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Probing epigenetic features on DNA has tremendous potential to advance our understanding of the phased epigenome. In this study, we use nanopore sequencing to evaluate CpG methylation and chromatin accessibility simultaneously on long strands of DNA by applying GpC methyltransferase to exogenously label open chromatin. We performed nanopore sequencing of Nucleosome Occupancy and Methylome (nanoNOMe) on four human cell lines (GM12878, MCF-10A, MCF-7, MDA-MB-231). The single-molecule resolution allows footprinting of protein and nucleosome binding and determining the combinatorial promoter epigenetic signature on individual molecules. Long-read sequencing makes it possible to robustly assign reads to haplotypes, allowing us to generate the first fully phased human epigenome, consisting of chromosome-level allele-specific profiles of CpG methylation and chromatin accessibility. We further apply this to a breast cancer model to evaluate differential methylation and accessibility between cancerous and non-cancerous cells.

The aggregation and joint analysis of large numbers of exome sequences has recently made it possible to de-rive estimates of intolerance to loss-of-function (LoF) variation for human genes. Here, we demonstrate strong and widespread coupling between genic LoF-intolerance and promoter CpG density across the human genome. Genes downstream of the most CpG-rich pro-moters (top 10% CpG density) have a 67.2% probability of being highly LoF-intolerant, using the LOEUF metric from gnomAD. This is in contrast to 7.4% of genes downstream of the most CpG-poor (bottom 10% CpG density) promoters. Combining promoter CpG density with exonic and promoter conservation explains 33.4% of the variation in LOEUF, and the contribution of CpG density exceeds the individual contributions of exonic and promoter conservation. We leverage this to train a simple and easily interpretable predictive model that out-performs other existing predictors and allows us to classify 1,760 genes – which currently lack reliable LOEUF estimates – as highly LoF-intolerant or not. These predictions have the potential to aid in the interpretation of novel patient variants. Moreover, our results reveal that high CpG density is not merely a generic feature of human promoters, but is preferentially encountered at the promoters of the most selectively constrained genes, calling into question the prevailing view that CpG islands are not subject to selection.

We present recount3, a resource consisting of over 750,000 publicly available human and mouse RNA sequencing (RNA-seq) samples uniformly processed by our new Monorail analysis pipeline. To facilitate access to the data, we provide the recount3 and snapcount R/Bioconductor packages as well as complementary web resources. Using these tools, data can be downloaded as study-level summaries or queried for specific exon-exon junctions, genes, samples, or other features. Monorail can be used to process local and/or private data, allowing results to be directly compared to any study in recount3. Taken together, our tools help biologists maximize the utility of publicly available RNA-seq data, especially to improve their understanding of newly collected data. recount3 is available from http://rna.recount.bio.

The Mendelian Disorders of the Epigenetic Machinery (MDEMs) have emerged as a class of Mendelian disorders caused by loss-of-function variants in epigenetic regulators. Although each MDEM has a different causative gene, they exhibit several overlapping disease manifestations. Here, we hypothesize that this phenotypic convergence is a consequence of common abnormalities at the epigenomic level, which directly or indirectly lead to downstream convergence at the transcriptomic level. Therefore, we seek to identify abnormalities shared across multiple MDEMs, in order to pinpoint locations where epigenetic variation is causally related to disease phenotypes. To this end, we perform a comprehensive interrogation of chromatin (ATAC-Seq) and expression (RNA-Seq) states in B cells from mouse models of three MDEMs (Kabuki types 1&2 and Rubinstein-Taybi syndromes). We build on recent work in covariate-powered multiple testing to develop a new approach for the overlap analysis, which enables us to find extensive overlap primarily localized in gene promoters. We show that disruption of chromatin accessibility at promoters often leads to disruption of downstream gene expression, and identify 463 loci and 249 genes with shared disruption across all three MDEMs. As an example of how widespread dysregulation leads to specific phenotypes, we show that subtle expression alterations of multiple, IgA-relevant genes, collectively contribute to IgA deficiency in KS1 and RT1. In contrast, we predict that KS2 does not have IgA deficiency, and confirm this observationin vivo. We propose that the joint study of MDEMs offers a principled approach for systematically mapping functional epigenetic variation in mammals.

Single-cell profiling of chromatin structure remains a challenge due to cost, throughput, and resolution. We introduce compartmap to reconstruct higher-order chromatin domains in individual cells from transcriptomic (RNAseq) and epigenomic (ATACseq) assays. In cell lines and primary human samples, compartmap infers higher-order chromatin structure comparable to specialized chromatin capture methods, and identifies clinically relevant structural alterations in single cells. This provides a common lens to integrate transcriptional and epigenomic results, linking higher-order chromatin architecture to gene regulation and to clinically relevant phenotypes in individual cells.

Epigenetic modifications confer stable transcriptional patterns in the brain, and both normal and abnormal brain function involve specialized brain regions. We examined DNA methylation by whole-genome bisulfite sequencing in neuronal and non-neuronal populations from four brain regions (anterior cingulate gyrus, hippocampus, prefrontal cortex, and nucleus accumbens) as well as chromatin accessibility in the latter two. We find pronounced differences in both CpG and non-CpG methylation (CG-DMRs and CH-DMRs) only in neuronal cells across brain regions. Neuronal CH-DMRs were highly associated with differential gene expression, whereas CG-DMRs were consistent with chromatin accessibility and enriched for regulatory regions. These CG-DMRs comprise ~12 Mb of the genome that is highly enriched for genomic regions associated with heritability of neuropsychiatric traits including addictive behavior, schizophrenia, and neuroticism, thus suggesting a mechanistic link between pathology and differential neuron-specific epigenetic regulation in distinct brain regions. An extensive profile of DNA methylation in neuronal and non-neuronal cells across four brain regions is reported, showing that differential epigenetic marks are enriched for DNA variants associated with neuropsychiatric traits.

While DNA methylation (DNAm) is the most-studied epigenetic mark, few recent studies probe the breadth of publicly available DNAm array samples. We collectively analyzed 35 360 Illumina Infinium HumanMethylation450K DNAm array samples published on the Gene Expression Omnibus. We learned a controlled vocabulary of sample labels by applying regular expressions to metadata and used existing models to predict various sample properties including epigenetic age. We found approximately two-thirds of samples were from blood, one-quarter were from brain and one-third were from cancer patients. About 19% of samples failed at least one of Illumina’s 17 prescribed quality assessments; signal distributions across samples suggest modifying manufacturer-recommended thresholds for failure would make these assessments more informative. We further analyzed DNAm variances in seven tissues (adipose, nasal, blood, brain, buccal, sperm and liver) and characterized specific probes distinguishing them. Finally, we compiled DNAm array data and metadata, including our learned and predicted sample labels, into database files accessible via the recountmethylation R/Bioconductor companion package. Its vignettes walk the user through some analyses contained in this paper.

Fetal sex-specific differences in placental morphology and physiology have been associated with sexually dimorphic health outcomes. However, the molecular mechanisms underlying these sex differences are not well understood. We performed whole genome bisulfite sequencing in 133 placenta samples and discovered a significant difference in DNA methylation (DNAm) at the ZNF300 gene locus between male and female offspring and replicated this result in 6 independent datasets. Additionally, the sex-specific pattern appears to be placenta-specific, is robust to a wide range of gestational ages and adverse health outcomes and is present in sorted placenta villous cytotrophoblast cells. Integration of DNAm, genetic, and placental morphology data from the same individuals revealed ZNF300 methylation is also associated with placenta area, perimeter, and max diameter, genetic variants on chromosomes 5 and X, and may mediate the effects of genetic variation on placental area.

Infinium methylation arrays are widely used to robustly measure methylation of DNA in humans. However, such arrays are not available for the vast majority of non-human mammals. Moreover, even if species-specific arrays were available, probe differences between them would confound cross-species comparisons. To address these challenges, we developed the Mammalian Methylation Array, a single custom Infinium array that measures cytosine methylation levels of 36 thousand CpG sites that are well conserved across species within the mammalian class. By design, the probes on the array tolerate cross-species mutations. To design the array, we developed the Conserved Methylation Array Probe Selector (CMAPS) algorithm, which takes as input a multi-species sequence alignment and probe design constraints. A greedy search algorithm was used to identify oligonucleotide sequences (probes) with high coverage across different mammalian species. We annotate the probes on the array with respect to genes in 159 different species and provide details on the sequence context including CpG island status and chromatin states. Our calibration experiments demonstrate the high fidelity of this array in humans, rats, and mice. The mammalian methylation array has several strengths: it applies to all mammalian species even those that have not yet been sequenced, it provides deep coverage of specific cytosines facilitating the development of highly robust epigenetic biomarkers, and it covers highly conserved CpGs which greatly increases the probability that biological insights gained in one species will readily translate to others. The mammalian methylation array is expected to find many applications in preclinical studies, comparative biology, and epigenetic studies of aging and development.

The Genotype-Tissue Expression (GTEx) project dissects how genetic variation affects gene expression and splicing. Some human genetic variants affect the amount of RNA produced and the splicing of gene transcripts, crucial steps in development and maintaining a healthy individual. However, some of these changes only occur in a small number of tissues within the body. The Genotype-Tissue Expression (GTEx) project has been expanded over time, and, looking at the final data in version 8, Aguet et al. present a deep characterization of genetic associations and gene expression and splicing in 838 individuals over 49 tissues (see the Perspective by Wilson). This large study was able to characterize the details underlying many aspects of gene expression and provides a resource with which to better understand the fundamental molecular mechanisms of how genetic variants affect gene regulation and complex traits in humans. Science, this issue p. 1318; see also p. 1298 The Genotype-Tissue Expression (GTEx) project was established to characterize genetic effects on the transcriptome across human tissues and to link these regulatory mechanisms to trait and disease associations. Here, we present analyses of the version 8 data, examining 15,201 RNA-sequencing samples from 49 tissues of 838 postmortem donors. We comprehensively characterize genetic associations for gene expression and splicing in cis and trans, showing that regulatory associations are found for almost all genes, and describe the underlying molecular mechanisms and their contribution to allelic heterogeneity and pleiotropy of complex traits. Leveraging the large diversity of tissues, we provide insights into the tissue specificity of genetic effects and show that cell type composition is a key factor in understanding gene regulatory mechanisms in human tissues. We thank the donors and their families for their generous gifts of organ donation for transplantation and tissue donations for the GTEx research project; the Genomics Platform at the Broad Institute for data generation; J. Struewing for support and leadership of the GTEx project; M. Khan and C. Stolte for the illustrations in Fig. 1; and R. Do, D. Jordan, and M. Verbanck for providing GWAS pleiotropy scores. Funding: This work was supported by the Common Fund of the Office of the Director, U.S. National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, NIA, NIAID, and NINDS through NIH contracts HHSN261200800001E (Leidos Prime contract with NCI: A.M.S., D.E.T., N.V.R., J.A.M., L.S., M.E.B., L.Q., T.K., D.B., K.R., and A.U.), 10XS170 (NDRI: W.F.L., J.A.T., G.K., A.M., S.S., R.H., G.Wa., M.J., M.Wa., L.E.B., C.J., J.W., B.R., M.Hu., K.M., L.A.S., H.M.G., M.Mo., and L.K.B.), 10XS171 (Roswell Park Cancer Institute: B.A.F., M.T.M., E.K., B.M.G., K.D.R., and J.B.), 10X172 (Science Care Inc.), 12ST1039 (IDOX), 10ST1035 (Van Andel Institute: S.D.J., D.C.R., and D.R.V.), HHSN268201000029C (Broad Institute: F.A., G.G., K.G.A., A.V.S., X.Li., E.T., S.G., A.G., S.A., K.H.H., D.T.N., K.H., S.R.M., and J.L.N.), 5U41HG009494 (F.A., G.G., and K.G.A.), and through NIH grants R01 DA006227-17 (University of Miami Brain Bank: D.C.M. and D.A.D.), Supplement to University of Miami grant DA006227 (D.C.M. and D.A.D.), R01 MH090941 (University of Geneva), R01 MH090951 and R01 MH090937 (University of Chicago), R01 MH090936 (University of North Carolina–Chapel Hill), R01MH101814 (M.M.-A., V.W., S.B.M., R.G., E.T.D., D.G.-M., and A.V.), U01HG007593 (S.B.M.), R01MH101822 (C.D.B.), U01HG007598 (M.O. and B.E.S.), U01MH104393 (A.P.F.), extension H002371 to 5U41HG002371 (W.J.K.), as well as other funding sources: R01MH106842 (T.L., P.M., E.F., and P.J.H.), R01HL142028 (T.L., Si.Ka., and P.J.H.), R01GM122924 (T.L. and S.E.C.), R01MH107666 (H.K.I.), P30DK020595 (H.K.I.), UM1HG008901 (T.L.), R01GM124486 (T.L.), R01HG010067 (Y.Pa.), R01HG002585 (G.Wa. and M.St.), Gordon and Betty Moore Foundation GBMF 4559 (G.Wa. and M.St.), 1K99HG009916-01 (S.E.C.), R01HG006855 (Se.Ka. and R.E.H.), BIO2015-70777-P, Ministerio de Economia y Competitividad and FEDER funds (M.M.-A., V.W., R.G., and D.G.-M.), la Caixa Foundation ID 100010434 under agreement LCF/BQ/SO15/52260001 (D.G.-M.), NIH CTSA grant UL1TR002550-01 (P.M.), Marie-Skłodowska Curie fellowship H2020 Grant 706636 (S.K.-H.), R35HG010718 (E.R.G.), FPU15/03635, Ministerio de Educación, Cultura y Deporte (M.M.-A.),R01MH109905, 1R01HG010480 (A.Ba.), Searle Scholar Program (A.Ba.), R01HG008150 (S.B.M.), 5T32HG000044-22, NHGRI Institutional Training Grant in Genome Science (N.R.G.), EU IMI program (UE7-DIRECT-115317-1) (E.T.D. and A.V.), FNS funded project RNA1 (31003A_149984) (E.T.D. and A.V.), DK110919 (F.H.), F32HG009987 (F.H.), Massachusetts Lions Eye Research Fund Grant (A.R.H.), Wellcome grant WT108749/Z/15/Z (P.F.), and European Molecular Biology Laboratory (P.F. and D.Z.). Peer Reviewed "Article signat per 1 autors/es del BSC membres del THE GTEX CONSORTIUM: Marta Mele Messeguer"

BackgroundDNA methylation dynamics in the brain are associated with normal development and neuropsychiatric disease and differ across functionally distinct brain regions. Previous studies of genome-wide methylation differences among human brain regions focus on limited numbers of individuals and one to two brain regions.ResultsUsing GTEx samples, we generate a resource of DNA methylation in purified neuronal nuclei from 8 brain regions as well as lung and thyroid tissues from 12 to 23 donors. We identify differentially methylated regions between brain regions among neuronal nuclei in both CpG (181,146) and non-CpG (264,868) contexts, few of which were unique to a single pairwise comparison. This significantly expands the knowledge of differential methylation across the brain by 10-fold. In addition, we present the first differential methylation analysis among neuronal nuclei from basal ganglia tissues and identify unique CpG differentially methylated regions, many associated with ion transport. We also identify 81,130 regions of variably CpG methylated regions, i.e., variable methylation among individuals in the same brain region, which are enriched in regulatory regions and in CpG differentially methylated regions. Many variably methylated regions are unique to a specific brain region, with only 202 common across all brain regions, as well as lung and thyroid. Variably methylated regions identified in the amygdala, anterior cingulate cortex, and hippocampus are enriched for heritability of schizophrenia.ConclusionsThese data suggest that epigenetic variation in these particular human brain regions could be associated with the risk for this neuropsychiatric disorder.

Allele expression (AE) analysis robustly measures cis-regulatory effects. Here, we present and demonstrate the utility of a vast AE resource generated from the GTEx v8 release, containing 15,253 samples spanning 54 human tissues for a total of 431 million measurements of AE at the SNP level and 153 million measurements at the haplotype level. In addition, we develop an extension of our tool phASER that allows effect sizes of cis-regulatory variants to be estimated using haplotype-level AE data. This AE resource is the largest to date, and we are able to make haplotype-level data publicly available. We anticipate that the availability of this resource will enable future studies of regulatory variation across human tissues.

Background Meiosis is a specialized germ cell cycle that generates haploid gametes. In the initial stage of meiosis, meiotic prophase I (MPI), homologous chromosomes pair and recombine. Extensive changes in chromatin in MPI raise an important question concerning the contribution of epigenetic mechanisms such as DNA methylation to meiosis. Interestingly, previous studies concluded that in male mice, genome-wide DNA methylation patters are set in place prior to meiosis and remain constant subsequently. However, no prior studies examined DNA methylation during MPI in a systematic manner necessitating its further investigation. Results In this study, we used genome-wide bisulfite sequencing to determine DNA methylation of adult mouse spermatocytes at all MPI substages, spermatogonia and haploid sperm. This analysis uncovered transient reduction of DNA methylation (TRDM) of spermatocyte genomes. The genome-wide scope of TRDM, its onset in the meiotic S phase and presence of hemimethylated DNA in MPI are all consistent with a DNA replication-dependent DNA demethylation. Following DNA replication, spermatocytes regain DNA methylation gradually but unevenly, suggesting that key MPI events occur in the context of hemimethylated genome. TRDM also uncovers the prior deficit of DNA methylation of LINE-1 retrotransposons in spermatogonia resulting in their full demethylation during TRDM and likely contributing to the observed mRNA and protein expression of some LINE-1 elements in early MPI. Conclusions Our results suggest that contrary to the prevailing view, chromosomes exhibit dynamic changes in DNA methylation in MPI. We propose that TRDM facilitates meiotic prophase processes and gamete quality control. Electronic supplementary material The online version of this article (10.1186/s13072-018-0186-0) contains supplementary material, which is available to authorized users.

Long non-coding RNA (lncRNA) genes have well-established and important impacts on molecular and cellular functions. However, among the thousands of lncRNA genes, it is still a major challenge to identify the subset with disease or trait relevance. To systematically characterize these lncRNA genes, we used Genotype Tissue Expression (GTEx) project v8 genetic and multi-tissue transcriptomic data to profile the expression, genetic regulation, cellular contexts, and trait associations of 14,100 lncRNA genes across 49 tissues for 101 distinct complex genetic traits. Using these approaches, we identified 1,432 lncRNA gene-trait associations, 800 of which were not explained by stronger effects of neighboring protein-coding genes. This included associations between lncRNA quantitative trait loci and inflammatory bowel disease, type 1 and type 2 diabetes, and coronary artery disease, as well as rare variant associations to body mass index.

In the study of DNA methylation, genetic variation between species, strains, or individuals can result in CpG sites that are exclusive to a subset of samples, and insertions and deletions can rearrange the spatial distribution of CpGs. How to account for this variation in an analysis of the interplay between sequence variation and DNA methylation is not well understood, especially when the number of CpG differences between samples is large. Here we use whole-genome bisulfite sequencing data on two highly divergent inbred mouse strains to study this problem. We find that while the large number of strain-specific CpGs necessitates considerations regarding the reference genomes used during alignment, properties such as CpG density are surprisingly conserved across the genome. We introduce a method for including strain-specific CpGs in differential analysis, and show that accounting for strain-specific CpGs increases the power to find differentially methylated regions between the strains. Our method uses smoothing to impute methylation levels at strain-specific sites, thereby allowing strain-specific CpGs to contribute to the analysis, and also allowing us to account for differences in the spatial occurrences of CpGs. Our results have implications for analysis of genetic variation and DNA methylation using bisulfite-converted DNA.

Kabuki syndrome 1 (KS1) is a Mendelian disorder of the epigenetic machinery caused by mutations in the gene encoding KMT2D, which methylates lysine 4 on histone H3 (H3K4). KS1 is characterized by intellectual disability, postnatal growth retardation, and distinct craniofacial dysmorphisms. A mouse model (Kmt2d+/ β Geo) exhibits features of the human disorder and has provided insight into other phenotypes; however, the mechanistic basis of skeletal abnormalities and growth retardation remains elusive. Using high-resolution micro-computed tomography we show thatKmt2d+/βGeomice have shortened long bones and ventral bowing of skulls.In vivoexpansion of growth plates within both the skull and long bones suggests disrupted endochondral ossification as a common disease mechanism. Stable chondrocyte cell lines harboring inactivating mutations inKmt2dexhibit increased proliferation and differentiation, which further supports this mechanism. A known inducer of chondrogenesis, SOX9, and its targets show markedly increased expression inKmt2d-/-chondrocytes. By transcriptome profiling, we identifyShox2as a putative KMT2D target. We propose that decreased KMT2D-mediated H3K4me3 atShox2releasesSox9inhibition and thereby leads to enhanced chondrogenesis, providing a novel and plausible explanation for precocious chondrocyte differentiation. Our findings not only provide insight into the pathogenesis of growth retardation in KS1, but also suggest novel therapeutic targets to rescue growth retardation in KS1 and related disorders.

Publisher's version (útgefin grein), Coding variants in epigenetic regulators are emerging as causes of neurological dysfunction and cancer. However, a comprehensive effort to identify disease candidates within the human epigenetic machinery (EM) has not been performed; it is unclear whether features exist that distinguish between variation-intolerant and variation-tolerant EM genes, and between EM genes associated with neurological dysfunction versus cancer. Here, we rigorously define 295 genes with a direct role in epigenetic regulation (writers, erasers, remodelers, readers). Systematic exploration of these genes reveals that although individual enzymatic functions are always mutually exclusive, readers often also exhibit enzymatic activity (dual-function EM genes). We find that the majority of EM genes are very intolerant to loss-of-function variation, even when compared to the dosage sensitive transcription factors, and we identify 102 novel EM disease candidates. We show that this variation intolerance is driven by the protein domains encoding the epigenetic function, suggesting that disease is caused by a perturbed chromatin state. We then describe a large subset of EM genes that are coexpressed within multiple tissues. This subset is almost exclusively populated by extremely variation-intolerant genes and shows enrichment for dual-function EM genes. It is also highly enriched for genes associated with neurological dysfunction, even when accounting for dosage sensitivity, but not for cancer-associated EM genes. Finally, we show that regulatory regions near epigenetic regulators are genetically important for common neurological traits. These findings prioritize novel disease candidate EM genes and suggest that this coexpression plays a functional role in normal neurological homeostasis., This research was supported by the National Institute of General Medical Sciences of the National Institutes of Health under award numbers R01GM121459 and DP5OD017877. L.B. was supported by the Maryland Genetics, Epidemiology and Medicine (MD-GEM) training program, funded by the Burroughs-Wellcome Fund. H.T.B. received support from the Louma G. Foundation. L.B., H.T.B., and K.D.H. received support from a Discovery Award from Johns Hopkins University. J.M.H. and A.R.Q. were supported by National Institutes of Health awards from the National Human Genome Research Institute (R01HG006693 and R01HG009141) and the National Institute of General Medical Sciences (R01GM124355). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

BackgroundThe 3-dimensional (3D) conformation of chromatin inside the nucleus is integral to a variety of nuclear processes including transcriptional regulation, DNA replication, and DNA damage repair. Aberrations in 3D chromatin conformation have been implicated in developmental abnormalities and cancer. Despite the importance of 3D chromatin conformation to cellular function and human health, little is known about how 3D chromatin conformation varies in the human population, or whether DNA sequence variation between individuals influences 3D chromatin conformation.ResultsTo address these questions, we perform Hi-C on lymphoblastoid cell lines from 20 individuals. We identify thousands of regions across the genome where 3D chromatin conformation varies between individuals and find that this variation is often accompanied by variation in gene expression, histone modifications, and transcription factor binding. Moreover, we find that DNA sequence variation influences several features of 3D chromatin conformation including loop strength, contact insulation, contact directionality, and density of local cis contacts. We map hundreds of quantitative trait loci associated with 3D chromatin features and find evidence that some of these same variants are associated at modest levels with other molecular phenotypes as well as complex disease risk.ConclusionOur results demonstrate that common DNA sequence variants can influence 3D chromatin conformation, pointing to a more pervasive role for 3D chromatin conformation in human phenotypic variation than previously recognized.

Chromatin modifiers act to coordinate gene expression changes critical to neuronal differentiation from neural stem/progenitor cells (NSPCs). Lysine-specific methyltransferase 2D (KMT2D) encodes a histone methyltransferase that promotes transcriptional activation, and is frequently mutated in cancers and in the majority (>70%) of patients diagnosed with the congenital, multisystem intellectual disability (ID) disorder Kabuki syndrome 1 (KS1). Critical roles for KMT2D are established in various non-neural tissues, but the effects of KMT2D loss in brain cell development have not been described. We conducted parallel studies of proliferation, differentiation, transcription, and chromatin profiling in KMT2D-deficient human and mouse models to define KMT2D-regulated functions in neurodevelopmental contexts, including adult-born hippocampal NSPCs in vivo and in vitro. We report cell-autonomous defects in proliferation, cell cycle, and survival, accompanied by early NSPC maturation in several KMT2D-deficient model systems. Transcriptional suppression in KMT2D-deficient cells indicated strong perturbation of hypoxia-responsive metabolism pathways. Functional experiments confirmed abnormalities of cellular hypoxia responses in KMT2D-deficient neural cells, and accelerated NSPC maturation in vivo. Together, our findings support a model in which loss of KMT2D function suppresses expression of oxygen-responsive gene programs important to neural progenitor maintenance, resulting in precocious neuronal differentiation in a mouse model of KS1.Graphical Abstract

Massively parallel reporter assays (MPRAs) have emerged as a popular means for understanding noncoding variation in a variety of conditions. While a large number of experiments have been described in the literature, analysis typically uses ad-hoc methods. There has been little attention to comparing performance of methods across datasets.We present the mpralm method which we show is calibrated and powerful, by analyzing its performance on multiple MPRA datasets. We show that it outperforms existing statistical methods for analysis of this data type, in the first comprehensive evaluation of statistical methods on several datasets. We investigate theoretical and real-data properties of barcode summarization methods and show an unappreciated impact of summarization method for some datasets. Finally, we use our model to conduct a power analysis for this assay and show substantial improvements in power by performing up to 6 replicates per condition, whereas sequencing depth has smaller impact; we recommend to always use at least 4 replicates. Together, these results inform recommendations for differential analysis, general group comparisons, and power analysis and will help improve design and analysis of MPRA experiments. An R package is available from the Bioconductor project athttps://bioconductor.org/packages/mpra.

Determining protein levels in each tissue and how they compare with RNA levels is important for understanding human biology and disease as well as regulatory processes that control protein levels. We quantified the relative protein levels from 12,627 genes across 32 normal human tissue types prepared by the GTEx project. Known and new tissue specific or enriched proteins (5,499) were identified and compared to transcriptome data. Many ubiquitous transcripts are found to encode highly tissue specific proteins. Discordance in the sites of RNA expression and protein detection also revealed potential sites of synthesis and action of protein signaling molecules. Overall, these results provide an extraordinary resource, and demonstrate that understanding protein levels can provide insights into metabolism, regulation, secretome, and human diseases.SummaryQuantitative proteome study of 32 human tissues and integrated analysis with transcriptome data revealed that understanding protein levels could provide in-depth knowledge to post transcriptional or translational regulations, human metabolism, secretome, and diseases.

Recent genome-wide association studies (GWAS) identified numerous schizophrenia (SZ) and Alzheimer’s disease (AD) associated loci, most outside protein-coding regions and hypothesized to affect gene transcription. We used a massively parallel reporter assay (MPRA) to screen, 1,049 SZ and 30 AD variants in 64 and 9 loci respectively for allele differences in driving reporter gene expression. A library of synthetic oligonucleotides assaying each allele 5 times was transfected into K562 chronic myelogenous leukemia lymphoblasts and SK-SY5Y human neuroblastoma cells. 148 variants showed allelic differences in K562 and 53 in SK-SY5Y cells, on average 2.6 variants per locus. Nine showed significant differences in both lines, a modest overlap reflecting different regulatory landscapes of these lines that also differ significantly in chromatin marks. Eight of nine were in the same direction. We observe no preference for risk alleles to increase or decrease expression. We find a positive correlation between the number of SNPs in Linkage Disequilibrium (LD) and the proportion of functional SNPs supporting combinatorial effects that may lead to haplotype selection. Our results prioritize future functional follow up of disease associated SNPs to determine the driver GWAS variant(s), at each locus and enhance our understanding of gene regulation dynamics.

Coding variants in genes encoding for epigenetic regulators are an emerging cause of neurological dysfunction and cancer. However, a systematic effort to identify disease candidates within the human epigenetic machinery (EM) has not been performed, and it is unclear whether features exist that distinguish between variation-intolerant and variation-tolerant EM genes, and between EM genes associated with neurological dysfunction versus cancer. Here, we rigorously define a set of 295 human genes with a direct role in epigenetic regulation (writers, erasers, remodelers, readers). Systematic exploration of these genes reveals that while individual enzymatic functions are always mutually exclusive, readers often also exhibit enzymatic activity as well (dual function EM genes). We find that the majority of EM genes are very intolerant to loss-of-function variation, even when compared to the dosage sensitive group of transcription factors. Using this strategy, we identify 103 novel EM disease candidates. We show that the intolerance to loss-of-function variation is driven by the protein domains encoding the epigenetic function, strongly suggesting that disease is caused by a perturbed chromatin state. Unexpectedly, we also describe a large subset of EM genes that are co-expressed within multiple tissues. This subset is almost exclusively populated by extremely variation-intolerant EM genes, and shows enrichment for dual function EM genes. It is also highly enriched for genes associated with neurological dysfunction, even when accounting for dosage sensitivity, but not for cancer-associated EM genes. These findings prioritize novel disease candidate EM genes, and suggest that the co-expression itself may play a functional role in normal neurological homeostasis.

Gene co-expression networks capture biologically important patterns in gene expression data, enabling functional analyses of genes, discovery of biomarkers, and interpretation of regulatory genetic variants. Most network analyses to date have been limited to assessing correlation between total gene expression levels in a single or small sets of tissues. Here, we have reconstructed networks that capture a much more complete set of regulatory relationships, specifically including regulation of relative isoform abundance and splicing, and tissue-specific connections unique to each of a diverse set of tissues. Using the Genotype-Tissue Expression (GTEx) project v6 RNA-sequencing data across 44 tissues in 449 individuals, we evaluated shared and tissue-specific network relationships. First, we developed a framework called Transcriptome Wide Networks (TWNs) for combining total expression and relative isoform levels into a single sparse network, capturing the complex interplay between the regulation of splicing and transcription. We built TWNs for sixteen tissues, and found that hubs with isoform node neighbors in these networks were strongly enriched for splicing and RNA binding genes, demonstrating their utility in unraveling regulation of splicing in the human transcriptome, and providing a set of candidate shared and tissue-specific regulatory hub genes. Next, we used a Bayesian biclustering model that identifies network edges between genes with co-expression in a single tissue to reconstruct tissue-specific networks (TSNs) for 27 distinct GTEx tissues and for four subsets of related tissues. Using both TWNs and TSNs, we characterized gene co-expression patterns shared across tissues. Finally, we found genetic variants associated with multiple neighboring nodes in our networks, supporting the estimated network structures and identifying 33 genetic variants with distant regulatory impact on transcription and splicing. Our networks provide an improved understanding of the complex relationships between genes in the human transcriptome, including tissue-specificity of gene co-expression, regulation of splicing, and the coordinated impact of genetic variation on transcription.

Barrington et al. examined the effect of four human diets (American, Mediterranean, Japanese, and Maasai/ketogenic) on metabolic health across four mouse..., The incidence of diet-induced metabolic disease has soared over the last half-century, despite national efforts to improve health through universal dietary recommendations. Studies comparing dietary patterns of populations with health outcomes have historically provided the basis for healthy diet recommendations. However, evidence that population-level diet responses are reliable indicators of responses across individuals is lacking. This study investigated how genetic differences influence health responses to several popular diets in mice, which are similar to humans in genetic composition and the propensity to develop metabolic disease, but enable precise genetic and environmental control. We designed four human-comparable mouse diets that are representative of those eaten by historical human populations. Across four genetically distinct inbred mouse strains, we compared the American diet’s impact on metabolic health to three alternative diets (Mediterranean, Japanese, and Maasai/ketogenic). Furthermore, we investigated metabolomic and epigenetic alterations associated with diet response. Health effects of the diets were highly dependent on genetic background, demonstrating that individualized diet strategies improve health outcomes in mice. If similar genetic-dependent diet responses exist in humans, then a personalized, or “precision dietetics,” approach to dietary recommendations may yield better health outcomes than the traditional one-size-fits-all approach.

Epigenetic modifications confer stable transcriptional patterns in the brain, and both normal and abnormal brain function involve specialized brain regions, yet little is known about brain region-specific epigenetic differences. Here, we compared prefrontal cortex, anterior cingulate gyrus, hippocampus and nucleus accumbens from 6 individuals, performing whole genome bisulfite sequencing for DNA methylation. In addition, we have performed ATAC-seq for chromatin accessibility, and RNA-seq for gene expression in the nucleus accumbens and prefrontal cortex from 6 additional individuals. We found substantial neuron- and brain region-specific differences in both DNA methylation and chromatin accessibility which were largely non-overlapping, and were greatest between nucleus accumbens and the other regions. In contrast, glial methylation and chromatin were relatively homogeneous across brain regions, although neuron/glia ratios varied greatly, demonstrating the necessity for cellular fractionation. Gene expression was also largely the same across glia from different brain regions and substantially different for neurons. Expression was correlated with methylation and accessibility across promoters and known enhancers. Several classes of transcription factor binding sites were enriched at regions of differential methylation and accessibility, including many that respond to synaptic activity. Finally, both regions of differential methylation and those of differential accessibility showed a surprising >10-fold enrichment of explained heritability associated with addictive behavior, as well as schizophrenia- and neuroticism-associated regions, suggesting that common psychiatric illness is mediated through brain region-specific epigenetic marks.

Correcting for cell-type heterogeneity in epigenome-wide association studies: revisiting previous analyses

Kabuki syndrome is a Mendelian intellectual disability syndrome caused by mutations in either of two genes (KMT2D and KDM6A) involved in chromatin accessibility. We previously showed that an agent that promotes chromatin opening, the histone deacetylase inhibitor (HDACi) AR-42, ameliorates the deficiency of adult neurogenesis in the granule cell layer of the dentate gyrus and rescues hippocampal memory defects in a mouse model of Kabuki syndrome (Kmt2d+/βGeo). Unlike a drug, a dietary intervention could be quickly transitioned to the clinic. Therefore, we have explored whether treatment with a ketogenic diet could lead to a similar rescue through increased amounts of beta-hydroxybutyrate, an endogenous HDACi. Here, we report that a ketogenic diet in Kmt2d+/βGeo mice modulates H3ac and H3K4me3 in the granule cell layer, with concomitant rescue of both the neurogenesis defect and hippocampal memory abnormalities seen in Kmt2d+/βGeo mice; similar effects on neurogenesis were observed on exogenous administration of beta-hydroxybutyrate. These data suggest that dietary modulation of epigenetic modifications through elevation of beta-hydroxybutyrate may provide a feasible strategy to treat the intellectual disability seen in Kabuki syndrome and related disorders.

DNA methylation at the 5-position of cytosine (5mC) is an epigenetic modification that regulates gene expression and cellular plasticity in development and disease. The ten-eleven translocation (TET) gene family oxidizes 5mC to 5-hydroxymethylcytosine (5hmC), providing an active mechanism for DNA demethylation, and it may also provide its own regulatory function. Here we applied oxidative bisulfite sequencing to generate whole-genome DNA methylation and hydroxymethylation maps at single-base resolution in human normal liver and lung as well as paired tumor tissues. We found that 5hmC is significantly enriched in CpG island (CGI) shores while depleted in CGIs themselves, especially in active genes, which exhibit a bimodal distribution of 5hmC around CGI that corresponds to H3K4me1 modifications. Hydroxymethylation on promoters, gene bodies, and transcription termination regions (TTRs) showed strong positive correlation with gene expression within and across tissues, suggesting that 5hmC is a marker of active genes and could play a role in gene expression mediated by DNA demethylation. Comparative analysis of methylomes and hydroxymethylomes revealed that 5hmC is significantly enriched in both tissue-specific DMRs (t-DMRs) and cancer-specific DMRs (c-DMRs), and 5hmC is negatively correlated with methylation changes, especially in non-CGI-associated DMRs. These findings revealed novel reciprocity between epigenetic markers at CGI shores corresponding to differential gene expression in normal tissues and matching tumors. Overall, our study provided a comprehensive analysis of the interplay between the methylome, hydroxymethylome, and histone modifications during tumorigenesis.

Gene annotations, such as those in GENCODE, are derived primarily from alignments of spliced cDNA sequences and protein sequences. The impact of RNA-seq data on annotation has been confined to major projects like ENCODE and Illumina Body Map 2.0. We aligned 21,504 Illumina-sequenced human RNA-seq samples from the Sequence Read Archive (SRA) to the human genome and compared detected exon-exon junctions with junctions in several recent gene annotations. We found 56,861 junctions (18.6%) in at least 1000 samples that were not annotated, and their expression associated with tissue type. Junctions well expressed in individual samples tended to be annotated. Newer samples contributed few novel well-supported junctions, with the vast majority of detected junctions present in samples before 2013. We compiled junction data into a resource called intropolis available at http://intropolis.rail.bio . We used this resource to search for a recently validated isoform of the ALK gene and characterized the potential functional implications of unannotated junctions with publicly available TRAP-seq data. Considering only the variation contained in annotation may suffice if an investigator is interested only in well-expressed transcript isoforms. However, genes that are not generally well expressed and nonetheless present in a small but significant number of samples in the SRA are likelier to be incompletely annotated. The rate at which evidence for novel junctions has been added to the SRA has tapered dramatically, even to the point of an asymptote. Now is perhaps an appropriate time to update incomplete annotations to include splicing present in the now-stable snapshot provided by the SRA.

Altered DNA methylation occurs ubiquitously in human cancer from the earliest measurable stages. A cogent approach to understanding the mechanism and timing of altered DNA methylation is to analyze it in the context of carcinogenesis by a defined agent. Epstein-Barr virus (EBV) is a human oncogenic herpesvirus associated with lymphoma and nasopharyngeal carcinoma, but also used commonly in the laboratory to immortalize human B-cells in culture. Here we have performed whole-genome bisulfite sequencing of normal B-cells, activated B-cells, and EBV-immortalized B-cells from the same three individuals, in order to identify the impact of transformation on the methylome. Surprisingly, large-scale hypomethylated blocks comprising two-thirds of the genome were induced by EBV immortalization but not by B-cell activation per se. These regions largely corresponded to hypomethylated blocks that we have observed in human cancer, and they were associated with gene-expression hypervariability, similar to human cancer, and consistent with a model of epigenomic change promoting tumor cell heterogeneity. We also describe small-scale changes in DNA methylation near CpG islands. These results suggest that methylation disruption is an early and critical step in malignant transformation.

Autism spectrum disorders (ASD) are increasingly common neurodevelopmental disorders defined clinically by a triad of features including impairment in social interaction, impairment in communication in social situations, and restricted and repetitive patterns of behavior and interests, with considerable phenotypic heterogeneity among individuals. Although heritability estimates for ASD are high, conventional genetic-based efforts to identify genes involved in ASD have yielded only few reproducible candidate genes that account for only a small proportion of ASDs. There is mounting evidence to suggest environmental and epigenetic factors play a stronger role in the etiology of ASD than previously thought. To begin to understand the contribution of epigenetics to ASD, we have examined DNA methylation (DNAm) in a pilot study of post-mortem brain tissue from 19 autism cases and 21 unrelated controls, among three brain regions including dorsolateral prefrontal cortex, temporal cortex, and cerebellum. We measured over 485,000 CpG loci across a diverse set of functionally relevant genomic regions using the Infinium HumanMethylation450 BeadChip and identified 4 genome-wide significant differentially methylated regions (DMRs) using a novel bumphunting approach and a permutation-based multiple testing correction method. We replicated 3/4 DMRs identified in our genome-wide screen in a different set of samples and across different brain regions. The DMRs identified in this study represent suggestive evidence for commonly altered methylation sites in ASD and provide several promising new candidate genes.

DNA methylation at the 5-postion of cytosine (5mC) is a well-established epigenetic modification which regulates gene expression and cellular plasticity in development and disease. The ten-eleven translocation (TET) gene family is able to oxidize 5mC to 5-hydroxymethyl-cytosine (5hmC), providing an active mechanism for DNA demethylation, and may also provide its own regulatory function. Here we applied oxidative bisulfite sequencing to generate whole-genome DNA methylation and hydroxymethylation maps at single-base resolution in paired human liver and lung normal and cancer. We found that 5hmC is significantly enriched in CpG island (CGI) shores while depleted in CGIs themselves, in particular at active genes, resulting in a 5hmC but not 5mC bimodal distribution around CGI corresponding to H3K4me1 marks. Hydroxymethylation on promoters, gene bodies, and transcription termination regions showed strong positive correlation with gene expression within and across tissues, suggesting that 5hmC is a mark of active genes and could play a role gene expression mediated by DNA demethylation. Comparative analysis of methylomes and hydroxymethylomes revealed that 5hmC is significantly enriched in both tissue specific DMRs (t-DMRs) and cancer specific DMRs (c-DMRs), and 5hmC is negatively correlated with methylation changes, particularly in non-CGI associated DMRs. Together these findings indicate that changes in 5mC as well as in 5hmC and coupled to H3K4me1 correspond to differential gene expression in tissues and matching tumors, revealing an intricate gene expression regulation through interplay of methylome, hydroxyl-methylome, and histone modifications.

BackgroundThe Illumina 450K array has been widely used in epigenetic association studies. Current quality-control (QC) pipelines typically remove certain sets of probes, such as those containing a SNP or with multiple mapping locations. An additional set of potentially problematic probes are those with DNA methylation (DNAm) distributions characterized by two or more distinct clusters separated by gaps. Data-driven identification of such probes may offer additional insights for downstream analyses.ResultsWe developed a procedure, termed “gap hunting”, to identify probes showing clustered distributions. Among 590 peripheral blood samples from the Study to Explore Early Development, we identified 11,007 “gap probes”. The vast majority (9,199) are likely attributed to an underlying SNP(s) or other variant in the probe, although SNP-affected probes exist that do not produce a gap signals. Specific factors predict which SNPs lead to gap signals, including type of nucleotide change, probe type, DNA strand, and overall methylation state. These expected effects are demonstrated in paired genotype and 450k data on the same samples. Gap probes can also serve as a surrogate for the local genetic sequence on a haplotype scale and can be used to adjust for population stratification.ConclusionsThe characteristics of gap probes reflect potentially informative biology. QC pipelines may benefit from an efficient data-driven approach that “flags” gap probes, rather than filtering such probes, followed by careful interpretation of downstream association analyses. Our results should translate directly to the recently released Illumina 850K EPIC array given the similar chemistry and content design.

We aligned 21,504 publicly available Illumina-sequenced human RNA-seq samples from the Sequence Read Archive (SRA) to the human genome and compared detected exon-exon junctions with junctions in several recent gene annotations. 56,865 junctions (18.6%) found in at least 1,000 samples were not annotated, and their expression associated with tissue type. Newer samples contributed few novel well-supported junctions, with 96.1% of junctions detected in at least 20 reads across samples present in samples before 2013. Junction data is compiled into a resource called intropolis available at http://intropolis.rail.bio. We discuss an application of this resource to cancer involving a recently validated isoform of the ALK gene.

Chronic hepatitis C virus (HCV) infection is complicated by hepatic fibrosis. Hypothesizing that early fibrogenic signals may originate in cells susceptible to HCV infection, hepatocyte gene expression was analyzed from persons with chronic HCV at different stages of liver fibrosis. Four HCV-infected subjects with pre-cirrhotic liver fibrosis (Ishak fibrosis 3–5) were matched for age, race, and gender to five HCV-infected subjects with no evidence of fibrosis (Ishak fibrosis 0). Hepatocytes from each subject were isolated from liver biopsies using laser capture microdissection. Transcriptome profiling was performed on hepatocyte RNA using hybridization arrays. We found that hepatocytes in pre-cirrhotic fibrosis were depleted for genes involved in small molecule and drug metabolism, especially butyrylcholinesterase (BCHE), a gene involved in the metabolism of drugs of abuse. Differential expression of BCHE was validated in the same tissues and cross-sectionally in an expanded cohort of 143 HCV-infected individuals. In a longitudinal study, serum BCHE activity were already decreased at study inception in 19 fibrosis progressors compared to 20 fibrosis non-progressors (p

DNA methylation is an epigenetic modification with important functions in development. Large-scale loss of DNA methylation is a hallmark of cancer. Recent work has identified large genomic blocks of hypomethylation associated with cancer, EBV transformation and replicative senescence, all of which change the proportion of actively proliferating cells within the population measured. We asked if replication or cell-cycle arrest affects the global levels of methylation or leads to hypomethylated blocks as observed in other settings. We used fluorescence activated cell sorting to isolate primary dermal fibroblasts in G0, G1 and G2 based on DNA content and Ki67 staining. We additionally examined G0 cells arrested by contact inhibition for one week to determine the effects of extended arrest. We analyzed genome wide DNA methylation from sorted cells using whole genome bisulfite sequencing. This analysis demonstrated no global changes or large-scale hypomethylated blocks in any of the examined cell cycle phases, indicating that global levels of methylation are stable with replication and arrest.

DNA methylation is an epigenetic mark thought to be robust to environmental perturbations on a short time scale. Here, we challenge that view by demonstrating that the infection of human dendritic cells (DCs) with a live pathogenic bacteria is associated with rapid and active demethylation at thousands of loci, independent of cell division. We performed an integrated analysis of data on genome-wide DNA methylation, histone mark patterns, chromatin accessibility, and gene expression, before and after infection. We found that infection-induced demethylation rarely occurs at promoter regions and instead localizes to distal enhancer elements, including those that regulate the activation of key immune transcription factors. Active demethylation is associated with extensive epigenetic remodeling, including the gain of histone activation marks and increased chromatin accessibility, and is strongly predictive of changes in the expression levels of nearby genes. Collectively, our observations show that active, rapid changes in DNA methylation in enhancers play a previously unappreciated role in regulating the transcriptional response to infection, even in nonproliferating cells., Reseau de Medecine Genetique Appliquee (Fellowship)

Summary Tumor heterogeneity is a major barrier to effective cancer diagnosis and treatment. We recently identified cancer-specific differentially DNA-methylated regions (cDMRs) in colon cancer, which also distinguish normal tissue types from each other, suggesting that these cDMRs might be generalized across cancer types. Here we show stochastic methylation variation of the same cDMRs, distinguishing cancer from normal, in colon, lung, breast, thyroid, and Wilms tumors, with intermediate variation in adenomas. Whole genome bisulfite sequencing shows these variable cDMRs are related to loss of sharply delimited methylation boundaries at CpG islands. Furthermore, we find hypomethylation of discrete blocks encompassing half the genome, with extreme gene expression variability. Genes associated with the cDMRs and large blocks are involved in mitosis and matrix remodeling, respectively. These data suggest a model for cancer involving loss of epigenetic stability of well-defined genomic domains that underlies increased methylation variability in cancer and could contribute to tumor heterogeneity.

Alternative splicing is a process by which multiple messenger RNAs (mRNAs) can be generated by joining exons together in different combinations. This process is used to both increase protein diversity and to regulate gene expression (Nilsen and Graveley 2010). Approximately 95% of human genes contain introns and therefore have the potential to be alternatively spliced. Recent deep sequencing surveys of 10 human tissues found that nearly all (95%–98%) multi-exon human genes are alternatively spliced (Pan et al. 2008; Wang et al. 2008). Given the ubiquity of alternative splicing and the key roles it plays in the control of gene expression, it is important to develop a complete understanding of the mechanisms by which alternative splicing is regulated. Alternative splicing is most commonly controlled by RNA binding proteins that bind to sequence elements called enhancers and silencers (Nilsen and Graveley 2010). Splicing regulators bound to these enhancers or silencers are thought to either recruit or inhibit assembly or activity of spliceosomal components at nearby splice sites. The best-characterized splicing regulator proteins are the SR and hnRNP protein families. SR proteins primarily bind to enhancer sequences in exons where they activate adjacent splice sites, while hnRNPs have mostly been shown to suppress splicing when bound to intronic silencers. In addition to SR and hnRNPs proteins, several other splicing regulators have been identified that function in a tissue specific manner (Chen and Manley 2009). The mammalian proteins NOVA1 and NOVA2 (collectively named here as NOVA) are perhaps the best-characterized splicing regulators to date. NOVA1/2 encode RNA binding proteins with three KH-domains that recognize clusters of YCAY repeats. Over the past decade, several hundred splicing events have been shown to be regulated by NOVA1/2 (Ule et al. 2005, 2006; Licatalosi et al. 2008). A comparison of the locations of the NOVA1/2 binding sites with NOVA-regulated splicing events has revealed a stereotypical “RNA map” for NOVA1/2. Specifically, regions upstream of exons where NOVA inhibits splicing and regions downstream from exons where NOVA activates splicing were enriched with NOVA binding sites (Ule et al. 2006; Licatalosi et al. 2008). Similar “RNA maps” that link the position of binding sites to typical activities of the regulatory proteins have also been developed for mammalian FOX1/2 (Zhang et al. 2008; Yeo et al. 2009), PTB (Xue et al. 2009), and four D. melanogaster hnRNP proteins (Blanchette et al. 2009). Such maps, splicing expression data, and RNA sequence motifs have recently been used to predict regulated tissue-specific splicing changes in mouse, strongly supporting the existence of a splicing code (Wang and Burge 2008; Barash et al. 2010; Zhang et al. 2010), a decipherable sequence-based information system that dictates the splicing pattern of a given pre-mRNA under a specific condition. Though considerable progress has been made, interpreting this code remains a formidable task in the field. In particular, it is unclear how the mouse splicing code can be applied to different species, especially distantly related organisms such as Drosophila. Moreover, the extent to which the RNA maps of individual splicing regulators are static or plastic throughout evolution has been unknown. We were interested in exploring the conservation of the splicing code between distantly related organisms. As a first step in this process, we sought to generate an RNA map of Pasilla (PS) (Seshaiah et al. 2001), the D. melanogaster ortholog of NOVA1/2. To identify PS-regulated exons, we used RNA-seq (Wold and Myers 2008) to identify splicing events that changed upon depletion of PS by RNAi. We conclude that the RNA map of PS and NOVA1/2 is highly conserved between mammals and insects.

Analysis of Hi-C data has shown that the genome can be divided into two compartments called A/B compartments. These compartments are cell-type specific and are associated with open and closed chromatin. We show that A/B compartments can be reliably estimated using epigenetic data from several different platforms, the Illumina 450k DNA methylation microarray, DNase hypersensitivity sequencing, single-cell ATAC sequencing and single-cell whole-genome bisulfite sequencing. We do this by exploiting the fact that the structure of long range correlations differs between open and closed compartments. This work makes A/B compartments readily available in a wide variety of cell types, including many human cancers.

Background Aging and sun exposure are the leading causes of skin cancer. It has been shown that epigenetic changes, such as DNA methylation, are well established mechanisms for cancer, and also have emerging roles in aging and common disease. Here, we directly ask whether DNA methylation is altered following skin aging and/or chronic sun exposure in humans. Results We compare epidermis and dermis of both sun-protected and sun-exposed skin derived from younger subjects (under 35 years old) and older subjects (over 60 years old), using the Infinium HumanMethylation450 array and whole genome bisulfite sequencing. We observe large blocks of the genome that are hypomethylated in older, sun-exposed epidermal samples, with the degree of hypomethylation associated with clinical measures of photo-aging. We replicate these findings using whole genome bisulfite sequencing, comparing epidermis from an additional set of younger and older subjects. These blocks largely overlap known hypomethylated blocks in colon cancer and we observe that these same regions are similarly hypomethylated in squamous cell carcinoma samples. Conclusions These data implicate large scale epigenomic change in mediating the effects of environmental damage with photo-aging. Electronic supplementary material The online version of this article (doi:10.1186/s13059-015-0644-y) contains supplementary material, which is available to authorized users.

DNA methylation is thought to be robust to environmental perturbations on a short time scale. Here, we challenge that view by demonstrating that the infection of human dendritic cells (DCs) with a pathogenic bacteria is associated with rapid changes in methylation at thousands of loci. Infection-induced changes in methylation occur primarily at distal enhancer elements, including those associated with the activation of key immune transcription factors and genes involved in the crosstalk between DCs and adaptive immunity. Active demethylation is associated with extensive epigenetic remodeling and is strongly predictive of changes in the expression levels of nearby genes. Collectively, our observations show that rapid changes in methylation play a previously unappreciated role in regulating the transcriptional response of DCs to infection.

Food allergy (FA) affects 2%-10% of US children and is a growing clinical and public health problem. Here we conduct the first genome-wide association study of well-defined FA, including specific subtypes (peanut, milk and egg) in 2,759 US participants (1,315 children and 1,444 parents) from the Chicago Food Allergy Study, and identify peanut allergy (PA)-specific loci in the HLA-DR and -DQ gene region at 6p21.32, tagged by rs7192 (P=5.5 × 10(-8)) and rs9275596 (P=6.8 × 10(-10)), in 2,197 participants of European ancestry. We replicate these associations in an independent sample of European ancestry. These associations are further supported by meta-analyses across the discovery and replication samples. Both single-nucleotide polymorphisms (SNPs) are associated with differential DNA methylation levels at multiple CpG sites (P

In honeybee societies, distinct caste phenotypes are created from the same genotype, suggesting a role for epigenetics in deriving these behaviorally different phenotypes. We found no differences in DNA methylation between irreversible worker and queen castes, but substantial differences between nurses and forager subcastes. Reverting foragers back to nurses reestablished methylation levels for a majority of genes and provides, to the best of our knowledge, the first evidence in any organism of reversible epigenetic changes associated with behavior.

Kabuki syndrome is caused by haploinsufficiency for either of two genes that promote the opening of chromatin. If an imbalance between open and closed chromatin is central to the pathogenesis of Kabuki syndrome, agents that promote chromatin opening might have therapeutic potential. We have characterized a mouse model of Kabuki syndrome with a heterozygous deletion in the gene encoding the lysine-specific methyltransferase 2D (Kmt2d), leading to impairment of methyltransferase function. In vitro reporter alleles demonstrated a reduction in histone 4 acetylation and histone 3 lysine 4 trimethylation (H3K4me3) activity in mouse embryonic fibroblasts from Kmt2d(+/βGeo) mice. These activities were normalized in response to AR-42, a histone deacetylase inhibitor. In vivo, deficiency of H3K4me3 in the dentate gyrus granule cell layer of Kmt2d(+/βGeo) mice correlated with reduced neurogenesis and hippocampal memory defects. These abnormalities improved upon postnatal treatment with AR-42. Our work suggests that a reversible deficiency in postnatal neurogenesis underlies intellectual disability in Kabuki syndrome.

Motivation: The recently released Infinium HumanMethylation450 array (the ‘450k’ array) provides a high-throughput assay to quantify DNA methylation (DNAm) at ∼450 000 loci across a range of genomic features. Although less comprehensive than high-throughput sequencing-based techniques, this product is more cost-effective and promises to be the most widely used DNAm high-throughput measurement technology over the next several years. Results: Here we describe a suite of computational tools that incorporate state-of-the-art statistical techniques for the analysis of DNAm data. The software is structured to easily adapt to future versions of the technology. We include methods for preprocessing, quality assessment and detection of differentially methylated regions from the kilobase to the megabase scale. We show how our software provides a powerful and flexible development platform for future methods. We also illustrate how our methods empower the technology to make discoveries previously thought to be possible only with sequencing-based methods. Availability and implementation: http://bioconductor.org/packages/release/bioc/html/minfi.html. Contact: khansen@jhsph.edu; rafa@jimmy.harvard.edu Supplementary information: Supplementary data are available at Bioinformatics online.

RNA-sequencing (RNA-seq) is a flexible technology for measuring genome-wide expression that is rapidly replacing microarrays as costs become comparable. Current differential expression analysis methods for RNA-seq data fall into two broad classes: (1) methods that quantify expression within the boundaries of genes previously published in databases and (2) methods that attempt to reconstruct full length RNA transcripts. The first class cannot discover differential expression outside of previously known genes. While the second approach does possess discovery capabilities, statistical analysis of differential expression is complicated by the ambiguity and variability incurred while assembling transcripts and estimating their abundances. Here, we propose a novel method that first identifies differentially expressed regions (DERs) of interest by assessing differential expression at each base of the genome. The method then segments the genome into regions comprised of bases showing similar differential expression signal, and then assigns a measure of statistical significance to each region. Optionally, DERs can be annotated using a reference database of genomic features. We compare our approach with leading competitors from both current classes of differential expression methods and highlight the strengths and weaknesses of each. A software implementation of our method is available on github (https://github.com/alyssafrazee/derfinder).