{"doi":"10.1111/mec.12488","title":"Analyses of genetic ancestry enable key insights for molecular ecology","abstract":"<jats:title>Abstract</jats:title><jats:p>Gene flow and recombination in admixed populations produce genomes that are mosaic combinations of chromosome segments inherited from different source populations, that is, chromosome segments with different genetic ancestries. The statistical problem of estimating genetic ancestry from <jats:styled-content style=\"fixed-case\">DNA</jats:styled-content> sequence data has been widely studied, and analyses of genetic ancestry have facilitated research in molecular ecology and ecological genetics. In this review, we describe and compare different model‐based statistical methods used to infer genetic ancestry. We describe the conceptual and mathematical structure of these models and highlight some of their key differences and shared features. We then discuss recent empirical studies that use estimates of genetic ancestry to analyse population histories, the nature and genetic basis of species boundaries, and the genetic architecture of traits. These diverse studies demonstrate the breadth of applications that rely on genetic ancestry estimates and typify the genomics‐enabled research that is becoming increasingly common in molecular ecology. We conclude by identifying key research areas where future studies might further advance this field.</jats:p>","journal":"Molecular Ecology","year":2013,"id":589031,"datarank":1.5688690778933851,"base_score":3.8501476017100584,"endowment":3.8501476017100584,"self_citation_contribution":0.5775221402565088,"citation_network_contribution":0.9913469376368763,"self_endowment_contribution":0.5775221402565088,"citer_contribution":0.9913469376368763,"corpus_percentile":null,"corpus_rank":null,"citation_count":46,"citer_count":35,"citers_with_citation_signal":31,"citers_with_endowment":31,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":556096,"name":"C. Alex Buerkle","orcid":"0000-0003-4222-8858","position":1,"is_corresponding":false},{"id":556095,"name":"Zachariah Gompert","orcid":"0000-0003-2248-2488","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Analyses of genetic ancestry enable key insights for molecular ecology","abstract":"<jats:title>Abstract</jats:title><jats:p>Gene flow and recombination in admixed populations produce genomes that are mosaic combinations of chromosome segments inherited from different source populations, that is, chromosome segments with different genetic ancestries. The statistical problem of estimating genetic ancestry from <jats:styled-content style=\"fixed-case\">DNA</jats:styled-content> sequence data has been widely studied, and analyses of genetic ancestry have facilitated research in molecular ecology and ecological genetics. In this review, we describe and compare different model‐based statistical methods used to infer genetic ancestry. We describe the conceptual and mathematical structure of these models and highlight some of their key differences and shared features. We then discuss recent empirical studies that use estimates of genetic ancestry to analyse population histories, the nature and genetic basis of species boundaries, and the genetic architecture of traits. These diverse studies demonstrate the breadth of applications that rely on genetic ancestry estimates and typify the genomics‐enabled research that is becoming increasingly common in molecular ecology. We conclude by identifying key research areas where future studies might further advance this field.</jats:p>","is_dataset_classified":null,"base_score":3.8501476017100584,"endowment":3.8501476017100584,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"24103088","pmcid":null,"openalex_id":"https://openalex.org/W2144035323","authors":[],"funders":[],"total_grants":0,"fwci":2.5319,"citation_percentile":0.89755359,"influential_citations":0,"citation_trend":[{"year":2014,"count":3},{"year":2015,"count":4},{"year":2016,"count":5},{"year":2017,"count":1},{"year":2018,"count":7},{"year":2019,"count":2},{"year":2020,"count":4},{"year":2021,"count":4},{"year":2023,"count":1},{"year":2024,"count":7},{"year":2025,"count":7},{"year":2026,"count":1}],"oa_status":"closed","license":"http://doi.wiley.com/10.1002/tdm_license_1.1","oa_locations":[{"url":"https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fmec.12488","host_type":"publisher"},{"url":"https://onlinelibrary.wiley.com/doi/pdf/10.1111/mec.12488","host_type":"publisher"},{"url":"https://doi.org/10.1111/mec.12488","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/24103088","host_type":"repository"}],"fields_of_study":["Genetic diversity and population structure","Genetic and phenotypic traits in livestock","Genetic Mapping and Diversity in Plants and Animals","Bayes Theorem","Ecology","Gene Flow","Gene Frequency","Genetic Speciation","Genetics, Population","Haplotypes","Likelihood Functions","Markov Chains","Models, Genetic","Models, Statistical","Polymorphism, Single Nucleotide"],"mesh_terms":["Bayes Theorem","Ecology","Gene Frequency","Genetics, Population","Haplotypes","Markov Chains","Models, Genetic","Models, Statistical","Likelihood Functions","Polymorphism, Single Nucleotide","Genetic Speciation","Gene Flow"],"keywords":["Biology","Evolutionary biology","Molecular ecology","Population genetics","Genetic genealogy","Genetic architecture","Genomics","Population genomics","Population","Gene flow","Genome","Ecological genetics","Ecology","Key (lock)","Genetic variation","Genetics","Quantitative trait locus","Gene","Hidden Markov model","Introgression","Admixture","Markov Chain Monte Carlo"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-23T11:59:50.212287Z","pmid":null,"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":[]}