Morphometric trait normalization, cluster analysis and molecular phylogenetic analysis in delimiting sympatric Neolissochilus hexastichus and N. hexagonolepis in Umngi River, Meghalaya (India)

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dc.contributor.authorLaskar, M.A.en_US
dc.contributor.authorSarma, D.en_US
dc.contributor.authorNath, R.en_US
dc.contributor.authorKharbani, R.en_US
dc.contributor.authorShahi, N.en_US
dc.contributor.authorHaldar, R.S.en_US
dc.contributor.authorGanie, P.A.en_US
dc.date.accessioned2025-05-12T10:14:27Z
dc.date.available2025-05-12T10:14:27Z
dc.date.issued2024-12
dc.description.abstractAim: To assess the ability of an integrative approach comprising multivariate morphometric data analysis and mitochondrial cytochrome oxidase subunit I (CO I) sequence divergence analysis in delimiting sympatric Neolissochilus hexastichus (McClleland, 1839) and N. hexagonolepis (McClleland, 1839) mahseer populations in River Umngi, Meghalaya. Methodology: Authoritative descriptions of mahseers were referred during the sampling of 40 individuals from River Umngi, Meghalaya. Multivariate morphometric data were normalized with respect to standard length. The normalization procedure maintained the particular shape factor for each sample. Normalised data were subjected to hierarchical clustering on principal components Analysis (HCPC) for grouping samples according to morphometric features. Genetic affinities based on CO I sequence divergence were assessed by Bayesian Inference (BI) and Automatic Barcode Gap Discovery (ABGD) protocols. Results: The normalization protocols removed the variations in traits due to body size effects and facilitated the identification of allometric traits. HCPC analysis revealed morphometric features that had a significant impact on clustering. Nine N. hexagonolepis and 13 N. hexastichus individuals were identified by integrative morphological and molecular phylogenetic approach. The remaining 18 individuals had incongruence in their memberships in the morphometric and phylogenetic clusters. Interpretation: The integrative approach, apart from delineating N. hexagonolepis and N. hexastichus congeners, highlighted the need to include nuclear genetic markers in future studies for confirming the presence of natural hybrids in sympatric populations of Neolissochilus mahseers.en_US
dc.identifier.affiliationsBiotechnology Department, St. Anthony’s College, Shillong-793 001, Indiaen_US
dc.identifier.affiliationsDivision of Aquaculture, ICAR-Central Institute of Fisheries Education, Mumbai-400 061, Indiaen_US
dc.identifier.affiliationsFishery Science Department, St. Anthony’s College, Shillong-793 001, Indiaen_US
dc.identifier.affiliationsFishery Science Department, St. Anthony’s College, Shillong-793 001, Indiaen_US
dc.identifier.affiliationsICAR-Directorate of Coldwater Fisheries Research, Bhimtal-263 136, Indiaen_US
dc.identifier.affiliationsICAR-Directorate of Coldwater Fisheries Research, Bhimtal-263 136, Indiaen_US
dc.identifier.affiliationsICAR-Directorate of Coldwater Fisheries Research, Bhimtal-263 136, Indiaen_US
dc.identifier.citationLaskar M.A., Sarma D., Nath R., Kharbani R., Shahi N., Haldar R.S., Ganie P.A. . Morphometric trait normalization, cluster analysis and molecular phylogenetic analysis in delimiting sympatric Neolissochilus hexastichus and N. hexagonolepis in Umngi River, Meghalaya (India). Journal of Environmental Biology. 2024 Dec; 45(6): 705-713en_US
dc.identifier.issn0254-8704
dc.identifier.issn2394-0379
dc.identifier.placeIndiaen_US
dc.identifier.urihttps://imsear.searo.who.int/handle/123456789/247545
dc.languageenen_US
dc.publisherTriveni Enterprisesen_US
dc.relation.issuenumber6en_US
dc.relation.volume45en_US
dc.source.urihttps://doi.org/10.22438/jeb/45/6/MRN-5337en_US
dc.subjectClusteren_US
dc.subjectMorphometricen_US
dc.subjectNeolissochilusen_US
dc.subjectNormalizationen_US
dc.subjectPhylogeneticsen_US
dc.titleMorphometric trait normalization, cluster analysis and molecular phylogenetic analysis in delimiting sympatric Neolissochilus hexastichus and N. hexagonolepis in Umngi River, Meghalaya (India)en_US
dc.typeJournal Articleen_US
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