1
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Simon A, Coop G. The contribution of gene flow, selection, and genetic drift to five thousand years of human allele frequency change. Proc Natl Acad Sci U S A 2024; 121:e2312377121. [PMID: 38363870 PMCID: PMC10907250 DOI: 10.1073/pnas.2312377121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 01/09/2024] [Indexed: 02/18/2024] Open
Abstract
Genomic time series from experimental evolution studies and ancient DNA datasets offer us a chance to directly observe the interplay of various evolutionary forces. We show how the genome-wide variance in allele frequency change between two time points can be decomposed into the contributions of gene flow, genetic drift, and linked selection. In closed populations, the contribution of linked selection is identifiable because it creates covariances between time intervals, and genetic drift does not. However, repeated gene flow between populations can also produce directionality in allele frequency change, creating covariances. We show how to accurately separate the fraction of variance in allele frequency change due to admixture and linked selection in a population receiving gene flow. We use two human ancient DNA datasets, spanning around 5,000 y, as time transects to quantify the contributions to the genome-wide variance in allele frequency change. We find that a large fraction of genome-wide change is due to gene flow. In both cases, after correcting for known major gene flow events, we do not observe a signal of genome-wide linked selection. Thus despite the known role of selection in shaping long-term polymorphism levels, and an increasing number of examples of strong selection on single loci and polygenic scores from ancient DNA, it appears to be gene flow and drift, and not selection, that are the main determinants of recent genome-wide allele frequency change. Our approach should be applicable to the growing number of contemporary and ancient temporal population genomics datasets.
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Affiliation(s)
- Alexis Simon
- Center for Population Biology, University of California, Davis, CA95616
- Department of Evolution and Ecology, University of California, Davis, CA95616
| | - Graham Coop
- Center for Population Biology, University of California, Davis, CA95616
- Department of Evolution and Ecology, University of California, Davis, CA95616
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2
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Boumajdi N, Bendani H, Kartti S, Alouane T, Belyamani L, Ibrahimi A. A Comprehensive Analysis of 3 Moroccan Genomes Revealed Contributions From Both African and European Ancestries. Evol Bioinform Online 2024; 20:11769343241229278. [PMID: 38327511 PMCID: PMC10848790 DOI: 10.1177/11769343241229278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 01/12/2024] [Indexed: 02/09/2024] Open
Abstract
Genetic variations in the human genome represent the differences in DNA sequence within individuals. This highlights the important role of whole human genome sequencing which has become the keystone for precision medicine and disease prediction. Morocco is an important hub for studying human population migration and mixing history. This study presents the analysis of 3 Moroccan genomes; the variant analysis revealed 6 379 606 single nucleotide variants (SNVs) and 1 050 577 small InDels. Of those identified SNVs, 219 152 were novel, with 1233 occurring in coding regions, and 5580 non-synonymous single nucleotide variants (nsSNP) variants were predicted to affect protein functions. The InDels produced 1055 coding variants and 454 non-3n length variants, and their size ranged from -49 and 49 bp. We further analysed the gene pathways of 8 novel coding variants found in the 3 genomes and revealed 5 genes involved in various diseases and biological pathways. We found that the Moroccan genomes share 92.78% of African ancestry, and 92.86% of Non-Finnish European ancestry, according to the gnomAD database. Then, population structure inference, by admixture analysis and network-based approach, revealed that the studied genomes form a mixed population structure, highlighting the increased genetic diversity in Morocco.
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Affiliation(s)
- Nasma Boumajdi
- Laboratory of Biotechnology, Medical and Pharmacy School, Mohammed V University, Rabat, Morocco
- Mohammed VI Center for Research & Innovation (CM6), Rabat, Morocco
| | - Houda Bendani
- Laboratory of Biotechnology, Medical and Pharmacy School, Mohammed V University, Rabat, Morocco
- Mohammed VI Center for Research & Innovation (CM6), Rabat, Morocco
| | - Souad Kartti
- Laboratory of Biotechnology, Medical and Pharmacy School, Mohammed V University, Rabat, Morocco
- Mohammed VI Center for Research & Innovation (CM6), Rabat, Morocco
| | - Tarek Alouane
- Laboratory of Biotechnology, Medical and Pharmacy School, Mohammed V University, Rabat, Morocco
| | - Lahcen Belyamani
- Mohammed VI Center for Research & Innovation (CM6), Rabat, Morocco
- Mohammed VI University of Health Sciences (UM6SS), Casablanca, Morocco
- Emergency Department, Military Hospital Mohammed V, Rabat Medical and Pharmacy School, Mohammed V University, Rabat, Morocco
| | - Azeddine Ibrahimi
- Laboratory of Biotechnology, Medical and Pharmacy School, Mohammed V University, Rabat, Morocco
- Mohammed VI Center for Research & Innovation (CM6), Rabat, Morocco
- Mohammed VI University of Health Sciences (UM6SS), Casablanca, Morocco
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3
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Hui R, Scheib CL, D’Atanasio E, Inskip SA, Cessford C, Biagini SA, Wohns AW, Ali MQ, Griffith SJ, Solnik A, Niinemäe H, Ge XJ, Rose AK, Beneker O, O’Connell TC, Robb JE, Kivisild T. Genetic history of Cambridgeshire before and after the Black Death. SCIENCE ADVANCES 2024; 10:eadi5903. [PMID: 38232165 PMCID: PMC10793959 DOI: 10.1126/sciadv.adi5903] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 12/14/2023] [Indexed: 01/19/2024]
Abstract
The extent of the devastation of the Black Death pandemic (1346-1353) on European populations is known from documentary sources and its bacterial source illuminated by studies of ancient pathogen DNA. What has remained less understood is the effect of the pandemic on human mobility and genetic diversity at the local scale. Here, we report 275 ancient genomes, including 109 with coverage >0.1×, from later medieval and postmedieval Cambridgeshire of individuals buried before and after the Black Death. Consistent with the function of the institutions, we found a lack of close relatives among the friars and the inmates of the hospital in contrast to their abundance in general urban and rural parish communities. While we detect long-term shifts in local genetic ancestry in Cambridgeshire, we find no evidence of major changes in genetic ancestry nor higher differentiation of immune loci between cohorts living before and after the Black Death.
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Affiliation(s)
- Ruoyun Hui
- Alan Turing Institute, London, UK
- McDonald Institute for Archaeological Research, University of Cambridge, Cambridge, UK
| | - Christiana L. Scheib
- McDonald Institute for Archaeological Research, University of Cambridge, Cambridge, UK
- Estonian Biocentre, Institute of Genomics, University of Tartu, Tartu, Estonia
- St John’s College, University of Cambridge, Cambridge, UK
| | | | - Sarah A. Inskip
- McDonald Institute for Archaeological Research, University of Cambridge, Cambridge, UK
- School of Archaeology and Ancient History, University of Leicester, Leicester, UK
| | - Craig Cessford
- McDonald Institute for Archaeological Research, University of Cambridge, Cambridge, UK
- Cambridge Archaeological Unit, Department of Archaeology, University of Cambridge, Cambridge, UK
| | | | - Anthony W. Wohns
- School of Medicine, Stanford University, Stanford, CA, USA
- Department of Genetics and Biology, Stanford University, Stanford, CA, USA
| | | | - Samuel J. Griffith
- Estonian Biocentre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Anu Solnik
- Core Facility, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Helja Niinemäe
- Estonian Biocentre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Xiangyu Jack Ge
- Wellcome Genome Campus, Wellcome Sanger Institute, Hinxton, UK
| | - Alice K. Rose
- McDonald Institute for Archaeological Research, University of Cambridge, Cambridge, UK
- Department of Archaeology, University of Durham, Durham, UK
| | - Owyn Beneker
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Tamsin C. O’Connell
- McDonald Institute for Archaeological Research, University of Cambridge, Cambridge, UK
| | - John E. Robb
- Department of Archaeology, University of Cambridge, Cambridge, UK
| | - Toomas Kivisild
- McDonald Institute for Archaeological Research, University of Cambridge, Cambridge, UK
- Estonian Biocentre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Department of Human Genetics, KU Leuven, Leuven, Belgium
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4
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Simon A, Coop G. The contribution of gene flow, selection, and genetic drift to five thousand years of human allele frequency change. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.07.11.548607. [PMID: 37503227 PMCID: PMC10370008 DOI: 10.1101/2023.07.11.548607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Genomic time series from experimental evolution studies and ancient DNA datasets offer us a chance to directly observe the interplay of various evolutionary forces. We show how the genome-wide variance in allele frequency change between two time points can be decomposed into the contributions of gene flow, genetic drift, and linked selection. In closed populations, the contribution of linked selection is identifiable because it creates covariances between time intervals, and genetic drift does not. However, repeated gene flow between populations can also produce directionality in allele frequency change, creating covariances. We show how to accurately separate the fraction of variance in allele frequency change due to admixture and linked selection in a population receiving gene flow. We use two human ancient DNA datasets, spanning around 5,000 years, as time transects to quantify the contributions to the genome-wide variance in allele frequency change. We find that a large fraction of genome-wide change is due to gene flow. In both cases, after correcting for known major gene flow events, we do not observe a signal of genome-wide linked selection. Thus despite the known role of selection in shaping long-term polymorphism levels, and an increasing number of examples of strong selection on single loci and polygenic scores from ancient DNA, it appears to be gene flow and drift, and not selection, that are the main determinants of recent genome-wide allele frequency change. Our approach should be applicable to the growing number of contemporary and ancient temporal population genomics datasets.
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Affiliation(s)
- Alexis Simon
- Center for Population Biology, University of California, Davis, CA 95616
- Department of Evolution and Ecology, University of California, Davis, CA 95616
| | - Graham Coop
- Center for Population Biology, University of California, Davis, CA 95616
- Department of Evolution and Ecology, University of California, Davis, CA 95616
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5
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Gao Z. Unveiling recent and ongoing adaptive selection in human populations. PLoS Biol 2024; 22:e3002469. [PMID: 38236800 PMCID: PMC10796035 DOI: 10.1371/journal.pbio.3002469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2024] Open
Abstract
Genome-wide scans for signals of selection have become a routine part of the analysis of population genomic variation datasets and have resulted in compelling evidence of selection during recent human evolution. This Essay spotlights methodological innovations that have enabled the detection of selection over very recent timescales, even in contemporary human populations. By harnessing large-scale genomic and phenotypic datasets, these new methods use different strategies to uncover connections between genotype, phenotype, and fitness. This Essay outlines the rationale and key findings of each strategy, discusses challenges in interpretation, and describes opportunities to improve detection and understanding of ongoing selection in human populations.
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Affiliation(s)
- Ziyue Gao
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
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6
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Irving-Pease EK, Refoyo-Martínez A, Barrie W, Ingason A, Pearson A, Fischer A, Sjögren KG, Halgren AS, Macleod R, Demeter F, Henriksen RA, Vimala T, McColl H, Vaughn AH, Speidel L, Stern AJ, Scorrano G, Ramsøe A, Schork AJ, Rosengren A, Zhao L, Kristiansen K, Iversen AKN, Fugger L, Sudmant PH, Lawson DJ, Durbin R, Korneliussen T, Werge T, Allentoft ME, Sikora M, Nielsen R, Racimo F, Willerslev E. The selection landscape and genetic legacy of ancient Eurasians. Nature 2024; 625:312-320. [PMID: 38200293 PMCID: PMC10781624 DOI: 10.1038/s41586-023-06705-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2022] [Accepted: 10/03/2023] [Indexed: 01/12/2024]
Abstract
The Holocene (beginning around 12,000 years ago) encompassed some of the most significant changes in human evolution, with far-reaching consequences for the dietary, physical and mental health of present-day populations. Using a dataset of more than 1,600 imputed ancient genomes1, we modelled the selection landscape during the transition from hunting and gathering, to farming and pastoralism across West Eurasia. We identify key selection signals related to metabolism, including that selection at the FADS cluster began earlier than previously reported and that selection near the LCT locus predates the emergence of the lactase persistence allele by thousands of years. We also find strong selection in the HLA region, possibly due to increased exposure to pathogens during the Bronze Age. Using ancient individuals to infer local ancestry tracts in over 400,000 samples from the UK Biobank, we identify widespread differences in the distribution of Mesolithic, Neolithic and Bronze Age ancestries across Eurasia. By calculating ancestry-specific polygenic risk scores, we show that height differences between Northern and Southern Europe are associated with differential Steppe ancestry, rather than selection, and that risk alleles for mood-related phenotypes are enriched for Neolithic farmer ancestry, whereas risk alleles for diabetes and Alzheimer's disease are enriched for Western hunter-gatherer ancestry. Our results indicate that ancient selection and migration were large contributors to the distribution of phenotypic diversity in present-day Europeans.
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Affiliation(s)
- Evan K Irving-Pease
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark.
| | - Alba Refoyo-Martínez
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - William Barrie
- GeoGenetics Group, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Andrés Ingason
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Institute of Biological Psychiatry, Mental Health Services, Copenhagen University Hospital, Roskilde, Denmark
| | - Alice Pearson
- Department of Genetics, University of Cambridge, Cambridge, UK
- Department of Zoology, University of Cambridge, Cambridge, UK
| | - Anders Fischer
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Department of Historical Studies, University of Gothenburg, Gothenburg, Sweden
- Sealand Archaeology, Kalundborg, Denmark
| | - Karl-Göran Sjögren
- Department of Historical Studies, University of Gothenburg, Gothenburg, Sweden
| | - Alma S Halgren
- Department of Integrative Biology, University of California Berkeley, Berkeley, CA, USA
| | - Ruairidh Macleod
- GeoGenetics Group, Department of Zoology, University of Cambridge, Cambridge, UK
- UCL Genetics Institute, University College London, London, UK
| | - Fabrice Demeter
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Eco-anthropologie, Muséum national d'Histoire naturelle, CNRS, Université Paris Cité, Musée de l'Homme, Paris, France
| | - Rasmus A Henriksen
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Tharsika Vimala
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Hugh McColl
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Andrew H Vaughn
- Center for Computational Biology, University of California, Berkeley, CA, USA
| | - Leo Speidel
- UCL Genetics Institute, University College London, London, UK
- Ancient Genomics Laboratory, The Francis Crick Institute, London, UK
| | - Aaron J Stern
- Center for Computational Biology, University of California, Berkeley, CA, USA
| | - Gabriele Scorrano
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Abigail Ramsøe
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Andrew J Schork
- Institute of Biological Psychiatry, Mental Health Services, Copenhagen University Hospital, Roskilde, Denmark
- Neurogenomics Division, The Translational Genomics Research Institute (TGEN), Phoenix, AZ, USA
| | - Anders Rosengren
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Institute of Biological Psychiatry, Mental Health Services, Copenhagen University Hospital, Roskilde, Denmark
| | - Lei Zhao
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Kristian Kristiansen
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Department of Historical Studies, University of Gothenburg, Gothenburg, Sweden
| | - Astrid K N Iversen
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Lars Fugger
- Oxford Centre for Neuroinflammation, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
- Department of Clinical Medicine, Aarhus University Hospital, Aarhus, Denmark
- MRC Human Immunology Unit, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Peter H Sudmant
- Department of Integrative Biology, University of California Berkeley, Berkeley, CA, USA
- Center for Computational Biology, University of California, Berkeley, CA, USA
| | - Daniel J Lawson
- Institute of Statistical Sciences, School of Mathematics, University of Bristol, Bristol, UK
| | - Richard Durbin
- Department of Genetics, University of Cambridge, Cambridge, UK
- Wellcome Sanger Institute, Cambridge, UK
| | - Thorfinn Korneliussen
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Thomas Werge
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Institute of Biological Psychiatry, Mental Health Center Sct Hans, Copenhagen University Hospital, Copenhagen, Denmark
| | - Morten E Allentoft
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
- Trace and Environmental DNA (TrEnD) Laboratory, School of Molecular and Life Science, Curtin University, Perth, Western Australia, Australia
| | - Martin Sikora
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Rasmus Nielsen
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark.
- Departments of Integrative Biology and Statistics, UC Berkeley, Berkeley, CA, USA.
| | - Fernando Racimo
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark.
| | - Eske Willerslev
- Lundbeck Foundation GeoGenetics Centre, Globe Institute, University of Copenhagen, Copenhagen, Denmark.
- GeoGenetics Group, Department of Zoology, University of Cambridge, Cambridge, UK.
- MARUM Center for Marine Environmental Sciences and Faculty of Geosciences, University of Bremen, Bremen, Germany.
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Pivirotto AM, Platt A, Patel R, Kumar S, Hey J. Analyses of allele age and fitness impact reveal human beneficial alleles to be older than neutral controls. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.09.561569. [PMID: 37873438 PMCID: PMC10592680 DOI: 10.1101/2023.10.09.561569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
A classic population genetic prediction is that alleles experiencing directional selection should swiftly traverse allele frequency space, leaving detectable reductions in genetic variation in linked regions. However, despite this expectation, identifying clear footprints of beneficial allele passage has proven to be surprisingly challenging. We addressed the basic premise underlying this expectation by estimating the ages of large numbers of beneficial and deleterious alleles in a human population genomic data set. Deleterious alleles were found to be young, on average, given their allele frequency. However, beneficial alleles were older on average than non-coding, non-regulatory alleles of the same frequency. This finding is not consistent with directional selection and instead indicates some type of balancing selection. Among derived beneficial alleles, those fixed in the population show higher local recombination rates than those still segregating, consistent with a model in which new beneficial alleles experience an initial period of balancing selection due to linkage disequilibrium with deleterious recessive alleles. Alleles that ultimately fix following a period of balancing selection will leave a modest 'soft' sweep impact on the local variation, consistent with the overall paucity of species-wide 'hard' sweeps in human genomes.
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Affiliation(s)
| | - Alexander Platt
- Temple University, Department of Biology, Philadelphia PA 19122, USA
- University of Pennsylvania, Department of Genetics, Philadelphia PA 19104, USA
| | - Ravi Patel
- Temple University, Department of Biology, Philadelphia PA 19122, USA
- Institute for Genomics and Evolutionary Medicine, Temple University, PA 19122, USA
| | - Sudhir Kumar
- Temple University, Department of Biology, Philadelphia PA 19122, USA
- Institute for Genomics and Evolutionary Medicine, Temple University, PA 19122, USA
| | - Jody Hey
- Temple University, Department of Biology, Philadelphia PA 19122, USA
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8
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Amin MR, Hasan M, Arnab SP, DeGiorgio M. Tensor Decomposition-based Feature Extraction and Classification to Detect Natural Selection from Genomic Data. Mol Biol Evol 2023; 40:msad216. [PMID: 37772983 PMCID: PMC10581699 DOI: 10.1093/molbev/msad216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 08/10/2023] [Accepted: 09/14/2023] [Indexed: 09/30/2023] Open
Abstract
Inferences of adaptive events are important for learning about traits, such as human digestion of lactose after infancy and the rapid spread of viral variants. Early efforts toward identifying footprints of natural selection from genomic data involved development of summary statistic and likelihood methods. However, such techniques are grounded in simple patterns or theoretical models that limit the complexity of settings they can explore. Due to the renaissance in artificial intelligence, machine learning methods have taken center stage in recent efforts to detect natural selection, with strategies such as convolutional neural networks applied to images of haplotypes. Yet, limitations of such techniques include estimation of large numbers of model parameters under nonconvex settings and feature identification without regard to location within an image. An alternative approach is to use tensor decomposition to extract features from multidimensional data although preserving the latent structure of the data, and to feed these features to machine learning models. Here, we adopt this framework and present a novel approach termed T-REx, which extracts features from images of haplotypes across sampled individuals using tensor decomposition, and then makes predictions from these features using classical machine learning methods. As a proof of concept, we explore the performance of T-REx on simulated neutral and selective sweep scenarios and find that it has high power and accuracy to discriminate sweeps from neutrality, robustness to common technical hurdles, and easy visualization of feature importance. Therefore, T-REx is a powerful addition to the toolkit for detecting adaptive processes from genomic data.
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Affiliation(s)
- Md Ruhul Amin
- Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USA
| | - Mahmudul Hasan
- Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USA
| | - Sandipan Paul Arnab
- Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USA
| | - Michael DeGiorgio
- Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431, USA
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9
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Tobler R, Souilmi Y, Huber CD, Bean N, Turney CSM, Grey ST, Cooper A. The role of genetic selection and climatic factors in the dispersal of anatomically modern humans out of Africa. Proc Natl Acad Sci U S A 2023; 120:e2213061120. [PMID: 37220274 PMCID: PMC10235988 DOI: 10.1073/pnas.2213061120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 03/14/2023] [Indexed: 05/25/2023] Open
Abstract
The evolutionarily recent dispersal of anatomically modern humans (AMH) out of Africa (OoA) and across Eurasia provides a unique opportunity to examine the impacts of genetic selection as humans adapted to multiple new environments. Analysis of ancient Eurasian genomic datasets (~1,000 to 45,000 y old) reveals signatures of strong selection, including at least 57 hard sweeps after the initial AMH movement OoA, which have been obscured in modern populations by extensive admixture during the Holocene. The spatiotemporal patterns of these hard sweeps provide a means to reconstruct early AMH population dispersals OoA. We identify a previously unsuspected extended period of genetic adaptation lasting ~30,000 y, potentially in the Arabian Peninsula area, prior to a major Neandertal genetic introgression and subsequent rapid dispersal across Eurasia as far as Australia. Consistent functional targets of selection initiated during this period, which we term the Arabian Standstill, include loci involved in the regulation of fat storage, neural development, skin physiology, and cilia function. Similar adaptive signatures are also evident in introgressed archaic hominin loci and modern Arctic human groups, and we suggest that this signal represents selection for cold adaptation. Surprisingly, many of the candidate selected loci across these groups appear to directly interact and coordinately regulate biological processes, with a number associated with major modern diseases including the ciliopathies, metabolic syndrome, and neurodegenerative disorders. This expands the potential for ancestral human adaptation to directly impact modern diseases, providing a platform for evolutionary medicine.
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Affiliation(s)
- Raymond Tobler
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, SA5005, Australia
| | - Yassine Souilmi
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, SA5005, Australia
- Environment Institute, The University of Adelaide, Adelaide, SA5005, Australia
| | - Christian D. Huber
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, SA5005, Australia
| | - Nigel Bean
- Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers, The University of Adelaide, Adelaide, SA5005, Australia
- School of Mathematical Sciences, The University of Adelaide, Adelaide, SA5005, Australia
| | - Chris S. M. Turney
- Division of Research, University of Technology Sydney, Ultimo, NSW2007, Australia
| | - Shane T. Grey
- School of Biotechnology and Biomolecular Sciences, Faculty of Science, University of New South Wales, Sydney, NSW2052, Australia
- Transplantation Immunology Group, Translation Science Pillar, Garvan Institute of Medical Research, Darlinghurst, NSW2010, Australia
| | - Alan Cooper
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, SA5005, Australia
- Blue Sky Genetics, Ashton, SA5137, Australia
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10
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Pandey D, Harris M, Garud NR, Narasimhan VM. Understanding natural selection in Holocene Europe using multi-locus genotype identity scans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.24.538113. [PMID: 37163039 PMCID: PMC10168228 DOI: 10.1101/2023.04.24.538113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Ancient DNA (aDNA) has been a revolutionary technology in understanding human history but has not been used extensively to study natural selection as large sample sizes to study allele frequency changes over time have thus far not been available. Here, we examined a time transect of 708 published samples over the past 7,000 years of European history using multi-locus genotype-based selection scans. As aDNA data is affected by high missingness, ascertainment bias, DNA damage, random allele calling, and is unphased, we first validated our selection scan, G 12 a n c i e n t , on simulated data resembling aDNA under a demographic model that captures broad features of the allele frequency spectrum of European genomes as well as positive controls that have been previously identified and functionally validated in modern European datasets on data from ancient individuals from time periods very close to the present time. We then applied our statistic to the aDNA time transect to detect and resolve the timing of natural selection occurring genome wide and found several candidates of selection across the different time periods that had not been picked up by selection scans using single SNP allele frequency approaches. In addition, enrichment analysis discovered multiple categories of complex traits that might be under adaptation across these periods. Our results demonstrate the utility of applying different types of selection scans to aDNA to uncover putative selection signals at loci in the ancient past that might have been masked in modern samples.
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Affiliation(s)
- Devansh Pandey
- Department of Integrative Biology, The University of Texas at Austin
| | - Mariana Harris
- Department of Computational Medicine, University of California, Los Angeles
| | - Nandita R Garud
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles
- Department of Human Genetics, University of California, Los Angeles
| | - Vagheesh M Narasimhan
- Department of Integrative Biology, The University of Texas at Austin
- Department of Statistics and Data Science, The University of Texas at Austin
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Wegmann D, Eckel R. Human evolution: When admixture met selection. Curr Biol 2023; 33:R259-R261. [PMID: 37040705 DOI: 10.1016/j.cub.2023.02.077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/13/2023]
Abstract
Admixture has been a major force during human evolution. Two new studies using ancient DNA now show how two key admixture events in the evolutionary history of Europeans altered their adaptive trajectories and facilitated rapid evolution.
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Affiliation(s)
- Daniel Wegmann
- Department of Biology, University of Fribourg, 1700 Fribourg, Switzerland; Swiss Institute of Bioinformatics, 1700 Fribourg, Switzerland.
| | - Raphael Eckel
- Department of Biology, University of Fribourg, 1700 Fribourg, Switzerland; Swiss Institute of Bioinformatics, 1700 Fribourg, Switzerland
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Davy T, Ju D, Mathieson I, Skoglund P. Hunter-gatherer admixture facilitated natural selection in Neolithic European farmers. Curr Biol 2023; 33:1365-1371.e3. [PMID: 36963383 PMCID: PMC10153476 DOI: 10.1016/j.cub.2023.02.049] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 11/17/2022] [Accepted: 02/15/2023] [Indexed: 03/26/2023]
Abstract
Ancient DNA has revealed multiple episodes of admixture in human prehistory during geographic expansions associated with cultural innovations. One important example is the expansion of Neolithic agricultural groups out of the Near East into Europe and their consequent admixture with Mesolithic hunter-gatherers.1,2,3,4 Ancient genomes from this period provide an opportunity to study the role of admixture in providing new genetic variation for selection to act upon, and also to identify genomic regions that resisted hunter-gatherer introgression and may thus have contributed to agricultural adaptations. We used genome-wide DNA from 677 individuals spanning Mesolithic and Neolithic Europe to infer ancestry deviations in the genomes of admixed individuals and to test for natural selection after admixture by testing for deviations from a genome-wide null distribution. We find that the region around the pigmentation-associated gene SLC24A5 shows the greatest overrepresentation of Neolithic local ancestry in the genome (|Z| = 3.46). In contrast, we find the greatest overrepresentation of Mesolithic ancestry across the major histocompatibility complex (MHC; |Z| = 4.21), a major immunity locus, which also shows allele frequency deviations indicative of selection following admixture (p = 1 × 10-56). This could reflect negative frequency-dependent selection on MHC alleles common in Neolithic populations or that Mesolithic alleles were positively selected for and facilitated adaptation in Neolithic populations to pathogens or other environmental factors. Our study extends previous results that highlight immune function and pigmentation as targets of adaptation in more recent populations to selection processes in the Stone Age.
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Affiliation(s)
- Tom Davy
- Ancient Genomics Laboratory, Francis Crick Institute, 1 Midland Road, NW1 1AT London, UK.
| | - Dan Ju
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, 415 Curie Blvd, Philadelphia, PA 19104, USA
| | - Iain Mathieson
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, 415 Curie Blvd, Philadelphia, PA 19104, USA
| | - Pontus Skoglund
- Ancient Genomics Laboratory, Francis Crick Institute, 1 Midland Road, NW1 1AT London, UK.
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Souilmi Y, Tobler R, Johar A, Williams M, Grey ST, Schmidt J, Teixeira JC, Rohrlach A, Tuke J, Johnson O, Gower G, Turney C, Cox M, Cooper A, Huber CD. Admixture has obscured signals of historical hard sweeps in humans. Nat Ecol Evol 2022; 6:2003-2015. [PMID: 36316412 PMCID: PMC9715430 DOI: 10.1038/s41559-022-01914-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Accepted: 09/16/2022] [Indexed: 11/06/2022]
Abstract
The role of natural selection in shaping biological diversity is an area of intense interest in modern biology. To date, studies of positive selection have primarily relied on genomic datasets from contemporary populations, which are susceptible to confounding factors associated with complex and often unknown aspects of population history. In particular, admixture between diverged populations can distort or hide prior selection events in modern genomes, though this process is not explicitly accounted for in most selection studies despite its apparent ubiquity in humans and other species. Through analyses of ancient and modern human genomes, we show that previously reported Holocene-era admixture has masked more than 50 historic hard sweeps in modern European genomes. Our results imply that this canonical mode of selection has probably been underappreciated in the evolutionary history of humans and suggest that our current understanding of the tempo and mode of selection in natural populations may be inaccurate.
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Affiliation(s)
- Yassine Souilmi
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia.
| | - Raymond Tobler
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia.
- Evolution of Cultural Diversity Initiative, Australian National University, Canberra, Australian Capital Territory, Australia.
| | - Angad Johar
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia.
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA.
| | - Matthew Williams
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia
| | - Shane T Grey
- Transplantation Immunology Group, Immunology Division, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
- St Vincent's Clinical School, Faculty of Medicine, UNSW, Darlinghurst, New South Wales, Australia
| | - Joshua Schmidt
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia
| | - João C Teixeira
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia
| | - Adam Rohrlach
- ARC Centre of Excellence for Mathematical and Statistical Frontiers, The University of Adelaide, Adelaide, South Australia, Australia
- Department of Archaeogenetics, Max Planck Institute for the Science of Human History, Jena, Germany
| | - Jonathan Tuke
- ARC Centre of Excellence for Mathematical and Statistical Frontiers, The University of Adelaide, Adelaide, South Australia, Australia
- School of Mathematical Sciences, The University of Adelaide, Adelaide, South Australia, Australia
| | - Olivia Johnson
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia
| | - Graham Gower
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia
| | - Chris Turney
- Chronos 14Carbon-Cycle Facility and Earth and Sustainability Science Research Centre, University of New South Wales, Sydney, New South Wales, Australia
| | - Murray Cox
- Statistics and Bioinformatics Group, School of Fundamental Sciences, Massey University, Palmerston North, New Zealand
| | - Alan Cooper
- South Australian Museum, Adelaide, South Australia, Australia.
- BlueSky Genetics, Ashton, South Australia, Australia.
| | - Christian D Huber
- Australian Centre for Ancient DNA, The University of Adelaide, Adelaide, South Australia, Australia.
- Department of Biology, Penn State University, University Park, PA, USA.
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