{"doi":"10.1093/gpbjnl/qzaf022","title":"High-quality Population-specific Haplotype-resolved Reference Panel in the Genomic and Pangenomic Eras","abstract":"<jats:title>Abstract</jats:title>\n                  <jats:p>Large-scale international and regional human genomic and pangenomic resources derived from population-scale biobanks and ancient DNA sequences have provided significant insights into human evolution and the genetic determinants of complex diseases and traits. Despite these advances, challenges persist in optimizing the integration of phasing tools, merging haplotype reference panels (HRPs), developing imputation algorithms, and fully exploiting the diverse applications of post-imputation data. This review comprehensively summarizes the advancements, applications, limitations, and future directions of HRPs in human genomics research. Recent progress in the reconstruction of HRPs, based on over 830,000 human whole-genome sequences, has been synthesized, highlighting the broad spectrum of human genetic diversity captured. Additionally, we recapitulate advancements in 56 HRPs for global and regional populations. The evaluation of imputation accuracy indicated that Beagle and Glimpse are the most effective tools for phasing and imputing data from genotyping arrays and low-coverage sequencing, respectively. A critical strategy for selecting an appropriate HRP involves matching the population background of target groups with HRP reference populations and considering multi-ancestry or homogeneous genetic structures. The necessity of a single, integrative, high-quality HRP that captures haplotype structures and genetic diversity across various genetic variation types from globally representative populations is emphasized to support both modern and ancient genomic research and advance human precision medicine.</jats:p>","journal":"Genomics, Proteomics &amp; Bioinformatics","year":2025,"id":612797,"datarank":0.4566783656585135,"base_score":3.044522437723423,"endowment":3.044522437723423,"self_citation_contribution":0.4566783656585135,"citation_network_contribution":0.0,"self_endowment_contribution":0.4566783656585135,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":20,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"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":1578000,"name":"Yuntao Sun","orcid":"0009-0007-8419-1420","position":1,"is_corresponding":false},{"id":1578002,"name":"Shuhan Duan","orcid":"0009-0005-7214-581X","position":2,"is_corresponding":false},{"id":1578004,"name":"Shengjie Nie","orcid":"0000-0001-6414-6621","position":3,"is_corresponding":false},{"id":432879,"name":"Chao Liu","orcid":"0000-0003-0316-4994","position":4,"is_corresponding":false},{"id":546759,"name":"Hong Deng","orcid":"0009-0002-5901-9606","position":5,"is_corresponding":false},{"id":901566,"name":"Mengge Wang","orcid":"0000-0002-3673-1855","position":6,"is_corresponding":false},{"id":552458,"name":"Guanglin He","orcid":"0000-0002-6614-5267","position":7,"is_corresponding":false},{"id":1577997,"name":"Qingxin Yang","orcid":"0009-0007-5099-6925","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"High-quality Population-specific Haplotype-resolved Reference Panel in the Genomic and Pangenomic Eras","abstract":"<jats:title>Abstract</jats:title>\n                  <jats:p>Large-scale international and regional human genomic and pangenomic resources derived from population-scale biobanks and ancient DNA sequences have provided significant insights into human evolution and the genetic determinants of complex diseases and traits. Despite these advances, challenges persist in optimizing the integration of phasing tools, merging haplotype reference panels (HRPs), developing imputation algorithms, and fully exploiting the diverse applications of post-imputation data. This review comprehensively summarizes the advancements, applications, limitations, and future directions of HRPs in human genomics research. Recent progress in the reconstruction of HRPs, based on over 830,000 human whole-genome sequences, has been synthesized, highlighting the broad spectrum of human genetic diversity captured. Additionally, we recapitulate advancements in 56 HRPs for global and regional populations. The evaluation of imputation accuracy indicated that Beagle and Glimpse are the most effective tools for phasing and imputing data from genotyping arrays and low-coverage sequencing, respectively. A critical strategy for selecting an appropriate HRP involves matching the population background of target groups with HRP reference populations and considering multi-ancestry or homogeneous genetic structures. The necessity of a single, integrative, high-quality HRP that captures haplotype structures and genetic diversity across various genetic variation types from globally representative populations is emphasized to support both modern and ancient genomic research and advance human precision medicine.</jats:p>","is_dataset_classified":null,"base_score":2.9444389791664403,"endowment":2.9444389791664403,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"40059317","pmcid":"PMC13175255","openalex_id":"https://openalex.org/W4408272644","authors":[],"funders":[{"funder_name":"National Natural Science Foundation of China","grant_id":"82402203","title":null},{"funder_name":"National Natural Science Foundation of China","grant_id":"82202078","title":null},{"funder_name":"Major Project of the National Social Science Foundation of China","grant_id":"23&ZD203","title":null},{"funder_name":"Open Project of the Key Laboratory of Forensic Genetics of the Ministry of Public Security","grant_id":"2022FGKFKT05","title":null},{"funder_name":"Open Project of the Key Laboratory of Forensic Genetics of the Ministry of Public Security","grant_id":"2024FGKFKT02","title":null},{"funder_name":"Center for Archaeological Science of Sichuan University","grant_id":"23SASA01","title":null},{"funder_name":"Center for Archaeological Science of Sichuan University","grant_id":"24SASB03","title":null},{"funder_name":"1·3·5 Project for Disciplines of Excellence, West China Hospital, Sichuan University","grant_id":"ZYJC20002","title":null},{"funder_name":"Sichuan Science and Technology Program","grant_id":"2024NSFSC1518","title":null},{"funder_name":"Major Project of the National Social Science Foundation of China","grant_id":"23&amp;ZD203","title":null}],"total_grants":10,"fwci":17.0145,"citation_percentile":0.99421711,"influential_citations":0,"citation_trend":[{"year":2025,"count":12},{"year":2026,"count":6}],"oa_status":"gold","license":"cc-by","oa_locations":[{"url":"https://academic.oup.com/gpb/advance-article-pdf/doi/10.1093/gpbjnl/qzaf022/62352871/qzaf022.pdf","host_type":"journal"},{"url":"https://academic.oup.com/gpb/advance-article-pdf/doi/10.1093/gpbjnl/qzaf022/62352871/qzaf022.pdf","host_type":"publisher"},{"url":"https://academic.oup.com/gpb/article-pdf/23/6/qzaf022/62352871/qzaf022.pdf","host_type":"publisher"},{"url":"https://doi.org/10.1093/gpbjnl/qzaf022","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/40059317","host_type":"repository"},{"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13175255/","host_type":"repository"},{"url":"https://europepmc.org/articles/PMC13175255","host_type":"Europe_PMC"},{"url":"https://europepmc.org/articles/PMC13175255?pdf=render","host_type":"Europe_PMC"}],"fields_of_study":["Forensic and Genetic Research","Genetic Associations and Epidemiology","Genetic Mapping and Diversity in Plants and Animals"],"mesh_terms":["Genetics, Population","Haplotypes","Humans","Genetic Variation","Genome, Human","Genomics"],"keywords":["Imputation (statistics)","Genotyping","Biobank","Haplotype","Genomics","Population","Human genetic variation","Biology","Computational biology","Human genome","Data science","Genetics","Genome","Computer science","Missing data","Genotype","Machine learning","Gene","Population Genomics","Genomic Medicine","Genotype Imputation","Imputation Accuracy","Haplotype Reference Panel"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Partnerships for the goals"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[{"name":"refsnp"}],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-02T04:59:56.937681Z","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":[]}