074074%\"\u003e\n \u003cp\u003e0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026plusmn;\u0026nbsp;\u003c/strong\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.44444444444444%\"\u003e\n \u003cp\u003eVentral sucker (diameter)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.814814814814815%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.77777777777778%\"\u003e\n \u003cp\u003e0.027 \u0026ndash; 0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.074074074074074%\"\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026plusmn;\u0026nbsp;\u003c/strong\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.44444444444444%\" rowspan=\"2\"\u003e\n \u003cp\u003eOvary:\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.814814814814815%\"\u003e\n \u003cp\u003eLength\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.77777777777778%\"\u003e\n \u003cp\u003e0.048 \u0026ndash; 0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.074074074074074%\"\u003e\n \u003cp\u003e0.070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026plusmn;\u0026nbsp;\u003c/strong\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.598870056497177%\"\u003e\n \u003cp\u003eWidth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.74576271186441%\"\u003e\n \u003cp\u003e0.036 \u0026ndash; 0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.468926553672315%\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.1864406779661%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026plusmn;\u0026nbsp;\u003c/strong\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.44444444444444%\" rowspan=\"2\"\u003e\n \u003cp\u003eLeft testis:\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.814814814814815%\"\u003e\n \u003cp\u003eLength\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.77777777777778%\"\u003e\n \u003cp\u003e0.060 \u0026ndash; 0.105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.074074074074074%\"\u003e\n \u003cp\u003e0.080\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026plusmn;\u0026nbsp;\u003c/strong\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.598870056497177%\"\u003e\n \u003cp\u003eWidth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.74576271186441%\"\u003e\n \u003cp\u003e0.063 \u0026ndash; 0.108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.468926553672315%\"\u003e\n \u003cp\u003e0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.1864406779661%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026plusmn;\u0026nbsp;\u003c/strong\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.44444444444444%\" rowspan=\"2\"\u003e\n \u003cp\u003eRight testis:\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.814814814814815%\"\u003e\n \u003cp\u003eLength\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.77777777777778%\"\u003e\n \u003cp\u003e0.051 \u0026ndash; 0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.074074074074074%\"\u003e\n \u003cp\u003e0.070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.88888888888889%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026plusmn;\u0026nbsp;\u003c/strong\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.598870056497177%\"\u003e\n \u003cp\u003eWidth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.74576271186441%\"\u003e\n \u003cp\u003e0.060 \u0026ndash; 0.099\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.468926553672315%\"\u003e\n \u003cp\u003e0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.1864406779661%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026plusmn;\u0026nbsp;\u003c/strong\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\" 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\" style=\"width: 1470px;\" width=\"1470\" height=\"1008\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5\u003c/strong\u003e. Difference in nucleotide positions\u0026nbsp;between\u0026nbsp;\u003cem\u003eMicrophallus\u003c/em\u003e sp. under study and \u003cem\u003eM. indicus\u003c/em\u003e, Indian isolate. A) ITS2 B) 28S\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;(Ts \u0026ndash;Transition; Tv \u0026ndash; Transversion; Indel \u0026ndash; Insertion/Deletion; * - Query sequence)\u003c/p\u003e\n\u003cp\u003e(a) ITS2\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003eSl. No.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eBase position\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.242268041237113%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eMicrophallus\u003c/em\u003e sp. *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eM. indicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eDifferences\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003eSr. No.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eBase position\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.561855670103093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eMicrophallus\u003c/em\u003e sp.*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eM. indicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eDifferences\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003e1.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.242268041237113%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003e13.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003e315\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.561855670103093%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003e2.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.242268041237113%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003e14.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003e316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.561855670103093%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003e3.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.242268041237113%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003e15.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003e317\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.561855670103093%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003e4.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003e142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.242268041237113%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003e16.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003e318\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.561855670103093%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003e5.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003e153\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.242268041237113%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003e17.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003e319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.561855670103093%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003e6.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003e154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.242268041237113%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003e18.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003e320\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.561855670103093%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003e7.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003e237\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.242268041237113%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003e19.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003e333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.561855670103093%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003e8.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003e248\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.242268041237113%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003e20.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003e334\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.561855670103093%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003e9.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003e251\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.242268041237113%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003e21.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003e357\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.561855670103093%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003e10.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003e265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.242268041237113%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003e22.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003e400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.561855670103093%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003e11.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003e295\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.242268041237113%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003e23.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003e402\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.561855670103093%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003e12.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003e297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.242268041237113%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003e24.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003e410\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.561855670103093%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.242268041237113%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.896907216494846%\" valign=\"top\"\u003e\n \u003cp\u003e25.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003e412\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.561855670103093%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.793814432989691%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.95360824742268%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e(b) 28S\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003eSl. No.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eBase position\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eMicrophallus\u003c/em\u003e sp.*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eM. indicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eDifferences\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003eSr. No.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eBase position\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eMicrophallus\u003c/em\u003e sp.*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eM. indicus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eDifferences\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e1.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e61.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e2.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e62.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e3.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e63.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e242\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e4.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e64.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e249\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e5.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e65.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e6.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e66.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e7.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e67.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e258\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e8.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e68.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e9.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e69.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e10.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e70.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e267\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e11.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e71.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e268\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e12.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e72.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e13.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e73.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e274\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e14.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e74.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e275\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e15.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e75.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e276\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e16.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e76.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e17.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e77.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e280\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e18.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e78.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e281\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e19.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e79.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e20.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e80.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e283\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e21.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e81.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e284\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e22.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e82.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e23.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e83.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e292\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e24.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e84.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e294\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e25.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e85.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e26.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e86.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e27.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e87.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e301\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e28.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e88.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e302\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e29.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e89.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e30.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e90.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e31.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e91.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e306\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e32.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e92.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e307\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e33.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e93.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e34.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e94.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e309\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e35.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e95.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e312\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e36.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e96.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e317\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e37.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e97.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e320\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e38.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e98.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e321\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e39.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e99.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e322\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e40.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e100.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e342\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e41.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e101.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e347\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e42.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e102.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e348\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e43.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e103.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e370\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e44.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e104.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e389\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e45.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e105.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e406\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e46.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e106.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e411\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e47.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e107.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e441\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e48.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e169\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e108.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e442\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e49.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e109.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e443\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e50.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e110.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e444\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e51.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e176\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e111.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e454\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e52.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e186\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e112.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e494\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eIndel\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e53.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e113.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e515\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e54.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e114.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e822\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003eG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003eTv\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.529411764705882%\" valign=\"top\"\u003e\n 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width=\"5.529411764705882%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.294117647058824%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.176470588235293%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-parasitic-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jopd","sideBox":"Learn more about [Journal of Parasitic Diseases](https://www.springer.com/journal/12639)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/jopd/default.aspx","title":"Journal of Parasitic Diseases","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"crabs, Potamiscus manipuriensis, metacercaria, Microphallidae, rDNA","lastPublishedDoi":"10.21203/rs.3.rs-4064777/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4064777/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eFreshwater crabs (\u003cem\u003ePotamiscus manipuriensis\u003c/em\u003e), commonly consumed as local delicacies by the native people in the state of Manipur, were found to harbour metacercariae of \u003cem\u003eMicrophallus\u003c/em\u003e sp. (Family Microphyllidae), which were morphologically different from metacercariae of \u003cem\u003eMicrophallus indicus\u003c/em\u003e reported earlier from a different host (\u003cem\u003eBarytelphusa lugubris mansoniana\u003c/em\u003e) in Meghalaya, another state in Northeast India. So, PCR-based molecular characterization of this metacercaria was done utilizing rDNA marker regions: larger subunit (LSU) or 28S and inter-transcribed spacer 2 (ITS2). Sequence and phylogenetic analyses confirmed that the taxon under study belonged to family Microphyllidae. The ITS2 secondary structure data analyses also confirmed the primary sequence analysis. The analysis also revealed sequence differences in one hundred and nineteen bases (with 38 transitions, 35 transversions and 46 indels) with regard to 28S, though ITS2 showed sequence differences in 25 bases (10 transitions, 7 transversions and 8 indels) between the present microphallid and \u003cem\u003eM. indicus\u003c/em\u003e.\u003c/p\u003e","manuscriptTitle":"Molecular characterization and phylogeny based on ITS2 and 28S regions of rDNA of Microphallus sp. (Digenea: Microphallidae) parasitic in freshwater crabs of Manipur, India","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-25 11:48:20","doi":"10.21203/rs.3.rs-4064777/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2024-04-09T11:14:42+00:00","index":0,"fulltext":""},{"type":"editorInvited","content":"Journal of Parasitic Diseases","date":"2024-04-01T13:54:44+00:00","index":"","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-03-21T15:39:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-16T05:56:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Parasitic Diseases","date":"2024-03-15T12:06:13+00:00","index":"","fulltext":""},{"type":"decision","content":"Minor revisions needed","date":"2024-03-12T10:47:24+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-parasitic-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jopd","sideBox":"Learn more about [Journal of Parasitic Diseases](https://www.springer.com/journal/12639)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/jopd/default.aspx","title":"Journal of Parasitic Diseases","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"d6302d6d-d022-4855-838c-dd0941051a1b","owner":[],"postedDate":"March 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-06-01T10:13:38+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-25 11:48:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4064777","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4064777","identity":"rs-4064777","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}