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      Ubiquitously transcribed genes use alternative polyadenylation to achieve tissue-specific expression.

      Genes & development
      3' Untranslated Regions, genetics, Cell Differentiation, Cell Line, Cell Line, Tumor, Cell Transformation, Viral, physiology, Embryonic Stem Cells, metabolism, Gene Expression Profiling, Gene Expression Regulation, Developmental, HEK293 Cells, HeLa Cells, Herpesvirus 4, Human, Humans, MCF-7 Cells, Molecular Sequence Data, Organ Specificity, Polyadenylation, Protein Isoforms, RNA, Messenger, chemistry

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          Abstract

          More than half of human genes use alternative cleavage and polyadenylation (ApA) to generate mRNA transcripts that differ in the lengths of their 3' untranslated regions (UTRs), thus altering the post-transcriptional fate of the message and likely the protein output. The extent of 3' UTR variation across tissues and the functional role of ApA remain poorly understood. We developed a sequencing method called 3'-seq to quantitatively map the 3' ends of the transcriptome of diverse human tissues and isogenic transformation systems. We found that cell type-specific gene expression is accomplished by two complementary programs. Tissue-restricted genes tend to have single 3' UTRs, whereas a majority of ubiquitously transcribed genes generate multiple 3' UTRs. During transformation and differentiation, single-UTR genes change their mRNA abundance levels, while multi-UTR genes mostly change 3' UTR isoform ratios to achieve tissue specificity. However, both regulation programs target genes that function in the same pathways and processes that characterize the new cell type. Instead of finding global shifts in 3' UTR length during transformation and differentiation, we identify tissue-specific groups of multi-UTR genes that change their 3' UTR ratios; these changes in 3' UTR length are largely independent from changes in mRNA abundance. Finally, tissue-specific usage of ApA sites appears to be a mechanism for changing the landscape targetable by ubiquitously expressed microRNAs.

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          Differential expression analysis for sequence count data

          High-throughput sequencing assays such as RNA-Seq, ChIP-Seq or barcode counting provide quantitative readouts in the form of count data. To infer differential signal in such data correctly and with good statistical power, estimation of data variability throughout the dynamic range and a suitable error model are required. We propose a method based on the negative binomial distribution, with variance and mean linked by local regression and present an implementation, DESeq, as an R/Bioconductor package.
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            MicroRNAs: genomics, biogenesis, mechanism, and function.

            MicroRNAs (miRNAs) are endogenous approximately 22 nt RNAs that can play important regulatory roles in animals and plants by targeting mRNAs for cleavage or translational repression. Although they escaped notice until relatively recently, miRNAs comprise one of the more abundant classes of gene regulatory molecules in multicellular organisms and likely influence the output of many protein-coding genes.
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              Comprehensive analysis of mRNA methylation reveals enrichment in 3' UTRs and near stop codons.

              Methylation of the N(6) position of adenosine (m(6)A) is a posttranscriptional modification of RNA with poorly understood prevalence and physiological relevance. The recent discovery that FTO, an obesity risk gene, encodes an m(6)A demethylase implicates m(6)A as an important regulator of physiological processes. Here, we present a method for transcriptome-wide m(6)A localization, which combines m(6)A-specific methylated RNA immunoprecipitation with next-generation sequencing (MeRIP-Seq). We use this method to identify mRNAs of 7,676 mammalian genes that contain m(6)A, indicating that m(6)A is a common base modification of mRNA. The m(6)A modification exhibits tissue-specific regulation and is markedly increased throughout brain development. We find that m(6)A sites are enriched near stop codons and in 3' UTRs, and we uncover an association between m(6)A residues and microRNA-binding sites within 3' UTRs. These findings provide a resource for identifying transcripts that are substrates for adenosine methylation and reveal insights into the epigenetic regulation of the mammalian transcriptome. Copyright © 2012 Elsevier Inc. All rights reserved.
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