Impact of regulatory variation across human iPSCs and differentiated cells

Addressing variability in iPSC-derived models of human disease: guidelines to promote reproducibility

Induced pluripotent stem cell (iPSC) technologies have provided in vitro models of inaccessible human cell types, yielding new insights into disease mechanisms especially for neurological disorders. However, without due consideration, the thousands of new human iPSC lines generated in the past decade will inevitably affect the reproducibility of iPSC-based experiments. Differences between donor individuals, genetic stability and experimental variability contribute to iPSC model variation by impacting differentiation potency, cellular heterogeneity, morphology, and transcript and protein abundance. Such effects will confound reproducible disease modelling in the absence of appropriate strategies. In this Review, we explore the causes and effects of iPSC heterogeneity, and propose approaches to detect and account for experimental variation between studies, or even exploit it for deeper biological insight.

Association of Human iPSC Gene Signatures and X Chromosome Dosage with Two Distinct Cardiac Differentiation Trajectories

Despite the importance of understanding how variability across induced pluripotent stem cell (iPSC) lines due to non-genetic factors (clone and passage) influences their differentiation outcome, large-scale studies capable of addressing this question have not yet been conducted. Here, we differentiated 191 iPSC lines to generate iPSC-derived cardiovascular progenitor cells (iPSC-CVPCs). We observed cellular heterogeneity across the iPSC-CVPC samples due to varying fractions of two cell types: cardiomyocytes (CMs) and epicardium-derived cells (EPDCs). Comparing the transcriptomes of CM-fated and EPDC-fated iPSCs, we discovered that 91 signature genes and X chromosome dosage differences are associated with these two distinct cardiac developmental trajectories. In an independent set of 39 iPSCs differentiated into CMs, we confirmed that sex and transcriptional differences affect cardiac-fate outcome. Our study provides novel insights into how iPSC transcriptional and X chromosome gene dosage differences influence their response to differentiation stimuli and, hence, cardiac cell fate.

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Cellular heterogeneity across iPSC-CVPCs due to varying fractions of CMs and EPDCs

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iPSC non-genetic factors (clone and passage) associated with cardiac cell fate

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Expression levels of signature genes in iPSCs associated with cardiac lineage fate

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iPSC donor sex plays a role in cardiac lineage fate

Landscape of stimulation-responsive chromatin across diverse human immune cells

A hallmark of the immune system is the interplay among specialized cell types transitioning between resting and stimulated states. The gene regulatory landscape of this dynamic system has not been fully characterized in human cells. Here, we collected ATAC-seq and RNA-seq data under resting and stimulated conditions for up to 32 immune cell populations. Stimulation caused widespread chromatin remodeling, including response elements shared between stimulated B and T cells. Furthermore, several autoimmune traits showed significant heritability in stimulation-responsive elements from distinct cell types, highlighting the importance of these cell states in autoimmunity. Use of allele-specific read-mapping identified variants that alter chromatin accessibility in particular conditions, allowing us to observe evidence of function for a candidate causal variant that is undetected by existing large-scale studies in resting cells. Our results provide a resource of chromatin dynamics and highlight the need for characterization of effects of genetic variation in stimulated cells.

Analysis of gene expression and open chromatin regions in up to 32 immune cell populations under resting and stimulated conditions identifies widespread chromatin remodeling and shared response elements between stimulated B and T cells.

Allele-specific NKX2-5 binding underlies multiple genetic associations with human electrocardiographic traits

The cardiac transcription factor (TF) gene NKX2-5 has been associated with electrocardiographic (EKG) traits through genome-wide association studies (GWASs), but the extent to which differential binding of NKX2-5 at common regulatory variants contributes to these traits has not yet been studied. We analyzed transcriptomic and epigenomic data from induced pluripotent stem cell-derived cardiomyocytes from seven related individuals, and identified ~2,000 single-nucleotide variants associated with allele-specific effects (ASE-SNVs) on NKX2-5 binding. NKX2-5 ASE-SNVs were enriched for altered TF motifs, for heart-specific expression quantitative trait loci and for EKG GWAS signals. Using fine-mapping combined with epigenomic data from induced pluripotent stem cell-derived cardiomyocytes, we prioritized candidate causal variants for EKG traits, many of which were NKX2-5 ASE-SNVs. Experimentally characterizing two NKX2-5 ASE-SNVs (rs3807989 and rs590041) showed that they modulate the expression of target genes via differential protein binding in cardiac cells, indicating that they are functional variants underlying EKG GWAS signals. Our results show that differential NKX2-5 binding at numerous regulatory variants across the genome contributes to EKG phenotypes.

Tbx20 Is Required in Mid-Gestation Cardiomyocytes and Plays a Central Role in Atrial Development

Supplemental Digital Content is available in the text.

Rationale:

Mutations in the transcription factor TBX20 (T-box 20) are associated with congenital heart disease. Germline ablation of Tbx20 results in abnormal heart development and embryonic lethality by embryonic day 9.5. Because Tbx20 is expressed in multiple cell lineages required for myocardial development, including pharyngeal endoderm, cardiogenic mesoderm, endocardium, and myocardium, the cell type–specific requirement for TBX20 in early myocardial development remains to be explored.

Objective:

Here, we investigated roles of TBX20 in midgestation cardiomyocytes for heart development.

Methods and Results:

Ablation of Tbx20 from developing cardiomyocytes using a doxycycline inducible cTnTCre transgene led to embryonic lethality. The circumference of developing ventricular and atrial chambers, and in particular that of prospective left atrium, was significantly reduced in Tbx20 conditional knockout mutants. Cell cycle analysis demonstrated reduced proliferation of Tbx20 mutant cardiomyocytes and their arrest at the G1-S phase transition. Genome-wide transcriptome analysis of mutant cardiomyocytes revealed differential expression of multiple genes critical for cell cycle regulation. Moreover, atrial and ventricular gene programs seemed to be aberrantly regulated. Putative direct TBX20 targets were identified using TBX20 ChIP-Seq (chromatin immunoprecipitation with high throughput sequencing) from embryonic heart and included key cell cycle genes and atrial and ventricular specific genes. Notably, TBX20 bound a conserved enhancer for a gene key to atrial development and identity, COUP-TFII/Nr2f2 (chicken ovalbumin upstream promoter transcription factor 2/nuclear receptor subfamily 2, group F, member 2). This enhancer interacted with the NR2F2 promoter in human cardiomyocytes and conferred atrial specific gene expression in a transgenic mouse in a TBX20-dependent manner.

Conclusions:

Myocardial TBX20 directly regulates a subset of genes required for fetal cardiomyocyte proliferation, including those required for the G1-S transition. TBX20 also directly downregulates progenitor-specific genes and, in addition to regulating genes that specify chamber versus nonchamber myocardium, directly activates genes required for establishment or maintenance of atrial and ventricular identity. TBX20 plays a previously unappreciated key role in atrial development through direct regulation of an evolutionarily conserved COUPT-FII enhancer.

Single-cell RNA sequencing of a European and an African lymphoblastoid cell line

In biomedical research, lymphoblastoid cell lines (LCLs), often established by in vitro infection of resting B cells with Epstein-Barr virus, are commonly used as surrogates for peripheral blood lymphocytes. Genomic and transcriptomic information on LCLs has been used to study the impact of genetic variation on gene expression in humans. Here we present single-cell RNA sequencing (scRNA-seq) data on GM12878 and GM18502—two LCLs derived from the blood of female donors of European and African ancestry, respectively. Cells from three samples (the two LCLs and a 1:1 mixture of the two) were prepared separately using a 10x Genomics Chromium Controller and deeply sequenced. The final dataset contained 7,045 cells from GM12878, 5,189 from GM18502, and 5,820 from the mixture, offering valuable information on single-cell gene expression in highly homogenous cell populations. This dataset is a suitable reference for population differentiation in gene expression at the single-cell level. Data from the mixture provide additional valuable information facilitating the development of statistical methods for data normalization and batch effect correction.

Design Type(s)	transcription profiling design • strain comparison design
Measurement Type(s)	transcription profiling assay
Technology Type(s)	RNA sequencing
Factor Type(s)	ancestry status • sex
Sample Characteristic(s)	GM12878 cell • GM18502 cell • immortal human peripheral vein-derived B cell line cell

Machine-accessible metadata file describing the reported data (ISA-Tab format)

Dynamic genetic regulation of gene expression during cellular differentiation

Genetic regulation of gene expression is dynamic, as transcription can change during cell differentiation and across cell types. We mapped expression quantitative trait loci (eQTLs) throughout differentiation to elucidate the dynamics of genetic effects on cell type-specific gene expression. We generated time-series RNA sequencing data, capturing 16 time points during the differentiation of induced pluripotent stem cells to cardiomyocytes, in 19 human cell lines. We identified hundreds of dynamic eQTLs that change over time, with enrichment in enhancers of relevant cell types. We also found nonlinear dynamic eQTLs, which affect only intermediate stages of differentiation and cannot be found by using data from mature tissues. These fleeting genetic associations with gene regulation may explain some of the components of complex traits and disease. We highlight one example of a nonlinear eQTL that is associated with body mass index.

Discovery and characterization of variance QTLs in human induced pluripotent stem cells

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.

Common genetic variation can alter the level of average gene expression in human tissues, and through changes in gene expression have downstream consequences on cell function, human development, and human disease. However, human tissues are composed of many cells, each with its own level of gene expression. With advances in single cell sequencing technologies, we can now go beyond simply measuring the average level of gene expression in a tissue sample and directly measure cell-to-cell variance in gene expression. We hypothesized that genetic variation could also alter gene expression variance, potentially revealing new insights into human development and disease. To test this hypothesis, we used single cell RNA sequencing to directly measure gene expression variance in multiple individuals, and then associated the gene expression variance with genetic variation in those same individuals. Our results suggest that effects on gene expression variance are smaller than effects on mean expression, relative to how much the phenotypes vary between individuals, and will require much larger studies than previously thought to detect.

A generally conserved response to hypoxia in iPSC-derived cardiomyocytes from humans and chimpanzees

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.

New considerations for hiPSC-based models of neuropsychiatric disorders

The development of human-induced pluripotent stem cells (hiPSCs) has made possible patient-specific modeling across the spectrum of human disease. Here, we discuss recent advances in psychiatric genomics and post-mortem studies that provide critical insights concerning cell-type composition and sample size that should be considered when designing hiPSC-based studies of complex genetic disease. We review recent hiPSC-based models of SZ, in light of our new understanding of critical power limitations in the design of hiPSC-based studies of complex genetic disorders. Three possible solutions are a movement towards genetically stratified cohorts of rare variant patients, application of CRISPR technologies to engineer isogenic neural cells to study the impact of common variants, and integration of advanced genetics and hiPSC-based datasets in future studies. Overall, we emphasize that to advance the reproducibility and relevance of hiPSC-based studies, stem cell biologists must contemplate statistical and biological considerations that are already well accepted in the field of genetics. We conclude with a discussion of the hypothesis of biological convergence of disease-through molecular, cellular, circuit, and patient level phenotypes-and how this might emerge through hiPSC-based studies.

Childhood-Onset Schizophrenia: Insights from Induced Pluripotent Stem Cells

Childhood-onset schizophrenia (COS) is a rare psychiatric disorder characterized by earlier onset, more severe course, and poorer outcome relative to adult-onset schizophrenia (AOS). Even though, clinical, neuroimaging, and genetic studies support that COS is continuous to AOS. Early neurodevelopmental deviations in COS are thought to be significantly mediated through poorly understood genetic risk factors that may also predispose to long-term outcome. In this review, we discuss findings from induced pluripotent stem cells (iPSCs) that allow the generation of disease-relevant cell types from early brain development. Because iPSCs capture each donor's genotype, case/control studies can uncover molecular and cellular underpinnings of COS. Indeed, recent studies identified alterations in neural progenitor and neuronal cell function, comprising dendrites, synapses, electrical activity, glutamate signaling, and miRNA expression. Interestingly, transcriptional signatures of iPSC-derived cells from patients with COS showed concordance with postmortem brain samples from SCZ, indicating that changes in vitro may recapitulate changes from the diseased brain. Considering this progress, we discuss also current caveats from the field of iPSC-based disease modeling and how to proceed from basic studies to improved diagnosis and treatment of COS.

Type 2 Diabetes-Associated Genetic Variants Regulate Chromatin Accessibility in Human Islets

Type 2 diabetes (T2D) is a complex disorder in which both genetic and environmental risk factors contribute to islet dysfunction and failure. Genome-wide association studies (GWAS) have linked single nucleotide polymorphisms (SNPs), most of which are noncoding, in >200 loci to islet dysfunction and T2D. Identification of the putative causal variants and their target genes and whether they lead to gain or loss of function remains challenging. Here, we profiled chromatin accessibility in pancreatic islet samples from 19 genotyped individuals and identified 2,949 SNPs associated with in vivo cis-regulatory element use (i.e., chromatin accessibility quantitative trait loci [caQTL]). Among the caQTLs tested (n = 13) using luciferase reporter assays in MIN6 β-cells, more than half exhibited effects on enhancer activity that were consistent with in vivo chromatin accessibility changes. Importantly, islet caQTL analysis nominated putative causal SNPs in 13 T2D-associated GWAS loci, linking 7 and 6 T2D risk alleles, respectively, to gain or loss of in vivo chromatin accessibility. By investigating the effect of genetic variants on chromatin accessibility in islets, this study is an important step forward in translating T2D-associated GWAS SNP into functional molecular consequences.

A Comparative Assessment of Human and Chimpanzee iPSC-derived Cardiomyocytes with Primary Heart Tissues

Comparative genomic studies in primates have the potential to reveal the genetic and mechanistic basis for human specific traits. These studies may also help us better understand inter-species phenotypic differences that are clinically relevant. Unfortunately, the obvious limitation on sample collection and experimentation in humans and non-human apes severely restrict our ability to perform dynamic comparative studies in primates. Induced pluripotent stem cells (iPSCs), and their corresponding differentiated cells, may provide a suitable alternative system for dynamic comparative studies. Yet, to effectively use iPSCs and differentiated cells for comparative studies, one must characterize the extent to which these systems faithfully represent biological processes in primary tissues. To do so, we compared gene expression data from primary adult heart tissue and iPSC-derived cardiomyocytes from multiple human and chimpanzee individuals. We determined that gene expression in cultured cardiomyocytes from both human and chimpanzee is most similar to that of adult hearts compared to other adult tissues. Using a comparative framework, we found that 50% of gene regulatory differences between human and chimpanzee hearts are also observed between species in cultured cardiomyocytes; conversely, inter-species regulatory differences seen in cardiomyocytes are found significantly more often in hearts than in other primary tissues. Our work provides a detailed description of the utility and limitation of differentiated cardiomyocytes as a system for comparative functional genomic studies in primates.

A comparative study of endoderm differentiation in humans and chimpanzees

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.

Tracing Early Neurodevelopment in Schizophrenia with Induced Pluripotent Stem Cells

Schizophrenia (SCZ) is a devastating mental disorder that is characterized by distortions in thinking, perception, emotion, language, sense of self, and behavior. Epidemiological evidence suggests that subtle perturbations in early neurodevelopment increase later susceptibility for disease, which typically manifests in adolescence to early adulthood. Early perturbations are thought to be significantly mediated through incompletely understood genetic risk factors. The advent of induced pluripotent stem cell (iPSC) technology allows for the in vitro analysis of disease-relevant neuronal cell types from the early stages of human brain development. Since iPSCs capture each donor's genotype, comparison between neuronal cells derived from healthy and diseased individuals can provide important insights into the molecular and cellular basis of SCZ. In this review, we discuss results from an increasing number of iPSC-based SCZ/control studies that highlight alterations in neuronal differentiation, maturation, and neurotransmission in addition to perturbed mitochondrial function and micro-RNA expression. In light of this remarkable progress, we consider also ongoing challenges from the field of iPSC-based disease modeling that call for further improvements on the generation and design of patient-specific iPSC studies to ultimately progress from basic studies on SCZ to tailored treatments.

A promoter interaction map for cardiovascular disease genetics

Over 500 genetic loci have been associated with risk of cardiovascular diseases (CVDs); however, most loci are located in gene-distal non-coding regions and their target genes are not known. Here, we generated high-resolution promoter capture Hi-C (PCHi-C) maps in human induced pluripotent stem cells (iPSCs) and iPSC-derived cardiomyocytes (CMs) to provide a resource for identifying and prioritizing the functional targets of CVD associations. We validate these maps by demonstrating that promoters preferentially contact distal sequences enriched for tissue-specific transcription factor motifs and are enriched for chromatin marks that correlate with dynamic changes in gene expression. Using the CM PCHi-C map, we linked 1999 CVD-associated SNPs to 347 target genes. Remarkably, more than 90% of SNP-target gene interactions did not involve the nearest gene, while 40% of SNPs interacted with at least two genes, demonstrating the importance of considering long-range chromatin interactions when interpreting functional targets of disease loci.

An atlas of chromatin accessibility in the adult human brain

Most common genetic risk variants associated with neuropsychiatric disease are noncoding and are thought to exert their effects by disrupting the function of cis regulatory elements (CREs), including promoters and enhancers. Within each cell, chromatin is arranged in specific patterns to expose the repertoire of CREs required for optimal spatiotemporal regulation of gene expression. To further understand the complex mechanisms that modulate transcription in the brain, we used frozen postmortem samples to generate the largest human brain and cell-type–specific open chromatin data set to date. Using the Assay for Transposase Accessible Chromatin followed by sequencing (ATAC-seq), we created maps of chromatin accessibility in two cell types (neurons and non-neurons) across 14 distinct brain regions of five individuals. Chromatin structure varies markedly by cell type, with neuronal chromatin displaying higher regional variability than that of non-neurons. Among our findings is an open chromatin region (OCR) specific to neurons of the striatum. When placed in the mouse, a human sequence derived from this OCR recapitulates the cell type and regional expression pattern predicted by our ATAC-seq experiments. Furthermore, differentially accessible chromatin overlaps with the genetic architecture of neuropsychiatric traits and identifies differences in molecular pathways and biological functions. By leveraging transcription factor binding analysis, we identify protein-coding and long noncoding RNAs (lncRNAs) with cell-type and brain region specificity. Our data provide a valuable resource to the research community and we provide this human brain chromatin accessibility atlas as an online database “Brain Open Chromatin Atlas (BOCA)” to facilitate interpretation.

Determining the genetic basis of anthracycline-cardiotoxicity by molecular response QTL mapping in induced cardiomyocytes

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.

A Mixed-Effects Model for Powerful Association Tests in Integrative Functional Genomics

Genome-wide association studies (GWASs) have successfully identified thousands of genetic variants for many complex diseases; however, these variants explain only a small fraction of the heritability. Recently, genetic association studies that leverage external transcriptome data have received much attention and shown promise for discovering novel variants. One such approach, PrediXcan, is to use predicted gene expression through genetic regulation. However, there are limitations in this approach. The predicted gene expression may be biased, resulting from regularized regression applied to moderately sample-sized reference studies. Further, some variants can individually influence disease risk through alternative functional mechanisms besides expression. Thus, testing only the association of predicted gene expression as proposed in PrediXcan will potentially lose power. To tackle these challenges, we consider a unified mixed effects model that formulates the association of intermediate phenotypes such as imputed gene expression through fixed effects, while allowing residual effects of individual variants to be random. We consider a set-based score testing framework, MiST (mixed effects score test), and propose two data-driven combination approaches to jointly test for the fixed and random effects. We establish the asymptotic distributions, which enable rapid calculation of p values for genome-wide analyses, and provide p values for fixed and random effects separately to enhance interpretability over GWASs. Extensive simulations demonstrate that our approaches are more powerful than existing ones. We apply our approach to a large-scale GWAS of colorectal cancer and identify two genes, POU5F1B and ATF1, which would have otherwise been missed by PrediXcan, after adjusting for all known loci.

Inferring the effect of genomic variation in the new era of genomics

Accurate and detailed understanding of the effects of variants in the coding and noncoding regions of the genome is the next big challenge in the new genomic era of personalized medicine, especially to tackle newer findings of genetic and phenotypic heterogeneity of diseases. This is necessary to resolve the gene-variant-disease relationship, the pathogenic variant spectrum of genes, pathogenic variants with variable clinical consequences, and multiloci diseases. In turn, this will facilitate patient recruitment for relevant clinical trials. In this review, we describe the trends in research at the intersection of basic and clinical genomics aiming to (a) overcome molecular diagnostic challenges and increase the clinical utility of next-generation sequencing (NGS) platforms, (b) elucidate variants associated with disease, (c) determine overall genomic complexity including epistasis, complex inheritance patterns such as "synergistic heterozygosity," digenic/multigenic inheritance, modifier effect, and rare variant load. We describe the newly emerging field of integrated functional genomics, in vivo or in vitro large-scale functional approaches, statistical bioinformatics algorithms that support NGS genomics data to interpret variants for timely clinical diagnostics and disease management. Thus, facilitating the discovery of new therapeutic or biomarker options, and their roles in the future of personalized medicine.

Silencing of transposable elements may not be a major driver of regulatory evolution in primate iPSCs

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.

From the Psychiatrist's Couch to Induced Pluripotent Stem Cells: Bipolar Disease in a Dish

Bipolar disease (BD) is one of the major public health burdens worldwide and more people are affected every year. Comprehensive genetic studies have associated thousands of single nucleotide polymorphisms (SNPs) with BD risk; yet, very little is known about their functional roles. Induced pluripotent stem cells (iPSCs) are powerful tools for investigating the relationship between genotype and phenotype in disease-relevant tissues and cell types. Neural cells generated from BD-specific iPSCs are thought to capture associated genetic risk factors, known and unknown, and to allow the analysis of their effects on cellular and molecular phenotypes. Interestingly, an increasing number of studies on BD-derived iPSCs report distinct alterations in neural patterning, postmitotic calcium signaling, and neuronal excitability. Importantly, these alterations are partly normalized by lithium, a first line treatment in BD. In light of these exciting findings, we discuss current challenges to the field of iPSC-based disease modelling and future steps to be taken in order to fully exploit the potential of this approach for the investigation of BD and the development of new therapies.

Taming Human Genetic Variability: Transcriptomic Meta-Analysis Guides the Experimental Design and Interpretation of iPSC-Based Disease Modeling

Both the promises and pitfalls of the cell reprogramming research platform rest on human genetic variation, making the measurement of its impact one of the most urgent issues in the field. Harnessing large transcriptomics datasets of induced pluripotent stem cells (iPSC), we investigate the implications of this variability for iPSC-based disease modeling. In particular, we show that the widespread use of more than one clone per individual in combination with current analytical practices is detrimental to the robustness of the findings. We then proceed to identify methods to address this challenge and leverage multiple clones per individual. Finally, we evaluate the specificity and sensitivity of different sample sizes and experimental designs, presenting computational tools for power analysis. These findings and tools reframe the nature of replicates used in disease modeling and provide important resources for the design, analysis, and interpretation of iPSC-based studies.

Shared genetic effects on chromatin and gene expression indicate a role for enhancer priming in immune response

Regulatory variants are often context specific, modulating gene expression in a subset of possible cellular states. Although these genetic effects can play important roles in disease, the molecular mechanisms underlying context specificity are poorly understood. Here, we identified shared quantitative trait loci (QTLs) for chromatin accessibility and gene expression in human macrophages exposed to IFNγ, Salmonella and IFNγ plus Salmonella. We observed that ~60% of stimulus-specific expression QTLs with a detectable effect on chromatin altered the chromatin accessibility in naive cells, thus suggesting that they perturb enhancer priming. Such variants probably influence binding of cell-type-specific transcription factors, such as PU.1, which can then indirectly alter the binding of stimulus-specific transcription factors, such as NF-κB or STAT2. Thus, although chromatin accessibility assays are powerful for fine-mapping causal regulatory variants, detecting their downstream effects on gene expression will be challenging, requiring profiling of large numbers of stimulated cellular states and time points.

Computational biology: deep learning

Deep learning is the trendiest tool in a computational biologist's toolbox. This exciting class of methods, based on artificial neural networks, quickly became popular due to its competitive performance in prediction problems. In pioneering early work, applying simple network architectures to abundant data already provided gains over traditional counterparts in functional genomics, image analysis, and medical diagnostics. Now, ideas for constructing and training networks and even off-the-shelf models have been adapted from the rapidly developing machine learning subfield to improve performance in a range of computational biology tasks. Here, we review some of these advances in the last 2 years.

Large-Scale Profiling Reveals the Influence of Genetic Variation on Gene Expression in Human Induced Pluripotent Stem Cells

In this study, we used whole-genome sequencing and gene expression profiling of 215 human induced pluripotent stem cell (iPSC) lines from different donors to identify genetic variants associated with RNA expression for 5,746 genes. We were able to predict causal variants for these expression quantitative trait loci (eQTLs) that disrupt transcription factor binding and validated a subset of them experimentally. We also identified copy-number variant (CNV) eQTLs, including some that appear to affect gene expression by altering the copy number of intergenic regulatory regions. In addition, we were able to identify effects on gene expression of rare genic CNVs and regulatory single-nucleotide variants and found that reactivation of gene expression on the X chromosome depends on gene chromosomal position. Our work highlights the value of iPSCs for genetic association analyses and provides a unique resource for investigating the genetic regulation of gene expression in pluripotent cells.