Tyler Borrman

Abstract The human and mouse genomes contain instructions that specify RNAs and proteins and govern the timing, magnitude, and cellular context of their production. To better delineate these elements, phase III of the Encyclopedia of DNA Elements (ENCODE) Project has expanded analysis of the cell and tissue repertoires of RNA transcription, chromatin structure and modification, DNA methylation, chromatin looping, and occupancy by transcription factors and RNA-binding proteins. Here we summarize these efforts, which have produced 5,992 new experimental datasets, including systematic determinations across mouse fetal development. All data are available through the ENCODE data portal ( https://www.encodeproject.org ), including phase II ENCODE 1 and Roadmap Epigenomics 2 data. We have developed a registry of 926,535 human and 339,815 mouse candidate cis -regulatory elements, covering 7.9 and 3.4% of their respective genomes, by integrating selected datatypes associated with gene regulation, and constructed a web-based server (SCREEN; http://screen.encodeproject.org ) to provide flexible, user-defined access to this resource. Collectively, the ENCODE data and registry provide an expansive resource for the scientific community to build a better understanding of the organization and function of the human and mouse genomes.

INTRODUCTION The human cerebral cortex has undergone an extraordinary increase in size and complexity during mammalian evolution. Cortical cell lineages are specified in the embryo, and genetic and epidemiological evidence implicates early cortical development in the etiology of neuropsychiatric disorders such as autism spectrum disorder (ASD), intellectual disabilities, and schizophrenia. Most of the disease-implicated genomic variants are located outside of genes, and the interpretation of noncoding mutations is lagging behind owing to limited annotation of functional elements in the noncoding genome. RATIONALE We set out to discover gene-regulatory elements and chart their dynamic activity during prenatal human cortical development, focusing on enhancers, which carry most of the weight upon regulation of gene expression. We longitudinally modeled human brain development using human induced pluripotent stem cell (hiPSC)–derived cortical organoids and compared organoids to isogenic fetal brain tissue. RESULTS Fetal fibroblast–derived hiPSC lines were used to generate cortically patterned organoids and to compare oganoids’ epigenome and transcriptome to that of isogenic fetal brains and external datasets. Organoids model cortical development between 5 and 16 postconception weeks, thus enabling us to study transitions from cortical stem cells to progenitors to early neurons. The greatest changes occur at the transition from stem cells to progenitors. The regulatory landscape encompasses a total set of 96,375 enhancers linked to target genes, with 49,640 enhancers being active in organoids but not in mid-fetal brain, suggesting major roles in cortical neuron specification. Enhancers that gained activity in the human lineage are active in the earliest stages of organoid development, when they target genes that regulate the growth of radial glial cells. Parallel weighted gene coexpression network analysis (WGCNA) of transcriptome and enhancer activities defined a number of modules of coexpressed genes and coactive enhancers, following just six and four global temporal patterns that we refer to as supermodules, likely reflecting fundamental programs in embryonic and fetal brain. Correlations between gene expression and enhancer activity allowed stratifying enhancers into two categories: activating regulators (A-regs) and repressive regulators (R-regs). Several enhancer modules converged with gene modules, suggesting that coexpressed genes are regulated by enhancers with correlated patterns of activity. Furthermore, enhancers active in organoids and fetal brains were enriched for ASD de novo variants that disrupt binding sites of homeodomain, Hes1, NR4A2, Sox3, and NFIX transcription factors. CONCLUSION We validated hiPSC-derived cortical organoids as a suitable model system for studying gene regulation in human embryonic brain development, evolution, and disease. Our results suggest that organoids may reveal how noncoding mutations contribute to ASD etiology. Summary of the study, analyses, and main results. Data were generated for iPSC-derived human telencephalic organoids and isogenic fetal cortex. Organoids modeled embryonic and early fetal cortex and show a larger repertoire of enhancers. Enhancers could be divided into activators and repressors of gene expression. We derived networks of modules and supermodules with correlated gene and enhancer activities, some of which were implicated in autism spectrum disorders (ASD).

INTRODUCTION Chromosomal conformations, topologically associated chromatin domains (TADs) assembling in nested fashion across hundreds of kilobases, and other “three-dimensional genome” (3DG) structures bypass the linear genome on a kilo- or megabase scale and play an important role in transcriptional regulation. Most of the genetic variants associated with risk for schizophrenia (SZ) are common and could be located in enhancers, repressors, and other regulatory elements that influence gene expression; however, the role of the brain’s 3DG for SZ genetic risk architecture, including developmental and cell type–specific regulation, remains poorly understood. RATIONALE We monitored changes in 3DG after isogenic differentiation of human induced pluripotent stem cell–derived neural progenitor cells (NPCs) into neurons or astrocyte-like glial cells on a genome-wide scale using Hi-C. With this in vitro model of brain development, we mapped cell type–specific chromosomal conformations associated with SZ risk loci and defined a risk-associated expanded genome space. RESULTS Neural differentiation was associated with genome-wide 3DG remodeling, including pruning and de novo formations of chromosomal loopings. The NPC-to-neuron transition was defined by the pruning of loops involving regulators of cell proliferation, morphogenesis, and neurogenesis, which is consistent with a departure from a precursor stage toward postmitotic neuronal identity. Loops lost during NPC-to-glia transition included many genes associated with neuron-specific functions, which is consistent with non-neuronal lineage commitment. However, neurons together with NPCs, as compared with glia, harbored a much larger number of chromosomal interactions anchored in common variant sequences associated with SZ risk. Because spatial 3DG proximity of genes is an indicator for potential coregulation, we tested whether the neural cell type–specific SZ-related “chromosomal connectome” showed evidence of coordinated transcriptional regulation and proteomic interaction of the participating genes. To this end, we generated lists of genes anchored in cell type–specific SZ risk-associated interactions. Thus, for the NPC-specific interactions, we counted 386 genes, including 146 within the risk loci and another 240 genes positioned elsewhere in the linear genome but connected via intrachromosomal contacts to risk locus sequences. Similarly, for the neuron-specific interactions, we identified 385 genes: 158 within risk loci and 227 outside of risk loci. Last, for glia-specific interactions, we identified 201 genes: 88 within and 113 outside of risk loci. We labeled the genes located outside of schizophrenia risk loci as “risk locus–connect,” which we define as a collection of genes identified only through Hi-C interaction data, expanding—depending on cell type—by 50 to 150% the current network of known genes overlapping risk sequences that is informed only by genome-wide association studies. This disease-related chromosomal connectome was associated with “clusters” of coordinated gene expression and protein interactions, with at least one cluster strongly enriched for regulators of neuronal connectivity and synaptic plasticity and another cluster for chromatin-associated proteins, including transcriptional regulators. CONCLUSION Our study shows that neural differentiation is associated with highly cell type–specific 3DG remodeling. This process is paralleled by an expansion of 3DG space associated with SZ risk. Specifically, developmentally regulated chromosomal conformation changes at SZ-relevant sequences disproportionally occurred in neurons, highlighting the existence of cell type–specific disease risk vulnerabilities in spatial genome organization. 3DG remodeling across neuronal differentiation with parallel expansion of SZ risk space. (Left) Chromatin conformation assays reveal pruning of short-range loops in neurons along with widening of TADs upon differentiation from NPCs. (Right) Cell type–specific chromatin interactions, functionally validated with CRISPR assays, expand the network of known risk-associated genes (blue circle), which show evidence for coregulation at the transcriptomic and proteomic levels.

The Encylopedia of DNA Elements (ENCODE) Project launched in 2003 with the long-term goal of developing a comprehensive map of functional elements in the human genome. These included genes, biochemical regions associated with gene regulation (for example, transcription factor binding sites, open chromatin, and histone marks) and transcript isoforms. The marks serve as sites for candidate cis-regulatory elements (cCREs) that may serve functional roles in regulating gene expression1. The project has been extended to model organisms, particularly the mouse. In the third phase of ENCODE, nearly a million and more than 300,000 cCRE annotations have been generated for human and mouse, respectively, and these have provided a valuable resource for the scientific community. The authors summarize the history of the ENCODE Project, the achievements of ENCODE 1 and ENCODE 2, and how the new data generated and analysed in ENCODE 3 complement the previous phases.

We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein-protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact-sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology-built subunit models and the smaller pair-wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy. Proteins 2016; 84(Suppl 1):323-348. © 2016 Wiley Periodicals, Inc.