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Abstract Background Inter- and intra-tumor heterogeneity is considered a significant factor contributing to the development of endocrine resistance in breast cancer. Recent advances in single-cell RNA sequencing (scRNA-seq) and single-cell ATAC sequencing (scATAC-seq) allow us to explore inter- and intra-tumor heterogeneity at single-cell resolution. However, such integrated single-cell analysis has not yet been demonstrated to characterize the transcriptome and chromatin accessibility in breast cancer endocrine resistance. Methods In this study, we conducted an integrated analysis combining scRNA-seq and scATAC-seq on more than 80,000 breast tissue cells from two normal tissues (NTs), three primary tumors (PTs), and three tamoxifen-treated recurrent tumors (RTs). A variety of cell types among breast tumor tissues were identified, PT- and RT-specific cancer cell states (CSs) were defined, and a heterogeneity-guided core signature (HCS) was derived through such integrated analysis. Functional experiments were performed to validate the oncogenic role of BMP7, a key gene within the core signature. Results We observed a striking level of cell-to-cell heterogeneity among six tumor tissues and delineated the primary to recurrent tumor progression, underscoring the significance of these single-cell level tumor cell clusters classified from scRNA-seq data. We defined nine CSs, including five PT-specific, three RT-specific, and one PT-RT-shared CSs, and identified distinct open chromatin regions of CSs, as well as a HCS of 137 genes. In addition, we predicted specific transcription factors (TFs) associated with the core signature and novel biological/metabolism pathways that mediate the communications between CSs and the tumor microenvironment (TME). We finally demonstrated that BMP7 plays an oncogenic role in tamoxifen-resistant breast cancer cells through modulating MAPK signaling pathways. Conclusions Our integrated single-cell analysis provides a comprehensive understanding of the tumor heterogeneity in tamoxifen resistance. We envision this integrated single-cell epigenomic and transcriptomic measure will become a powerful approach to unravel how epigenetic factors and the tumor microenvironment govern the development of tumor heterogeneity and to uncover potential therapeutic targets that circumvent heterogeneity-related failures.

Abstract An integration of 3D chromatin structure and gene expression at single-cell resolution has yet been demonstrated. Here, we develop a computational method, a multiomic data integration (MUDI) algorithm, which integrates scHi-C and scRNA-seq data to precisely define the 3D-regulated and biological-context dependent cell subpopulations or topologically integrated subpopulations (TISPs). We demonstrate its algorithmic utility on the publicly available and newly generated scHi-C and scRNA-seq data. We then test and apply MUDI in a breast cancer cell model system to demonstrate its biological-context dependent utility. We find the newly defined topologically conserved associating domain (CAD) is the characteristic single-cell 3D chromatin structure and better characterizes chromatin domains in single-cell resolution. We further identify 20 TISPs uniquely characterizing 3D-regulated breast cancer cellular states. We reveal two of TISPs are remarkably resemble to high cycling breast cancer persister cells and chromatin modifying enzymes might be functional regulators to drive the alteration of the 3D chromatin structures. Our comprehensive integration of scHi-C and scRNA-seq data in cancer cells at single-cell resolution provides mechanistic insights into 3D-regulated heterogeneity of developing drug-tolerant cancer cells.

Introduction: The Euchromatic Histone Methyl Transferase Protein 2 (EHMT2), also known as G9a, deposits transcriptionally repressive chromatin marks that play pivotal roles in the maturation and homeostasis of multiple organs. Recently, we have shown that Ehmt2 inactivation in the mouse pancreas alters growth and immune gene expression networks, antagonizing Kras-mediated pancreatic cancer initiation and promotion. Here, we elucidate the essential role of Ehmt2 in maintaining a transcriptional landscape that protects organs from inflammation.Methods: Comparative RNA-seq studies between normal postnatal and young adult pancreatic tissue from Ehmt2 conditional knockout animals (Ehmt2fl/fl) targeted to the exocrine pancreatic epithelial cells (Pdx1-Cre and P48Cre/+), reveal alterations in gene expression networks in the whole organ related to injury-inflammation-repair, suggesting an increased predisposition to damage. Thus, we induced an inflammation repair response in the Ehmt2fl/fl pancreas and used a data science-based approach to integrate RNA-seq-derived pathways and networks, deconvolution digital cytology, and spatial transcriptomics. We also analyzed the tissue response to damage at the morphological, biochemical, and molecular pathology levels.Results and discussion: The Ehmt2fl/fl pancreas displays an enhanced injury-inflammation-repair response, offering insights into fundamental molecular and cellular mechanisms involved in this process. More importantly, these data show that conditional Ehmt2 inactivation in exocrine cells reprograms the local environment to recruit mesenchymal and immunological cells needed to mount an increased inflammatory response. Mechanistically, this response is an enhanced injury-inflammation-repair reaction with a small contribution of specific Ehmt2-regulated transcripts. Thus, this new knowledge extends the mechanisms underlying the role of the Ehmt2-mediated pathway in suppressing pancreatic cancer initiation and modulating inflammatory pancreatic diseases.

Cancer-associated fibroblasts (CAFs) are the main component of the stroma in pancreatic cancer, but their tissue of origin remains to be defined. Here the authors perform lineage tracing and single cell RNA sequencing in mice and suggest the splanchnic mesenchyme as the tissue of origin for CAFs.

Here the authors provide a multi-omic study of the nucleosome landscape in LNCaP cells and observe nine functional nucleosome states each with characteristic nucleosome footprints. Upon androgen stimulation, they observed changes in these nucleosome states accompanied by changes in binding and function of pioneer factors, including GATA2.

Abstract Background Transcription factor (TF) binding motifs are identified by high throughput sequencing technologies as means to capture Protein-DNA interactions. These motifs are often represented by consensus sequences in form of position weight matrices (PWMs). With ever-increasing pool of TF binding motifs from multiple sources, redundancy issues are difficult to avoid, especially when every source maintains its own database for collection. One solution can be to cluster biologically relevant or similar PWMs, whether coming from experimental detection or in silico predictions. However, there is a lack of efficient tools to cluster PWMs. Assessing quality of PWM clusters is yet another challenge. Therefore, new methods and tools are required to efficiently cluster PWMs and assess quality of clusters. Results A new Python package Affinity Based Clustering for Position Weight Matrices (abc4pwm) was developed. It efficiently clustered PWMs from multiple sources with or without using DNA-Binding Domain (DBD) information, generated a representative motif for each cluster, evaluated the clustering quality automatically, and filtered out incorrectly clustered PWMs. Additionally, it was able to update human DBD family database automatically, classified known human TF PWMs to the respective DBD family, and performed TF motif searching and motif discovery by a new ensemble learning approach. Conclusion This work demonstrates applications of abc4pwm in the DNA sequence analysis for various high throughput sequencing data using ~ 1770 human TF PWMs. It recovered known TF motifs at gene promoters based on gene expression profiles (RNA-seq) and identified true TF binding targets for motifs predicted from ChIP-seq experiments. Abc4pwm is a useful tool for TF motif searching, clustering, quality assessment and integration in multiple types of sequence data analysis including RNA-seq, ChIP-seq and ATAC-seq.

With ever-growing genomic sequencing data, the data variabilities and the underlying biases of the sequencing technologies pose significant computational challenges ranging from the need for accurately detecting the nucleosome positioning or chromatin interaction to the need for developing normalization methods to eliminate systematic biases. This review mainly surveys the computational methods for mapping the higher-resolution nucleosome and higher-order chromatin architectures. While a detailed discussion of the underlying algorithms is beyond the scope of our survey, we have discussed the methods and tools that can detect the nucleosomes in the genome, then demonstrated the computational methods for identifying 3D chromatin domains and interactions. We further illustrated computational approaches for integrating multi-omics data with Hi-C data and the advance of single-cell (sc)Hi-C data analysis. Our survey provides a comprehensive and valuable resource for biomedical scientists interested in studying nucleosome organization and chromatin structures as well as for computational scientists who are interested in improving upon them.

Abstract We develop a novel computational method, NucHMM, to identify functional nucleosome states associated with cell type-specific combinatorial histone marks and nucleosome organization features such as phasing, spacing and positioning. We test it on publicly available MNase-seq and ChIP-seq data in MCF7, H1, and IMR90 cells and identify 11 distinct functional nucleosome states. We demonstrate these nucleosome states are distinctly associated with the splicing potentiality of skipping exons. This advances our understanding of the chromatin function at the nucleosome level and offers insights into the interplay between nucleosome organization and splicing processes.

Bone metastasis is a common and devastating consequence of several major cancer types, including breast and prostate. Osteocytes are the predominant bone cell, and through connexin (Cx) 43 hemichannels release ATP to the bone microenvironment that can be hydrolyzed to adenosine. Here, we investigated how genes related to ATP paracrine signaling are involved in two common bone-metastasizing malignancies, estrogen receptor positive (ER+) breast and prostate cancers. Compared to other sites, bone metastases of both cancer types expressed higher levels of ENTPD1 and NT5E, which encode CD39 and CD73, respectively, and hydrolyze ATP to adenosine. ADORA3, encoding the adenosine A3 receptor, had a similar expression pattern. In primary ER+ breast cancer, high levels of the triplet ENTPD1/NT5E/ADORA3 expression signature was correlated with lower overall, distant metastasis-free, and progression-free survival. In ER+ bone metastasis biopsies, this expression signature is associated with lower survival. This expression signature was also higher in bone-metastasizing primary prostate cancers than in those that caused other tumor events or did not lead to progressive disease. In 3D culture, a non-hydrolyzable ATP analog inhibited the growth of breast and prostate cancer cell lines more than ATP did. A3 inhibition also reduced spheroid growth. Large-scale screens by the Drug Repurposing Hub found ER+ breast cancer cell lines were uniquely sensitive to adenosine receptor antagonists. Together, these data suggest a vital role for extracellular ATP degradation and adenosine receptor signaling in cancer bone metastasis, and this study provides potential diagnostic means for bone metastasis and specific targets for treatment and prevention.

Abstract Current computational methods on Hi-C analysis focused on identifying Mb-size domains often failed to unveil the underlying functional and mechanistic relationship of chromatin structure and gene regulation. We developed a novel computational method HiSIF to identify genome-wide interacting loci. We illustrated HiSIF outperformed other tools for identifying chromatin loops. We applied it to Hi-C data in breast cancer cells and identified 21 genes with gained loops showing worse relapse-free survival in endocrine-treated patients, suggesting the genes with enhanced loops can be used for prognostic signatures for measuring the outcome of the endocrine treatment. HiSIF is available at https://github.com/yufanzhouonline/HiSIF .

Abstract Background BRCA1-associated breast cancer originates from luminal progenitor cells. BRCA1 functions in multiple biological processes, including double-strand break repair, replication stress suppression, transcriptional regulation, and chromatin reorganization. While non-malignant cells carrying cancer-predisposing BRCA1 mutations exhibit increased genomic instability, it remains unclear whether BRCA1 haploinsufficiency affects transcription and chromatin dynamics in breast epithelial cells. Methods H3K27ac-associated super-enhancers were compared in primary breast epithelial cells from BRCA1 mutation carriers (BRCA1 mut/+ ) and non-carriers (BRCA1 +/+ ). Non-tumorigenic MCF10A breast epithelial cells with engineered BRCA1 haploinsufficiency were used to confirm the H3K27ac changes. The impact of BRCA1 mutations on enhancer function and enhancer-promoter looping was assessed in MCF10A cells. Results Here, we show that primary mammary epithelial cells from women with BRCA1 mutations display significant loss of H3K27ac-associated super-enhancers. These BRCA1-dependent super-enhancers are enriched with binding motifs for the GATA family. Non-tumorigenic BRCA1 mut/+ MCF10A cells recapitulate the H3K27ac loss. Attenuated histone mark and enhancer activity in these BRCA1 mut/+ MCF10A cells can be partially restored with wild-type BRCA1. Furthermore, chromatin conformation analysis demonstrates impaired enhancer-promoter looping in BRCA1 mut/+ MCF10A cells. Conclusions H3K27ac-associated super-enhancer loss is a previously unappreciated functional deficiency in ostensibly normal BRCA1 mutation-carrying breast epithelium. Our findings offer new mechanistic insights into BRCA1 mutation-associated transcriptional and epigenetic abnormality in breast epithelial cells and tissue/cell lineage-specific tumorigenesis.

In breast cancer, the 3D architecture of the genome can impact gene regulation. Here, the authors use tethered chromatin conformation profiling to investigate 3D chromatin structure in models of hormone-induced breast cancer and endocrine resistance, finding dynamic temporal reorganisation.

Abstract Background Accumulating evidence suggests alternative splicing (AS) is a co-transcriptional splicing process not only controlled by RNA-binding splicing factors, but also mediated by epigenetic regulators, such as chromatin structure, nucleosome density, and histone modification. Aberrant AS plays an important role in regulating various diseases, including cancers. Methods In this study, we integrated AS events derived from RNA-seq with H3K79me2 ChIP-seq data across 34 different normal and cancer cell types and found the higher enrichment of H3K79me2 in two AS types, skipping exon (SE) and alternative 3′ splice site (A3SS). Results Interestingly, by applying self-organizing map (SOM) clustering, we unveiled two clusters mainly comprised of blood cancer cell types with a strong correlation between H3K79me2 and SE. Remarkably, the expression of transcripts associated with SE was not significantly different from that of those not associated with SE, indicating the involvement of H3K79me2 in splicing has little impact on full mRNA transcription. We further showed that the deletion of DOT1L1, the sole H3K79 methyltransferase, impeded leukemia cell proliferation as well as switched exon skipping to the inclusion isoform in two MLL-rearranged acute myeloid leukemia cell lines. Our data demonstrate H3K79me2 was involved in mediating SE processing, which might in turn influence transformation and disease progression in leukemias. Conclusions Collectively, our work for the first time reveals that H3K79me2 plays functional and regulatory roles through a co-transcriptional splicing mechanism.

Although circadian rhythms are thought to be essential for maintaining body health, the effects of chronic circadian disruption during neurodevelopment remain elusive. Here, using the “Short Day” (SD) mouse model, in which an 8 h/8 h light/dark (LD) cycle was applied from embryonic day 1 to postnatal day 42, we investigated the molecular and behavioral changes after circadian disruption in mice. Adult SD mice fully entrained to the 8 h/8 h LD cycle, and the circadian oscillations of the clock proteins, PERIOD1 and PERIOD2, were disrupted in the suprachiasmatic nucleus and the hippocampus of these mice. By RNA-seq widespread changes were identified in the hippocampal transcriptome, which are functionally associated with neurodevelopment, translational control, and autism. By western blotting and immunostaining hyperactivation of the mTOR and MAPK signaling pathways and enhanced global protein synthesis were found in the hippocampi of SD mice. Electrophysiological recording uncovered enhanced excitatory, but attenuated inhibitory, synaptic transmission in the hippocampal CA1 pyramidal neurons. These functional changes at synapses were corroborated by the immature morphology of the dendritic spines in these neurons. Lastly, autistic-like animal behavioral changes, including impaired social interaction and communication, increased repetitive behaviors, and impaired novel object recognition and location memory, were found in SD mice. Together, these results demonstrate molecular, cellular, and behavioral changes in SD mice, all of which resemble autistic-like phenotypes caused by circadian rhythm disruption. The findings highlight a critical role for circadian rhythms in neurodevelopment.

The vast majority of BRCA1-driven breast cancers derive from luminal progenitor cells but the mechanisms of this lineage specificity are unclear. Here the authors show that dangerous accumulation of DNA-RNA hybrid structures due to RNA polymerase II pausing, occurs specifically in luminal epithelial cells.

Abstract Despite numerous studies done on understanding the role of DNA methylation, limited work has focused on systems integration of cell type-specific interplay between DNA methylation and gene transcription. Through a genome-wide analysis of DNA methylation across 19 cell types with T-47D as reference, we identified 106,252 cell type-specific differentially-methylated CpGs categorized into 7,537 differentially (46.6% hyper- and 53.4% hypo-) methylated regions. We found 44% promoter regions and 75% CpG islands were T-47D cell type-specific methylated. Pyrosequencing experiments validated the cell type-specific methylation across three benchmark cell lines. Interestingly, these DMRs overlapped with 1,145 known tumor suppressor genes. We then developed a Bayesian Gaussian Regression model to measure the relationship among DNA methylation, genomic segment distribution, differential gene expression and tumor suppressor gene status. The model uncovered that 3′UTR methylation has much less impact on transcriptional activity than other regions. Integration of DNA methylation and 82 transcription factor binding information across the 19 cell types suggested diverse interplay patterns between the two regulators. Our integrative analysis reveals cell type-specific and genomic region-dependent regulatory patterns and provides a perspective for integrating hundreds of various omics-seq data together.

Abstract Background Recent studies have suggested that combinations of multiple epigenetic modifications are essential for controlling gene expression. Despite numerous computational approaches have been developed to decipher the combinatorial epigenetic patterns or “epigenetic code”, none of them has explicitly addressed the relationship between a specific transcription factor (TF) and the patterns. Methods Here, we developed a novel computational method, T-cep, for annotating chromatin states associated with a specific TF. T-cep is composed of three key consecutive modules: (i) Data preprocessing, (ii) HMM training, and (iii) Potential TF-states calling. Results We evaluated T-cep on a TCF7L2-omics data. Unexpectedly, our method has uncovered a novel set of TCF7L2-regulated intragenic enhancers missed by other software tools, where the associated genes exert the highest gene expression. We further used siRNA knockdown, Co-transfection, RT-qPCR and Luciferase Reporter Assay not only to validate the accuracy and efficiency of prediction by T-cep, but also to confirm the functionality of TCF7L2-regulated enhancers in both MCF7 and PANC1 cells respectively. Conclusions Our study for the first time at a genome-wide scale reveals the enhanced transcriptional activity of cell-type-specific TCF7L2 intragenic enhancers in regulating gene expression.

COBRA1 is a BRCA1-binding protein and, as part of the negative elongation factor, regulates RNA polymerase II pausing and transcription elongation. Here, the authors show that tissue-specific deletion of mouse Cobra1 inhibits postnatal mammary gland development and that the mammary defects can be rescued by additional deletion of Brca1in a DNA repair-independent manner.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The spreading of epigenetic domains has emerged as a distinguishing epigenomic phenotype for diverse cell types. In particular, clusters of H3K27ac- and H3K4me3-marked elements, referred to as super-enhancers, and broad H3K4me3 domains, respectively, have been linked to cell identity and disease states. Here, we characterized the broad domains from different pancreatic ductal adenocarcinoma (PDAC) cell lines that represent distinct histological grades. Our integrative genomic analysis found that human derived cell line models for distinct PDAC grades exhibit characteristic broad epigenetic features associated with gene expression patterns that are predictive of patient prognosis and provide insight into pancreatic cancer cell identity. In particular, we find that genes marked by overlapping Low-Grade broad domains correspond to an epithelial phenotype and hold potential as markers for patient stratification. We further utilize ChIP-seq to compare the effects of histone acetyltransferase (HAT) inhibitors to detect global changes in histone acetylation and methylation levels. We found that HAT inhibitors impact certain broad domains of pancreatic cancer cells. Overall, our results reveal potential roles for broad domains in cells from distinct PDAC grades and demonstrate the plasticity of particular broad epigenomic domains to epigenetic inhibitors.

Nature Communications 8: Article number: 15908 (2017); Published 26 June 2017; Updated 30 March 2018 The original version of this Article omitted the following from the Acknowledgements: ‘The work was also supported by a grant to Y.H. from the Cancer Prevention Research Institute of Texas CPRIT RP170126.