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Pearson NM, Novembre J. No evidence that ACE2 or TMPRSS2 drive population disparity in COVID risks. BMC Med 2024; 22:337. [PMID: 39183295 PMCID: PMC11346279 DOI: 10.1186/s12916-024-03539-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 07/22/2024] [Indexed: 08/27/2024] Open
Abstract
Early in the SARS-CoV2 pandemic, in this journal, Hou et al. (BMC Med 18:216, 2020) interpreted public genotype data, run through functional prediction tools, as suggesting that members of particular human populations carry potentially COVID-risk-increasing variants in genes ACE2 and TMPRSS2 far more often than do members of other populations. Beyond resting on predictions rather than clinical outcomes, and focusing on variants too rare to typify population members even jointly, their claim mistook a well known artifact (that large samples reveal more of a population's variants than do small samples) as if showing real and congruent population differences for the two genes, rather than lopsided population sampling in their shared source data. We explain that artifact, and contrast it with empirical findings, now ample, that other loci shape personal COVID risks far more significantly than do ACE2 and TMPRSS2-and that variation in ACE2 and TMPRSS2 per se unlikely exacerbates any net population disparity in the effects of such more risk-informative loci.
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Affiliation(s)
| | - John Novembre
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
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2
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Nursyifa C, Brüniche-Olsen A, Garcia-Erill G, Heller R, Albrechtsen A. Joint identification of sex and sex-linked scaffolds in non-model organisms using low depth sequencing data. Mol Ecol Resour 2021; 22:458-467. [PMID: 34431216 DOI: 10.1111/1755-0998.13491] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 07/23/2021] [Accepted: 08/12/2021] [Indexed: 12/17/2022]
Abstract
Being able to assign sex to individuals and identify autosomal and sex-linked scaffolds are essential in most population genomic analyses. Non-model organisms often have genome assemblies at scaffold-level and lack characterization of sex-linked scaffolds. Previous methods to identify sex and sex-linked scaffolds have relied on synteny between the non-model organism and a closely related species or prior knowledge about the sex of the samples to identify sex-linked scaffolds. In the latter case, the difference in depth of coverage between the autosomes and the sex chromosomes are used. Here, we present "sex assignment through coverage" (SATC), a method to assign sex to samples and identify sex-linked scaffolds from next generation sequencing (NGS) data. The method works for species with a homogametic/heterogametic sex determination system and only requires a scaffold-level reference assembly and sampling of both sexes with whole genome sequencing (WGS) data. We use the sequencing depth distribution across scaffolds to jointly identify: (i) male and female individuals, and (ii) sex-linked scaffolds. This is achieved through projecting the scaffold depths into a low-dimensional space using principal component analysis (PCA) and subsequent Gaussian mixture clustering. We demonstrate the applicability of our method using data from five mammal species and a bird species complex. The method is freely available at https://github.com/popgenDK/SATC as R code and a graphical user interface (GUI).
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Affiliation(s)
- Casia Nursyifa
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Anna Brüniche-Olsen
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Genis Garcia-Erill
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Rasmus Heller
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Anders Albrechtsen
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
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3
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Le Guen Y, Napolioni V, Belloy ME, Yu E, Krohn L, Ruskey JA, Gan-Or Z, Kennedy G, Eger SJ, Greicius MD. Common X-Chromosome Variants Are Associated with Parkinson Disease Risk. Ann Neurol 2021; 90:22-34. [PMID: 33583074 PMCID: PMC8601399 DOI: 10.1002/ana.26051] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Revised: 02/12/2021] [Accepted: 02/12/2021] [Indexed: 12/14/2022]
Abstract
OBJECTIVE The objective of this study was to identify genetic variants on the X-chromosome associated with Parkinson disease (PD) risk. METHODS We performed an X-chromosome-wide association study (XWAS) of PD risk by meta-analyzing results from sex-stratified analyses. To avoid spurious associations, we designed a specific harmonization pipeline for the X-chromosome and focused on a European ancestry sample. We included 11,142 cases, 280,164 controls, and 5,379 proxy cases, based on parental history of PD. Additionally, we tested the association of significant variants with (1) PD risk in an independent replication with 1,561 cases and 2,465 controls and (2) putamen volume in 33,360 individuals from the UK Biobank. RESULTS In the discovery meta-analysis, we identified rs7066890 (odds ratio [OR] = 1.10, 95% confidence interval [CI] = 1.06-1.14, p = 2.2 × 10-9 ), intron of GPM6B, and rs28602900 (OR = 1.10, 95% CI = 1.07-1.14, p = 1.6 × 10-8 ) in a high gene density region including RPL10, ATP6A1, FAM50A, and PLXNA3. The rs28602900 association with PD was replicated (OR = 1.16, 95% CI = 1.03-1.30, p = 0.016) and shown to colocalize with a significant expression quantitative locus (eQTL) regulating RPL10 expression in the putamen and other brain tissues in the Genotype-Tissue Expression Project. Additionally, the rs28602900 locus was found to be associated with reduced brain putamen volume. No results reached genome-wide significance in the sex-stratified analyses. INTERPRETATION We report the first XWAS of PD and identify 2 genome-wide significant loci. The rs28602900 association was replicated in an independent PD dataset and showed concordant effects in its association with putamen volume. Critically, rs26802900 is a significant eQTL of RPL10. These results support a role for ribosomal proteins in PD pathogenesis and show that the X-chromosome contributes to PD genetic risk. ANN NEUROL 2021;90:22-34.
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Affiliation(s)
- Yann Le Guen
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Valerio Napolioni
- School of Biosciences and Veterinary Medicine, University of Camerino, Camerino, Italy
| | - Michael E Belloy
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Eric Yu
- Department of Human Genetics, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Lynne Krohn
- Department of Human Genetics, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Jennifer A Ruskey
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Ziv Gan-Or
- Department of Human Genetics, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Gabriel Kennedy
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Sarah J Eger
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Michael D Greicius
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
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4
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Lasne C, Van Heerwaarden B, Sgrò CM, Connallon T. Quantifying the relative contributions of the X chromosome, autosomes, and mitochondrial genome to local adaptation. Evolution 2018; 73:262-277. [PMID: 30417348 DOI: 10.1111/evo.13647] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2018] [Revised: 10/29/2018] [Accepted: 11/01/2018] [Indexed: 12/20/2022]
Abstract
During local adaptation with gene flow, some regions of the genome are inherently more responsive to selection than others. Recent theory predicts that X-linked genes should disproportionately contribute to local adaptation relative to other genomic regions, yet this prediction remains to be tested. We carried out a multigeneration crossing scheme, using two cline-end populations of Drosophila melanogaster, to estimate the relative contributions of the X chromosome, autosomes, and mitochondrial genome to divergence in four traits involved in local adaptation (wing size, resistance to heat, desiccation, and starvation stresses). We found that the mitochondrial genome and autosomes contributed significantly to clinal divergence in three of the four traits. In contrast, the X made no significant contribution to divergence in these traits. Given the small size of the mitochondrial genome, our results indicate that it plays a surprisingly large role in clinal adaptation. In contrast, the X, which represents roughly 20% of the Drosophila genome, contributes negligibly-a pattern that conflicts with theoretical predictions. These patterns reinforce recent work implying a central role of mitochondria in climatic adaptation, and suggest that different genomic regions may play fundamentally different roles in processes of divergence with gene flow.
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Affiliation(s)
- Clementine Lasne
- School of Biological Sciences, Monash University, Clayton, Victoria, 3800, Australia
| | | | - Carla M Sgrò
- School of Biological Sciences, Monash University, Clayton, Victoria, 3800, Australia
| | - Tim Connallon
- School of Biological Sciences, Monash University, Clayton, Victoria, 3800, Australia
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5
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Povysil G, Hochreiter S. IBD Sharing between Africans, Neandertals, and Denisovans. Genome Biol Evol 2018; 8:3406-3416. [PMID: 28158547 PMCID: PMC5381509 DOI: 10.1093/gbe/evw234] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/19/2016] [Indexed: 12/03/2022] Open
Abstract
Interbreeding between ancestors of humans and other hominins outside of Africa has been studied intensively, while their common history within Africa still lacks proper attention. However, shedding light on human evolution in this time period about which little is known, is essential for understanding subsequent events outside of Africa. We investigate the genetic relationships of humans, Neandertals, and Denisovans by identifying very short DNA segments in the 1000 Genomes Phase 3 data that these hominins share identical by descent (IBD). By focusing on low frequency and rare variants, we identify very short IBD segments with high confidence. These segments reveal events from a very distant past because shorter IBD segments are presumably older than longer ones. We extracted two types of very old IBD segments that are not only shared among humans, but also with Neandertals and/or Denisovans. The first type contains longer segments that are found primarily in Asians and Europeans where more segments are found in South Asians than in East Asians for both Neandertal and Denisovan. These longer segments indicate complex admixture events outside of Africa. The second type consists of shorter segments that are shared mainly by Africans and therefore may indicate events involving ancestors of humans and other ancient hominins within Africa. Our results from the autosomes are further supported by an analysis of chromosome X, on which segments that are shared by Africans and match the Neandertal and/or Denisovan genome were even more prominent. Our results indicate that interbreeding with other hominins was a common feature of human evolution starting already long before ancestors of modern humans left Africa.
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Affiliation(s)
- Gundula Povysil
- Institute of Bioinformatics, Johannes Kepler University Linz, Austria
| | - Sepp Hochreiter
- Institute of Bioinformatics, Johannes Kepler University Linz, Austria
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6
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Pracana R, Priyam A, Levantis I, Nichols RA, Wurm Y. The fire ant social chromosome supergene variant Sb shows low diversity but high divergence from SB. Mol Ecol 2017; 26:2864-2879. [PMID: 28220980 PMCID: PMC5485014 DOI: 10.1111/mec.14054] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2016] [Revised: 01/22/2017] [Accepted: 02/06/2017] [Indexed: 02/01/2023]
Abstract
Variation in social behaviour is common, yet little is known about the genetic architectures underpinning its evolution. A rare exception is in the fire ant Solenopsis invicta: Alternative variants of a supergene region determine whether a colony will have exactly one or up to dozens of queens. The two variants of this region are carried by a pair of 'social chromosomes', SB and Sb, which resemble a pair of sex chromosomes. Recombination is suppressed between the two chromosomes in the supergene region. While the X-like SB can recombine with itself in SB/SB queens, recombination is effectively absent in the Y-like Sb because Sb/Sb queens die before reproducing. Here, we analyse whole-genome sequences of eight haploid SB males and eight haploid Sb males. We find extensive SB-Sb differentiation throughout the >19-Mb-long supergene region. We find no evidence of 'evolutionary strata' with different levels of divergence comparable to those reported in several sex chromosomes. A high proportion of substitutions between the SB and Sb haplotypes are nonsynonymous, suggesting inefficacy of purifying selection in Sb sequences, similar to that for Y-linked sequences in XY systems. Finally, we show that the Sb haplotype of the supergene region has 635-fold less nucleotide diversity than the rest of the genome. We discuss how this reduction could be due to a recent selective sweep affecting Sb specifically or associated with a population bottleneck during the invasion of North America by the sampled population.
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Affiliation(s)
- Rodrigo Pracana
- School of Biological and Chemical SciencesQueen Mary University of LondonMile End RoadLondonE1 4NSUK
| | - Anurag Priyam
- School of Biological and Chemical SciencesQueen Mary University of LondonMile End RoadLondonE1 4NSUK
| | - Ilya Levantis
- School of Biological and Chemical SciencesQueen Mary University of LondonMile End RoadLondonE1 4NSUK
| | - Richard A. Nichols
- School of Biological and Chemical SciencesQueen Mary University of LondonMile End RoadLondonE1 4NSUK
| | - Yannick Wurm
- School of Biological and Chemical SciencesQueen Mary University of LondonMile End RoadLondonE1 4NSUK
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7
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Lasne C, Sgrò CM, Connallon T. The Relative Contributions of the X Chromosome and Autosomes to Local Adaptation. Genetics 2017; 205:1285-1304. [PMID: 28064164 PMCID: PMC5340339 DOI: 10.1534/genetics.116.194670] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2016] [Accepted: 12/25/2016] [Indexed: 01/07/2023] Open
Abstract
Models of sex chromosome and autosome evolution yield key predictions about the genomic basis of adaptive divergence, and such models have been important in guiding empirical research in comparative genomics and studies of speciation. In addition to the adaptive differentiation that occurs between species over time, selection also favors genetic divergence across geographic space, with subpopulations of single species evolving conspicuous differences in traits involved in adaptation to local environmental conditions. The potential contribution of sex chromosomes (the X or Z) to local adaptation remains unclear, as we currently lack theory that directly links spatial variation in selection to local adaptation of X-linked and autosomal genes. Here, we develop population genetic models that explicitly consider the effects of genetic dominance, effective population size, and sex-specific migration and selection on the relative contributions of X-linked and autosomal genes to local adaptation. We show that X-linked genes should nearly always disproportionately contribute to local adaptation in the presence of gene flow. We also show that considerations of dominance and effective population size-which play pivotal roles in the theory of faster-X adaptation between species-have surprisingly little influence on the relative contribution of the X chromosome to local adaptation. Instead, sex-biased migration is the primary mediator of the strength of spatial large-X effects. Our results yield novel predictions about the role of sex chromosomes in local adaptation. We outline empirical approaches in evolutionary quantitative genetics and genomics that could build upon this new theory.
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Affiliation(s)
- Clémentine Lasne
- School of Biological Sciences, Monash University, Clayton 3800, Australia
| | - Carla M Sgrò
- School of Biological Sciences, Monash University, Clayton 3800, Australia
| | - Tim Connallon
- School of Biological Sciences, Monash University, Clayton 3800, Australia
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8
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Gao F, Chang D, Biddanda A, Ma L, Guo Y, Zhou Z, Keinan A. XWAS: A Software Toolset for Genetic Data Analysis and Association Studies of the X Chromosome. J Hered 2015; 106:666-71. [PMID: 26268243 PMCID: PMC4567842 DOI: 10.1093/jhered/esv059] [Citation(s) in RCA: 88] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2015] [Accepted: 07/20/2015] [Indexed: 12/21/2022] Open
Abstract
XWAS is a new software suite for the analysis of the X chromosome in association studies and similar genetic studies. The X chromosome plays an important role in human disease and traits of many species, especially those with sexually dimorphic characteristics. Special attention needs to be given to its analysis due to the unique inheritance pattern, which leads to analytical complications that have resulted in the majority of genome-wide association studies (GWAS) either not considering X or mishandling it with toolsets that had been designed for non-sex chromosomes. We hence developed XWAS to fill the need for tools that are specially designed for analysis of X. Following extensive, stringent, and X-specific quality control, XWAS offers an array of statistical tests of association, including: 1) the standard test between a SNP (single nucleotide polymorphism) and disease risk, including after first stratifying individuals by sex, 2) a test for a differential effect of a SNP on disease between males and females, 3) motivated by X-inactivation, a test for higher variance of a trait in heterozygous females as compared with homozygous females, and 4) for all tests, a version that allows for combining evidence from all SNPs across a gene. We applied the toolset analysis pipeline to 16 GWAS datasets of immune-related disorders and 7 risk factors of coronary artery disease, and discovered several new X-linked genetic associations. XWAS will provide the tools and incentive for others to incorporate the X chromosome into GWAS and similar studies in any species with an XX/XY system, hence enabling discoveries of novel loci implicated in many diseases and in their sexual dimorphism.
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Affiliation(s)
- Feng Gao
- From the Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14853 (Gao, Chang, Biddanda, Ma, Guo, Zhou, and Keinan); Program in Computational Biology and Medicine, Cornell University, Ithaca, NY 14853 (Chang and Keinan); Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20740 (Ma); and School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China (Guo)
| | - Diana Chang
- From the Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14853 (Gao, Chang, Biddanda, Ma, Guo, Zhou, and Keinan); Program in Computational Biology and Medicine, Cornell University, Ithaca, NY 14853 (Chang and Keinan); Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20740 (Ma); and School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China (Guo)
| | - Arjun Biddanda
- From the Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14853 (Gao, Chang, Biddanda, Ma, Guo, Zhou, and Keinan); Program in Computational Biology and Medicine, Cornell University, Ithaca, NY 14853 (Chang and Keinan); Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20740 (Ma); and School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China (Guo)
| | - Li Ma
- From the Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14853 (Gao, Chang, Biddanda, Ma, Guo, Zhou, and Keinan); Program in Computational Biology and Medicine, Cornell University, Ithaca, NY 14853 (Chang and Keinan); Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20740 (Ma); and School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China (Guo)
| | - Yingjie Guo
- From the Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14853 (Gao, Chang, Biddanda, Ma, Guo, Zhou, and Keinan); Program in Computational Biology and Medicine, Cornell University, Ithaca, NY 14853 (Chang and Keinan); Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20740 (Ma); and School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China (Guo)
| | - Zilu Zhou
- From the Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14853 (Gao, Chang, Biddanda, Ma, Guo, Zhou, and Keinan); Program in Computational Biology and Medicine, Cornell University, Ithaca, NY 14853 (Chang and Keinan); Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20740 (Ma); and School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China (Guo)
| | - Alon Keinan
- From the Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14853 (Gao, Chang, Biddanda, Ma, Guo, Zhou, and Keinan); Program in Computational Biology and Medicine, Cornell University, Ithaca, NY 14853 (Chang and Keinan); Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20740 (Ma); and School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China (Guo).
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9
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Abstract
Sex-biased demography, in which parameters governing migration and population size differ between females and males, has been studied through comparisons of X chromosomes, which are inherited sex-specifically, and autosomes, which are not. A common form of sex bias in humans is sex-biased admixture, in which at least one of the source populations differs in its proportions of females and males contributing to an admixed population. Studies of sex-biased admixture often examine the mean ancestry for markers on the X chromosome in relation to the autosomes. A simple framework noting that in a population with equally many females and males, two-thirds of X chromosomes appear in females, suggests that the mean X-chromosomal admixture fraction is a linear combination of female and male admixture parameters, with coefficients 2/3 and 1/3, respectively. Extending a mechanistic admixture model to accommodate the X chromosome, we demonstrate that this prediction is not generally true in admixture models, although it holds in the limit for an admixture process occurring as a single event. For a model with constant ongoing admixture, we determine the mean X-chromosomal admixture, comparing admixture on female and male X chromosomes to corresponding autosomal values. Surprisingly, in reanalyzing African-American genetic data to estimate sex-specific contributions from African and European sources, we find that the range of contributions compatible with the excess African ancestry on the X chromosome compared to autosomes has a wide spread, permitting scenarios either without male-biased contributions from Europe or without female-biased contributions from Africa.
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10
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Abstract
Sex-biased admixture has been observed in a wide variety of admixed populations. Genetic variation in sex chromosomes and functions of quantities computed from sex chromosomes and autosomes have often been examined to infer patterns of sex-biased admixture, typically using statistical approaches that do not mechanistically model the complexity of a sex-specific history of admixture. Here, expanding on a model of Verdu and Rosenberg (2011) that did not include sex specificity, we develop a model that mechanistically examines sex-specific admixture histories. Under the model, multiple source populations contribute to an admixed population, potentially with their male and female contributions varying over time. In an admixed population descended from two source groups, we derive the moments of the distribution of the autosomal admixture fraction from a specific source population as a function of sex-specific introgression parameters and time. Considering admixture processes that are constant in time, we demonstrate that surprisingly, although the mean autosomal admixture fraction from a specific source population does not reveal a sex bias in the admixture history, the variance of autosomal admixture is informative about sex bias. Specifically, the long-term variance decreases as the sex bias from a contributing source population increases. This result can be viewed as analogous to the reduction in effective population size for populations with an unequal number of breeding males and females. Our approach suggests that it may be possible to use the effect of sex-biased admixture on autosomal DNA to assist with methods for inference of the history of complex sex-biased admixture processes.
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11
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Casto AM, Henn BM, Kidd JM, Bustamante CD, Feldman MW. A tale of two haplotypes: the EDA2R/AR Intergenic region is the most divergent genomic segment between Africans and East Asians in the human genome. Hum Biol 2014; 84:641-94. [PMID: 23959643 DOI: 10.3378/027.084.0604] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/15/2013] [Indexed: 11/05/2022]
Abstract
Single nucleotide polymorphisms (SNPs) with large allele frequency differences between human populations are relatively rare. The longest run of SNPs with an allele frequency difference of one between the Yoruba of Nigeria and the Han Chinese is found on the long arm of the X chromosome in the intergenic region separating the EDA2R and AR genes. It has been proposed that the unusual allele frequency distributions of these SNPs are the result of a selective sweep affecting African populations that occurred after the out-of-Africa migration. To investigate the evolutionary history of the EDA2R/AR intergenic region, we characterized the haplotype structure of 52 of its highly differentiated SNPs. Using a publicly available data set of 3,000 X chromosomes from 65 human populations, we found that nearly all human X chromosomes carry one of two modal haplotypes for these 52 SNPs. The predominance of two highly divergent haplotypes at this locus was confirmed by use of a subset of individuals sequenced to high coverage. The first of these haplotypes, the α-haplotype is at high frequencies in most of the African populations surveyed and likely arose before the separation of African populations into distinct genetic entities. The second, the β-haplotype, is frequent or fixed in all non-African populations and likely arose in East Africa before the out-of-Africa migration. We also observed a small group or rare haplotypes with no clear relationship to the α- and β-haplotypes. These haplotypes occur at relatively high frequencies in African hunter-gatherer populations, such as the San and Mbuti Pygmies. Our analysis indicates that these haplotypes are part of a pool of diverse, ancestral haplotypes that have now been almost entirely replaced by the α- and β-haplotypes. We suggest that the rise of the α- and β-haplotypes was the result of the demographic forces that human populations experienced during the formation of modern African populations and the out-of-Africa migration. However, we also present evidence that this region is the target of selection in the form of positive selection on the α- and β-haplotypes and of purifying the selection against α/β recombinants.
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Affiliation(s)
- Amanda M Casto
- Department of Genetics, Stanford University, Mail Stop 5120, Stanford, California 94305, USA.
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Arbiza L, Gottipati S, Siepel A, Keinan A. Contrasting X-linked and autosomal diversity across 14 human populations. Am J Hum Genet 2014; 94:827-44. [PMID: 24836452 DOI: 10.1016/j.ajhg.2014.04.011] [Citation(s) in RCA: 45] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2014] [Accepted: 04/15/2014] [Indexed: 12/29/2022] Open
Abstract
Contrasting the genetic diversity of the human X chromosome (X) and autosomes has facilitated understanding historical differences between males and females and the influence of natural selection. Previous studies based on smaller data sets have left questions regarding how empirical patterns extend to additional populations and which forces can explain them. Here, we address these questions by analyzing the ratio of X-to-autosomal (X/A) nucleotide diversity with the complete genomes of 569 females from 14 populations. Results show that X/A diversity is similar within each continental group but notably lower in European (EUR) and East Asian (ASN) populations than in African (AFR) populations. X/A diversity increases in all populations with increasing distance from genes, highlighting the stronger impact of diversity-reducing selection on X than on the autosomes. However, relative X/A diversity (between two populations) is invariant with distance from genes, suggesting that selection does not drive the relative reduction in X/A diversity in non-Africans (0.842 ± 0.012 for EUR-to-AFR and 0.820 ± 0.032 for ASN-to-AFR comparisons). Finally, an array of models with varying population bottlenecks, expansions, and migration from the latest studies of human demographic history account for about half of the observed reduction in relative X/A diversity from the expected value of 1. They predict values between 0.91 and 0.94 for EUR-to-AFR comparisons and between 0.91 and 0.92 for ASN-to-AFR comparisons. Further reductions can be predicted by more extreme demographic events in excess of those captured by the latest studies but, in the absence of these, also by historical sex-biased demographic events or other processes.
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13
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Labuda D, Yotova V, Lefebvre JF, Moreau C, Utermann G, Williams SM. X-linked MTMR8 diversity and evolutionary history of sub-Saharan populations. PLoS One 2013; 8:e80710. [PMID: 24282552 PMCID: PMC3839994 DOI: 10.1371/journal.pone.0080710] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2013] [Accepted: 10/07/2013] [Indexed: 01/04/2023] Open
Abstract
The genetic diversity within an 11 kb segment of the MTMR8 gene in a sample of 111 sub-Saharan and 49 non-African X chromosomes was investigated to assess the early evolutionary history of sub-Saharan Africans and the out-of-Africa expansion. The analyses revealed a complex genetic structure of the Africans that contributed to the emergence of modern humans. We observed partitioning of two thirds of old lineages among southern, west/central and east African populations indicating ancient population stratification predating the out of Africa migration. Age estimates of these lineages, older than coalescence times of uniparentally inherited markers, raise the question whether contemporary humans originated from a single population or as an amalgamation of different populations separated by years of independent evolution, thus suggesting a greater antiquity of our species than generally assumed. While the oldest sub-Saharan lineages, ∼500 thousand years, are found among Khoe-San from southern-Africa, a distinct haplotype found among Biaka is likely due to admixture from an even older population. An East African population that gave rise to non-Africans underwent a selective sweep affecting the subcentromeric region where MTMR8 is located. This and similar sweeps in four other regions of the X chromosome, documented in the literature, effectively reduced genetic diversity of non-African chromosomes and therefore may have exacerbated the effect of the demographic bottleneck usually ascribed to the out of Africa migration. Our data is suggestive, however, that a bottleneck, occurred in Africa before range expansion.
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Affiliation(s)
- Damian Labuda
- Centre de Recherche, CHU Sainte-Justine, Université de Montréal, Montréal, Québec, Canada
- Département de Pédiatrie, Université de Montréal, Montréal, Québec, Canada
- * E-mail:
| | - Vania Yotova
- Centre de Recherche, CHU Sainte-Justine, Université de Montréal, Montréal, Québec, Canada
| | - Jean-François Lefebvre
- Centre de Recherche, CHU Sainte-Justine, Université de Montréal, Montréal, Québec, Canada
| | - Claudia Moreau
- Centre de Recherche, CHU Sainte-Justine, Université de Montréal, Montréal, Québec, Canada
| | - Gerd Utermann
- Department of Medical Genetics, Molecular and Clinical Pharmacology, Medical University of Innsbruck, Innsbruck, Austria
| | - Scott M. Williams
- Department of Genetics, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire, United States of America
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14
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Walther M, De Caul A, Aka P, Njie M, Amambua-Ngwa A, Walther B, Predazzi IM, Cunnington A, Deininger S, Takem EN, Ebonyi A, Weis S, Walton R, Rowland-Jones S, Sirugo G, Williams SM, Conway DJ. HMOX1 gene promoter alleles and high HO-1 levels are associated with severe malaria in Gambian children. PLoS Pathog 2012; 8:e1002579. [PMID: 22438807 PMCID: PMC3305414 DOI: 10.1371/journal.ppat.1002579] [Citation(s) in RCA: 72] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2011] [Accepted: 01/26/2012] [Indexed: 01/16/2023] Open
Abstract
Heme oxygenase 1 (HO-1) is an essential enzyme induced by heme and multiple stimuli associated with critical illness. In humans, polymorphisms in the HMOX1 gene promoter may influence the magnitude of HO-1 expression. In many diseases including murine malaria, HO-1 induction produces protective anti-inflammatory effects, but observations from patients suggest these may be limited to a narrow range of HO-1 induction, prompting us to investigate the role of HO-1 in malaria infection. In 307 Gambian children with either severe or uncomplicated P. falciparum malaria, we characterized the associations of HMOX1 promoter polymorphisms, HMOX1 mRNA inducibility, HO-1 protein levels in leucocytes (flow cytometry), and plasma (ELISA) with disease severity. The (GT)(n) repeat polymorphism in the HMOX1 promoter was associated with HMOX1 mRNA expression in white blood cells in vitro, and with severe disease and death, while high HO-1 levels were associated with severe disease. Neutrophils were the main HO-1-expressing cells in peripheral blood, and HMOX1 mRNA expression was upregulated by heme-moieties of lysed erythrocytes. We provide mechanistic evidence that induction of HMOX1 expression in neutrophils potentiates the respiratory burst, and propose this may be part of the causal pathway explaining the association between short (GT)(n) repeats and increased disease severity in malaria and other critical illnesses. Our findings suggest a genetic predisposition to higher levels of HO-1 is associated with severe illness, and enhances the neutrophil burst leading to oxidative damage of endothelial cells. These add important information to the discussion about possible therapeutic manipulation of HO-1 in critically ill patients.
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Affiliation(s)
- Michael Walther
- Medical Research Council Laboratories, Fajara, Banjul, Gambia.
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15
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LI JUNRUI, LI HAIPENG, JAKOBSSON MATTIAS, LI SEN, SJÖDIN PER, LASCOUX MARTIN. Joint analysis of demography and selection in population genetics: where do we stand and where could we go? Mol Ecol 2011; 21:28-44. [DOI: 10.1111/j.1365-294x.2011.05308.x] [Citation(s) in RCA: 112] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Affiliation(s)
- JUNRUI LI
- Laboratory of Evolutionary Genomics, CAS Key Laboratory of Computational Biology, CAS‐MPG Partner Institute for Computational Biology, Chinese Academy of Sciences, Shanghai, China
- Graduate School of the Chinese Academy of Sciences, Beijing 100039, China
| | - HAIPENG LI
- Laboratory of Evolutionary Genomics, CAS Key Laboratory of Computational Biology, CAS‐MPG Partner Institute for Computational Biology, Chinese Academy of Sciences, Shanghai, China
| | - MATTIAS JAKOBSSON
- Department of Evolutionary Biology, Evolutionary Biology Centre, and Science for Life Laboratory, Uppsala University, 752 36 Uppsala, Sweden
| | - SEN LI
- Department of Evolutionary Biology, Evolutionary Biology Centre, and Science for Life Laboratory, Uppsala University, 752 36 Uppsala, Sweden
| | - PER SJÖDIN
- Department of Evolutionary Biology, Evolutionary Biology Centre, and Science for Life Laboratory, Uppsala University, 752 36 Uppsala, Sweden
| | - MARTIN LASCOUX
- Laboratory of Evolutionary Genomics, CAS Key Laboratory of Computational Biology, CAS‐MPG Partner Institute for Computational Biology, Chinese Academy of Sciences, Shanghai, China
- Program in Plant Ecology and Evolution, Department of Ecology and Genetics, Uppsala University, 752 36 Uppsala, Sweden
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16
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Emery LS, Felsenstein J, Akey JM. Estimators of the human effective sex ratio detect sex biases on different timescales. Am J Hum Genet 2010; 87:848-56. [PMID: 21109223 DOI: 10.1016/j.ajhg.2010.10.021] [Citation(s) in RCA: 38] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2010] [Revised: 10/15/2010] [Accepted: 10/22/2010] [Indexed: 12/25/2022] Open
Abstract
Determining historical sex ratios throughout human evolution can provide insight into patterns of genomic variation, the structure and composition of ancient populations, and the cultural factors that influence the sex ratio (e.g., sex-specific migration rates). Although numerous studies have suggested that unequal sex ratios have existed in human evolutionary history, a coherent picture of sex-biased processes has yet to emerge. For example, two recent studies compared human X chromosome to autosomal variation to make inferences about historical sex ratios but reached seemingly contradictory conclusions, with one study finding evidence for a male bias and the other study identifying a female bias. Here, we show that a large part of this discrepancy can be explained by methodological differences. Specifically, through reanalysis of empirical data, derivation of explicit analytical formulae, and extensive simulations we demonstrate that two estimators of the effective sex ratio based on population structure and nucleotide diversity preferentially detect biases that have occurred on different timescales. Our results clarify apparently contradictory evidence on the role of sex-biased processes in human evolutionary history and show that extant patterns of human genomic variation are consistent with both a recent male bias and an earlier, persistent female bias.
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Affiliation(s)
- Leslie S Emery
- Department of Genome Sciences, University of Washington, Seattle, 98195, USA
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17
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Wang Z, Hildesheim A, Wang SS, Herrero R, Gonzalez P, Burdette L, Hutchinson A, Thomas G, Chanock SJ, Yu K. Genetic admixture and population substructure in Guanacaste Costa Rica. PLoS One 2010; 5:e13336. [PMID: 20967209 PMCID: PMC2954167 DOI: 10.1371/journal.pone.0013336] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2010] [Accepted: 08/23/2010] [Indexed: 11/20/2022] Open
Abstract
The population of Costa Rica (CR) represents an admixture of major continental populations. An investigation of the CR population structure would provide an important foundation for mapping genetic variants underlying common diseases and traits. We conducted an analysis of 1,301 women from the Guanacaste region of CR using 27,904 single nucleotide polymorphisms (SNPs) genotyped on a custom Illumina InfiniumII iSelect chip. The program STRUCTURE was used to compare the CR Guanacaste sample with four continental reference samples, including HapMap Europeans (CEU), East Asians (JPT+CHB), West African Yoruba (YRI), as well as Native Americans (NA) from the Illumina iControl database. Our results show that the CR Guanacaste sample comprises a three-way admixture estimated to be 43% European, 38% Native American and 15% West African. An estimated 4% residual Asian ancestry may be within the error range. Results from principal components analysis reveal a correlation between genetic and geographic distance. The magnitude of linkage disequilibrium (LD) measured by the number of tagging SNPs required to cover the same region in the genome in the CR Guanacaste sample appeared to be weaker than that observed in CEU, JPT+CHB and NA reference samples but stronger than that of the HapMap YRI sample. Based on the clustering pattern observed in both STRUCTURE and principal components analysis, two subpopulations were identified that differ by approximately 20% in LD block size averaged over all LD blocks identified by Haploview. We also show in a simulated association study conducted within the two subpopulations, that the failure to account for population stratification (PS) could lead to a noticeable inflation in the false positive rate. However, we further demonstrate that existing PS adjustment approaches can reduce the inflation to an acceptable level for gene discovery.
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Affiliation(s)
- Zhaoming Wang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, United States of America
- Core Genotyping Facility, SAIC Frederick, Inc., National Cancer Institute - Frederick, Frederick, Maryland, United States of America
| | - Allan Hildesheim
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, United States of America
| | - Sophia S. Wang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, United States of America
- Division of Etiology, Department of Population Sciences, Beckman Research Institute and the City of Hope, Duarte, California, United States of America
| | | | - Paula Gonzalez
- Proyecto Epidemiologico Guanacaste, San Jose, Costa Rica
| | - Laurie Burdette
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, United States of America
- Core Genotyping Facility, SAIC Frederick, Inc., National Cancer Institute - Frederick, Frederick, Maryland, United States of America
| | - Amy Hutchinson
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, United States of America
- Core Genotyping Facility, SAIC Frederick, Inc., National Cancer Institute - Frederick, Frederick, Maryland, United States of America
| | - Gilles Thomas
- Synergie-Lyon-Cancer, Universite Lyon 1, Lyon, France
| | - Stephen J. Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, United States of America
| | - Kai Yu
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, United States of America
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18
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Lambert CA, Tishkoff SA. Genetic structure in African populations: implications for human demographic history. COLD SPRING HARBOR SYMPOSIA ON QUANTITATIVE BIOLOGY 2010; 74:395-402. [PMID: 20453204 DOI: 10.1101/sqb.2009.74.053] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
The continent of Africa is the source of all anatomically modern humans that dispersed across the planet during the past 100,000 years. As such, African populations are characterized by high genetic diversity and low levels of linkage disequilibrium (LD) among loci, as compared to populations from other continents. African populations also possess a number of genetic adaptations that have evolved in response to the diverse climates, diets, geographic environments, and infectious agents that characterize the African continent. Recently, Tishkoff et al. (2009) performed a genome-wide analysis of substructure based on DNA from 2432 Africans from 121 geographically diverse populations. The authors analyzed patterns of variation at 1327 nuclear microsatellite and insertion/deletion markers and identified 14 ancestral population clusters that correlate well with self-described ethnicity and shared cultural or linguistic properties. The results suggest that African populations may have maintained a large and subdivided population structure throughout much of their evolutionary history. In this chapter, we synthesize recent work documenting evidence of African population structure and discuss the implications for inferences about evolutionary history in both African populations and anatomically modern humans as a whole.
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Affiliation(s)
- C A Lambert
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
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