Mapping the Genetic Landscape of Human Cells.

Seminal yeast studies have established the value of comprehensively mapping genetic interactions (GIs) for inferring gene function. Efforts in human cells using focused gene sets underscore the utility of this approach, but the feasibility of generating large-scale, diverse human GI maps remains unresolved. We developed a CRISPR interference platform for large-scale quantitative mapping of human GIs. We systematically perturbed 222,784 gene pairs in two cancer cell lines. The resultant maps cluster functionally related genes, assigning function to poorly characterized genes, including TMEM261, a new electron transport chain component. Individual GIs pinpoint unexpected relationships between pathways, exemplified by a specific cholesterol biosynthesis intermediate whose accumulation induces deoxynucleotide depletion, causing replicative DNA damage and a synthetic-lethal interaction with the ATR/9-1-1 DNA repair pathway. Our map provides a broad resource, establishes GI maps as a high-resolution tool for dissecting gene function, and serves as a blueprint for mapping the genetic landscape of human cells.

Genome-Wide Genetic Associations Prioritize Evaluation of Causal Mechanisms of Atherosclerotic Disease Risk.

OBJECTIVE: The goal of this review is to discuss the implementation of genome-wide association studies to identify causal mechanisms of vascular disease risk. APPROACH AND RESULTS: The history of genome-wide association studies is described, the use of imputation and the creation of consortia to conduct meta-analyses with sufficient power to arrive at consistent associated loci for vascular disease. Genomic methods are described that allow the identification of causal variants and causal genes and how they impact the disease process. The power of single-cell analyses to promote genome-wide association studies of causal gene function is described. CONCLUSIONS: Genome-wide association studies represent a paradigm shift in the study of cardiovascular disease, providing identification of genes, cellular phenotypes, and disease pathways that empower the future of targeted drug development.

An integrated approach to identify environmental modulators of genetic risk factors for complex traits.

Complex traits and diseases can be influenced by both genetics and environment. However, given the large number of environmental stimuli and power challenges for gene-by-environment testing, it remains a critical challenge to identify and prioritize specific disease-relevant environmental exposures. We propose a framework for leveraging signals from transcriptional responses to environmental perturbations to identify disease-relevant perturbations that can modulate genetic risk for complex traits and inform the functions of genetic variants associated with complex traits. We perturbed human skeletal-muscle-, fat-, and liver-relevant cell lines with 21 perturbations affecting insulin resistance, glucose homeostasis, and metabolic regulation in humans and identified thousands of environmentally responsive genes. By combining these data with GWASs from 31 distinct polygenic traits, we show that the heritability of multiple traits is enriched in regions surrounding genes responsive to specific perturbations and, further, that environmentally responsive genes are enriched for associations with specific diseases and phenotypes from the GWAS Catalog. Overall, we demonstrate the advantages of large-scale characterization of transcriptional changes in diversely stimulated and pathologically relevant cells to identify disease-relevant perturbations.

A single-cell CRISPRi platform for characterizing candidate genes relevant to metabolic disorders in human adipocytes.

CROP-Seq combines gene silencing using CRISPR interference with single-cell RNA sequencing. Here, we applied CROP-Seq to study adipogenesis and adipocyte biology. Human preadipocyte SGBS cell line expressing KRAB-dCas9 was transduced with a sgRNA library. Following selection, individual cells were captured using microfluidics at different timepoints during adipogenesis. Bioinformatic analysis of transcriptomic data was used to determine the knockdown effects, the dysregulated pathways, and to predict cellular phenotypes. Single-cell transcriptomes recapitulated adipogenesis states. For all targets, over 400 differentially expressed genes were identified at least at one timepoint. As a validation of our approach, the knockdown of PPARG and CEBPB (which encode key proadipogenic transcription factors) resulted in the inhibition of adipogenesis. Gene set enrichment analysis generated hypotheses regarding the molecular function of novel genes. MAFF knockdown led to downregulation of transcriptional response to proinflammatory cytokine TNF-α in preadipocytes and to decreased CXCL-16 and IL-6 secretion. TIPARP knockdown resulted in increased expression of adipogenesis markers. In summary, this powerful, hypothesis-free tool can identify novel regulators of adipogenesis, preadipocyte, and adipocyte function associated with metabolic disease.NEW & NOTEWORTHY Genomics efforts led to the identification of many genomic loci that are associated with metabolic traits, many of which are tied to adipose tissue function. However, determination of the causal genes, and their mechanism of action in metabolism, is a time-consuming process. Here, we use an approach to determine the transcriptional outcome of candidate gene knockdown for multiple genes at the same time in a human cell model of adipogenesis.

A functional genomic framework to elucidate novel causal non-alcoholic fatty liver disease genes.

Background & Aims: Non-alcoholic fatty liver disease (NAFLD) is the most prevalent chronic liver pathology in western countries, with serious public health consequences. Efforts to identify causal genes for NAFLD have been hampered by the relative paucity of human data from gold-standard magnetic resonance quantification of hepatic fat. To overcome insufficient sample size, genome-wide association studies using NAFLD surrogate phenotypes have been used, but only a small number of loci have been identified to date. In this study, we combined GWAS of NAFLD composite surrogate phenotypes with genetic colocalization studies followed by functional in vitro screens to identify bona fide causal genes for NAFLD. Approach & Results: We used the UK Biobank to explore the associations of our novel NAFLD score, and genetic colocalization to prioritize putative causal genes for in vitro validation. We created a functional genomic framework to study NAFLD genes in vitro using CRISPRi. Our data identify VKORC1, TNKS, LYPLAL1 and GPAM as regulators of lipid accumulation in hepatocytes and suggest the involvement of VKORC1 in the lipid storage related to the development of NAFLD. Conclusions: Complementary genetic and genomic approaches are useful for the identification of NAFLD genes. Our data supports VKORC1 as a bona fide NAFLD gene. We have established a functional genomic framework to study at scale putative novel NAFLD genes from human genetic association studies.

Single-cell transcriptome dataset of human and mouse in vitro adipogenesis models.

Adipogenesis is a process in which fat-specific progenitor cells (preadipocytes) differentiate into adipocytes that carry out the key metabolic functions of the adipose tissue, including glucose uptake, energy storage, and adipokine secretion. Several cell lines are routinely used to study the molecular regulation of adipogenesis, in particular the immortalized mouse 3T3-L1 line and the primary human Simpson-Golabi-Behmel syndrome (SGBS) line. However, the cell-to-cell variability of transcriptional changes prior to and during adipogenesis in these models is not well understood. Here, we present a single-cell RNA-Sequencing (scRNA-Seq) dataset collected before and during adipogenic differentiation of 3T3-L1 and SGBS cells. To minimize the effects of experimental variation, we mixed 3T3-L1 and SGBS cells and used computational analysis to demultiplex transcriptomes of mouse and human cells. In both models, adipogenesis results in the appearance of three cell clusters, corresponding to preadipocytes, early and mature adipocytes. These data provide a groundwork for comparative studies on these widely used in vitro models of human and mouse adipogenesis, and on cell-to-cell variability during this process.

Single-cell transcriptome dataset of human and mouse in vitro adipogenesis models.

Adipogenesis is a process in which fat-specific progenitor cells (preadipocytes) differentiate into adipocytes that carry out the key metabolic functions of the adipose tissue, including glucose uptake, energy storage, and adipokine secretion. Several cell lines are routinely used to study the molecular regulation of adipogenesis, in particular the immortalized mouse 3T3-L1 line and the primary human Simpson-Golabi-Behmel syndrome (SGBS) line. However, the cell-to-cell variability of transcriptional changes prior to and during adipogenesis in these models is not well understood. Here, we present a single-cell RNA-Sequencing (scRNA-Seq) dataset collected before and during adipogenic differentiation of 3T3-L1 and SGBS cells. To minimize the effects of experimental variation, we mixed 3T3-L1 and SGBS cells and used computational analysis to demultiplex transcriptomes of mouse and human cells. In both models, adipogenesis results in the appearance of three cell clusters, corresponding to preadipocytes, early and mature adipocytes. These data provide a groundwork for comparative studies on human and mouse adipogenesis, as well as on cell-to-cell variability in gene expression during this process.

Analysis of microRNA knockouts in mice.

MicroRNAs (miRNAs) are small noncoding RNAs that act as potent regulators of gene expression. The discovery of miRNAs with specific temporal and spatial expression patterns revealed a hidden layer of post-transcriptional gene regulation. Furthermore, differential expression of miRNAs during disease progression identified miRNAs as relevant candidate genes in human pathologies. Currently the exact roles of miRNAs in human development and disease progression remain largely unknown. There have been recent efforts to study the loss of these genes in vivo and this review will discuss published miRNA knockout mouse models, highlighting their potential mechanisms of action in vivo.

G protein-coupled receptor 151 regulates glucose metabolism and hepatic gluconeogenesis.

Human genetics has been instrumental in identification of genetic variants linked to type 2 diabetes. Recently a rare, putative loss-of-function mutation in the orphan G-protein coupled receptor 151 (GPR151) was found to be associated with lower odds ratio for type 2 diabetes, but the mechanism behind this association has remained elusive. Here we show that Gpr151 is a fasting- and glucagon-responsive hepatic gene which regulates hepatic gluconeogenesis. Gpr151 ablation in mice leads to suppression of hepatic gluconeogenesis genes and reduced hepatic glucose production in response to pyruvate. Importantly, the restoration of hepatic Gpr151 levels in the Gpr151 knockout mice reverses the reduced hepatic glucose production. In this work, we establish a previously unknown role of Gpr151 in the liver that provides an explanation to the lowered type 2 diabetes risk in individuals with nonsynonymous mutations in GPR151.

Components of genetic associations across 2,138 phenotypes in the UK Biobank highlight adipocyte biology.

Population-based biobanks with genomic and dense phenotype data provide opportunities for generating effective therapeutic hypotheses and understanding the genomic role in disease predisposition. To characterize latent components of genetic associations, we apply truncated singular value decomposition (DeGAs) to matrices of summary statistics derived from genome-wide association analyses across 2,138 phenotypes measured in 337,199 White British individuals in the UK Biobank study. We systematically identify key components of genetic associations and the contributions of variants, genes, and phenotypes to each component. As an illustration of the utility of the approach to inform downstream experiments, we report putative loss of function variants, rs114285050 (GPR151) and rs150090666 (PDE3B), that substantially contribute to obesity-related traits and experimentally demonstrate the role of these genes in adipocyte biology. Our approach to dissect components of genetic associations across the human phenome will accelerate biomedical hypothesis generation by providing insights on previously unexplored latent structures.

Identification of MiR-205 As a MicroRNA That Is Highly Expressed in Medullary Thymic Epithelial Cells.

Thymic epithelial cells (TECs) support T cell development in the thymus. Cortical thymic epithelial cells (cTECs) facilitate positive selection of developing thymocytes whereas medullary thymic epithelial cells (mTECs) facilitate the deletion of self-reactive thymocytes in order to prevent autoimmunity. The mTEC compartment is highly dynamic with continuous maturation and turnover, but the genetic regulation of these processes remains poorly understood. MicroRNAs (miRNAs) are important regulators of TEC genetic programs since miRNA-deficient TECs are severely defective. However, the individual miRNAs important for TEC maintenance and function and their mechanisms of action remain unknown. Here, we demonstrate that miR-205 is highly and preferentially expressed in mTECs during both thymic ontogeny and in the postnatal thymus. This distinct expression is suggestive of functional importance for TEC biology. Genetic ablation of miR-205 in TECs, however, neither revealed a role for miR-205 in TEC function during homeostatic conditions nor during recovery from thymic stress conditions. Thus, despite its distinct expression, miR-205 on its own is largely dispensable for mTEC biology.

The homeodomain transcription factor Irx5 establishes the mouse cardiac ventricular repolarization gradient.

Rhythmic cardiac contractions depend on the organized propagation of depolarizing and repolarizing wavefronts. Repolarization is spatially heterogeneous and depends largely on gradients of potassium currents. Gradient disruption in heart disease may underlie susceptibility to fatal arrhythmias, but it is not known how this gradient is established. We show that, in mice lacking the homeodomain transcription factor Irx5, the cardiac repolarization gradient is abolished due to increased Kv4.2 potassium-channel expression in endocardial myocardium, resulting in a selective increase of the major cardiac repolarization current, I(to,f), and increased susceptibility to arrhythmias. Myocardial Irx5 is expressed in a gradient opposite that of Kv4.2, and Irx5 represses Kv4.2 expression by recruiting mBop, a cardiac transcriptional repressor. Thus, an Irx5 repressor gradient negatively regulates potassium-channel-gene expression in the heart, forming an inverse I(to,f) gradient that ensures coordinated cardiac repolarization while also preventing arrhythmias.