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HFE (Hemochromatosis) is a conventional iron level regulator and its loss of function due to gene mutations increases the risk of cancers including hepatocellular carcinoma (HCC). Likewise, studies focusing on HFE overexpression in cancers are all limited to linking up these events as a consequence of iron level deregulation. No study has explored any iron unrelated role of HFE in cancers. Here, we first reported HFE as an oncogene in HCC and its undescribed function on promoting abscission in cytokinesis during mitotic cell division, independent of its iron-regulating ability. Clinical analyses revealed HFE upregulation in tumors linking to large tumor size and poor prognosis. Functionally and mechanistically, HFE promoted cytokinetic abscission via facilitating ESCRT abscission machinery recruitment to the abscission site through signaling a novel HFE/ALK3/Smads/LIF/Hippo/YAP/YY1/KIF13A axis. Pharmacological blockage of HFE signaling axis impeded tumor phenotypes in vitro and in vivo. Our data on HFE-driven HCC unveiled a new mechanism utilized by cancer cells to propel rapid cell division. This study also laid the groundwork for tumor intolerable therapeutics development given the high cytokinetic dependency of cancer cells and their vulnerability to cytokinetic blockage.

Neural stem cells (NSCs) divide asymmetrically to balance their self-renewal and differentiation, an imbalance in which can lead to NSC overgrowth and tumor formation. The functions of Parafibromin, a conserved tumor suppressor, in the nervous system are not established. Here, we demonstrate that Drosophila Parafibromin/Hyrax (Hyx) inhibits ectopic NSC formation by governing cell polarity. Hyx is essential for the asymmetric distribution and/or maintenance of polarity proteins. hyx depletion results in the symmetric division of NSCs, leading to the formation of supernumerary NSCs in the larval brain. Importantly, we show that human Parafibromin rescues the ectopic NSC phenotype in Drosophila hyx mutant brains. We have also discovered that Hyx is required for the proper formation of interphase microtubule-organizing center and mitotic spindles in NSCs. Moreover, Hyx is required for the proper localization of 2 key centrosomal proteins, Polo and AurA, and the microtubule-binding proteins Msps and D-TACC in dividing NSCs. Furthermore, Hyx directly regulates the polo and aurA expression in vitro. Finally, overexpression of polo and aurA could significantly suppress ectopic NSC formation and NSC polarity defects caused by hyx depletion. Our data support a model in which Hyx promotes the expression of polo and aurA in NSCs and, in turn, regulates cell polarity and centrosome/microtubule assembly. This new paradigm may be relevant to future studies on Parafibromin/HRPT2-associated cancers.

Integration of human papillomavirus (HPV) DNA into the human genome is a reputed key driver of cervical cancer. However, the effects of HPV integration on chromatin structural organization and gene expression are largely unknown. We studied a cohort of 61 samples and identified an integration hot spot in the CCDC106 gene on chromosome 19. We then selected fresh cancer tissue that contained the unique integration loci at CCDC106 with no HPV episomal DNA and performed whole-genome, RNA, chromatin immunoprecipitation and high-throughput chromosome conformation capture (Hi-C) sequencing to identify the mechanisms of HPV integration in cervical carcinogenesis. Molecular analyses indicated that chromosome 19 exhibited significant genomic variation and differential expression densities, with correlation found between three-dimensional (3D) structural change and gene expression. Importantly, HPV integration divided one topologically associated domain (TAD) into two smaller TADs and hijacked an enhancer from PEG3 to CCDC106, with a decrease in PEG3 expression and an increase in CCDC106 expression. This expression dysregulation was further confirmed using 10 samples from our cohort, which exhibited the same HPV-CCDC106 integration. In summary, we found that HPV-CCDC106 integration altered local chromosome architecture and hijacked an enhancer via 3D genome structure remodeling. Thus, this study provides insight into the 3D structural mechanism underlying HPV integration in cervical carcinogenesis.

DNA methylation is known to be the most stable epigenetic modification and has been extensively studied in relation to cell differentiation, development, X chromosome inactivation and disease. Allele-specific DNA methylation (ASM) is a well-established mechanism for genomic imprinting and regulates imprinted gene expression. Previous studies have confirmed that certain special regions with ASM are susceptible and closely related to human carcinogenesis and plant development. In addition, recent studies have proven ASM to be an effective tumour marker. However, research on the functions of ASM in diseases and development is still extremely scarce. Here, we collected 4400 BS-Seq datasets and 1598 corresponding RNA-Seq datasets from 47 species, including human and mouse, to establish a comprehensive ASM database. We obtained the data on DNA methylation level, ASM and allele-specific expressed genes (ASEGs) and further analysed the ASM/ASEG distribution patterns of these species. In-depth ASM distribution analysis and differential methylation analysis conducted in nine cancer types showed results consistent with the reported changes in ASM in key tumour genes and revealed several potential ASM tumour-related genes. Finally, integrating these results, we constructed the first well-resourced and comprehensive ASM database for 47 species (ASMdb, www.dna-asmdb.com).

Androgen receptor (AR) plays a central role in driving prostate cancer (PCa) progression. How AR promotes this process is still not completely clear. Herein, we used single-cell transcriptome analysis to reconstruct the transcriptional network of AR in PCa. Our work shows AR directly regulates a set of signature genes in the ER-to-Golgi protein vesicle-mediated transport pathway. The expression of these genes is required for maximum androgen-dependent ER-to-Golgi trafficking, cell growth, and survival. Our analyses also reveal the signature genes are associated with PCa progression and prognosis. Moreover, we find inhibition of the ER-to-Golgi transport process with a small molecule enhanced antiandrogen-mediated tumor suppression of hormone-sensitive and insensitive PCa. Finally, we demonstrate AR collaborates with CREB3L2 in mediating ER-to-Golgi trafficking in PCa. In summary, our findings uncover a critical role for dysregulation of ER-to-Golgi trafficking expression and function in PCa progression, provide detailed mechanistic insights for how AR tightly controls this process, and highlight the prospect of targeting the ER-to-Golgi pathway as a therapeutic strategy for advanced PCa.

Angiosarcomas are rare, clinically aggressive tumors with limited treatment options and a dismal prognosis. We analyzed angiosarcomas from 68 patients, integrating information from multiomic sequencing, NanoString immuno-oncology profiling, and multiplex immunohistochemistry and immunofluorescence for tumor-infiltrating immune cells. Through whole-genome sequencing (n = 18), 50% of the cutaneous head and neck angiosarcomas exhibited higher tumor mutation burden (TMB) and UV mutational signatures; others were mutationally quiet and non–UV driven. NanoString profiling revealed 3 distinct patient clusters represented by lack (clusters 1 and 2) or enrichment (cluster 3) of immune-related signaling and immune cells. Neutrophils (CD15(+)), macrophages (CD68(+)), cytotoxic T cells (CD8(+)), Tregs (FOXP3(+)), and PD-L1(+) cells were enriched in cluster 3 relative to clusters 2 and 1. Likewise, tumor inflammation signature (TIS) scores were highest in cluster 3 (7.54 vs. 6.71 vs. 5.75, respectively; P < 0.0001). Head and neck angiosarcomas were predominant in clusters 1 and 3, providing the rationale for checkpoint immunotherapy, especially in the latter subgroup with both high TMB and TIS scores. Cluster 2 was enriched for secondary angiosarcomas and exhibited higher expression of DNMT1, BRD3/4, MYC, HRAS, and PDGFRB, in keeping with the upregulation of epigenetic and oncogenic signaling pathways amenable to targeted therapies. Molecular and immunological dissection of angiosarcomas may provide insights into opportunities for precision medicine.

Accumulation of trimethylation of histone H3 at lysine 4 (H3K4me3) on immune-related gene promoters underlies robust transcription during trained immunity. However, the molecular basis for this remains unknown. Here we show three-dimensional chromatin topology enables immune genes to engage in chromosomal contacts with a subset of long noncoding RNAs (lncRNAs) we have defined as immune gene–priming lncRNAs (IPLs). We show that the prototypical IPL, UMLILO, acts in cis to direct the WD repeat-containing protein 5 (WDR5)–mixed lineage leukemia protein 1 (MLL1) complex across the chemokine promoters, facilitating their H3K4me3 epigenetic priming. This mechanism is shared amongst several trained immune genes. Training mediated by β-glucan epigenetically reprograms immune genes by upregulating IPLs in manner dependent on nuclear factor of activated T cells. The murine chemokine topologically associating domain lacks an IPL, and the Cxcl genes are not trained. Strikingly, the insertion of UMLILO into the chemokine topologically associating domain in mouse macrophages resulted in training of Cxcl genes. This provides strong evidence that lncRNA-mediated regulation is central to the establishment of trained immunity. This study shows that immune-related genes are primed for transcription by proximal lncRNAs. One such lncRNA, UMLILO, directs the WDR5–MLL1 complex to CXCL chemokine promoters, facilitating H3K4me3 deposition.

Hepatocellular carcinoma (HCC) has one of the poorest survival rates among cancers. Using multi-regional sampling of nine resected HCC with different aetiologies, here we construct phylogenetic relationships of these sectors, showing diverse levels of genetic sharing, spanning early to late diversification. Unlike the variegated pattern found in colorectal cancers, a large proportion of HCC display a clear isolation-by-distance pattern where spatially closer sectors are genetically more similar. Two resected intra-hepatic metastases showed genetic divergence occurring before and after primary tumour diversification, respectively. Metastatic tumours had much higher variability than their primary tumours, suggesting that intra-hepatic metastasis is accompanied by rapid diversification at the distant location. The presence of co-existing mutations offers the possibility of drug repositioning for HCC treatment. Taken together, these insights into intra-tumour heterogeneity allow for a comprehensive understanding of the evolutionary trajectories of HCC and suggest novel avenues for personalized therapy., Hepatocellular carcinoma has one of the poorest survival rates amongst cancers. Here, the authors highlight the intra-tumour heterogeneity of this disease, finding that spatially closer tumour sectors are genetically more similar and that intra-hepatic metastasis is accompanied by rapid genetic diversification.

Background Hepatocellular carcinoma is the second most deadly cancer with late presentation and limited treatment options, highlighting an urgent need to better understand HCC to facilitate the identification of early-stage biomarkers and uncover therapeutic targets for the development of novel therapies for HCC. Methods Deep transcriptome sequencing of tumor and paired non-tumor liver tissues was performed to comprehensively evaluate the profiles of both the host and HBV transcripts in HCC patients. Differential gene expression patterns and the dys-regulated genes associated with clinical outcomes were analyzed. Somatic mutations were identified from the sequencing data and the deleterious mutations were predicted. Lastly, human-HBV chimeric transcripts were identified, and their distribution, potential function and expression association were analyzed. Results Expression profiling identified the significantly upregulated TP73 as a nodal molecule modulating expression of apoptotic genes. Approximately 2.5% of dysregulated genes significantly correlated with HCC clinical characteristics. Of the 110 identified genes, those involved in post-translational modification, cell division and/or transcriptional regulation were upregulated, while those involved in redox reactions were downregulated in tumors of patients with poor prognosis. Mutation signature analysis identified that somatic mutations in HCC tumors were mainly non-synonymous, frequently affecting genes in the micro-environment and cancer pathways. Recurrent mutations occur mainly in ribosomal genes. The most frequently mutated genes were generally associated with a poorer clinical prognosis. Lastly, transcriptome sequencing suggest that HBV replication in the tumors of HCC patients is rare. HBV-human fusion transcripts are a common observation, with favored HBV and host insertion sites being the HBx C-terminus and gene introns (in tumors) and introns/intergenic-regions (in non-tumors), respectively. HBV-fused genes in tumors were mainly involved in RNA binding while those in non-tumors tissues varied widely. These observations suggest that while HBV may integrate randomly during chronic infection, selective expression of functional chimeric transcripts may occur during tumorigenesis. Conclusions Transcriptome sequencing of HCC patients reveals key cancer molecules and clinically relevant pathways deregulated/mutated in HCC patients and suggests that while HBV may integrate randomly during chronic infection, selective expression of functional chimeric transcripts likely occur during the process of tumorigenesis.

The aberrant activities of transcription factors such as the androgen receptor (AR) underpin prostate cancer development. While the AR cis-regulation has been extensively studied in prostate cancer, information pertaining to the spatial architecture of the AR transcriptional circuitry remains limited. In this paper, we propose a novel framework to profile long-range chromatin interactions associated with AR and its collaborative transcription factor, erythroblast transformation-specific related gene (ERG), using chromatin interaction analysis by paired-end tag (ChIA-PET). We identified ERG-associated long-range chromatin interactions as a cooperative component in the AR-associated chromatin interactome, acting in concert to achieve coordinated regulation of a subset of AR target genes. Through multifaceted functional data analysis, we found that AR-ERG interaction hub regions are characterized by distinct functional signatures, including bidirectional transcription and cotranscription factor binding. In addition, cancer-associated long noncoding RNAs were found to be connected near protein-coding genes through AR-ERG looping. Finally, we found strong enrichment of prostate cancer genome-wide association study (GWAS) single nucleotide polymorphisms (SNPs) at AR-ERG co-binding sites participating in chromatin interactions and gene regulation, suggesting GWAS target genes identified from chromatin looping data provide more biologically relevant findings than using the nearest gene approach. Taken together, our results revealed an AR-ERG-centric higher-order chromatin structure that drives coordinated gene expression in prostate cancer progression and the identification of potential target genes for therapeutic intervention.

We evaluate sequence data from the PathChip high-density hybridization array for epidemiological interpretation of detected pathogens. For influenza A, we derive similar relative outbreak clustering in phylogenetic trees from PathChip-derived compared to classical Sanger-derived sequences. For a positive polio detection, recent infection could be excluded based on vaccine strain similarity.

A significant portion of human cancers are due to viruses integrating into human genomes. Therefore, accurately predicting virus integrations can help uncover the mechanisms that lead to many devastating diseases. Virus integrations can be called by analysing second generation high-throughput sequencing datasets. Unfortunately, existing methods fail to report a significant portion of integrations, while predicting a large number of false positives. We observe that the inaccuracy is caused by incorrect alignment of reads in repetitive regions. False alignments create false positives, while missing alignments create false negatives. This paper proposes SurVirus, an improved virus integration caller that corrects the alignment of reads which are crucial for the discovery of integrations. We use publicly available datasets to show that existing methods predict hundreds of thousands of false positives; SurVirus, on the other hand, is significantly more precise while it also detects many novel integrations previously missed by other tools, most of which are in repetitive regions. We validate a subset of these novel integrations, and find that the majority are correct. Using SurVirus, we find that HPV and HBV integrations are enriched in LINE and Satellite regions which had been overlooked, as well as discover recurrent HBV and HPV breakpoints in human genome-virus fusion transcripts.

The [Formula: see text] Consistency problem takes as input two sets [Formula: see text] and [Formula: see text] of resolved triplets and two sets [Formula: see text] and [Formula: see text] of fan triplets, and asks for a distinctly leaf-labeled tree that contains all elements in [Formula: see text] and no elements in [Formula: see text] as embedded subtrees, if such a tree exists. This article presents a detailed characterization of how the computational complexity of the problem changes under various restrictions. Our main result is an efficient algorithm for dense inputs satisfying [Formula: see text] whose running time is linear in the size of the input and therefore optimal.

Transpositions transfer DNA segments between different loci within a genome; in particular, when a transposition is found in a sample but not in a reference genome, it is called a non-reference transposition. They are important structural variations that have clinical impact. Transpositions can be called by analyzing second generation high-throughput sequencing datasets. Current methods follow either a database-based or a database-free approach. Database-based methods require a database of transposable elements. Some of them have good specificity; however this approach cannot detect novel transpositions, and it requires a good database of transposable elements, which is not yet available for many species. Database-free methods perform de novo calling of transpositions, but their accuracy is low. We observe that this is due to the misalignment of the reads; since reads are short and the human genome has many repeats, false alignments create false positive predictions while missing alignments reduce the true positive rate. This paper proposes new techniques to improve database-free non-reference transposition calling: first, we propose a realignment strategy called one-end remapping that corrects the alignments of reads in interspersed repeats; second, we propose a SNV-aware filter that removes some incorrectly aligned reads. By combining these two techniques and other techniques like clustering and positive-to-negative ratio filter, our proposed transposition caller TranSurVeyor shows at least 3.1-fold improvement in terms of F1-score over existing database-free methods. More importantly, even though TranSurVeyor does not use databases of prior information, its performance is at least as good as existing database-based methods such as MELT, Mobster and Retroseq. We also illustrate that TranSurVeyor can discover transpositions that are not known in the current database.

Somatic mutations of TP53 are among the most common in cancer and germline mutations of TP53 (usually missense) can cause Li-Fraumeni syndrome (LFS). Recently, recurrent genomic rearrangements in intron 1 of TP53 have been described in osteosarcoma (OS), a highly malignant neoplasm of bone belonging to the spectrum of LFS tumors. Using whole-genome sequencing of OS, we found features of TP53 intron 1 rearrangements suggesting a unique mechanism correlated with transcription. Screening of 288 OS and 1,090 tumors of other types revealed evidence for TP53 rearrangements in 46 (16%) OS, while none were detected in other tumor types, indicating this rearrangement to be highly specific to OS. We revisited a four-generation LFS family where no TP53 mutation had been identified and found a 445 kb inversion spanning from the TP53 intron 1 towards the centromere. The inversion segregated with tumors in the LFS family. Cancers in this family had loss of heterozygosity, retaining the rearranged allele and resulting in TP53 expression loss. In conclusion, intron 1 rearrangements cause p53-driven malignancies by both germline and somatic mechanisms and provide an important mechanism of TP53 inactivation in LFS, which might in part explain the diagnostic gap of formerly classified "TP53 wild-type" LFS.

Background DNA methylation plays crucial roles in most eukaryotic organisms. Bisulfite sequencing (BS-Seq) is a sequencing approach that provides quantitative cytosine methylation levels in genome-wide scope and single-base resolution. However, genomic variations such as insertions and deletions (indels) affect methylation calling, and the alignment of reads near/across indels becomes inaccurate in the presence of polymorphisms. Hence, the simultaneous detection of DNA methylation and indels is important for exploring the mechanisms of functional regulation in organisms. Results These problems motivated us to develop the algorithm BatMeth2, which can align BS reads with high accuracy while allowing for variable-length indels with respect to the reference genome. The results from simulated and real bisulfite DNA methylation data demonstrated that our proposed method increases alignment accuracy. Additionally, BatMeth2 can calculate the methylation levels of individual loci, genomic regions or functional regions such as genes/transposable elements. Additional programs were also developed to provide methylation data annotation, visualization, and differentially methylated cytosine/region (DMC/DMR) detection. The whole package provides new tools and will benefit bisulfite data analysis. Conclusion BatMeth2 improves DNA methylation calling, particularly for regions close to indels. It is an autorun package and easy to use. In addition, a DNA methylation visualization program and a differential analysis program are provided in BatMeth2. We believe that BatMeth2 will facilitate the study of the mechanisms of DNA methylation in development and disease. BatMeth2 is an open source software program and is available on GitHub (https://github.com/GuoliangLi-HZAU/BatMeth2/). Electronic supplementary material The online version of this article (10.1186/s12859-018-2593-4) contains supplementary material, which is available to authorized users.

Accumulation of trimethylation of histone H3 at lysine 4 (H3K4me3) on immune-related gene promoters underlies robust transcription during trained immunity. However, the molecular basis for this remains unknown. Here we show three-dimensional chromatin topology enables immune genes to engage in chromosomal contacts with a subset of long noncoding RNAs (lncRNAs) we have defined as immune gene-priming lncRNAs (IPLs). We show that the prototypical IPL, UMLILO, acts in cis to direct the WD repeat-containing protein 5 (WDR5)-mixed lineage leukemia protein 1 (MLL1) complex across the chemokine promoters, facilitating their H3K4me3 epigenetic priming. This mechanism is shared amongst several trained immune genes. Training mediated by β-glucan epigenetically reprograms immune genes by upregulating IPLs in manner dependent on nuclear factor of activated T cells. The murine chemokine topologically associating domain lacks an IPL, and the Cxcl genes are not trained. Strikingly, the insertion of UMLILO into the chemokine topologically associating domain in mouse macrophages resulted in training of Cxcl genes. This provides strong evidence that lncRNA-mediated regulation is central to the establishment of trained immunity.

Hepatocellular carcinoma (HCC) is the most common type of liver cancer worldwide. Previously, we reported that cadherin-17 (CDH17) and its related CDH17/β-catenin axis may be responsible for inducing HCC in a subset of patients exhibiting CDH17 over-expression. Here we aimed at obtaining a better understanding of the CDH17-related HCC biology and to obtain further indications for the design of targeted therapies in CDH17 over-expressing HCC patients. We found that SPINK1 acts as a downstream effector of the CDH17/β-catenin axis in HCC. In addition, we found that SPINK1 expression exhibited a positive correlation with CDH17 expression in human HCCs and was over-expressed in up to 70% of the tumors. We identified SPINK1 as a downstream effector of the CDH17/β-catenin axis using a spectrum of in vitro assays, including gene expression modulation and inhibitor assays, bioinformatics analyses and luciferase reporter assays. These in vitro results were validated in primary human HCCs, including the observation that alteration in β-catenin expression (a core component of the CDH17/β-catenin axis) in tumors affects SPINK1 serum levels in HCC patients. Similar to CDH17, SPINK1 expression in HCC cells was found to be associated with specific tumor-related properties via activating the c-Raf/MEK/ERK pathway. Our current data substantiate our knowledge on the role of CDH17 in the biology of HCC and suggest that components of the CDH17/β-catenin axis may serve as therapeutic targets in CDH17 over-expressing HCC patients.

The study of virus integrations in human genome is important since virus integrations were shown to be associated with diseases. In the literature, few methods have been proposed that predict virus integrations using next generation sequencing datasets. Although they work, they are slow and are not very sensitive. This paper introduces a new method BatVI to predict viral integrations. Our method uses a fast screening method to filter out chimeric reads containing possible viral integrations. Next, sensitive alignments of these candidate chimeric reads are called by BLAST. Chimeric reads that are co-localized in the human genome are clustered. Finally, by assembling the chimeric reads in each cluster, high confident virus integration sites are extracted. We compared the performance of BatVI with existing methods VirusFinder and VirusSeq using both simulated and real-life datasets of liver cancer patients. BatVI ran an order of magnitude faster and was able to predict almost twice the number of true positives compared to other methods while maintaining a false positive rate less than 1%. For the liver cancer datasets, BatVI uncovered novel integrations to two important genes TERT and MLL4, which were missed by previous studies. Through gene expression data, we verified the correctness of these additional integrations. BatVI can be downloaded from http://biogpu.ddns.comp.nus.edu.sg/~ksung/batvi/index.html .

For a long period of time, scientists studied genomes while assuming they are linear. Recently, chromosome conformation capture (3C)-based technologies, such as Hi-C, have been developed that provide the loci contact frequencies among loci pairs in a genome-wide scale. The technology unveiled that two far-apart loci can interact in the tested genome. It indicated that the tested genome forms a three-dimensional (3D) chromosomal structure within the nucleus. With the available Hi-C data, our next challenge is to model the 3D chromosomal structure from the 3C-derived data computationally. This article presents a deterministic method called ChromSDE, which applies semi-definite programming techniques to find the best structure fitting the observed data and uses golden section search to find the correct parameter for converting the contact frequency to spatial distance. Further, we develop a measure called consensus index to indicate if the Hi-C data corresponds to a single structure or a mixture of structures. To the best of our knowledge, ChromSDE is the only method that can guarantee recovering the correct structure in the noise-free case. In addition, we prove that the parameter of conversion from contact frequency to spatial distance will change under different resolutions theoretically and empirically. Using simulation data and real Hi-C data, we showed that ChromSDE is much more accurate and robust than existing methods. Finally, we demonstrated that interesting biological findings can be uncovered from our predicted 3D structure.

Although elongation of telomeres is thought to be the prime function of reactivated telomerase in cancers, this activity alone does not account for all of the properties that telomerase reactivation attributes to human cancer cells. Here, we uncover a link between telomerase and NF-κB, a master regulator of inflammation. We observe that while blocking NF-κB signalling can inhibit effects of telomerase overexpression on processes relevant to transformation, increasing NF-κB activity can functionally substitute for reduced telomerase activity. Telomerase directly regulates NF-κB-dependent gene expression by binding to the NF-κB p65 subunit and recruitment to a subset of NF-κB promoters such as those of IL-6 and TNF-α, cytokines that are critical for inflammation and cancer progression. As NF-κB can transcriptionally upregulate telomerase levels, our findings suggest that a feed-forward regulation between them could be the key mechanistic basis for the coexistence of chronic inflammation and sustained telomerase activity in human cancers.

SUMMARY Chromatin interactions play important roles in transcription regulation. To better understand the underlying evolutionary and functional constraints of these interactions, we implemented a systems approach to examine RNA polymerase-II-associated chromatin interactions in human cells. We found that 40% of the total genomic elements involved in chromatin interactions converged to a giant, scale-free-like, hierarchical network organized into chromatin communities. The communities were enriched in specific functions and were syntenic through evolution. Disease-associated SNPs from genome-wide association studies were enriched among the nodes with fewer interactions, implying their selection against deleterious interactions by limiting the total number of interactions, a model that we further reconciled using somatic and germline cancer mutation data. The hubs lacked disease-associated SNPs, constituted a nonrandomly interconnected core of key cellular functions, and exhibited lethality in mouse mutants, supporting an evolutionary selection that favored the nonrandom spatial clustering of the least-evolving key genomic domains against random genetic or transcriptional errors in the genome. Altogether, our analyses reveal a systems-level evolutionary framework that shapes functionally compartmentalized and error-tolerant transcriptional regulation of human genome in three dimensions.

Long-range chromatin contacts between specific DNA regulatory elements play a pivotal role in gene expression regulation, and a global characterization of these interactions in the 3-dimensional (3D) chromatin structure is imperative in understanding signaling networks and cell states. Chromatin Interaction Analysis using Paired-End Tag sequencing (ChIA-PET) is a method which converts functional chromatin structure into millions of short tag sequences. Combining Chromatin Immunoprecipitation (ChIP), proximity ligation and high-throughput sequencing, ChIA-PET provides a global and unbiased interrogation of higher-order chromatin structures associated with specific protein factors. Here, we describe the detailed procedures of the ChIA-PET methodology, unraveling transcription-associated chromatin contacts in a model human cell line.

Many biologically important protein-protein interactions (PPIs) have been found to be mediated by short linear motifs (SLiMs). These interactions are mediated by the binding of a protein domain, often with a nonlinear interaction interface, to a SLiM. We propose a method called D-SLIMMER to mine for SLiMs in PPI data on the basis of the interaction density between a nonlinear motif (i.e., a protein domain) in one protein and a SLiM in the other protein. Our results on a benchmark of 113 experimentally verified reference SLiMs showed that D-SLIMMER outperformed existing methods notably for discovering domain-SLiMs interaction motifs. To illustrate the significance of the SLiMs detected, we highlighted two SLiMs discovered from the PPI data by D-SLIMMER that are variants of the known ELM SLiM, as well as a literature-backed SLiM that is yet to be listed in the reference databases. We also presented a novel SLiM predicted by D-SLIMMER that was strongly supported by existing biological literatures. These examples showed that D-SLIMMER is able to find SLiMs that are biologically relevant.

Scaffolding, the problem of ordering and orienting contigs, typically using paired-end reads, is a crucial step in the assembly of high-quality draft genomes. Even as sequencing technologies and mate-pair protocols have improved significantly, scaffolding programs still rely on heuristics, with no guarantees on the quality of the solution. In this work, we explored the feasibility of an exact solution for scaffolding and present a first tractable solution for this problem (Opera). We also describe a graph contraction procedure that allows the solution to scale to large scaffolding problems and demonstrate this by scaffolding several large real and synthetic datasets. In comparisons with existing scaffolders, Opera simultaneously produced longer and more accurate scaffolds demonstrating the utility of an exact approach. Opera also incorporates an exact quadratic programming formulation to precisely compute gap sizes (Availability: http://sourceforge.net/projects/operasf/ ).

Eukaryotic genome is, not only linearly but also spatially, organized into non-random architecture. Though the linear organization of genes and their epigenetic descriptors are well characterized, the relevance of their spatial organization is beginning to unfold only recently. It is increasingly being recognized that physical interactions among distant genomic elements could serve as an important mean to eukaryotic genome regulation. With the advent of proximity ligation based techniques coupled with next generation sequencing, it is now possible to explore whole genome chromatin interactions at high resolution. Emerging data on genome-wide chromatin interactions suggest that distantly located genes are not independent entities and instead cross-talk with each other in an extensive manner, supporting the notion of “chromatin interaction networks”. Moreover, the data also advance the field to “3-dimensional (3D) chromatin structure and dynamics”, which would enable molecular biologists to explore the spatiotemporal regulation of genome. In this article, we introduce a stepwise topological transformation of genome from 1-dimension (1D, linear) to 2-dimension (2D, networks) to 3-dimension (3D, architecture) and discuss how such transformations could advance our understanding of genome biology. J. Cell. Biochem. 112: 2218–2221, 2011. © 2011 Wiley-Liss, Inc.

Transcription factors (TFs) do not function alone but work together with other TFs (called co-TFs) in a combinatorial fashion to precisely control the transcription of target genes. Mining co-TFs is thus important to understand the mechanism of transcriptional regulation. Although existing methods can identify co-TFs, their accuracy depends heavily on the chosen background model and other parameters such as the enrichment window size and the PWM score cut-off. In this study, we have developed a novel web-based co-motif scanning program called CENTDIST (http://compbio.ddns.comp.nus.edu.sg/~chipseq/centdist/). In comparison to current co-motif scanning programs, CENTDIST does not require the input of any user-specific parameters and background information. Instead, CENTDIST automatically determines the best set of parameters and ranks co-TF motifs based on their distribution around ChIP-seq peaks. We tested CENTDIST on 14 ChIP-seq data sets and found CENTDIST is more accurate than existing methods. In particular, we applied CENTDIST on an Androgen Receptor (AR) ChIP-seq data set from a prostate cancer cell line and correctly predicted all known co-TFs (eight TFs) of AR in the top 20 hits as well as discovering AP4 as a novel co-TF of AR (which was missed by existing methods). Taken together, CENTDIST, which exploits the imbalanced nature of co-TF binding, is a user-friendly, parameter-less and powerful predictive web-based program for understanding the mechanism of transcriptional co-regulation.

Genomes are organized into high-level three-dimensional structures, and DNA elements separated by long genomic distances can in principle interact functionally. Many transcription factors bind to regulatory DNA elements distant from gene promoters. Although distal binding sites have been shown to regulate transcription by long-range chromatin interactions at a few loci, chromatin interactions and their impact on transcription regulation have not been investigated in a genome-wide manner. Here we describe the development of a new strategy, chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) for the de novo detection of global chromatin interactions, with which we have comprehensively mapped the chromatin interaction network bound by oestrogen receptor α (ER-α) in the human genome. We found that most high-confidence remote ER-α-binding sites are anchored at gene promoters through long-range chromatin interactions, suggesting that ER-α functions by extensive chromatin looping to bring genes together for coordinated transcriptional regulation. We propose that chromatin interactions constitute a primary mechanism for regulating transcription in mammalian genomes. © 2009 Macmillan Publishers Limited. All rights reserved.

Recombination detection is important before inferring phylogenetic relationships. This will eventually lead to a better understanding of pathogen evolution, more accurate genotyping, and advancements in vaccine development. In this paper, we introduce RB-Finder, a fast and accurate distance-based window method to detect recombination in a multiple sequence alignment. Our method introduces a more informative distance measure and a novel weighting strategy to reduce the window size sensitivity problem and hence improve the accuracy of breakpoint detection. Furthermore, our method is faster than existing phylogeny-based methods since we do not need to construct and compare complex phylogenetic trees. When compared with the current best method Pruned-PDM, our method is a few hundred times more efficient. Experimental evaluation of RB-Finder using synthetic and biological datasets showed that our method is more accurate than existing phylogeny-based methods. We also show how our method has potential use in other related applications such as genotyping.

Motivation: Locating transcription factor binding sites (motifs) is a key step in understanding gene regulation. Based on Tompa's benchmark study, the performance of current de novo motif finders is far from satisfactory (with sensitivity ≤0.222 and precision ≤0.307). The same study also shows that no motif finder performs consistently well over all datasets. Hence, it is not clear which finder one should use for a given dataset. To address this issue, a class of algorithms called ensemble methods have been proposed. Though the existing ensemble methods overall perform better than stand-alone motif finders, the improvement gained is not substantial. Our study reveals that these methods do not fully exploit the information obtained from the results of individual finders, resulting in minor improvement in sensitivity and poor precision. Results: In this article, we identify several key observations on how to utilize the results from individual finders and design a novel ensemble method, MotifVoter, to predict the motifs and binding sites. Evaluations on 186 datasets show that MotifVoter can locate more than 95% of the binding sites found by its component motif finders. In terms of sensitivity and precision, MotifVoter outperforms stand-alone motif finders and ensemble methods significantly on Tompa's benchmark, Escherichia coli, and ChIP-Chip datasets. MotifVoter is available online via a web server with several biologist-friendly features. Availability: http://www.comp.nus.edu.sg/~bioinfo/MotifVoter Contact: ksung@comp.nus.edu.sg supplementary information: Supplementary data are available at Bioinformatics online.

NF-kappaB is a key mediator of inflammation. Here, we mapped the genome-wide loci bound by the RELA subunit of NF-kappaB in lipopolysaccharide (LPS)-stimulated human monocytic cells, and together with global gene expression profiling, found an overrepresentation of the E2F1-binding motif among RELA-bound loci associated with NF-kappaB target genes. Knockdown of endogenous E2F1 impaired the LPS inducibility of the proinflammatory cytokines CCL3(MIP-1alpha), IL23A(p19), TNF-alpha, and IL1-beta. Upon LPS stimulation, E2F1 is rapidly recruited to the promoters of these genes along with p50/RELA heterodimer via a mechanism that is dependent on NF-kappaB activation. Together with the observation that E2F1 physically interacts with p50/RELA in LPS-stimulated cells, our findings suggest that NF-kappaB recruits E2F1 to fully activate the transcription of NF-kappaB target genes. Global gene expression profiling subsequently revealed a spectrum of NF-kappaB target genes that are positively regulated by E2F1, further demonstrating the critical role of E2F1 in the Toll-like receptor 4 pathway.

Identification of unconventional functional features such as fusion transcripts is a challenging task in the effort to annotate all functional DNA elements in the human genome. Paired-End diTag (PET) analysis possesses a unique capability to accurately and efficiently characterize the two ends of DNA fragments, which may have either normal or unusual compositions. This unique nature of PET analysis makes it an ideal tool for uncovering unconventional features residing in the human genome. Using the PET approach for comprehensive transcriptome analysis, we were able to identify fusion transcripts derived from genome rearrangements and actively expressed retrotransposed pseudogenes, which would be difficult to capture by other means. Here, we demonstrate this unique capability through the analysis of 865,000 individual transcripts in two types of cancer cells. In addition to the characterization of a large number of differentially expressed alternative 5′ and 3′ transcript variants and novel transcriptional units, we identified 70 fusion transcript candidates in this study. One was validated as the product of a fusion gene between BCAS4 and BCAS3 resulting from an amplification followed by a translocation event between the two loci, chr20q13 and chr17q23. Through an examination of PETs that mapped to multiple genomic locations, we identified 4055 retrotransposed loci in the human genome, of which at least three were found to be transcriptionally active. The PET mapping strategy presented here promises to be a useful tool in annotating the human genome, especially aberrations in human cancer genomes.

Structural variations (SVs) are mutations in the genome of size at least fifty nucleotides. They contribute to the phenotypic differences among healthy individuals, cause severe diseases and even cancers by breaking or linking genes. Thus, it is crucial to systematically profile SVs in the genome. In the past decade, many next-generation sequencing (NGS)-based SV detection methods have been proposed due to the significant cost reduction of NGS experiments and their ability to unbiasedly detect SVs to the base-pair resolution. These SV detection methods vary in both sensitivity and specificity, since they use different SV-property-dependent and library-property-dependent features. As a result, predictions from different SV callers are often inconsistent. Besides, the noises in the data (both platform-specific sequencing error and artificial chimeric reads) impede the specificity of SV detection. Poorly characterized regions in the human genome (e.g., repeat regions) greatly impact the reads mapping and in turn affect the SV calling accuracy. Calling of complex SVs requires specialized SV callers. Apart from accuracy, processing speed of SV caller is another factor deciding its usability. Knowing the pros and cons of different SV calling techniques and the objectives of the biological study are essential for biologists and bioinformaticians to make informed decisions. This paper describes different components in the SV calling pipeline and reviews the techniques used by existing SV callers. Through simulation study, we also demonstrate that library properties, especially insert size, greatly impact the sensitivity of different SV callers. We hope the community can benefit from this work both in designing new SV calling methods and in selecting the appropriate SV caller for specific biological studies.

In genome assembly graphs, motifs such as tips, bubbles, and cross links are studied in order to find sequencing errors and to understand the nature of the genome. Superbubble, a complex generalization of bubbles, was recently proposed as an important subgraph class for analyzing assembly graphs. At present, a quadratic time algorithm is known. This paper gives an O(m log m)-time algorithm to solve this problem for a graph with m edges.

The protooncogene MYC encodes the c-Myc transcription factor that regulates cell growth, cell proliferation, cell cycle, and apoptosis. Although deregulation of MYC contributes to tumorigenesis, it is still unclear what direct Myc-induced transcriptomes promote cell transformation. Here we provide a snapshot of genome-wide, unbiased characterization of direct Myc binding targets in a model of human B lymphoid tumor using ChIP coupled with pair-end ditag sequencing analysis (ChIP-PET). Myc potentially occupies >4,000 genomic loci with the majority near proximal promoter regions associated frequently with CpG islands. Using gene expression profiles with ChIP-PET, we identified 668 direct Myc-regulated gene targets, including 48 transcription factors, indicating that Myc is a central transcriptional hub in growth and proliferation control. This first global genomic view of Myc binding sites yields insights of transcriptional circuitries and cis regulatory modules involving Myc and provides a substantial framework for our understanding of mechanisms of Myc-induced tumorigenesis.

ALK is an established causative oncogenic driver in neuroblastoma, and is likely to emerge as a routine biomarker in neuroblastoma diagnostics. At present, the optimal strategy for clinical diagnostic evaluation of ALK protein, genomic and hotspot mutation status is not well-studied. We evaluated ALK immunohistochemical (IHC) protein expression using three different antibodies (ALK1, 5A4 and D5F3 clones), ALK genomic status using single-color chromogenic in situ hybridization (CISH), and ALK hotspot mutation status using conventional Sanger sequencing and a next-generation sequencing platform (Ion Torrent Personal Genome Machine (IT-PGM)), in archival formalin-fixed, paraffin-embedded neuroblastoma samples. We found a significant difference in IHC results using the three different antibodies, with the highest percentage of positive cases seen on D5F3 immunohistochemistry. Correlation with ALK genomic and hotspot mutational status revealed that the majority of D5F3 ALK-positive cases did not possess either ALK genomic amplification or hotspot mutations. Comparison of sequencing platforms showed a perfect correlation between conventional Sanger and IT-PGM sequencing. Our findings suggest that D5F3 immunohistochemistry, single-color CISH and IT-PGM sequencing are suitable assays for evaluation of ALK status in future neuroblastoma clinical trials.

Motivation: BigWig, a format to represent read density data, is one of the most popular data types. They can represent the peak intensity in ChIP-seq, the transcript expression in RNA-seq, the copy number variation in whole genome sequencing, etc. UCSC Encode project uses the bigWig format heavily for storage and visualization. Of 5.2 TB Encode hg19 database, 1.6 TB (31% of the total space) is used to store bigWig files. BigWig format not only saves a lot of space but also supports fast queries that are crucial for interactive analysis and browsing. In our benchmark, bigWig often has similar size to the gzipped raw data, while is still able to support ∼5000 random queries per second. Results: Although bigWig is good enough at the moment, both storage space and query time are expected to become limited when sequencing gets cheaper. This article describes a new method to store density data named CWig. The format uses on average one-third of the size of existing bigWig files and improves random query speed up to 100 times. Availability and implementation: http://genome.ddns.comp.nus.edu.sg/∼cwig Contact: ksung@comp.nus.edu.sg Supplementary information: Supplementary data are available at Bioinformatics online.

Hepatocellular carcinoma (HCC) is one of the most deadly cancers worldwide and has no effective treatment, yet the molecular basis of hepatocarcinogenesis remains largely unknown. Here we report findings from a whole-genome sequencing (WGS) study of 88 matched HCC tumor/normal pairs, 81 of which are Hepatitis B virus (HBV) positive, seeking to identify genetically altered genes and pathways implicated in HBV-associated HCC. We find beta-catenin to be the most frequently mutated oncogene (15.9%) and TP53 the most frequently mutated tumor suppressor (35.2%). The Wnt/beta-catenin and JAK/STAT pathways, altered in 62.5% and 45.5% of cases, respectively, are likely to act as two major oncogenic drivers in HCC. This study also identifies several prevalent and potentially actionable mutations, including activating mutations of Janus kinase 1 (JAK1), in 9.1% of patients and provides a path toward therapeutic intervention of the disease.

Aristolochic acid (AA), a natural product of Aristolochia plants found in herbal remedies and health supplements, is a group 1 carcinogen that can cause nephrotoxicity and upper urinary tract urothelial cell carcinoma (UTUC). Whole-genome and exome analysis of nine AA-associated UTUCs revealed a strikingly high somatic mutation rate (150 mutations/Mb), exceeding smoking-associated lung cancer (8 mutations/Mb) and ultraviolet radiation-associated melanoma (111 mutations/Mb). The AA-UTUC mutational signature was characterized by A:T to T:A transversions at the sequence motif A[C|T]AGG, located primarily on nontranscribed strands. AA-induced mutations were also significantly enriched at splice sites, suggesting a role for splice-site mutations in UTUC pathogenesis. RNA sequencing of AA-UTUC confirmed a general up-regulation of nonsense-mediated decay machinery components and aberrant splicing events associated with splice-site mutations. We observed a high frequency of somatic mutations in chromatin modifiers, particularly KDM6A, in AA-UTUC, demonstrated the sufficiency of AA to induce renal dysplasia in mice, and reproduced the AA mutational signature in experimentally treated human renal tubular cells. Finally, exploring other malignancies that were not known to be associated with AA, we screened 93 hepatocellular carcinoma genomes/exomes and identified AA-like mutational signatures in 11. Our study highlights an unusual genome-wide AA mutational signature and the potential use of mutation signatures as "molecular fingerprints" for interrogating high-throughput cancer genome data to infer previous carcinogen exposures.

A multi-labeled phylogenetic tree, or MUL-tree, is a generalization of a phylogenetic tree that allows each leaf label to be used many times. MUL-trees have applications in biogeography, the study of host–parasite cospeciation, gene evolution studies, and computer science. Here, we consider the problem of inferring a consensus MUL-tree that summarizes a given set of conflicting MUL-trees, and present the first polynomial-time algorithms for solving it. In particular, we give a straightforward, fast algorithm for building a strict consensus MUL-tree for any input set of MUL-trees with identical leaf label multisets, as well as a polynomial-time algorithm for building a majority rule consensus MUL-tree for the special case where every leaf label occurs at most twice. We also show that, although it is NP-hard to find a majority rule consensus MUL-tree in general, the variant that we call the singular majority rule consensus MUL-tree can be constructed efficiently whenever it exists.

To survey hepatitis B virus (HBV) integration in liver cancer genomes, we conducted massively parallel sequencing of 81 HBV-positive and 7 HBV-negative hepatocellular carcinomas (HCCs) and adjacent normal tissues. We found that HBV integration is observed more frequently in the tumors (86.4%) than in adjacent liver tissues (30.7%). Copy-number variations (CNVs) were significantly increased at HBV breakpoint locations where chromosomal instability was likely induced. Approximately 40% of HBV breakpoints within the HBV genome were located within a 1,800-bp region where the viral enhancer, X gene and core gene are located. We also identified recurrent HBV integration events (in ≥ 4 HCCs) that were validated by RNA sequencing (RNA-seq) and Sanger sequencing at the known and putative cancer-related TERT, MLL4 and CCNE1 genes, which showed upregulated gene expression in tumor versus normal tissue. We also report evidence that suggests that the number of HBV integrations is associated with patient survival.

SummaryHigher-order chromosomal organization for transcription regulation is poorly understood in eukaryotes. Using genome-wide Chromatin Interaction Analysis with Paired-End-Tag sequencing (ChIA-PET), we mapped long-range chromatin interactions associated with RNA polymerase II in human cells and uncovered widespread promoter-centered intragenic, extragenic, and intergenic interactions. These interactions further aggregated into higher-order clusters, wherein proximal and distal genes were engaged through promoter-promoter interactions. Most genes with promoter-promoter interactions were active and transcribed cooperatively, and some interacting promoters could influence each other implying combinatorial complexity of transcriptional controls. Comparative analyses of different cell lines showed that cell-specific chromatin interactions could provide structural frameworks for cell-specific transcription, and suggested significant enrichment of enhancer-promoter interactions for cell-specific functions. Furthermore, genetically-identified disease-associated noncoding elements were found to be spatially engaged with corresponding genes through long-range interactions. Overall, our study provides insights into transcription regulation by three-dimensional chromatin interactions for both housekeeping and cell-specific genes in human cells.

Structural variations (SVs) contribute significantly to the variability of the human genome and extensive genomic rearrangements are a hallmark of cancer. While genomic DNA paired-end-tag (DNA-PET) sequencing is an attractive approach to identify genomic SVs, the current application of PET sequencing with short insert size DNA can be insufficient for the comprehensive mapping of SVs in low complexity and repeat-rich genomic regions. We employed a recently developed procedure to generate PET sequencing data using large DNA inserts of 10–20 kb and compared their characteristics with short insert (1 kb) libraries for their ability to identify SVs. Our results suggest that although short insert libraries bear an advantage in identifying small deletions, they do not provide significantly better breakpoint resolution. In contrast, large inserts are superior to short inserts in providing higher physical genome coverage for the same sequencing cost and achieve greater sensitivity, in practice, for the identification of several classes of SVs, such as copy number neutral and complex events. Furthermore, our results confirm that large insert libraries allow for the identification of SVs within repetitive sequences, which cannot be spanned by short inserts. This provides a key advantage in studying rearrangements in cancer, and we show how it can be used in a fusion-point-guided-concatenation algorithm to study focally amplified regions in cancer.

HEY bHLH transcription factors have been shown to regulate multiple key steps in cardiovascular development. They can be induced by activated NOTCH receptors, but other upstream stimuli mediated by TGFß and BMP receptors may elicit a similar response. While the basic and helix-loop-helix domains exhibit strong similarity, large parts of the proteins are still unique and may serve divergent functions. The striking overlap of cardiac defects in HEY2 and combined HEY1/HEYL knockout mice suggested that all three HEY genes fulfill overlapping function in target cells. We therefore sought to identify target genes for HEY proteins by microarray expression and ChIPseq analyses in HEK293 cells, cardiomyocytes, and murine hearts. HEY proteins were found to modulate expression of their target gene to a rather limited extent, but with striking functional interchangeability between HEY factors. Chromatin immunoprecipitation revealed a much greater number of potential binding sites that again largely overlap between HEY factors. Binding sites are clustered in the proximal promoter region especially of transcriptional regulators or developmental control genes. Multiple lines of evidence suggest that HEY proteins primarily act as direct transcriptional repressors, while gene activation seems to be due to secondary or indirect effects. Mutagenesis of putative DNA binding residues supports the notion of direct DNA binding. While class B E-box sequences (CACGYG) clearly represent preferred target sequences, there must be additional and more loosely defined modes of DNA binding since many of the target promoters that are efficiently bound by HEY proteins do not contain an E-box motif. These data clearly establish the three HEY bHLH factors as highly redundant transcriptional repressors in vitro and in vivo, which explains the combinatorial action observed in different tissues with overlapping expression., Author Summary NOTCH signaling is a central developmental pathway that influences a multitude of cell fate decisions and differentiation steps as well as later tissue homeostasis and regeneration. The three HEY genes encode basic helix-loop-helix transcription factors that are critical effectors to convey signaling by NOTCH receptors and similar signaling systems. This is underscored by the multitude of developmental defects observed in HEY single- and double-mutant mice. The mode of action of HEY proteins remained largely unexplored, however. By gene expression analysis and chromatin immunoprecipitation we have now identified a large set of HEY target genes. While only 500–2,000 mRNAs are regulated by HEY1 or HEY2, there are around 10,000 binding sites in the genome. HEY proteins act as transcriptional repressors that bind close to transcriptional start sites in all cases tested. In contrast, gene activation seems to be mediated by indirect/secondary mechanisms. The extent of regulation is rather limited, implicating HEY genes in modulating rather than switching on or off target gene expression. All our in vitro and in vivo data point to a high degree of redundancy between the three HEY genes, suggesting that tissue specific patterns and expression levels determine the final outcome of HEY induced cellular responses.

The NKX3-1 gene is a homeobox gene required for prostate tumor progression, but how it functions is unclear. Here, using chromatin immunoprecipitation coupled to massively parallel sequencing (ChIP-seq) we showed that NKX3-1 colocalizes with the androgen receptor (AR) across the prostate cancer genome. We uncovered two distinct mechanisms by which NKX3-1 controls the AR transcriptional network in prostate cancer. First, NKX3-1 and AR directly regulate each other in a feed-forward regulatory loop. Second, NKX3-1 collaborates with AR and FoxA1 to mediate genes in advanced and recurrent prostate carcinoma. NKX3-1- and AR-coregulated genes include those found in the “protein trafficking” process, which integrates oncogenic signaling pathways. Moreover, we demonstrate that NKX3-1, AR, and FoxA1 promote prostate cancer cell survival by directly upregulating RAB3B, a member of the RAB GTPase family. Finally, we show that RAB3B is overexpressed in prostate cancer patients, suggesting that RAB3B together with AR, FoxA1, and NKX3-1 are important regulators of prostate cancer progression. Collectively, our work highlights a novel hierarchical transcriptional regulatory network between NKX3-1, AR, and the RAB GTPase signaling pathway that is critical for the genetic-molecular-phenotypic paradigm in androgen-dependent prostate cancer.

Epigenetic modifications are critical to gene regulations and genome functions. Among different epigenetic modifications, it is of great interest to study the differential histone modification sites (DHMSs), which contribute to the epigenetic dynamics and the gene regulations among various cell-types or environmental responses. ChIP-seq is a robust and comprehensive approach to capture the histone modifications at the whole genome scale. By comparing two histone modification ChIP-seq libraries, the DHMSs are potentially identifiable. With this aim, we proposed an approach called ChIPDiff for the genome-wide comparison of histone modification sites identified by ChIP-seq (Xu, Wei, Lin et al., Bioinformatics 24:2344-2349, 2008). The approach employs a hidden Markov model (HMM) to infer the states of histone modification changes at each genomic location. We evaluated the performance of ChIPDiff by comparing the H3K27me3 modification sites between mouse embryonic stem cell (ESC) and neural progenitor cell (NPC). We demonstrated that the H3K27me3 DHMSs identified by our approach are of high sensitivity, specificity, and technical reproducibility. ChIPDiff was further applied to uncover the differential H3K4me3 and H3K36me3 sites between different cell states. The result showed significant correlation between the histone modification states and the gene expression levels.

Tyrosine kinase inhibitors (TKIs) elicit high response rates among individuals with kinase-driven malignancies, including chronic myeloid leukemia (CML) and epidermal growth factor receptor-mutated non-small-cell lung cancer (EGFR NSCLC). However, the extent and duration of these responses are heterogeneous, suggesting the existence of genetic modifiers affecting an individual's response to TKIs. Using paired-end DNA sequencing, we discovered a common intronic deletion polymorphism in the gene encoding BCL2-like 11 (BIM). BIM is a pro-apoptotic member of the B-cell CLL/lymphoma 2 (BCL2) family of proteins, and its upregulation is required for TKIs to induce apoptosis in kinase-driven cancers. The polymorphism switched BIM splicing from exon 4 to exon 3, which resulted in expression of BIM isoforms lacking the pro-apoptotic BCL2-homology domain 3 (BH3). The polymorphism was sufficient to confer intrinsic TKI resistance in CML and EGFR NSCLC cell lines, but this resistance could be overcome with BH3-mimetic drugs. Notably, individuals with CML and EGFR NSCLC harboring the polymorphism experienced significantly inferior responses to TKIs than did individuals without the polymorphism (P = 0.02 for CML and P = 0.027 for EGFR NSCLC). Our results offer an explanation for the heterogeneity of TKI responses across individuals and suggest the possibility of personalizing therapy with BH3 mimetics to overcome BIM-polymorphism-associated TKI resistance.

Oestrogen receptor α (ERα) is key player in the progression of breast cancer. Recently, the cistrome and interactome of ERα were mapped in breast cancer cells, revealing the importance of spatial organization in oestrogen-mediated transcription. However, the underlying mechanism of this process is unclear. Here, we show that ERα binding sites (ERBS) identified from the Chromatin Interaction Analysis-Paired End DiTag of ERα are enriched for AP-2 motifs. We demonstrate the transcription factor, AP-2γ, which has been implicated in breast cancer oncogenesis, binds to ERBS in a ligand-independent manner. Furthermore, perturbation of AP-2γ expression impaired ERα DNA binding, long-range chromatin interactions, and gene transcription. In genome-wide analyses, we show that a large number of AP-2γ and ERα binding events converge together across the genome. The majority of these shared regions are also occupied by the pioneer factor, FoxA1. Molecular studies indicate there is functional interplay between AP-2γ and FoxA1. Finally, we show that most ERBS associated with long-range chromatin interactions are colocalized with AP-2γ and FoxA1. Together, our results suggest AP-2γ is a novel collaborative factor in ERα-mediated transcription.

Somatic genome rearrangements are thought to play important roles in cancer development. We optimized a long-span paired-end-tag (PET) sequencing approach using 10-Kb genomic DNA inserts to study human genome structural variations (SVs). The use of a 10-Kb insert size allows the identification of breakpoints within repetitive or homology-containing regions of a few kilobases in size and results in a higher physical coverage compared with small insert libraries with the same sequencing effort. We have applied this approach to comprehensively characterize the SVs of 15 cancer and two noncancer genomes and used a filtering approach to strongly enrich for somatic SVs in the cancer genomes. Our analyses revealed that most inversions, deletions, and insertions are germ-line SVs, whereas tandem duplications, unpaired inversions, interchromosomal translocations, and complex rearrangements are over-represented among somatic rearrangements in cancer genomes. We demonstrate that the quantitative and connective nature of DNA–PET data is precise in delineating the genealogy of complex rearrangement events, we observe signatures that are compatible with breakagefusion-bridge cycles, and we discover that large duplications are among the initial rearrangements that trigger genome instability for extensive amplification in epithelial cancers. [Supplemental material is available for this article. The sequencing data from this study have been submitted to NCBI Gene Expression Omnibus (GEO) (http://www.ncbi.nlm.nih.gov/geo) under accession no. GSE26954.]