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Testing times: disentangling admixture histories in recent and complex demographies using ancient DNA
Abstract Our knowledge of human evolutionary history has been greatly advanced by paleogenomics. Since the 2020s, the study of ancient DNA has increasingly focused on reconstructing the recent past. However, the accuracy of paleogenomic methods in resolving questions of historical and archaeological...
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Our knowledge of human evolutionary history has been greatly advanced by paleogenomics. Since the 2020s, the study of ancient DNA has increasingly focused on reconstructing the recent past. However, the accuracy of paleogenomic methods in resolving questions of historical and archaeological importance amidst the increased demographic complexity and decreased genetic differentiation remains an open question. We evaluated the performance and behavior of two commonly used methods, qpAdm and the f3-statistic, on admixture inference under a diversity of demographic models and data conditions. We performed two complementary simulation approaches—firstly exploring a wide demographic parameter space under four simple demographic models of varying complexities and configurations using branch-length data from two chromosomes—and secondly, we analyzed a model of Eurasian history composed of 59 populations using whole-genome data modified with ancient DNA conditions such as SNP ascertainment, data missingness, and pseudohaploidization. We observe that population differentiation is the primary factor driving qpAdm performance. Notably, while complex gene flow histories influence which models are classified as plausible, they do not reduce overall performance. Under conditions reflective of the historical period, qpAdm most frequently identifies the true model as plausible among a small candidate set of closely related populations. To increase the utility for resolving fine-scaled hypotheses, we provide a heuristic for further distinguishing between candidate models that incorporates qpAdm model P-values and f3-statistics. Finally, we demonstrate a significant performance increase for qpAdm using whole-genome branch-length f2-statistics, highlighting the potential for improved demographic inference that could be achieved with future advancements in f-statistic estimations.
Over the past decade, advances in ancient DNA research have provided crucial insights into population demographic history. Ancient DNA has been shifting towards studying the more recent past, referred to as archaeogenetics. The authors research evaluates the effectiveness and limitations of two widely used methods, the f3-statistic and qpAdm, in reconstructing admixture histories under complex historical population dynamics. Their findings highlight the challenges in accurately reconstructing complex genetic histories and provide guidelines for more reliable inference heuristics in archaeogen |
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Our knowledge of human evolutionary history has been greatly advanced by paleogenomics. Since the 2020s, the study of ancient DNA has increasingly focused on reconstructing the recent past. However, the accuracy of paleogenomic methods in resolving questions of historical and archaeological importance amidst the increased demographic complexity and decreased genetic differentiation remains an open question. We evaluated the performance and behavior of two commonly used methods, qpAdm and the f3-statistic, on admixture inference under a diversity of demographic models and data conditions. We performed two complementary simulation approaches—firstly exploring a wide demographic parameter space under four simple demographic models of varying complexities and configurations using branch-length data from two chromosomes—and secondly, we analyzed a model of Eurasian history composed of 59 populations using whole-genome data modified with ancient DNA conditions such as SNP ascertainment, data missingness, and pseudohaploidization. We observe that population differentiation is the primary factor driving qpAdm performance. Notably, while complex gene flow histories influence which models are classified as plausible, they do not reduce overall performance. Under conditions reflective of the historical period, qpAdm most frequently identifies the true model as plausible among a small candidate set of closely related populations. To increase the utility for resolving fine-scaled hypotheses, we provide a heuristic for further distinguishing between candidate models that incorporates qpAdm model P-values and f3-statistics. Finally, we demonstrate a significant performance increase for qpAdm using whole-genome branch-length f2-statistics, highlighting the potential for improved demographic inference that could be achieved with future advancements in f-statistic estimations.
Over the past decade, advances in ancient DNA research have provided crucial insights into population demographic history. Ancient DNA has been shifting towards studying the more recent past, referred to as archaeogenetics. The authors research evaluates the effectiveness and limitations of two widely used methods, the f3-statistic and qpAdm, in reconstructing admixture histories under complex historical population dynamics. Their findings highlight the challenges in accurately reconstructing complex genetic histories and provide guidelines for more reliable inference heuristics in archaeogenetic analyses.</description><identifier>ISSN: 1943-2631</identifier><identifier>ISSN: 0016-6731</identifier><identifier>EISSN: 1943-2631</identifier><identifier>DOI: 10.1093/genetics/iyae110</identifier><identifier>PMID: 39013011</identifier><language>eng</language><publisher>US: Oxford University Press</publisher><subject>Chromosomes ; Complexity ; Configuration management ; Demographics ; Demography ; Deoxyribonucleic acid ; Differentiation ; DNA ; DNA, Ancient - analysis ; Evolution, Molecular ; Evolutionary genetics ; Gene Flow ; Genetics, Population - methods ; Genome, Human ; Genomes ; Humans ; Inference ; Investigation ; Models, Genetic ; Parameter modification ; Performance evaluation ; Polymorphism, Single Nucleotide ; Population (statistical) ; Population differentiation ; Questions ; Single-nucleotide polymorphism ; Statistical methods ; Statistics</subject><ispartof>Genetics (Austin), 2024-09, Vol.228 (1)</ispartof><rights>The Author(s) 2024. Published by Oxford University Press on behalf of The Genetics Society of America. 2024</rights><rights>The Author(s) 2024. Published by Oxford University Press on behalf of The Genetics Society of America.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c302t-9165702bc8e5e367d1c3d6ad184ef089ce8f991c36e2852134f5a56b22da26c53</cites><orcidid>0000-0001-7117-193X ; 0000-0001-9759-4981 ; 0000-0002-2267-2604</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39013011$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Ramachandran, S</contributor><creatorcontrib>Williams, Matthew P</creatorcontrib><creatorcontrib>Flegontov, Pavel</creatorcontrib><creatorcontrib>Maier, Robert</creatorcontrib><creatorcontrib>Huber, Christian D</creatorcontrib><title>Testing times: disentangling admixture histories in recent and complex demographies using ancient DNA</title><title>Genetics (Austin)</title><addtitle>Genetics</addtitle><description>Abstract
Our knowledge of human evolutionary history has been greatly advanced by paleogenomics. Since the 2020s, the study of ancient DNA has increasingly focused on reconstructing the recent past. However, the accuracy of paleogenomic methods in resolving questions of historical and archaeological importance amidst the increased demographic complexity and decreased genetic differentiation remains an open question. We evaluated the performance and behavior of two commonly used methods, qpAdm and the f3-statistic, on admixture inference under a diversity of demographic models and data conditions. We performed two complementary simulation approaches—firstly exploring a wide demographic parameter space under four simple demographic models of varying complexities and configurations using branch-length data from two chromosomes—and secondly, we analyzed a model of Eurasian history composed of 59 populations using whole-genome data modified with ancient DNA conditions such as SNP ascertainment, data missingness, and pseudohaploidization. We observe that population differentiation is the primary factor driving qpAdm performance. Notably, while complex gene flow histories influence which models are classified as plausible, they do not reduce overall performance. Under conditions reflective of the historical period, qpAdm most frequently identifies the true model as plausible among a small candidate set of closely related populations. To increase the utility for resolving fine-scaled hypotheses, we provide a heuristic for further distinguishing between candidate models that incorporates qpAdm model P-values and f3-statistics. Finally, we demonstrate a significant performance increase for qpAdm using whole-genome branch-length f2-statistics, highlighting the potential for improved demographic inference that could be achieved with future advancements in f-statistic estimations.
Over the past decade, advances in ancient DNA research have provided crucial insights into population demographic history. Ancient DNA has been shifting towards studying the more recent past, referred to as archaeogenetics. The authors research evaluates the effectiveness and limitations of two widely used methods, the f3-statistic and qpAdm, in reconstructing admixture histories under complex historical population dynamics. Their findings highlight the challenges in accurately reconstructing complex genetic histories and provide guidelines for more reliable inference heuristics in archaeogenetic analyses.</description><subject>Chromosomes</subject><subject>Complexity</subject><subject>Configuration management</subject><subject>Demographics</subject><subject>Demography</subject><subject>Deoxyribonucleic acid</subject><subject>Differentiation</subject><subject>DNA</subject><subject>DNA, Ancient - analysis</subject><subject>Evolution, Molecular</subject><subject>Evolutionary genetics</subject><subject>Gene Flow</subject><subject>Genetics, Population - methods</subject><subject>Genome, Human</subject><subject>Genomes</subject><subject>Humans</subject><subject>Inference</subject><subject>Investigation</subject><subject>Models, Genetic</subject><subject>Parameter modification</subject><subject>Performance evaluation</subject><subject>Polymorphism, Single Nucleotide</subject><subject>Population (statistical)</subject><subject>Population differentiation</subject><subject>Questions</subject><subject>Single-nucleotide polymorphism</subject><subject>Statistical methods</subject><subject>Statistics</subject><issn>1943-2631</issn><issn>0016-6731</issn><issn>1943-2631</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>TOX</sourceid><recordid>eNqFkc1v1DAQxS0EoqVw54QicUFC23rstRNzqary0UoVXMrZ8tqTrKvEDnaC2v8eh91WhUtPMxr_3tOMHyFvgR4DVfykw4CTt_nE3xkEoM_IIag1XzHJ4fmj_oC8yvmGUiqVaF6SA64ocApwSPAa8-RDV01-wPypcj5jmEzo-mVo3OBvpzlhtfV5isljrnyoEtoCVSa4ysZh7PG2cjjELplxuyBz_isO1i_Y5-9nr8mL1vQZ3-zrEfn59cv1-cXq6se3y_Ozq5XllE0rBVLUlG1sgwK5rB1Y7qRx0KyxpY2y2LRKlaFE1ggGfN0KI-SGMWeYtIIfkdOd7zhvBnTLlsn0ekx-MOlOR-P1vy_Bb3UXf2sAXnMBtDh82Duk-Gsuf6MHny32vQkY56w5baCuQfCmoO__Q2_inEK5T_PiRNdKClYouqNsijknbB-2AaqXEPV9iHofYpG8e3zFg-A-tQJ83AFxHp-2-wNGhqv0</recordid><startdate>20240904</startdate><enddate>20240904</enddate><creator>Williams, Matthew P</creator><creator>Flegontov, Pavel</creator><creator>Maier, Robert</creator><creator>Huber, Christian D</creator><general>Oxford University Press</general><general>Genetics Society of America</general><scope>TOX</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>4T-</scope><scope>4U-</scope><scope>7QP</scope><scope>7SS</scope><scope>7TK</scope><scope>7TM</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>M7N</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-7117-193X</orcidid><orcidid>https://orcid.org/0000-0001-9759-4981</orcidid><orcidid>https://orcid.org/0000-0002-2267-2604</orcidid></search><sort><creationdate>20240904</creationdate><title>Testing times: disentangling admixture histories in recent and complex demographies using ancient DNA</title><author>Williams, Matthew P ; Flegontov, Pavel ; Maier, Robert ; Huber, Christian D</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c302t-9165702bc8e5e367d1c3d6ad184ef089ce8f991c36e2852134f5a56b22da26c53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Chromosomes</topic><topic>Complexity</topic><topic>Configuration management</topic><topic>Demographics</topic><topic>Demography</topic><topic>Deoxyribonucleic acid</topic><topic>Differentiation</topic><topic>DNA</topic><topic>DNA, Ancient - analysis</topic><topic>Evolution, Molecular</topic><topic>Evolutionary genetics</topic><topic>Gene Flow</topic><topic>Genetics, Population - methods</topic><topic>Genome, Human</topic><topic>Genomes</topic><topic>Humans</topic><topic>Inference</topic><topic>Investigation</topic><topic>Models, Genetic</topic><topic>Parameter modification</topic><topic>Performance evaluation</topic><topic>Polymorphism, Single Nucleotide</topic><topic>Population (statistical)</topic><topic>Population differentiation</topic><topic>Questions</topic><topic>Single-nucleotide polymorphism</topic><topic>Statistical methods</topic><topic>Statistics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Williams, Matthew P</creatorcontrib><creatorcontrib>Flegontov, Pavel</creatorcontrib><creatorcontrib>Maier, Robert</creatorcontrib><creatorcontrib>Huber, Christian D</creatorcontrib><collection>Oxford University Press Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Docstoc</collection><collection>University Readers</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Neurosciences Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Genetics (Austin)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Williams, Matthew P</au><au>Flegontov, Pavel</au><au>Maier, Robert</au><au>Huber, Christian D</au><au>Ramachandran, S</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Testing times: disentangling admixture histories in recent and complex demographies using ancient DNA</atitle><jtitle>Genetics (Austin)</jtitle><addtitle>Genetics</addtitle><date>2024-09-04</date><risdate>2024</risdate><volume>228</volume><issue>1</issue><issn>1943-2631</issn><issn>0016-6731</issn><eissn>1943-2631</eissn><abstract>Abstract
Our knowledge of human evolutionary history has been greatly advanced by paleogenomics. Since the 2020s, the study of ancient DNA has increasingly focused on reconstructing the recent past. However, the accuracy of paleogenomic methods in resolving questions of historical and archaeological importance amidst the increased demographic complexity and decreased genetic differentiation remains an open question. We evaluated the performance and behavior of two commonly used methods, qpAdm and the f3-statistic, on admixture inference under a diversity of demographic models and data conditions. We performed two complementary simulation approaches—firstly exploring a wide demographic parameter space under four simple demographic models of varying complexities and configurations using branch-length data from two chromosomes—and secondly, we analyzed a model of Eurasian history composed of 59 populations using whole-genome data modified with ancient DNA conditions such as SNP ascertainment, data missingness, and pseudohaploidization. We observe that population differentiation is the primary factor driving qpAdm performance. Notably, while complex gene flow histories influence which models are classified as plausible, they do not reduce overall performance. Under conditions reflective of the historical period, qpAdm most frequently identifies the true model as plausible among a small candidate set of closely related populations. To increase the utility for resolving fine-scaled hypotheses, we provide a heuristic for further distinguishing between candidate models that incorporates qpAdm model P-values and f3-statistics. Finally, we demonstrate a significant performance increase for qpAdm using whole-genome branch-length f2-statistics, highlighting the potential for improved demographic inference that could be achieved with future advancements in f-statistic estimations.
Over the past decade, advances in ancient DNA research have provided crucial insights into population demographic history. Ancient DNA has been shifting towards studying the more recent past, referred to as archaeogenetics. The authors research evaluates the effectiveness and limitations of two widely used methods, the f3-statistic and qpAdm, in reconstructing admixture histories under complex historical population dynamics. Their findings highlight the challenges in accurately reconstructing complex genetic histories and provide guidelines for more reliable inference heuristics in archaeogenetic analyses.</abstract><cop>US</cop><pub>Oxford University Press</pub><pmid>39013011</pmid><doi>10.1093/genetics/iyae110</doi><orcidid>https://orcid.org/0000-0001-7117-193X</orcidid><orcidid>https://orcid.org/0000-0001-9759-4981</orcidid><orcidid>https://orcid.org/0000-0002-2267-2604</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Chromosomes Complexity Configuration management Demographics Demography Deoxyribonucleic acid Differentiation DNA DNA, Ancient - analysis Evolution, Molecular Evolutionary genetics Gene Flow Genetics, Population - methods Genome, Human Genomes Humans Inference Investigation Models, Genetic Parameter modification Performance evaluation Polymorphism, Single Nucleotide Population (statistical) Population differentiation Questions Single-nucleotide polymorphism Statistical methods Statistics |
title | Testing times: disentangling admixture histories in recent and complex demographies using ancient DNA |
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