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.

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.