Robust Hi-C Maps of Enhancer-Promoter Interactions Reveal the Function of Non-coding Genome in Neural Development and Diseases.

Genome-wide mapping of chromatin interactions at high resolution remains experimentally and computationally challenging. Here we used a low-input "easy Hi-C" protocol to map the 3D genome architecture in human neurogenesis and brain tissues and also demonstrated that a rigorous Hi-C bias-correction pipeline (HiCorr) can significantly improve the sensitivity and robustness of Hi-C loop identification at sub-TAD level, especially the enhancer-promoter (E-P) interactions. We used HiCorr to compare the high-resolution maps of chromatin interactions from 10 tissue or cell types with a focus on neurogenesis and brain tissues. We found that dynamic chromatin loops are better hallmarks for cellular differentiation than compartment switching. HiCorr allowed direct observation of cell-type- and differentiation-specific E-P aggregates spanning large neighborhoods, suggesting a mechanism that stabilizes enhancer contacts during development. Interestingly, we concluded that Hi-C loop outperforms eQTL in explaining neurological GWAS results, revealing a unique value of high-resolution 3D genome maps in elucidating the disease etiology.

Identification of 67 histone marks and histone lysine crotonylation as a new type of histone modification.

We report the identification of 67 previously undescribed histone modifications, increasing the current number of known histone marks by about 70%. We further investigated one of the marks, lysine crotonylation (Kcr), confirming that it represents an evolutionarily-conserved histone posttranslational modification. The unique structure and genomic localization of histone Kcr suggest that it is mechanistically and functionally different from histone lysine acetylation (Kac). Specifically, in both human somatic and mouse male germ cell genomes, histone Kcr marks either active promoters or potential enhancers. In male germinal cells immediately following meiosis, Kcr is enriched on sex chromosomes and specifically marks testis-specific genes, including a significant proportion of X-linked genes that escape sex chromosome inactivation in haploid cells. These results therefore dramatically extend the repertoire of histone PTM sites and designate Kcr as a specific mark of active sex chromosome-linked genes in postmeiotic male germ cells.

STAG2 mutations regulate 3D genome organization, chromatin loops, and Polycomb signaling in glioblastoma multiforme.

Inactivating mutations of genes encoding the cohesin complex are common in a wide range of human cancers. STAG2 is the most commonly mutated subunit. Here we report the impact of stable correction of endogenous, naturally occurring STAG2 mutations on gene expression, 3D genome organization, chromatin loops, and Polycomb signaling in glioblastoma multiforme (GBM). In two GBM cell lines, correction of their STAG2 mutations significantly altered the expression of ∼10% of all expressed genes. Virtually all the most highly regulated genes were negatively regulated by STAG2 (i.e., expressed higher in STAG2-mutant cells), and one of them-HEPH-was regulated by STAG2 in uncultured GBM tumors as well. While STAG2 correction had little effect on large-scale features of 3D genome organization (A/B compartments, TADs), STAG2 correction did alter thousands of individual chromatin loops, some of which controlled the expression of adjacent genes. Loops specific to STAG2-mutant cells, which were regulated by STAG1-containing cohesin complexes, were very large, supporting prior findings that STAG1-containing cohesin complexes have greater loop extrusion processivity than STAG2-containing cohesin complexes and suggesting that long loops may be a general feature of STAG2-mutant cancers. Finally, STAG2 mutation activated Polycomb activity leading to increased H3K27me3 marks, identifying Polycomb signaling as a potential target for therapeutic intervention in STAG2-mutant GBM tumors. Together, these findings illuminate the landscape of STAG2-regulated genes, A/B compartments, chromatin loops, and pathways in GBM, providing important clues into the largely still unknown mechanism of STAG2 tumor suppression.

Novel correlative analysis identifies multiple genomic variations impacting ASD with macrocephaly.

Autism spectrum disorders (ASD) display both phenotypic and genetic heterogeneity, impeding the understanding of ASD and development of effective means of diagnosis and potential treatments. Genes affected by genomic variations for ASD converge in dozens of gene ontologies (GOs), but the relationship between the variations at the GO level have not been well elucidated. In the current study, multiple types of genomic variations were mapped to GOs and correlations among GOs were measured in ASD and control samples. Several ASD-unique GO correlations were found, suggesting the importance of co-occurrence of genomic variations in genes from different functional categories in ASD etiology. Combined with experimental data, several variations related to WNT signaling, neuron development, synapse morphology/function and organ morphogenesis were found to be important for ASD with macrocephaly, and novel co-occurrence patterns of them in ASD patients were found. Furthermore, we applied this gene ontology correlation analysis method to find genomic variations that contribute to ASD etiology in combination with changes in gene expression and transcription factor binding, providing novel insights into ASD with macrocephaly and a new methodology for the analysis of genomic variation.

magpie: A power evaluation method for differential RNA methylation analysis in N6-methyladenosine sequencing.

Recently, novel biotechnologies to quantify RNA modifications became an increasingly popular choice for researchers who study epitranscriptome. When studying RNA methylations such as N6-methyladenosine (m6A), researchers need to make several decisions in its experimental design, especially the sample size and a proper statistical power. Due to the complexity and high-throughput nature of m6A sequencing measurements, methods for power calculation and study design are still currently unavailable. In this work, we propose a statistical power assessment tool, magpie, for power calculation and experimental design for epitranscriptome studies using m6A sequencing data. Our simulation-based power assessment tool will borrow information from real pilot data, and inspect various influential factors including sample size, sequencing depth, effect size, and basal expression ranges. We integrate two modules in magpie: (i) a flexible and realistic simulator module to synthesize m6A sequencing data based on real data; and (ii) a power assessment module to examine a set of comprehensive evaluation metrics.

A locus at 19q13.31 significantly reduces the ApoE ε4 risk for Alzheimer's Disease in African Ancestry.

African descent populations have a lower Alzheimer disease risk from ApoE ε4 compared to other populations. Ancestry analysis showed that the difference in risk between African and European populations lies in the ancestral genomic background surrounding the ApoE locus (local ancestry). Identifying the mechanism(s) of this protection could lead to greater insight into the etiology of Alzheimer disease and more personalized therapeutic intervention. Our objective is to follow up the local ancestry finding and identify the genetic variants that drive this risk difference and result in a lower risk for developing Alzheimer disease in African ancestry populations. We performed association analyses using a logistic regression model with the ApoE ε4 allele as an interaction term and adjusted for genome-wide ancestry, age, and sex. Discovery analysis included imputed SNP data of 1,850 Alzheimer disease and 4,331 cognitively intact African American individuals. We performed replication analyses on 63 whole genome sequenced Alzheimer disease and 648 cognitively intact Ibadan individuals. Additionally, we reproduced results using whole-genome sequencing of 273 Alzheimer disease and 275 cognitively intact admixed Puerto Rican individuals. A further comparison was done with SNP imputation from an additional 8,463 Alzheimer disease and 11,365 cognitively intact non-Hispanic White individuals. We identified a significant interaction between the ApoE ε4 allele and the SNP rs10423769_A allele, (ß = -0.54,SE = 0.12,p-value = 7.50x10-6) in the discovery data set, and replicated this finding in Ibadan (ß = -1.32,SE = 0.52,p-value = 1.15x10-2) and Puerto Rican (ß = -1.27,SE = 0.64,p-value = 4.91x10-2) individuals. The non-Hispanic Whites analyses showed an interaction trending in the "protective" direction but failing to pass a 0.05 significance threshold (ß = -1.51,SE = 0.84,p-value = 7.26x10-2). The presence of the rs10423769_A allele reduces the odds ratio for Alzheimer disease risk from 7.2 for ApoE ε4/ε4 carriers lacking the A allele to 2.1 for ApoE ε4/ε4 carriers with at least one A allele. This locus is located approximately 2 mB upstream of the ApoE locus, in a large cluster of pregnancy specific beta-1 glycoproteins on chromosome 19 and lies within a long noncoding RNA, ENSG00000282943. This study identified a new African-ancestry specific locus that reduces the risk effect of ApoE ε4 for developing Alzheimer disease. The mechanism of the interaction with ApoEε4 is not known but suggests a novel mechanism for reducing the risk for ε4 carriers opening the possibility for potential ancestry-specific therapeutic intervention.

Extended genome-wide association study employing the African genome resources panel identifies novel susceptibility loci for Alzheimer's disease in individuals of African ancestry.

INTRODUCTION: Despite a two-fold risk, individuals of African ancestry have been underrepresented in Alzheimer's disease (AD) genomics efforts. METHODS: Genome-wide association studies (GWAS) of 2,903 AD cases and 6,265 controls of African ancestry. Within-dataset results were meta-analyzed, followed by functional genomics analyses. RESULTS: A novel AD-risk locus was identified in MPDZ on chromosome (chr) 9p23 (rs141610415, MAF = 0.002, P = 3.68×10-9). Two additional novel common and nine rare loci were identified with suggestive associations (P < 9×10-7). Comparison of association and linkage disequilibrium (LD) patterns between datasets with higher and lower degrees of African ancestry showed differential association patterns at chr12q23.2 (ASCL1), suggesting that this association is modulated by regional origin of local African ancestry. DISCUSSION: These analyses identified novel AD-associated loci in individuals of African ancestry and suggest that degree of African ancestry modulates some associations. Increased sample sets covering as much African genetic diversity as possible will be critical to identify additional loci and deconvolute local genetic ancestry effects. HIGHLIGHTS: Genetic ancestry significantly impacts risk of Alzheimer's Disease (AD). Although individuals of African ancestry are twice as likely to develop AD, they are vastly underrepresented in AD genomics studies. The Alzheimer's Disease Genetics Consortium has previously identified 16 common and rare genetic loci associated with AD in African American individuals. The current analyses significantly expand this effort by increasing the sample size and extending ancestral diversity by including populations from continental Africa. Single variant meta-analysis identified a novel genome-wide significant AD-risk locus in individuals of African ancestry at the MPDZ gene, and 11 additional novel loci with suggestive genome-wide significance at P < 9×10-7. Comparison of African American datasets with samples of higher degree of African ancestry demonstrated differing patterns of association and linkage disequilibrium at one of these loci, suggesting that degree and/or geographic origin of African ancestry modulates the effect at this locus. These findings illustrate the importance of increasing number and ancestral diversity of African ancestry samples in AD genomics studies to fully disentangle the genetic architecture underlying AD, and yield more effective ancestry-informed genetic screening tools and therapeutic interventions.

Ancestry-related differences in chromatin accessibility and gene expression of APOE ε4 are associated with Alzheimer's disease risk.

INTRODUCTION: European local ancestry (ELA) surrounding apolipoprotein E (APOE) ε4 confers higher risk for Alzheimer's disease (AD) compared to African local ancestry (ALA). We demonstrated significantly higher APOE ε4  expression in ELA versus ALA in AD brains from APOE ε4/ε4 carriers. Chromatin accessibility differences could contribute to these expression changes. METHODS: We performed single nuclei assays for transposase accessible chromatin sequencing from the frontal cortex of six ALA and six ELA AD brains, homozygous for local ancestry and APOE ε4. RESULTS: Our results showed an increased chromatin accessibility at the APOE ε4  promoter area in ELA versus ALA astrocytes. This increased accessibility in ELA astrocytes extended genome wide. Genes with increased accessibility in ELA in astrocytes were enriched for synapsis, cholesterol processing, and astrocyte reactivity. DISCUSSION: Our results suggest that increased chromatin accessibility of APOE ε4  in ELA astrocytes contributes to the observed elevated APOE ε4  expression, corresponding to the increased AD risk in ELA versus ALA APOE ε4/ε4 carriers.

TWO-SIGMA: A novel two-component single cell model-based association method for single-cell RNA-seq data.

In this paper, we develop TWO-SIGMA, a TWO-component SInGle cell Model-based Association method for differential expression (DE) analyses in single-cell RNA-seq (scRNA-seq) data. The first component models the probability of "drop-out" with a mixed-effects logistic regression model and the second component models the (conditional) mean expression with a mixed-effects negative binomial regression model. TWO-SIGMA is extremely flexible in that it: (i) does not require a log-transformation of the outcome, (ii) allows for overdispersed and zero-inflated counts, (iii) accommodates a correlation structure between cells from the same individual via random effect terms, (iv) can analyze unbalanced designs (in which the number of cells does not need to be identical for all samples), (v) can control for additional sample-level and cell-level covariates including batch effects, (vi) provides interpretable effect size estimates, and (vii) enables general tests of DE beyond two-group comparisons. To our knowledge, TWO-SIGMA is the only method for analyzing scRNA-seq data that can simultaneously accomplish each of these features. Simulations studies show that TWO-SIGMA outperforms alternative regression-based approaches in both type-I error control and power enhancement when the data contains even moderate within-sample correlation. A real data analysis using pancreas islet single-cells exhibits the flexibility of TWO-SIGMA and demonstrates that incorrectly failing to include random effect terms can have dramatic impacts on scientific conclusions. TWO-SIGMA is implemented in the R package twosigma available at https://github.com/edvanburen/twosigma.

5mC oxidation by Tet2 modulates enhancer activity and timing of transcriptome reprogramming during differentiation.

In mammals, cytosine methylation (5mC) is widely distributed throughout the genome but is notably depleted from active promoters and enhancers. While the role of DNA methylation in promoter silencing has been well documented, the function of this epigenetic mark at enhancers remains unclear. Recent experiments have demonstrated that enhancers are enriched for 5-hydroxymethylcytosine (5hmC), an oxidization product of the Tet family of 5mC dioxygenases and an intermediate of DNA demethylation. These results support the involvement of Tet proteins in the regulation of dynamic DNA methylation at enhancers. By mapping DNA methylation and hydroxymethylation at base resolution, we find that deletion of Tet2 causes extensive loss of 5hmC at enhancers, accompanied by enhancer hypermethylation, reduction of enhancer activity, and delayed gene induction in the early steps of differentiation. Our results reveal that DNA demethylation modulates enhancer activity, and its disruption influences the timing of transcriptome reprogramming during cellular differentiation.

Identifying differential regulatory control of APOE ɛ4 on African versus European haplotypes as potential therapeutic targets.

We previously demonstrated that in Alzheimer's disease (AD) patients, European apolipoprotein E (APOE) ε4 carriers express significantly more APOE ε4 in their brains than African AD carriers. We examined single nucleotide polymorphisms near APOE with significant frequency differences between African and European/Japanese APOE ε4 haplotypes that could contribute to this difference in expression through regulation. Two enhancer massively parallel reporter assay (MPRA) approaches were performed, supplemented with single fragment reporter assays. We used Capture C analyses to support interactions with the APOE promoter. Introns within TOMM40 showed increased enhancer activity in the European/Japanese versus African haplotypes in astrocytes and microglia. This region overlaps with APOE promoter interactions as assessed by Capture C analysis. Single variant analyses pinpoints rs2075650/rs157581, and rs59007384 as functionally different on these haplotypes. Identification of the mechanisms for differential regulatory function for APOE expression between African and European/Japanese haplotypes could lead to therapeutic targets for APOE ε4 carriers.

A high-resolution map of the three-dimensional chromatin interactome in human cells.

A large number of cis-regulatory sequences have been annotated in the human genome, but defining their target genes remains a challenge. One strategy is to identify the long-range looping interactions at these elements with the use of chromosome conformation capture (3C)-based techniques. However, previous studies lack either the resolution or coverage to permit a whole-genome, unbiased view of chromatin interactions. Here we report a comprehensive chromatin interaction map generated in human fibroblasts using a genome-wide 3C analysis method (Hi-C). We determined over one million long-range chromatin interactions at 5-10-kb resolution, and uncovered general principles of chromatin organization at different types of genomic features. We also characterized the dynamics of promoter-enhancer contacts after TNF-α signalling in these cells. Unexpectedly, we found that TNF-α-responsive enhancers are already in contact with their target promoters before signalling. Such pre-existing chromatin looping, which also exists in other cell types with different extracellular signalling, is a strong predictor of gene induction. Our observations suggest that the three-dimensional chromatin landscape, once established in a particular cell type, is relatively stable and could influence the selection or activation of target genes by a ubiquitous transcription activator in a cell-specific manner.

A hidden Markov random field-based Bayesian method for the detection of long-range chromosomal interactions in Hi-C data.

MOTIVATION: Advances in chromosome conformation capture and next-generation sequencing technologies are enabling genome-wide investigation of dynamic chromatin interactions. For example, Hi-C experiments generate genome-wide contact frequencies between pairs of loci by sequencing DNA segments ligated from loci in close spatial proximity. One essential task in such studies is peak calling, that is, detecting non-random interactions between loci from the two-dimensional contact frequency matrix. Successful fulfillment of this task has many important implications including identifying long-range interactions that assist interpreting a sizable fraction of the results from genome-wide association studies. The task - distinguishing biologically meaningful chromatin interactions from massive numbers of random interactions - poses great challenges both statistically and computationally. Model-based methods to address this challenge are still lacking. In particular, no statistical model exists that takes the underlying dependency structure into consideration. RESULTS: In this paper, we propose a hidden Markov random field (HMRF) based Bayesian method to rigorously model interaction probabilities in the two-dimensional space based on the contact frequency matrix. By borrowing information from neighboring loci pairs, our method demonstrates superior reproducibility and statistical power in both simulation studies and real data analysis. AVAILABILITY AND IMPLEMENTATION: The Source codes can be downloaded at: http://www.unc.edu/∼yunmli/HMRFBayesHiC CONTACT: ming.hu@nyumc.org or yunli@med.unc.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Lysine 2-hydroxyisobutyrylation is a widely distributed active histone mark.

We report the identification of a new type of histone mark, lysine 2-hydroxyisobutyrylation (Khib), and identify the mark at 63 human and mouse histone Khib sites, including 27 unique lysine sites that are not known to be modified by lysine acetylation (Kac) and lysine crotonylation (Kcr). This histone mark was initially identified by MS and then validated by chemical and biochemical methods. Histone Khib shows distinct genomic distributions from histone Kac or histone Kcr during male germ cell differentiation. Using chromatin immunoprecipitation sequencing, gene expression analysis and immunodetection, we show that in male germ cells, H4K8hib is associated with active gene transcription in meiotic and post-meiotic cells. In addition, H4K8ac-associated genes are included in and constitute only a subfraction of H4K8hib-labeled genes. The histone Khib mark is conserved and widely distributed, has high stoichiometry and induces a large structural change. These findings suggest its critical role on the regulation of chromatin functions.

CBX3 regulates efficient RNA processing genome-wide.

CBX5, CBX1, and CBX3 (HP1α, ß, and γ, respectively) play an evolutionarily conserved role in the formation and maintenance of heterochromatin. In addition, CBX5, CBX1, and CBX3 may also participate in transcriptional regulation of genes. Recently, CBX3 binding to the bodies of a subset of genes has been observed in human and murine cells. However, the generality of this phenomenon and the role CBX3 may play in this context are unknown. Genome-wide localization analysis reveals CBX3 binding at genic regions, which strongly correlates with gene activity across multiple cell types. Depletion of CBX3 resulted in down-regulation of a subset of target genes. Loss of CBX3 binding leads to a more dramatic accumulation of unspliced nascent transcripts. In addition, we observed defective recruitment of splicing factors, including SNRNP70, to CBX3 target genes. Collectively, our data suggest a role for CBX3 in aiding in efficient cotranscriptional RNA processing.

Combined gene expression and DNA occupancy profiling identifies potential therapeutic targets of t(8;21) AML.

Chromosome translocation 8q22;21q22 [t(8;21)] is commonly associated with acute myeloid leukemia (AML), and the resulting AML1-ETO fusion proteins are involved in the pathogenesis of AML. To identify novel molecular and therapeutic targets, we performed combined gene expression microarray and promoter occupancy (ChIP-chip) profiling using Lin(-)/Sca1(-)/cKit(+) cells, the major leukemia cell population, from an AML mouse model induced by AML1-ETO9a (AE9a). Approximately 30% of the identified common targets of microarray and ChIP-chip assays overlap with the human t(8;21)-gene expression molecular signature. CD45, a protein tyrosine phosphatase and a negative regulator of cytokine/growth factor receptor and JAK/STAT signaling, is among those targets. Its expression is substantially down-regulated in leukemia cells. Consequently, JAK/STAT signaling is enhanced. Re-expression of CD45 suppresses JAK/STAT activation, delays leukemia development, and promotes apoptosis of t(8;21)-positive cells. This study demonstrates the benefit of combining gene expression and promoter occupancy profiling assays to identify molecular and potential therapeutic targets in human cancers and describes a previously unappreciated signaling pathway involving t(8;21) fusion proteins, CD45, and JAK/STAT, which could be a potential novel target for treating t(8;21) AML.

PU.1 and C/EBP(alpha) synergistically program distinct response to NF-kappaB activation through establishing monocyte specific enhancers.

Unraveling the complexity of transcriptional programs coded by different cell types has been one of the central goals of cell biology. By using genome-wide location analysis, we examined how two different cell types generate different responses to the NF-κB signaling pathway. We showed that, after TNF-α treatment, the NF-κB p65 subunit binds to distinct genome locations and subsequently induces different subsets of genes in human monocytic THP-1 cells versus HeLa cells. Interestingly, the differential p65 binding in two cell types correlates with preexisting cell type-specific enhancers before TNF-α stimulation, marked by histone modifications. We also found that two transcription factors, PU.1 and C/EBPα, appear to synergistically mediate enhancer creation and affect NF-κB target selection in THP-1 cells. In HeLa cells, coexpression of PU.1 and C/EBPα conferred TNF-α responsiveness to a subset of THP-1-specific NF-κB target genes. These results suggest that the diversity of transcriptional programs in mammalian cells arises, at least in part, from preexisting enhancers that are established by cell-specific transcription factors.

Easy Hi-C: A Low-Input Method for Capturing Genome Organization.

Chromosome conformation capture technology and its derivatives have been widely used to study genome organization. Among them, Hi-C (chromosome conformation capture coupling with high-throughput sequencing) is popular in dissecting chromatin architecture on the genome-wide level. However, the intrinsic limitations prevent its application when it comes to rare samples. Here, we present easy Hi-C, a biotin-free technology that dramatically reduces DNA loss and is suitable for low-input samples.

Single cell multiomic analysis reveals diabetes-associated ß-cell heterogeneity driven by HNF1A.

Broad heterogeneity in pancreatic ß-cell function and morphology has been widely reported. However, determining which components of this cellular heterogeneity serve a diabetes-relevant function remains challenging. Here, we integrate single-cell transcriptome, single-nuclei chromatin accessibility, and cell-type specific 3D genome profiles from human islets and identify Type II Diabetes (T2D)-associated ß-cell heterogeneity at both transcriptomic and epigenomic levels. We develop a computational method to explicitly dissect the intra-donor and inter-donor heterogeneity between single ß-cells, which reflect distinct mechanisms of T2D pathogenesis. Integrative transcriptomic and epigenomic analysis identifies HNF1A as a principal driver of intra-donor heterogeneity between ß-cells from the same donors; HNF1A expression is also reduced in ß-cells from T2D donors. Interestingly, HNF1A activity in single ß-cells is significantly associated with lower Na+ currents and we nominate a HNF1A target, FXYD2, as the primary mitigator. Our study demonstrates the value of investigating disease-associated single-cell heterogeneity and provides new insights into the pathogenesis of T2D.

DeepLoop robustly maps chromatin interactions from sparse allele-resolved or single-cell Hi-C data at kilobase resolution.

Mapping chromatin loops from noisy Hi-C heatmaps remains a major challenge. Here we present DeepLoop, which performs rigorous bias correction followed by deep-learning-based signal enhancement for robust chromatin interaction mapping from low-depth Hi-C data. DeepLoop enables loop-resolution, single-cell Hi-C analysis. It also achieves a cross-platform convergence between different Hi-C protocols and micrococcal nuclease (micro-C). DeepLoop allowed us to map the genetic and epigenetic determinants of allele-specific chromatin interactions in the human genome. We nominate new loci with allele-specific interactions governed by imprinting or allelic DNA methylation. We also discovered that, in the inactivated X chromosome (Xi), local loops at the DXZ4 'megadomain' boundary escape X-inactivation but the FIRRE 'superloop' locus does not. Importantly, DeepLoop can pinpoint heterozygous single-nucleotide polymorphisms and large structure variants that cause allelic chromatin loops, many of which rewire enhancers with transcription consequences. Taken together, DeepLoop expands the use of Hi-C to provide loop-resolution insights into the genetics of the three-dimensional genome.