{"doi":"10.1002/ajp.70088","title":"Re‐Evaluating the Demographic History of, and Inferring the Fine‐Scale Recombination Landscape For, Wild Chinese Rhesus Macaques ( <i>Macaca mulatta</i> )","abstract":"As a major model for biomedical research, the rhesus macaque (Macaca mulatta) is one of the most important and heavily studied nonhuman primates. Despite this importance, the level of population structure and subspecific division in this species remains relatively unclear; for example, the number of proposed subspecies in the literature ranges from one to six within China, with additional populations found across India. Motivated by an interest in comparing recombination rate landscapes between rhesus macaque subspecies, we re-evaluated the demographic history of this group using a previously published data set from 79 wild-born individuals sampled across 17 regions in China. In so doing, we found that previously published demographic models utilizing five subspecies did not well reproduce empirical levels or patterns of genomic variation. Thus, we re-performed demographic inference, finding instead multiple lines of support for a single, interbreeding population (i.e., an absence of population structuring), as well as a population size-change history linking periods of population growth and contraction to historical patterns of glaciation. Finally, utilizing this well-fitting population history, we inferred a genome-wide, fine-scale recombination rate map for this population, finding mean rates consistent with those estimated in other closely related populations and species. However, we also observed notable difference in the fine-scale landscape between rhesus macaques of Chinese and Indian origin - two populations widely used as models in biomedical research - highlighting the importance of accounting for population-specific demographic history and recombination rate variation in future population genomic studies of this species.","journal":"American Journal of Primatology","year":2025,"id":515008,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":7,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.7446,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1379059,"name":"Adriana Calahorra‐Oliart","orcid":null,"position":1,"is_corresponding":false},{"id":1047712,"name":"Cyril J. Versoza","orcid":"0000-0002-4202-6589","position":2,"is_corresponding":false},{"id":1379060,"name":"Devangana Shah","orcid":null,"position":3,"is_corresponding":false},{"id":1039399,"name":"Vivak Soni","orcid":"0000-0002-9496-9562","position":4,"is_corresponding":false},{"id":374841,"name":"Susanne P. Pfeifer","orcid":"0000-0003-1378-2913","position":5,"is_corresponding":false},{"id":7661,"name":"Jeffrey D. Jensen","orcid":"0000-0002-4786-8064","position":6,"is_corresponding":false},{"id":1058376,"name":"John W. Terbot","orcid":"0000-0002-8067-0674","position":0,"is_corresponding":true}],"reference_count":86,"raw_metadata":null,"created_at":"2026-07-19T02:48:34.431522Z","pmid":"41195497","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}