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Pancreatic cancer is characterized by abundant desmoplasia, a dense stroma composed of extra-cellular and cellular components, with cancer associated fibroblasts (CAFs) being the major cellular component. However, the tissue(s) of origin for CAFs remains controversial. Here we determine the tissue origin of pancreatic CAFs through comprehensive lineage tracing studies in mice. We find that the splanchnic mesenchyme, the fetal cell layer surrounding the endoderm from which the pancreatic epithelium originates, gives rise to the majority of resident fibroblasts in the normal pancreas. In a genetic mouse model of pancreatic cancer, resident fibroblasts expand and constitute the bulk of CAFs. Single cell RNA profiling identifies gene expression signatures that are shared among the fetal splanchnic mesenchyme, adult fibroblasts and CAFs, suggesting a persistent transcriptional program underlies splanchnic lineage differentiation. Together, this study defines the phylogeny of the mesenchymal component of the pancreas and provides insights into pancreatic morphogenesis and tumorigenesis.

Knowledge gaps remain on how nucleosome organization and dynamic reorganization are governed by specific pioneer factors in a genome-wide manner. In this study, we generate over three billons of multi-omics sequencing data to exploit dynamic nucleosome landscape governed by pioneer factors (PFs), FOXA1 and GATA2. We quantitatively define nine functional nucleosome states each with specific characteristic nucleosome footprints in LNCaP prostate cancer cells. Interestingly, we observe dynamic switches among nucleosome states upon androgen stimulation, accompanied by distinct differential (gained or lost) binding of FOXA1, GATA2, H1 as well as many other coregulators. Intriguingly, we reveal a noncanonical pioneer model of GATA2 that it initially functions as a PF binding at the edge of a nucleosome in an inaccessible crowding array. Upon androgen stimulation, GATA2 re-configures an inaccessible to accessible nucleosome state and subsequently acts as a master transcription factor either directly or recruits signaling specific transcription factors to enhance WNT signaling in an androgen receptor (AR)-independent manner. Our data elicit a pioneer and master dual role of GATA2 in mediating nucleosome dynamics and enhancing downstream signaling pathways. Our work offers structural and mechanistic insight into the dynamics of pioneer factors governing nucleosome reorganization.

Although circadian and sleep disorders are frequently associated with autism spectrum disorders (ASD), it remains elusive whether clock gene disruption can lead to autistic-like phenotypes in animals. The essential clock gene Bmal1 has been associated with human sociability and its missense mutations are identified in ASD. Here we report that global Bmal1 deletion led to significant social impairments, excessive stereotyped and repetitive behaviors, as well as motor learning disabilities in mice, all of which resemble core behavioral deficits in ASD. Furthermore, aberrant cell density and immature morphology of dendritic spines were identified in the cerebellar Purkinje cells (PCs) of Bmal1 knockout (KO) mice. Electrophysiological recordings uncovered enhanced excitatory and inhibitory synaptic transmission and reduced firing rates in the PCs of Bmal1 KO mice. Differential expression of ASD- and ataxia-associated genes (Ntng2, Mfrp, Nr4a2, Thbs1, Atxn1, and Atxn3) and dysregulated pathways of translational control, including hyperactivated mammalian target of rapamycin complex 1 (mTORC1) signaling, were identified in the cerebellum of Bmal1 KO mice. Interestingly, the antidiabetic drug metformin reversed mTORC1 hyperactivation and alleviated major behavioral and PC deficits in Bmal1 KO mice. Importantly, conditional Bmal1 deletion only in cerebellar PCs was sufficient to recapitulate autistic-like behavioral and cellular changes akin to those identified in Bmal1 KO mice. Together, these results unveil a previously unidentified role for Bmal1 disruption in cerebellar dysfunction and autistic-like behaviors. Our findings provide experimental evidence supporting a putative role for dysregulation of circadian clock gene expression in the pathogenesis of ASD.

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.

Background Organoids or spheroids have emerged as a physiologically relevant in vitro preclinical model to study patient-specific diseases. A recent study used spheroids of MCF10 cells to model breast cancer progression and identified targetable alterations more similar to those in vivo. Thus, it is practical and essential to explore and characterize the spheroids of the commonly used human breast cancer (BC) cells. Methods In this study, we conducted Hi-C analyses in three-dimensional (3D) spheroids of MCF10A, MCF7 and MCF7TR cells and compared TADs and looping genes with those in 2D monolayers. Furthermore, we performed in silico functional analysis on 3D-growth-specific looping genes and to compare patient outcomes with or without endocrinal therapy. Finally, we performed 3C/RT-qPCR validations in 3D spheroids and 3D-FISH confirmations in organoids of breast cancer patient tissues. Results We found that chromatin structures have experienced drastic changes during the 3D culture growth of BC cells although there is not much change in the quantity of chromatin domains. We also observed that the strengths of looping genes were statistically different between 2D monolayers and 3D spheroids. We further identified novel 3D growth-specific looping genes within Hippo relevant pathways, of which two genes showed potential prognostic values in measuring the outcome of the endocrine treatment. We finally confirmed a few selected genes in Hippo relevant pathways with enhanced looping in organoids of breast cancer patient tissues. Conclusions Hence, our work has provided significant insights into our understanding of 3D-growth-specific chromatin architecture in tamoxifen-resistant breast cancer. Our analyses suggest that the strengthened looping-mediated Hippo relevant pathways may contribute to endocrine therapy resistance in breast cancer patients.

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

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 (BRCA1mut/+) 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 BRCA1mut/+ MCF10A cells recapitulate the H3K27ac loss. Attenuated histone mark and enhancer activity in these BRCA1mut/+ MCF10A cells can be partially restored with wild-type BRCA1. Furthermore, chromatin conformation analysis demonstrates impaired enhancer-promoter looping in BRCA1mut/+ 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. Electronic supplementary material The online version of this article (10.1186/s13058-019-1132-1) contains supplementary material, which is available to authorized users.

Recruitment of transcription machinery to target promoters for aberrant gene expression has been well studied, but underlying control directed by distant-acting enhancers remains unclear in cancer development. Our previous study demonstrated that distant estrogen response elements (DEREs) located on chromosome 20q13 are frequently amplified and translocated to other chromosomes in ERα-positive breast cancer cells. In this study, we used three-dimensional interphase fluorescence in situ hybridization to decipher spatiotemporal gathering of multiple DEREs in the nucleus. Upon estrogen stimulation, scattered 20q13 DEREs were mobilized to form regulatory depots for synchronized gene expression of target loci. A chromosome conformation capture assay coupled with chromatin immunoprecipitation further uncovered that ERα-bound regulatory depots are tethered to heterochromatin protein 1 (HP1) for coordinated chromatin movement and histone modifications of target loci, resulting in transcription repression. Neutralizing HP1 function dysregulated the formation of DERE-involved regulatory depots and transcription inactivation of candidate tumor-suppressor genes. Deletion of amplified DEREs using the CRISPR/Cas9 genomic-editing system profoundly altered transcriptional profiles of proliferation-associated signaling networks, resulting in reduction of cancer cell growth. These findings reveal a formerly uncharacterized feature wherein multiple copies of the amplicon congregate as transcriptional units in the nucleus for synchronous regulation of function-related loci in tumorigenesis. Disruption of their assembly can be a new strategy for treating breast cancers and other malignancies.

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. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-3764-9) contains supplementary material, which is available to authorized users.

The breast cancer susceptibility gene BRCA1 is well known for its function in double-strand break (DSB) DNA repair. While BRCA1 is also implicated in transcriptional regulation, the physiological significance remains unclear. COBRA1 (also known as NELF-B) is a BRCA1-binding protein that regulates RNA polymerase II (RNAPII) pausing and transcription elongation. Here we interrogate functional interaction between BRCA1 and COBRA1 during mouse mammary gland development. Tissue-specific deletion of Cobra1 reduces mammary epithelial compartments and blocks ductal morphogenesis, alveologenesis and lactogenesis, demonstrating a pivotal role of COBRA1 in adult tissue development. Remarkably, these developmental deficiencies due to Cobra1 knockout are largely rescued by additional loss of full-length Brca1. Furthermore, Brca1/Cobra1 double knockout restores developmental transcription at puberty, alters luminal epithelial homoeostasis, yet remains deficient in homologous recombination-based DSB repair. Thus our genetic suppression analysis uncovers a previously unappreciated, DNA repair-independent function of BRCA1 in antagonizing COBRA1-dependent transcription programme during mammary gland development., 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 Brca1 in a DNA repair-independent manner.

Aberrant DNA methylation at promoters is often linked to tumorigenesis. But many aspects of DNA methylation remain unexplored, including the individual roles of distal and gene body methylation, as well as their collaborative roles with promoter methylation. Here we performed a MBD-seq analysis on prostate specimens classified into low, high and very high risk group based on Gleason score and TNM stages. We identified gene sets with differential methylation regions (DMRs) in Distal, TSS, gene body and TES. To understand the collaborative roles, TSS was compared with the other three DMRs, resulted in 12 groups of genes with collaborative differential methylation patterns (CDMPs). We found several groups of genes that show opposite methylation patterns in Distal and Genic regions compared to TSS region and in general they are differentially expressed genes (DEGs) in tumors in TCGA RNA-seq data. IPA (Ingenuity Pathway Analysis) reveals AR/TP53 signaling network to be a major signaling pathway and survival analysis indicates genes subsets significantly associated with prostate cancer recurrence. Our results suggest that DNA methylation in Distal and Genic regions also plays critical roles in contributing to prostate tumorigenesis and may act either positively or negatively with TSSs to alter gene regulation in tumors.

Glucocorticoids (GCs) have been widely used as coadjuvants in the treatment of solid tumours, but GC treatment may be associated with poor pharmacotherapeutic response or prognosis. The genomic action of GC in these tumours is largely unknown. Here we find that dexamethasone (Dex, a synthetic GC)-regulated genes in triple-negative breast cancer (TNBC) cells are associated with drug resistance. Importantly, these GC-regulated genes are aberrantly expressed in TNBC patients and are associated with unfavourable clinical outcomes. Interestingly, in TNBC cells, Compound A (CpdA, a selective GR modulator) only regulates a small number of genes not involved in carcinogenesis and therapy resistance. Mechanistic studies using a ChIP-exo approach reveal that Dex- but not CpdA-liganded glucocorticoid receptor (GR) binds to a single glucocorticoid response element (GRE), which drives the expression of pro-tumorigenic genes. Our data suggest that development of safe coadjuvant therapy should consider the distinct genomic function between Dex- and CpdA-liganded GR., Glucocorticoids are widely used as coadjuvants in the treatment of solid tumours. Here, Chen et al. show that genes regulated by dexamethasone- but not Compound A-liganded glucocorticoid receptor are associated with therapy resistance and unfavourable clinical outcomes in triple-negative breast cancer.

A series of novel bischelate bridging ligands, CH3NH(CH2)2N(CH3)(CH2)nN(CH3)(CH2)2NHCH3 (n = 9, 10, 11, and 12) were synthesized as hydrochloride salts and characterized by elemental analyses, electrospray mass spectrometry, and 1H and 13C NMR spectroscopy. These ligands form [2]pseudorotaxanes with α-cyclodextrin (α-CD) and the stability constants have been determined from 1H NMR titrations in D2O. The kinetics and mechanism of the assembly and dissociation of a [2]pseudorotaxane in which α-CD has been threaded by the CH3NH2(CH2)2N(CH3)(CH2)12N(CH3)(CH2)2NH2CH32+ ligand were determined in aqueous solution using 1H NMR spectroscopy. A weak inclusion of the dimethylethylenediamine end group precedes the passage of the α-CD onto the hydrophobic dodecamethylene chain.

Many computational programs have been developed to identify enriched regions for a single biological ChIP-seq sample. Given that many biological questions are often asked to compare the difference between two different conditions, it is important to develop new programs that address the comparison of two biological ChIP-seq samples. Despite several programs designed to address this question, these programs suffer from some drawbacks, such as inability to distinguish whether the identified differential enriched regions are indeed significantly enriched, lack of distinguishing binding patterns, and neglect of the normalization between samples. In this study, we developed a novel quantitative method for comparing two biological ChIP-seq samples, called QChIPat. Our method employs a new global normalization method: nonparametric empirical Bayes (NEB) correction normalization, utilizes pre-defined enriched regions identified from single-sample peak calling programs, uses statistical methods to define differential enriched regions, then defines binding (histone modification) pattern information for those differential enriched regions. Our program was tested on a benchmark data: histone modifications data used by ChIPDiffs. It was then applied on two study cases: one to identify differential histone modification sites for ChIP-seq of H3K27me3 and H3K9me2 data in AKT1-transfected MCF10A cells; the other to identify differential binding sites for ChIP-seq of TCF7L2 data in MCF7 and PANC1 cells. Several advantages of our program include: 1) it considers a control (or input) experiment; 2) it incorporates a novel global normalization strategy: nonparametric empirical Bayes correction normalization; 3) it provides the binding pattern information among different enriched regions. QChIPat is implemented in R, Perl and C++, and has been tested under Linux. The R package is available at http://motif.bmi.ohio-state.edu/QChIPat .

The second ISCB-Asia conference of the International Society for Computational Biology took place December 17-19, 2012, in Shenzhen, China. The conference was co-hosted by BGI as the first Shenzhen Conference on Computational Genomics (SCCG). 45 talks were presented at ISCB-Asia/SCCG 2012. The topics covered included software tools, reproducible computing, next-generation sequencing data analysis, transcription and mRNA regulation, protein structure and function, cancer genomics and personalized medicine. Nine of the proceedings track talks are included as full papers in this supplement. In this report we first give a short overview of the conference by listing some statistics and visualizing the talk abstracts as word clouds. Then we group the talks by topic and briefly summarize each one, providing references to related publications whenever possible. Finally, we close with a few comments on the success of this conference.

Background Global profiling of in vivo protein-DNA interactions using ChIP-based technologies has evolved rapidly in recent years. Although many genome-wide studies have identified thousands of ERα binding sites and have revealed the associated transcription factor (TF) partners, such as AP1, FOXA1 and CEBP, little is known about ERα associated hierarchical transcriptional regulatory networks. Results In this study, we applied computational approaches to analyze three public available ChIP-based datasets: ChIP-seq, ChIP-PET and ChIP-chip, and to investigate the hierarchical regulatory network for ERα and ERα partner TFs regulation in estrogen-dependent breast cancer MCF7 cells. 16 common TFs and two common new TF partners (RORA and PITX2) were found among ChIP-seq, ChIP-chip and ChIP-PET datasets. The regulatory networks were constructed by scanning the ChIP-peak region with TF specific position weight matrix (PWM). A permutation test was performed to test the reliability of each connection of the network. We then used DREM software to perform gene ontology function analysis on the common genes. We found that FOS, PITX2, RORA and FOXA1 were involved in the up-regulated genes. We also conducted the ERα and Pol-II ChIP-seq experiments in tamoxifen resistance MCF7 cells (denoted as MCF7-T in this study) and compared the difference between MCF7 and MCF7-T cells. The result showed very little overlap between these two cells in terms of targeted genes (21.2% of common genes) and targeted TFs (25% of common TFs). The significant dissimilarity may indicate totally different transcriptional regulatory mechanisms between these two cancer cells. Conclusions Our study uncovers new estrogen-mediated regulatory networks by mining three ChIP-based data in MCF7 cells and ChIP-seq data in MCF7-T cells. We compared the different ChIP-based technologies as well as different breast cancer cells. Our computational analytical approach may guide biologists to further study the underlying mechanisms in breast cancer cells or other human diseases.

Background The canonical core promoter elements consist of the TATA box, initiator (Inr), downstream core promoter element (DPE), TFIIB recognition element (BRE) and the newly-discovered motif 10 element (MTE). The motifs for these core promoter elements are highly degenerate, which tends to lead to a high false discovery rate when attempting to detect them in promoter sequences. Results In this study, we have performed the first analysis of these core promoter elements in orthologous mouse and human promoters with experimentally-supported transcription start sites. We have identified these various elements using a combination of positional weight matrices (PWMs) and the degree of conservation of orthologous mouse and human sequences – a procedure that significantly reduces the false positive rate of motif discovery. Our analysis of 9,010 orthologous mouse-human promoter pairs revealed two combinations of three-way synergistic effects, TATA-Inr-MTE and BRE-Inr-MTE. The former has previously been putatively identified in human, but the latter represents a novel synergistic relationship. Conclusion Our results demonstrate that DNA sequence conservation can greatly improve the identification of functional core promoter elements in the human genome. The data also underscores the importance of synergistic occurrence of two or more core promoter elements. Furthermore, the sequence data and results presented here can help build better computational models for predicting the transcription start sites in the promoter regions, which remains one of the most challenging problems.