Genetic Diversity, Genetic Structure, and Demographic History of Black Snub‐Nosed Monkey (<i>Rhinopithecus strykeri</i>) in the Gaoligong Mountains, Southwestern China

The Gaoligong Mountains, located in the southeastern Tibetan Plateau, is one of the world's biodiversity hotspots and provides a refugium for many endangered endemic animals. In this study, we reported a population genetic study on black snub-nosed monkey (Rhinopithecus strykeri), a critically endangered primate endemic to the Gaoligong Mountains, yet their large-scale population genetic study remains underexplored. Here, we performed population genetic analyses from two geographical populations (Pianma and Luoma) based on targeted genomic single-nucleotide polymorphism (SNP) data (37.7 K) and mitochondrial DNA (mtDNA) control region (842 bp). Both nuclear SNP data and mtDNA revealed relatively low levels of genetic variation in both populations compared to other reported primates, which is most likely to be explained by loss of historical genetic diversity due to inbreeding and long-term small effective population size, thus potentially aggravating the effects of inbreeding and genetic depression. Phylogenetic and population structure analyses for mtDNA revealed two deep lineages (approximately 0.69 million years ago), but limited genetic differentiation in nuclear data, which might have been caused by the Late Cenozoic uplift of the Tibetan Plateau and glacial refuge, and subsequent secondary contact as a result of historically high and bidirectional gene flow between populations. Ecological niche modeling and landscape connectivity analyses also showed historical and recent connectivity between two geographical populations. The demographic history inferred from both mtDNA and nuclear data revealed at least two continuous declines in the effective population size occurring around 43 Kya and 8-10 Kya, respectively, probably due to Pleistocene glaciations and subsequent human activities. Our results provide the first detailed and comprehensive genetic insights into the genetic diversity, population structure, and demographic history of a critically endangered species, and provide essential baseline information to guide conservation efforts.

Authors

Institutions

Publication Details

Journal
American Journal of Primatology
Published
2025-04-01
DOI
https://doi.org/10.1002/ajp.70031
Primary Topic
Genomics and Phylogenetic Studies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Genetic Diversity, Genetic Structure, and Demographic History of Black Snub‐Nosed Monkey (Rhinopithecus strykeri) in the Gaoligong Mountains, Southwestern China

Christian Roos, Weimin Kuang, Zhechang Hu, Yuan Li et al.
American Journal of Primatology
Genomics and Phylogenetic Studies
article

Genetic Diversity, Genetic Structure, and Demographic History of Black Snub‐Nosed Monkey (Rhinopithecus strykeri) in the Gaoligong Mountains, Southwestern China

Christian Roos, Weimin Kuang, Zhechang Hu, Yuan Li, Yingping Tian, Rui Guo, Yixin Chen, Li Yu, Jia Luo, Minglin Chen
article en

Abstract

The Gaoligong Mountains, located in the southeastern Tibetan Plateau, is one of the world's biodiversity hotspots and provides a refugium for many endangered endemic animals. In this study, we reported a population genetic study on black snub-nosed monkey (Rhinopithecus strykeri), a critically endangered primate endemic to the Gaoligong Mountains, yet their large-scale population genetic study remains underexplored. Here, we performed population genetic analyses from two geographical populations (Pianma and Luoma) based on targeted genomic single-nucleotide polymorphism (SNP) data (37.7 K) and mitochondrial DNA (mtDNA) control region (842 bp). Both nuclear SNP data and mtDNA revealed relatively low levels of genetic variation in both populations compared to other reported primates, which is most likely to be explained by loss of historical genetic diversity due to inbreeding and long-term small effective population size, thus potentially aggravating the effects of inbreeding and genetic depression. Phylogenetic and population structure analyses for mtDNA revealed two deep lineages (approximately 0.69 million years ago), but limited genetic differentiation in nuclear data, which might have been caused by the Late Cenozoic uplift of the Tibetan Plateau and glacial refuge, and subsequent secondary contact as a result of historically high and bidirectional gene flow between populations. Ecological niche modeling and landscape connectivity analyses also showed historical and recent connectivity between two geographical populations. The demographic history inferred from both mtDNA and nuclear data revealed at least two continuous declines in the effective population size occurring around 43 Kya and 8-10 Kya, respectively, probably due to Pleistocene glaciations and subsequent human activities. Our results provide the first detailed and comprehensive genetic insights into the genetic diversity, population structure, and demographic history of a critically endangered species, and provide essential baseline information to guide conservation efforts.

American Journal of PrimatologyVol. 87(4)
Central South University of Forestry and Technology (CN), Central South University (CN), Kunming Institute of Zoology (CN), Yunnan University (CN), Chinese Academy of Sciences (CN), German Primate Center (DE), Fanjingshan National Nature Reserve (CN), University of Chinese Academy of Sciences (CN)
National Natural Science Foundation of China
Life in Land
Openalex Percentile: Top 94%
Genomics and Phylogenetic Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.