bioRxivEcology
Consideration of genetic variation and evolutionary history in future conservation of Indian one-horned rhinoceros (Rhinoceros unicornis)
T. Ghosh, S. Kumar, K. Sharma, P. Kakati, A. Sharma, S. Mondol
Abstract
The extant members of the Eurasian rhino species have experienced severe population and range declines through a combination of natural and anthropogenic factors since Pleistocene. The one-horned rhino is the only Asian species recovered from such strong population decline but most of their fragmented populations in India and Nepal are reaching carrying capacity. Implementation of any future reintroduction-based conservation efforts would greatly benefit from currently unavailable detailed genetic assessments and evolutionary history of these populations. We sequenced wild one-horned rhino mitogenome from all the extant populations (n=16 individuals) for the first time, identified the polymorphic sites and assessed genetic variation (2531bp mtDNA, n=111 individuals) across India. Results showed 30 unique rhino haplotypes distributed as three distinct genetic clades (Fst value 0.68-1) corresponding to the states of Assam (n=28 haplotypes), West Bengal and Uttar Pradesh (both monomorphic). Phylogenetic analyses suggest earlier coalescence of Assam ([~]0.5 Mya) followed by parallel divergence of West Bengal and Uttar Pradesh/Nepal ([~]0.06-0.05Mya), supported by the paleobiogeographic history of the Indian subcontinent. Combined together, we propose recognising three Evolutionary Significant Units (ESUs) of Indian rhino. As recent assessments suggest further genetic isolations of Indian rhinos at local scales, future management efforts should focus on identifying genetically variable founder animals and consider periodic supplementation events while planning future rhino reintroduction programs in India. Such well-informed, multidisciplinary approach is the only way to ensure evolutionary, ecological and demographic stability of the species across its range.
- organism: non-human primate
- assay: DNA methylation
- research focus: clustering
- approach: statistical model
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