Genomic and epigenomic responses to aspirin in human colonic organoids.

Aspirin (ASA) is a proven chemoprotective agent for colorectal cancer, though mechanisms underlying these effects are incompletely understood. Human organoids are an ideal system to study genomic and epigenomic host-environment interactions. We use human colonic organoids to profile ASA responses on genome-wide gene expression and chromatin accessibility. Human colonic organoids from one individual were cultured and treated in triplicate with 3 mM ASA or vehicle control (DMSO) for 24 h. Gene expression and chromatin accessibility were measured using RNA- and ATAC-sequencing, respectively. Differentially expressed genes were analyzed using DESeq2. Top genes were validated by qPCR. Gene set enrichment was performed by SetRank. Differentially accessible peaks were analyzed using DiffBind and edgeR. Peak annotation and differential transcription factor motifs were determined by HOMER and diffTF. The results showed robust transcriptional responses to ASA with significant enrichment for fatty acid oxidation and peroxisome proliferator-activated receptor (PPAR) signaling that were validated in independent organoid lines. A large number of differentially accessible chromatin regions were found in response to ASA with significant enrichment for Fos, Jun, and Hnf transcription factor motifs. Integrated analysis of epigenomic and genomic treatment responses highlighted gene regions that could mediate ASA's specific effects in the colon including those involved in chemoprotection and/or toxicity. Assessment of chromatin accessibility and transcriptional responses to ASA yielded new observations about genome-wide effects in the colon facilitated by application of human colonic organoids. This framework can be applied to study colonic ASA responses between individuals and populations in future studies.

Genomic and epigenomic active vitamin D responses in human colonic organoids.

Active vitamin D, 1α,25(OH)2D3, is a nuclear hormone with roles in colonic homeostasis and carcinogenesis; yet, mechanisms underlying these effects are incompletely understood. Human organoids are an ideal system to study genomic and epigenomic host-environment interactions. Here, we use human colonic organoids to measure 1α,25(OH)2D3 responses on genome-wide gene expression and chromatin accessibility over time. Human colonic organoids were cultured and treated in triplicate with 100 nM 1α,25(OH)2D3 or vehicle control for 4 h and 18 h for chromatin accessibility, and 6 h and 24 h for gene expression. ATAC- and RNA-sequencing were performed. Differentially accessible peaks were analyzed using DiffBind and edgeR; differentially expressed genes were analyzed using DESeq2. Motif enrichment was determined using HOMER. At 6 h and 24 h, 2,870 and 2,721 differentially expressed genes, respectively (false discovery rate, FDR < 5%), were identified with overall stronger responses with 1α,25(OH)2D3. Similarly, 1α,25(OH)2D3 treatment led to stronger chromatin accessibility especially at 4 h. The vitamin D receptor (VDR) motif was strongly enriched among accessible chromatin peaks with 1α,25(OH)2D3 treatment accounting for 30.5% and 11% of target sequences at 4 h and 18 h, respectively (FDR < 1%). A number of genes such as CYP24A1, FGF19, MYC, FOS, and TGFBR2 showed significant transcriptional and chromatin accessibility responses to 1α,25(OH)2D3 treatment with accessible chromatin located distant from promoters for some gene regions. Assessment of chromatin accessibility and transcriptional responses to 1α,25(OH)2D3 yielded new observations about vitamin D genome-wide effects in the colon facilitated by application of human colonic organoids. This framework can be applied to study host-environment interactions between individuals and populations in the future.

Detecting past and ongoing natural selection among ethnically Tibetan women at high altitude in Nepal.

Adaptive evolution in humans has rarely been characterized for its whole set of components, i.e. selective pressure, adaptive phenotype, beneficial alleles and realized fitness differential. We combined approaches for detecting polygenic adaptations and for mapping the genetic bases of physiological and fertility phenotypes in approximately 1000 indigenous ethnically Tibetan women from Nepal, adapted to high altitude. The results of genome-wide association analyses and tests for polygenic adaptations showed evidence of positive selection for alleles associated with more pregnancies and live births and evidence of negative selection for those associated with higher offspring mortality. Lower hemoglobin level did not show clear evidence for polygenic adaptation, despite its strong association with an EPAS1 haplotype carrying selective sweep signals.

Long-term genetic stability and a high-altitude East Asian origin for the peoples of the high valleys of the Himalayan arc.

The high-altitude transverse valleys [>3,000 m above sea level (masl)] of the Himalayan arc from Arunachal Pradesh to Ladahk were among the last habitable places permanently colonized by prehistoric humans due to the challenges of resource scarcity, cold stress, and hypoxia. The modern populations of these valleys, who share cultural and linguistic affinities with peoples found today on the Tibetan plateau, are commonly assumed to be the descendants of the earliest inhabitants of the Himalayan arc. However, this assumption has been challenged by archaeological and osteological evidence suggesting that these valleys may have been originally populated from areas other than the Tibetan plateau, including those at low elevation. To investigate the peopling and early population history of this dynamic high-altitude contact zone, we sequenced the genomes (0.04×-7.25×, mean 2.16×) and mitochondrial genomes (20.8×-1,311.0×, mean 482.1×) of eight individuals dating to three periods with distinct material culture in the Annapurna Conservation Area (ACA) of Nepal, spanning 3,150-1,250 y before present (yBP). We demonstrate that the region is characterized by long-term stability of the population genetic make-up despite marked changes in material culture. The ancient genomes, uniparental haplotypes, and high-altitude adaptive alleles suggest a high-altitude East Asian origin for prehistoric Himalayan populations.

Reconstructing Native American population history.

The peopling of the Americas has been the subject of extensive genetic, archaeological and linguistic research; however, central questions remain unresolved. One contentious issue is whether the settlement occurred by means of a single migration or multiple streams of migration from Siberia. The pattern of dispersals within the Americas is also poorly understood. To address these questions at a higher resolution than was previously possible, we assembled data from 52 Native American and 17 Siberian groups genotyped at 364,470 single nucleotide polymorphisms. Here we show that Native Americans descend from at least three streams of Asian gene flow. Most descend entirely from a single ancestral population that we call 'First American'. However, speakers of Eskimo-Aleut languages from the Arctic inherit almost half their ancestry from a second stream of Asian gene flow, and the Na-Dene-speaking Chipewyan from Canada inherit roughly one-tenth of their ancestry from a third stream. We show that the initial peopling followed a southward expansion facilitated by the coast, with sequential population splits and little gene flow after divergence, especially in South America. A major exception is in Chibchan speakers on both sides of the Panama isthmus, who have ancestry from both North and South America.

Genetic mapping with multiple levels of phenotypic information reveals determinants of lymphocyte glucocorticoid sensitivity.

Clinical response to glucocorticoids, steroid hormones widely used as pharmaceuticals, varies extensively in that many individuals (∼30%) show a weak response to treatment. Although little is known about the molecular basis of this variation, regulatory polymorphisms are likely to play a key role given that glucocorticoids act largely through activation of a transcription factor, the glucocorticoid receptor. In an effort to characterize the molecular basis of variation in glucocorticoid sensitivity, we measured in vitro lymphocyte glucocorticoid sensitivity and transcriptome-wide response to glucocorticoids in peripheral-blood mononuclear cells from African American healthy donors. We found that variation in lymphocyte glucocorticoid sensitivity was correlated with transcriptional response at 27 genes (false-discovery rate < 0.1). Furthermore, a genome-wide association scan revealed a quantitative trait locus (QTL) for lymphocyte glucocorticoid sensitivity (rs11129354, p = 4 × 10(-8)); it was also associated with transcriptional response at multiple genes, including many (14/27) where transcriptional response was correlated with lymphocyte glucocorticoid sensitivity. Using allelic-imbalance assays, we show that this QTL is a glucocorticoid-dependent cis-regulatory polymorphism for RBMS3, which encodes an RNA-binding protein known as a tumor suppressor. We found that siRNA-mediated knockdown of RBMS3 expression increased cellular proliferation in PBMCs, consistent with the role of the gene as a negative regulator of proliferation. We propose that differences in lymphocyte glucocorticoid sensitivity reflect variation in transcriptional response, which is influenced by a glucocorticoid-dependent regulatory polymorphism that acts in cis relative to RBMS3 and in trans to affect the transcriptional response of multiple distant genes.

The genetic architecture of adaptations to high altitude in Ethiopia.

Although hypoxia is a major stress on physiological processes, several human populations have survived for millennia at high altitudes, suggesting that they have adapted to hypoxic conditions. This hypothesis was recently corroborated by studies of Tibetan highlanders, which showed that polymorphisms in candidate genes show signatures of natural selection as well as well-replicated association signals for variation in hemoglobin levels. We extended genomic analysis to two Ethiopian ethnic groups: Amhara and Oromo. For each ethnic group, we sampled low and high altitude residents, thus allowing genetic and phenotypic comparisons across altitudes and across ethnic groups. Genome-wide SNP genotype data were collected in these samples by using Illumina arrays. We find that variants associated with hemoglobin variation among Tibetans or other variants at the same loci do not influence the trait in Ethiopians. However, in the Amhara, SNP rs10803083 is associated with hemoglobin levels at genome-wide levels of significance. No significant genotype association was observed for oxygen saturation levels in either ethnic group. Approaches based on allele frequency divergence did not detect outliers in candidate hypoxia genes, but the most differentiated variants between high- and lowlanders have a clear role in pathogen defense. Interestingly, a significant excess of allele frequency divergence was consistently detected for genes involved in cell cycle control and DNA damage and repair, thus pointing to new pathways for high altitude adaptations. Finally, a comparison of CpG methylation levels between high- and lowlanders found several significant signals at individual genes in the Oromo.

A reduced representation approach to population genetic analyses and applications to human evolution.

Second-generation sequencing technologies allow surveys of sequence variation on an unprecedented scale. However, despite the rapid decrease in sequencing costs, collecting whole-genome sequence data on a population scale is still prohibitive for many laboratories. We have implemented an inexpensive, reduced representation protocol for preparing resequencing targets, and we have developed the analytical tools necessary for making population genetic inferences. This approach can be applied to any species for which a draft or complete reference genome sequence is available. The new tools we have developed include methods for aligning reads, calling genotypes, and incorporating sample-specific sequencing error rates in the estimate of evolutionary parameters. When applied to 19 individuals from a total of 18 human populations, our approach allowed sampling regions that are largely overlapping across individuals and that are representative of the entire genome. The resequencing data were used to test the serial founder model of human dispersal and to estimate the time of the Out of Africa migration. Our results also represent the first attempt to provide a time frame for the colonization of Australia based on large-scale resequencing data.

Interactions between glucocorticoid treatment and cis-regulatory polymorphisms contribute to cellular response phenotypes.

Glucocorticoids (GCs) mediate physiological responses to environmental stress and are commonly used as pharmaceuticals. GCs act primarily through the GC receptor (GR, a transcription factor). Despite their clear biomedical importance, little is known about the genetic architecture of variation in GC response. Here we provide an initial assessment of variability in the cellular response to GC treatment by profiling gene expression and protein secretion in 114 EBV-transformed B lymphocytes of African and European ancestry. We found that genetic variation affects the response of nearby genes and exhibits distinctive patterns of genotype-treatment interactions, with genotypic effects evident in either only GC-treated or only control-treated conditions. Using a novel statistical framework, we identified interactions that influence the expression of 26 genes known to play central roles in GC-related pathways (e.g. NQO1, AIRE, and SGK1) and that influence the secretion of IL6.

Adaptations to climate-mediated selective pressures in humans.

Humans inhabit a remarkably diverse range of environments, and adaptation through natural selection has likely played a central role in the capacity to survive and thrive in extreme climates. Unlike numerous studies that used only population genetic data to search for evidence of selection, here we scan the human genome for selection signals by identifying the SNPs with the strongest correlations between allele frequencies and climate across 61 worldwide populations. We find a striking enrichment of genic and nonsynonymous SNPs relative to non-genic SNPs among those that are strongly correlated with these climate variables. Among the most extreme signals, several overlap with those from GWAS, including SNPs associated with pigmentation and autoimmune diseases. Further, we find an enrichment of strong signals in gene sets related to UV radiation, infection and immunity, and cancer. Our results imply that adaptations to climate shaped the spatial distribution of variation in humans.

Distinct positions of genetic and oral histories: Perspectives from India.

Over the past decade, genomic data have contributed to several insights on global human population histories. These studies have been met both with interest and critically, particularly by populations with oral histories that are records of their past and often reference their origins. While several studies have reported concordance between oral and genetic histories, there is potential for tension that may stem from genetic histories being prioritized or used to confirm community-based knowledge and ethnography, especially if they differ. To investigate the interplay between oral and genetic histories, we focused on the southwestern region of India and analyzed whole-genome sequence data from 156 individuals identifying as Bunt, Kodava, Nair, and Kapla. We supplemented limited anthropological records on these populations with oral history accounts from community members and historical literature, focusing on references to non-local origins such as the ancient Scythians in the case of Bunt, Kodava, and Nair, members of Alexander the Great's army for the Kodava, and an African-related source for Kapla. We found these populations to be genetically most similar to other Indian populations, with the Kapla more similar to South Indian tribal populations that maximize a genetic ancestry related to Ancient Ancestral South Indians. We did not find evidence of additional genetic sources in the study populations than those known to have contributed to many other present-day South Asian populations. Our results demonstrate that oral and genetic histories may not always provide consistent accounts of population origins and motivate further community-engaged, multi-disciplinary investigations of non-local origin stories in these communities.

Natural selection and functional genetic variation in the p53 pathway.

The allele frequencies of two functional single-nucleotide polymorphisms (SNPs) in the p53 pathway, the MDM2 SNP309 and TP53 Arg72Pro, vary dramatically among populations. That the frequencies of the TP53 SNP follow a clinal distribution may suggest that selective pressure from environmental variables correlated with latitude contributed to these observed population differences. Recently, winter temperature and UV radiation were found to be significantly correlated with the TP53 and the MDM2 SNPs, respectively, in East Asians; whether these correlations are more extreme than expected based upon nonselective factors such as patterns of human migration remains unclear. Here, we genotyped these two SNPs in 971 unrelated individuals from 52 unique populations worldwide and tested for correlations with both latitude and a number of climate-related environmental variables on a global scale, controlling for these neutral processes. The TP53 SNP was associated with a significant selection signal for a few climate variables, such as short-wave radiation flux in the winter, but these signals were no longer significant after correction for multiple tests. The MDM2 SNP did not exhibit a significant signal with any climate variable. Therefore, these SNPs are unlikely to be under selective pressure driven by these variables. Thus, these data underscore the need to incorporate population history when assessing signatures of selection.

Allele-specific down-regulation of RPTOR expression induced by retinoids contributes to climate adaptations.

The mechanistic target of rapamycin (MTOR) pathway regulates cell growth, energy homeostasis, apoptosis, and immune response. The regulatory associated protein of MTOR encoded by the RPTOR gene is a key component of this pathway. A previous survey of candidate genes found that RPTOR contains multiple SNPs with strong correlations between allele frequencies and climate variables, consistent with the action of selective pressures that vary across environments. Using data from a recent genome scan for selection signals, we honed in on a SNP (rs11868112) 26 kb upstream to the transcription start site of RPTOR that exhibits the strongest association with temperature variables. Transcription factor motif scanning and mining of recently mapped transcription factor binding sites identified a binding site for POU class 2 homeobox 1 (POU2F1) spanning the SNP and an adjacent retinoid acid receptor (RAR) binding site. Using expression quantification, chromatin immunoprecipitation (ChIP), and reporter gene assays, we demonstrate that POU2F1 and RARA do bind upstream of the RPTOR gene to regulate its expression in response to retinoids; this regulation is affected by the allele status at rs11868112 with the derived allele resulting in lower expression levels. We propose a model in which the derived allele influences thermogenesis or immune response by altering MTOR pathway activity and thereby increasing fitness in colder climates. Our results show that signatures of genetic adaptations can identify variants with functional effects, consistent with the idea that selection signals may be used for SNP annotation.

Colloquium paper: human adaptations to diet, subsistence, and ecoregion are due to subtle shifts in allele frequency.

Human populations use a variety of subsistence strategies to exploit an exceptionally broad range of ecoregions and dietary components. These aspects of human environments have changed dramatically during human evolution, giving rise to new selective pressures. To understand the genetic basis of human adaptations, we combine population genetics data with ecological information to detect variants that increased in frequency in response to new selective pressures. Our approach detects SNPs that show concordant differences in allele frequencies across populations with respect to specific aspects of the environment. Genic and especially nonsynonymous SNPs are overrepresented among those most strongly correlated with environmental variables. This provides genome-wide evidence for selection due to changes in ecoregion, diet, and subsistence. We find particularly strong signals associated with polar ecoregions, with foraging, and with a diet rich in roots and tubers. Interestingly, several of the strongest signals overlap with those implicated in energy metabolism phenotypes from genome-wide association studies, including SNPs influencing glucose levels and susceptibility to type 2 diabetes. Furthermore, several pathways, including those of starch and sucrose metabolism, are enriched for strong signals of adaptations to a diet rich in roots and tubers, whereas signals associated with polar ecoregions are overrepresented in genes associated with energy metabolism pathways.

Adaptive variation regulates the expression of the human SGK1 gene in response to stress.

The Serum and Glucocorticoid-regulated Kinase1 (SGK1) gene is a target of the glucocorticoid receptor (GR) and is central to the stress response in many human tissues. Because environmental stress varies across habitats, we hypothesized that natural selection shaped the geographic distribution of genetic variants regulating the level of SGK1 expression following GR activation. By combining population genetics and molecular biology methods, we identified a variant (rs9493857) with marked allele frequency differences between populations of African and European ancestry and with a strong correlation between allele frequency and latitude in worldwide population samples. This SNP is located in a GR-binding region upstream of SGK1 that was identified using a GR ChIP-chip. SNP rs9493857 also lies within a predicted binding site for Oct1, a transcription factor known to cooperate with the GR in the transactivation of target genes. Using ChIP assays, we show that both GR and Oct1 bind to this region and that the ancestral allele at rs9493857 binds the GR-Oct1 complex more efficiently than the derived allele. Finally, using a reporter gene assay, we demonstrate that the ancestral allele is associated with increased glucocorticoid-dependent gene expression when compared to the derived allele. Our results suggest a novel paradigm in which hormonal responsiveness is modulated by sequence variation in the regulatory regions of nuclear receptor target genes. Identifying such functional variants may shed light on the mechanisms underlying inter-individual variation in response to environmental stressors and to hormonal therapy, as well as in the susceptibility to hormone-dependent diseases.

Ancient genomes from the Himalayas illuminate the genetic history of Tibetans and their Tibeto-Burman speaking neighbors.

Present-day Tibetans have adapted both genetically and culturally to the high altitude environment of the Tibetan Plateau, but fundamental questions about their origins remain unanswered. Recent archaeological and genetic research suggests the presence of an early population on the Plateau within the past 40 thousand years, followed by the arrival of subsequent groups within the past 10 thousand years. Here, we obtain new genome-wide data for 33 ancient individuals from high elevation sites on the southern fringe of the Tibetan Plateau in Nepal, who we show are most closely related to present-day Tibetans. They derive most of their ancestry from groups related to Late Neolithic populations at the northeastern edge of the Tibetan Plateau but also harbor a minor genetic component from a distinct and deep Paleolithic Eurasian ancestry. In contrast to their Tibetan neighbors, present-day non-Tibetan Tibeto-Burman speakers living at mid-elevations along the southern and eastern margins of the Plateau form a genetic cline that reflects a distinct genetic history. Finally, a comparison between ancient and present-day highlanders confirms ongoing positive selection of high altitude adaptive alleles.

A pleiotropic hypoxia-sensitive EPAS1 enhancer is disrupted by adaptive alleles in Tibetans.

In Tibetans, noncoding alleles in EPAS1-whose protein product hypoxia-inducible factor 2α (HIF-2α) drives the response to hypoxia-carry strong signatures of positive selection; however, their functional mechanism has not been systematically examined. Here, we report that high-altitude alleles disrupt the activity of four EPAS1 enhancers in one or more cell types. We further characterize one enhancer (ENH5) whose activity is both allele specific and hypoxia dependent. Deletion of ENH5 results in down-regulation of EPAS1 and HIF-2α targets in acute hypoxia and in a blunting of the transcriptional response to sustained hypoxia. Deletion of ENH5 in mice results in dysregulation of gene expression across multiple tissues. We propose that pleiotropic adaptive effects of the Tibetan alleles in EPAS1 underlie the strong selective signal at this gene.

A signature of balancing selection in the region upstream to the human UGT2B4 gene and implications for breast cancer risk.

UDP-glucuronosyltransferase 2 family, polypeptide B4 (UGT2B4) is an important metabolizing enzyme involved in the clearance of many xenobiotics and endogenous substrates, especially steroid hormones and bile acids. The HapMap data show that numerous SNPs upstream of UGT2B4 are in near-perfect linkage disequilibrium with each other and occur at intermediate frequency, indicating that this region might contain a target of natural selection. To investigate this possibility, we chose three regions (4.8 kb in total) for resequencing and observed a striking excess of intermediate-frequency alleles that define two major haplotypes separated by many mutation events and with little differentiation across populations, thus suggesting that the variation pattern upstream UGT2B4 is highly unusual and may be the result of balancing selection. We propose that this pattern is due to the maintenance of a regulatory polymorphism involved in the fine tuning of UGT2B4 expression so that heterozygous genotypes result in optimal enzyme levels. Considering the important role of steroid hormones in breast cancer susceptibility, we hypothesized that variation in this region could predispose to breast cancer. To test this hypothesis, we genotyped tag SNP rs13129471 in 1,261 patients and 825 normal women of African ancestry from three populations. The frequency comparison indicated that rs13129471 was significantly associated with breast cancer after adjusting for ethnicity [P = 0.003; heterozygous odds ratio (OR) 1.02, 95% confidence interval (CI) 0.81-1.28; homozygous OR 1.50, 95% CI 1.15-1.95]. Our results provide new insights into UGT2B4 sequence variation and indicate that a signal of natural selection may lead to the identification of disease susceptibility variants.

Adaptations to climate in candidate genes for common metabolic disorders.

Evolutionary pressures due to variation in climate play an important role in shaping phenotypic variation among and within species and have been shown to influence variation in phenotypes such as body shape and size among humans. Genes involved in energy metabolism are likely to be central to heat and cold tolerance. To test the hypothesis that climate shaped variation in metabolism genes in humans, we used a bioinformatics approach based on network theory to select 82 candidate genes for common metabolic disorders. We genotyped 873 tag SNPs in these genes in 54 worldwide populations (including the 52 in the Human Genome Diversity Project panel) and found correlations with climate variables using rank correlation analysis and a newly developed method termed Bayesian geographic analysis. In addition, we genotyped 210 carefully matched control SNPs to provide an empirical null distribution for spatial patterns of allele frequency due to population history alone. For nearly all climate variables, we found an excess of genic SNPs in the tail of the distributions of the test statistics compared to the control SNPs, implying that metabolic genes as a group show signals of spatially varying selection. Among our strongest signals were several SNPs (e.g., LEPR R109K, FABP2 A54T) that had previously been associated with phenotypes directly related to cold tolerance. Since variation in climate may be correlated with other aspects of environmental variation, it is possible that some of the signals that we detected reflect selective pressures other than climate. Nevertheless, our results are consistent with the idea that climate has been an important selective pressure acting on candidate genes for common metabolic disorders.

Allelic imbalance (AI) identifies novel tissue-specific cis-regulatory variation for human UGT2B15.

Allelic imbalance (AI) is a powerful tool to identify cis-regulatory variation for gene expression. UGT2B15 is an important enzyme involved in the metabolism of multiple endobiotics and xenobiotics. In this study, we measured the relative expression of two alleles at this gene by using SNP rs1902023:G>T. An excess of the G over the T allele was consistently observed in liver (P<0.001), but not in breast (P=0.06) samples, suggesting that SNPs in strong linkage disequilibrium with G253T regulate UGT2B15 expression in liver. Seven such SNPs were identified by resequencing the promoter and exon 1, which define two distinct haplotypes. Reporter gene assays confirmed that one haplotype displayed approximately 20% higher promoter activity compared to the other major haplotype in liver HepG2 (P<0.001), but not in breast MCF-7 (P=0.540) cells. Reporter gene assays with additional constructs pointed to rs34010522:G>T and rs35513228:C>T as the cis-regulatory variants; both SNPs were also evaluated in LNCaP and Caco-2 cells. By ChIP, we showed that the transcription factor Nrf2 binds to the region spanning rs34010522:G>T in all four cell lines. Our results provide a good example for how AI can be used to identify cis-regulatory variation and gain insights into the tissue specific regulation of gene expression.