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Thousands of non-coding variants have been associated with increased risk of human diseases, yet the causal variants and their mechanisms-of-action remain obscure. In an integrative study combining massively parallel reporter assays (MPRA), expression analyses (eQTL, meQTL, PCHiC) and chromatin accessibility analyses in primary cells (caQTL), we investigate 1,039 variants associated with multiple myeloma (MM). We demonstrate that MM susceptibility is mediated by gene-regulatory changes in plasma cells and B-cells, and identify putative causal variants at six risk loci (SMARCD3, WAC, ELL2, CDCA7L, CEP120, and PREX1). Notably, three of these variants co-localize with significant plasma cell caQTLs, signaling the presence of causal activity at these precise genomic positions in an endogenous chromosomal context in vivo. Our results provide a systematic functional dissection of risk loci for a hematologic malignancy. The causality and functional roles of disease-associated variants revealed by genome-wide association studies (GWAS) are mostly unexplored. Here the authors identify putative causal variants in multiple myeloma and find their association with gene expression and chromatin accessibility. [ABSTRACT FROM AUTHOR]

Response to antidepressant treatment in major depressive disorder (MDD) cannot be predicted currently, leading to uncertainty in medication selection, increasing costs, and prolonged suffering for many patients. Despite tremendous efforts in identifying response-associated genes in large genome-wide association studies, the results have been fairly modest, underlining the need to establish conceptually novel strategies. For the identification of transcriptome signatures that can distinguish between treatment responders and nonresponders, we herein submit a novel animal experimental approach focusing on extreme phenotypes. We utilized the large variance in response to antidepressant treatment occurring in DBA/2J mice, enabling sample stratification into subpopulations of good and poor treatment responders to delineate response-associated signature transcript profiles in peripheral blood samples. As a proof of concept, we translated our murine data to the transcriptome data of a clinically relevant human cohort. A cluster of 259 differentially regulated genes was identified when peripheral transcriptome profiles of good and poor treatment responders were compared in the murine model. Differences in expression profiles from baseline to week 12 of the human orthologues selected on the basis of the murine transcript signature allowed prediction of response status with an accuracy of 76% in the patient population. Finally, we show that glucocorticoid receptor (GR)-regulated genes are significantly enriched in this cluster of antidepressant-response genes. Our findings point to the involvement of GR sensitivity as a potential key mechanism shaping response to antidepressant treatment and support the hypothesis that antidepressants could stimulate resilience-promoting molecular mechanisms. Our data highlight the suitability of an appropriate animal experimental approach for the discovery of treatment response-associated pathways across species. [ABSTRACT FROM AUTHOR]

Although many diseases and traits show large heritability, few genetic variants have been found to strongly separate phenotype groups by genotype. Complex regulatory networks of variants and expression of multiple genes lead to small individual-variant effects and difficulty replicating the effect of any single variant in an affected pathway. Interaction network modeling of GWAS identifies effects ignored by univariate models, but population differences may still cause specific genes to not replicate. Integrative network models may help detect indirect effects of variants in the underlying biological pathway. In this study, we used gene-level functional interaction information from the Integrative Multi-species Prediction (IMP) tool to reveal important genes associated with a complex phenotype through evidence from epistasis networks and pathway enrichment. We test this method for augmenting variant-based network analyses with functional interactions by applying it to a smallpox vaccine immune response GWAS. The integrative analysis spotlights the role of genes related to retinoid X receptor alpha (RXRA), which has been implicated in a previous epistasis network analysis of smallpox vaccine. [ABSTRACT FROM AUTHOR]

Recent studies have implicated the role of differential co-expression or correlation structure in gene expression data to help explain phenotypic differences. However, few attempts have been made to characterize the function of variants based on their role in regulating differential co-expression. Here, we describe a statistical methodology that identifies pairs of transcripts that display differential correlation structure conditioned on genotypes of variants that regulate co-expression. Additionally, we present a user-friendly, computationally efficient tool, dcVar, that can be applied to expression quantitative trait loci (eQTL) or RNA-Seq datasets to infer differential co-expression variants (dcVars). We apply dcVar to the HapMap3 eQTL dataset and demonstrate the utility of this methodology at uncovering novel function of variants of interest with examples from a height genome-wide association and cancer drug resistance. We provide evidence that differential correlation structure is a valuable intermediate molecular phenotype for further characterizing the function of variants identified in GWAS and related studies. [ABSTRACT FROM AUTHOR]

The 3D architecture of DNA within the nucleus is a key determinant of interactions between genes, regulatory elements, and transcriptional machinery. As a result, differences in DNA looping structure are associated with variation in gene expression and cell state. To systematically assess changes in DNA looping architecture between samples, we introduce diffloop, an R/ Bioconductor package that provides a suite of functions for the quality control, statistical testing, annotation, and visualization of DNA loops. We demonstrate this functionality by detecting differences between ENCODE ChIA-PET samples and relate looping to variability in epigenetic state. [ABSTRACT FROM AUTHOR]

The memory CD8+ T cell pool contains phenotypically and transcriptionally heterogeneous subsets with specialized functions and recirculation patterns. Here, we examined the epigenetic landscape of CD8+ T cells isolated from seven non-lymphoid organs across four distinct infection models, alongside their circulating T cell counterparts. Using single-cell transposase-accessible chromatin sequencing (scATAC-seq), we found that tissue-resident memory T (T RM) cells and circulating memory T (T CIRC) cells develop along distinct epigenetic trajectories. We identified organ-specific transcriptional regulators of T RM cell development, including FOSB, FOS, FOSL1, and BACH2, and defined an epigenetic signature common to T RM cells across organs. Finally, we found that although terminal T EX cells share accessible regulatory elements with T RM cells, they are defined by T EX -specific epigenetic features absent from T RM cells. Together, this comprehensive data resource shows that T RM cell development is accompanied by dynamic transcriptome alterations and chromatin accessibility changes that direct tissue-adapted and functionally distinct T cell states. [Display omitted] • Memory T cell subsets develop along distinct epigenetic trajectories • T RM cells exhibit a distinct chromatin landscape from that of T CIRC cell subsets • Epigenetic analyses reveal novel organ-specific regulators of T RM cell development • T RM and T EX are epigenetically distinct but exhibit cis -regulatory element overlap Epigenomic features steering CD8+ T cell heterogeneity across tissues has not yet been extensively explored. By profiling chromatin accessibility changes and gene expression in T cells derived from multiple organs, Buquicchio et al. reveal the epigenetic state of memory CD8+ T cells and identify subset and organ-specific regulators involved in T cell differentiation. [ABSTRACT FROM AUTHOR]

Cytokine expression during T cell differentiation is a highly regulated process that involves long-range promoter-enhancer and CTCF-CTCF contacts at cytokine loci. Here, we investigated the impact of dynamic chromatin loop formation within the topologically associating domain (TAD) in regulating the expression of interferon gamma (IFN-γ) and interleukin-22 (IL-22); these cytokine loci are closely located in the genome and are associated with complex enhancer landscapes, which are selectively active in type 1 and type 3 lymphocytes. In situ Hi-C analyses revealed inducible TADs that insulated Ifng and Il22 enhancers during Th1 cell differentiation. Targeted deletion of a 17 bp boundary motif of these TADs imbalanced Th1- and Th17-associated immunity, both in vitro and in vivo , upon Toxoplasma gondii infection. In contrast, this boundary element was dispensable for cytokine regulation in natural killer cells. Our findings suggest that precise cytokine regulation relies on lineage- and developmental stage-specific interactions of 3D chromatin architectures and enhancer landscapes. [Display omitted] • Profiling 3D genome architecture reveals a boundary between Il22 and Ifng enhancers • Deletion of a 17 bp CTCF-binding motif dysregulates Il22 and Ifng expression in Th1 cells • The mutation does not impair Ifng production in NK cells • The mutant mice are susceptible to Toxoplasma gondii infection Multilayered gene regulation orchestrates cell-type-specific cytokine expression. Liu et al. examine the impact of chromatin loop formation on the expression of IFN-γ and IL-22, which are cytokine loci closely located in the genome, and identify an inducible topologically associating domain required for proper IFN-γ production in Th1 cells. Deleting a CTCF-binding site within this domain leads to lineage-specific cytokine dysregulation and increased susceptibility to pathogens. [ABSTRACT FROM AUTHOR]

Summary Human hematopoiesis involves cellular differentiation of multipotent cells into progressively more lineage-restricted states. While the chromatin accessibility landscape of this process has been explored in defined populations, single-cell regulatory variation has been hidden by ensemble averaging. We collected single-cell chromatin accessibility profiles across 10 populations of immunophenotypically defined human hematopoietic cell types and constructed a chromatin accessibility landscape of human hematopoiesis to characterize differentiation trajectories. We find variation consistent with lineage bias toward different developmental branches in multipotent cell types. We observe heterogeneity within common myeloid progenitors (CMPs) and granulocyte-macrophage progenitors (GMPs) and develop a strategy to partition GMPs along their differentiation trajectory. Furthermore, we integrated single-cell RNA sequencing (scRNA-seq) data to associate transcription factors to chromatin accessibility changes and regulatory elements to target genes through correlations of expression and regulatory element accessibility. Overall, this work provides a framework for integrative exploration of complex regulatory dynamics in a primary human tissue at single-cell resolution. [ABSTRACT FROM AUTHOR]