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Moorjani P, Hellenthal G. Methods for Assessing Population Relationships and History Using Genomic Data. Annu Rev Genomics Hum Genet 2023; 24:305-332. [PMID: 37220313 PMCID: PMC11040641 DOI: 10.1146/annurev-genom-111422-025117] [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] [Indexed: 05/25/2023]
Abstract
Genetic data contain a record of our evolutionary history. The availability of large-scale datasets of human populations from various geographic areas and timescales, coupled with advances in the computational methods to analyze these data, has transformed our ability to use genetic data to learn about our evolutionary past. Here, we review some of the widely used statistical methods to explore and characterize population relationships and history using genomic data. We describe the intuition behind commonly used approaches, their interpretation, and important limitations. For illustration, we apply some of these techniques to genome-wide autosomal data from 929 individuals representing 53 worldwide populations that are part of the Human Genome Diversity Project. Finally, we discuss the new frontiers in genomic methods to learn about population history. In sum, this review highlights the power (and limitations) of DNA to infer features of human evolutionary history, complementing the knowledge gleaned from other disciplines, such as archaeology, anthropology, and linguistics.
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Affiliation(s)
- Priya Moorjani
- Department of Molecular and Cell Biology and Center for Computational Biology, University of California, Berkeley, California, USA;
| | - Garrett Hellenthal
- UCL Genetics Institute and Research Department of Genetics, Evolution, and Environment, University College London, London, United Kingdom;
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2
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Tournebize R, Chu G, Moorjani P. Reconstructing the history of founder events using genome-wide patterns of allele sharing across individuals. PLoS Genet 2022; 18:e1010243. [PMID: 35737729 PMCID: PMC9223333 DOI: 10.1371/journal.pgen.1010243] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2022] [Accepted: 05/08/2022] [Indexed: 11/30/2022] Open
Abstract
Founder events play a critical role in shaping genetic diversity, fitness and disease risk in a population. Yet our understanding of the prevalence and distribution of founder events in humans and other species remains incomplete, as most existing methods require large sample sizes or phased genomes. Thus, we developed ASCEND that measures the correlation in allele sharing between pairs of individuals across the genome to infer the age and strength of founder events. We show that ASCEND can reliably estimate the parameters of founder events under a range of demographic scenarios. We then apply ASCEND to two species with contrasting evolutionary histories: ~460 worldwide human populations and ~40 modern dog breeds. In humans, we find that over half of the analyzed populations have evidence for recent founder events, associated with geographic isolation, modes of sustenance, or cultural practices such as endogamy. Notably, island populations have lower population sizes than continental groups and most hunter-gatherer, nomadic and indigenous groups have evidence of recent founder events. Many present-day groups––including Native Americans, Oceanians and South Asians––have experienced more extreme founder events than Ashkenazi Jews who have high rates of recessive diseases due their known history of founder events. Using ancient genomes, we show that the strength of founder events differs markedly across geographic regions and time––with three major founder events related to the peopling of Americas and a trend in decreasing strength of founder events in Europe following the Neolithic transition and steppe migrations. In dogs, we estimate extreme founder events in most breeds that occurred in the last 25 generations, concordant with the establishment of many dog breeds during the Victorian times. Our analysis highlights a widespread history of founder events in humans and dogs and elucidates some of the demographic and cultural practices related to these events. A founder event occurs when small numbers of ancestral individuals give rise to a large fraction of the population. Founder events reduce genetic variation and increase the risk of recessive diseases. Despite their importance in evolutionary and disease studies, we still only have a limited comprehension of their prevalence and properties in humans and other species, as most existing methods require large sample sizes or phased genomes. Here, we present a flexible method, ASCEND, to infer the timing and the strength of founder events that is suitable for sparse datasets with few samples or limited coverage. ASCEND provides reliable estimates across a wide range of demographic scenarios. By applying it to data from two species (humans and dogs), we document a widespread history of recent founder events in both species and provide insights about the demographic processes related to these events. Our analysis helps to identify groups with strong founder events that should be prioritized for future studies as they offer a unique opportunity for biological discovery and reducing disease burden through mapping of recessive disease-causing genes and pathways, as previously shown in studies of Ashkenazi Jews and Finns.
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Affiliation(s)
- Rémi Tournebize
- Department of Molecular and Cell Biology, University of California, Berkeley, California, United States of America
- Center for Computational Biology, University of California, Berkeley, California, United States of America
- * E-mail: (RT); (PM)
| | - Gillian Chu
- Department of Electrical Engineering and Computer Science, University of California, Berkeley, California, United States of America
| | - Priya Moorjani
- Department of Molecular and Cell Biology, University of California, Berkeley, California, United States of America
- Center for Computational Biology, University of California, Berkeley, California, United States of America
- * E-mail: (RT); (PM)
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Hernández CL, Pita G, Cavadas B, López S, Sánchez-Martínez LJ, Dugoujon JM, Novelletto A, Cuesta P, Pereira L, Calderón R. Human Genomic Diversity Where the Mediterranean Joins the Atlantic. Mol Biol Evol 2021; 37:1041-1055. [PMID: 31816048 PMCID: PMC7086172 DOI: 10.1093/molbev/msz288] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Throughout the past few years, a lively debate emerged about the timing and magnitude of the human migrations between the Iberian Peninsula and the Maghreb. Several pieces of evidence, including archaeological, anthropological, historical, and genetic data, have pointed to a complex and intermingled evolutionary history in the western Mediterranean area. To study to what extent connections across the Strait of Gibraltar and surrounding areas have shaped the present-day genomic diversity of its populations, we have performed a screening of 2.5 million single-nucleotide polymorphisms in 142 samples from southern Spain, southern Portugal, and Morocco. We built comprehensive data sets of the studied area and we implemented multistep bioinformatic approaches to assess population structure, demographic histories, and admixture dynamics. Both local and global ancestry inference showed an internal substructure in the Iberian Peninsula, mainly linked to a differential African ancestry. Western Iberia, from southern Portugal to Galicia, constituted an independent cluster within Iberia characterized by an enriched African genomic input. Migration time modeling showed recent historic dates for the admixture events occurring both in Iberia and in the North of Africa. However, an integrative vision of both paleogenomic and modern DNA data allowed us to detect chronological transitions and population turnovers that could be the result of transcontinental migrations dating back from Neolithic times. The present contribution aimed to fill the gaps in the modern human genomic record of a key geographic area, where the Mediterranean and the Atlantic come together.
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Affiliation(s)
- Candela L Hernández
- Departamento de Biodiversidad, Ecología y Evolución, Facultad de Biología, Universidad Complutense, Madrid, Spain
| | - Guillermo Pita
- Human Genotyping Unit-CeGen, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Bruno Cavadas
- i3S, Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal.,IPATIMUP-Instituto de Patologia e Imunologia Molecular, Universidade do Porto, Porto, Portugal
| | - Saioa López
- UCL Cancer Institute, London, United Kingdom
| | - Luis J Sánchez-Martínez
- Departamento de Biodiversidad, Ecología y Evolución, Facultad de Biología, Universidad Complutense, Madrid, Spain
| | - Jean-Michel Dugoujon
- CNRS UMR 5288 Laboratoire d'Anthropologie Moléculaire et d'Imagerie de Synthèse (AMIS), Université Paul Sabatier Toulouse III, Toulouse, France
| | | | - Pedro Cuesta
- Centro de Proceso de Datos, Universidad Complutense, Madrid, Spain
| | - Luisa Pereira
- i3S, Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal.,IPATIMUP-Instituto de Patologia e Imunologia Molecular, Universidade do Porto, Porto, Portugal
| | - Rosario Calderón
- Departamento de Biodiversidad, Ecología y Evolución, Facultad de Biología, Universidad Complutense, Madrid, Spain
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Agrawal A, Chiu AM, Le M, Halperin E, Sankararaman S. Scalable probabilistic PCA for large-scale genetic variation data. PLoS Genet 2020; 16:e1008773. [PMID: 32469896 PMCID: PMC7286535 DOI: 10.1371/journal.pgen.1008773] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Revised: 06/10/2020] [Accepted: 04/09/2020] [Indexed: 01/04/2023] Open
Abstract
Principal component analysis (PCA) is a key tool for understanding population structure and controlling for population stratification in genome-wide association studies (GWAS). With the advent of large-scale datasets of genetic variation, there is a need for methods that can compute principal components (PCs) with scalable computational and memory requirements. We present ProPCA, a highly scalable method based on a probabilistic generative model, which computes the top PCs on genetic variation data efficiently. We applied ProPCA to compute the top five PCs on genotype data from the UK Biobank, consisting of 488,363 individuals and 146,671 SNPs, in about thirty minutes. To illustrate the utility of computing PCs in large samples, we leveraged the population structure inferred by ProPCA within White British individuals in the UK Biobank to identify several novel genome-wide signals of recent putative selection including missense mutations in RPGRIP1L and TLR4. Principal component analysis is a commonly used technique for understanding population structure and genetic variation. With the advent of large-scale datasets that contain the genetic information of hundreds of thousands of individuals, there is a need for methods that can compute principal components (PCs) with scalable computational and memory requirements. In this study, we present ProPCA, a highly scalable statistical method to compute genetic PCs efficiently. We systematically evaluate the accuracy and scalability of our method on large-scale simulated data and apply it to the UK Biobank. Leveraging the population structure inferred by ProPCA within the White British individuals in the UK Biobank, we identify several novel signals of putative recent selection.
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Affiliation(s)
- Aman Agrawal
- Department of Computer Science, Indian Institute of Technology, Delhi, India
| | - Alec M. Chiu
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, California, United States of America
| | - Minh Le
- Department of Computer Science, University of California, Los Angeles, California, United States of America
| | - Eran Halperin
- Department of Computer Science, University of California, Los Angeles, California, United States of America
- Department of Human Genetics, University of California, Los Angeles, California, United States of America
- Department of Anesthesiology and Perioperative Medicine, University of California, Los Angeles, California, United States of America
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, California, United States of America
- Institute of Precision Health, University of California, Los Angeles, California, United States of America
| | - Sriram Sankararaman
- Department of Computer Science, University of California, Los Angeles, California, United States of America
- Department of Human Genetics, University of California, Los Angeles, California, United States of America
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, California, United States of America
- * E-mail:
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5
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Castro-Santos P, Verdugo RA, Alonso-Arias R, Gutiérrez MA, Suazo J, Aguillón JC, Olloquequi J, Pinochet C, Lucia A, Quiñones LA, Díaz-Peña R. Association analysis in a Latin American population revealed ethnic differences in rheumatoid arthritis-associated SNPs in Caucasian and Asian populations. Sci Rep 2020; 10:7879. [PMID: 32398702 PMCID: PMC7217883 DOI: 10.1038/s41598-020-64659-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2018] [Accepted: 04/08/2020] [Indexed: 11/17/2022] Open
Abstract
Large genome-wide association studies (GWAS) have increased our knowledge of the genetic risk factors of rheumatoid arthritis (RA). However, little is known about genetic susceptibility in populations with a large admixture of Amerindian ancestry. The aim of the present study was to test the generalizability of previously reported RA loci in a Latin American (LA) population with admixed ancestry. We selected 128 single nucleotide polymorphisms (SNPs) in linkage equilibrium, with high association to RA in multiple populations of non-Amerindian origin. Genotyping of 118 SNPs was performed in 313 RA patients/487 healthy control subjects by mid-density arrays of polymerase chain reaction (PCR). Some of the identified associations were validated in an additional cohort (250 cases/290 controls). One marker, the SNP rs2451258, located upstream of T Cell Activation RhoGTPase Activating Protein (TAGAP) gene, showed significant association with RA (p = 5 × 10-3), whereas 18 markers exhibited suggestive associations (p < 0.05). Haplotype testing showed association of some groups of adjacent SNPs around the signal transducer and activator of transcription 4 (STAT4) gene (p = 9.82 × 10-3 to 2.04 × 10-3) with RA. Our major finding was little replication of previously reported genetic associations with RA. These results suggest that performing GWAS and admixture mapping in LA populations has the potential to reveal novel loci associated with RA. This in turn might help to gain insight into the 'pathogenomics' of this disease and to explore trans-population differences for RA in general.
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Affiliation(s)
- P Castro-Santos
- Facultad de Ciencias de la Salud, Universidad Autónoma de Chile, Talca, Chile
- Inmunología, Centro de Investigaciones Biomédicas (CINBIO), Universidad de Vigo, Vigo, Spain
| | - R A Verdugo
- Programa de Genética Humana, ICBM, Facultad de Medicina, Universidad de Chile, Santiago, Chile
- Departamento de Oncología Básico Clínica, Facultad de Medicina, Universidad de Chile, Santiago, Chile
| | - R Alonso-Arias
- Facultad de Ciencias de la Salud, Universidad Autónoma de Chile, Talca, Chile
- Immunology Department, Hospital Universitario Central de Asturias, Oviedo, Spain
| | - M A Gutiérrez
- Rheumatology, Almirante Nef Naval Hospital, Viña del Mar, Valparaíso, Chile
- Valparaíso University, Viña del Mar, Valparaíso, Chile
| | - J Suazo
- Instituto de Investigación en Ciencias Odontológicas, Facultad de Odontología, Universidad de Chile, Santiago, Chile
| | - J C Aguillón
- Immune Regulation and Tolerance Research Group, Programa de Inmunología, ICBM, Facultad de Medicina, Universidad de Chile, Santiago, Chile
| | - J Olloquequi
- Facultad de Ciencias de la Salud, Universidad Autónoma de Chile, Talca, Chile
| | - C Pinochet
- Hospital Regional de Talca, Talca, Chile
| | - A Lucia
- Universidad Europea de Madrid (Faculty of Sports Sciences) and Research Institute Hospital 12 de Octubre ('i + 12'), Madrid, Spain
| | - L A Quiñones
- Laboratory of Chemical Carcinogenesis and Pharmacogenetics, Department de Basic-Clinical Oncology, Faculty of Medicine, University of Chile, Santiago, Chile.
- Latin American Network for Implementation and Validation of Clinical Pharmacogenomics Guidelines (RELIVAF-CYTED), Madrid, Spain.
| | - R Díaz-Peña
- Facultad de Ciencias de la Salud, Universidad Autónoma de Chile, Talca, Chile.
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Selecting among Alternative Scenarios of Human Evolution by Simulated Genetic Gradients. Genes (Basel) 2018; 9:genes9100506. [PMID: 30340387 PMCID: PMC6210830 DOI: 10.3390/genes9100506] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2018] [Revised: 10/11/2018] [Accepted: 10/16/2018] [Indexed: 11/16/2022] Open
Abstract
Selecting among alternative scenarios of human evolution is nowadays a common methodology to investigate the history of our species. This strategy is usually based on computer simulations of genetic data under different evolutionary scenarios, followed by a fitting of the simulated data with the real data. A recent trend in the investigation of ancestral evolutionary processes of modern humans is the application of genetic gradients as a measure of fitting, since evolutionary processes such as range expansions, range contractions, and population admixture (among others) can lead to different genetic gradients. In addition, this strategy allows the analysis of the genetic causes of the observed genetic gradients. Here, we review recent findings on the selection among alternative scenarios of human evolution based on simulated genetic gradients, including pros and cons. First, we describe common methodologies to simulate genetic gradients and apply them to select among alternative scenarios of human evolution. Next, we review previous studies on the influence of range expansions, population admixture, last glacial period, and migration with long-distance dispersal on genetic gradients for some regions of the world. Finally, we discuss this analytical approach, including technical limitations, required improvements, and advice. Although here we focus on human evolution, this approach could be extended to study other species.
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Retshabile G, Mlotshwa BC, Williams L, Mwesigwa S, Mboowa G, Huang Z, Rustagi N, Swaminathan S, Katagirya E, Kyobe S, Wayengera M, Kisitu GP, Kateete DP, Wampande EM, Maplanka K, Kasvosve I, Pettitt ED, Matshaba M, Nsangi B, Marape M, Tsimako-Johnstone M, Brown CW, Yu F, Kekitiinwa A, Joloba M, Mpoloka SW, Mardon G, Anabwani G, Hanchard NA. Whole-Exome Sequencing Reveals Uncaptured Variation and Distinct Ancestry in the Southern African Population of Botswana. Am J Hum Genet 2018; 102:731-743. [PMID: 29706352 DOI: 10.1016/j.ajhg.2018.03.010] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2017] [Accepted: 02/26/2018] [Indexed: 01/08/2023] Open
Abstract
Large-scale, population-based genomic studies have provided a context for modern medical genetics. Among such studies, however, African populations have remained relatively underrepresented. The breadth of genetic diversity across the African continent argues for an exploration of local genomic context to facilitate burgeoning disease mapping studies in Africa. We sought to characterize genetic variation and to assess population substructure within a cohort of HIV-positive children from Botswana-a Southern African country that is regionally underrepresented in genomic databases. Using whole-exome sequencing data from 164 Batswana and comparisons with 150 similarly sequenced HIV-positive Ugandan children, we found that 13%-25% of variation observed among Batswana was not captured by public databases. Uncaptured variants were significantly enriched (p = 2.2 × 10-16) for coding variants with minor allele frequencies between 1% and 5% and included predicted-damaging non-synonymous variants. Among variants found in public databases, corresponding allele frequencies varied widely, with Botswana having significantly higher allele frequencies among rare (<1%) pathogenic and damaging variants. Batswana clustered with other Southern African populations, but distinctly from 1000 Genomes African populations, and had limited evidence for admixture with extra-continental ancestries. We also observed a surprising lack of genetic substructure in Botswana, despite multiple tribal ethnicities and language groups, alongside a higher degree of relatedness than purported founder populations from the 1000 Genomes project. Our observations reveal a complex, but distinct, ancestral history and genomic architecture among Batswana and suggest that disease mapping within similar Southern African populations will require a deeper repository of genetic variation and allelic dependencies than presently exists.
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Affiliation(s)
- Gaone Retshabile
- Department of Biological Sciences, University of Botswana, Gaborone, Botswana
| | - Busisiwe C Mlotshwa
- Department of Biological Sciences, University of Botswana, Gaborone, Botswana
| | - Lesedi Williams
- Department of Biological Sciences, University of Botswana, Gaborone, Botswana
| | - Savannah Mwesigwa
- Department of Medical Microbiology, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Gerald Mboowa
- Department of Medical Microbiology, College of Health Sciences, Makerere University, Kampala, Uganda; Department of Immunology and Molecular Biology, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Zhuoyi Huang
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Navin Rustagi
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Shanker Swaminathan
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; USDA/ARS/Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Eric Katagirya
- Department of Medical Microbiology, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Samuel Kyobe
- Department of Medical Microbiology, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Misaki Wayengera
- Department of Immunology and Molecular Biology, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Grace P Kisitu
- Baylor College of Medicine Children's Foundation, Kampala, Uganda
| | - David P Kateete
- Department of Medical Microbiology, College of Health Sciences, Makerere University, Kampala, Uganda; Department of Immunology and Molecular Biology, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Eddie M Wampande
- Department of Medical Microbiology, College of Health Sciences, Makerere University, Kampala, Uganda; Department of Bio-molecular Resources, College of Veterinary Medicine, Makerere University, Kampala, Uganda
| | - Koketso Maplanka
- Department of Biological Sciences, University of Botswana, Gaborone, Botswana
| | - Ishmael Kasvosve
- Department of Medical Laboratory Sciences, University of Botswana, Gaborone, Botswana
| | - Edward D Pettitt
- Botswana-Baylor Children's Clinical Centre of Excellence, Gaborone, Botswana
| | - Mogomotsi Matshaba
- Botswana-Baylor Children's Clinical Centre of Excellence, Gaborone, Botswana; Pediatric Retrovirology, Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Betty Nsangi
- Baylor College of Medicine Children's Foundation, Kampala, Uganda
| | - Marape Marape
- Botswana-Baylor Children's Clinical Centre of Excellence, Gaborone, Botswana
| | | | - Chester W Brown
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; University of Tennessee Health Science Center, Memphis, TN 38105, USA
| | - Fuli Yu
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Adeodata Kekitiinwa
- Baylor College of Medicine Children's Foundation, Kampala, Uganda; Pediatric Retrovirology, Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Moses Joloba
- Department of Medical Microbiology, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Sununguko W Mpoloka
- Department of Biological Sciences, University of Botswana, Gaborone, Botswana
| | - Graeme Mardon
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Department of Pathology and Immunology, Baylor College of Medicine, Houston, TX 77030, USA
| | - Gabriel Anabwani
- Botswana-Baylor Children's Clinical Centre of Excellence, Gaborone, Botswana; Pediatric Retrovirology, Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Neil A Hanchard
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; USDA/ARS/Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX 77030, USA.
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8
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Martin HC, Batty EM, Hussin J, Westall P, Daish T, Kolomyjec S, Piazza P, Bowden R, Hawkins M, Grant T, Moritz C, Grutzner F, Gongora J, Donnelly P. Insights into Platypus Population Structure and History from Whole-Genome Sequencing. Mol Biol Evol 2018; 35:1238-1252. [PMID: 29688544 PMCID: PMC5913675 DOI: 10.1093/molbev/msy041] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
The platypus is an egg-laying mammal which, alongside the echidna, occupies a unique place in the mammalian phylogenetic tree. Despite widespread interest in its unusual biology, little is known about its population structure or recent evolutionary history. To provide new insights into the dispersal and demographic history of this iconic species, we sequenced the genomes of 57 platypuses from across the whole species range in eastern mainland Australia and Tasmania. Using a highly improved reference genome, we called over 6.7 M SNPs, providing an informative genetic data set for population analyses. Our results show very strong population structure in the platypus, with our sampling locations corresponding to discrete groupings between which there is no evidence for recent gene flow. Genome-wide data allowed us to establish that 28 of the 57 sampled individuals had at least a third-degree relative among other samples from the same river, often taken at different times. Taking advantage of a sampled family quartet, we estimated the de novo mutation rate in the platypus at 7.0 × 10-9/bp/generation (95% CI 4.1 × 10-9-1.2 × 10-8/bp/generation). We estimated effective population sizes of ancestral populations and haplotype sharing between current groupings, and found evidence for bottlenecks and long-term population decline in multiple regions, and early divergence between populations in different regions. This study demonstrates the power of whole-genome sequencing for studying natural populations of an evolutionarily important species.
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Affiliation(s)
- Hilary C Martin
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, United Kingdom
| | - Elizabeth M Batty
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Julie Hussin
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Portia Westall
- Sydney School of Veterinary Science, The University of Sydney, Sydney, NSW, Australia
| | - Tasman Daish
- Department of Genetics and Evolution, School of Biological Sciences, The University of Adelaide, Adelaide, SA, Australia
| | - Stephen Kolomyjec
- School of Biological Sciences, Lake Superior State University, Sault Sainte Marie, MI
| | - Paolo Piazza
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Department of Medicine, Faculty of Medicine, Imperial College, London, United Kingdom
| | - Rory Bowden
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | | | - Tom Grant
- School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, NSW, Australia
| | - Craig Moritz
- Research School of Biology and Centre for Biodiversity Analysis, The Australian National University, Acton, ACT, Australia
| | - Frank Grutzner
- Department of Genetics and Evolution, School of Biological Sciences, The University of Adelaide, Adelaide, SA, Australia
| | - Jaime Gongora
- Sydney School of Veterinary Science, The University of Sydney, Sydney, NSW, Australia
| | - Peter Donnelly
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Department of Statistics, University of Oxford, Oxford, United Kingdom
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9
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Triska P, Chekanov N, Stepanov V, Khusnutdinova EK, Kumar GPA, Akhmetova V, Babalyan K, Boulygina E, Kharkov V, Gubina M, Khidiyatova I, Khitrinskaya I, Khrameeva EE, Khusainova R, Konovalova N, Litvinov S, Marusin A, Mazur AM, Puzyrev V, Ivanoshchuk D, Spiridonova M, Teslyuk A, Tsygankova S, Triska M, Trofimova N, Vajda E, Balanovsky O, Baranova A, Skryabin K, Tatarinova TV, Prokhortchouk E. Between Lake Baikal and the Baltic Sea: genomic history of the gateway to Europe. BMC Genet 2017; 18:110. [PMID: 29297395 PMCID: PMC5751809 DOI: 10.1186/s12863-017-0578-3] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND The history of human populations occupying the plains and mountain ridges separating Europe from Asia has been eventful, as these natural obstacles were crossed westward by multiple waves of Turkic and Uralic-speaking migrants as well as eastward by Europeans. Unfortunately, the material records of history of this region are not dense enough to reconstruct details of population history. These considerations stimulate growing interest to obtain a genetic picture of the demographic history of migrations and admixture in Northern Eurasia. RESULTS We genotyped and analyzed 1076 individuals from 30 populations with geographical coverage spanning from Baltic Sea to Baikal Lake. Our dense sampling allowed us to describe in detail the population structure, provide insight into genomic history of numerous European and Asian populations, and significantly increase quantity of genetic data available for modern populations in region of North Eurasia. Our study doubles the amount of genome-wide profiles available for this region. We detected unusually high amount of shared identical-by-descent (IBD) genomic segments between several Siberian populations, such as Khanty and Ket, providing evidence of genetic relatedness across vast geographic distances and between speakers of different language families. Additionally, we observed excessive IBD sharing between Khanty and Bashkir, a group of Turkic speakers from Southern Urals region. While adding some weight to the "Finno-Ugric" origin of Bashkir, our studies highlighted that the Bashkir genepool lacks the main "core", being a multi-layered amalgamation of Turkic, Ugric, Finnish and Indo-European contributions, which points at intricacy of genetic interface between Turkic and Uralic populations. Comparison of the genetic structure of Siberian ethnicities and the geography of the region they inhabit point at existence of the "Great Siberian Vortex" directing genetic exchanges in populations across the Siberian part of Asia. Slavic speakers of Eastern Europe are, in general, very similar in their genetic composition. Ukrainians, Belarusians and Russians have almost identical proportions of Caucasus and Northern European components and have virtually no Asian influence. We capitalized on wide geographic span of our sampling to address intriguing question about the place of origin of Russian Starovers, an enigmatic Eastern Orthodox Old Believers religious group relocated to Siberia in seventeenth century. A comparative reAdmix analysis, complemented by IBD sharing, placed their roots in the region of the Northern European Plain, occupied by North Russians and Finno-Ugric Komi and Karelian people. Russians from Novosibirsk and Russian Starover exhibit ancestral proportions close to that of European Eastern Slavs, however, they also include between five to 10 % of Central Siberian ancestry, not present at this level in their European counterparts. CONCLUSIONS Our project has patched the hole in the genetic map of Eurasia: we demonstrated complexity of genetic structure of Northern Eurasians, existence of East-West and North-South genetic gradients, and assessed different inputs of ancient populations into modern populations.
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MESH Headings
- Algorithms
- Asia
- DNA
- Datasets as Topic
- Emigration and Immigration/history
- Ethnicity/genetics
- Europe
- Female
- Genetic Variation
- Genetics, Population
- Genotyping Techniques
- History, 15th Century
- History, 16th Century
- History, 17th Century
- History, 18th Century
- History, 19th Century
- History, 20th Century
- History, 21st Century
- History, Ancient
- History, Medieval
- Humans
- Male
- Russia
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Affiliation(s)
- Petr Triska
- Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - Nikolay Chekanov
- Federal State Institution "Federal Research Centre «Fundamentals of Biotechnology» of the Russian Academy of Sciences", Moscow, Russia
- "Genoanalytica" CJSC, Moscow, Russia
| | - Vadim Stepanov
- Institute of Medical Genetics, Tomsk National Medical Research Center, Russian Academy of Sciences, Siberian Branch, Tomsk, Russia
| | - Elza K Khusnutdinova
- Institute of Biochemistry and Genetics, Russian Academy of Sciences, Ufa Scientific Centre of Russian Academy of Sciences, Ufa, Russia
- Bashkir State University, Ufa, Russia
| | | | - Vita Akhmetova
- Institute of Biochemistry and Genetics, Russian Academy of Sciences, Ufa Scientific Centre of Russian Academy of Sciences, Ufa, Russia
| | - Konstantin Babalyan
- Moscow Institute of Physics and Technology, Department of Molecular and Bio-Physics, Moscow, Russia
| | | | - Vladimir Kharkov
- Institute of Medical Genetics, Tomsk National Medical Research Center, Russian Academy of Sciences, Siberian Branch, Tomsk, Russia
| | - Marina Gubina
- Institute of Cytology and Genetics, Russian Academy of Sciences, Siberian Branch, Novosibirsk, Russia
| | - Irina Khidiyatova
- Institute of Biochemistry and Genetics, Russian Academy of Sciences, Ufa Scientific Centre of Russian Academy of Sciences, Ufa, Russia
- Bashkir State University, Ufa, Russia
| | - Irina Khitrinskaya
- Institute of Medical Genetics, Tomsk National Medical Research Center, Russian Academy of Sciences, Siberian Branch, Tomsk, Russia
| | - Ekaterina E Khrameeva
- "Genoanalytica" CJSC, Moscow, Russia
- Skolkovo Institute of Science and Technology, Skolkovo Innovation Center, Moscow, Russia
| | - Rita Khusainova
- Institute of Biochemistry and Genetics, Russian Academy of Sciences, Ufa Scientific Centre of Russian Academy of Sciences, Ufa, Russia
- Bashkir State University, Ufa, Russia
| | | | - Sergey Litvinov
- Institute of Biochemistry and Genetics, Russian Academy of Sciences, Ufa Scientific Centre of Russian Academy of Sciences, Ufa, Russia
| | - Andrey Marusin
- Institute of Medical Genetics, Tomsk National Medical Research Center, Russian Academy of Sciences, Siberian Branch, Tomsk, Russia
| | - Alexandr M Mazur
- Federal State Institution "Federal Research Centre «Fundamentals of Biotechnology» of the Russian Academy of Sciences", Moscow, Russia
| | - Valery Puzyrev
- Institute of Medical Genetics, Tomsk National Medical Research Center, Russian Academy of Sciences, Siberian Branch, Tomsk, Russia
| | - Dinara Ivanoshchuk
- Institute of Cytology and Genetics, Russian Academy of Sciences, Siberian Branch, Novosibirsk, Russia
| | - Maria Spiridonova
- Institute of Medical Genetics, Tomsk National Medical Research Center, Russian Academy of Sciences, Siberian Branch, Tomsk, Russia
| | - Anton Teslyuk
- Moscow Institute of Physics and Technology, Department of Molecular and Bio-Physics, Moscow, Russia
| | - Svetlana Tsygankova
- Moscow Institute of Physics and Technology, Department of Molecular and Bio-Physics, Moscow, Russia
| | - Martin Triska
- Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - Natalya Trofimova
- Institute of Biochemistry and Genetics, Russian Academy of Sciences, Ufa Scientific Centre of Russian Academy of Sciences, Ufa, Russia
| | - Edward Vajda
- Department of Modern and Classical Languages, Western Washington University, Bellingham, WA, USA
| | - Oleg Balanovsky
- Research Centre for Medical Genetics, Moscow, Russia
- Vavilov Institute of General Genetics, Moscow, Russia
| | - Ancha Baranova
- Research Centre for Medical Genetics, Moscow, Russia
- School of Systems Biology, George Mason University, Fairfax, VA, USA
- Atlas Biomed Group, Moscow, Russia
| | - Konstantin Skryabin
- Federal State Institution "Federal Research Centre «Fundamentals of Biotechnology» of the Russian Academy of Sciences", Moscow, Russia
- Russian Scientific Centre "Kurchatov Institute", Moscow, Russia
- Department of Biology, Lomonosov Moscow State University, Moscow, Russia
| | - Tatiana V Tatarinova
- Vavilov Institute of General Genetics, Moscow, Russia.
- School of Systems Biology, George Mason University, Fairfax, VA, USA.
- Atlas Biomed Group, Moscow, Russia.
- Department of Biology, University of La Verne, La Verne, CA, USA.
- A. A. Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences, Moscow, Russia.
| | - Egor Prokhortchouk
- Federal State Institution "Federal Research Centre «Fundamentals of Biotechnology» of the Russian Academy of Sciences", Moscow, Russia.
- Department of Biology, Lomonosov Moscow State University, Moscow, Russia.
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10
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Quach H, Quintana-Murci L. Living in an adaptive world: Genomic dissection of the genus Homo and its immune response. J Exp Med 2017; 214:877-894. [PMID: 28351985 PMCID: PMC5379985 DOI: 10.1084/jem.20161942] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2016] [Revised: 02/14/2017] [Accepted: 03/06/2017] [Indexed: 12/14/2022] Open
Abstract
More than a decade after the sequencing of the human genome, a deluge of genome-wide population data are generating a portrait of human genetic diversity at an unprecedented level of resolution. Genomic studies have provided new insight into the demographic and adaptive history of our species, Homo sapiens, including its interbreeding with other hominins, such as Neanderthals, and the ways in which natural selection, in its various guises, has shaped genome diversity. These studies, combined with functional genomic approaches, such as the mapping of expression quantitative trait loci, have helped to identify genes, functions, and mechanisms of prime importance for host survival and involved in phenotypic variation and differences in disease risk. This review summarizes new findings in this rapidly developing field, focusing on the human immune response. We discuss the importance of defining the genetic and evolutionary determinants driving immune response variation, and highlight the added value of population genomic approaches in settings relevant to immunity and infection.
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Affiliation(s)
- Hélène Quach
- Human Evolutionary Genetics Unit, Department of Genomes and Genetics, Institut Pasteur, 75015 Paris, France.,Center of Bioinformatics, Biostatistics and Integrative Biology, Institut Pasteur, 75015 Paris, France.,Centre National de la Recherche Scientifique, URA3012, 75015 Paris, France
| | - Lluis Quintana-Murci
- Human Evolutionary Genetics Unit, Department of Genomes and Genetics, Institut Pasteur, 75015 Paris, France .,Center of Bioinformatics, Biostatistics and Integrative Biology, Institut Pasteur, 75015 Paris, France.,Centre National de la Recherche Scientifique, URA3012, 75015 Paris, France
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11
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Silva M, Oliveira M, Vieira D, Brandão A, Rito T, Pereira JB, Fraser RM, Hudson B, Gandini F, Edwards C, Pala M, Koch J, Wilson JF, Pereira L, Richards MB, Soares P. A genetic chronology for the Indian Subcontinent points to heavily sex-biased dispersals. BMC Evol Biol 2017; 17:88. [PMID: 28335724 PMCID: PMC5364613 DOI: 10.1186/s12862-017-0936-9] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2016] [Accepted: 03/14/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND India is a patchwork of tribal and non-tribal populations that speak many different languages from various language families. Indo-European, spoken across northern and central India, and also in Pakistan and Bangladesh, has been frequently connected to the so-called "Indo-Aryan invasions" from Central Asia ~3.5 ka and the establishment of the caste system, but the extent of immigration at this time remains extremely controversial. South India, on the other hand, is dominated by Dravidian languages. India displays a high level of endogamy due to its strict social boundaries, and high genetic drift as a result of long-term isolation which, together with a very complex history, makes the genetic study of Indian populations challenging. RESULTS We have combined a detailed, high-resolution mitogenome analysis with summaries of autosomal data and Y-chromosome lineages to establish a settlement chronology for the Indian Subcontinent. Maternal lineages document the earliest settlement ~55-65 ka (thousand years ago), and major population shifts in the later Pleistocene that explain previous dating discrepancies and neutrality violation. Whilst current genome-wide analyses conflate all dispersals from Southwest and Central Asia, we were able to tease out from the mitogenome data distinct dispersal episodes dating from between the Last Glacial Maximum to the Bronze Age. Moreover, we found an extremely marked sex bias by comparing the different genetic systems. CONCLUSIONS Maternal lineages primarily reflect earlier, pre-Holocene processes, and paternal lineages predominantly episodes within the last 10 ka. In particular, genetic influx from Central Asia in the Bronze Age was strongly male-driven, consistent with the patriarchal, patrilocal and patrilineal social structure attributed to the inferred pastoralist early Indo-European society. This was part of a much wider process of Indo-European expansion, with an ultimate source in the Pontic-Caspian region, which carried closely related Y-chromosome lineages, a smaller fraction of autosomal genome-wide variation and an even smaller fraction of mitogenomes across a vast swathe of Eurasia between 5 and 3.5 ka.
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Affiliation(s)
- Marina Silva
- Department of Biological Sciences, School of Applied Sciences, University of Huddersfield, Queensgate, Huddersfield, HD1 3DH, UK
| | - Marisa Oliveira
- i3S (Instituto de Investigação e Inovação em Saúde, Universidade do Porto), R. Alfredo Allen 208, 4200-135, Porto, Portugal.,IPATIMUP (Instituto de Patologia e Imunologia Molecular da Universidade do Porto), Rua Júlio Amaral de Carvalho 45, 4200-135, Porto, Portugal
| | - Daniel Vieira
- Department of Informatics, University of Minho, Campus de Gualtar, 4710-057, Braga, Portugal.,CBMA (Centre of Molecular and Environmental Biology), Department of Biology, University of Minho, Campus de Gualtar, 4710-057, Braga, Portugal
| | - Andreia Brandão
- i3S (Instituto de Investigação e Inovação em Saúde, Universidade do Porto), R. Alfredo Allen 208, 4200-135, Porto, Portugal.,IPATIMUP (Instituto de Patologia e Imunologia Molecular da Universidade do Porto), Rua Júlio Amaral de Carvalho 45, 4200-135, Porto, Portugal
| | - Teresa Rito
- i3S (Instituto de Investigação e Inovação em Saúde, Universidade do Porto), R. Alfredo Allen 208, 4200-135, Porto, Portugal.,Life and Health Sciences Research Institute (ICVS), School of Health Sciences, University of Minho, Campus de Gualtar, 4710-057, Braga, Portugal.,ICVS/3B's-PT Government Associate Laboratory, Braga/Guimarães, Portugal
| | - Joana B Pereira
- i3S (Instituto de Investigação e Inovação em Saúde, Universidade do Porto), R. Alfredo Allen 208, 4200-135, Porto, Portugal.,IPATIMUP (Instituto de Patologia e Imunologia Molecular da Universidade do Porto), Rua Júlio Amaral de Carvalho 45, 4200-135, Porto, Portugal
| | - Ross M Fraser
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland, UK.,Synpromics Ltd, Nine Edinburgh Bioquarter, Edinburgh, EH16 4UX, UK
| | - Bob Hudson
- Archaeology Department, University of Sydney, Sydney, NSW, 2006, Australia
| | - Francesca Gandini
- Department of Biological Sciences, School of Applied Sciences, University of Huddersfield, Queensgate, Huddersfield, HD1 3DH, UK
| | - Ceiridwen Edwards
- Department of Biological Sciences, School of Applied Sciences, University of Huddersfield, Queensgate, Huddersfield, HD1 3DH, UK
| | - Maria Pala
- Department of Biological Sciences, School of Applied Sciences, University of Huddersfield, Queensgate, Huddersfield, HD1 3DH, UK
| | - John Koch
- University of Wales Centre for Advanced Welsh and Celtic Studies, National Library of Wales, Aberystwyth, SY23 3HH, Wales, UK
| | - James F Wilson
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh, EH8 9AG, Scotland, UK.,MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, Scotland, UK
| | - Luísa Pereira
- i3S (Instituto de Investigação e Inovação em Saúde, Universidade do Porto), R. Alfredo Allen 208, 4200-135, Porto, Portugal.,IPATIMUP (Instituto de Patologia e Imunologia Molecular da Universidade do Porto), Rua Júlio Amaral de Carvalho 45, 4200-135, Porto, Portugal
| | - Martin B Richards
- Department of Biological Sciences, School of Applied Sciences, University of Huddersfield, Queensgate, Huddersfield, HD1 3DH, UK.
| | - Pedro Soares
- IPATIMUP (Instituto de Patologia e Imunologia Molecular da Universidade do Porto), Rua Júlio Amaral de Carvalho 45, 4200-135, Porto, Portugal. .,CBMA (Centre of Molecular and Environmental Biology), Department of Biology, University of Minho, Campus de Gualtar, 4710-057, Braga, Portugal.
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12
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Inference of the Distribution of Selection Coefficients for New Nonsynonymous Mutations Using Large Samples. Genetics 2017; 206:345-361. [PMID: 28249985 PMCID: PMC5419480 DOI: 10.1534/genetics.116.197145] [Citation(s) in RCA: 115] [Impact Index Per Article: 16.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2016] [Accepted: 02/14/2017] [Indexed: 12/23/2022] Open
Abstract
The distribution of fitness effects (DFE) has considerable importance in population genetics. To date, estimates of the DFE come from studies using a small number of individuals. Thus, estimates of the proportion of moderately to strongly deleterious new mutations may be unreliable because such variants are unlikely to be segregating in the data. Additionally, the true functional form of the DFE is unknown, and estimates of the DFE differ significantly between studies. Here we present a flexible and computationally tractable method, called Fit∂a∂i, to estimate the DFE of new mutations using the site frequency spectrum from a large number of individuals. We apply our approach to the frequency spectrum of 1300 Europeans from the Exome Sequencing Project ESP6400 data set, 1298 Danes from the LuCamp data set, and 432 Europeans from the 1000 Genomes Project to estimate the DFE of deleterious nonsynonymous mutations. We infer significantly fewer (0.38-0.84 fold) strongly deleterious mutations with selection coefficient |s| > 0.01 and more (1.24-1.43 fold) weakly deleterious mutations with selection coefficient |s| < 0.001 compared to previous estimates. Furthermore, a DFE that is a mixture distribution of a point mass at neutrality plus a gamma distribution fits better than a gamma distribution in two of the three data sets. Our results suggest that nearly neutral forces play a larger role in human evolution than previously thought.
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13
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Abstract
The wealth of available genetic information is allowing the reconstruction of human demographic and adaptive history. Demography and purifying selection affect the purge of rare, deleterious mutations from the human population, whereas positive and balancing selection can increase the frequency of advantageous variants, improving survival and reproduction in specific environmental conditions. In this review, I discuss how theoretical and empirical population genetics studies, using both modern and ancient DNA data, are a powerful tool for obtaining new insight into the genetic basis of severe disorders and complex disease phenotypes, rare and common, focusing particularly on infectious disease risk.
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Affiliation(s)
- Lluis Quintana-Murci
- Human Evolutionary Genetics Unit, Department of Genomes & Genetics, Institut Pasteur, Paris, 75015, France.
- Centre National de la Recherche Scientifique, URA3012, Paris, 75015, France.
- Center of Bioinformatics, Biostatistics and Integrative Biology, Institut Pasteur, Paris, 75015, France.
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14
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Novembre J, Peter BM. Recent advances in the study of fine-scale population structure in humans. Curr Opin Genet Dev 2016; 41:98-105. [PMID: 27662060 DOI: 10.1016/j.gde.2016.08.007] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2016] [Revised: 08/18/2016] [Accepted: 08/24/2016] [Indexed: 01/17/2023]
Abstract
Empowered by modern genotyping and large samples, population structure can be accurately described and quantified even when it only explains a fraction of a percent of total genetic variance. This is especially relevant and interesting for humans, where fine-scale population structure can both confound disease-mapping studies and reveal the history of migration and divergence that shaped our species' diversity. Here we review notable recent advances in the detection, use, and understanding of population structure. Our work addresses multiple areas where substantial progress is being made: improved statistics and models for better capturing differentiation, admixture, and the spatial distribution of variation; computational speed-ups that allow methods to scale to modern data; and advances in haplotypic modeling that have wide ranging consequences for the analysis of population structure. We conclude by outlining four important open challenges: the limitations of discrete population models, uncertainty in individual origins, the incorporation of both fine-scale structure and ancient DNA in parametric models, and the development of efficient computational tools, particularly for haplotype-based methods.
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Affiliation(s)
- John Novembre
- Department of Human Genetics, University of Chicago, IL 60636, United States; Department of Ecology and Evolutionary Biology, University of Chicago, IL 60636, United States
| | - Benjamin M Peter
- Department of Human Genetics, University of Chicago, IL 60636, United States
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15
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Shin Y, Jung HJ, Jung M, Yoo S, Subramaniyam S, Markkandan K, Kang JM, Rai R, Park J, Kim JJ. Discovery of Gene Sources for Economic Traits in Hanwoo by Whole-genome Resequencing. ASIAN-AUSTRALASIAN JOURNAL OF ANIMAL SCIENCES 2016; 29:1353-62. [PMID: 26954201 PMCID: PMC5003998 DOI: 10.5713/ajas.15.0760] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/10/2015] [Revised: 01/06/2016] [Accepted: 02/16/2016] [Indexed: 11/27/2022]
Abstract
Hanwoo, a Korean native cattle (Bos taurus coreana), has great economic value due to high meat quality. Also, the breed has genetic variations that are associated with production traits such as health, disease resistance, reproduction, growth as well as carcass quality. In this study, next generation sequencing technologies and the availability of an appropriate reference genome were applied to discover a large amount of single nucleotide polymorphisms (SNPs) in ten Hanwoo bulls. Analysis of whole-genome resequencing generated a total of 26.5 Gb data, of which 594,716,859 and 592,990,750 reads covered 98.73% and 93.79% of the bovine reference genomes of UMD 3.1 and Btau 4.6.1, respectively. In total, 2,473,884 and 2,402,997 putative SNPs were discovered, of which 1,095,922 (44.3%) and 982,674 (40.9%) novel SNPs were discovered against UMD3.1 and Btau 4.6.1, respectively. Among the SNPs, the 46,301 (UMD 3.1) and 28,613 SNPs (Btau 4.6.1) that were identified as Hanwoo-specific SNPs were included in the functional genes that may be involved in the mechanisms of milk production, tenderness, juiciness, marbling of Hanwoo beef and yellow hair. Most of the Hanwoo-specific SNPs were identified in the promoter region, suggesting that the SNPs influence differential expression of the regulated genes relative to the relevant traits. In particular, the non-synonymous (ns) SNPs found in CORIN, which is a negative regulator of Agouti, might be a causal variant to determine yellow hair of Hanwoo. Our results will provide abundant genetic sources of variation to characterize Hanwoo genetics and for subsequent breeding.
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Affiliation(s)
- Younhee Shin
- Codes Division, Insilicogen Inc., Yongin 446-908, Korea
| | - Ho-Jin Jung
- Codes Division, Insilicogen Inc., Yongin 446-908, Korea
| | - Myunghee Jung
- Codes Division, Insilicogen Inc., Yongin 446-908, Korea
| | - Seungil Yoo
- Codes Division, Insilicogen Inc., Yongin 446-908, Korea
| | | | | | - Jun-Mo Kang
- School of Biotechnology, Yeungnam University, Gyeongsan 712-749, Korea
| | - Rajani Rai
- School of Biotechnology, Yeungnam University, Gyeongsan 712-749, Korea
| | - Junhyung Park
- Codes Division, Insilicogen Inc., Yongin 446-908, Korea
| | - Jong-Joo Kim
- School of Biotechnology, Yeungnam University, Gyeongsan 712-749, Korea
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16
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Lozier JD, Jackson JM, Dillon ME, Strange JP. Population genomics of divergence among extreme and intermediate color forms in a polymorphic insect. Ecol Evol 2016; 6:1075-91. [PMID: 26811748 PMCID: PMC4722823 DOI: 10.1002/ece3.1928] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2015] [Revised: 12/08/2015] [Accepted: 12/09/2015] [Indexed: 01/01/2023] Open
Abstract
Geographic variation in insect coloration is among the most intriguing examples of rapid phenotypic evolution and provides opportunities to study mechanisms of phenotypic change and diversification in closely related lineages. The bumble bee Bombus bifarius comprises two geographically disparate color groups characterized by red‐banded and black‐banded abdominal pigmentation, but with a range of spatially and phenotypically intermediate populations across western North America. Microsatellite analyses have revealed that B. bifarius in the USA are structured into two major groups concordant with geography and color pattern, but also suggest ongoing gene flow among regional populations. In this study, we better resolve the relationships among major color groups to better understand evolutionary mechanisms promoting and maintaining such polymorphism. We analyze >90,000 and >25,000 single‐nucleotide polymorphisms derived from transcriptome (RNAseq) and double digest restriction site associated DNA sequencing (ddRAD), respectively, in representative samples from spatial and color pattern extremes in B. bifarius as well as phenotypic and geographic intermediates. Both ddRAD and RNAseq data illustrate substantial genome‐wide differentiation of the red‐banded (eastern) color form from both black‐banded (western) and intermediate (central) phenotypes and negligible differentiation among the latter populations, with no obvious admixture among bees from the two major lineages. Results thus indicate much stronger background differentiation among B. bifarius lineages than expected, highlighting potential challenges for revealing loci underlying color polymorphism from population genetic data alone. These findings will have significance for resolving taxonomic confusion in this species and in future efforts to investigate color‐pattern evolution in B. bifarius and other polymorphic bumble bee species.
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Affiliation(s)
- Jeffrey D Lozier
- Department of Biological Sciences University of Alabama Tuscaloosa Alabama
| | - Jason M Jackson
- Department of Biological Sciences University of Alabama Tuscaloosa Alabama
| | - Michael E Dillon
- Department of Zoology & Physiology and Program in Ecology University of Wyoming Laramie Wyoming
| | - James P Strange
- USDA-ARS Pollinating Insect Research Unit Utah State University Logan Utah
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17
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Pacifiplex : an ancestry-informative SNP panel centred on Australia and the Pacific region. Forensic Sci Int Genet 2016; 20:71-80. [DOI: 10.1016/j.fsigen.2015.10.003] [Citation(s) in RCA: 50] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2015] [Revised: 09/22/2015] [Accepted: 10/06/2015] [Indexed: 12/18/2022]
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18
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Behar DM, Metspalu M, Baran Y, Kopelman NM, Yunusbayev B, Gladstein A, Tzur S, Sahakyan H, Bahmanimehr A, Yepiskoposyan L, Tambets K, Khusnutdinova EK, Kushniarevich A, Balanovsky O, Balanovsky E, Kovacevic L, Marjanovic D, Mihailov E, Kouvatsi A, Triantaphyllidis C, King RJ, Semino O, Torroni A, Hammer MF, Metspalu E, Skorecki K, Rosset S, Halperin E, Villems R, Rosenberg NA. No evidence from genome-wide data of a Khazar origin for the Ashkenazi Jews. Hum Biol 2015; 85:859-900. [PMID: 25079123 DOI: 10.3378/027.085.0604] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/06/2013] [Indexed: 11/05/2022]
Abstract
The origin and history of the Ashkenazi Jewish population have long been of great interest, and advances in high-throughput genetic analysis have recently provided a new approach for investigating these topics. We and others have argued on the basis of genome-wide data that the Ashkenazi Jewish population derives its ancestry from a combination of sources tracing to both Europe and the Middle East. It has been claimed, however, through a reanalysis of some of our data, that a large part of the ancestry of the Ashkenazi population originates with the Khazars, a Turkic-speaking group that lived to the north of the Caucasus region ~1,000 years ago. Because the Khazar population has left no obvious modern descendants that could enable a clear test for a contribution to Ashkenazi Jewish ancestry, the Khazar hypothesis has been difficult to examine using genetics. Furthermore, because only limited genetic data have been available from the Caucasus region, and because these data have been concentrated in populations that are genetically close to populations from the Middle East, the attribution of any signal of Ashkenazi-Caucasus genetic similarity to Khazar ancestry rather than shared ancestral Middle Eastern ancestry has been problematic. Here, through integration of genotypes from newly collected samples with data from several of our past studies, we have assembled the largest data set available to date for assessment of Ashkenazi Jewish genetic origins. This data set contains genome-wide single-nucleotide polymorphisms in 1,774 samples from 106 Jewish and non-Jewish populations that span the possible regions of potential Ashkenazi ancestry: Europe, the Middle East, and the region historically associated with the Khazar Khaganate. The data set includes 261 samples from 15 populations from the Caucasus region and the region directly to its north, samples that have not previously been included alongside Ashkenazi Jewish samples in genomic studies. Employing a variety of standard techniques for the analysis of population-genetic structure, we found that Ashkenazi Jews share the greatest genetic ancestry with other Jewish populations and, among non-Jewish populations, with groups from Europe and the Middle East. No particular similarity of Ashkenazi Jews to populations from the Caucasus is evident, particularly populations that most closely represent the Khazar region. Thus, analysis of Ashkenazi Jews together with a large sample from the region of the Khazar Khaganate corroborates the earlier results that Ashkenazi Jews derive their ancestry primarily from populations of the Middle East and Europe, that they possess considerable shared ancestry with other Jewish populations, and that there is no indication of a significant genetic contribution either from within or from north of the Caucasus region.
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Affiliation(s)
- Doron M Behar
- Molecular Medicine Laboratory, Rambam Health Care Campus, Haifa, Israel AND Estonian Biocentre, Evolutionary Biology Group, Tartu, Estonia
| | - Mait Metspalu
- Estonian Biocentre, Evolutionary Biology Group, Tartu, Estonia AND Department of Evolutionary Biology, University of Tartu, Tartu, Estonia. AND Department of Integrative Biology, University of California, Berkeley, CA
| | - Yael Baran
- Blavatnik School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel
| | - Naama M Kopelman
- Porter School of Environmental Studies, Department of Zoology, Tel-Aviv University, Tel-Aviv, Israel
| | - Bayazit Yunusbayev
- Estonian Biocentre, Evolutionary Biology Group, Tartu, Estonia. AND Institute of Biochemistry and Genetics, Ufa Research Center, Russian Academy of Sciences, Ufa, Russia
| | | | - Shay Tzur
- Molecular Medicine Laboratory, Rambam Health Care Campus, Haifa, Israel
| | - Hovhannes Sahakyan
- Estonian Biocentre, Evolutionary Biology Group, Tartu, Estonia. AND Laboratory of Ethnogenomics, Institute of Molecular Biology, National Academy of Sciences, Yerevan, Armenia
| | - Ardeshir Bahmanimehr
- Laboratory of Ethnogenomics, Institute of Molecular Biology, National Academy of Sciences, Yerevan, Armenia
| | - Levon Yepiskoposyan
- Laboratory of Ethnogenomics, Institute of Molecular Biology, National Academy of Sciences, Yerevan, Armenia
| | | | - Elza K Khusnutdinova
- Estonian Biocentre, Evolutionary Biology Group, Tartu, Estonia. AND Institute of Biochemistry and Genetics, Ufa Research Center, Russian Academy of Sciences, Ufa, Russia. AND Department of Genetics and Fundamental Medicine, Bashkir State University, Ufa, Russia
| | | | - Oleg Balanovsky
- Vavilov Institute for General Genetics, Russian Academy of Sciences, Moscow, Russia. AND Research Centre for Medical Genetics, Russian Academy of Medical Sciences, Moscow, Russia
| | - Elena Balanovsky
- Vavilov Institute for General Genetics, Russian Academy of Sciences, Moscow, Russia. AND Research Centre for Medical Genetics, Russian Academy of Medical Sciences, Moscow, Russia
| | - Lejla Kovacevic
- Institute for Genetic Engineering and Biotechnology, Sarajevo, Bosnia and Herzegovina. AND Faculty of Pharmacy, University of Sarajevo, Sarajevo, Bosnia and Herzegovina
| | - Damir Marjanovic
- Institute for Genetic Engineering and Biotechnology, Sarajevo, Bosnia and Herzegovina. AND Genos doo, Zagreb, Croatia
| | | | - Anastasia Kouvatsi
- Department of Genetics, Development and Molecular Biology, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Costas Triantaphyllidis
- Department of Genetics, Development and Molecular Biology, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Roy J King
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA
| | - Ornella Semino
- Dipartimento di Biologia e Biotecnologie "Lazzaro Spallanzani," Università di Pavia, Pavia, Italy. AND Centro Interdipartimentale "Studi di Genere," Università di Pavia, Pavia, Italy
| | - Antonio Torroni
- Dipartimento di Biologia e Biotecnologie "Lazzaro Spallanzani," Università di Pavia, Pavia, Italy
| | - Michael F Hammer
- ARL Division of Biotechnology, University of Arizona, Tucson, AZ
| | - Ene Metspalu
- Department of Evolutionary Biology, University of Tartu, Tartu, Estonia
| | - Karl Skorecki
- Molecular Medicine Laboratory, Rambam Health Care Campus, Haifa, Israel. AND Ruth and Bruce Rappaport Faculty of Medicine and Research Institute, Technion-Israel Institute of Technology, Haifa, Israel
| | - Saharon Rosset
- Department of Statistics and Operations Research, School of Mathematical Sciences, Tel-Aviv University, Tel-Aviv, Israel
| | - Eran Halperin
- Blavatnik School of Computer Science, Tel-Aviv University, Tel-Aviv, Israel. AND Department of Molecular Microbiology and Biotechnology, George Wise Faculty of Life Science, Tel- Aviv University, Tel-Aviv, Israel. AND International Computer Science Institute, Berkeley, CA
| | - Richard Villems
- Estonian Biocentre, Evolutionary Biology Group, Tartu, Estonia. AND Department of Evolutionary Biology, University of Tartu, Tartu, Estonia. AND Estonian Academy of Sciences, Tallinn, Estonia
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Zhang L, Jia S, Plath M, Huang Y, Li C, Lei C, Zhao X, Chen H. Impact of Parental Bos taurus and Bos indicus Origins on Copy Number Variation in Traditional Chinese Cattle Breeds. Genome Biol Evol 2015; 7:2352-61. [PMID: 26260653 PMCID: PMC4558867 DOI: 10.1093/gbe/evv151] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Copy number variation (CNV) is an important component of genomic structural variation and plays a role not only in evolutionary diversification but also in domestication. Chinese cattle were derived from Bos taurus and Bos indicus, and several breeds presumably are of hybrid origin, but the evolution of CNV regions (CNVRs) has not yet been examined in this context. Here, we of CNVRs, mtDNA D-loop sequence variation, and Y-chromosomal single nucleotide polymorphisms to assess the impact of maternal and paternal B. taurus and B. indicus origins on the distribution of CNVRs in 24 Chinese domesticated bulls. We discovered 470 genome-wide CNVRs, only 72 of which were shared by all three Y-lineages (B. taurus: Y1, Y2; B. indicus: Y3), whereas 265 were shared by inferred taurine or indicine paternal lineages, and 228 when considering their maternal taurine or indicine origins. Phylogenetic analysis uncovered eight taurine/indicine hybrids, and principal component analysis on CNVs corroborated genomic exchange during hybridization. The distribution patterns of CNVRs tended to be lineage-specific, and correlation analysis revealed significant positive or negative co-occurrences of CNVRs across lineages. Our study suggests that CNVs in Chinese cattle partly result from selective breeding during domestication, but also from hybridization and introgression.
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Affiliation(s)
- Liangzhi Zhang
- Shaanxi Key Laboratory of Molecular Biology for Agriculture, College of Animal Science and Technology, Northwest A & F University, Yangling, Shaanxi, China Key laboratory of adaptation and evolution of plateau biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences
| | - Shangang Jia
- Shaanxi Key Laboratory of Molecular Biology for Agriculture, College of Animal Science and Technology, Northwest A & F University, Yangling, Shaanxi, China
| | - Martin Plath
- Shaanxi Key Laboratory of Molecular Biology for Agriculture, College of Animal Science and Technology, Northwest A & F University, Yangling, Shaanxi, China
| | - Yongzhen Huang
- Shaanxi Key Laboratory of Molecular Biology for Agriculture, College of Animal Science and Technology, Northwest A & F University, Yangling, Shaanxi, China
| | - Congjun Li
- United States Department of Agriculture-Agricultural Research Service, Bovine Functional Genomics Laboratory, Beltsville, Maryland
| | - Chuzhao Lei
- Shaanxi Key Laboratory of Molecular Biology for Agriculture, College of Animal Science and Technology, Northwest A & F University, Yangling, Shaanxi, China
| | - Xin Zhao
- Shaanxi Key Laboratory of Molecular Biology for Agriculture, College of Animal Science and Technology, Northwest A & F University, Yangling, Shaanxi, China
| | - Hong Chen
- Shaanxi Key Laboratory of Molecular Biology for Agriculture, College of Animal Science and Technology, Northwest A & F University, Yangling, Shaanxi, China
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21
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60,000 years of interactions between Central and Eastern Africa documented by major African mitochondrial haplogroup L2. Sci Rep 2015. [PMID: 26211407 PMCID: PMC4515592 DOI: 10.1038/srep12526] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Mitochondrial DNA (mtDNA) haplogroup L2 originated in Western Africa but is nowadays spread across the entire continent. L2 movements were previously postulated to be related to the Bantu expansion, but L2 expansions eastwards probably occurred much earlier. By reconstructing the phylogeny of L2 (44 new complete sequences) we provide insights on the complex net of within-African migrations in the last 60 thousand years (ka). Results show that lineages in Southern Africa cluster with Western/Central African lineages at a recent time scale, whereas, eastern lineages seem to be substantially more ancient. Three moments of expansion from a Central African source are associated to L2: (1) one migration at 70–50 ka into Eastern or Southern Africa, (2) postglacial movements (15–10 ka) into Eastern Africa; and (3) the southward Bantu Expansion in the last 5 ka. The complementary population and L0a phylogeography analyses indicate no strong evidence of mtDNA gene flow between eastern and southern populations during the later movement, suggesting low admixture between Eastern African populations and the Bantu migrants. This implies that, at least in the early stages, the Bantu expansion was mainly a demic diffusion with little incorporation of local populations.
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22
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ArunKumar G, Tatarinova TV, Duty J, Rollo D, Syama A, Arun VS, Kavitha VJ, Triska P, Greenspan B, Wells RS, Pitchappan R. Genome-wide signatures of male-mediated migration shaping the Indian gene pool. J Hum Genet 2015; 60:493-9. [DOI: 10.1038/jhg.2015.51] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2014] [Revised: 04/13/2015] [Accepted: 04/17/2015] [Indexed: 02/02/2023]
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Wollstein A, Lao O. Detecting individual ancestry in the human genome. INVESTIGATIVE GENETICS 2015; 6:7. [PMID: 25937887 PMCID: PMC4416275 DOI: 10.1186/s13323-015-0019-x] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/13/2014] [Accepted: 01/12/2015] [Indexed: 01/26/2023]
Abstract
Detecting and quantifying the population substructure present in a sample of individuals are of main interest in the fields of genetic epidemiology, population genetics, and forensics among others. To date, several algorithms have been proposed for estimating the amount of genetic ancestry within an individual. In the present review, we introduce the most widely used methods in population genetics for detecting individual genetic ancestry. We further show, by means of simulations, the performance of popular algorithms for detecting individual ancestry in various controlled demographic scenarios. Finally, we provide some hints on how to interpret the results from these algorithms.
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Affiliation(s)
- Andreas Wollstein
- Department of Forensic Molecular Biology, Erasmus MC University Medical Center Rotterdam, 3000 CA Rotterdam, The Netherlands ; Section of Evolutionary Biology, Department of Biology II, University of Munich, 82152 Planegg-Martinsried, Germany
| | - Oscar Lao
- Department of Forensic Molecular Biology, Erasmus MC University Medical Center Rotterdam, 3000 CA Rotterdam, The Netherlands ; Current address: Centro Nacional de Análisis Genómico, Baldiri Reixac, 4, Barcleona Science Park - Tower I, 08028 Barcelona, Spain
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24
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O'Connor TD, Fu W, Mychaleckyj JC, Logsdon B, Auer P, Carlson CS, Leal SM, Smith JD, Rieder MJ, Bamshad MJ, Nickerson DA, Akey JM. Rare variation facilitates inferences of fine-scale population structure in humans. Mol Biol Evol 2014; 32:653-60. [PMID: 25415970 PMCID: PMC4327153 DOI: 10.1093/molbev/msu326] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Understanding the genetic structure of human populations has important implications for the design and interpretation of disease mapping studies and reconstructing human evolutionary history. To date, inferences of human population structure have primarily been made with common variants. However, recent large-scale resequencing studies have shown an abundance of rare variation in humans, which may be particularly useful for making inferences of fine-scale population structure. To this end, we used an information theory framework and extensive coalescent simulations to rigorously quantify the informativeness of rare and common variation to detect signatures of fine-scale population structure. We show that rare variation affords unique insights into patterns of recent population structure. Furthermore, to empirically assess our theoretical findings, we analyzed high-coverage exome sequences in 6,515 European and African American individuals. As predicted, rare variants are more informative than common polymorphisms in revealing a distinct cluster of European–American individuals, and subsequent analyses demonstrate that these individuals are likely of Ashkenazi Jewish ancestry. Our results provide new insights into the population structure using rare variation, which will be an important factor to account for in rare variant association studies.
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Affiliation(s)
- Timothy D O'Connor
- Institute for Genome Sciences, University of Maryland School of Medicine Program in Personalized and Genomic Medicine, University of Maryland School of Medicine
| | - Wenqing Fu
- Department of Genome Sciences, University of Washington, Seattle
| | | | | | - Josyf C Mychaleckyj
- Department of Public Health Sciences, University of Virginia School of Medicine
| | - Benjamin Logsdon
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Paul Auer
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA Biostatistics: University of Wisconsin-Milwaukee, School of Public Health
| | - Christopher S Carlson
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Suzanne M Leal
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX
| | - Joshua D Smith
- Department of Genome Sciences, University of Washington, Seattle
| | - Mark J Rieder
- Department of Genome Sciences, University of Washington, Seattle
| | - Michael J Bamshad
- Department of Genome Sciences, University of Washington, Seattle Department of Pediatrics, University of Washington, Seattle
| | | | - Joshua M Akey
- Department of Genome Sciences, University of Washington, Seattle
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Pickrell JK, Reich D. Toward a new history and geography of human genes informed by ancient DNA. Trends Genet 2014; 30:377-89. [PMID: 25168683 PMCID: PMC4163019 DOI: 10.1016/j.tig.2014.07.007] [Citation(s) in RCA: 94] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2014] [Revised: 07/21/2014] [Accepted: 07/28/2014] [Indexed: 12/12/2022]
Abstract
Genetic information contains a record of the history of our species, and technological advances have transformed our ability to access this record. Many studies have used genome-wide data from populations today to learn about the peopling of the globe and subsequent adaptation to local conditions. Implicit in this research is the assumption that the geographic locations of people today are informative about the geographic locations of their ancestors in the distant past. However, it is now clear that long-range migration, admixture, and population replacement subsequent to the initial out-of-Africa expansion have altered the genetic structure of most of the world's human populations. In light of this we argue that it is time to critically reevaluate current models of the peopling of the globe, as well as the importance of natural selection in determining the geographic distribution of phenotypes. We specifically highlight the transformative potential of ancient DNA. By accessing the genetic make-up of populations living at archaeologically known times and places, ancient DNA makes it possible to directly track migrations and responses to natural selection.
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Affiliation(s)
- Joseph K Pickrell
- New York Genome Center, New York, NY, USA; Department of Biological Sciences, Columbia University, New York, NY, USA.
| | - David Reich
- Department of Genetics, Harvard Medical School, Boston, MA, USA; Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA; Broad Institute of the Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA.
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26
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Sanchez-Mazas A, Meyer D. The relevance of HLA sequencing in population genetics studies. J Immunol Res 2014; 2014:971818. [PMID: 25126587 PMCID: PMC4122113 DOI: 10.1155/2014/971818] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2014] [Accepted: 06/20/2014] [Indexed: 11/18/2022] Open
Abstract
Next generation sequencing (NGS) is currently being adapted by different biotechnological platforms to the standard typing method for HLA polymorphism, the huge diversity of which makes this initiative particularly challenging. Boosting the molecular characterization of the HLA genes through efficient, rapid, and low-cost technologies is expected to amplify the success of tissue transplantation by enabling us to find donor-recipient matching for rare phenotypes. But the application of NGS technologies to the molecular mapping of the MHC region also anticipates essential changes in population genetic studies. Huge amounts of HLA sequence data will be available in the next years for different populations, with the potential to change our understanding of HLA variation in humans. In this review, we first explain how HLA sequencing allows a better assessment of the HLA diversity in human populations, taking also into account the methodological difficulties it introduces at the statistical level; secondly, we show how analyzing HLA sequence variation may improve our comprehension of population genetic relationships by facilitating the identification of demographic events that marked human evolution; finally, we discuss the interest of both HLA and genome-wide sequencing and genotyping in detecting functionally significant SNPs in the MHC region, the latter having also contributed to the makeup of the HLA molecular diversity observed today.
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Affiliation(s)
- Alicia Sanchez-Mazas
- Department of Genetics and Evolution—Anthropology Unit, University of Geneva and Institute of Genetics and Genomics of Geneva (IGE3), 12 Rue Gustave-Revilliod, 1211 Geneva 4, Switzerland
| | - Diogo Meyer
- Department of Genetics and Evolutionary Biology, University of São Paulo, Rua do Matão 277, São Paulo, SP 05508-090, Brazil
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Malaspinas AS, Tange O, Moreno-Mayar JV, Rasmussen M, DeGiorgio M, Wang Y, Valdiosera CE, Politis G, Willerslev E, Nielsen R. bammds: a tool for assessing the ancestry of low-depth whole-genome data using multidimensional scaling (MDS). ACTA ACUST UNITED AC 2014; 30:2962-4. [PMID: 24974206 PMCID: PMC4184259 DOI: 10.1093/bioinformatics/btu410] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Summary: We present bammds, a practical tool that allows visualization of samples sequenced by second-generation sequencing when compared with a reference panel of individuals (usually genotypes) using a multidimensional scaling algorithm. Our tool is aimed at determining the ancestry of unknown samples—typical of ancient DNA data—particularly when only low amounts of data are available for those samples. Availability and implementation: The software package is available under GNU General Public License v3 and is freely available together with test datasets https://savannah.nongnu.org/projects/bammds/. It is using R (http://www.r-project.org/), parallel (http://www.gnu.org/software/parallel/), samtools (https://github.com/samtools/samtools). Contact:bammds-users@nongnu.org Supplementary information:Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Anna-Sapfo Malaspinas
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, 1350 Copenhagen K, Denmark, Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, Department of Biology, Pennsylvania State University, Wartik Laboratory, University Park, PA 16802, Centre for Theoretical Evolutionary Genomics, Departments of Integrative Biology and Statistics, University of California, Berkeley, CA 94720-3140, Ancestry.com DNA LLC, San Francisco, CA 94107, Department of Archaeology, Environment and Community Planning Faculty of Humanities and Social Sciences, La Trobe University, Melbourne, VIC 3086, Australia, INCUAPA-CONICET, Universidad del Centro de la Provincia de Buenos Aires, 7600 Olavarría, Argentina and Facultad de Ciencias Naturales y Museo de La Plata, 1900 La Plata, Argentina
| | - Ole Tange
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, 1350 Copenhagen K, Denmark, Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, Department of Biology, Pennsylvania State University, Wartik Laboratory, University Park, PA 16802, Centre for Theoretical Evolutionary Genomics, Departments of Integrative Biology and Statistics, University of California, Berkeley, CA 94720-3140, Ancestry.com DNA LLC, San Francisco, CA 94107, Department of Archaeology, Environment and Community Planning Faculty of Humanities and Social Sciences, La Trobe University, Melbourne, VIC 3086, Australia, INCUAPA-CONICET, Universidad del Centro de la Provincia de Buenos Aires, 7600 Olavarría, Argentina and Facultad de Ciencias Naturales y Museo de La Plata, 1900 La Plata, Argentina
| | - José Víctor Moreno-Mayar
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, 1350 Copenhagen K, Denmark, Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, Department of Biology, Pennsylvania State University, Wartik Laboratory, University Park, PA 16802, Centre for Theoretical Evolutionary Genomics, Departments of Integrative Biology and Statistics, University of California, Berkeley, CA 94720-3140, Ancestry.com DNA LLC, San Francisco, CA 94107, Department of Archaeology, Environment and Community Planning Faculty of Humanities and Social Sciences, La Trobe University, Melbourne, VIC 3086, Australia, INCUAPA-CONICET, Universidad del Centro de la Provincia de Buenos Aires, 7600 Olavarría, Argentina and Facultad de Ciencias Naturales y Museo de La Plata, 1900 La Plata, Argentina
| | - Morten Rasmussen
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, 1350 Copenhagen K, Denmark, Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, Department of Biology, Pennsylvania State University, Wartik Laboratory, University Park, PA 16802, Centre for Theoretical Evolutionary Genomics, Departments of Integrative Biology and Statistics, University of California, Berkeley, CA 94720-3140, Ancestry.com DNA LLC, San Francisco, CA 94107, Department of Archaeology, Environment and Community Planning Faculty of Humanities and Social Sciences, La Trobe University, Melbourne, VIC 3086, Australia, INCUAPA-CONICET, Universidad del Centro de la Provincia de Buenos Aires, 7600 Olavarría, Argentina and Facultad de Ciencias Naturales y Museo de La Plata, 1900 La Plata, Argentina Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, 1350 Copenhagen K, Denmark, Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, Department of Biology, Pennsylvania State University, Wartik Laboratory, University Park, PA 16802, Centre for Theoretical Evolutionary Genomics, Departments of Integrative Biology and Statistics, University of California, Berkeley, CA 94720-3140, Ancestry.com DNA LLC, San Francisco, CA 94107, Department of Archaeology, Environment and Community Planning Faculty of Humanities and Social Sciences, La Trobe University, Melbourne, VIC 3086, Australia, INCUAPA-CONICET, Universidad del Centro de la Provincia de Buenos Aires, 7600 Olavarría, Argentina and Facultad de Ciencias Naturales y Museo de La Plata, 1900 La Plata, Argentina
| | - Michael DeGiorgio
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, 1350 Copenhagen K, Denmark, Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, Department of Biology, Pennsylvania State University, Wartik Laboratory, University Park, PA 16802, Centre for Theoretical Evolutionary Genomics, Departments of Integrative Biology and Statistics, University of California, Berkeley, CA 94720-3140, Ancestry.com DNA LLC, San Francisco, CA 94107, Department of Archaeology, Environment and Community Planning Faculty of Humanities and Social Sciences, La Trobe University, Melbourne, VIC 3086, Australia, INCUAPA-CONICET, Universidad del Centro de la Provincia de Buenos Aires, 7600 Olavarría, Argentina and Facultad de Ciencias Naturales y Museo de La Plata, 1900 La Plata, Argentina
| | - Yong Wang
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, 1350 Copenhagen K, Denmark, Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, Department of Biology, Pennsylvania State University, Wartik Laboratory, University Park, PA 16802, Centre for Theoretical Evolutionary Genomics, Departments of Integrative Biology and Statistics, University of California, Berkeley, CA 94720-3140, Ancestry.com DNA LLC, San Francisco, CA 94107, Department of Archaeology, Environment and Community Planning Faculty of Humanities and Social Sciences, La Trobe University, Melbourne, VIC 3086, Australia, INCUAPA-CONICET, Universidad del Centro de la Provincia de Buenos Aires, 7600 Olavarría, Argentina and Facultad de Ciencias Naturales y Museo de La Plata, 1900 La Plata, Argentina Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, 1350 Copenhagen K, Denmark, Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, Department of Biology, Pennsylvania State University, Wartik Laboratory, University Park, PA 16802, Centre for Theoretical Evolutionary Genomics, Departments of Integrative Biology and Statistics, University of California, Berkeley, CA 94720-3140, Ancestry.com DNA LLC, San Francisco, CA 94107, Department of Archaeology, Environment and Community Planning Faculty of Humanities and Social Sciences, La Trobe University, Melbourne, VIC 3086, Australia, INCUAPA-CONICET, Universidad del Centro de la Provincia de Buenos Aires, 7600 Olavarría, Argentina and Facultad de Ciencias Naturales y Museo de La Plata, 1900 La Plata, Argentina
| | - Cristina E Valdiosera
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, 1350 Copenhagen K, Denmark, Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, Department of Biology, Pennsylvania State University, Wartik Laboratory, University Park, PA 16802, Centre for Theoretical Evolutionary Genomics, Departments of Integrative Biology and Statistics, University of California, Berkeley, CA 94720-3140, Ancestry.com DNA LLC, San Francisco, CA 94107, Department of Archaeology, Environment and Community Planning Faculty of Humanities and Social Sciences, La Trobe University, Melbourne, VIC 3086, Australia, INCUAPA-CONICET, Universidad del Centro de la Provincia de Buenos Aires, 7600 Olavarría, Argentina and Facultad de Ciencias Naturales y Museo de La Plata, 1900 La Plata, Argentina Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, 1350 Copenhagen K, Denmark, Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, Department of Biology, Pennsylvania State University, Wartik Laboratory, University Park, PA 16802, Centre for Theoretical Evolutionary Genomics, Departments of Integrative Biology and Statistics, University of California, Berkeley, CA 94720-3140, Ancestry.com DNA LLC, San Francisco, CA 94107, Department of Archaeology, Environment and Community Planning Faculty of Humanities and Social Sciences, La Trobe University, Melbourne, VIC 3086, Australia, INCUAPA-CONICET, Universidad del Centro de la Provincia de Buenos Aires, 7600 Olavarría, Argentina and Facultad de Ciencias Naturales y Museo de La Plata, 1900 La Plata, Argentina
| | - Gustavo Politis
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, 1350 Copenhagen K, Denmark, Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, Department of Biology, Pennsylvania State University, Wartik Laboratory, University Park, PA 16802, Centre for Theoretical Evolutionary Genomics, Departments of Integrative Biology and Statistics, University of California, Berkeley, CA 94720-3140, Ancestry.com DNA LLC, San Francisco, CA 94107, Department of Archaeology, Environment and Community Planning Faculty of Humanities and Social Sciences, La Trobe University, Melbourne, VIC 3086, Australia, INCUAPA-CONICET, Universidad del Centro de la Provincia de Buenos Aires, 7600 Olavarría, Argentina and Facultad de Ciencias Naturales y Museo de La Plata, 1900 La Plata, Argentina Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, 1350 Copenhagen K, Denmark, Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, Department of Biology, Pennsylvania State University, Wartik Laboratory, University Park, PA 16802, Centre for Theoretical Evolutionary Genomics, Departments of Integrative Biology and Statistics, University of California, Berkeley, CA 94720-3140, Ancestry.com DNA LLC, San Francisco, CA 94107, Department of Archaeology, Environment and Community Planning Faculty of Humanities and Social Sciences, La Trobe University, Melbourne, VIC 3086, Australia, INCUAPA-CONICET, Universidad del Centro de la Provincia de Buenos Aires, 7600 Olavarría, Argentina and Facultad de Ciencias Naturales y Museo de La Plata, 1900 La Plata, Argentina
| | - Eske Willerslev
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, 1350 Copenhagen K, Denmark, Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, Department of Biology, Pennsylvania State University, Wartik Laboratory, University Park, PA 16802, Centre for Theoretical Evolutionary Genomics, Departments of Integrative Biology and Statistics, University of California, Berkeley, CA 94720-3140, Ancestry.com DNA LLC, San Francisco, CA 94107, Department of Archaeology, Environment and Community Planning Faculty of Humanities and Social Sciences, La Trobe University, Melbourne, VIC 3086, Australia, INCUAPA-CONICET, Universidad del Centro de la Provincia de Buenos Aires, 7600 Olavarría, Argentina and Facultad de Ciencias Naturales y Museo de La Plata, 1900 La Plata, Argentina
| | - Rasmus Nielsen
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, 1350 Copenhagen K, Denmark, Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, Department of Biology, Pennsylvania State University, Wartik Laboratory, University Park, PA 16802, Centre for Theoretical Evolutionary Genomics, Departments of Integrative Biology and Statistics, University of California, Berkeley, CA 94720-3140, Ancestry.com DNA LLC, San Francisco, CA 94107, Department of Archaeology, Environment and Community Planning Faculty of Humanities and Social Sciences, La Trobe University, Melbourne, VIC 3086, Australia, INCUAPA-CONICET, Universidad del Centro de la Provincia de Buenos Aires, 7600 Olavarría, Argentina and Facultad de Ciencias Naturales y Museo de La Plata, 1900 La Plata, Argentina Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, 1350 Copenhagen K, Denmark, Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, Department of Biology, Pennsylvania State University, Wartik Laboratory, University Park, PA 16802, Centre for Theoretical Evolutionary Genomics, Departments of Integrative Biology and Statistics, University of California, Berkeley, CA 94720-3140, Ancestry.com DNA LLC, San Francisco, CA 94107, Department of Archaeology, Environment and Community Planning Faculty of Humanities and Social Sciences, La Trobe University, Melbourne, VIC 3086, Australia, INCUAPA-CONICET, Universidad del Centro de la Provincia de Buenos Aires, 7600 Olavarría, Argentina and Facultad de Ciencias Naturales y Museo de La Plata, 1900 La Plata, Argentina
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Choudhury A, Hazelhurst S, Meintjes A, Achinike-Oduaran O, Aron S, Gamieldien J, Jalali Sefid Dashti M, Mulder N, Tiffin N, Ramsay M. Population-specific common SNPs reflect demographic histories and highlight regions of genomic plasticity with functional relevance. BMC Genomics 2014; 15:437. [PMID: 24906912 PMCID: PMC4092225 DOI: 10.1186/1471-2164-15-437] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2013] [Accepted: 05/19/2014] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND Population differentiation is the result of demographic and evolutionary forces. Whole genome datasets from the 1000 Genomes Project (October 2012) provide an unbiased view of genetic variation across populations from Europe, Asia, Africa and the Americas. Common population-specific SNPs (MAF > 0.05) reflect a deep history and may have important consequences for health and wellbeing. Their interpretation is contextualised by currently available genome data. RESULTS The identification of common population-specific (CPS) variants (SNPs and SSV) is influenced by admixture and the sample size under investigation. Nine of the populations in the 1000 Genomes Project (2 African, 2 Asian (including a merged Chinese group) and 5 European) revealed that the African populations (LWK and YRI), followed by the Japanese (JPT) have the highest number of CPS SNPs, in concordance with their histories and given the populations studied. Using two methods, sliding 50-SNP and 5-kb windows, the CPS SNPs showed distinct clustering across large genome segments and little overlap of clusters between populations. iHS enrichment score and the population branch statistic (PBS) analyses suggest that selective sweeps are unlikely to account for the clustering and population specificity. Of interest is the association of clusters close to recombination hotspots. Functional analysis of genes associated with the CPS SNPs revealed over-representation of genes in pathways associated with neuronal development, including axonal guidance signalling and CREB signalling in neurones. CONCLUSIONS Common population-specific SNPs are non-randomly distributed throughout the genome and are significantly associated with recombination hotspots. Since the variant alleles of most CPS SNPs are the derived allele, they likely arose in the specific population after a split from a common ancestor. Their proximity to genes involved in specific pathways, including neuronal development, suggests evolutionary plasticity of selected genomic regions. Contrary to expectation, selective sweeps did not play a large role in the persistence of population-specific variation. This suggests a stochastic process towards population-specific variation which reflects demographic histories and may have some interesting implications for health and susceptibility to disease.
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Affiliation(s)
- Ananyo Choudhury
- />Sydney Brenner Institute of Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa
- />Division of Human Genetics, National Health Laboratory Service, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Scott Hazelhurst
- />Sydney Brenner Institute of Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa
- />School of Electrical & Information Engineering, University of the Witwatersrand, Johannesburg, South Africa
| | - Ayton Meintjes
- />Department Clinical Laboratory Sciences, Computational Biology Group, IDM, University of Cape Town, Cape Town, South Africa
| | - Ovokeraye Achinike-Oduaran
- />Sydney Brenner Institute of Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa
- />Division of Human Genetics, National Health Laboratory Service, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Shaun Aron
- />Sydney Brenner Institute of Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa
| | - Junaid Gamieldien
- />South African National Bioinformatics Institute/Medical Research Council of South Africa Bioinformatics Unit, University of the Western Cape, Bellville, South Africa
| | - Mahjoubeh Jalali Sefid Dashti
- />South African National Bioinformatics Institute/Medical Research Council of South Africa Bioinformatics Unit, University of the Western Cape, Bellville, South Africa
| | - Nicola Mulder
- />Department Clinical Laboratory Sciences, Computational Biology Group, IDM, University of Cape Town, Cape Town, South Africa
| | - Nicki Tiffin
- />South African National Bioinformatics Institute/Medical Research Council of South Africa Bioinformatics Unit, University of the Western Cape, Bellville, South Africa
| | - Michèle Ramsay
- />Sydney Brenner Institute of Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa
- />Division of Human Genetics, National Health Laboratory Service, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
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29
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Decker JE, McKay SD, Rolf MM, Kim J, Molina Alcalá A, Sonstegard TS, Hanotte O, Götherström A, Seabury CM, Praharani L, Babar ME, Correia de Almeida Regitano L, Yildiz MA, Heaton MP, Liu WS, Lei CZ, Reecy JM, Saif-Ur-Rehman M, Schnabel RD, Taylor JF. Worldwide patterns of ancestry, divergence, and admixture in domesticated cattle. PLoS Genet 2014; 10:e1004254. [PMID: 24675901 PMCID: PMC3967955 DOI: 10.1371/journal.pgen.1004254] [Citation(s) in RCA: 290] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2013] [Accepted: 02/04/2014] [Indexed: 11/19/2022] Open
Abstract
The domestication and development of cattle has considerably impacted human societies, but the histories of cattle breeds and populations have been poorly understood especially for African, Asian, and American breeds. Using genotypes from 43,043 autosomal single nucleotide polymorphism markers scored in 1,543 animals, we evaluate the population structure of 134 domesticated bovid breeds. Regardless of the analytical method or sample subset, the three major groups of Asian indicine, Eurasian taurine, and African taurine were consistently observed. Patterns of geographic dispersal resulting from co-migration with humans and exportation are recognizable in phylogenetic networks. All analytical methods reveal patterns of hybridization which occurred after divergence. Using 19 breeds, we map the cline of indicine introgression into Africa. We infer that African taurine possess a large portion of wild African auroch ancestry, causing their divergence from Eurasian taurine. We detect exportation patterns in Asia and identify a cline of Eurasian taurine/indicine hybridization in Asia. We also identify the influence of species other than Bos taurus taurus and B. t. indicus in the formation of Asian breeds. We detect the pronounced influence of Shorthorn cattle in the formation of European breeds. Iberian and Italian cattle possess introgression from African taurine. American Criollo cattle originate from Iberia, and not directly from Africa with African ancestry inherited via Iberian ancestors. Indicine introgression into American cattle occurred in the Americas, and not Europe. We argue that cattle migration, movement and trading followed by admixture have been important forces in shaping modern bovine genomic variation. The DNA of domesticated plants and animals contains information about how species were domesticated, exported, and bred by early farmers. Modern breeds were developed by lengthy and complex processes; however, our use of 134 breeds and new analytical models enabled us to reveal some of the processes that created modern cattle diversity. In Asia, Africa, North and South America, humpless (Bos t. taurus or taurine) and humped (Bos t. indicus or indicine) cattle were crossbred to produce hybrids adapted to the environment and local production systems. The history of Asian cattle involves the domestication and admixture of several species whereas African taurines arose through the introduction of domesticated Fertile Crescent taurines and their hybridization with wild African aurochs. African taurine genetic background is commonly observed among European Mediterranean breeds. The absence of indicine introgression within most European taurine breeds, but presence within three Italian breeds is consistent with at least two separate migration waves of cattle to Europe, one from the Middle East which captured taurines in which indicine introgression had already occurred and the second from western Africa into Spain with no indicine introgression. This second group seems to have radiated from Spain into the Mediterranean resulting in a cline of African taurine introgression into European taurines.
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Affiliation(s)
- Jared E. Decker
- Division of Animal Sciences, University of Missouri, Columbia, Missouri, United States of America
- * E-mail: (JED); (JFT)
| | - Stephanie D. McKay
- Department of Animal Science, The University of Vermont, Burlington, Vermont, United States of America
| | - Megan M. Rolf
- Department of Animal Sciences, Oklahoma State University, Stillwater, Oklahoma, United States of America
| | - JaeWoo Kim
- Division of Animal Sciences, University of Missouri, Columbia, Missouri, United States of America
| | - Antonio Molina Alcalá
- Departamento de Genética, Facultad de Veterinaria, Universidad de Córdoba, Córdoba, Spain
| | - Tad S. Sonstegard
- USDA-ARS Bovine Functional Genomics Lab, Beltsville, Maryland, United States of America
| | - Olivier Hanotte
- Medicine & Health Sciences, The University of Nottingham, Nottingham, United Kingdom
| | | | - Christopher M. Seabury
- Department of Veterinary Pathobiology, College of Veterinary Medicine, Texas A&M University, College Station, Texas, United States of America
| | - Lisa Praharani
- Indonesian Research Institute for Animal Production, Ciawi, Bogor, Indonesia
| | - Masroor Ellahi Babar
- Institute of Biochemistry & Biotechnology, University of Veterinary and Animal Sciences, Lahore, Pakistan
| | | | - Mehmet Ali Yildiz
- Animal Science, Biometry and Genetics, Ankara University, Diskapi, Ankara, Turkey
| | - Michael P. Heaton
- USDA, ARS, U.S. Meat Animal Research Center, Clay Center, Nebraska, United States of America
| | - Wan-Sheng Liu
- Department of Animal Science, Pennsylvania State University, University Park, Pennsylvania, United States of America
| | - Chu-Zhao Lei
- College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - James M. Reecy
- Department of Animal Science, Iowa State University, Ames, Iowa, United States of America
| | | | - Robert D. Schnabel
- Division of Animal Sciences, University of Missouri, Columbia, Missouri, United States of America
| | - Jeremy F. Taylor
- Division of Animal Sciences, University of Missouri, Columbia, Missouri, United States of America
- * E-mail: (JED); (JFT)
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30
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Lao O, Liu F, Wollstein A, Kayser M. GAGA: a new algorithm for genomic inference of geographic ancestry reveals fine level population substructure in Europeans. PLoS Comput Biol 2014; 10:e1003480. [PMID: 24586132 PMCID: PMC3930519 DOI: 10.1371/journal.pcbi.1003480] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2013] [Accepted: 01/03/2014] [Indexed: 02/04/2023] Open
Abstract
Attempts to detect genetic population substructure in humans are troubled by the fact that the vast majority of the total amount of observed genetic variation is present within populations rather than between populations. Here we introduce a new algorithm for transforming a genetic distance matrix that reduces the within-population variation considerably. Extensive computer simulations revealed that the transformed matrix captured the genetic population differentiation better than the original one which was based on the T1 statistic. In an empirical genomic data set comprising 2,457 individuals from 23 different European subpopulations, the proportion of individuals that were determined as a genetic neighbour to another individual from the same sampling location increased from 25% with the original matrix to 52% with the transformed matrix. Similarly, the percentage of genetic variation explained between populations by means of Analysis of Molecular Variance (AMOVA) increased from 1.62% to 7.98%. Furthermore, the first two dimensions of a classical multidimensional scaling (MDS) using the transformed matrix explained 15% of the variance, compared to 0.7% obtained with the original matrix. Application of MDS with Mclust, SPA with Mclust, and GemTools algorithms to the same dataset also showed that the transformed matrix gave a better association of the genetic clusters with the sampling locations, and particularly so when it was used in the AMOVA framework with a genetic algorithm. Overall, the new matrix transformation introduced here substantially reduces the within population genetic differentiation, and can be broadly applied to methods such as AMOVA to enhance their sensitivity to reveal population substructure. We herewith provide a publically available (http://www.erasmusmc.nl/fmb/resources/GAGA) model-free method for improved genetic population substructure detection that can be applied to human as well as any other species data in future studies relevant to evolutionary biology, behavioural ecology, medicine, and forensics.
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Affiliation(s)
- Oscar Lao
- Department of Forensic Molecular Biology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
- * E-mail:
| | - Fan Liu
- Department of Forensic Molecular Biology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Andreas Wollstein
- Department of Forensic Molecular Biology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands
| | - Manfred Kayser
- Department of Forensic Molecular Biology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
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31
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Veeramah KR, Hammer MF. The impact of whole-genome sequencing on the reconstruction of human population history. Nat Rev Genet 2014; 15:149-62. [PMID: 24492235 DOI: 10.1038/nrg3625] [Citation(s) in RCA: 127] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Examining patterns of molecular genetic variation in both modern-day and ancient humans has proved to be a powerful approach to learn about our origins. Rapid advances in DNA sequencing technology have allowed us to characterize increasing amounts of genomic information. Although this clearly provides unprecedented power for inference, it also introduces more complexity into the way we use and interpret such data. Here, we review ongoing debates that have been influenced by improvements in our ability to sequence DNA and discuss some of the analytical challenges that need to be overcome in order to fully exploit the rich historical information that is contained in the entirety of the human genome.
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Affiliation(s)
- Krishna R Veeramah
- 1] Arizona Research Laboratories Division of Biotechnology, Room 231, Life Sciences South, 1007 East Lowell Street, University of Arizona, Tucson, Arizona 85721, USA. [2] Stony Brook University, Stony Brook, New York 11794-5245, USA
| | - Michael F Hammer
- Arizona Research Laboratories Division of Biotechnology, Room 231, Life Sciences South, 1007 East Lowell Street, University of Arizona, Tucson, Arizona 85721, USA
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32
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Markus B, Alshafee I, Birk OS. Deciphering the fine-structure of tribal admixture in the Bedouin population using genomic data. Heredity (Edinb) 2014; 112:182-9. [PMID: 24084643 PMCID: PMC3907104 DOI: 10.1038/hdy.2013.90] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2013] [Revised: 07/03/2013] [Accepted: 08/22/2013] [Indexed: 02/04/2023] Open
Abstract
The Bedouin Israeli population is highly inbred and structured with a very high prevalence of recessive diseases. Many studies in the past two decades focused on linkage analysis in large, multiple consanguineous pedigrees of this population. The advent of high-throughput technologies motivated researchers to search for rare variants shared between smaller pedigrees, integrating data from clinically similar yet seemingly non-related sporadic cases. However, such analyses are challenging because, without pedigree data, there is no prior knowledge regarding possible relatedness between the sporadic cases. Here, we describe models and techniques for the study of relationships between pedigrees and use them for the inference of tribal co-ancestry, delineating the complex social interactions between different tribes in the Negev Bedouins of southern Israel. Through our analysis, we differentiate between tribes that share many yet small genomic segments because of co-ancestry versus tribes that share larger segments because of recent admixture. The emergent pattern is well correlated with the prevalence of rare mutations in the different tribes. Tribes that do not intermarry, mostly because of social restrictions, hold private mutations, whereas tribes that do intermarry demonstrate a genetic flow of mutations between them. Thus, social structure within an inbred community can be delineated through genomic data, with implications to genetic counseling and genetic mapping.
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Affiliation(s)
- B Markus
- The Morris Kahn Laboratory of Human Genetics
at the National Institute for Biotechnology in the Negev (NIBN) and Faculty of Health
Sciences, Ben Gurion University, Beer-Sheva, Israel
| | - I Alshafee
- Soroka Medical Center, The Genetics
Institute, Beer-sheva, Israel
| | - O S Birk
- The Morris Kahn Laboratory of Human Genetics
at the National Institute for Biotechnology in the Negev (NIBN) and Faculty of Health
Sciences, Ben Gurion University, Beer-Sheva, Israel
- Soroka Medical Center, The Genetics
Institute, Beer-sheva, Israel
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33
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Coia V, Capocasa M, Anagnostou P, Pascali V, Scarnicci F, Boschi I, Battaggia C, Crivellaro F, Ferri G, Alù M, Brisighelli F, Busby GBJ, Capelli C, Maixner F, Cipollini G, Viazzo PP, Zink A, Destro Bisol G. Demographic histories, isolation and social factors as determinants of the genetic structure of Alpine linguistic groups. PLoS One 2013; 8:e81704. [PMID: 24312576 PMCID: PMC3847036 DOI: 10.1371/journal.pone.0081704] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2013] [Accepted: 10/15/2013] [Indexed: 11/25/2022] Open
Abstract
Great European mountain ranges have acted as barriers to gene flow for resident populations since prehistory and have offered a place for the settlement of small, and sometimes culturally diverse, communities. Therefore, the human groups that have settled in these areas are worth exploring as an important potential source of diversity in the genetic structure of European populations. In this study, we present new high resolution data concerning Y chromosomal variation in three distinct Alpine ethno-linguistic groups, Italian, Ladin and German. Combining unpublished and literature data on Y chromosome and mitochondrial variation, we were able to detect different genetic patterns. In fact, within and among population diversity values observed vary across linguistic groups, with German and Italian speakers at the two extremes, and seem to reflect their different demographic histories. Using simulations we inferred that the joint effect of continued genetic isolation and reduced founding group size may explain the apportionment of genetic diversity observed in all groups. Extending the analysis to other continental populations, we observed that the genetic differentiation of Ladins and German speakers from Europeans is comparable or even greater to that observed for well known outliers like Sardinian and Basques. Finally, we found that in south Tyroleans, the social practice of Geschlossener Hof, a hereditary norm which might have favored male dispersal, coincides with a significant intra-group diversity for mtDNA but not for Y chromosome, a genetic pattern which is opposite to those expected among patrilocal populations. Together with previous evidence regarding the possible effects of “local ethnicity” on the genetic structure of German speakers that have settled in the eastern Italian Alps, this finding suggests that taking socio-cultural factors into account together with geographical variables and linguistic diversity may help unveil some yet to be understood aspects of the genetic structure of European populations.
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MESH Headings
- Chromosomes, Human, Y/genetics
- Demography/history
- Ethnicity/genetics
- Ethnicity/history
- Evolution, Molecular
- Female
- Gene Flow
- Genetic Variation
- History, 15th Century
- History, 16th Century
- History, 17th Century
- History, 18th Century
- History, 19th Century
- History, 20th Century
- History, 21st Century
- Humans
- Linguistics
- Male
- Mitochondria/genetics
- Polymorphism, Single Nucleotide
- White People/ethnology
- White People/genetics
- White People/history
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Affiliation(s)
- Valentina Coia
- Accademia Europea di Bolzano (EURAC), Istituto per le Mummie e l'Iceman, Bolzano, Italy
- * E-mail: (VC); (GDB)
| | - Marco Capocasa
- Dipartimento Biologia e Biotecnologie “Charles Darwin”, Sapienza Università di Roma, Rome, Italy
- Istituto Italiano di Antropologia, Rome, Italy
| | - Paolo Anagnostou
- Istituto Italiano di Antropologia, Rome, Italy
- Dipartimento Biologia Ambientale, Sapienza Università di Roma, Rome, Italy
| | - Vincenzo Pascali
- Istituto di Medicina Legale e delle Assicurazioni, Università Cattolica di Roma, Rome, Italy
| | - Francesca Scarnicci
- Istituto di Medicina Legale e delle Assicurazioni, Università Cattolica di Roma, Rome, Italy
| | - Ilaria Boschi
- Istituto di Medicina Legale e delle Assicurazioni, Università Cattolica di Roma, Rome, Italy
| | - Cinzia Battaggia
- Dipartimento Biologia Ambientale, Sapienza Università di Roma, Rome, Italy
| | - Federica Crivellaro
- Sezione di Antropologia, Museo Nazionale Preistorico Etnografico “Luigi Pigorini”, Rome, Italy
| | - Gianmarco Ferri
- Dipartimento Integrato di Servizi Diagnostici e di Laboratorio e di Medicina Legale, Università di Modena e Reggio Emilia, Modena, Italy
| | - Milena Alù
- Dipartimento Integrato di Servizi Diagnostici e di Laboratorio e di Medicina Legale, Università di Modena e Reggio Emilia, Modena, Italy
| | - Francesca Brisighelli
- Istituto di Medicina Legale e delle Assicurazioni, Università Cattolica di Roma, Rome, Italy
| | | | - Cristian Capelli
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Frank Maixner
- Accademia Europea di Bolzano (EURAC), Istituto per le Mummie e l'Iceman, Bolzano, Italy
| | - Giovanna Cipollini
- Accademia Europea di Bolzano (EURAC), Istituto per le Mummie e l'Iceman, Bolzano, Italy
| | - Pier Paolo Viazzo
- Dipartimento Culture, Politica e Società-Sezione Scienze Antropologiche, Università degli Studi di Torino, Turin, Italy
| | - Albert Zink
- Accademia Europea di Bolzano (EURAC), Istituto per le Mummie e l'Iceman, Bolzano, Italy
| | - Giovanni Destro Bisol
- Istituto Italiano di Antropologia, Rome, Italy
- Dipartimento Biologia Ambientale, Sapienza Università di Roma, Rome, Italy
- * E-mail: (VC); (GDB)
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34
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Olivieri A, Pala M, Gandini F, Hooshiar Kashani B, Perego UA, Woodward SR, Grugni V, Battaglia V, Semino O, Achilli A, Richards MB, Torroni A. Mitogenomes from two uncommon haplogroups mark late glacial/postglacial expansions from the near east and neolithic dispersals within Europe. PLoS One 2013; 8:e70492. [PMID: 23936216 PMCID: PMC3729697 DOI: 10.1371/journal.pone.0070492] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2013] [Accepted: 06/20/2013] [Indexed: 11/19/2022] Open
Abstract
The current human mitochondrial (mtDNA) phylogeny does not equally represent all human populations but is biased in favour of representatives originally from north and central Europe. This especially affects the phylogeny of some uncommon West Eurasian haplogroups, including I and W, whose southern European and Near Eastern components are very poorly represented, suggesting that extensive hidden phylogenetic substructure remains to be uncovered. This study expanded and re-analysed the available datasets of I and W complete mtDNA genomes, reaching a comprehensive 419 mitogenomes, and searched for precise correlations between the ages and geographical distributions of their numerous newly identified subclades with events of human dispersal which contributed to the genetic formation of modern Europeans. Our results showed that haplogroups I (within N1a1b) and W originated in the Near East during the Last Glacial Maximum or pre-warming period (the period of gradual warming between the end of the LGM, ∼19 ky ago, and the beginning of the first main warming phase, ∼15 ky ago) and, like the much more common haplogroups J and T, may have been involved in Late Glacial expansions starting from the Near East. Thus our data contribute to a better definition of the Late and postglacial re-peopling of Europe, providing further evidence for the scenario that major population expansions started after the Last Glacial Maximum but before Neolithic times, but also evidencing traces of diffusion events in several I and W subclades dating to the European Neolithic and restricted to Europe.
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Affiliation(s)
- Anna Olivieri
- Dipartimento di Biologia e Biotecnologie L. Spallanzani, Università di Pavia, Pavia, Italy.
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Lachance J, Tishkoff SA. SNP ascertainment bias in population genetic analyses: why it is important, and how to correct it. Bioessays 2013; 35:780-6. [PMID: 23836388 DOI: 10.1002/bies.201300014] [Citation(s) in RCA: 196] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Whole genome sequencing and SNP genotyping arrays can paint strikingly different pictures of demographic history and natural selection. This is because genotyping arrays contain biased sets of pre-ascertained SNPs. In this short review, we use comparisons between high-coverage whole genome sequences of African hunter-gatherers and data from genotyping arrays to highlight how SNP ascertainment bias distorts population genetic inferences. Sample sizes and the populations in which SNPs are discovered affect the characteristics of observed variants. We find that SNPs on genotyping arrays tend to be older and present in multiple populations. In addition, genotyping arrays cause allele frequency distributions to be shifted towards intermediate frequency alleles, and estimates of linkage disequilibrium are modified. Since population genetic analyses depend on allele frequencies, it is imperative that researchers are aware of the effects of SNP ascertainment bias. With this in mind, we describe multiple ways to correct for SNP ascertainment bias.
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Affiliation(s)
- Joseph Lachance
- Departments of Biology and Genetics, University of Pennsylvania, Philadelphia, PA, USA.
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Igea J, Aymerich P, Fernández-González A, González-Esteban J, Gómez A, Alonso R, Gosálbez J, Castresana J. Phylogeography and postglacial expansion of the endangered semi-aquatic mammal Galemys pyrenaicus. BMC Evol Biol 2013; 13:115. [PMID: 23738626 PMCID: PMC3682870 DOI: 10.1186/1471-2148-13-115] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2012] [Accepted: 05/28/2013] [Indexed: 01/20/2023] Open
Abstract
Background Species with strict ecological requirements may provide new insights into the forces that shaped the geographic variation of genetic diversity. The Pyrenean desman, Galemys pyrenaicus, is a small semi-aquatic mammal that inhabits clean streams of the northern half of the Iberian Peninsula and is endangered in most of its geographic range, but its genetic structure is currently unknown. While the stringent ecological demands derived from its aquatic habitat might have caused a partition of the genetic diversity among river basins, Pleistocene glaciations would have generated a genetic pattern related to glacial refugia. Results To study the relative importance of historical and ecological factors in the genetic structure of G. pyrenaicus, we used mitochondrial and intronic sequences of specimens covering most of the species range. We show, first, that the Pyrenean desman has very low levels of genetic diversity compared to other mammals. In addition, phylogenetic and dating analyses of the mitochondrial sequences reveal a strong phylogeographic structure of a Middle Pleistocene origin, suggesting that the main lineages arose during periods of glacial isolation. Furthermore, both the spatial distribution of nuclear and mitochondrial diversity and the results of species distribution modeling suggest the existence of a major glacial refugium in the northwestern part of the Iberian Peninsula. Finally, the main mitochondrial lineages show a striking parapatric distribution without any apparent exchange of mitochondrial haplotypes between the lineages that came into secondary contact (although with certain permeability to nuclear genes), indicating incomplete mixing after the post-glacial recolonization. On the other hand, when we analyzed the partition of the genetic diversity among river basins, the Pyrenean desman showed a lower than expected genetic differentiation among main rivers. Conclusions The analysis of mitochondrial and intronic markers in G. pyrenaicus showed the predominant effects of Pleistocene glaciations on the genetic structure of this species, while the distribution of the genetic diversity was not greatly influenced by the main river systems. These results and, particularly, the discovery of a marked phylogeographic structure, may have important implications for the conservation of the Pyrenean desman.
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Affiliation(s)
- Javier Igea
- Institut de Biologia Evolutiva (CSIC-UPF), Passeig Marítim de la Barceloneta 37, Barcelona 08003, Spain
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Yahara K, Furuta Y, Oshima K, Yoshida M, Azuma T, Hattori M, Uchiyama I, Kobayashi I. Chromosome painting in silico in a bacterial species reveals fine population structure. Mol Biol Evol 2013; 30:1454-64. [PMID: 23505045 PMCID: PMC3649679 DOI: 10.1093/molbev/mst055] [Citation(s) in RCA: 64] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Identifying population structure forms an important basis for genetic and evolutionary studies. Most current methods to identify population structure have limitations in analyzing haplotypes and recombination across the genome. Recently, a method of chromosome painting in silico has been developed to overcome these shortcomings and has been applied to multiple human genome sequences. This method detects the genome-wide transfer of DNA sequence chunks through homologous recombination. Here, we apply it to the frequently recombining bacterial species Helicobacter pylori that has infected Homo sapiens since their birth in Africa and shows wide phylogeographic divergence. Multiple complete genome sequences were analyzed including sequences from Okinawa, Japan, that we recently sequenced. The newer method revealed a finer population structure than revealed by a previous method that examines only MLST housekeeping genes or a phylogenetic network analysis of the core genome. Novel subgroups were found in Europe, Amerind, and East Asia groups. Examination of genetic flux showed some singleton strains to be hybrids of subgroups and revealed evident signs of population admixture in Africa, Europe, and parts of Asia. We expect this approach to further our understanding of intraspecific bacterial evolution by revealing population structure at a finer scale.
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Affiliation(s)
- Koji Yahara
- Department of Medical Genome Sciences, Graduate School of Frontier Sciences, University of Tokyo, Minato-ku, Tokyo, Japan
- Institute of Medical Science, University of Tokyo, Minato-ku, Tokyo, Japan
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Yoshikazu Furuta
- Department of Medical Genome Sciences, Graduate School of Frontier Sciences, University of Tokyo, Minato-ku, Tokyo, Japan
- Institute of Medical Science, University of Tokyo, Minato-ku, Tokyo, Japan
| | - Kenshiro Oshima
- Department of Computational Biology, Graduate School of Frontier Sciences, University of Tokyo, Kashiwa, Chiba, Japan
| | - Masaru Yoshida
- Department of Gastroenterology, Graduate School of Medicine, Kobe University, Chuou-ku, Kobe, Hyogo, Japan
| | - Takeshi Azuma
- Department of Gastroenterology, Graduate School of Medicine, Kobe University, Chuou-ku, Kobe, Hyogo, Japan
| | - Masahira Hattori
- Department of Computational Biology, Graduate School of Frontier Sciences, University of Tokyo, Kashiwa, Chiba, Japan
| | - Ikuo Uchiyama
- Laboratory of Genome Informatics, National Institute for Basic Biology, Okazaki, Aichi, Japan
| | - Ichizo Kobayashi
- Department of Medical Genome Sciences, Graduate School of Frontier Sciences, University of Tokyo, Minato-ku, Tokyo, Japan
- Institute of Medical Science, University of Tokyo, Minato-ku, Tokyo, Japan
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Ralph P, Coop G. The geography of recent genetic ancestry across Europe. PLoS Biol 2013; 11:e1001555. [PMID: 23667324 PMCID: PMC3646727 DOI: 10.1371/journal.pbio.1001555] [Citation(s) in RCA: 192] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2012] [Accepted: 03/27/2013] [Indexed: 01/11/2023] Open
Abstract
A genomic survey of recent genealogical relatedness reveals the close ties of kinship and the impact of events across the past 3,000 years of European history. The recent genealogical history of human populations is a complex mosaic formed by individual migration, large-scale population movements, and other demographic events. Population genomics datasets can provide a window into this recent history, as rare traces of recent shared genetic ancestry are detectable due to long segments of shared genomic material. We make use of genomic data for 2,257 Europeans (in the Population Reference Sample [POPRES] dataset) to conduct one of the first surveys of recent genealogical ancestry over the past 3,000 years at a continental scale. We detected 1.9 million shared long genomic segments, and used the lengths of these to infer the distribution of shared ancestors across time and geography. We find that a pair of modern Europeans living in neighboring populations share around 2–12 genetic common ancestors from the last 1,500 years, and upwards of 100 genetic ancestors from the previous 1,000 years. These numbers drop off exponentially with geographic distance, but since these genetic ancestors are a tiny fraction of common genealogical ancestors, individuals from opposite ends of Europe are still expected to share millions of common genealogical ancestors over the last 1,000 years. There is also substantial regional variation in the number of shared genetic ancestors. For example, there are especially high numbers of common ancestors shared between many eastern populations that date roughly to the migration period (which includes the Slavic and Hunnic expansions into that region). Some of the lowest levels of common ancestry are seen in the Italian and Iberian peninsulas, which may indicate different effects of historical population expansions in these areas and/or more stably structured populations. Population genomic datasets have considerable power to uncover recent demographic history, and will allow a much fuller picture of the close genealogical kinship of individuals across the world. Few of us know our family histories more than a few generations back. It is therefore easy to overlook the fact that we are all distant cousins, related to one another via a vast network of relationships. Here we use genome-wide data from European individuals to investigate these relationships over the past 3,000 years, by looking for long stretches of genome that are shared between pairs of individuals through their inheritance from common genetic ancestors. We quantify this ubiquitous recent common ancestry, showing for instance that even pairs of individuals from opposite ends of Europe share hundreds of genetic common ancestors over this time period. Despite this degree of commonality, there are also striking regional differences. Southeastern Europeans, for example, share large numbers of common ancestors that date roughly to the era of the Slavic and Hunnic expansions around 1,500 years ago, while most common ancestors that Italians share with other populations lived longer than 2,500 years ago. The study of long stretches of shared genetic material promises to uncover rich information about many aspects of recent population history.
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Affiliation(s)
- Peter Ralph
- Department of Evolution and Ecology & Center for Population Biology, University of California, Davis, California, United States of America
- * E-mail: (PR); (GC)
| | - Graham Coop
- Department of Evolution and Ecology & Center for Population Biology, University of California, Davis, California, United States of America
- * E-mail: (PR); (GC)
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Novembre J. Commentary on Sokal, Oden, and Thomson's "a problem with synthetic maps" (1999). Hum Biol 2013; 84:623-6. [PMID: 23526348 DOI: 10.3378/027.084.0512] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/22/2013] [Indexed: 11/05/2022]
Affiliation(s)
- John Novembre
- Interdepartmental Program in Bioinformatics, Dept. of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA 90095-7239, USA.
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41
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Parry RM, Wang MD. A fast least-squares algorithm for population inference. BMC Bioinformatics 2013; 14:28. [PMID: 23343408 PMCID: PMC3602075 DOI: 10.1186/1471-2105-14-28] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2012] [Accepted: 11/06/2012] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Population inference is an important problem in genetics used to remove population stratification in genome-wide association studies and to detect migration patterns or shared ancestry. An individual's genotype can be modeled as a probabilistic function of ancestral population memberships, Q, and the allele frequencies in those populations, P. The parameters, P and Q, of this binomial likelihood model can be inferred using slow sampling methods such as Markov Chain Monte Carlo methods or faster gradient based approaches such as sequential quadratic programming. This paper proposes a least-squares simplification of the binomial likelihood model motivated by a Euclidean interpretation of the genotype feature space. This results in a faster algorithm that easily incorporates the degree of admixture within the sample of individuals and improves estimates without requiring trial-and-error tuning. RESULTS We show that the expected value of the least-squares solution across all possible genotype datasets is equal to the true solution when part of the problem has been solved, and that the variance of the solution approaches zero as its size increases. The Least-squares algorithm performs nearly as well as Admixture for these theoretical scenarios. We compare least-squares, Admixture, and FRAPPE for a variety of problem sizes and difficulties. For particularly hard problems with a large number of populations, small number of samples, or greater degree of admixture, least-squares performs better than the other methods. On simulated mixtures of real population allele frequencies from the HapMap project, Admixture estimates sparsely mixed individuals better than Least-squares. The least-squares approach, however, performs within 1.5% of the Admixture error. On individual genotypes from the HapMap project, Admixture and least-squares perform qualitatively similarly and within 1.2% of each other. Significantly, the least-squares approach nearly always converges 1.5- to 6-times faster. CONCLUSIONS The computational advantage of the least-squares approach along with its good estimation performance warrants further research, especially for very large datasets. As problem sizes increase, the difference in estimation performance between all algorithms decreases. In addition, when prior information is known, the least-squares approach easily incorporates the expected degree of admixture to improve the estimate.
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Affiliation(s)
- R Mitchell Parry
- The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
| | - May D Wang
- The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
- Parker H. Petit Institute of Bioengineering and Biosciences and Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Winship Cancer Institute and Hematology and Oncology Department, Emory University, 30322, Atlanta, GA, USA
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Magalhães TR, Casey JP, Conroy J, Regan R, Fitzpatrick DJ, Shah N, Sobral J, Ennis S. HGDP and HapMap analysis by Ancestry Mapper reveals local and global population relationships. PLoS One 2012; 7:e49438. [PMID: 23189146 PMCID: PMC3506643 DOI: 10.1371/journal.pone.0049438] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2012] [Accepted: 10/09/2012] [Indexed: 11/18/2022] Open
Abstract
Knowledge of human origins, migrations, and expansions is greatly enhanced by the availability of large datasets of genetic information from different populations and by the development of bioinformatic tools used to analyze the data. We present Ancestry Mapper, which we believe improves on existing methods, for the assignment of genetic ancestry to an individual and to study the relationships between local and global populations. The principle function of the method, named Ancestry Mapper, is to give each individual analyzed a genetic identifier, made up of just 51 genetic coordinates, that corresponds to its relationship to the HGDP reference population. As a consequence, the Ancestry Mapper Id (AMid) has intrinsic biological meaning and provides a tool to measure similarity between world populations. We applied Ancestry Mapper to a dataset comprised of the HGDP and HapMap data. The results show distinctions at the continental level, while simultaneously giving details at the population level. We clustered AMids of HGDP/HapMap and observe a recapitulation of human migrations: for a small number of clusters, individuals are grouped according to continental origins; for a larger number of clusters, regional and population distinctions are evident. Calculating distances between AMids allows us to infer ancestry. The number of coordinates is expandable, increasing the power of Ancestry Mapper. An R package called Ancestry Mapper is available to apply this method to any high density genomic data set.
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Affiliation(s)
- Tiago R. Magalhães
- School of Medicine and Medical Science, University College Dublin, Dublin, Ireland
| | - Jillian P. Casey
- School of Medicine and Medical Science, University College Dublin, Dublin, Ireland
- National Children’s Research Centre, Our Lady’s Childrens Hospital Crumlin, Dublin, Ireland
| | - Judith Conroy
- School of Medicine and Medical Science, University College Dublin, Dublin, Ireland
| | - Regina Regan
- School of Medicine and Medical Science, University College Dublin, Dublin, Ireland
- National Children’s Research Centre, Our Lady’s Childrens Hospital Crumlin, Dublin, Ireland
| | - Darren J. Fitzpatrick
- School of Medicine and Medical Science, University College Dublin, Dublin, Ireland
- Clique Research Cluster, School of Computer Science and Informatics, University College Dublin, Dublin, Ireland
| | - Naisha Shah
- School of Medicine and Medical Science, University College Dublin, Dublin, Ireland
- Complex and Adaptive Systems Laboratory, and Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland
| | - João Sobral
- Instituto Gulbenkian de Ciência, Oeiras, Portugal
| | - Sean Ennis
- School of Medicine and Medical Science, University College Dublin, Dublin, Ireland
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43
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Pickrell JK, Pritchard JK. Inference of population splits and mixtures from genome-wide allele frequency data. PLoS Genet 2012; 8:e1002967. [PMID: 23166502 PMCID: PMC3499260 DOI: 10.1371/journal.pgen.1002967] [Citation(s) in RCA: 1458] [Impact Index Per Article: 121.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2012] [Accepted: 08/08/2012] [Indexed: 11/29/2022] Open
Abstract
Many aspects of the historical relationships between populations in a species are reflected in genetic data. Inferring these relationships from genetic data, however, remains a challenging task. In this paper, we present a statistical model for inferring the patterns of population splits and mixtures in multiple populations. In our model, the sampled populations in a species are related to their common ancestor through a graph of ancestral populations. Using genome-wide allele frequency data and a Gaussian approximation to genetic drift, we infer the structure of this graph. We applied this method to a set of 55 human populations and a set of 82 dog breeds and wild canids. In both species, we show that a simple bifurcating tree does not fully describe the data; in contrast, we infer many migration events. While some of the migration events that we find have been detected previously, many have not. For example, in the human data, we infer that Cambodians trace approximately 16% of their ancestry to a population ancestral to other extant East Asian populations. In the dog data, we infer that both the boxer and basenji trace a considerable fraction of their ancestry (9% and 25%, respectively) to wolves subsequent to domestication and that East Asian toy breeds (the Shih Tzu and the Pekingese) result from admixture between modern toy breeds and "ancient" Asian breeds. Software implementing the model described here, called TreeMix, is available at http://treemix.googlecode.com.
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Affiliation(s)
- Joseph K. Pickrell
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
| | - Jonathan K. Pritchard
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
- Howard Hughes Medical Institute, University of Chicago, Chicago, Illinois, United States of America
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Arenas M, François O, Currat M, Ray N, Excoffier L. Influence of admixture and paleolithic range contractions on current European diversity gradients. Mol Biol Evol 2012; 30:57-61. [PMID: 22923464 DOI: 10.1093/molbev/mss203] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
Cavalli-Sforza and Edwards (Analysis of human evolution. 1963. In: Geerts SJ, editor. Genetics today: Proceedings of the 11th International Congress of Genetics, The Hague, The Netherlands. New York: Pergamon. p. 923-993.) initiated the representation of genetic relationships among human populations with principal component (PC) analysis (PCA). Their study revealed the presence of a southeast-northwest (SE-NW) gradient of genetic variation in current European populations, which was interpreted as the result of the demic diffusion of early neolithic farmers during their expansion from the near east. However, this interpretation has been questioned, as PCA gradients can occur even when there is no expansion and because the first PC axis is often orthogonal to the expansion axis. Here, we revisit PCA patterns obtained under realistic scenarios of the settlement of Europe, focusing on the effects of various levels of admixture between paleolithic and neolithic populations, and of range contractions during the last glacial maximum (LGM). Using extensive simulations, we find that the first PC (PC1) gradients are orthogonal to the expansion axis, but only when the expansion is recent (neolithic). More ancient (paleolithic) expansions alter the orientation of the PC1 gradient due to a spatial homogenization of genetic diversity over time, and to the exact location of LGM refugia from which re-expansions proceeded. Overall we find that PC1 gradients consistently follow an SE-NW orientation if there is a large paleolithic contribution to the current European gene pool, and if the main refuge area during the last ice age was in the Iberian Peninsula. Our study suggests that an SE-NW PC1 gradient is compatible with little genetic impact of neolithic populations on the current European gene pool, and that range contractions have affected observed genetic patterns.
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Affiliation(s)
- Miguel Arenas
- Computational and Molecular Population Genetics Lab, Institute of Ecology and Evolution, University of Bern, Bern, Switzerland.
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45
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Wang C, Zöllner S, Rosenberg NA. A quantitative comparison of the similarity between genes and geography in worldwide human populations. PLoS Genet 2012; 8:e1002886. [PMID: 22927824 PMCID: PMC3426559 DOI: 10.1371/journal.pgen.1002886] [Citation(s) in RCA: 78] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2012] [Accepted: 06/24/2012] [Indexed: 01/06/2023] Open
Abstract
Multivariate statistical techniques such as principal components analysis (PCA) and multidimensional scaling (MDS) have been widely used to summarize the structure of human genetic variation, often in easily visualized two-dimensional maps. Many recent studies have reported similarity between geographic maps of population locations and MDS or PCA maps of genetic variation inferred from single-nucleotide polymorphisms (SNPs). However, this similarity has been evident primarily in a qualitative sense; and, because different multivariate techniques and marker sets have been used in different studies, it has not been possible to formally compare genetic variation datasets in terms of their levels of similarity with geography. In this study, using genome-wide SNP data from 128 populations worldwide, we perform a systematic analysis to quantitatively evaluate the similarity of genes and geography in different geographic regions. For each of a series of regions, we apply a Procrustes analysis approach to find an optimal transformation that maximizes the similarity between PCA maps of genetic variation and geographic maps of population locations. We consider examples in Europe, Sub-Saharan Africa, Asia, East Asia, and Central/South Asia, as well as in a worldwide sample, finding that significant similarity between genes and geography exists in general at different geographic levels. The similarity is highest in our examples for Asia and, once highly distinctive populations have been removed, Sub-Saharan Africa. Our results provide a quantitative assessment of the geographic structure of human genetic variation worldwide, supporting the view that geography plays a strong role in giving rise to human population structure. The spatial pattern of human genetic variation provides a basis for investigating the history of human migrations. Statistical techniques such as principal components analysis (PCA) and multidimensional scaling (MDS) have been used to summarize spatial patterns of genetic variation, typically by placing individuals on a two-dimensional map in such a way that pairwise Euclidean distances between individuals on the map approximately reflect corresponding genetic relationships. Although similarity between these statistical maps of genetic variation and the geographic maps of sampling locations is often observed, it has not been assessed systematically across different parts of the world. In this study, we combine genome-wide SNP data from more than 100 populations worldwide to perform a formal comparison between genes and geography in different regions. By examining a worldwide sample and samples from Europe, Sub-Saharan Africa, Asia, East Asia, and Central/South Asia, we find that significant similarity between genes and geography exists in general in different geographic regions and at different geographic levels. Surprisingly, the highest similarity is found in Asia, even though the geographic barrier of the Himalaya Mountains has created a discontinuity on the PCA map of genetic variation.
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Affiliation(s)
- Chaolong Wang
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA.
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46
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Rosenberg NA. A population-genetic perspective on the similarities and differences among worldwide human populations. Hum Biol 2012; 83:659-84. [PMID: 22276967 DOI: 10.3378/027.083.0601] [Citation(s) in RCA: 44] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Recent studies have produced a variety of advances in the investigation of genetic similarities and differences among human populations. Here, I pose a series of questions about human population-genetic similarities and differences, and I then answer these questions by numerical computation with a single shared population-genetic data set. The collection of answers obtained provides an introductory perspective for understanding key results on the features of worldwide human genetic variation.
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Affiliation(s)
- Noah A Rosenberg
- Department of Biology, Stanford University, Stanford, CA 94305, USA.
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Novembre J, Han E. Human population structure and the adaptive response to pathogen-induced selection pressures. Philos Trans R Soc Lond B Biol Sci 2012; 367:878-86. [PMID: 22312055 DOI: 10.1098/rstb.2011.0305] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
The past few years of research in human evolutionary genetics have provided novel insights and questions regarding how human adaptations to recent selective pressures have taken place. Here, we review the advances most relevant to understanding human evolution in response to pathogen-induced selective pressures. Key insights come from theoretical models of adaptive evolution, particularly those that consider spatially structured populations, and from empirical population genomic studies of adaptive evolution in humans. We also review the CCR5-Δ32 HIV resistance allele as a case study of pathogen resistance in humans. Taken together, the results make clear that the human response to pathogen-induced selection pressures depends on a complex interplay between the age of the pathogen, the genetic basis of potential resistance phenotypes, and how population structure impacts the adaptive process in humans.
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Affiliation(s)
- John Novembre
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, USA.
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48
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Jobling MA. The impact of recent events on human genetic diversity. Philos Trans R Soc Lond B Biol Sci 2012; 367:793-9. [PMID: 22312046 DOI: 10.1098/rstb.2011.0297] [Citation(s) in RCA: 62] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
The historical record tells us stories of migrations, population expansions and colonization events in the last few thousand years, but what was their demographic impact? Genetics can throw light on this issue, and has mostly done so through the maternally inherited mitochondrial DNA (mtDNA) and the male-specific Y chromosome. However, there are a number of problems, including marker ascertainment bias, possible influences of natural selection, and the obscuring layers of the palimpsest of historical and prehistorical events. Y-chromosomal lineages are particularly affected by genetic drift, which can be accentuated by recent social selection. A diversity of approaches to expansions in Europe is yielding insights into the histories of Phoenicians, Roma, Anglo-Saxons and Vikings, and new methods for producing and analysing genome-wide data hold much promise. The field would benefit from more consensus on appropriate methods, and better communication between geneticists and experts in other disciplines, such as history, archaeology and linguistics.
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Affiliation(s)
- Mark A Jobling
- Department of Genetics, University of Leicester, Leicester, UK.
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49
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Skoglund P, Malmstrom H, Raghavan M, Stora J, Hall P, Willerslev E, Gilbert MTP, Gotherstrom A, Jakobsson M. Origins and Genetic Legacy of Neolithic Farmers and Hunter-Gatherers in Europe. Science 2012; 336:466-9. [DOI: 10.1126/science.1216304] [Citation(s) in RCA: 405] [Impact Index Per Article: 33.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
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50
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Abstract
Recent studies of ancient genomes have suggested that gene flow from archaic hominin groups to the ancestors of modern humans occurred on two separate occasions during the modern human expansion out of Africa. At the same time, decreasing levels of human genetic diversity have been found at increasing distance from Africa as a consequence of human expansion out of Africa. We analyzed the signal of archaic ancestry in modern human populations, and we investigated how serial founder models of human expansion affect the signal of archaic ancestry using simulations. For descendants of an archaic admixture event, we show that genetic drift coupled with ascertainment bias for common alleles can cause artificial but largely predictable differences in similarity to archaic genomes. In genotype data from non-Africans, this effect results in a biased genetic similarity to Neandertals with increasing distance from Africa. However, in addition to the previously reported gene flow between Neandertals and non-Africans as well as gene flow between an archaic human population from Siberia ("Denisovans") and Oceanians, we found a significant affinity between East Asians, particularly Southeast Asians, and the Denisova genome--a pattern that is not expected under a model of solely Neandertal admixture in the ancestry of East Asians. These results suggest admixture between Denisovans or a Denisova-related population and the ancestors of East Asians, and that the history of anatomically modern and archaic humans might be more complex than previously proposed.
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