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Gene selection is an indispensable step for analyzing noisy and high-dimensional single-cell RNA-seq (scRNA-seq) data. Compared with the commonly used variance-based methods, by mimicking the human maker selection in the 2D visualization of cells, a new feature selection method called HRG (Highly Regional Genes) is proposed to find the informative genes, which show regional expression patterns in the cell-cell similarity network. We mathematically find the optimal expression patterns that can maximize the proposed scoring function. In comparison with several unsupervised methods, HRG shows high accuracy and robustness, and can increase the performance of downstream cell clustering and gene correlation analysis. Also, it is applicable for selecting informative genes of sequencing-based spatial transcriptomic data.

Motivation Intermediately methylated regions occupy a significant fraction of the human genome and are closely associated with epigenetic regulations or cell-type deconvolution of bulk data. However, these regions show distinct methylation patterns, corresponding to different biological mechanisms. Although there have been some metrics developed for investigating these regions, the high noise sensitivity limits the utility for distinguishing distinct methylation patterns. Results We proposed a method named MeConcord to measure local methylation concordance across reads and CpG sites, respectively. MeConcord showed the most stable performance in distinguishing distinct methylation patterns (‘identical’, ‘uniform’ and ‘disordered’) compared with other metrics. Applying MeConcord to the whole genome data across 25 cell lines or primary cells or tissues, we found that distinct methylation patterns were associated with different genomic characteristics, such as CTCF binding or imprinted genes. Further, we showed the differences of CpG island hypermethylation patterns between senescence and tumorigenesis by using MeConcord. MeConcord is a powerful method to study local read-level methylation patterns for both the whole genome and specific regions of interest. Availability and implementation MeConcord is available at https://github.com/WangLabTHU/MeConcord. Supplementary information Supplementary data are available at Bioinformatics online.

Early detection is crucial to improve breast cancer (BC) patients’ outcomes and survival. Mammogram and ultrasound adopting the Breast Imaging Reporting and Data System (BI-RADS) categorization are widely used for BC early detection, while suffering high false-positive rate leading to unnecessary biopsy, especially in BI-RADS category-4 patients. Plasma cell-free DNA (cfDNA) carrying on DNA methylation information has emerged as a non-invasive approach for cancer detection. Here we present a prospective multi-center study with whole-genome bisulfite sequencing data to address the clinical utility of cfDNA methylation markers from 203 female patients with breast lesions suspected for malignancy. The cfDNA is enriched with hypo-methylated genomic regions. A practical computational framework was devised to excavate optimal cfDNA-rich DNA methylation markers, which significantly improved the early diagnosis of BI-RADS category-4 patients (AUC from 0.78–0.79 to 0.93–0.94). As a proof-of-concept study, we performed the first blood-based whole-genome DNA methylation study for detecting early-stage breast cancer from benign tumors at single-base resolution, which suggests that combining the liquid biopsy with the traditional diagnostic imaging can improve the current clinical practice, by reducing the false-positive rate and avoiding unnecessary harms. Supplementary Information The online version contains supplementary material available at 10.1186/s12943-021-01330-w.

Hematopoietic stem cells (HSC) give rise to the cells of the blood system over the whole lifespan. N6-methyladenosine (m6A), the most prevalent RNA modification, modulates gene expression via the processes of "writing" and "reading". Recent studies showed that m6A "writer" genes (Mettl3 and Mettl14) play an essential role in HSC. However, which reader deciphers the m6A modification to modulate HSC remains unknown. In this study, we observed that dysfunction of Ythdf3 and Ccnd1 severely impaired the reconstitution capacity of HSC, which phenocopies Mettl3-deficient HSC. Dysfunction of Ythdf3 and Mettl3 results in a translational defect of Ccnd1. Ythdf3 and Mettl3 regulate HSC by transmitting m6A RNA methylation on the 5' untranslated region of Ccnd1. Enforced Ccnd1 expression completely rescued the defect of Ythdf3-/- HSC and partially rescued Mettl3-compromised HSC. Taken together, this study identified, for the first time, that Ccnd1 is the target of METTL3 and YTHDF3 to transmit the m6A RNA methylation signal and thereby regulate the reconstitution capacity of HSC.

Detecting cancer signals in cell-free DNA (cfDNA) high-throughput sequencing data is emerging as a novel noninvasive cancer detection method. Due to the high cost of sequencing, it is crucial to make robust and precise predictions with low-depth cfDNA sequencing data. Here we propose a novel approach named DISMIR, which can provide ultrasensitive and robust cancer detection by integrating DNA sequence and methylation information in plasma cfDNA whole-genome bisulfite sequencing (WGBS) data. DISMIR introduces a new feature termed as ‘switching region’ to define cancer-specific differentially methylated regions, which can enrich the cancer-related signal at read-resolution. DISMIR applies a deep learning model to predict the source of every single read based on its DNA sequence and methylation state and then predicts the risk that the plasma donor is suffering from cancer. DISMIR exhibited high accuracy and robustness on hepatocellular carcinoma detection by plasma cfDNA WGBS data even at ultralow sequencing depths. Further analysis showed that DISMIR tends to be insensitive to alterations of single CpG sites’ methylation states, which suggests DISMIR could resist to technical noise of WGBS. All these results showed DISMIR with the potential to be a precise and robust method for low-cost early cancer detection.

Cellular senescence is an important mechanism of autonomous tumor suppression, while its consequence such as the senescence-associated secretory phenotype (SASP) may drive tumorigenesis and age-related diseases. Therefore, controlling the cell fate optimally when encountering senescence stress is helpful for anti-cancer or anti-aging treatments. To identify genes essential for senescence establishment or maintenance, we carried out a CRISPR-based screen with a deliberately designed single-guide RNA (sgRNA) library. The library comprised of about 12,000 kinds of sgRNAs targeting 1378 senescence-associated genes selected by integrating the information of literature mining, protein-protein interaction network, and differential gene expression. We successfully detected a dozen gene deficiencies potentially causing senescence bypass, and their phenotypes were further validated with a high true positive rate. RNA-seq analysis showed distinct transcriptome patterns of these bypass cells. Interestingly, in the bypass cells, the expression of SASP genes was maintained or elevated with CHEK2, HAS1, or MDK deficiency; but neutralized with MTOR, CRISPLD2, or MORF4L1 deficiency. Pathways of some age-related neurodegenerative disorders were also downregulated with MTOR, CRISPLD2, or MORF4L1 deficiency. The results demonstrated that disturbing these genes could lead to distinct cell fates as a consequence of senescence bypass, suggesting that they may play essential roles in cellular senescence.

With the development of liquid biopsy technology, plasma cell-free DNA (cfDNA) becomes one of the research hotspots. Whole-genome bisulfite sequencing of plasma cell-free DNA has shown great potential medical applications such as cancer detection. However, the practical stability evaluation is still lacking. In this study, plasma cell-free DNA samples from two volunteers at different time were collected and prepared for sequencing in multiple laboratories. The library preparation strategies include pre-bisulfite, post-bisulfite and regular whole-genome sequencing. We established a set of quality control references for plasma cell-free DNA sequencing data and evaluated practical stability of blood collection, DNA extraction, and library preparation and sequencing depth. This work provided a technical practice guide for the application of plasma cfDNA methylation sequencing for clinical applications.随着液体活检技术的发展，血浆游离DNA 成为当前的研究热点之一。血浆游离DNA 的全基因组甲基化测序被认为在癌症检测等医学应用拥有巨大潜力，但目前尚缺乏针对该实验流程的实用稳定性评估。文中利用两名志愿者在不同时间采样的血浆游离DNA，在不同实验平台分别进行DNA 甲基化的重亚硫酸盐转化前建库(Pre-BS)、转化后建库 (Post-BS) 和常规DNA 建库，获取多因素影响下的测序数据样本。在此基础上，建立了一套血浆游离DNA 测序数据分析的质量控制参考流程，综合评估了血液采集提取、游离DNA 建库测序过程的实用稳定性，为血浆游离DNA 全基因组甲基化测序应用于临床液体活检提供实用性的基础参考。.

Dysregulation of mRNA splicing has been observed in certain cellular senescence process. However, the common splicing alterations on the whole transcriptome shared by various types of senescence are poorly understood. In order to systematically identify senescence-associated transcriptomic changes in genome-wide scale, we collected RNA sequencing datasets of different human cell types with a variety of senescence-inducing methods from public databases and performed meta-analysis. First, we discovered that a group of RNA binding proteins were consistently down-regulated in diverse senescent samples and identified 406 senescence-associated common differential splicing events. Then, eight differentially expressed RNA binding proteins were predicted to regulate these senescence-associated splicing alterations through an enrichment analysis of their RNA binding information, including motif scanning and enhanced cross-linking immunoprecipitation data. In addition, we constructed the splicing regulatory modules that might contribute to senescence-associated biological processes. Finally, it was confirmed that knockdown of the predicted senescence-associated potential splicing regulators through shRNAs in HepG2 cell line could result in senescence-like splicing changes. Taken together, our work demonstrated a broad range of common changes in mRNA splicing switches and detected their central regulatory RNA binding proteins during senescence. These findings would help to better understand the coordinating splicing alterations in cellular senescence.

Background Chemoresistance is one of the main causes of poor prognosis in pancreatic cancer patients. Understanding the mechanisms implicated in chemoresistance of pancreatic cancer is critical to improving patient outcomes. Recent evidences indicate that the long noncoding RNAs (lncRNAs) are involving in chemoresistance of pancreatic cancer. However, the mechanisms of lncRNAs contribute to resistance in pancreatic cancer and remain largely unknown. The objective of this study is to construct a chemoresistance-related lncRNA-associated competing endogenous RNA (ceRNA) network of pancreatic cancer and identify the key lncRNAs in regulating chemoresistance of the network. Methods Firstly, lncRNA expression profiling of gemcitabine-resistant pancreatic cancer cells was performed to identify lncRNAs related to chemoresistance by microarray analysis. Secondly, with insights into the mechanism of ceRNA, we used a bioinformatics approach to construct a chemoresistance-related lncRNAs-associated ceRNA network. We then identified the topological key lncRNAs in the ceRNA network and demonstrated its function or mechanism in chemoresistance of pancreatic cancer using molecular biological methods. Further studies evaluated its expression to assess its potential association with survival in patients with pancreatic cancer. Results Firstly, we demonstrated that lncRNAs were dysregulated in gemcitabine-resistant pancreatic cancer cells. We then constructed a chemoresistance-related lncRNA-associated ceRNA network and proposed that lncRNA Homo sapiens glutathione S-transferase mu 3, transcript variant 2 and noncoding RNA (GSTM3TV2; NCBI Reference Sequence: NR_024537.1) might act as a key ceRNA to enhance chemoresistance by upregulating L-type amino acid transporter 2 (LAT2) and oxidized low-density lipoprotein receptor 1(OLR1) in pancreatic cancer. Further studies demonstrated that GSTM3TV2, overexpressed in gemcitabine-resistant cells, enhanced the gemcitabine resistance of pancreatic cancer cells in vitro and in vivo. Mechanistically, we identified that GSTM3TV2 upregulated LAT2 and OLR1 by competitively sponging let-7 to promote gemcitabine resistance. In addition, we revealed that the expression levels of GSTM3TV2 were significantly increased in pancreatic cancer tissues and were associated with poor prognosis. Conclusion Our results suggest that GSTM3TV2 is a crucial oncogenic regulator involved in chemoresistance and could be a new therapeutic target or prognostic marker in pancreatic cancer.

Cellular senescence is an irreversible cell cycle arrest process associated with aging and senescence-related diseases. DNA damage is an extensive feature of cellular senescence and aging. Different levels of DNA damage could lead to cellular senescence or transient cell-cycle arrest, but the genetic regulatory mechanisms determining cell fate are still not clear. In this work, high-resolution time course analysis of gene expression in DNA damage-induced cellular senescence and transient cell-cycle arrest was used to explore the transcriptomic differences between different cell fates after DNA damage response and to investigate the key regulatory factors affecting senescent cell fates. Pathways such as the cell cycle, DNA repair and cholesterol metabolism showed characteristic differential response. A number of key transcription factors were predicted to regulating cell cycle and DNA repair. Our study provides genome-wide insights into the molecular-level mechanisms of senescent cell fate decisions after DNA damage response.

Summary ATAC-seq is rapidly emerging as one of the major experimental approaches to probe chromatin accessibility genome-wide. Here, we present ‘esATAC’, a highly integrated easy-to-use R/Bioconductor package, for systematic ATAC-seq data analysis. It covers essential steps for full analyzing procedure, including raw data processing, quality control and downstream statistical analysis such as peak calling, enrichment analysis and transcription factor footprinting. esATAC supports one command line execution for preset pipelines and provides flexible interfaces for building customized pipelines. Availability and implementation esATAC package is open source under the GPL-3.0 license. It is implemented in R and C++. Source code and binaries for Linux, MAC OS X and Windows are available through Bioconductor (https://www.bioconductor.org/packages/release/bioc/html/esATAC.html). Supplementary information Supplementary data are available at Bioinformatics online.

Many enhancers regulate their target genes via long-distance interactions. High-throughput experiments like ChIA-PET have been developed to map such largely cell-type-specific interactions between cis-regulatory elements genome-widely. In this study, we integrated multiple types of data in order to reveal the general hidden patterns embedded in the ChIA-PET data. We found characteristic distance features related to promoter–promoter, enhancer–enhancer and insulator–insulator interactions. Although a protein may have many binding sites along the genome, our hypothesis is that those sites that share certain open chromatin structure can accommodate relatively larger protein complex consisting of specific regulatory and ‘bridging’ factors, and may be more likely to form robust long-range deoxyribonucleic acid (DNA) loops. This hypothesis was validated in the estrogen receptor alpha (ERα) ChIA-PET data. An efficient classifier was built to predict ERα-associated long-range interactions solely from the related ChIP-seq data, hence linking distal ERα-dependent enhancers to their target genes. We further applied the classifier to generate additional novel interactions, which were undetected in the original ChIA-PET paper but were validated by other independent experiments. Our work provides a new insight into the long-range chromatin interactions through deeper and integrative ChIA-PET data analysis and demonstrates DNA looping predictability from ordinary ChIP-seq data.

MicroRNA (miRNA) regulation is highly cell-type specific. It is sensitive to both the miRNA-mRNA relative abundance and the competitive endogenous RNA (ceRNA) effect. However, almost all existing miRNA target prediction methods neglected the influence of the cellular environment when analyzing miRNA regulation effects. In this study, we proposed a method, MIROR (miRNA Occupancy Rate predictor), to predict miRNA regulation intensity in a given cell type. The major considerations were the miRNA-mRNA relative abundance and the endogenous competition between different mRNA species. The output of MIROR is the predicted miRNA occupancy rates of each target site. The predicted results significantly correlated with Ago HITS-CLIP experiment that indicated miRNA binding intensities. When applied to the analysis of the breast invasive carcinoma dataset, MIROR identified a number of differentially regulated miRNA-mRNA pairs with significant miRNA occupancy rate changes between tumor and normal tissues. Many of the predictions were supported by previous research studies, including the ones without a significant change in the mRNA expression level. These results indicate that MIROR provides a novel strategy to study the miRNA differential regulation in different cell types.

Cellular senescence is an irreversible cell cycle arrest program in response to various exogenous and endogenous stimuli like telomere dysfunction and DNA damage. It has been widely accepted as an anti-tumor program and is also found closely related to embryo development, tissue repair, organismal aging and age-related degenerative diseases. In the past decades, numerous efforts have been made to uncover the gene regulatory mechanisms of cellular senescence. There is a strong demand to integrate these data from various resources into one open platform. To facilitate researchers on cellular senescence, we have developed Human Cellular Senescence Gene Database (HCSGD) by integrating multiple online published data sources into a comprehensive senescence gene annotation platform (http://bioinfo.au.tsinghua.edu.cn/member/xwwang/HCSGD). Potential Human Cellular Senescence Genes (HCSGS) were collected by combining information from published literatures, gene expression profiling data and Protein-Protein Interaction networks. Additionally, genes are annotated with gene ontology annotation and microRNA/drug/compound target information. HCSGD provides a valuable resource to visualize cellular senescence gene networks, browse annotated functional information, and retrieve senescence-associated genes with a user-friendly web interface.

SummaryThe excessive amount of zeros in single-cell RNA-seq data include “real” zeros due to the on-off nature of gene transcription in single cells and “dropout” zeros due to technical reasons. Existing differential expression (DE) analysis methods cannot distinguish these two types of zeros. We developed an R package DEsingle which employed Zero-Inflated Negative Binomial model to estimate the proportion of real and dropout zeros and to define and detect 3 types of DE genes in single-cell RNA-seq data with higher accuracy.Availability and ImplementationThe R package DEsingle is freely available at https://github.com/miaozhun/DEsingle and is under Bioconductor’s consideration now.Contactzhangxg@tsinghua.edu.cnSupplementary informationSupplementary data are available at bioRxiv online.

// Zhe Cao 1, * , Chang Liu 2, * , Jianwei Xu 3, * , Lei You 1 , Chunyou Wang 4 , Wenhui Lou 5 , Bei Sun 6 , Yi Miao 7 , Xubao Liu 8 , Xiaowo Wang 2 , Taiping Zhang 1 , Yupei Zhao 1 1 Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China 2 MOE Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic and Systems Biology, TNLIST/Department of Automation, Tsinghua University, Beijing, 100084, China 3 Department of General Surgery, Qilu Hospital, Shandong University, Jinan, 250012, China 4 Department of General Surgery, Pancreatic Disease Institute, Wuhan Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, 430022, China 5 Department of Pancreatic Surgery, Zhong Shan Hospital, Fudan University, Shanghai, 200032, China 6 Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, Harbin Medical University, Harbin, 150001, China 7 Department of General Surgery, The First Affiliated Hospital, Nanjing Medical University, Nanjing, 210029, China 8 Department of Hepatopancreatobiliary Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, China * These authors contributed equally to this work and are co-first authors Correspondence to: Xiaowo Wang, email: xwwang@tsinghua.edu.cn Taiping Zhang, email: tpingzhang@yahoo.com Yupei Zhao, email: zhao8028@263.net Keywords: pancreatic cancer, microRNA panels, multicenter study, diagnosis Received: February 15, 2016 Accepted: May 04, 2016 Published: May 19, 2016 ABSTRACT Biomarkers for the early diagnosis of pancreatic cancer (PC) are urgent needed. Plasma microRNAs (miRNAs) might be used as biomarkers for the diagnosis of cancer. We analyzed 361 plasma samples from 6 surgical centers in China and performed machine learning approach. We gain insight of the association between the aberrant plasma miRNA expression and pancreatic disease. 671 microRNAs were screened in the discovery phase and 33 microRNAs in the training phase and 13 microRNAs in the validation phase. After the discovery phase and training phase, 2 diagnostic panels were constructed comprising 3 microRNAs in panel I (miR-486-5p, miR-126-3p, miR-106b-3p) and 6 microRNAs in panel II (miR-486-5p, miR-126-3p, miR-106b-3p, miR-938, miR-26b-3p, miR-1285). Panel I and panel II had high accuracy for distinguishing pancreatic cancer from chronic pancreatitis (CP) with area under the curve (AUC) values of 0.891 (Standard Error (SE): 0.097) and 0.889 (SE: 0.097) respectively, in the validation phase. Additionally, we demonstrated that the diagnostic value of the panels in discriminating PC from CP were comparable to that of carbohydrate antigen 19–9 (CA 19–9) 0.775 (SE: 0.053) ( P = 0.1 for both). This study identified 2 diagnostic panels based on microRNA expression in plasma with the potential to distinguish PC from CP. These patterns might be developed as biomarkers for pancreatic cancer.

The advances of high throughput profiling methods, such as microarray gene profiling and RNA-seq, have enabled researchers to identify thousands of differentially expressed genes under a certain perturbation. Much work has been done to understand the genetic factors that contribute to the expression changes by searching the over-represented regulatory motifs in the promoter regions of these genes. However, the changes could also be caused by epigenetic regulation, especially histone modifications, and no web server has been constructed to study the epigenetic factors responsible for gene expression changes. Here, we pre-sent a web tool for this purpose. Provided with different categories of genes (e.g., up-regulated, down-regulated or unchanged genes), the server will find epigenetic factors responsible for the difference among the categories and construct an epigenetic regulatory network. Furthermore, it will perform co-localization analyses between these epigenetic factors and transcription factors, which were collected from large scale experimental ChIP-seq or computational predicted data. In addition, for users who want to analyze dynamic change of a histone modification mark under different cell conditions, the server will find direct and indirect target genes of this mark by integrative analysis of experimental data and computational prediction, and present a regulatory network around this mark. Both networks can be visualized by a user friendly interface and the data are downloadable in batch. The server currently supports 12 cell types in human, including ESC and CD4+ T cells, and will expand as more public data are available. It also allows user to create a self-defined cell type, upload and analyze multiple ChIP-seq data. It is freely available to academic users at http://jjwanglab.org/EpiRegNet.

Cellular senescence acts as a potent barrier to tumorigenesis and contributes to the anti-tumor activity of certain chemotherapeutic agents. Senescent cells undergo a stable cell cycle arrest controlled by RB and p53 and, in addition, display a senescence-associated secretory phenotype (SASP) involving the production of factors that reinforce the senescence arrest, alter the microenvironment, and trigger immune surveillance of the senescent cells. Through a proteomics analysis of senescent chromatin, we identified the nuclear factor-κB (NF-κB) subunit p65 as a major transcription factor that accumulates on chromatin of senescent cells. We found that NF-κB acts as a master regulator of the SASP, influencing the expression of more genes than RB and p53 combined. In cultured fibroblasts, NF-κB suppression causes escape from immune recognition by natural killer (NK) cells and cooperates with p53 inactivation to bypass senescence. In a mouse lymphoma model, NF-κB inhibition bypasses treatment-induced senescence, producing drug resistance, early relapse, and reduced survival. Our results demonstrate that NF-κB controls both cell-autonomous and non-cell-autonomous aspects of the senescence program and identify a tumor-suppressive function of NF-κB that contributes to the outcome of cancer therapy.

High-throughput RNA sequencing (RNA-seq) technology provides a revolutionary approach to studying splicing events de novo. However, identifying splice junctions with high sensitivity and specificity remains a challenge. In the present study, we proposed a new tool named SeqSaw to detect splice junctions with or without the canonical GT-AG splicing signal. SeqSaw was applied to two ENCODE RNA-seq datasets and also compared with two existing methods. It was shown that the proposed method obtained better results on finding novel splice junctions. Experiments also revealed that the current sequencing depth has not yet reached saturation to detect novel transcripts. Moreover, by comparing the number of supporting reads, we demonstrated that many un-annotated splicing events can be tissue specific.

Summary: ChIA-PET is rapidly emerging as an important experimental approach to detect chromatin long-range interactions at high resolution. Here, we present Model based Interaction Calling from ChIA-PET data (MICC), an easy-to-use R package to detect chromatin interactions from ChIA-PET sequencing data. By applying a Bayesian mixture model to systematically remove random ligation and random collision noise, MICC could identify chromatin interactions with a significantly higher sensitivity than existing methods at the same false discovery rate. Availability and implementation: http://bioinfo.au.tsinghua.edu.cn/member/xwwang/MICCusage Contact: michael.zhang@utdallas.edu or xwwang@tsinghua.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online.

Oncogene-induced senescence is an anti-proliferative stress response program that acts as a fail-safe mechanism to limit oncogenic transformation and is regulated by the RB and p53 tumor suppressor pathways. In this study from Lowe and colleagues, E2F7, a poorly understood member of the E2F gene family, is identified as a key regulator of cellular senescence. The authors show that E2F7 is the only member of the E2F family of proteins that is consistently up-regulated during oncogene-induced senescence and that disruption of E2F7 and RB promotes escape from senescence, immortalization, and oncogenic transformation. ChIP-seq and gene expression profiling experiments identified genes regulated by E2F7 under different conditions, and the results indicate that E2F7 inactivation leads to complete derepression of mitotic E2F targets, thereby allowing cells to proliferate normally and bypass senescence. Thus, this study provides novel insight into the role of E2F7 in senescence, identifying it as a novel p53 target gene and showing that it cooperates with RB during the senescence program.

Gene expression is a dynamic process, and what factors influence gene expression changes upon external stimulus have not been clearly understood. We studied gene expression profiles in human umbilical vein endothelial cells (HUVEC) after the Tumor Necrosis Factor (TNF) stimulus, and found that: the promoters of fast-response up-regulated genes were enriched with several “active” chromatin markers like H3K27ac and H3K4me3, and also preferentially bound by Pol II and c-Myc; the core-promoter regions of slow-response up-regulated genes were frequently occupied by nucleosomes; down-regulated genes were more intensively regulated by microRNAs. Moreover, the Gene Ontology and motif analysis of the promoter regions revealed that gene clusters with different response behaviors had different functions and were regulated by different sets of transcription factors. Our observations suggested that the different gene expression patterns upon external stimulus were regulated by a combination of multi-layer regulators.

Cellular senescence is a tumor-suppressive program that involves chromatin reorganization and specific changes in gene expression that trigger an irreversible cell-cycle arrest. Here we combine quantitative mass spectrometry, ChIP deep-sequencing, and functional studies to determine the role of histone modifications on chromatin structure and gene-expression alterations associated with senescence in primary human cells. We uncover distinct senescence-associated changes in histone-modification patterns consistent with a repressive chromatin environment and link the establishment of one of these patterns—loss of H3K4 methylation—to the retinoblastoma tumor suppressor and the H3K4 demethylases Jarid1a and Jarid1b. Our results show that Jarid1a/b-mediated H3K4 demethylation contributes to silencing of retinoblastoma target genes in senescent cells, suggesting a mechanism by which retinoblastoma triggers gene silencing. Therefore, we link the Jarid1a and Jarid1b demethylases to a tumor-suppressor network controlling cellular senescence.

SummaryThe RB protein family (RB, p107, and p130) has overlapping and compensatory functions in cell-cycle control. However, cancer-associated mutations are almost exclusively found in RB, implying that RB has a nonredundant role in tumor suppression. We demonstrate that RB preferentially associates with E2F target genes involved in DNA replication and is uniquely required to repress these genes during senescence but not other growth states. Consequently, RB loss leads to inappropriate DNA synthesis following a senescence trigger and, together with disruption of a p21-mediated cell-cycle checkpoint, enables extensive proliferation and rampant genomic instability. Our results identify a nonredundant RB effector function that may contribute to tumor suppression and reveal how loss of RB and p53 cooperate to bypass senescence.

Correctly locating the gene transcription start site and the core-promoter is important for understanding transcriptional regulation mechanism. Here we have integrated specific genome-wide histone modification and DNA sequence features together to predict RNA polymerase II core-promoters in the human genome. Our new predictor CoreBoost_HM outperforms existing promoter prediction algorithms by providing significantly higher sensitivity and specificity at high resolution. We demonstrated that even though the histone modification data used in this study are from a specific cell type (CD4+ T-cell), our method can be used to identify both active and repressed promoters. We have applied it to search the upstream regions of microRNA genes, and show that CoreBoost_HM can accurately identify the known promoters of the intergenic microRNAs. We also identified a few intronic microRNAs that may have their own promoters. This result suggests that our new method can help to identify and characterize the core-promoters of both coding and noncoding genes.

Background The liver is the largest human internal organ – it is composed of multiple cell types and plays a vital role in fulfilling the body's metabolic needs and maintaining homeostasis. Of these cell types the hepatocytes, which account for three-quarters of the liver's volume, perform its main functions. To discover the molecular basis of hepatocyte function, we employed Massively Parallel Signature Sequencing (MPSS) to determine the transcriptomic profile of adult human hepatocytes obtained by laser capture microdissection (LCM). Results 10,279 UniGene clusters, representing 7,475 known genes, were detected in human hepatocytes. In addition, 1,819 unique MPSS signatures matching the antisense strand of 1,605 non-redundant UniGene clusters (such as APOC1, APOC2, APOB and APOH) were highly expressed in hepatocytes. Conclusion Apart from a large number of protein-coding genes, some of the antisense transcripts expressed in hepatocytes could play important roles in transcriptional interference via a cis-/trans-regulation mechanism. Our result provided a comprehensively transcriptomic atlas of human hepatocytes using MPSS technique, which could be served as an available resource for an in-depth understanding of human liver biology and diseases.

MicroRNAs (miRNAs) are a class of approximately 22-nt small RNAs that regulate posttranscriptional gene expression. Thousands of expressed sequence tags (ESTs) have been identified by using upstream 2500-nt and downstream 4000-nt flanking sequences to BLAST in the dbEST database. The cotranscription of the miRNAs and their flanking sequences covered by the matched ESTs is verified by RT-PCR. It directly reveals that a large portion of mammalian intergenic miRNAs are first transcribed as long primary transcripts (pri-miRNAs). Also, the transcripts' ranges of tens of pri-miRNAs are predicted by the EST-extension method. We then extracted the tissue-specific expression information from the annotations of the matched ESTs and established the expression profile of the studied miRNAs for tens of tissues. This provided a new way to establish the expression profiles of miRNAs. Results show that the human brain, lung, liver, and eye and the mouse brain, eye, and mammary gland are tissues in which enriched numbers of miRNAs are expressed.

Background Alternative splicing expands transcriptome diversity and plays an important role in regulation of gene expression. Previous studies focus on the regulation of a single cassette exon, but recent experiments indicate that multiple cassette exons within a gene may interact with each other. This interaction can increase the potential to generate various transcripts and adds an extra layer of complexity to gene regulation. Several cases of exon interaction have been discovered. However, the extent to which the cassette exons coordinate with each other remains unknown. Results Based on EST data, we employed a metric of correlation coefficients to describe the interaction between two adjacent cassette exons and then categorized these exon pairs into three different groups by their interaction (correlation) patterns. Sequence analysis demonstrates that strongly-correlated groups are more conserved and contain a higher proportion of pairs with reading frame preservation in a combinatorial manner. Multiple genome comparison further indicates that different groups of correlated pairs have different evolutionary courses: (1) The vast majority of positively-correlated pairs are old, (2) most of the weakly-correlated pairs are relatively young, and (3) negatively-correlated pairs are a mixture of old and young events. Conclusion We performed a large-scale analysis of interactions between adjacent cassette exons. Compared with weakly-correlated pairs, the strongly-correlated pairs, including both the positively and negatively correlated ones, show more evidence that they are under delicate splicing control and tend to be functionally important. Additionally, the positively-correlated pairs bear strong resemblance to constitutive exons, which suggests that they may evolve from ancient constitutive exons, while negatively and weakly correlated pairs are more likely to contain newly emerging exons.