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Sagar V, Kaelin CB, Natesh M, Reddy PA, Mohapatra RK, Chhattani H, Thatte P, Vaidyanathan S, Biswas S, Bhatt S, Paul S, Jhala YV, Verma MM, Pandav B, Mondol S, Barsh GS, Swain D, Ramakrishnan U. High frequency of an otherwise rare phenotype in a small and isolated tiger population. Proc Natl Acad Sci U S A 2021; 118:e2025273118. [PMID: 34518374 PMCID: PMC8488692 DOI: 10.1073/pnas.2025273118] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/09/2021] [Indexed: 11/18/2022] Open
Abstract
Most endangered species exist today in small populations, many of which are isolated. Evolution in such populations is largely governed by genetic drift. Empirical evidence for drift affecting striking phenotypes based on substantial genetic data are rare. Approximately 37% of tigers (Panthera tigris) in the Similipal Tiger Reserve (in eastern India) are pseudomelanistic, characterized by wide, merged stripes. Camera trap data across the tiger range revealed the presence of pseudomelanistic tigers only in Similipal. We investigated the genetic basis for pseudomelanism and examined the role of drift in driving this phenotype's frequency. Whole-genome data and pedigree-based association analyses from captive tigers revealed that pseudomelanism cosegregates with a conserved and functionally important coding alteration in Transmembrane Aminopeptidase Q (Taqpep), a gene responsible for similar traits in other felid species. Noninvasive sampling of tigers revealed a high frequency of the Taqpep p.H454Y mutation in Similipal (12 individuals, allele frequency = 0.58) and absence from all other tiger populations (395 individuals). Population genetic analyses confirmed few (minimal number) tigers in Similipal, and its genetic isolation, with poor geneflow. Pairwise FST (0.33) at the mutation site was high but not an outlier. Similipal tigers had low diversity at 81 single nucleotide polymorphisms (mean heterozygosity = 0.28, SD = 0.27). Simulations were consistent with founding events and drift as possible drivers for the observed stark difference of allele frequency. Our results highlight the role of stochastic processes in the evolution of rare phenotypes. We highlight an unusual evolutionary trajectory in a small and isolated population of an endangered species.
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Affiliation(s)
- Vinay Sagar
- National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore 560065, India;
| | - Christopher B Kaelin
- Department of Genetics, Stanford University, Palo Alto, CA 94309
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806
| | - Meghana Natesh
- National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore 560065, India
- Biology Department, Indian Institute of Science Education and Research, Tirupati 411008, India
| | - P Anuradha Reddy
- Laboratory for Conservation of Endangered Species, Center for Cellular & Molecular Biology, Hyderabad 500048, India
| | | | - Himanshu Chhattani
- National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore 560065, India
| | - Prachi Thatte
- World Wide Fund for Nature - India, New Delhi 110003 India
| | - Srinivas Vaidyanathan
- Foundation for Ecological Research, Advocacy and Learning, Auroville Post, Tamil Nadu 605101 India
| | | | | | - Shashi Paul
- Odisha Forest Department, Bhubaneswar 751023, India
| | - Yadavendradev V Jhala
- Wildlife Institute of India, Dehradun 248001, India
- National Tiger Conservation Authority, Wildlife Institute of India Tiger Cell, Wildlife Institute of India, Dehradun 248001, India
| | | | | | | | - Gregory S Barsh
- Department of Genetics, Stanford University, Palo Alto, CA 94309
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806
| | - Debabrata Swain
- Former Member Secretary, National Tiger Conservation Authority, New Delhi 110003, India
- Former Principal Chief Conservator of Forest and Head of Forest Force, Indian Forest Service, Bhubaneswar 751023, India
| | - Uma Ramakrishnan
- National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore 560065, India;
- DBT - Wellcome Trust India Alliance, Hyderabad 500034, India
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Thinley P, Rajaratnam R, Morreale SJ, Lassoie JP. Assessing the adequacy of a protected area network in conserving a wide‐ranging apex predator: The case for tiger (
Panthera tigris
) conservation in Bhutan. CONSERVATION SCIENCE AND PRACTICE 2021. [DOI: 10.1111/csp2.318] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Affiliation(s)
- Phuntsho Thinley
- Center for Forest Science and Technology Ugyen Wangchuck Institute for Conservation and Environmental Research Lamaigoenpa Bumthang Bhutan
- Ecosystem Management University of New England Armidale New South Wales Australia
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Atzeni L, Cushman SA, Bai D, Wang J, Chen P, Shi K, Riordan P. Meta-replication, sampling bias, and multi-scale model selection: A case study on snow leopard ( Panthera uncia) in western China. Ecol Evol 2020; 10:7686-7712. [PMID: 32760557 PMCID: PMC7391562 DOI: 10.1002/ece3.6492] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Revised: 05/15/2020] [Accepted: 05/18/2020] [Indexed: 12/04/2022] Open
Abstract
Replicated multiple scale species distribution models (SDMs) have become increasingly important to identify the correct variables determining species distribution and their influences on ecological responses. This study explores multi-scale habitat relationships of the snow leopard (Panthera uncia) in two study areas on the Qinghai-Tibetan Plateau of western China. Our primary objectives were to evaluate the degree to which snow leopard habitat relationships, expressed by predictors, scales of response, and magnitude of effects, were consistent across study areas or locally landcape-specific. We coupled univariate scale optimization and the maximum entropy algorithm to produce multivariate SDMs, inferring the relative suitability for the species by ensembling top performing models. We optimized the SDMs based on average omission rate across the top models and ensembles' overlap with a simulated reference model. Comparison of SDMs in the two study areas highlighted landscape-specific responses to limiting factors. These were dependent on the effects of the hydrological network, anthropogenic features, topographic complexity, and the heterogeneity of the landcover patch mosaic. Overall, even accounting for specific local differences, we found general landscape attributes associated with snow leopard ecological requirements, consisting of a positive association with uplands and ridges, aggregated low-contrast landscapes, and large extents of grassy and herbaceous vegetation. As a means to evaluate the performance of two bias correction methods, we explored their effects on three datasets showing a range of bias intensities. The performance of corrections depends on the bias intensity; however, density kernels offered a reliable correction strategy under all circumstances. This study reveals the multi-scale response of snow leopards to environmental attributes and confirms the role of meta-replicated study designs for the identification of spatially varying limiting factors. Furthermore, this study makes important contributions to the ongoing discussion about the best approaches for sampling bias correction.
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Affiliation(s)
- Luciano Atzeni
- Wildlife InstituteSchool of Ecology and Nature ConservationBeijing Forestry UniversityBeijingChina
| | | | - Defeng Bai
- Wildlife InstituteSchool of Ecology and Nature ConservationBeijing Forestry UniversityBeijingChina
| | - Jun Wang
- Wildlife InstituteSchool of Ecology and Nature ConservationBeijing Forestry UniversityBeijingChina
- Faculty of Science and EngineeringManchester Metropolitan UniversityManchesterUK
| | - Pengju Chen
- Wildlife InstituteSchool of Ecology and Nature ConservationBeijing Forestry UniversityBeijingChina
| | - Kun Shi
- Wildlife InstituteSchool of Ecology and Nature ConservationBeijing Forestry UniversityBeijingChina
- Eco‐Bridge ContinentalBeijingChina
| | - Philip Riordan
- Wildlife InstituteSchool of Ecology and Nature ConservationBeijing Forestry UniversityBeijingChina
- Marwell WildlifeWinchesterUK
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