Journal ArticleDOI
Mapping and quantifying mammalian transcriptomes by RNA-Seq.
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TLDR
Although >90% of uniquely mapped reads fell within known exons, the remaining data suggest new and revised gene models, including changed or additional promoters, exons and 3′ untranscribed regions, as well as new candidate microRNA precursors.Abstract:
We have mapped and quantified mouse transcriptomes by deeply sequencing them and recording how frequently each gene is represented in the sequence sample (RNA-Seq). This provides a digital measure of the presence and prevalence of transcripts from known and previously unknown genes. We report reference measurements composed of 41–52 million mapped 25-base-pair reads for poly(A)-selected RNA from adult mouse brain, liver and skeletal muscle tissues. We used RNA standards to quantify transcript prevalence and to test the linear range of transcript detection, which spanned five orders of magnitude. Although >90% of uniquely mapped reads fell within known exons, the remaining data suggest new and revised gene models, including changed or additional promoters, exons and 3′ untranscribed regions, as well as new candidate microRNA precursors. RNA splice events, which are not readily measured by standard gene expression microarray or serial analysis of gene expression methods, were detected directly by mapping splice-crossing sequence reads. We observed 1.45 × 10 5 distinct splices, and alternative splices were prominent, with 3,500 different genes expressing one or more alternate internal splices. The mRNA population specifies a cell’s identity and helps to govern its present and future activities. This has made transcriptome analysis a general phenotyping method, with expression microarrays of many kinds in routine use. Here we explore the possibility that transcriptome analysis, transcript discovery and transcript refinement can be done effectively in large and complex mammalian genomes by ultra-high-throughput sequencing. Expression microarrays are currently the most widely used methodology for transcriptome analysis, although some limitations persist. These include hybridization and cross-hybridization artifacts 1–3 , dye-based detection issues and design constraints that preclude or seriously limit the detection of RNA splice patterns and previously unmapped genes. These issues have made it difficult for standard array designs to provide full sequence comprehensiveness (coverage of all possible genes, including unknown ones, in large genomes) or transcriptome comprehensiveness (reliable detection of all RNAs of all prevalence classes, including the least abundant ones that are physiologically relevant). Otherread more
Citations
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Journal ArticleDOI
Measuring differential gene expression by short read sequencing: quantitative comparison to 2-channel gene expression microarrays.
TL;DR: Using a large number of quantitative PCR (qPCR) assays, more than previous studies, it is found that neither technology is decisively better at measuring differential gene expression.
Journal ArticleDOI
Digital transcriptome profiling using selective hexamer priming for cDNA synthesis.
Christopher D. Armour,John C. Castle,Ronghua Chen,Tomas Babak,Patrick M. Loerch,Stuart Jackson,Jyoti Shah,John Dey,Carol A. Rohl,Jason M. Johnson,Christopher K. Raymond +10 more
TL;DR: The procedure for the preparation of whole transcriptome cDNA libraries depleted of ribosomal RNA from only 1 μg of total RNA is developed and validated by profiling human whole brain and universal human reference RNA using ultra-high-throughput sequencing.
Journal ArticleDOI
The B-cell identity factor Pax5 regulates distinct transcriptional programmes in early and late B lymphopoiesis
Roger Revilla-i-Domingo,Ivan Bilic,Bojan Vilagos,Hiromi Tagoh,Anja Ebert,Ido Tamir,Leonie Smeenk,Johanna Trupke,Andreas Sommer,Markus Jaritz,Meinrad Busslinger +10 more
TL;DR: Regulated Pax5 target genes minimally overlap in pro‐B and mature B cells, which reflects massive expression changes between these cell types and identifies Pax5 as an important regulator of this developmental transition.
Journal ArticleDOI
Epigenetic mechanisms in diabetic vascular complications.
Marpadga A. Reddy,Rama Natarajan +1 more
TL;DR: The role of epigenetics in diabetes and its vascular complications, and recent technological advances that have significantly accelerated the field are highlighted.
Journal ArticleDOI
Smooth Muscle Enriched Long Noncoding RNA (SMILR) Regulates Cell Proliferation
Margaret D. Ballantyne,Karine Pinel,Rachel S. Dakin,Alex T. Vesey,Louise A. Diver,Ruth M. Mackenzie,Raquel Garcia,Paul Welsh,Naveed Sattar,Graham Hamilton,Nikhil Joshi,Marc R. Dweck,Joseph M. Miano,Martin W. McBride,David E. Newby,Robert A. McDonald,Andrew H. Baker +16 more
TL;DR: The results identify SMILR as a driver of vascular smooth muscle cell proliferation and suggest that modulation of SMilR may be a novel therapeutic strategy to reduce vascular pathologies.
References
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Ugrappa Nagalakshmi,Zhong Wang,Karl Waern,C. Shou,Debasish Raha,Mark Gerstein,Michael Snyder +6 more
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Journal ArticleDOI
Highly Integrated Single-Base Resolution Maps of the Epigenome in Arabidopsis
Ryan Lister,Ronan C. O'Malley,Julian Tonti-Filippini,Brian D. Gregory,Charles C. Berry,A. Harvey Millar,Joseph R. Ecker +6 more
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RNA Maps Reveal New RNA Classes and a Possible Function for Pervasive Transcription
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