Genetic Ancestry and Natural Selection Drive Population Differences in Immune Responses to Pathogens.

Individuals from different populations vary considerably in their susceptibility to immune-related diseases. To understand how genetic variation and natural selection contribute to these differences, we tested for the effects of African versus European ancestry on the transcriptional response of primary macrophages to live bacterial pathogens. A total of 9.3% of macrophage-expressed genes show ancestry-associated differences in the gene regulatory response to infection, and African ancestry specifically predicts a stronger inflammatory response and reduced intracellular bacterial growth. A large proportion of these differences are under genetic control: for 804 genes, more than 75% of ancestry effects on the immune response can be explained by a single cis- or trans-acting expression quantitative trait locus (eQTL). Finally, we show that genetic effects on the immune response are strongly enriched for recent, population-specific signatures of adaptation. Together, our results demonstrate how historical selective events continue to shape human phenotypic diversity today, including for traits that are key to controlling infection.

Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program.

The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.

selscan 2.0: scanning for sweeps in unphased data.

SUMMARY: Several popular haplotype-based statistics for identifying recent or ongoing positive selection in genomes require knowledge of haplotype phase. Here, we provide an update to selscan which implements a re-definition of these statistics for use in unphased data. AVAILABILITY AND IMPLEMENTATION: Source code and binaries are freely available at https://github.com/szpiech/selscan, implemented in C/C++, and supported on Linux, Windows, and MacOS.

A spatially aware likelihood test to detect sweeps from haplotype distributions.

The inference of positive selection in genomes is a problem of great interest in evolutionary genomics. By identifying putative regions of the genome that contain adaptive mutations, we are able to learn about the biology of organisms and their evolutionary history. Here we introduce a composite likelihood method that identifies recently completed or ongoing positive selection by searching for extreme distortions in the spatial distribution of the haplotype frequency spectrum along the genome relative to the genome-wide expectation taken as neutrality. Furthermore, the method simultaneously infers two parameters of the sweep: the number of sweeping haplotypes and the "width" of the sweep, which is related to the strength and timing of selection. We demonstrate that this method outperforms the leading haplotype-based selection statistics, though strong signals in low-recombination regions merit extra scrutiny. As a positive control, we apply it to two well-studied human populations from the 1000 Genomes Project and examine haplotype frequency spectrum patterns at the LCT and MHC loci. We also apply it to a data set of brown rats sampled in NYC and identify genes related to olfactory perception. To facilitate use of this method, we have implemented it in user-friendly open source software.

Ancestry-Dependent Enrichment of Deleterious Homozygotes in Runs of Homozygosity.

Runs of homozygosity (ROH) are important genomic features that manifest when an individual inherits two haplotypes that are identical by descent. Their length distributions are informative about population history, and their genomic locations are useful for mapping recessive loci contributing to both Mendelian and complex disease risk. We have previously shown that ROH, and especially long ROH that are likely the result of recent parental relatedness, are enriched for homozygous deleterious coding variation in a worldwide sample of outbred individuals. However, the distribution of ROH in admixed populations and their relationship to deleterious homozygous genotypes is understudied. Here we analyze whole-genome sequencing data from 1,441 unrelated individuals from self-identified African American, Puerto Rican, and Mexican American populations. These populations are three-way admixed between European, African, and Native American ancestries and provide an opportunity to study the distribution of deleterious alleles partitioned by local ancestry and ROH. We re-capitulate previous findings that long ROH are enriched for deleterious variation genome-wide. We then partition by local ancestry and show that deleterious homozygotes arise at a higher rate when ROH overlap African ancestry segments than when they overlap European or Native American ancestry segments of the genome. These results suggest that, while ROH on any haplotype background are associated with an inflation of deleterious homozygous variation, African haplotype backgrounds may play a particularly important role in the genetic architecture of complex diseases for admixed individuals, highlighting the need for further study of these populations.

Correction: Human demographic history has amplified the effects of background selection across the genome.

[This corrects the article DOI: 10.1371/journal.pgen.1007387.].

Relationship between Deleterious Variation, Genomic Autozygosity, and Disease Risk: Insights from The 1000 Genomes Project.

Genomic regions of autozygosity (ROAs) represent segments of individual genomes that are homozygous for haplotypes inherited identical-by-descent (IBD) from a common ancestor. ROAs are nonuniformly distributed across the genome, and increased ROA levels are a reported risk factor for numerous complex diseases. Previously, we hypothesized that long ROAs are enriched for deleterious homozygotes as a result of young haplotypes with recent deleterious mutations-relatively untouched by purifying selection-being paired IBD as a consequence of recent parental relatedness, a pattern supported by ROA and whole-exome sequence data on 27 individuals. Here, we significantly bolster support for our hypothesis and expand upon our original analyses using ROA and whole-genome sequence data on 2,436 individuals from The 1000 Genomes Project. Considering CADD deleteriousness scores, we reaffirm our previous observation that long ROAs are enriched for damaging homozygotes worldwide. We show that strongly damaging homozygotes experience greater enrichment than weaker damaging homozygotes, while overall enrichment varies appreciably among populations. Mendelian disease genes and those encoding FDA-approved drug targets have significantly increased rates of gain in damaging homozygotes with increasing ROA coverage relative to all other genes. In genes implicated in eight complex phenotypes for which ROA levels have been identified as a risk factor, rates of gain in damaging homozygotes vary across phenotypes and populations but frequently differ significantly from non-disease genes. These findings highlight the potential confounding effects of population background in the assessment of associations between ROA levels and complex disease risk, which might underlie reported inconsistencies in ROA-phenotype associations.

Human demographic history has amplified the effects of background selection across the genome.

Natural populations often grow, shrink, and migrate over time. Such demographic processes can affect genome-wide levels of genetic diversity. Additionally, genetic variation in functional regions of the genome can be altered by natural selection, which drives adaptive mutations to higher frequencies or purges deleterious ones. Such selective processes affect not only the sites directly under selection but also nearby neutral variation through genetic linkage via processes referred to as genetic hitchhiking in the context of positive selection and background selection (BGS) in the context of purifying selection. While there is extensive literature examining the consequences of selection at linked sites at demographic equilibrium, less is known about how non-equilibrium demographic processes influence the effects of hitchhiking and BGS. Utilizing a global sample of human whole-genome sequences from the Thousand Genomes Project and extensive simulations, we investigate how non-equilibrium demographic processes magnify and dampen the consequences of selection at linked sites across the human genome. When binning the genome by inferred strength of BGS, we observe that, compared to Africans, non-African populations have experienced larger proportional decreases in neutral genetic diversity in strong BGS regions. We replicate these findings in admixed populations by showing that non-African ancestral components of the genome have also been affected more severely in these regions. We attribute these differences to the strong, sustained/recurrent population bottlenecks that non-Africans experienced as they migrated out of Africa and throughout the globe. Furthermore, we observe a strong correlation between FST and the inferred strength of BGS, suggesting a stronger rate of genetic drift. Forward simulations of human demographic history with a model of BGS support these observations. Our results show that non-equilibrium demography significantly alters the consequences of selection at linked sites and support the need for more work investigating the dynamic process of multiple evolutionary forces operating in concert.

High-resolution network biology: connecting sequence with function.

Proteins are not monolithic entities; rather, they can contain multiple domains that mediate distinct interactions, and their functionality can be regulated through post-translational modifications at multiple distinct sites. Traditionally, network biology has ignored such properties of proteins and has instead examined either the physical interactions of whole proteins or the consequences of removing entire genes. In this Review, we discuss experimental and computational methods to increase the resolution of protein-protein, genetic and drug-gene interaction studies to the domain and residue levels. Such work will be crucial for using interaction networks to connect sequence and structural information, and to understand the biological consequences of disease-associated mutations, which will hopefully lead to more effective therapeutic strategies.

Whole-Genome Sequencing of Pharmacogenetic Drug Response in Racially Diverse Children with Asthma.

RATIONALE: Albuterol, a bronchodilator medication, is the first-line therapy for asthma worldwide. There are significant racial/ethnic differences in albuterol drug response. OBJECTIVES: To identify genetic variants important for bronchodilator drug response (BDR) in racially diverse children. METHODS: We performed the first whole-genome sequencing pharmacogenetics study from 1,441 children with asthma from the tails of the BDR distribution to identify genetic association with BDR. MEASUREMENTS AND MAIN RESULTS: We identified population-specific and shared genetic variants associated with BDR, including genome-wide significant (P < 3.53 × 10-7) and suggestive (P < 7.06 × 10-6) loci near genes previously associated with lung capacity (DNAH5), immunity (NFKB1 and PLCB1), and ß-adrenergic signaling (ADAMTS3 and COX18). Functional analyses of the BDR-associated SNP in NFKB1 revealed potential regulatory function in bronchial smooth muscle cells. The SNP is also an expression quantitative trait locus for a neighboring gene, SLC39A8. The lack of other asthma study populations with BDR and whole-genome sequencing data on minority children makes it impossible to perform replication of our rare variant associations. Minority underrepresentation also poses significant challenges to identify age-matched and population-matched cohorts of sufficient sample size for replication of our common variant findings. CONCLUSIONS: The lack of minority data, despite a collaboration of eight universities and 13 individual laboratories, highlights the urgent need for a dedicated national effort to prioritize diversity in research. Our study expands the understanding of pharmacogenetic analyses in racially/ethnically diverse populations and advances the foundation for precision medicine in at-risk and understudied minority populations.

GARLIC: Genomic Autozygosity Regions Likelihood-based Inference and Classification.

SUMMARY: Runs of homozygosity (ROH) are important genomic features that manifest when identical-by-descent haplotypes are inherited from parents. Their length distributions and genomic locations are informative about population history and they are useful for mapping recessive loci contributing to both Mendelian and complex disease risk. Here, we present software implementing a model-based method ( Pemberton et al., 2012 ) for inferring ROH in genome-wide SNP datasets that incorporates population-specific parameters and a genotyping error rate as well as provides a length-based classification module to identify biologically interesting classes of ROH. Using simulations, we evaluate the performance of this method. AVAILABILITY AND IMPLEMENTATION: GARLIC is written in C ++. Source code and pre-compiled binaries (Windows, OSX and Linux) are hosted on GitHub ( https://github.com/szpiech/garlic ) under the GNU General Public License version 3. CONTACT: zachary.szpiech@ucsf.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Using genotype array data to compare multi- and single-sample variant calls and improve variant call sets from deep coverage whole-genome sequencing data.

Motivation: Variant calling from next-generation sequencing (NGS) data is susceptible to false positive calls due to sequencing, mapping and other errors. To better distinguish true from false positive calls, we present a method that uses genotype array data from the sequenced samples, rather than public data such as HapMap or dbSNP, to train an accurate classifier using Random Forests. We demonstrate our method on a set of variant calls obtained from 642 African-ancestry genomes from the Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA), sequenced to high depth (30X). Results: We have applied our classifier to compare call sets generated with different calling methods, including both single-sample and multi-sample callers. At a False Positive Rate of 5%, our method determines true positive rates of 97.5%, 95% and 99% on variant calls obtained using Illuminas single-sample caller CASAVA, Real Time Genomics multisample variant caller, and the GATK UnifiedGenotyper, respectively. Since NGS sequencing data may be accompanied by genotype data for the same samples, either collected concurrent to sequencing or from a previous study, our method can be trained on each dataset to provide a more accurate computational validation of site calls compared to generic methods. Moreover, our method allows for adjustment based on allele frequency (e.g. a different set of criteria to determine quality for rare versus common variants) and thereby provides insight into sequencing characteristics that indicate call quality for variants of different frequencies. Availability and Implementation: Code is available on Github at: https://github.com/suyashss/variant_validation. Contacts: suyashs@stanford.edu or mtaub@jhsph.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

Weighted likelihood inference of genomic autozygosity patterns in dense genotype data.

BACKGROUND: Genomic regions of autozygosity (ROA) arise when an individual is homozygous for haplotypes inherited identical-by-descent from ancestors shared by both parents. Over the past decade, they have gained importance for understanding evolutionary history and the genetic basis of complex diseases and traits. However, methods to infer ROA in dense genotype data have not evolved in step with advances in genome technology that now enable us to rapidly create large high-resolution genotype datasets, limiting our ability to investigate their constituent ROA patterns. METHODS: We report a weighted likelihood approach for inferring ROA in dense genotype data that accounts for autocorrelation among genotyped positions and the possibilities of unobserved mutation and recombination events, and variability in the confidence of individual genotype calls in whole genome sequence (WGS) data. RESULTS: Forward-time genetic simulations under two demographic scenarios that reflect situations where inbreeding and its effect on fitness are of interest suggest this approach is better powered than existing state-of-the-art methods to infer ROA at marker densities consistent with WGS and popular microarray genotyping platforms used in human and non-human studies. Moreover, we present evidence that suggests this approach is able to distinguish ROA arising via consanguinity from ROA arising via endogamy. Using subsets of The 1000 Genomes Project Phase 3 data we show that, relative to WGS, intermediate and long ROA are captured robustly with popular microarray platforms, while detection of short ROA is more variable and improves with marker density. Worldwide ROA patterns inferred from WGS data are found to accord well with those previously reported on the basis of microarray genotype data. Finally, we highlight the potential of this approach to detect genomic regions enriched for autozygosity signals in one group relative to another based upon comparisons of per-individual autozygosity likelihoods instead of inferred ROA frequencies. CONCLUSIONS: This weighted likelihood ROA inference approach can assist population- and disease-geneticists working with a wide variety of data types and species to explore ROA patterns and to identify genomic regions with differential ROA signals among groups, thereby advancing our understanding of evolutionary history and the role of recessive variation in phenotypic variation and disease.

Long runs of homozygosity are enriched for deleterious variation.

Exome sequencing offers the potential to study the population-genomic variables that underlie patterns of deleterious variation. Runs of homozygosity (ROH) are long stretches of consecutive homozygous genotypes probably reflecting segments shared identically by descent as the result of processes such as consanguinity, population size reduction, and natural selection. The relationship between ROH and patterns of predicted deleterious variation can provide insight into the way in which these processes contribute to the maintenance of deleterious variants. Here, we use exome sequencing to examine ROH in relation to the distribution of deleterious variation in 27 individuals of varying levels of apparent inbreeding from 6 human populations. A significantly greater fraction of all genome-wide predicted damaging homozygotes fall in ROH than would be expected from the corresponding fraction of nondamaging homozygotes in ROH (p < 0.001). This pattern is strongest for long ROH (p < 0.05). ROH, and especially long ROH, harbor disproportionately more deleterious homozygotes than would be expected on the basis of the total ROH coverage of the genome and the genomic distribution of nondamaging homozygotes. The results accord with a hypothesis that recent inbreeding, which generates long ROH, enables rare deleterious variants to exist in homozygous form. Thus, just as inbreeding can elevate the occurrence of rare recessive diseases that represent homozygotes for strongly deleterious mutations, inbreeding magnifies the occurrence of mildly deleterious variants as well.

Genome-wide association studies in diverse populations.

Genome-wide association (GWA) studies have identified a large number of SNPs associated with disease phenotypes. As most GWA studies have been performed in populations of European descent, this Review examines the issues involved in extending the consideration of GWA studies to diverse worldwide populations. Although challenges exist with issues such as imputation, admixture and replication, investigation of a greater diversity of populations could make substantial contributions to the goal of mapping the genetic determinants of complex diseases for the human population as a whole.

selscan: an efficient multithreaded program to perform EHH-based scans for positive selection.

Haplotype-based scans to detect natural selection are useful to identify recent or ongoing positive selection in genomes. As both real and simulated genomic data sets grow larger, spanning thousands of samples and millions of markers, there is a need for a fast and efficient implementation of these scans for general use. Here, we present selscan, an efficient multithreaded application that implements Extended Haplotype Homozygosity (EHH), Integrated Haplotype Score (iHS), and Cross-population EHH (XPEHH). selscan accepts phased genotypes in multiple formats, including TPED, and performs extremely well on both simulated and real data and over an order of magnitude faster than existing available implementations. It calculates iHS on chromosome 22 (22,147 loci) across 204 CEU haplotypes in 353 s on one thread (33 s on 16 threads) and calculates XPEHH for the same data relative to 210 YRI haplotypes in 578 s on one thread (52 s on 16 threads). Source code and binaries (Windows, OSX, and Linux) are available at https://github.com/szpiech/selscan.

Genotype, haplotype and copy-number variation in worldwide human populations.

Genome-wide patterns of variation across individuals provide a powerful source of data for uncovering the history of migration, range expansion, and adaptation of the human species. However, high-resolution surveys of variation in genotype, haplotype and copy number have generally focused on a small number of population groups. Here we report the analysis of high-quality genotypes at 525,910 single-nucleotide polymorphisms (SNPs) and 396 copy-number-variable loci in a worldwide sample of 29 populations. Analysis of SNP genotypes yields strongly supported fine-scale inferences about population structure. Increasing linkage disequilibrium is observed with increasing geographic distance from Africa, as expected under a serial founder effect for the out-of-Africa spread of human populations. New approaches for haplotype analysis produce inferences about population structure that complement results based on unphased SNPs. Despite a difference from SNPs in the frequency spectrum of the copy-number variants (CNVs) detected--including a comparatively large number of CNVs in previously unexamined populations from Oceania and the Americas--the global distribution of CNVs largely accords with population structure analyses for SNP data sets of similar size. Our results produce new inferences about inter-population variation, support the utility of CNVs in human population-genetic research, and serve as a genomic resource for human-genetic studies in diverse worldwide populations.

The Maintenance of Deleterious Variation in Wild Chinese Rhesus Macaques.

Understanding how deleterious variation is shaped and maintained in natural populations is important in conservation and evolutionary biology, as decreased fitness caused by these deleterious mutations can potentially lead to an increase in extinction risk. It is known that demographic processes can influence these patterns. For example, population bottlenecks and inbreeding increase the probability of inheriting identical-by-descent haplotypes from a recent common ancestor, creating long tracts of homozygous genotypes called runs of homozygosity (ROH), which have been associated with an accumulation of mildly deleterious homozygotes. Counter intuitively, positive selection can also maintain deleterious variants in a population through genetic hitchhiking. Here we analyze the whole genomes of 79 wild Chinese rhesus macaques across five subspecies and characterize patterns of deleterious variation with respect to ROH and signals of recent positive selection. We show that the fraction of homozygotes occurring in long ROH is significantly higher for deleterious homozygotes than tolerated ones, whereas this trend is not observed for short and medium ROH. This confirms that inbreeding, by generating these long tracts of homozygosity, is the main driver of the high burden of homozygous deleterious alleles in wild macaque populations. Furthermore, we show evidence that homozygous LOF variants are being purged. Next, we identify 7 deleterious variants at high frequency in regions putatively under selection near genes involved with olfaction and other processes. Our results shed light on how evolutionary processes can shape the distribution of deleterious variation in wild non-human primates.

Genotypic and phenotypic consequences of domestication in dogs.

Runs of homozygosity (ROH) are genomic regions that arise when two copies of an identical ancestral haplotype are inherited from parents with a recent common ancestor. In this study, we performed a novel comprehensive analysis to infer genetic diversity among dogs and quantified the association between ROH and non-disease phenotypes. We found distinct patterns of genetic diversity across clades of breed dogs and elevated levels of long ROH, compared to non- domesticated dogs. These high levels of F ROH (inbreeding coefficient) are a consequence of recent inbreeding among domesticated dogs during breed establishment. We identified statistically significant associations between F ROH and height, weight, lifespan, muscled, white head, white chest, furnish, and length of fur. After correcting for population structure, we identified more than 45 genes across the three examined quantitative traits that exceeded the threshold for suggestive significance, indicating significant polygenic inheritance for the complex quantitative phenotypes in dogs.

The Maintenance of Deleterious Variation in Wild Chinese Rhesus Macaques.

Understanding how deleterious variation is shaped and maintained in natural populations is important in conservation and evolutionary biology, as decreased fitness caused by these deleterious mutations can potentially lead to an increase in extinction risk. It is known that demographic processes can influence these patterns. For example, population bottlenecks and inbreeding increase the probability of inheriting identical-by-descent haplotypes from a recent common ancestor, creating long tracts of homozygous genotypes called runs of homozygosity (ROH), which have been associated with an accumulation of mildly deleterious homozygotes. Counterintuitively, positive selection can also maintain deleterious variants in a population through genetic hitchhiking. Here, we analyze the whole genomes of 79 wild Chinese rhesus macaques across five subspecies and characterize patterns of deleterious variation with respect to ROH and signals of recent positive selection. We show that the fraction of homozygotes occurring in long ROH is significantly higher for deleterious homozygotes than tolerated ones, whereas this trend is not observed for short and medium ROH. This confirms that inbreeding, by generating these long tracts of homozygosity, is the main driver of the high burden of homozygous deleterious alleles in wild macaque populations. Furthermore, we show evidence that homozygous LOF variants are being purged. Next, we identify seven deleterious variants at high frequency in regions putatively under selection near genes involved with olfaction and other processes. Our results shed light on how evolutionary processes can shape the distribution of deleterious variation in wild nonhuman primates.