We report the generation and analysis of functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project. These data have been further integrated and augmented by a number of evolutionary and computational analyses. Together, our results advance the collective knowledge about human genome function in several major areas. First, our studies provide convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts, including non-protein-coding transcripts, and those that extensively overlap one another. Second, systematic examination of transcriptional regulation has yielded new understanding about transcription start sites, including their relationship to specific regulatory sequences and features of chromatin accessibility and histone modification. Third, a more sophisticated view of chromatin structure has emerged, including its inter-relationship with DNA replication and transcriptional regulation. Finally, integration of these new sources of information, in particular with respect to mammalian evolution based on inter- and intra-species sequence comparisons, has yielded new mechanistic and evolutionary insights concerning the functional landscape of the human genome. Together, these studies are defining a path for pursuit of a more comprehensive characterization of human genome function.

Transcriptional promoters comprise one of many classes of eukaryotic transcriptional regulatory elements. Identification and characterization of these elements are vital to understanding the complex network of human gene regulation. Using full-length cDNA sequences to identify transcription start sites (TSS), we predicted more than 900 putative human transcriptional promoters in the ENCODE regions, representing a comprehensive sampling of promoters in 1% of the genome. We identified 387 fragments that function as promoters in at least one of 16 cell lines by measuring promoter activity in high-throughput transient transfection reporter assays. These positive functional results demonstrate widespread use of alternative promoters. We show a strong correlation between promoter activity and the corresponding endogenous RNA transcript levels, providing the first experimental quantitative estimate of promoter contribution to gene regulation. Finally, we identified functional regions within a randomly selected subset of 45 promoters using deletion analyses. These experiments showed that, on average, the sequence −300 to −50 bp of the TSS positively contributes to core promoter activity. Interestingly, putative negative elements were identified −1000 to −500 bp upstream of the TSS for 55% of genes tested. These data provide the largest and most comprehensive view of promoter function in the human genome.[Supplemental material is available online at www.genome.org.]The regulation of human gene expression is a critical, highly coordinated, and complex process. Gene regulation plays a crucial role in virtually every biological process from coordinating cell division to responding to extracellular stimuli and directing transcription during development (Pirkkala et al. 2001;Ahituv et al. 2004;Blais and Dynlacht 2004). While knowledge of regulation at the level of individual genes is progressing, global characterization of gene regulation currently represents one of the major challenges and fundamental goals for biomedical research. An initial step in achieving this goal is the comprehensive identification of transcriptional regulatory elements in the human genome. Towards this end, the ENCODE (Encyclopedia of DNA Elements) project began in 2004 as a collective effort of many laboratories to identify the functional elements in 1% of the human genome (The ENCODE Project Consortium 2004). In this paper, we describe our efforts to identify and study the transcriptional promoters in the ENCODE regions.Promoters are the best-characterized transcriptional regulatory sequences in complex genomes because of their predictable location immediately upstream of transcription start sites (TSS). They are often described as having two separate segments: core and extended promoter regions. The core promoter is generally within 50 bp of the TSS, where the preinitiation complex forms and the general transcription machinery assembles. The extended promoter can contain specific regulatory sequences that control spatial and temporal expression of...

BACKGROUNDPatients with metastatic sarcomas have poor outcomes and although the disease may be amenable to immunotherapies, information regarding the immunologic profiles of soft tissue sarcoma (STS) subtypes is limited.METHODSThe authors identified patients with the common STS subtypes: leiomyosarcoma, undifferentiated pleomorphic sarcoma (UPS), synovial sarcoma (SS), well‐differentiated/dedifferentiated liposarcoma, and myxoid/round cell liposarcoma. Gene expression, immunohistochemistry for programmed cell death protein (PD‐1) and programmed death‐ligand 1 (PD‐L1), and T‐cell receptor Vβ gene sequencing were performed on formalin‐fixed, paraffin‐embedded tumors from 81 patients. Differences in liposarcoma subsets also were evaluated.RESULTSUPS and leiomyosarcoma had high expression levels of genes related to antigen presentation and T‐cell infiltration. UPS were found to have higher levels of PD‐L1 (P≤.001) and PD‐1 (P≤.05) on immunohistochemistry and had the highest T‐cell infiltration based on T‐cell receptor sequencing, significantly more than SS, which had the lowest (P≤.05). T‐cell infiltrates in UPS also were more oligoclonal compared with SS and liposarcoma (P≤.05). A model adjusted for STS histologic subtype found that for all sarcomas, T‐cell infiltration and clonality were highly correlated with PD‐1 and PD‐L1 expression levels (P≤.01).CONCLUSIONSIn the current study, the authors provide the most detailed overview of the immune microenvironment in sarcoma subtypes to date. UPS, which is a more highly mutated STS subtype, provokes a substantial immune response, suggesting that it may be well suited to treatment with immune checkpoint inhibitors. The SS and liposarcoma subsets are less mutated but do express immunogenic self‐antigens, and therefore strategies to improve antigen presentation and T‐cell infiltration may allow for successful immunotherapy in patients with these diagnoses. Cancer 2017;123:3291‐304. © 2017 The Authors. Cancer published by Wiley Periodicals, Inc. on behalf of American Cancer Society. This is an open access article under the terms of the Creative Commons Attribution NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

To better understand the quantitative characteristics and structure of phenotypic diversity, we measured over 14,000 transcript, protein, metabolite, and morphological traits in 22 genetically diverse strains of Saccharomyces cerevisiae. More than 50% of all measured traits varied significantly across strains [false discovery rate (FDR) = 5%]. The structure of phenotypic correlations is complex, with 85% of all traits significantly correlated with at least one other phenotype (median = 6, maximum = 328). We show how high-dimensional molecular phenomics data sets can be leveraged to accurately predict phenotypic variation between strains, often with greater precision than afforded by DNA sequence information alone. These results provide new insights into the spectrum and structure of phenotypic diversity and the characteristics influencing the ability to accurately predict phenotypes.

BackgroundPsychiatric disorders are multigenic diseases with complex etiology that contribute significantly to human morbidity and mortality. Although clinically distinct, several disorders share many symptoms, suggesting common underlying molecular changes exist that may implicate important regulators of pathogenesis and provide new therapeutic targets.MethodsWe performed RNA sequencing on tissue from the anterior cingulate cortex, dorsolateral prefrontal cortex, and nucleus accumbens from three groups of 24 patients each diagnosed with schizophrenia, bipolar disorder, or major depressive disorder, and from 24 control subjects. We identified differentially expressed genes and validated the results in an independent cohort. Anterior cingulate cortex samples were also subjected to metabolomic analysis. ChIP-seq data were used to characterize binding of the transcription factor EGR1.ResultsWe compared molecular signatures across the three brain regions and disorders in the transcriptomes of post-mortem human brain samples. The most significant disease-related differences were in the anterior cingulate cortex of schizophrenia samples compared to controls. Transcriptional changes were assessed in an independent cohort, revealing the transcription factor EGR1 as significantly down-regulated in both cohorts and as a potential regulator of broader transcription changes observed in schizophrenia patients. Additionally, broad down-regulation of genes specific to neurons and concordant up-regulation of genes specific to astrocytes was observed in schizophrenia and bipolar disorder patients relative to controls. Metabolomic profiling identified disruption of GABA levels in schizophrenia patients.ConclusionsWe provide a comprehensive post-mortem transcriptome profile of three psychiatric disorders across three brain regions. We highlight a high-confidence set of independently validated genes differentially expressed between schizophrenia and control patients in the anterior cingulate cortex and integrate transcriptional changes with untargeted metabolite profiling.Electronic supplementary materialThe online version of this article (doi:10.1186/s13073-017-0458-5) contains supplementary material, which is available to authorized users.