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Feng Y, McQuillan MA, Tishkoff SA. Evolutionary genetics of skin pigmentation in African populations. Hum Mol Genet 2021; 30:R88-R97. [PMID: 33438000 PMCID: PMC8117430 DOI: 10.1093/hmg/ddab007] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Revised: 01/07/2021] [Accepted: 01/07/2021] [Indexed: 12/14/2022] Open
Abstract
Skin color is a highly heritable human trait, and global variation in skin pigmentation has been shaped by natural selection, migration and admixture. Ethnically diverse African populations harbor extremely high levels of genetic and phenotypic diversity, and skin pigmentation varies widely across Africa. Recent genome-wide genetic studies of skin pigmentation in African populations have advanced our understanding of pigmentation biology and human evolutionary history. For example, novel roles in skin pigmentation for loci near MFSD12 and DDB1 have recently been identified in African populations. However, due to an underrepresentation of Africans in human genetic studies, there is still much to learn about the evolutionary genetics of skin pigmentation. Here, we summarize recent progress in skin pigmentation genetics in Africans and discuss the importance of including more ethnically diverse African populations in future genetic studies. In addition, we discuss methods for functional validation of adaptive variants related to skin pigmentation.
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Affiliation(s)
- Yuanqing Feng
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Michael A McQuillan
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sarah A Tishkoff
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA
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Khrunin AV, Khvorykh GV, Fedorov AN, Limborska SA. Genomic landscape of the signals of positive natural selection in populations of Northern Eurasia: A view from Northern Russia. PLoS One 2020; 15:e0228778. [PMID: 32023328 PMCID: PMC7001972 DOI: 10.1371/journal.pone.0228778] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2019] [Accepted: 01/23/2020] [Indexed: 12/15/2022] Open
Abstract
Natural selection of beneficial genetic variants played a critical role in human adaptation to a wide range of environmental conditions. Northern Eurasia, despite its severe climate, is home to lots of ethnically diverse populations. The genetic variants associated with the survival of these populations have hardly been analyzed. We searched for the genomic signatures of positive selection in (1) the genome-wide microarray data of 432 people from eight different northern Russian populations and (2) the whole-genome sequences of 250 people from Northern Eurasia from a public repository through testing the extended haplotype homozigosity (EHH) and direct comparison of allele frequency, respectively. The 20 loci with the strongest selection signals were characterized in detail. Among the top EHH hits were the NRG3 and NBEA genes, which are involved in the development and functioning of the neural system, the PTPRM gene, which mediates cell-cell interactions and adhesion, and a region on chromosome 4 (chr4:28.7-28.9 Mb) that contained several loci affiliated with different classes of non-coding RNAs (RN7SL101P, MIR4275, MESTP3, and LINC02364). NBEA and the region on chromosome 4 were novel selection targets that were identified for the first time in Western Siberian populations. Cross-population comparisons of EHH profiles suggested a particular role for the chr4:28.7-28.9 Mb region in the local adaptation of Western Siberians. The strongest selection signal identified in Siberian sequenced genomes was formed by six SNPs on chromosome 11 (chr11:124.9-125.2 Mb). This region included well-known genes SLC37A2 and PKNOX2. SLC37A2 is most-highly expressed in the gut. Its expression is regulated by vitamin D, which is often deficient in northern regions. The PKNOX2 gene is a transcription factor of the homeobox family that is expressed in the brain and many other tissues. This gene is associated with alcohol addiction, which is widespread in many Northern Eurasian populations.
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Affiliation(s)
- Andrey V. Khrunin
- Department of Molecular Bases of Human Genetics, Institute of Molecular Genetics of Russian Academy of Sciences, Moscow, Russia
| | - Gennady V. Khvorykh
- Department of Molecular Bases of Human Genetics, Institute of Molecular Genetics of Russian Academy of Sciences, Moscow, Russia
| | - Alexei N. Fedorov
- Department of Molecular Bases of Human Genetics, Institute of Molecular Genetics of Russian Academy of Sciences, Moscow, Russia
- Department of Medicine, University of Toledo, Toledo, Ohio, United States of America
| | - Svetlana A. Limborska
- Department of Molecular Bases of Human Genetics, Institute of Molecular Genetics of Russian Academy of Sciences, Moscow, Russia
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Grech L, Jeffares DC, Sadée CY, Rodríguez-López M, Bitton DA, Hoti M, Biagosch C, Aravani D, Speekenbrink M, Illingworth CJR, Schiffer PH, Pidoux AL, Tong P, Tallada VA, Allshire R, Levin HL, Bähler J. Fitness Landscape of the Fission Yeast Genome. Mol Biol Evol 2019; 36:1612-1623. [PMID: 31077324 PMCID: PMC6657727 DOI: 10.1093/molbev/msz113] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
The relationship between DNA sequence, biochemical function, and molecular evolution is relatively well-described for protein-coding regions of genomes, but far less clear in noncoding regions, particularly, in eukaryote genomes. In part, this is because we lack a complete description of the essential noncoding elements in a eukaryote genome. To contribute to this challenge, we used saturating transposon mutagenesis to interrogate the Schizosaccharomyces pombe genome. We generated 31 million transposon insertions, a theoretical coverage of 2.4 insertions per genomic site. We applied a five-state hidden Markov model (HMM) to distinguish insertion-depleted regions from insertion biases. Both raw insertion-density and HMM-defined fitness estimates showed significant quantitative relationships to gene knockout fitness, genetic diversity, divergence, and expected functional regions based on transcription and gene annotations. Through several analyses, we conclude that transposon insertions produced fitness effects in 66-90% of the genome, including substantial portions of the noncoding regions. Based on the HMM, we estimate that 10% of the insertion depleted sites in the genome showed no signal of conservation between species and were weakly transcribed, demonstrating limitations of comparative genomics and transcriptomics to detect functional units. In this species, 3'- and 5'-untranslated regions were the most prominent insertion-depleted regions that were not represented in measures of constraint from comparative genomics. We conclude that the combination of transposon mutagenesis, evolutionary, and biochemical data can provide new insights into the relationship between genome function and molecular evolution.
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Affiliation(s)
- Leanne Grech
- Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
| | - Daniel C Jeffares
- Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
- Department of Biology and York Biomedical Research Institute, University of York, United Kingdom
| | - Christoph Y Sadée
- Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
| | - María Rodríguez-López
- Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
| | - Danny A Bitton
- Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
| | - Mimoza Hoti
- Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
| | - Carolina Biagosch
- Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
| | - Dimitra Aravani
- Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
| | | | | | - Philipp H Schiffer
- Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
| | - Alison L Pidoux
- Wellcome Trust Centre for Cell Biology, University of Edinburgh, Edinburgh, United Kingdom
| | - Pin Tong
- Wellcome Trust Centre for Cell Biology, University of Edinburgh, Edinburgh, United Kingdom
| | - Victor A Tallada
- Centro Andaluz de Biología del Desarrollo, Universidad Pablo de Olavide/Consejo Superior de Investigaciones Científicas, Seville, Spain
| | - Robin Allshire
- Wellcome Trust Centre for Cell Biology, University of Edinburgh, Edinburgh, United Kingdom
| | - Henry L Levin
- Division of Molecular and Cellular Biology, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Jürg Bähler
- Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
- UCL Genetics Institute, University College London, London, United Kingdom
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Abstract
Levels and patterns of genetic diversity can provide insights into a population’s history. In species with sex chromosomes, differences between genomic regions with unique inheritance patterns can be used to distinguish between different sets of possible demographic and selective events. This review introduces the differences in population history for sex chromosomes and autosomes, provides the expectations for genetic diversity across the genome under different evolutionary scenarios, and gives an introductory description for how deviations in these expectations are calculated and can be interpreted. Predominantly, diversity on the sex chromosomes has been used to explore and address three research areas: 1) Mating patterns and sex-biased variance in reproductive success, 2) signatures of selection, and 3) evidence for modes of speciation and introgression. After introducing the theory, this review catalogs recent studies of genetic diversity on the sex chromosomes across species within the major research areas that sex chromosomes are typically applied to, arguing that there are broad similarities not only between male-heterogametic (XX/XY) and female-heterogametic (ZZ/ZW) sex determination systems but also any mating system with reduced recombination in a sex-determining region. Further, general patterns of reduced diversity in nonrecombining regions are shared across plants and animals. There are unique patterns across populations with vastly different patterns of mating and speciation, but these do not tend to cluster by taxa or sex determination system.
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Affiliation(s)
- Melissa A Wilson Sayres
- School of Life Sciences, Center for Evolution and Medicine, The Biodesign Institute, Arizona State University
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Johnson KE, Voight BF. Patterns of shared signatures of recent positive selection across human populations. Nat Ecol Evol 2018; 2:713-720. [PMID: 29459708 PMCID: PMC5866773 DOI: 10.1038/s41559-018-0478-6] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2017] [Accepted: 01/11/2018] [Indexed: 12/28/2022]
Abstract
Signatures of recent positive selection often overlap across human populations, but the question of how often these overlaps represent a single ancestral event remains unresolved. If a single selective event spread across many populations, the same sweeping haplotype should appear in each population and the selective pressure could be common across populations and environments. Identifying such shared selective events could identify genomic loci and human traits important in recent history across the globe. In addition, genomic annotations that recently became available could help attach these signatures to a potential gene and molecular phenotype selected across populations. Here, we present a catalogue of selective sweeps in humans, and identify those that overlap and share a sweeping haplotype. We connect these sweep overlaps with potential biological mechanisms at several loci, including potential new sites of adaptive introgression, the glycophorin locus associated with malarial resistance and the alcohol dehydrogenase cluster associated with alcohol dependency.
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Affiliation(s)
- Kelsey Elizabeth Johnson
- Genetics and Gene Regulation Program, Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Benjamin F Voight
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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Sheep genome functional annotation reveals proximal regulatory elements contributed to the evolution of modern breeds. Nat Commun 2018; 9:859. [PMID: 29491421 PMCID: PMC5830443 DOI: 10.1038/s41467-017-02809-1] [Citation(s) in RCA: 68] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2017] [Accepted: 12/03/2017] [Indexed: 12/30/2022] Open
Abstract
Domestication fundamentally reshaped animal morphology, physiology and behaviour, offering the opportunity to investigate the molecular processes driving evolutionary change. Here we assess sheep domestication and artificial selection by comparing genome sequence from 43 modern breeds (Ovis aries) and their Asian mouflon ancestor (O. orientalis) to identify selection sweeps. Next, we provide a comparative functional annotation of the sheep genome, validated using experimental ChIP-Seq of sheep tissue. Using these annotations, we evaluate the impact of selection and domestication on regulatory sequences and find that sweeps are significantly enriched for protein coding genes, proximal regulatory elements of genes and genome features associated with active transcription. Finally, we find individual sites displaying strong allele frequency divergence are enriched for the same regulatory features. Our data demonstrate that remodelling of gene expression is likely to have been one of the evolutionary forces that drove phenotypic diversification of this common livestock species. The domestication of plants and animals causes genomic changes underlying various morphologic, physiologic and behavioral changes. Here, Naval-Sanchez et al. provide a ChIP-Seq validated comparative functional annotation of the sheep genome, and show widespread evolution of proximal regulatory elements.
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Morrison AC, Huang Z, Yu B, Metcalf G, Liu X, Ballantyne C, Coresh J, Yu F, Muzny D, Feofanova E, Rustagi N, Gibbs R, Boerwinkle E. Practical Approaches for Whole-Genome Sequence Analysis of Heart- and Blood-Related Traits. Am J Hum Genet 2017; 100:205-215. [PMID: 28089252 DOI: 10.1016/j.ajhg.2016.12.009] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2016] [Accepted: 12/14/2016] [Indexed: 01/11/2023] Open
Abstract
Whole-genome sequencing (WGS) allows for a comprehensive view of the sequence of the human genome. We present and apply integrated methodologic steps for interrogating WGS data to characterize the genetic architecture of 10 heart- and blood-related traits in a sample of 1,860 African Americans. In order to evaluate the contribution of regulatory and non-protein coding regions of the genome, we conducted aggregate tests of rare variation across the entire genomic landscape using a sliding window, complemented by an annotation-based assessment of the genome using predefined regulatory elements and within the first intron of all genes. These tests were performed treating all variants equally as well as with individual variants weighted by a measure of predicted functional consequence. Significant findings were assessed in 1,705 individuals of European ancestry. After these steps, we identified and replicated components of the genomic landscape significantly associated with heart- and blood-related traits. For two traits, lipoprotein(a) levels and neutrophil count, aggregate tests of low-frequency and rare variation were significantly associated across multiple motifs. For a third trait, cardiac troponin T, investigation of regulatory domains identified a locus on chromosome 9. These practical approaches for WGS analysis led to the identification of informative genomic regions and also showed that defined non-coding regions, such as first introns of genes and regulatory domains, are associated with important risk factor phenotypes. This study illustrates the tractable nature of WGS data and outlines an approach for characterizing the genetic architecture of complex traits.
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Affiliation(s)
- Alanna C Morrison
- Human Genetics Center, University of Texas School of Public Health, Houston, TX 77030, USA.
| | - Zhuoyi Huang
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Bing Yu
- Human Genetics Center, University of Texas School of Public Health, Houston, TX 77030, USA
| | - Ginger Metcalf
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Xiaoming Liu
- Human Genetics Center, University of Texas School of Public Health, Houston, TX 77030, USA
| | - Christie Ballantyne
- Section of Cardiovascular Research, Baylor College of Medicine, Houston, TX 77030, USA; Houston Methodist Debakey Heart and Vascular Center, Houston, TX 77030, USA
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21287, USA
| | - Fuli Yu
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Donna Muzny
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Elena Feofanova
- Human Genetics Center, University of Texas School of Public Health, Houston, TX 77030, USA
| | - Navin Rustagi
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Richard Gibbs
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Eric Boerwinkle
- Human Genetics Center, University of Texas School of Public Health, Houston, TX 77030, USA; Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA.
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Huang Z, Rustagi N, Veeraraghavan N, Carroll A, Gibbs R, Boerwinkle E, Venkata MG, Yu F. A hybrid computational strategy to address WGS variant analysis in >5000 samples. BMC Bioinformatics 2016; 17:361. [PMID: 27612449 PMCID: PMC5018196 DOI: 10.1186/s12859-016-1211-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2016] [Accepted: 08/25/2016] [Indexed: 11/22/2022] Open
Abstract
Background The decreasing costs of sequencing are driving the need for cost effective and real time variant calling of whole genome sequencing data. The scale of these projects are far beyond the capacity of typical computing resources available with most research labs. Other infrastructures like the cloud AWS environment and supercomputers also have limitations due to which large scale joint variant calling becomes infeasible, and infrastructure specific variant calling strategies either fail to scale up to large datasets or abandon joint calling strategies. Results We present a high throughput framework including multiple variant callers for single nucleotide variant (SNV) calling, which leverages hybrid computing infrastructure consisting of cloud AWS, supercomputers and local high performance computing infrastructures. We present a novel binning approach for large scale joint variant calling and imputation which can scale up to over 10,000 samples while producing SNV callsets with high sensitivity and specificity. As a proof of principle, we present results of analysis on Cohorts for Heart And Aging Research in Genomic Epidemiology (CHARGE) WGS freeze 3 dataset in which joint calling, imputation and phasing of over 5300 whole genome samples was produced in under 6 weeks using four state-of-the-art callers. The callers used were SNPTools, GATK-HaplotypeCaller, GATK-UnifiedGenotyper and GotCloud. We used Amazon AWS, a 4000-core in-house cluster at Baylor College of Medicine, IBM power PC Blue BioU at Rice and Rhea at Oak Ridge National Laboratory (ORNL) for the computation. AWS was used for joint calling of 180 TB of BAM files, and ORNL and Rice supercomputers were used for the imputation and phasing step. All other steps were carried out on the local compute cluster. The entire operation used 5.2 million core hours and only transferred a total of 6 TB of data across the platforms. Conclusions Even with increasing sizes of whole genome datasets, ensemble joint calling of SNVs for low coverage data can be accomplished in a scalable, cost effective and fast manner by using heterogeneous computing platforms without compromising on the quality of variants. Electronic supplementary material The online version of this article (doi:10.1186/s12859-016-1211-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Zhuoyi Huang
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Navin Rustagi
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | | | | | - Richard Gibbs
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Eric Boerwinkle
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.,Human Genetics Center, University of Texas Health Science Center, Houston, TX, USA
| | | | - Fuli Yu
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.
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Du C, Pusey BN, Adams CJ, Lau CC, Bone WP, Gahl WA, Markello TC, Adams DR. Explorations to improve the completeness of exome sequencing. BMC Med Genomics 2016; 9:56. [PMID: 27568008 PMCID: PMC5002202 DOI: 10.1186/s12920-016-0216-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2015] [Accepted: 08/05/2016] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Exome sequencing has advanced to clinical practice and proven useful for obtaining molecular diagnoses in rare diseases. In approximately 75 % of cases, however, a clinical exome study does not produce a definitive molecular diagnosis. These residual cases comprise a new diagnostic challenge for the genetics community. The Undiagnosed Diseases Program of the National Institutes of Health routinely utilizes exome sequencing for refractory clinical cases. Our preliminary data suggest that disease-causing variants may be missed by current standard-of-care clinical exome analysis. Such false negatives reflect limitations in experimental design, technical performance, and data analysis. RESULTS We present examples from our datasets to quantify the analytical performance associated with current practices, and explore strategies to improve the completeness of data analysis. In particular, we focus on patient ascertainment, exome capture, inclusion of intronic variants, and evaluation of medium-sized structural variants. CONCLUSIONS The strategies we present may recover previously-missed, disease causing variants in second-pass exome analysis. Understanding the limitations of the current clinical exome search space provides a rational basis to improve methods for disease variant detection using genome-scale sequencing techniques.
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Affiliation(s)
- Chen Du
- NIH Undiagnosed Diseases Program, Common Fund, National Institutes of Health, National Human Genome Research Institute, Bethesda, MD, USA
| | - Barbara N Pusey
- NIH Undiagnosed Diseases Program, Common Fund, National Institutes of Health, National Human Genome Research Institute, Bethesda, MD, USA
| | - Christopher J Adams
- NIH Undiagnosed Diseases Program, Common Fund, National Institutes of Health, National Human Genome Research Institute, Bethesda, MD, USA
| | - C Christopher Lau
- NIH Undiagnosed Diseases Program, Common Fund, National Institutes of Health, National Human Genome Research Institute, Bethesda, MD, USA
| | - William P Bone
- NIH Undiagnosed Diseases Program, Common Fund, National Institutes of Health, National Human Genome Research Institute, Bethesda, MD, USA
| | - William A Gahl
- NIH Undiagnosed Diseases Program, Common Fund, National Institutes of Health, National Human Genome Research Institute, Bethesda, MD, USA
| | - Thomas C Markello
- NIH Undiagnosed Diseases Program, Common Fund, National Institutes of Health, National Human Genome Research Institute, Bethesda, MD, USA
| | - David R Adams
- NIH Undiagnosed Diseases Program, Common Fund, National Institutes of Health, National Human Genome Research Institute, Bethesda, MD, USA.
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