Increasing diversity of functional genetics studies to advance biological discovery and human health.

In this perspective we discuss the current lack of genetic and environmental diversity in functional genomics datasets. There is a well-described Eurocentric bias in genetic and functional genomic research that has a clear impact on the benefit this research can bring to underrepresented populations. Current research focused on genetic variant-to-function experiments aims to identify molecular QTLs, but the lack of data from genetically diverse individuals has limited analyses to mostly populations of European ancestry. Although some efforts have been established to increase diversity in functional genomic studies, much remains to be done to consistently generate data for underrepresented populations from now on. We discuss the major barriers for this continuity and suggest actionable insights, aiming to empower research and researchers from underserved populations.

Genetic architecture of gene regulation in Indonesian populations identifies QTLs associated with global and local ancestries.

Lack of diversity in human genomics limits our understanding of the genetic underpinnings of complex traits, hinders precision medicine, and contributes to health disparities. To map genetic effects on gene regulation in the underrepresented Indonesian population, we have integrated genotype, gene expression, and CpG methylation data from 115 participants across three island populations that capture the major sources of genomic diversity in the region. In a comparison with European datasets, we identify eQTLs shared between Indonesia and Europe as well as population-specific eQTLs that exhibit differences in allele frequencies and/or overall expression levels between populations. By combining local ancestry and archaic introgression inference with eQTLs and methylQTLs, we identify regulatory loci driven by modern Papuan ancestry as well as introgressed Denisovan and Neanderthal variation. GWAS colocalization connects QTLs detected here to hematological traits, and further comparison with European datasets reflects the poor overall transferability of GWAS statistics across diverse populations. Our findings illustrate how population-specific genetic architecture, local ancestry, and archaic introgression drive variation in gene regulation across genetically distinct and in admixed populations and highlight the need for performing association studies on non-European populations.

Denisovan introgression has shaped the immune system of present-day Papuans.

Modern humans have admixed with multiple archaic hominins. Papuans, in particular, owe up to 5% of their genome to Denisovans, a sister group to Neanderthals whose remains have only been identified in Siberia and Tibet. Unfortunately, the biological and evolutionary significance of these introgression events remain poorly understood. Here we investigate the function of both Denisovan and Neanderthal alleles characterised within a set of 56 genomes from Papuan individuals. By comparing the distribution of archaic and non-archaic variants we assess the consequences of archaic admixture across a multitude of different cell types and functional elements. We observe an enrichment of archaic alleles within cis-regulatory elements and transcribed regions of the genome, with Denisovan variants strongly affecting elements active within immune-related cells. We identify 16,048 and 10,032 high-confidence Denisovan and Neanderthal variants that fall within annotated cis-regulatory elements and with the potential to alter the affinity of multiple transcription factors to their cognate DNA motifs, highlighting a likely mechanism by which introgressed DNA can impact phenotypes. Lastly, we experimentally validate these predictions by testing the regulatory potential of five Denisovan variants segregating within Papuan individuals, and find that two are associated with a significant reduction of transcriptional activity in plasmid reporter assays. Together, these data provide support for a widespread contribution of archaic DNA in shaping the present levels of modern human genetic diversity, with different archaic ancestries potentially affecting multiple phenotypic traits within non-Africans.

Genome-wide DNA methylation and gene expression patterns reflect genetic ancestry and environmental differences across the Indonesian archipelago.

Indonesia is the world's fourth most populous country, host to striking levels of human diversity, regional patterns of admixture, and varying degrees of introgression from both Neanderthals and Denisovans. However, it has been largely excluded from the human genomics sequencing boom of the last decade. To serve as a benchmark dataset of molecular phenotypes across the region, we generated genome-wide CpG methylation and gene expression measurements in over 100 individuals from three locations that capture the major genomic and geographical axes of diversity across the Indonesian archipelago. Investigating between- and within-island differences, we find up to 10.55% of tested genes are differentially expressed between the islands of Sumba and New Guinea. Variation in gene expression is closely associated with DNA methylation, with expression levels of 9.80% of genes correlating with nearby promoter CpG methylation, and many of these genes being differentially expressed between islands. Genes identified in our differential expression and methylation analyses are enriched in pathways involved in immunity, highlighting Indonesia's tropical role as a source of infectious disease diversity and the strong selective pressures these diseases have exerted on humans. Finally, we identify robust within-island variation in DNA methylation and gene expression, likely driven by fine-scale environmental differences across sampling sites. Together, these results strongly suggest complex relationships between DNA methylation, transcription, archaic hominin introgression and immunity, all jointly shaped by the environment. This has implications for the application of genomic medicine, both in critically understudied Indonesia and globally, and will allow a better understanding of the interacting roles of genomic and environmental factors shaping molecular and complex phenotypes.

Papua New Guinean Genomes Reveal the Complex Settlement of North Sahul.

The settlement of Sahul, the lost continent of Oceania, remains one of the most ancient and debated human migrations. Modern New Guineans inherited a unique genetic diversity tracing back 50,000 years, and yet there is currently no model reconstructing their past population dynamics. We generated 58 new whole-genome sequences from Papua New Guinea, filling geographical gaps in previous sampling, specifically to address alternative scenarios of the initial migration to Sahul and the settlement of New Guinea. Here, we present the first genomic models for the settlement of northeast Sahul considering one or two migrations from Wallacea. Both models fit our data set, reinforcing the idea that ancestral groups to New Guinean and Indigenous Australians split early, potentially during their migration in Wallacea where the northern route could have been favored. The earliest period of human presence in Sahul was an era of interactions and gene flow between related but already differentiated groups, from whom all modern New Guineans, Bismarck islanders, and Indigenous Australians descend. The settlement of New Guinea was probably initiated from its southeast region, where the oldest archaeological sites have been found. This was followed by two migrations into the south and north lowlands that ultimately reached the west and east highlands. We also identify ancient gene flows between populations in New Guinea, Australia, East Indonesia, and the Bismarck Archipelago, emphasizing the fact that the anthropological landscape during the early period of Sahul settlement was highly dynamic rather than the traditional view of extensive isolation.

Ancestry-Specific Analyses Reveal Differential Demographic Histories and Opposite Selective Pressures in Modern South Asian Populations.

Genetic variation in contemporary South Asian populations follows a northwest to southeast decreasing cline of shared West Eurasian ancestry. A growing body of ancient DNA evidence is being used to build increasingly more realistic models of demographic changes in the last few thousand years. Through high-quality modern genomes, these models can be tested for gene and genome level deviations. Using local ancestry deconvolution and masking, we reconstructed population-specific surrogates of the two main ancestral components for more than 500 samples from 25 South Asian populations and showed our approach to be robust via coalescent simulations. Our f3 and f4 statistics-based estimates reveal that the reconstructed haplotypes are good proxies for the source populations that admixed in the area and point to complex interpopulation relationships within the West Eurasian component, compatible with multiple waves of arrival, as opposed to a simpler one wave scenario. Our approach also provides reliable local haplotypes for future downstream analyses. As one such example, the local ancestry deconvolution in South Asians reveals opposite selective pressures on two pigmentation genes (SLC45A2 and SLC24A5) that are common or fixed in West Eurasians, suggesting post-admixture purifying and positive selection signals, respectively.

Genetic Variation, Not Cell Type of Origin, Underlies the Majority of Identifiable Regulatory Differences in iPSCs.

The advent of induced pluripotent stem cells (iPSCs) revolutionized human genetics by allowing us to generate pluripotent cells from easily accessible somatic tissues. This technology can have immense implications for regenerative medicine, but iPSCs also represent a paradigm shift in the study of complex human phenotypes, including gene regulation and disease. Yet, an unresolved caveat of the iPSC model system is the extent to which reprogrammed iPSCs retain residual phenotypes from their precursor somatic cells. To directly address this issue, we used an effective study design to compare regulatory phenotypes between iPSCs derived from two types of commonly used somatic precursor cells. We find a remarkably small number of differences in DNA methylation and gene expression levels between iPSCs derived from different somatic precursors. Instead, we demonstrate genetic variation is associated with the majority of identifiable variation in DNA methylation and gene expression levels. We show that the cell type of origin only minimally affects gene expression levels and DNA methylation in iPSCs, and that genetic variation is the main driver of regulatory differences between iPSCs of different donors. Our findings suggest that studies using iPSCs should focus on additional individuals rather than clones from the same individual.

The light skin allele of SLC24A5 in South Asians and Europeans shares identity by descent.

Skin pigmentation is one of the most variable phenotypic traits in humans. A non-synonymous substitution (rs1426654) in the third exon of SLC24A5 accounts for lighter skin in Europeans but not in East Asians. A previous genome-wide association study carried out in a heterogeneous sample of UK immigrants of South Asian descent suggested that this gene also contributes significantly to skin pigmentation variation among South Asians. In the present study, we have quantitatively assessed skin pigmentation for a largely homogeneous cohort of 1228 individuals from the Southern region of the Indian subcontinent. Our data confirm significant association of rs1426654 SNP with skin pigmentation, explaining about 27% of total phenotypic variation in the cohort studied. Our extensive survey of the polymorphism in 1573 individuals from 54 ethnic populations across the Indian subcontinent reveals wide presence of the derived-A allele, although the frequencies vary substantially among populations. We also show that the geospatial pattern of this allele is complex, but most importantly, reflects strong influence of language, geography and demographic history of the populations. Sequencing 11.74 kb of SLC24A5 in 95 individuals worldwide reveals that the rs1426654-A alleles in South Asian and West Eurasian populations are monophyletic and occur on the background of a common haplotype that is characterized by low genetic diversity. We date the coalescence of the light skin associated allele at 22-28 KYA. Both our sequence and genome-wide genotype data confirm that this gene has been a target for positive selection among Europeans. However, the latter also shows additional evidence of selection in populations of the Middle East, Central Asia, Pakistan and North India but not in South India.

Ethiopian genetic diversity reveals linguistic stratification and complex influences on the Ethiopian gene pool.

Humans and their ancestors have traversed the Ethiopian landscape for millions of years, and present-day Ethiopians show great cultural, linguistic, and historical diversity, which makes them essential for understanding African variability and human origins. We genotyped 235 individuals from ten Ethiopian and two neighboring (South Sudanese and Somali) populations on an Illumina Omni 1M chip. Genotypes were compared with published data from several African and non-African populations. Principal-component and STRUCTURE-like analyses confirmed substantial genetic diversity both within and between populations, and revealed a match between genetic data and linguistic affiliation. Using comparisons with African and non-African reference samples in 40-SNP genomic windows, we identified "African" and "non-African" haplotypic components for each Ethiopian individual. The non-African component, which includes the SLC24A5 allele associated with light skin pigmentation in Europeans, may represent gene flow into Africa, which we estimate to have occurred ~3 thousand years ago (kya). The non-African component was found to be more similar to populations inhabiting the Levant rather than the Arabian Peninsula, but the principal route for the expansion out of Africa ~60 kya remains unresolved. Linkage-disequilibrium decay with genomic distance was less rapid in both the whole genome and the African component than in southern African samples, suggesting a less ancient history for Ethiopian populations.

RNA-seq: impact of RNA degradation on transcript quantification.

BACKGROUND: The use of low quality RNA samples in whole-genome gene expression profiling remains controversial. It is unclear if transcript degradation in low quality RNA samples occurs uniformly, in which case the effects of degradation can be corrected via data normalization, or whether different transcripts are degraded at different rates, potentially biasing measurements of expression levels. This concern has rendered the use of low quality RNA samples in whole-genome expression profiling problematic. Yet, low quality samples (for example, samples collected in the course of fieldwork) are at times the sole means of addressing specific questions. RESULTS: We sought to quantify the impact of variation in RNA quality on estimates of gene expression levels based on RNA-seq data. To do so, we collected expression data from tissue samples that were allowed to decay for varying amounts of time prior to RNA extraction. The RNA samples we collected spanned the entire range of RNA Integrity Number (RIN) values (a metric commonly used to assess RNA quality). We observed widespread effects of RNA quality on measurements of gene expression levels, as well as a slight but significant loss of library complexity in more degraded samples. CONCLUSIONS: While standard normalizations failed to account for the effects of degradation, we found that by explicitly controlling for the effects of RIN using a linear model framework we can correct for the majority of these effects. We conclude that in instances in which RIN and the effect of interest are not associated, this approach can help recover biologically meaningful signals in data from degraded RNA samples.

De novo transcriptome assembly and genome annotation of the fat-tailed dunnart (Sminthopsis crassicaudata).

Marsupials exhibit distinctive modes of reproduction and early development that set them apart from their eutherian counterparts and render them invaluable for comparative studies. However, marsupial genomic resources still lag far behind those of eutherian mammals. We present a series of novel genomic resources for the fat-tailed dunnart (Sminthopsis crassicaudata), a mouse-like marsupial that, due to its ease of husbandry and ex-utero development, is emerging as a laboratory model. We constructed a highly representative multi-tissue de novo transcriptome assembly of dunnart RNA-seq reads spanning 12 tissues. The transcriptome includes 2,093,982 assembled transcripts and has a mammalian transcriptome BUSCO completeness score of 93.3%, the highest amongst currently published marsupial transcriptomes. This global transcriptome, along with ab initio predictions, supported annotation of the existing dunnart genome, revealing 21,622 protein-coding genes. Altogether, these resources will enable wider use of the dunnart as a model marsupial and deepen our understanding of mammalian genome evolution.

Defining and Reducing Variant Classification Disparities.

Background: Multiplexed Assays of Variant Effects (MAVEs) can test all possible single variants in a gene of interest. The resulting saturation-style data may help resolve variant classification disparities between populations, especially for variants of uncertain significance (VUS). Methods: We analyzed clinical significance classifications in 213,663 individuals of European-like genetic ancestry versus 206,975 individuals of non-European-like genetic ancestry from All of Us and the Genome Aggregation Database. Then, we incorporated clinically calibrated MAVE data into the Clinical Genome Resource's Variant Curation Expert Panel rules to automate VUS reclassification for BRCA1, TP53, and PTEN . Results: Using two orthogonal statistical approaches, we show a higher prevalence ( p ≤5.95e-06) of VUS in individuals of non-European-like genetic ancestry across all medical specialties assessed in all three databases. Further, in the non-European-like genetic ancestry group, higher rates of Benign or Likely Benign and variants with no clinical designation ( p ≤2.5e-05) were found across many medical specialties, whereas Pathogenic or Likely Pathogenic assignments were higher in individuals of European-like genetic ancestry ( p ≤2.5e-05). Using MAVE data, we reclassified VUS in individuals of non-European-like genetic ancestry at a significantly higher rate in comparison to reclassified VUS from European-like genetic ancestry ( p =9.1e-03) effectively compensating for the VUS disparity. Further, essential code analysis showed equitable impact of MAVE evidence codes but inequitable impact of allele frequency ( p =7.47e-06) and computational predictor ( p =6.92e-05) evidence codes for individuals of non-European-like genetic ancestry. Conclusions: Generation of saturation-style MAVE data should be a priority to reduce VUS disparities and produce equitable training data for future computational predictors.

Herders of Indian and European cattle share their predominant allele for lactase persistence.

Milk consumption and lactose digestion after weaning are exclusively human traits made possible by the continued production of the enzyme lactase in adulthood. Multiple independent mutations in a 100-bp region--part of an enhancer--approximately 14-kb upstream of the LCT gene are associated with this trait in Europeans and pastoralists from Saudi Arabia and Africa. However, a single mutation of purported western Eurasian origin accounts for much of observed lactase persistence outside Africa. Given the high levels of present-day milk consumption in India, together with archaeological and genetic evidence for the independent domestication of cattle in the Indus valley roughly 7,000 years ago, we sought to determine whether lactase persistence has evolved independently in the subcontinent. Here, we present the results of the first comprehensive survey of the LCT enhancer region in south Asia. Having genotyped 2,284 DNA samples from across the Indian subcontinent, we find that the previously described west Eurasian -13910 C>T mutation accounts for nearly all the genetic variation we observed in the 400- to 700-bp LCT regulatory region that we sequenced. Geography is a significant predictor of -13910*T allele frequency, and consistent with other genomic loci, its distribution in India follows a general northwest to southeast declining pattern, although frequencies among certain neighboring populations vary substantially. We confirm that the mutation is identical by descent to the European allele and is associated with the same>1 Mb extended haplotype in both populations.

Variation at diabetes- and obesity-associated Loci may mirror neutral patterns of human population diversity and diabetes prevalence in India.

South Asian populations harbor a high degree of genetic diversity, due in part to demographic history. Two studies on genome-wide variation in Indian populations have shown that most Indian populations show varying degrees of admixture between ancestral north Indian and ancestral south Indian components. As a result of this structure, genetic variation in India appears to follow a geographic cline. Similarly, Indian populations seem to show detectable differences in diabetes and obesity prevalence between different geographic regions of the country. We tested the hypothesis that genetic variation at diabetes- and obesity-associated loci may be potentially related to different genetic ancestries. We genotyped 2977 individuals from 61 populations across India for 18 SNPs in genes implicated in T2D and obesity. We examined patterns of variation in allele frequency across different geographical gradients and considered state of origin and language affiliation. Our results show that most of the 18 SNPs show no significant correlation with latitude, the geographic cline reported in previous studies, or by language family. Exceptions include KCNQ1 with latitude and THADA and JAK1 with language, which suggests that genetic variation at previously ascertained diabetes-associated loci may only partly mirror geographic patterns of genome-wide diversity in Indian populations.

A general linear model-based approach for inferring selection to climate.

BACKGROUND: Many efforts have been made to detect signatures of positive selection in the human genome, especially those associated with expansion from Africa and subsequent colonization of all other continents. However, most approaches have not directly probed the relationship between the environment and patterns of variation among humans. We have designed a method to identify regions of the genome under selection based on Mantel tests conducted within a general linear model framework, which we call MAntel-GLM to Infer Clinal Selection (MAGICS). MAGICS explicitly incorporates population-specific and genome-wide patterns of background variation as well as information from environmental values to provide an improved picture of selection and its underlying causes in human populations. RESULTS: Our results significantly overlap with those obtained by other published methodologies, but MAGICS has several advantages. These include improvements that: limit false positives by reducing the number of independent tests conducted and by correcting for geographic distance, which we found to be a major contributor to selection signals; yield absolute rather than relative estimates of significance; identify specific geographic regions linked most strongly to particular signals of selection; and detect recent balancing as well as directional selection. CONCLUSIONS: We find evidence of selection associated with climate (P < 10-5) in 354 genes, and among these observe a highly significant enrichment for directional positive selection. Two of our strongest 'hits', however, ADRA2A and ADRA2C, implicated in vasoconstriction in response to cold and pain stimuli, show evidence of balancing selection. Our results clearly demonstrate evidence of climate-related signals of directional and balancing selection.

Leveraging massively parallel reporter assays for evolutionary questions.

A long-standing goal of evolutionary biology is to decode how gene regulation contributes to organismal diversity. Doing so is challenging because it is hard to predict function from non-coding sequence and to perform molecular research with non-model taxa. Massively parallel reporter assays (MPRAs) enable the testing of thousands to millions of sequences for regulatory activity simultaneously. Here, we discuss the execution, advantages, and limitations of MPRAs, with a focus on evolutionary questions. We propose solutions for extending MPRAs to rare taxa and those with limited genomic resources, and we underscore MPRA's broad potential for driving genome-scale, functional studies across organisms.

Harnessing pluripotent stem cells as models to decipher human evolution.

The study of human evolution, long constrained by a lack of experimental model systems, has been transformed by the emergence of the induced pluripotent stem cell (iPSC) field. iPSCs can be readily established from noninvasive tissue sources, from both humans and other primates; they can be maintained in the laboratory indefinitely, and they can be differentiated into other tissue types. These qualities mean that iPSCs are rapidly becoming established as viable and powerful model systems with which it is possible to address questions in human evolution that were until now logistically and ethically intractable, especially in the quest to understand humans' place among the great apes, and the genetic basis of human uniqueness. In this review, we discuss the key lessons and takeaways of this nascent field; from the types of research, iPSCs make possible to lingering challenges and likely future directions. We provide a comprehensive overview of how the seemingly unlikely combination of iPSCs and explicit evolutionary frameworks is transforming what is possible in our understanding of humanity's past and present.

Genetic Diversity in Chimpanzee Transcriptomics Does Not Represent Wild Populations.

Chimpanzees (Pan troglodytes) are a genetically diverse species, consisting of four highly distinct subspecies. As humans' closest living relative, they have been a key model organism in the study of human evolution, and comparisons of human and chimpanzee transcriptomes have been widely used to characterize differences in gene expression levels that could underlie the phenotypic differences between the two species. However, the subspecies from which these transcriptomic data sets have been derived is not recorded in metadata available in the public NCBI Sequence Read Archive (SRA). Furthermore, labeling of RNA sequencing (RNA-seq) samples is for the most part inconsistent across studies, and the true number of individuals from whom transcriptomic data are available is difficult to ascertain. Thus, we have evaluated genetic diversity at the subspecies and individual level in 486 public RNA-seq samples available in the SRA, spanning the vast majority of public chimpanzee transcriptomic data. Using multiple population genetics approaches, we find that nearly all samples (96.6%) have some degree of Western chimpanzee ancestry. At the individual donor level, we identify multiple samples that have been repeatedly analyzed across different studies and identify a total of 135 genetically distinct individuals within our data, a number that falls to 89 when we exclude likely first- and second-degree relatives. Altogether, our results show that current transcriptomic data from chimpanzees are capturing low levels of genetic diversity relative to what exists in wild chimpanzee populations. These findings provide important context to current comparative transcriptomics research involving chimpanzees.

CFTR mutations and reproductive outcomes in a population isolate.

Multiple hypotheses have been proposed to explain the high incidence of cystic fibrosis in Caucasian populations. Most rely on a fitness advantage to carriers of CF mutations, either through increased resistance to infectious disease, such as cholera, or through increased fertility. In this study we tested the latter hypothesis in the Hutterites of South Dakota, a genetic isolate with a relatively high CF carrier frequency. Following a population-wide screen for the only two mutations present in the Hutterites (M1101K, DeltaF508), we tested for associations between carrier status and measures of fertility. There was no evidence of nonrandom transmission of mutations (P = 0.409) or skewed sex ratios (P = 0.847) in children of carrier parents. Moreover, carrier status was not associated with overall fertility (P = 0.597 for carrier fathers and 0.694 for carrier mothers). Although carrier males' sibship sizes were larger than carrier females' sibship sizes (P = 0.049), this was not significant after accounting for multiple testing. Overall, our results suggest that if there is a fertility advantage among CF carriers, it is too small to be detected in our sample (85 carriers out of approximately 950 screened), or the effects are confined to DeltaF508 carriers, for which there are too few in our sample to test this specific hypothesis.