The demographic history and mutational load of African hunter-gatherers and farmers

AbstractThe distribution of deleterious genetic variation across human populations is a key issue in evolutionary biology and medical genetics. However, the impact of different modes of subsistence on recent changes in population size, patterns of gene flow, and deleterious mutational load remains unclear. Here, we report high-coverage exome sequencing data from various populations of rainforest hunter-gatherers and farmers from central Africa. We find that the recent demographic histories of hunter-gatherers and farmers differed considerably, with population collapses for hunter-gatherers and expansions for farmers, accompanied by increased gene flow. We show that purifying selection against deleterious alleles is of similar efficiency across African populations, in contrast with Europeans where we detect weaker purifying selection. Furthermore, the per-individual mutation load of rainforest hunter-gatherers is similar to that of farmers, under both additive and recessive models. Our results indicate that differences in the cultural practices and demographic regimes of African populations have not resulted in large differences in mutational burden, and highlight the beneficial role of gene flow in reshaping the distribution of deleterious genetic variation across human populations.

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Recent demography drives changes in linked selection across the maize genome

10.1101/031666 ◽

2015 ◽

Author(s):

Timothy M. Beissinger ◽

Li Wang ◽

Kate Crosby ◽

Arun Durvasula ◽

Matthew B. Hufford ◽

...

Keyword(s):

Population Size ◽

Demographic History ◽

Purifying Selection ◽

Rapid Expansion ◽

Whole Genome Sequencing Data ◽

Whole Genome ◽

Sequencing Data ◽

Effective Population ◽

The Impact ◽

Linked Selection

AbstractGenetic diversity is shaped by the interaction of drift and selection, but the details of this interaction are not well understood. The impact of genetic drift in a population is largely determined by its demographic history, typically summarized by its long-term effective population size (Ne). Rapidly changing population demographics complicate this relationship, however. To better understand how changing demography impacts selection, we used whole-genome sequencing data to investigate patterns of linked selection in domesticated and wild maize (teosinte). We produce the first whole-genome estimate of the demography of maize domestication, showing that maize was reduced to approximately 5% the population size of teosinte before it experienced rapid expansion post-domestication to population sizes much larger than its ancestor. Evaluation of patterns of nucleotide diversity in and near genes shows little evidence of selection on beneficial amino acid substitutions, and that the domestication bottleneck led to a decline in the efficiency of purifying selection in maize. Young alleles, however, show evidence of much stronger purifying selection in maize, reflecting the much larger effective size of present day populations. Our results demonstrate that recent demographic change — a hallmark of many species including both humans and crops — can have immediate and wide-ranging impacts on diversity that conflict with would-be expectations based on Ne alone.

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Efficient phasing and imputation of low-coverage sequencing data using large reference panels

10.1101/2020.04.14.040329 ◽

2020 ◽

Cited By ~ 2

Author(s):

S. Rubinacci ◽

D.M. Ribeiro ◽

R. Hofmeister ◽

O. Delaneau

Keyword(s):

Paradigm Shift ◽

Rare Variants ◽

Association Studies ◽

Cost Effective ◽

Human Populations ◽

Sequencing Data ◽

Snp Arrays ◽

Genomic Studies ◽

Low Coverage ◽

The Impact

AbstractLow-coverage whole genome sequencing followed by imputation has been proposed as a cost-effective genotyping approach for disease and population genetics studies. However, its competitiveness against SNP arrays is undermined as current imputation methods are computationally expensive and unable to leverage large reference panels.Here, we describe a method, GLIMPSE, for phasing and imputation of low-coverage sequencing datasets from modern reference panels. We demonstrate its remarkable performance across different coverages and human populations. It achieves imputation of a full genome for less than $1, outperforming existing methods by orders of magnitude, with an increased accuracy of more than 20% at rare variants. We also show that 1x coverage enables effective association studies and is better suited than dense SNP arrays to access the impact of rare variations. Overall, this study demonstrates the promising potential of low-coverage imputation and suggests a paradigm shift in the design of future genomic studies.

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The genomic impact of European colonization of the Americas

10.1101/676437 ◽

2019 ◽

Cited By ~ 1

Author(s):

Linda Ongaro ◽

Marilia O. Scliar ◽

Rodrigo Flores ◽

Alessandro Raveane ◽

Davide Marnetto ◽

...

Keyword(s):

Gene Flow ◽

Demographic History ◽

Colonial Era ◽

Genome Wide ◽

A Genome ◽

European Colonization ◽

High Degree ◽

The Impact ◽

North And South America ◽

North And South

AbstractThe human genetic diversity of the Americas has been shaped by several events of gene flow that have continued since the Colonial Era and the Atlantic slave trade. Moreover, multiple waves of migration followed by local admixture occurred in the last two centuries, the impact of which has been largely unexplored.Here we compiled a genome-wide dataset of ∼12,000 individuals from twelve American countries and ∼6,000 individuals from worldwide populations and applied haplotype-based methods to investigate how historical movements from outside the New World affected i) the genetic structure, ii) the admixture profile, iii) the demographic history and iv) sex-biased gene-flow dynamics, of the Americas.We revealed a high degree of complexity underlying the genetic contribution of European and African populations in North and South America, from both geographic and temporal perspectives, identifying previously unreported sources related to Italy, the Middle East and to specific regions of Africa.

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Tracking human population structure through time from whole genome sequences

10.1101/585265 ◽

2019 ◽

Cited By ~ 4

Author(s):

Ke Wang ◽

Iain Mathieson ◽

Jared O’Connell ◽

Stephan Schiffels

Keyword(s):

Population Structure ◽

Gene Flow ◽

Demographic History ◽

Time Dependent ◽

Human Populations ◽

Whole Genome ◽

Genome Sequences ◽

Migration Model ◽

Novel Approach ◽

Different Populations

AbstractThe genetic diversity of humans, like many species, has been shaped by a complex pattern of population separations followed by isolation and subsequent admixture. This pattern, reaching at least as far back as the appearance of our species in the paleontological record, has left its traces in our genomes. Reconstructing a population’s history from these traces is a challenging problem. Here we present a novel approach based on the Multiple Sequentially Markovian Coalescent (MSMC) to analyse the population separation history. Our approach, called MSMC-IM, uses an improved implementation of the MSMC (MSMC2) to estimate coalescence rates within and across pairs of populations, and then fits a continuous Isolation-Migration model to these rates to obtain a time-dependent estimate of gene flow. We show, using simulations, that our method can identify complex demographic scenarios involving post-split admixture or archaic introgression. We apply MSMC-IM to whole genome sequences from 15 worldwide populations, tracking the process of human genetic diversification. We detect traces of extremely deep ancestry between some African populations, with around 1% of ancestry dating to divergences older than a million years ago.Author SummaryHuman demographic history is reflected in specific patterns of shared mutations between the genomes from different populations. Here we aim to unravel this pattern to infer population structure through time with a new approach, called MSMC-IM. Based on estimates of coalescence rates within and across populations, MSMC-IM fits a time-dependent migration model to the pairwise rate of coalescences. We implemented this approach as an extension to existing software (MSMC2), and tested it with simulations exhibiting different histories of admixture and gene flow. We then applied it to the genomes from 15 worldwide populations to reveal their pairwise separation history ranging from a few thousand up to several million years ago. Among other results, we find evidence for remarkably deep population structure in some African population pairs, suggesting that deep ancestry dating to one million years ago and older is still present in human populations in small amounts today.

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Global patterns of genetic variation and association with clinical phenotypes at genes involved in SARS-CoV-2 infection

10.1101/2021.06.28.21259529 ◽

2021 ◽

Author(s):

Chao Zhang ◽

Anurag Verma ◽

Yuanqing Feng ◽

Marcelo C. R. Melo ◽

Michael McQuillan ◽

...

Keyword(s):

Genetic Variation ◽

Positive Selection ◽

Low Frequency ◽

Purifying Selection ◽

Upper Respiratory Tract ◽

Genetic Associations ◽

Hunter Gatherers ◽

Clinical Phenotypes ◽

Global Patterns ◽

Coding Variants

The COVID-19 pandemic caused by SARS-COV-2 has had a devastating impact on population health. We investigated global patterns of genetic variation and signatures of natural selection at host genes relevant to SARS-CoV-2 infection (ACE2, TMPRSS2, DPP4, and LY6E). We analyzed novel data from 2,012 ethnically diverse Africans, 15,997 individuals of European (7,061) and African (8,916) ancestry recruited by the Penn Medicine BioBank (PMBB), and comparative data from 2,504 individuals from the 1000 Genomes project. At ACE2 we identified 41 non-synonymous variants, found to be at low frequency in most populations. However, three non-synonymous variants were frequent among Central African hunter-gatherers (CAHG) from Cameroon, and signatures of positive selection could be detected on haplotypes encompassing those variants. We also detected signatures of positive selection for variants at regulatory regions upstream of ACE2 in diverse African populations. At TMPRSS2, we identified 48 non-synonymous variants, several of which are common in global populations, and 13 amino acid changes that are fixed in the human lineage after divergence from Chimpanzee. At DPP4 and LY6E most variants were rare in global populations indicating that purifying selection is acting at these loci. At all four loci, we identified common non-coding variants associated with gene expression that vary in frequency across global populations. By analyzing electronic health records from the PMBB we discovered genetic associations with clinical phenotypes, such as respiratory failure with ACE2 and upper respiratory tract infection with DPP4. Our study provides new insights into global variation at genes potentially affecting susceptibility to SARS-CoV-2 infection.

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Genetic diversity of CHC22 clathrin impacts its function in glucose metabolism

eLife ◽

10.7554/elife.41517 ◽

2019 ◽

Vol 8 ◽

Cited By ~ 11

Author(s):

Matteo Fumagalli ◽

Stephane M Camus ◽

Yoan Diekmann ◽

Alice Burke ◽

Marine D Camus ◽

...

Keyword(s):

Glucose Transporter ◽

Phylogenetic Analyses ◽

Insulin Response ◽

Membrane Traffic ◽

Purifying Selection ◽

Human Populations ◽

Gene Encoding ◽

Hunter Gatherers ◽

Functional Studies ◽

Glucose Transporter Glut4

CHC22 clathrin plays a key role in intracellular membrane traffic of the insulin-responsive glucose transporter GLUT4 in humans. We performed population genetic and phylogenetic analyses of the CHC22-encoding CLTCL1 gene, revealing independent gene loss in at least two vertebrate lineages, after arising from gene duplication. All vertebrates retained the paralogous CLTC gene encoding CHC17 clathrin, which mediates endocytosis. For vertebrates retaining CLTCL1, strong evidence for purifying selection supports CHC22 functionality. All human populations maintained two high frequency CLTCL1 allelic variants, encoding either methionine or valine at position 1316. Functional studies indicated that CHC22-V1316, which is more frequent in farming populations than in hunter-gatherers, has different cellular dynamics than M1316-CHC22 and is less effective at controlling GLUT4 membrane traffic, altering its insulin-regulated response. These analyses suggest that ancestral human dietary change influenced selection of allotypes that affect CHC22’s role in metabolism and have potential to differentially influence the human insulin response.

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The mixed genetic origin of the first farmers of Europe

10.1101/2020.11.23.394502 ◽

2020 ◽

Author(s):

Nina Marchi ◽

Laura Winkelbach ◽

Ilektra Schulz ◽

Maxime Brami ◽

Zuzana Hofmanová ◽

...

Keyword(s):

Population Genomics ◽

Near East ◽

Demographic History ◽

Time Frame ◽

Western Anatolia ◽

Human Populations ◽

Climatic Fluctuations ◽

Genetic Origins ◽

Early Farmers ◽

The Impact

SummaryWhile the Neolithic expansion in Europe is well described archaeologically, the genetic origins of European first farmers and their affinities with local hunter-gatherers (HGs) remain unclear. To infer the demographic history of these populations, the genomes of 15 ancient individuals located between Western Anatolia and Southern Germany were sequenced to high quality, allowing us to perform population genomics analyses formerly restricted to modern genomes. We find that all European and Anatolian early farmers descend from the merging of a European and a Near Eastern group of HGs, possibly in the Near East, shortly after the Last Glacial Maximum (LGM). Western and Southeastern European HG are shown to split during the LGM, and share signals of a very strong LGM bottleneck that drastically reduced their genetic diversity. Early Neolithic Central Anatolians seem only indirectly related to ancestors of European farmers, who probably originated in the Near East and dispersed later on from the Aegean along the Danubian corridor following a stepwise demic process with only limited (2-6%) but additive input from local HGs.Our analyses provide a time frame and resolve the genetic origins of early European farmers. They highlight the impact of Late Pleistocene climatic fluctuations that caused the fragmentation, merging and reexpansion of human populations in SW Asia and Europe, and eventually led to the world's first agricultural populations.

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Genetic and morphological differentiation among populations of the Rivoli’s Hummingbird (Eugenes fulgens) species complex (Aves: Trochilidae)

The Auk ◽

10.1093/auk/ukaa032 ◽

2020 ◽

Vol 137 (4) ◽

Cited By ~ 1

Author(s):

Luz E Zamudio-Beltrán ◽

Juan Francisco Ornelas ◽

Andreia Malpica ◽

Blanca E Hernández-Baños

Keyword(s):

Genetic Variation ◽

Gene Flow ◽

Genetic Differentiation ◽

Species Complex ◽

Ecological Niche Modeling ◽

Demographic History ◽

Morphological Differentiation ◽

Last Interglacial ◽

Haplotype Networks ◽

Isthmus Of Tehuantepec

Abstract Genetic variation and phylogeographic studies have been crucial for understanding mechanisms of speciation. We analyzed genetic variation and phylogeography to reconstruct the demographic history of the Rivoli’s Hummingbird (Eugenes fulgens) species complex and also evaluated their morphological differentiation. This widely distributed species inhabits the highlands of Mexico and northern Central America, with 2 subspecies separated by the Isthmus of Tehuantepec (west: E. f. fulgens, east: E. f. viridiceps). We surveyed genetic variation in 2 mitochondrial DNA markers (mtDNA, with 129 individuals) and nuclear DNA (6 microsatellites, with 85 individuals). We also inferred the demographic history, estimated divergence times, and analyzed morphological variation using 470 vouchered specimens. We modeled the current potential distribution of the species using ecological niche modeling and projected it into the past to model the effects of the Pleistocene climatic cycles. Haplotype networks, pairwise FST comparisons, AMOVA, and morphological analysis revealed differences between geographically isolated populations separated by the Isthmus of Tehuantepec (IT; corresponding to the 2 recognized subspecies: fulgens and viridiceps), and by the Motagua-Polochic-Jocotán (MPJ) system fault. Demographic scenarios revealed a contraction in distribution during the last interglacial, and expansion during the Last Glacial Maximum (LGM) with little change since the LGM. Divergence between groups separated by the Isthmus of Tehuantepec ~59,600 yr ago occurred in the presence of gene flow, suggesting that the Isthmus of Tehuantepec is a semipermeable barrier to gene flow. STRUCTURE analyses of microsatellite data detected 3 genetically differentiated groups. Several results fit a model of recent lineage divergence, including a significant signal of genetic differentiation, demographic expansion, decreased gene flow from past to present, and northward expansion during the LGM and contraction during the interglacial periods. We conclude that the genetic differentiation of E. fulgens in the Madrean Pine-Oak Woodlands resulted from recent geographical isolation of populations separated by natural barriers (IT and MPJ).

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Transfer RNA genes experience exceptionally elevated mutation rates

10.1101/229906 ◽

2017 ◽

Cited By ~ 1

Author(s):

Bryan P. Thornlow ◽

Josh Hough ◽

Jacquelyn M. Roger ◽

Henry Gong ◽

Todd M. Lowe ◽

...

Keyword(s):

Mutation Rate ◽

Sequence Variation ◽

Trna Gene ◽

Purifying Selection ◽

Transfer Rna ◽

Mutation Rates ◽

Biological Synthesis ◽

Human Populations ◽

Trna Genes ◽

Mutational Load

AbstractTransfer RNAs (tRNAs) are a central component for the biological synthesis of proteins, and they are among the most highly conserved and frequently transcribed genes in all living things. Despite their clear significance for fundamental cellular processes, the forces governing tRNA evolution are poorly understood. We present evidence that transcription-associated mutagenesis and strong purifying selection are key determinants of patterns of sequence variation within and surrounding tRNA genes in humans and diverse model organisms. Remarkably, the mutation rate at broadly expressed cytosolic tRNA loci is likely between seven and ten times greater than the nuclear genome average. Furthermore, evolutionary analyses provide strong evidence that tRNA genes, but not their flanking sequences, experience strong purifying selection, acting against this elevated mutation rate. We also find a strong correlation between tRNA expression levels and the mutation rates in their immediate flanking regions, suggesting a simple new method for estimating individual tRNA gene activity. Collectively, this study illuminates the extreme competing forces in tRNA gene evolution, and implies that mutations at tRNA loci contribute disproportionately to mutational load and have unexplored fitness consequences in human populations.Significance StatementWhile transcription-associated mutagenesis (TAM) has been demonstrated for protein coding genes, its implications in shaping genome structure at transfer RNA (tRNA) loci in metazoans have not been fully appreciated. We show that cytosolic tRNAs are a striking example of TAM because of their variable rates of transcription, well-defined boundaries and internal promoter sequences. tRNA loci have a mutation rate approximately seven-to tenfold greater than the genome-wide average, and these mutations are consistent with signatures of TAM. These observations indicate that tRNA loci are disproportionately large contributors to mutational load in the human genome. Furthermore, the correlations between tRNA locus variation and transcription implicate that prediction of tRNA gene expression based on sequence variation data is possible.

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The impact of recent population history on the deleterious mutation load in humans and close evolutionary relatives

10.1101/073635 ◽

2016 ◽

Author(s):

Yuval B. Simons ◽

Guy Sella

Keyword(s):

Demographic History ◽

Population History ◽

Human Populations ◽

Data Sets ◽

Loss Of Function ◽

Mutation Load ◽

Synonymous Mutations ◽

Show Evidence ◽

Out Of Africa ◽

The Impact

AbstractOver the past decade, there has been both great interest and confusion about whether recent demographic events—notably the Out-of-Africa-bottleneck and recent population growth—have led to differences in mutation load among human populations. The confusion can be traced to the use of different summary statistics to measure load, which lead to apparently conflicting results. We argue, however, that when statistics more directly related to load are used, the results of different studies and data sets consistently reveal little or no difference in the load of non-synonymous mutations among human populations. Theory helps to understand why no such differences are seen, as well as to predict in what settings they are to be expected. In particular, as predicted by modeling, there is evidence for changes in the load of recessive loss of function mutations in founder and inbred human populations. Also as predicted, eastern subspecies of gorilla, Neanderthals and Denisovans, who are thought to have undergone reductions in population sizes that exceed the human Out-of-Africa bottleneck in duration and severity, show evidence for increased load of non-synonymous mutations (relative to western subspecies of gorillas and modern humans, respectively). A coherent picture is thus starting to emerge about the effects of demographic history on the mutation load in populations of humans and close evolutionary relatives.

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