Despite progress in defining genetic risk for psychiatric disorders, their molecular mechanisms remain elusive. Addressing this, the PsychENCODE Consortium has generated a comprehensive online resource for the adult brain across 1866 individuals. The PsychENCODE resource contains ~79,000 brain-active enhancers, sets of Hi-C linkages, and topologically associating domains; single-cell expression profiles for many cell types; expression quantitative-trait loci (QTLs); and further QTLs associated with chromatin, splicing, and cell-type proportions. Integration shows that varying cell-type proportions largely account for the cross-population variation in expression (with >88% reconstruction accuracy). It also allows building of a gene regulatory network, linking genome-wide association study variants to genes (e.g., 321 for schizophrenia). We embed this network into an interpretable deep-learning model, which improves disease prediction by ~6-fold versus polygenic risk scores and identifies key genes and pathways in psychiatric disorders.

BackgroundGenome-wide quantification of enhancer activity in the human genome has proven to be a challenging problem. Recent efforts have led to the development of powerful tools for enhancer quantification. However, because of genome size and complexity, these tools have yet to be applied to the whole human genome.Results In the current study, we use a human prostate cancer cell line, LNCaP as a model to perform whole human genome STARR-seq (WHG-STARR-seq) to reliably obtain an assessment of enhancer activity. This approach builds upon previously developed STARR-seq in the fly genome and CapSTARR-seq techniques in targeted human genomic regions. With an improved library preparation strategy, our approach greatly increases the library complexity per unit of starting material, which makes it feasible and cost-effective to explore the landscape of regulatory activity in the much larger human genome. In addition to our ability to identify active, accessible enhancers located in open chromatin regions, we can also detect sequences with the potential for enhancer activity that are located in inaccessible, closed chromatin regions. When treated with the histone deacetylase inhibitor, Trichostatin A, genes nearby this latter class of enhancers are up-regulated, demonstrating the potential for endogenous functionality of these regulatory elements.ConclusionWHG-STARR-seq provides an improved approach to current pipelines for analysis of high complexity genomes to gain a better understanding of the intricacies of transcriptional regulation.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-017-1345-5) contains supplementary material, which is available to authorized users.

Patient-derived pancreatic ductal adenocarcinoma (PDAC) organoid systems show great promise for understanding the biological underpinnings of disease and advancing therapeutic precision medicine. Despite the increased use of organoids, the fidelity of molecular features, genetic heterogeneity, and drug response to the tumor of origin remain important unanswered questions limiting their utility. To address this gap in knowledge, primary tumor- and patient-derived xenograft (PDX)-derived organoids, and 2D cultures for in-depth genomic and histopathologic comparisons with the primary tumor were created. Histopathologic features and PDAC representative protein markers (e.g., claudin 4 and CA19-9) showed strong concordance. DNA- and RNA-sequencing (RNAseq) of single organoids revealed patient-specific genomic and transcriptomic consistency. Single-cell RNAseq demonstrated that organoids are primarily a clonal population. In drug response assays, organoids displayed patient-specific sensitivities. In addition, the PDX response to FOLFIRINOX and gemcitabine/abraxane treatments were examined, which was recapitulated with organoids. This study has demonstrated that organoids are potentially invaluable for precision medicine as well as preclinical drug treatment studies because they maintain distinct patient phenotypes and respond differently to drug combinations and dosage. The patient-specific molecular and histopathologic fidelity of organoids indicate that they can be used to understand the etiology of the patient's tumor and the differential response to therapies and suggests utility for predicting drug responses.

SUMMARY Here we identify a key role for the homeodomain proteins Extradenticle (Exd) and Homothorax (Hth) in the specification of muscle fiber fate in Drosophila. exd and hth are expressed in the fibrillar indirect flight muscles but not in tubular jump muscles, and manipulating exd or hth expression converts one muscle type into the other. In the flight muscles, exd and hth are genetically upstream of another muscle identity gene, salm, and are direct transcriptional regulators of the signature flight muscle structural gene, Actin88F. Exd and Hth also impact muscle identity in other somatic muscles of the body by cooperating with Hox factors. Because mammalian orthologs of exd and hth also contribute to muscle gene regulation, our studies suggest that an evolutionarily conserved genetic pathway determines muscle fiber differentiation.

Schizophrenia and bipolar disorder are complex mental disorders with risks contributed by multiple genes. Dysregulation of gene expression has been implicated, but little is known about such regulation systems in the human brain. We analyzed three transcriptome datasets using 394 brain tissue samples from patients with schizophrenia or bipolar disorder and healthy control individuals without known history of psychiatric disorders. We built genome wide co-expression networks that included microRNAs (miRNAs). We identified a co-expression network module that was differentially expressed between patients and control individuals. This module contained genes that were principally involved in glial and neural cell genesis and glial cell differentiation, and included schizophrenia risk genes carrying rare variants. This module included five miRNAs and 545 mRNAs, with six transcription factors serving as hub genes in this module. We found that the most connected transcription factor POU3F2, a gene also identified on a GWAS for bipolar disorder, could regulate hsa-miR-320e and other putative target mRNAs. These regulatory relationships were replicated by PsychENCODE/BrainGVEX data and validated by knockdown and overexpression experiments in the SH-SY5Y and neural progenitor cell lines in vitro. We identified a psychosis-associated brain gene expression module that was enriched for rare coding variants in genes associated with schizophrenia and contained the putative bipolar disorder risk gene POU3F2 as a key regulator of gene expression in this module.

Most T lymphocytes leave the thymus as naïve cells with limited functionality. However, unique populations of innate-like T cells differentiate into functionally distinct effector subsets during their development in the thymus. Here, we profiled >10,000 differentiating thymic invariant natural killer T (iNKT) cells using single-cell RNA sequencing to produce a comprehensive transcriptional landscape that highlights their maturation, function, and fate decisions at homeostasis. Our results reveal transcriptional profiles that are broadly shared between iNKT and mucosal-associated invariant T (MAIT) cells, illustrating a common core developmental program. We further unmask a mutual requirement for Hivep3, a zinc finger transcription factor and adapter protein. Hivep3 is expressed in early precursors and regulates the post-selection proliferative burst, differentiation and functions of iNKT cells. Altogether, our results highlight the common requirements for the development of innate-like T cells with a focus on how Hivep3 impacts the maturation of these lymphocytes.

Cellular heterogeneity in the human brain obscures the identification of robust cellular regulatory networks, which is necessary to understand the function of non-coding elements and the impact of non-coding genetic variation. Here we integrate genome-wide chromosome conformation data from purified neurons and glia with transcriptomic and enhancer profiles, to characterize the gene regulatory landscape of two major cell classes in the human brain. We then leverage cell-type-specific regulatory landscapes to gain insight into the cellular etiology of several brain disorders. We find that Alzheimer’s disease (AD)-associated epigenetic dysregulation is linked to neurons and oligodendrocytes, whereas genetic risk factors for AD highlighted microglia, suggesting that different cell types may contribute to disease risk, via different mechanisms. Moreover, integration of glutamatergic and GABAergic regulatory maps with genetic risk factors for schizophrenia (SCZ) and bipolar disorder (BD) identifies shared (parvalbumin-expressing interneurons) and distinct cellular etiologies (upper layer neurons for BD, and deeper layer projection neurons for SCZ). Collectively, these findings shed new light on cell-type-specific gene regulatory networks in brain disorders.

RATIONALE: Pulmonary mast cells (MC) have been associated with asthma pathogenesis. We have previously shown differences in MC phenotype by location in the lung (submucosa and epithelium) [Balzar, AJRCCM, 2011]. Little is known regarding the relative importance of luminal MCs to asthma. We hypothesized that distal/luminal MCs would better predict more severe clinical outcomes than proximal/epithelial MCs. METHODS: In 102 University of Pittsburgh asthmatics enrolled in NHLBI trials, bronchial epithelial brushings, bronchoalveolar (BAL) cells and fluid were obtained at bronchoscopy. Expression of the MC protease, tryptase mRNA was determined by qRT-PCR. Using the median tryptase mRNA values for epithelial brushings and BAL cells, subjects were classified as proximal and distal MC ''Hi'' or ''Lo.'' Regression analysis was performed to assess the effect of MC ''Hi'' on the outcomes of history of recent exacerbation, baseline FEV1% predicted and FEV1/FVC. RESULTS: Distal MCHi asthma significantly predicted exacerbation [OR53.6, p50.004], while proximal MCHi asthma did not [OR51.7, p50.2]. Distal MCHi asthma negatively associated with baseline FEV1% predicted [Beta5 -12.5, p50.006, R250.07] and baseline FEV1/FVC [Beta5 -0.06, p50.019, R250.05]. This relationship was not seen with proximal MCHi asthma [p for FEV1% predicted50.6, p for FEV1/ FVC50.8]. CONCLUSIONS: In matched samples from asthmatic subjects, the distal/ BAL cell MC signature better predicted asthma exacerbation, lower FEV1%predicted and decreased FEV1/FVC than the proximal/epithelial MC signature. In asthma, this suggests an important difference in MC function based on the location in the lung. Use of distal MC biomarkers should better identify more clinically severe asthma. 900 Association study in African-admixed J ALLERGY CLIN IMMUNOL FEBRUARY 2019 AB296 Abstracts MONDAY