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Open AccessJournal ArticleDOI

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

TLDR
This work developed a sequencing method called 3'-seq to quantitatively map the 3' ends of the transcriptome of diverse human tissues and isogenic transformation systems and found that cell type-specific gene expression is accomplished by two complementary programs.
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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Book ChapterDOI

The Secret Life of RNA: Lessons from Emerging Methodologies

TL;DR: How recently developed technologies aiming at detecting and visualizing RNA molecules have contributed to the emergence of entirely new research fields, and to dramatic progress in the authors' understanding of gene expression regulation is highlighted.
Journal ArticleDOI

Specific Tandem 3'UTR Patterns and Gene Expression Profiles in Mouse Thy1+ Germline Stem Cells

TL;DR: The results identified the expression level and polyadenylation site profiles of male germline stem cells and these data provide new insights into the processes potentially involved in the GSC life cycle and spermatogenesis.
Journal ArticleDOI

RNAs as Regulators of Cellular Matchmaking.

TL;DR: A review of RNA scaffolds and decoys in both the nucleus and cytoplasm can be found in this article, illustrating common themes, the suitability of RNA to such roles, and future challenges in identifying and better understanding RNA scaffolding and decoy functions.
References
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TL;DR: 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.
Journal ArticleDOI

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Journal ArticleDOI

Differential expression analysis for sequence count data.

Simon Anders, +1 more
- 27 Oct 2010 - 
TL;DR: A method based on the negative binomial distribution, with variance and mean linked by local regression, is proposed and an implementation, DESeq, as an R/Bioconductor package is presented.
Journal ArticleDOI

MicroRNA expression profiles classify human cancers

TL;DR: A new, bead-based flow cytometric miRNA expression profiling method is used to present a systematic expression analysis of 217 mammalian miRNAs from 334 samples, including multiple human cancers, and finds the miRNA profiles are surprisingly informative, reflecting the developmental lineage and differentiation state of the tumours.
Journal ArticleDOI

A mammalian microRNA expression atlas based on small RNA library sequencing.

TL;DR: A relatively small set of miRNAs, many of which are ubiquitously expressed, account for most of the differences in miRNA profiles between cell lineages and tissues.
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