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      Expression and regulation of lincRNAs during T cell development and differentiation

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          Abstract

          Although lincRNAs are implicated in gene regulation in various tissues, little is known about lincRNA transcriptomes in the T cell lineages. Here we identify 1,524 lincRNA clusters in 42 T cell samples from early T cell progenitors to terminally differentiated T helper (T H) subsets. Our analysis revealed highly dynamic and cell-specific expression patterns of lincRNAs during T cell differentiation. Importantly, these lincRNAs are located in genomic regions enriched for protein-coding genes with immune-regulatory functions. Many of them are bound and regulated by the key T cell transcription factors T-bet, GATA-3, STAT4 and STAT6. We demonstrate that the lincRNA LincR-Ccr2-5′AS, together with GATA-3, is an essential component of a regulatory circuit in T H2-specific gene expression and important for T H2 cell migration.

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          Most cited references17

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          Is Open Access

          NCBI Reference Sequences (RefSeq): current status, new features and genome annotation policy

          The National Center for Biotechnology Information (NCBI) Reference Sequence (RefSeq) database is a collection of genomic, transcript and protein sequence records. These records are selected and curated from public sequence archives and represent a significant reduction in redundancy compared to the volume of data archived by the International Nucleotide Sequence Database Collaboration. The database includes over 16 000 organisms, 2.4 × 106 genomic records, 13 × 106 proteins and 2 × 106 RNA records spanning prokaryotes, eukaryotes and viruses (RefSeq release 49, September 2011). The RefSeq database is maintained by a combined approach of automated analyses, collaboration and manual curation to generate an up-to-date representation of the sequence, its features, names and cross-links to related sources of information. We report here on recent growth, the status of curating the human RefSeq data set, more extensive feature annotation and current policy for eukaryotic genome annotation via the NCBI annotation pipeline. More information about the resource is available online (see http://www.ncbi.nlm.nih.gov/RefSeq/).
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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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              Large intergenic non-coding RNA-RoR modulates reprogramming of human induced pluripotent stem cells.

              The conversion of lineage-committed cells to induced pluripotent stem cells (iPSCs) by reprogramming is accompanied by a global remodeling of the epigenome, resulting in altered patterns of gene expression. Here we characterize the transcriptional reorganization of large intergenic non-coding RNAs (lincRNAs) that occurs upon derivation of human iPSCs and identify numerous lincRNAs whose expression is linked to pluripotency. Among these, we defined ten lincRNAs whose expression was elevated in iPSCs compared with embryonic stem cells, suggesting that their activation may promote the emergence of iPSCs. Supporting this, our results indicate that these lincRNAs are direct targets of key pluripotency transcription factors. Using loss-of-function and gain-of-function approaches, we found that one such lincRNA (lincRNA-RoR) modulates reprogramming, thus providing a first demonstration for critical functions of lincRNAs in the derivation of pluripotent stem cells.
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                Author and article information

                Journal
                100941354
                21750
                Nat Immunol
                Nat. Immunol.
                Nature immunology
                1529-2908
                1529-2916
                24 September 2013
                22 September 2013
                November 2013
                01 May 2014
                : 14
                : 11
                : 1190-1198
                Affiliations
                [1 ]Systems Biology Center, National Heart, Lung and Blood Institute, National Institutes of Health (NIH), Bethesda, MD 20892
                [2 ]Laboratory of Immunology, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, MD 20892
                Author notes
                [# ]Corresponding authors: Jinfang Zhu, Laboratory of Immunology, NIAID, Bethesda, MD 20892, Tel. (301) 402-6662, Fax. (301)-480-7352, JFZHU@ 123456niaid.nih.gov . Keji Zhao, Systems Biology Center, NHLBI, Bethesda, MD 20892, Tel. (301) 496-2098, Fax. (301) 480-0961, zhaok@ 123456nhlbi.nih.gov
                [3]

                These authors contributed equally to this work.

                Article
                NIHMS517483
                10.1038/ni.2712
                3805781
                24056746
                e3c240c0-3384-4cbd-8c76-0b74994af57f

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                History
                Funding
                Funded by: National Institute of Allergy and Infectious Diseases Extramural Activities : NIAID
                Award ID: ZIA AI001169-01 || AI
                Categories
                Article

                Immunology
                Immunology

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