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Abstract Background Comparative gene expression studies in apes are fundamentally limited by the challenges associated with sampling across different tissues. Here, we used single-cell RNA sequencing of embryoid bodies to collect transcriptomic data from over 70 cell types in three humans and three chimpanzees. Results We find hundreds of genes whose regulation is conserved across cell types, as well as genes whose regulation likely evolves under directional selection in one or a handful of cell types. Using embryoid bodies from a human-chimpanzee fused cell line, we also infer the proportion of inter-species regulatory differences due to changes in cis and trans elements between the species. Using the cis/trans inference and an analysis of transcription factor binding sites, we identify dozens of transcription factors whose inter-species differences in expression are affecting expression differences between humans and chimpanzees in hundreds of target genes. Conclusions Here, we present the most comprehensive dataset of comparative gene expression from humans and chimpanzees to date, including a catalog of regulatory mechanisms associated with inter-species differences.

Abstract Background Alternative cleavage and polyadenylation (APA), an RNA processing event, occurs in over 70% of human protein-coding genes. APA results in mRNA transcripts with distinct 3′ ends. Most APA occurs within 3′ UTRs, which harbor regulatory elements that can impact mRNA stability, translation, and localization. Results APA can be profiled using a number of established computational tools that infer polyadenylation sites from standard, short-read RNA-seq datasets. Here, we benchmarked a number of such tools—TAPAS, QAPA, DaPars2, GETUTR, and APATrap— against 3′-Seq, a specialized RNA-seq protocol that enriches for reads at the 3′ ends of genes, and Iso-Seq, a Pacific Biosciences (PacBio) single-molecule full-length RNA-seq method in their ability to identify polyadenylation sites and quantify polyadenylation site usage. We demonstrate that 3′-Seq and Iso-Seq are able to identify and quantify the usage of polyadenylation sites more reliably than computational tools that take short-read RNA-seq as input. However, we find that running one such tool, QAPA, with a set of polyadenylation site annotations derived from small quantities of 3′-Seq or Iso-Seq can reliably quantify variation in APA across conditions, such asacross genotypes, as demonstrated by the successful mapping of alternative polyadenylation quantitative trait loci (apaQTL). Conclusions We envisage that our analyses will shed light on the advantages of studying APA with more specialized sequencing protocols, such as 3′-Seq or Iso-Seq, and the limitations of studying APA with short-read RNA-seq. We provide a computational pipeline to aid in the identification of polyadenylation sites and quantification of polyadenylation site usages using Iso-Seq data as input.

The evolution of complex skeletal traits in primates was likely influenced by both genetic and environmental factors. Because skeletal tissues are notoriously challenging to study using functional genomic approaches, they remain poorly characterized even in humans, let alone across multiple species. The challenges involved in obtaining functional genomic data from the skeleton, combined with the difficulty of obtaining such tissues from nonhuman apes, motivated us to consider an alternative in vitro system with which to comparatively study gene regulation in skeletal cell types. Specifically, we differentiated six human (Homo sapiens) and six chimpanzee (Pan troglodytes) induced pluripotent stem cell lines (iPSCs) into mesenchymal stem cells (MSCs) and subsequently into osteogenic cells (bone cells). We validated differentiation using standard methods and collected single-cell RNA sequencing data from over 100,000 cells across multiple samples and replicates at each stage of differentiation. While most genes that we examined display conserved patterns of expression across species, hundreds of genes are differentially expressed (DE) between humans and chimpanzees within and across stages of osteogenic differentiation. Some of these interspecific DE genes show functional enrichments relevant in skeletal tissue trait development. Moreover, topic modeling indicates that interspecific gene programs become more pronounced as cells mature. Overall, we propose that this in vitro model can be used to identify interspecific regulatory differences that may have contributed to skeletal trait differences between species.

Practically all studies of gene expression in humans to date have been performed in a relatively small number of adult tissues. Gene regulation is highly dynamic and context-dependent. In order to better understand the connection between gene regulation and complex phenotypes, including disease, we need to be able to study gene expression in more cell types, tissues, and states that are relevant to human phenotypes. In particular, we need to characterize gene expression in early development cell types, as mutations that affect developmental processes may be of particular relevance to complex traits. To address this challenge, we propose to use embryoid bodies (EBs), which are organoids that contain a multitude of cell types in dynamic states. EBs provide a system in which one can study dynamic regulatory processes at an unprecedentedly high resolution. To explore the utility of EBs, we systematically explored cellular and gene expression heterogeneity in EBs from multiple individuals. We characterized the various cell types that arise from EBs, the extent to which they recapitulate gene expression in vivo, and the relative contribution of technical and biological factors to variability in gene expression, cell composition, and differentiation efficiency. Our results highlight the utility of EBs as a new model system for mapping dynamic inter-individual regulatory differences in a large variety of cell types.

Dynamic and temporally specific gene regulatory changes may underlie unexplained genetic associations with complex disease. During a dynamic process such as cellular differentiation, the overall cell type composition of a tissue (or an in vitro culture) and the gene regulatory profile of each cell can both experience significant changes over time. To identify these dynamic effects in high resolution, we collected single-cell RNA-sequencing data over a differentiation time course from induced pluripotent stem cells to cardiomyocytes, sampled at 7 unique time points in 19 human cell lines. We employed a flexible approach to map dynamic eQTLs whose effects vary significantly over the course of bifurcating differentiation trajectories, including many whose effects are specific to one of these two lineages. Our study design allowed us to distinguish true dynamic eQTLs affecting a specific cell lineage from expression changes driven by potentially non-genetic differences between cell lines such as cell composition. Additionally, we used the cell type profiles learned from single-cell data to deconvolve and re-analyze data from matched bulk RNA-seq samples. Using this approach, we were able to identify a large number of novel dynamic eQTLs in single cell data while also attributing dynamic effects in bulk to a particular lineage. Overall, we found that using single cell data to uncover dynamic eQTLs can provide new insight into the gene regulatory changes that occur among heterogeneous cell types during cardiomyocyte differentiation.

Genetic effects on gene expression and splicing can be modulated by cellular and environmental factors; yet interactions between genotypes, cell type, and treatment have not been comprehensively studied together. We used an induced pluripotent stem cell system to study multiple cell types derived from the same individuals and exposed them to a large panel of treatments. Cellular responses involved different genes and pathways for gene expression and splicing and were highly variable across contexts. For thousands of genes, we identified variable allelic expression across contexts and characterized different types of gene-environment interactions, many of which are associated with complex traits. Promoter functional and evolutionary features distinguished genes with elevated allelic imbalance mean and variance. On average, half of the genes with dynamic regulatory interactions were missed by large eQTL mapping studies, indicating the importance of exploring multiple treatments to reveal previously unrecognized regulatory loci that may be important for disease.

One life-threatening outcome of cardiovascular disease is myocardial infarction, where cardiomyocytes are deprived of oxygen. To study inter-individual differences in response to hypoxia, we established an in vitro model of induced pluripotent stem cell-derived cardiomyocytes from 15 individuals. We measured gene expression levels, chromatin accessibility, and methylation levels in four culturing conditions that correspond to normoxia, hypoxia, and short- or long-term re-oxygenation. We characterized thousands of gene regulatory changes as the cells transition between conditions. Using available genotypes, we identified 1,573 genes with a cis expression quantitative locus (eQTL) in at least one condition, as well as 367 dynamic eQTLs, which are classified as eQTLs in at least one, but not in all conditions. A subset of genes with dynamic eQTLs is associated with complex traits and disease. Our data demonstrate how dynamic genetic effects on gene expression, which are likely relevant for disease, can be uncovered under stress.

While comparative functional genomic studies have shown that inter-species differences in gene expression can be explained by corresponding inter-species differences in genetic and epigenetic regulatory mechanisms, co-transcriptional mechanisms, such as alternative polyadenylation (APA), have received little attention. We characterized APA in lymphoblastoid cell lines from six humans and six chimpanzees by identifying and estimating the usage for 44,432 polyadenylation sites (PAS) in 9518 genes. Although APA is largely conserved, 1705 genes showed significantly different PAS usage (FDR 0.05) between species. Genes with divergent APA also tend to be differentially expressed, are enriched among genes showing differences in protein translation, and can explain a subset of observed inter-species protein expression differences that do not differ at the transcript level. Finally, we found that genes with a dominant PAS, which is used more often than other PAS, are particularly enriched for differentially expressed genes.

Inter-individual variation in gene expression has been shown to be heritable and is often associated with differences in disease susceptibility between individuals. Many studies focused on mapping associations between genetic and gene regulatory variation, yet much less attention has been paid to the evolutionary processes that shape the observed differences in gene regulation between individuals in humans or any other primate. To begin addressing this gap, we performed a comparative analysis of gene expression variability and expression quantitative trait loci (eQTLs) in humans and chimpanzees, using gene expression data from primary heart samples. We found that expression variability in both species is often determined by non-genetic sources, such as cell-type heterogeneity. However, we also provide evidence that inter-individual variation in gene regulation can be genetically controlled, and that the degree of such variability is generally conserved in humans and chimpanzees. In particular, we found a significant overlap of orthologous genes associated with eQTLs in both species. We conclude that gene expression variability in humans and chimpanzees often evolves under similar evolutionary pressures.

Little is known about co-transcriptional or post-transcriptional regulatory mechanisms linking noncoding variation to variation in organismal traits. To begin addressing this gap, we used 3’ Seq to study the impact of genetic variation on alternative polyadenylation (APA) in the nuclear and total mRNA fractions of 52 HapMap Yoruba human lymphoblastoid cell lines. We mapped 602 APA quantitative trait loci (apaQTLs) at 10% FDR, of which 152 were nuclear specific. Effect sizes at intronic apaQTLs are negatively correlated with eQTL effect sizes. These observations suggest genetic variants can decrease mRNA expression levels by increasing usage of intronic PAS. We also identified 24 apaQTLs associated with protein levels, but not mRNA expression. Finally, we found that 19% of apaQTLs can be associated with disease. Thus, our work demonstrates that APA links genetic variation to variation in gene expression, protein expression, and disease risk, and reveals uncharted modes of genetic regulation.

Abstract Background There is substantial interest in the evolutionary forces that shaped the regulatory framework in early human development. Progress in this area has been slow because it is difficult to obtain relevant biological samples. Induced pluripotent stem cells (iPSCs) may provide the ability to establish in vitro models of early human and non-human primate developmental stages. Results Using matched iPSC panels from humans and chimpanzees, we comparatively characterize gene regulatory changes through a four-day time course differentiation of iPSCs into primary streak, endoderm progenitors, and definitive endoderm. As might be expected, we find that differentiation stage is the major driver of variation in gene expression levels, followed by species. We identify thousands of differentially expressed genes between humans and chimpanzees in each differentiation stage. Yet, when we consider gene-specific dynamic regulatory trajectories throughout the time course, we find that at least 75% of genes, including nearly all known endoderm developmental markers, have similar trajectories in the two species. Interestingly, we observe a marked reduction of both intra- and inter-species variation in gene expression levels in primitive streak samples compared to the iPSCs, with a recovery of regulatory variation in endoderm progenitors. Conclusions The reduction of variation in gene expression levels at a specific developmental stage, paired with overall high degree of conservation of temporal gene regulation, is consistent with the dynamics of a conserved developmental process.

Abstract Tuberculosis (TB) is a deadly infectious disease, which kills millions of people every year. The causative pathogen, Mycobacterium tuberculosis (MTB), is estimated to have infected up to a third of the world’s population; however, only approximately 10% of infected healthy individuals progress to active TB. Despite evidence for heritability, it is not currently possible to predict who may develop TB. To explore approaches to classify susceptibility to TB, we infected with MTB dendritic cells (DCs) from putatively resistant individuals diagnosed with latent TB, and from susceptible individuals that had recovered from active TB. We measured gene expression levels in infected and non-infected cells and found hundreds of differentially expressed genes between susceptible and resistant individuals in the non-infected cells. We further found that genetic polymorphisms nearby the differentially expressed genes between susceptible and resistant individuals are more likely to be associated with TB susceptibility in published GWAS data. Lastly, we trained a classifier based on the gene expression levels in the non-infected cells, and demonstrated reasonable performance on our data and an independent data set. Overall, our promising results from this small study suggest that training a classifier on a larger cohort may enable us to accurately predict TB susceptibility.

Abstract ATAC-seq is a high-throughput sequencing technique that identifies open chromatin. Depending on the cell type, ATAC-seq samples may contain ~20–80% of mitochondrial sequencing reads. As the regions of open chromatin of interest are usually located in the nuclear genome, mitochondrial reads are typically discarded from the analysis. We tested two approaches to decrease wasted sequencing in ATAC-seq libraries generated from lymphoblastoid cell lines: targeted cleavage of mitochondrial DNA fragments using CRISPR technology and removal of detergent from the cell lysis buffer. We analyzed the effects of these treatments on the number of usable (unique, non-mitochondrial) reads and the number and quality of peaks called, including peaks identified in enhancers and transcription start sites. Both treatments resulted in considerable reduction of mitochondrial reads (1.7 and 3-fold, respectively). The removal of detergent, however, resulted in increased background and fewer peaks. The highest number of peaks and highest quality data was obtained by preparing samples with the original ATAC-seq protocol (using detergent) and treating them with CRISPR. This strategy reduced the amount of sequencing required to call a high number of peaks, which could lead to cost reduction when performing ATAC-seq on large numbers of samples and in cell types that contain a large amount of mitochondria.

A growing body of evidence supports the notion that variation in gene regulation plays a crucial role in both speciation and adaptation. However, a comprehensive functional understanding of the mechanisms underlying regulatory evolution remains elusive. In primates, one of the crucial missing pieces of information towards a better understanding of regulatory evolution is a comparative annotation of interactions between distal regulatory elements and promoters. Chromatin conformation capture technologies have enabled genome-wide quantifications of such distal 3D interactions. However, relatively little comparative research in primates has been done using such technologies. To address this gap, we used Hi-C to characterize 3D chromatin interactions in induced pluripotent stem cells (iPSCs) from humans and chimpanzees. We also used RNA-seq to collect gene expression data from the same lines. We generally observed that lower-order, pairwise 3D genomic interactions are conserved in humans and chimpanzees, but higher order genomic structures, such as topologically associating domains (TADs), are not as conserved. Inter-species differences in 3D genomic interactions are often associated with gene expression differences between the species. To provide additional functional context to our observations, we considered previously published chromatin data from human stem cells. We found that inter-species differences in 3D genomic interactions, which are also associated with gene expression differences between the species, are enriched for both active and repressive marks. Overall, our data demonstrate that, as expected, an understanding of 3D genome reorganization is key to explaining regulatory evolution.

Despite anatomical similarities, there are differences in susceptibility to cardiovascular disease (CVD) between primates; humans are prone to myocardial ischemia, while chimpanzees are prone to myocardial fibrosis. Induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) allow for direct inter-species comparisons of the gene regulatory response to CVD-relevant perturbations such as oxygen deprivation, a consequence of ischemia. To gain insight into the evolution of disease susceptibility, we characterized gene expression levels in iPSC-CMs in humans and chimpanzees, before and after hypoxia and re-oxygenation. The transcriptional response to hypoxia is generally conserved across species, yet we were able to identify hundreds of species-specific regulatory responses including in genes previously associated with CVD. The 1,920 genes that respond to hypoxia in both species are enriched for loss-of-function intolerant genes; but are depleted for expression quantitative trait loci and cardiovascular-related genes. Our results indicate that response to hypoxic stress is highly conserved in humans and chimpanzees.

Quantification of gene expression levels at the single cell level has revealed that gene expression can vary substantially even across a population of homogeneous cells. However, it is currently unclear what genomic features control variation in gene expression levels, and whether common genetic variants may impact gene expression variation. Here, we take a genome-wide approach to identify expression variance quantitative trait loci (vQTLs). To this end, we generated single cell RNA-seq (scRNA-seq) data from induced pluripotent stem cells (iPSCs) derived from 53 Yoruba individuals. We collected data for a median of 95 cells per individual and a total of 5,447 single cells, and identified 235 mean expression QTLs (eQTLs) at 10% FDR, of which 79% replicate in bulk RNA-seq data from the same individuals. We further identified 5 vQTLs at 10% FDR, but demonstrate that these can also be explained as effects on mean expression. Our study suggests that dispersion QTLs (dQTLs) which could alter the variance of expression independently of the mean can have larger fold changes, but explain less phenotypic variance than eQTLs. We estimate 4,015 individuals as a lower bound to achieve 80% power to detect the strongest dQTLs in iPSCs. These results will guide the design of future studies on understanding the genetic control of gene expression variance.

Anthracycline-induced cardiotoxicity (ACT) is a key limiting factor in setting optimal chemotherapy regimes, with almost half of patients expected to develop congestive heart failure given high doses. However, the genetic basis of sensitivity to anthracyclines remains unclear. We created a panel of iPSC-derived cardiomyocytes from 45 individuals and performed RNA-seq after 24 hr exposure to varying doxorubicin dosages. The transcriptomic response is substantial: the majority of genes are differentially expressed and over 6000 genes show evidence of differential splicing, the later driven by reduced splicing fidelity in the presence of doxorubicin. We show that inter-individual variation in transcriptional response is predictive of in vitro cell damage, which in turn is associated with in vivo ACT risk. We detect 447 response-expression quantitative trait loci (QTLs) and 42 response-splicing QTLs, which are enriched in lower ACT GWAS [Formula: see text]-values, supporting the in vivo relevance of our map of genetic regulation of cellular response to anthracyclines.

Transposable elements (TEs) comprise almost half of primate genomes and their aberrant regulation can result in deleterious effects. In pluripotent stem cells, rapidly evolving KRAB-ZNF genes target TEs for silencing by H3K9me3. To investigate the evolution of TE silencing, we performed H3K9me3 ChIP-seq experiments in induced pluripotent stem cells from 10 human and 7 chimpanzee individuals. We identified four million orthologous TEs and found the SVA and ERV families to be marked most frequently by H3K9me3. We found little evidence of inter-species differences in TE silencing, with as many as 82% of putatively silenced TEs marked at similar levels in humans and chimpanzees. TEs that are preferentially silenced in one species are a similar age to those silenced in both species and are not more likely to be associated with expression divergence of nearby orthologous genes. Our data suggest limited species-specificity of TE silencing across 6 million years of primate evolution.

Accurate annotation of protein coding regions is essential for understanding how genetic information is translated into function. We describe riboHMM, a new method that uses ribosome footprint data to accurately infer translated sequences. Applying riboHMM to human lymphoblastoid cell lines, we identified 7273 novel coding sequences, including 2442 translated upstream open reading frames. We observed an enrichment of footprints at inferred initiation sites after drug-induced arrest of translation initiation, validating many of the novel coding sequences. The novel proteins exhibit significant selective constraint in the inferred reading frames, suggesting that many are functional. Moreover, ~40% of bicistronic transcripts showed negative correlation in the translation levels of their two coding sequences, suggesting a potential regulatory role for these novel regions. Despite known limitations of mass spectrometry to detect protein expressed at low level, we estimated a 14% validation rate. Our work significantly expands the set of known coding regions in humans.

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.

Comparative genomics studies in primates are restricted due to our limited access to samples. In order to gain better insight into the genetic processes that underlie variation in complex phenotypes in primates, we must have access to faithful model systems for a wide range of cell types. To facilitate this, we generated a panel of 7 fully characterized chimpanzee induced pluripotent stem cell (iPSC) lines derived from healthy donors. To demonstrate the utility of comparative iPSC panels, we collected RNA-sequencing and DNA methylation data from the chimpanzee iPSCs and the corresponding fibroblast lines, as well as from 7 human iPSCs and their source lines, which encompass multiple populations and cell types. We observe much less within-species variation in iPSCs than in somatic cells, indicating the reprogramming process erases many inter-individual differences. The low within-species regulatory variation in iPSCs allowed us to identify many novel inter-species regulatory differences of small magnitude.

Recently, the Mouse ENCODE Consortium reported that comparative gene expression data from human and mouse tend to cluster more by species rather than by tissue. This observation was surprising, as it contradicted much of the comparative gene regulatory data collected previously, as well as the common notion that major developmental pathways are highly conserved across a wide range of species, in particular across mammals. Here we show that the Mouse ENCODE gene expression data were collected using a flawed study design, which confounded sequencing batch (namely, the assignment of samples to sequencing flowcells and lanes) with species. When we account for the batch effect, the corrected comparative gene expression data from human and mouse tend to cluster by tissue, not by species.

Renewable in vitro cell cultures, such as lymphoblastoid cell lines (LCLs), have facilitated studies that contributed to our understanding of genetic influence on human traits. However, the degree to which cell lines faithfully maintain differences in donor-specific phenotypes is still debated. We have previously reported that standard cell line maintenance practice results in a loss of donor-specific gene expression signatures in LCLs. An alternative to the LCL model is the induced pluripotent stem cell (iPSC) system, which carries the potential to model tissue-specific physiology through the use of differentiation protocols. Still, existing LCL banks represent an important source of starting material for iPSC generation, and it is possible that the disruptions in gene regulation associated with long-term LCL maintenance could persist through the reprogramming process. To address this concern, we studied the effect of reprogramming mature LCL cultures from six unrelated donors to iPSCs on the ensuing gene expression patterns within and between individuals. We show that the reprogramming process results in a recovery of donor-specific gene regulatory signatures, increasing the number of genes with a detectable donor effect by an order of magnitude. The proportion of variation in gene expression statistically attributed to donor increases from 6.9% in LCLs to 24.5% in iPSCs (P < 10-15). Since environmental contributions are unlikely to be a source of individual variation in our system of highly passaged cultured cell lines, our observations suggest that the effect of genotype on gene regulation is more pronounced in iPSCs than in LCLs. Our findings indicate that iPSCs can be a powerful model system for studies of phenotypic variation across individuals in general, and the genetic association with variation in gene regulation in particular. We further conclude that LCLs are an appropriate starting material for iPSC generation.

Rhinovirus (RV) is the most prevalent human respiratory virus and is responsible for at least half of all common colds. RV infections may result in a broad spectrum of effects that range from asymptomatic infections to severe lower respiratory illnesses. The basis for inter-individual variation in the response to RV infection is not well understood. In this study, we explored whether host genetic variation is associated with variation in gene expression response to RV infections between individuals. To do so, we obtained genome-wide genotype and gene expression data in uninfected and RV-infected peripheral blood mononuclear cells (PBMCs) from 98 individuals. We mapped local and distant genetic variation that is associated with inter-individual differences in gene expression levels (eQTLs) in both uninfected and RV-infected cells. We focused specifically on response eQTLs (reQTLs), namely, genetic associations with inter-individual variation in gene expression response to RV infection. We identified local reQTLs for 38 genes, including genes with known functions in viral response (UBA7, OAS1, IRF5) and genes that have been associated with immune and RV-related diseases (e.g., ITGA2, MSR1, GSTM3). The putative regulatory regions of genes with reQTLs were enriched for binding sites of virus-activated STAT2, highlighting the role of condition-specific transcription factors in genotype-by-environment interactions. Overall, we suggest that the 38 loci associated with inter-individual variation in gene expression response to RV-infection represent promising candidates for affecting immune and RV-related respiratory diseases.

Primate evolution has been argued to result, in part, from changes in how genes are regulated. However, we still know little about gene regulation in natural primate populations. We conducted an RNA sequencing (RNA-seq)-based study of baboons from an intensively studied wild population. We performed complementary expression quantitative trait locus (eQTL) mapping and allele-specific expression analyses, discovering substantial evidence for, and surprising power to detect, genetic effects on gene expression levels in the baboons. eQTL were most likely to be identified for lineage-specific, rapidly evolving genes; interestingly, genes with eQTL significantly overlapped between baboons and a comparable human eQTL data set. Our results suggest that genes vary in their tolerance of genetic perturbation, and that this property may be conserved across species. Further, they establish the feasibility of eQTL mapping using RNA-seq data alone, and represent an important step towards understanding the genetic architecture of gene expression in primates.

It is now well established that noncoding regulatory variants play a central role in the genetics of common diseases and in evolution. However, until recently, we have known little about the mechanisms by which most regulatory variants act. For instance, what types of functional elements in DNA, RNA, or proteins are most often affected by regulatory variants? Which stages of gene regulation are typically altered? How can we predict which variants are most likely to impact regulation in a given cell type? Recent studies, in many cases using quantitative trait loci (QTL)-mapping approaches in cell lines or tissue samples, have provided us with considerable insight into the properties of genetic loci that have regulatory roles. Such studies have uncovered novel biochemical regulatory interactions and led to the identification of previously unrecognized regulatory mechanisms. We have learned that genetic variation is often directly associated with variation in regulatory activities (namely, we can map regulatory QTLs, not just expression QTLs [eQTLs]), and we have taken the first steps towards understanding the causal order of regulatory events (for example, the role of pioneer transcription factors). Yet, in most cases, we still do not know how to interpret overlapping combinations of regulatory interactions, and we are still far from being able to predict how variation in regulatory mechanisms is propagated through a chain of interactions to eventually result in changes in gene expression profiles.

The bacterial composition of the human fecal microbiome is influenced by many lifestyle factors, notably diet. It is less clear, however, what role host genetics plays in dictating the composition of bacteria living in the gut. In this study, we examined the association of ~200K host genotypes with the relative abundance of fecal bacterial taxa in a founder population, the Hutterites, during two seasons (n = 91 summer, n = 93 winter, n = 57 individuals collected in both). These individuals live and eat communally, minimizing variation due to environmental exposures, including diet, which could potentially mask small genetic effects. Using a GWAS approach that takes into account the relatedness between subjects, we identified at least 8 bacterial taxa whose abundances were associated with single nucleotide polymorphisms in the host genome in each season (at genome-wide FDR of 20%). For example, we identified an association between a taxon known to affect obesity (genus Akkermansia) and a variant near PLD1, a gene previously associated with body mass index. Moreover, we replicate a previously reported association from a quantitative trait locus (QTL) mapping study of fecal microbiome abundance in mice (genus Lactococcus, rs3747113, P = 3.13 x 10-7). Finally, based on the significance distribution of the associated microbiome QTLs in our study with respect to chromatin accessibility profiles, we identified tissues in which host genetic variation may be acting to influence bacterial abundance in the gut.

Understanding global gene regulation depends critically on accurate annotation of regulatory elements that are functional in a given cell type. CENTIPEDE, a powerful, probabilistic framework for identifying transcription factor binding sites from tissue-specific DNase I cleavage patterns and genomic sequence content, leverages the hypersensitivity of factor-bound chromatin and the information in the DNase I spatial cleavage profile characteristic of each DNA binding protein to accurately infer functional factor binding sites. However, the model for the spatial profile in this framework fails to account for the substantial variation in the DNase I cleavage profiles across different binding sites. Neither does it account for variation in the profiles at the same binding site across multiple replicate DNase I experiments, which are increasingly available. In this work, we introduce new methods, based on multi-scale models for inhomogeneous Poisson processes, to account for such variation in DNase I cleavage patterns both within and across binding sites. These models account for the spatial structure in the heterogeneity in DNase I cleavage patterns for each factor. Using DNase-seq measurements assayed in a lymphoblastoid cell line, we demonstrate the improved performance of this model for several transcription factors by comparing against the Chip-seq peaks for those factors. Finally, we explore the effects of DNase I sequence bias on inference of factor binding using a simple extension to our framework that allows for a more flexible background model. The proposed model can also be easily applied to paired-end ATAC-seq and DNase-seq data. msCentipede, a Python implementation of our algorithm, is available at http://rajanil.github.io/msCentipede.

DNA methylation is an important epigenetic regulator of gene expression. Recent studies have revealed widespread associations between genetic variation and methylation levels. However, the mechanistic links between genetic variation and methylation remain unclear. To begin addressing this gap, we collected methylation data at ∼300,000 loci in lymphoblastoid cell lines (LCLs) from 64 HapMap Yoruba individuals, and genome-wide bisulfite sequence data in ten of these individuals. We identified (at an FDR of 10%) 13,915 cis methylation QTLs (meQTLs)-i.e., CpG sites in which changes in DNA methylation are associated with genetic variation at proximal loci. We found that meQTLs are frequently associated with changes in methylation at multiple CpGs across regions of up to 3 kb. Interestingly, meQTLs are also frequently associated with variation in other properties of gene regulation, including histone modifications, DNase I accessibility, chromatin accessibility, and expression levels of nearby genes. These observations suggest that genetic variants may lead to coordinated molecular changes in all of these regulatory phenotypes. One plausible driver of coordinated changes in different regulatory mechanisms is variation in transcription factor (TF) binding. Indeed, we found that SNPs that change predicted TF binding affinities are significantly enriched for associations with DNA methylation at nearby CpGs.

One goal of human genetics is to understand how the information for precise and dynamic gene expression programs is encoded in the genome. The interactions of transcription factors (TFs) with DNA regulatory elements clearly play an important role in determining gene expression outputs, yet the regulatory logic underlying functional transcription factor binding is poorly understood. Many studies have focused on characterizing the genomic locations of TF binding, yet it is unclear to what extent TF binding at any specific locus has functional consequences with respect to gene expression output. To evaluate the context of functional TF binding we knocked down 59 TFs and chromatin modifiers in one HapMap lymphoblastoid cell line. We then identified genes whose expression was affected by the knockdowns. We intersected the gene expression data with transcription factor binding data (based on ChIP-seq and DNase-seq) within 10 kb of the transcription start sites of expressed genes. This combination of data allowed us to infer functional TF binding. Using this approach, we found that only a small subset of genes bound by a factor were differentially expressed following the knockdown of that factor, suggesting that most interactions between TF and chromatin do not result in measurable changes in gene expression levels of putative target genes. We found that functional TF binding is enriched in regulatory elements that harbor a large number of TF binding sites, at sites with predicted higher binding affinity, and at sites that are enriched in genomic regions annotated as "active enhancers."

The composition of the human gut microbiome is influenced by many environmental factors. Diet is thought to be one of the most important determinants, though we have limited understanding of the extent to which dietary fluctuations alter variation in the gut microbiome between individuals. In this study, we examined variation in gut microbiome composition between winter and summer over the course of one year in 60 members of a founder population, the Hutterites. Because of their communal lifestyle, Hutterite diets are similar across individuals and remarkably stable throughout the year, with the exception that fresh produce is primarily served during the summer and autumn months. Our data indicate that despite overall gut microbiome stability within individuals over time, there are consistent and significant population-wide shifts in microbiome composition across seasons. We found seasonal differences in both (i) the abundance of particular taxa (false discovery rate

Epstein-Barr virus (EBV) transformed lymphoblastoid cell lines (LCLs) are a widely used renewable resource for functional genomic studies in humans. The ability to accumulate multidimensional data pertaining to the same individual cell lines, from complete genomic sequences to detailed gene regulatory profiles, further enhances the utility of LCLs as a model system. However, the extent to which LCLs are a faithful model system is relatively unknown. We have previously shown that gene expression profiles of newly established LCLs maintain a strong individual component. Here, we extend our study to investigate the effect of freeze-thaw cycles on gene expression patterns in mature LCLs, especially in the context of inter-individual variation in gene expression. We report a profound difference in the gene expression profiles of newly established and mature LCLs. Once newly established LCLs undergo a freeze-thaw cycle, the individual specific gene expression signatures become much less pronounced as the gene expression levels in LCLs from different individuals converge to a more uniform profile, which reflects a mature transformed B cell phenotype. We found that previously identified eQTLs are enriched among the relatively few genes whose regulations in mature LCLs maintain marked individual signatures. We thus conclude that while insight drawn from gene regulatory studies in mature LCLs may generally not be affected by the artificial nature of the LCL model system, many aspects of primary B cell biology cannot be observed and studied in mature LCL cultures.

Massively parallel high throughput sequencing technologies allow us to interrogate the microbial composition of biological samples at unprecedented resolution. The typical approach is to perform high-throughout sequencing of 16S rRNA genes, which are then taxonomically classified based on similarity to known sequences in existing databases. Current technologies cause a predicament though, because although they enable deep coverage of samples, they are limited in the length of sequence they can produce. As a result, high-throughout studies of microbial communities often do not sequence the entire 16S rRNA gene. The challenge is to obtain reliable representation of bacterial communities through taxonomic classification of short 16S rRNA gene sequences. In this study we explored properties of different study designs and developed specific recommendations for effective use of short-read sequencing technologies for the purpose of interrogating bacterial communities, with a focus on classification using naïve Bayesian classifiers. To assess precision and coverage of each design, we used a collection of ∼8,500 manually curated 16S rRNA gene sequences from cultured bacteria and a set of over one million bacterial 16S rRNA gene sequences retrieved from environmental samples, respectively. We also tested different configurations of taxonomic classification approaches using short read sequencing data, and provide recommendations for optimal choice of the relevant parameters. We conclude that with a judicious selection of the sequenced region and the corresponding choice of a suitable training set for taxonomic classification, it is possible to explore bacterial communities at great depth using current technologies, with only a minimal loss of taxonomic resolution.

Mapping of expression quantitative trait loci (eQTLs) is an important technique for studying how genetic variation affects gene regulation in natural populations. In a previous study using Illumina expression data from human lymphoblastoid cell lines, we reported that cis-eQTLs are especially enriched around transcription start sites (TSSs) and immediately upstream of transcription end sites (TESs). In this paper, we revisit the distribution of eQTLs using additional data from Affymetrix exon arrays and from RNA sequencing. We confirm that most eQTLs lie close to the target genes; that transcribed regions are generally enriched for eQTLs; that eQTLs are more abundant in exons than introns; and that the peak density of eQTLs occurs at the TSS. However, we find that the intriguing TES peak is greatly reduced or absent in the Affymetrix and RNA-seq data. Instead our data suggest that the TES peak observed in the Illumina data is mainly due to exon-specific QTLs that affect 3' untranslated regions, where most of the Illumina probes are positioned. Nonetheless, we do observe an overall enrichment of eQTLs in exons versus introns in all three data sets, consistent with an important role for exonic sequences in gene regulation.

Nucleosomes are important for gene regulation because their arrangement on the genome can control which proteins bind to DNA. Currently, few human nucleosomes are thought to be consistently positioned across cells; however, this has been difficult to assess due to the limited resolution of existing data. We performed paired-end sequencing of micrococcal nuclease-digested chromatin (MNase-seq) from seven lymphoblastoid cell lines and mapped over 3.6 billion MNase-seq fragments to the human genome to create the highest-resolution map of nucleosome occupancy to date in a human cell type. In contrast to previous results, we find that most nucleosomes have more consistent positioning than expected by chance and a substantial fraction (8.7%) of nucleosomes have moderate to strong positioning. In aggregate, nucleosome sequences have 10 bp periodic patterns in dinucleotide frequency and DNase I sensitivity; and, across cells, nucleosomes frequently have translational offsets that are multiples of 10 bp. We estimate that almost half of the genome contains regularly spaced arrays of nucleosomes, which are enriched in active chromatin domains. Single nucleotide polymorphisms that reduce DNase I sensitivity can disrupt the phasing of nucleosome arrays, which indicates that they often result from positioning against a barrier formed by other proteins. However, nucleosome arrays can also be created by DNA sequence alone. The most striking example is an array of over 400 nucleosomes on chromosome 12 that is created by tandem repetition of sequences with strong positioning properties. In summary, a large fraction of nucleosomes are consistently positioned--in some regions because they adopt favored sequence positions, and in other regions because they are forced into specific arrangements by chromatin remodeling or DNA binding proteins.

Recent gene expression QTL (eQTL) mapping studies have provided considerable insight into the genetic basis for inter-individual regulatory variation. However, a limitation of all eQTL studies to date, which have used measurements of steady-state gene expression levels, is the inability to directly distinguish between variation in transcription and decay rates. To address this gap, we performed a genome-wide study of variation in gene-specific mRNA decay rates across individuals. Using a time-course study design, we estimated mRNA decay rates for over 16,000 genes in 70 Yoruban HapMap lymphoblastoid cell lines (LCLs), for which extensive genotyping data are available. Considering mRNA decay rates across genes, we found that: (i) as expected, highly expressed genes are generally associated with lower mRNA decay rates, (ii) genes with rapid mRNA decay rates are enriched with putative binding sites for miRNA and RNA binding proteins, and (iii) genes with similar functional roles tend to exhibit correlated rates of mRNA decay. Focusing on variation in mRNA decay across individuals, we estimate that steady-state expression levels are significantly correlated with variation in decay rates in 10% of genes. Somewhat counter-intuitively, for about half of these genes, higher expression is associated with faster decay rates, possibly due to a coupling of mRNA decay with transcriptional processes in genes involved in rapid cellular responses. Finally, we used these data to map genetic variation that is specifically associated with variation in mRNA decay rates across individuals. We found 195 such loci, which we named RNA decay quantitative trait loci ("rdQTLs"). All the observed rdQTLs are located near the regulated genes and therefore are assumed to act in cis. By analyzing our data within the context of known steady-state eQTLs, we estimate that a substantial fraction of eQTLs are associated with inter-individual variation in mRNA decay rates.

The modification of DNA by methylation is an important epigenetic mechanism that affects the spatial and temporal regulation of gene expression. Methylation patterns have been described in many contexts within and across a range of species. However, the extent to which changes in methylation might underlie inter-species differences in gene regulation, in particular between humans and other primates, has not yet been studied. To this end, we studied DNA methylation patterns in livers, hearts, and kidneys from multiple humans and chimpanzees, using tissue samples for which genome-wide gene expression data were also available. Using the multi-species gene expression and methylation data for 7,723 genes, we were able to study the role of promoter DNA methylation in the evolution of gene regulation across tissues and species. We found that inter-tissue methylation patterns are often conserved between humans and chimpanzees. However, we also found a large number of gene expression differences between species that might be explained, at least in part, by corresponding differences in methylation levels. In particular, we estimate that, in the tissues we studied, inter-species differences in promoter methylation might underlie as much as 12%-18% of differences in gene expression levels between humans and chimpanzees.

Humans respond differently than other primates to a large number of infections. Differences in susceptibility to infectious agents between humans and other primates are probably due to inter-species differences in immune response to infection. Consistent with that notion, genes involved in immunity-related processes are strongly enriched among recent targets of positive selection in primates, suggesting that immune responses evolve rapidly, yet providing only indirect evidence for possible inter-species functional differences. To directly compare immune responses among primates, we stimulated primary monocytes from humans, chimpanzees, and rhesus macaques with lipopolysaccharide (LPS) and studied the ensuing time-course regulatory responses. We find that, while the universal Toll-like receptor response is mostly conserved across primates, the regulatory response associated with viral infections is often lineage-specific, probably reflecting rapid host-virus mutual adaptation cycles. Additionally, human-specific immune responses are enriched for genes involved in apoptosis, as well as for genes associated with cancer and with susceptibility to infectious diseases or immune-related disorders. Finally, we find that chimpanzee-specific immune signaling pathways are enriched for HIV-interacting genes. Put together, our observations lend strong support to the notion that lineage-specific immune responses may help explain known inter-species differences in susceptibility to infectious diseases.

While the majority of multiexonic human genes show some evidence of alternative splicing, it is unclear what fraction of observed splice forms is functionally relevant. In this study, we examine the extent of alternative splicing in human cells using deep RNA sequencing and de novo identification of splice junctions. We demonstrate the existence of a large class of low abundance isoforms, encompassing approximately 150,000 previously unannotated splice junctions in our data. Newly-identified splice sites show little evidence of evolutionary conservation, suggesting that the majority are due to erroneous splice site choice. We show that sequence motifs involved in the recognition of exons are enriched in the vicinity of unconserved splice sites. We estimate that the average intron has a splicing error rate of approximately 0.7% and show that introns in highly expressed genes are spliced more accurately, likely due to their shorter length. These results implicate noisy splicing as an important property of genome evolution.

Variation in genes underlying host immunity can lead to marked differences in susceptibility to HIV infection among humans. Despite heavy reliance on non-human primates as models for HIV/AIDS, little is known about which host factors are shared and which are unique to a given primate lineage. Here, we investigate whether copy number variation (CNV) at CCL3-like genes (CCL3L), a key genetic host factor for HIV/AIDS susceptibility and cell-mediated immune response in humans, is also a determinant of time until onset of simian-AIDS in rhesus macaques. Using a retrospective study of 57 rhesus macaques experimentally infected with SIVmac, we find that CCL3L CNV explains approximately 18% of the variance in time to simian-AIDS (p

Regulatory changes have long been hypothesized to play an important role in primate evolution. To identify adaptive regulatory changes in humans, we performed a genome-wide survey for genes in which regulation has likely evolved under natural selection. To do so, we used a multi-species microarray to measure gene expression levels in livers, kidneys, and hearts from six humans, chimpanzees, and rhesus macaques. This comparative gene expression data allowed us to identify a large number of genes, as well as specific pathways, whose inter-species expression profiles are consistent with the action of stabilizing or directional selection on gene regulation. Among the latter set, we found an enrichment of genes involved in metabolic pathways, consistent with the hypothesis that shifts in diet underlie many regulatory adaptations in humans. In addition, we found evidence for tissue-specific selection pressures, as well as lower rates of protein evolution for genes in which regulation evolves under natural selection. These observations are consistent with the notion that adaptive circumscribed changes in gene regulation have fewer deleterious pleiotropic effects compared with changes at the protein sequence level.

Recent studies of the HapMap lymphoblastoid cell lines have identified large numbers of quantitative trait loci for gene expression (eQTLs). Reanalyzing these data using a novel Bayesian hierarchical model, we were able to create a surprisingly high-resolution map of the typical locations of sites that affect mRNA levels in cis. Strikingly, we found a strong enrichment of eQTLs in the 250 bp just upstream of the transcription end site (TES), in addition to an enrichment around the transcription start site (TSS). Most eQTLs lie either within genes or close to genes; for example, we estimate that only 5% of eQTLs lie more than 20 kb upstream of the TSS. After controlling for position effects, SNPs in exons are approximately 2-fold more likely than SNPs in introns to be eQTLs. Our results suggest an important role for mRNA stability in determining steady-state mRNA levels, and highlight the potential of eQTL mapping as a high-resolution tool for studying the determinants of gene regulation.

The question of a potential biological sexual signature in the human brain is a heavily disputed subject. In order to provide further insight into this issue, we used an evolutionary approach to identify genes with sex differences in brain expression level among primates. We reasoned that expression patterns important to uphold key male and female characteristics may be conserved during evolution. We selected cortex for our studies because this specific brain region is responsible for many higher behavioral functions. We compared gene expression profiles in the occipital cortex of male and female humans (Homo sapiens, a great ape) and cynomolgus macaques (Macaca fascicularis, an old world monkey), two catarrhine species that show abundant morphological sexual dimorphism, as well as in common marmosets (Callithrix Jacchus, a new world monkey) which are relatively sexually monomorphic. We identified hundreds of genes with sex-biased expression patterns in humans and macaques, while fewer than ten were differentially expressed between the sexes in marmosets. In primates, a general rule is that many of the morphological and behavioral sexual dimorphisms seen in polygamous species, such as macaques, are typically less pronounced in monogamous species such as the marmosets. Our observations suggest that this correlation may also be reflected in the extent of sex-biased gene expression in the brain. We identified 85 genes with common sex-biased expression, in both human and macaque and 2 genes, X inactivation-specific transcript (XIST) and Heat shock factor binding protein 1 (HSBP1), that were consistently sex-biased in the female direction in human, macaque, and marmoset. These observations imply a conserved signature of sexual gene expression dimorphism in cortex of primates. Further, we found that the coding region of female-biased genes is more evolutionarily constrained compared to the coding region of both male-biased and non sex-biased brain expressed genes. We found genes with conserved sexual gene expression dimorphism in the occipital cortex of humans, cynomolgus macaques, and common marmosets. Genes within sexual expression profiles may underlie important functional differences between the sexes, with possible importance during primate evolution.

While many of the phenotypic differences between human and chimpanzee may result from changes in gene regulation, only a handful of functionally important regulatory differences are currently known. As a first step towards identifying transcriptional pathways that have been remodeled in the human lineage, we focused on a transcription factor, FOXO1a, which we had previously found to be up-regulated in the human liver compared to that of three other primate species. We concentrated on this gene because of its known role in the regulation of metabolism and in longevity.Using a combination of expression profiling following siRNA knockdown and chromatin immunoprecipitation in a human liver cell line, we identified eight novel direct transcriptional targets of FOXO1a. This set includes the gene for thioredoxin-interacting protein (TXNIP), the expression of which is directly repressed by FOXO1a. The thioredoxin-interacting protein is known to inhibit the reducing activity of thioredoxin (TRX), thereby hindering the cellular response to oxidative stress and affecting life span.Our results provide an explanation for the repeated observations that differences in the regulation of FOXO transcription factors affect longevity. Moreover, we found that TXNIP is down-regulated in human compared to chimpanzee, consistent with the up-regulation of its direct repressor FOXO1a in humans, and with differences in longevity between the two species.

Olfactory receptors (ORs) are the largest gene family in mammalian genomes. Since nearly all OR genes are orphan receptors, inference of functional similarity or differences between odorant receptors typically relies on sequence comparisons. Based on the alignment of entire coding region sequence, OR genes are classified into families and subfamilies, a classification that is believed to be a proxy for OR gene functional variability. However, the assumption that overall protein sequence diversity is a good proxy for functional properties is untested.Here, we propose an alternative sequence-based approach to infer the similarities and differences in OR binding capacity. Our approach is based on similarities and differences in the predicted binding pockets of OR genes, rather than on the entire OR coding region.Interestingly, our approach yields markedly different results compared to the analysis based on the entire OR coding-regions. While neither approach can be tested at this time, the discrepancy between the two calls into question the assumption that the current classification reliably reflects OR gene functional variability.

Recent experiments using sperm typing have demonstrated that, in several regions of the human genome, recombination does not occur uniformly but instead is concentrated in "hotspots" of 1-2 kb. Moreover, the crossover asymmetry observed in a subset of these has led to the suggestion that hotspots may be short-lived on an evolutionary time scale. To test this possibility, we focused on a region known to contain a recombination hotspot in humans, TAP2, and asked whether chimpanzees, the closest living evolutionary relatives of humans, harbor a hotspot in a similar location. Specifically, we used a new statistical approach to estimate recombination rate variation from patterns of linkage disequilibrium in a sample of 24 western chimpanzees (Pan troglodytes verus). This method has been shown to produce reliable results on simulated data and on human data from the TAP2 region. Strikingly, however, it finds very little support for recombination rate variation at TAP2 in the western chimpanzee data. Moreover, simulations suggest that there should be stronger support if there were a hotspot similar to the one characterized in humans. Thus, it appears that the human TAP2 recombination hotspot is not shared by western chimpanzees. These findings demonstrate that fine-scale recombination rates can change between very closely related species and raise the possibility that rates differ among human populations, with important implications for linkage-disequilibrium based association studies.

Olfactory receptor (OR) genes constitute the molecular basis for the sense of smell and are encoded by the largest gene family in mammalian genomes. Previous studies suggested that the proportion of pseudogenes in the OR gene family is significantly larger in humans than in other apes and significantly larger in apes than in the mouse. To investigate the process of degeneration of the olfactory repertoire in primates, we estimated the proportion of OR pseudogenes in 19 primate species by surveying randomly chosen subsets of 100 OR genes from each species. We find that apes, Old World monkeys and one New World monkey, the howler monkey, have a significantly higher proportion of OR pseudogenes than do other New World monkeys or the lemur (a prosimian). Strikingly, the howler monkey is also the only New World monkey to possess full trichromatic vision, along with Old World monkeys and apes. Our findings suggest that the deterioration of the olfactory repertoire occurred concomitant with the acquisition of full trichromatic color vision in primates.

Background: Both genetic and environmental factors appear to contribute to joint health and disease. For example, pathological levels of biomechanical stress on joints play a notable role in initiation and progression of osteoarthritis (OA), a common chronic degenerative joint disease affecting articular cartilage and underlying bone. Population-level gene expression studies of cartilage cells experiencing biomechanical stress may uncover gene-by-environment interactions relevant to human joint health. Methods: To build a foundation for population-level gene expression studies in cartilage, we applied differentiation protocols to develop an in vitro system of chondrogenic cell lines (iPSC-chondrocytes). We characterized gene regulatory responses of three human iPSC-chondrocyte lines to cyclic tensile strain treatment. We measured the contribution of biological and technical factors to gene expression variation in this system. Results: We identified patterns of gene regulation that differ between strain-treated and control iPSC-chondrocytes. Differentially expressed genes between strain and control conditions are enriched for gene sets relevant to joint health and OA. Furthermore, even in this small sample, we found several genes that exhibit inter-individual expression differences in response to mechanical strain, including genes previously implicated in OA. Conclusions: Expanding this system to include iPSC-chondrocytes from a larger number of individuals will allow us to characterize and better understand gene-by-environment interactions related to joint health.