Genome-wide Comparison of African-Ancestry Populations from CARe and Other Cohorts Reveals Signals of Natural Selection

Bhatia, Gaurav; Patterson, Nick; Paşaniuc, Bogdan; Zaitlen, Noah; Genovese, Giulio; Pollack, Samuela; Mallick, Swapan; Myers, Simon; Tandon, Arti; Spencer, Chris C. A.; Palmer, Cameron D.; Adeyemo, Adebowale; Akylbekova, Ermeg L.; Cupples, L. Adrienne; Divers, Jasmin; Fornage, Myriam; Kao, W. H. Linda; Lange, Leslie A.; Li, Mingyao; Musani, Solomon K.; Mychaleckyj, Josyf C.; Ogunniyi, Adesola; Papanicolaou, George; Rotimi, Charles N.; Rotter, Jerome I.; Ruczinski, Ingo; Salako, Babatunde Lawal; Siscovick, David S.; Tayo, Bamidele O.; Yang, Qiong; McCarroll, Steven A.; Sabeti, Pardis C.; Lettre, Guillaume; Jager, Phil De; Hirschhorn, Joel N.; Zhu, Xiaofeng; Cooper, Richard S.; Reich, David; Wilson, James G.; Price, Alkes L.

doi:10.1016/j.ajhg.2011.07.025

Cited by 81 publications

(113 citation statements)

References 62 publications

(90 reference statements)

Supporting

Mentioning

105

Contrasting

Unclassified

Order By: Relevance

“…Since the Mandenka and Yoruba both inhabit western Africa, this may indicate strong pressure from infectious or parasite-related diseases in this region or may reflect recent selective pressure associated with adoption of agriculture only 5000 years ago . These enrichments agree with recent studies, which have highlighted pathogens as a primary driver of recent human evolution (Fumagalli et al 2011;Novembre and Han 2012) and which have presented evidence that HLA and other diseaserelated genes are under selection in West Africans (Bhatia et al 2011).…”

Section: Enrichment Of Biological Functionssupporting

confidence: 81%

Limited Evidence for Classic Selective Sweeps in African Populations

et al. 2012

View full text Add to dashboard Cite

While hundreds of loci have been identified as reflecting strong-positive selection in human populations, connections between candidate loci and specific selective pressures often remain obscure. This study investigates broader patterns of selection in African populations, which are underrepresented despite their potential to offer key insights into human adaptation. We scan for hard selective sweeps using several haplotype and allele-frequency statistics with a data set of nearly 500,000 genome-wide singlenucleotide polymorphisms in 12 highly diverged African populations that span a range of environments and subsistence strategies. We find that positive selection does not appear to be a strong determinant of allele-frequency differentiation among these African populations. Haplotype statistics do identify putatively selected regions that are shared across African populations. However, as assessed by extensive simulations, patterns of haplotype sharing between African populations follow neutral expectations and suggest that tails of the empirical distributions contain false-positive signals. After highlighting several genomic regions where positive selection can be inferred with higher confidence, we use a novel method to identify biological functions enriched among populations' empirical tail genomic windows, such as immune response in agricultural groups. In general, however, it seems that current methods for selection scans are poorly suited to populations that, like the African populations in this study, are affected by ascertainment bias and have low levels of linkage disequilibrium, possibly old selective sweeps, and potentially reduced phasing accuracy. Additionally, population history can confound the interpretation of selection statistics, suggesting that greater care is needed in attributing broad genetic patterns to human adaptation. E LUCIDATING the selective pressures that human populations have encountered, as well as the means by which they have adapted to them, is a central aim of evolutionary biology and anthropology. Recently, statistical methods in population genetics have been applied to genome-wide polymorphism data to identify genetic loci that may have experienced natural selection. Such inferences have primarily been made under the model of a hard selective sweep, where a new allele rapidly rises to fixation within a population due to positive selection (Sabeti et al. 2002(Sabeti et al. , 2005(Sabeti et al. , 2006Voight et al. 2006;Sabeti et al. 2007;Williamson et al. 2007;Akey 2009;Pickrell et al. 2009;. While these genome-wide scans have detected hundreds of loci as focal sites of selective sweeps, most connections between the loci and their selective pressures remain unknown. Lack of phenotypic or functional information, the relative effect of background selection, demography, and statistical noise have been suggested as some of the causes of the lack of agreement between studies (Teshima et al. 2006;Akey 2009;Hermisson 2009;Hernandez et al. 2011).In light of these issues, it ...

show abstract

Section: Enrichment Of Biological Functionssupporting

confidence: 81%

Limited Evidence for Classic Selective Sweeps in African Populations

et al. 2012

View full text Add to dashboard Cite

show abstract

“…[20][21][22][23][24][25] Studies of admixed populations have been particularly fruitful in identifying genetic adaptations and risk for diseases that are stratified across diverged ancestral origins. [26][27][28][29][30][31] Admixture patterns became especially complex during the peopling of the Americas, with extensive recent admixture spanning multiple continents. Processes shaping structure in these admixed populations include sex-biased migration and admixture, isolationby-distance, differential drift in mainland versus island populations, and variable admixture timing.…”

Section: Introductionmentioning

confidence: 99%

Human Demographic History Impacts Genetic Risk Prediction across Diverse Populations

Gignoux

Walters

et al. 2017

The American Journal of Human Genetics

1,182

1,097

View full text Add to dashboard Cite

The vast majority of genome-wide association studies (GWASs) are performed in Europeans, and their transferability to other populations is dependent on many factors (e.g., linkage disequilibrium, allele frequencies, genetic architecture). As medical genomics studies become increasingly large and diverse, gaining insights into population history and consequently the transferability of disease risk measurement is critical. Here, we disentangle recent population history in the widely used 1000 Genomes Project reference panel, with an emphasis on populations underrepresented in medical studies. To examine the transferability of single-ancestry GWASs, we used published summary statistics to calculate polygenic risk scores for eight well-studied phenotypes. We identify directional inconsistencies in all scores; for example, height is predicted to decrease with genetic distance from Europeans, despite robust anthropological evidence that West Africans are as tall as Europeans on average. To gain deeper quantitative insights into GWAS transferability, we developed a complex trait coalescent-based simulation framework considering effects of polygenicity, causal allele frequency divergence, and heritability. As expected, correlations between true and inferred risk are typically highest in the population from which summary statistics were derived. We demonstrate that scores inferred from European GWASs are biased by genetic drift in other populations even when choosing the same causal variants and that biases in any direction are possible and unpredictable. This work cautions that summarizing findings from large-scale GWASs may have limited portability to other populations using standard approaches and highlights the need for generalized risk prediction methods and the inclusion of more diverse individuals in medical genomics.

show abstract

“…To identify signals of positive selection shared between Europeans and Rroma but not present in the Indian population, we looked for shared signals of important genetic differentiation between these two populations with the Indian population, accompanied by the absence of genetic differentiation between them. Two tests were used: (i) Cross-Population Composite Likelihood Ratio (XP-CLR) (10), which is a test that aims to identify selective sweeps in a population by detecting important genetic differentiation in an extended genomic region by including information about linkage disequilibrium without requiring haplotype information, and (ii) TreeSelect test (11), which is a tree-based method that incorporates allele frequency information from all populations analyzed to increase power to detect selection and distinguishes which population has been under positive selection. A window was considered to show an extreme score if its summary statistic (maximum in the case of XP-CLR, mean in case of TreeSelect statistic) belonged to the 1% upper tail of the genome-wide summary statistic distribution.…”

Section: Resultsmentioning

confidence: 99%

Convergent evolution in European and Rroma populations reveals pressure exerted by plague on Toll-like receptors

Laayouni

Oosting

Luisi

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

View full text Add to dashboard Cite

Significance This article gives a unique perspective on the impact of evolution on the immune system under pressure by infections, using the special demographic history of Europe in which two populations with different genetic ancestry, Europeans and Rroma (Gypsies), have lived in the same geographic area and have been exposed to similar environmental hazards, including infections. We identified convergent evolution signals in genes from different human populations. Reconstruction of evolutionary history of European populations has identified Toll-like receptor 1 (TLR1)/TLR6/TLR10 as a pattern recognition pathway shaped by convergent evolution by infections, among which plague is a likely cause, influencing the survival of these populations during the infection.

show abstract

Genome-wide Comparison of African-Ancestry Populations from CARe and Other Cohorts Reveals Signals of Natural Selection

Cited by 81 publications

References 62 publications

Limited Evidence for Classic Selective Sweeps in African Populations

Limited Evidence for Classic Selective Sweeps in African Populations

Human Demographic History Impacts Genetic Risk Prediction across Diverse Populations

Convergent evolution in European and Rroma populations reveals pressure exerted by plague on Toll-like receptors

Contact Info

Product

Resources

About