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      The Association Between H3K4me3 and Antisense Transcription

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          Abstract

          Histone H3 lysine 4 trimethylation (H3K4me3) is well known to occur in the promoter region of genes for transcription activation. However, when investigating the H3K4me3 profiles in the mouse cerebrum and testis, we discovered that H3K4me3 also has a significant enrichment at the 3′ end of actively transcribed (sense) genes, named as 3′-H3K4me3. 3′-H3K4me3 is associated with ∼15% of protein-coding genes in both tissues. In addition, we examined the transcriptional initiation signals including RNA polymerase II (RNAPII) binding sites and 5′-CAGE-tag that marks transcriptional start sites. Interestingly, we found that 3′-H3K4me3 is associated with the initiation of antisense transcription. Furthermore, 3′-H3K4me3 modification levels correlate positively with the antisense expression levels of the associated sense genes, implying that 3′-H3K4me3 is involved in the activation of antisense transcription. Taken together, our findings suggest that H3K4me3 may be involved in the regulation of antisense transcription that initiates from the 3′ end of sense genes. In addition, a positive correlation was also observed between the expression of antisense and the associated sense genes with 3′-H3K4me3 modification. More importantly, we observed the 3′-H3K4me3 enrichment among genes in human, fruitfly and Arabidopsis, and found that the sequences of 3′-H3K4me3-marked regions are highly conserved and essentially indistinguishable from known promoters in vertebrate. Therefore, we speculate that these 3′-H3K4me3-marked regions may serve as potential promoters for antisense transcription and 3′-H3K4me3 appear to be a universal epigenetic feature in eukaryotes. Our results provide a novel insight into the epigenetic roles of H3K4me3 and the regulatory mechanism of antisense transcription.

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          The transcriptional landscape of the mammalian genome.

          This study describes comprehensive polling of transcription start and termination sites and analysis of previously unidentified full-length complementary DNAs derived from the mouse genome. We identify the 5' and 3' boundaries of 181,047 transcripts with extensive variation in transcripts arising from alternative promoter usage, splicing, and polyadenylation. There are 16,247 new mouse protein-coding transcripts, including 5154 encoding previously unidentified proteins. Genomic mapping of the transcriptome reveals transcriptional forests, with overlapping transcription on both strands, separated by deserts in which few transcripts are observed. The data provide a comprehensive platform for the comparative analysis of mammalian transcriptional regulation in differentiation and development.
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            RNA maps reveal new RNA classes and a possible function for pervasive transcription.

            Significant fractions of eukaryotic genomes give rise to RNA, much of which is unannotated and has reduced protein-coding potential. The genomic origins and the associations of human nuclear and cytosolic polyadenylated RNAs longer than 200 nucleotides (nt) and whole-cell RNAs less than 200 nt were investigated in this genome-wide study. Subcellular addresses for nucleotides present in detected RNAs were assigned, and their potential processing into short RNAs was investigated. Taken together, these observations suggest a novel role for some unannotated RNAs as primary transcripts for the production of short RNAs. Three potentially functional classes of RNAs have been identified, two of which are syntenically conserved and correlate with the expression state of protein-coding genes. These data support a highly interleaved organization of the human transcriptome.
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              A clustering approach for identification of enriched domains from histone modification ChIP-Seq data.

              Chromatin states are the key to gene regulation and cell identity. Chromatin immunoprecipitation (ChIP) coupled with high-throughput sequencing (ChIP-Seq) is increasingly being used to map epigenetic states across genomes of diverse species. Chromatin modification profiles are frequently noisy and diffuse, spanning regions ranging from several nucleosomes to large domains of multiple genes. Much of the early work on the identification of ChIP-enriched regions for ChIP-Seq data has focused on identifying localized regions, such as transcription factor binding sites. Bioinformatic tools to identify diffuse domains of ChIP-enriched regions have been lacking. Based on the biological observation that histone modifications tend to cluster to form domains, we present a method that identifies spatial clusters of signals unlikely to appear by chance. This method pools together enrichment information from neighboring nucleosomes to increase sensitivity and specificity. By using genomic-scale analysis, as well as the examination of loci with validated epigenetic states, we demonstrate that this method outperforms existing methods in the identification of ChIP-enriched signals for histone modification profiles. We demonstrate the application of this unbiased method in important issues in ChIP-Seq data analysis, such as data normalization for quantitative comparison of levels of epigenetic modifications across cell types and growth conditions. http://home.gwu.edu/ approximately wpeng/Software.htm. Supplementary data are available at Bioinformatics online.
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                Author and article information

                Contributors
                Journal
                Genomics Proteomics Bioinformatics
                Genomics Proteomics Bioinformatics
                Genomics, Proteomics & Bioinformatics
                Elsevier
                1672-0229
                2210-3244
                08 June 2012
                April 2012
                08 June 2012
                : 10
                : 2
                : 74-81
                Affiliations
                [a ]CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100029, China
                [b ]Institute of Epigenetics and Cancer Research, School of Medicine, Tsinghua University, Beijing 100080, China
                [c ]Graduate University of Chinese Academy of Sciences, Beijing 100049, China
                Author notes
                [1]

                Equal contribution.

                Article
                S1672-0229(12)00004-6
                10.1016/j.gpb.2012.05.001
                5054153
                22768981
                20b2339f-eaaf-4824-9538-96950c303387
                © 2012 Beijing Institute of Genomics, Chinese Academy of Sciences and Genetics Society of China. Published by Elsevier Ltd and Science Press. All rights reserved.

                This is an open access article under the CC BY-NC-SA license (http://creativecommons.org/licenses/by-nc-sa/3.0/).

                History
                : 1 May 2012
                : 13 May 2012
                Categories
                Original Research

                antisense initiation and activation,antisense transcription,h3k4me3

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