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Open AccessJournal ArticleDOI

RNA-Seq: a revolutionary tool for transcriptomics

Zhong Wang, +2 more
- 01 Jan 2009 - 
- Vol. 10, Iss: 1, pp 57-63
TLDR
The RNA-Seq approach to transcriptome profiling that uses deep-sequencing technologies provides a far more precise measurement of levels of transcripts and their isoforms than other methods.
Abstract
RNA-Seq is a recently developed approach to transcriptome profiling that uses deep-sequencing technologies. Studies using this method have already altered our view of the extent and complexity of eukaryotic transcriptomes. RNA-Seq also provides a far more precise measurement of levels of transcripts and their isoforms than other methods. This article describes the RNA-Seq approach, the challenges associated with its application, and the advances made so far in characterizing several eukaryote transcriptomes.

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Citations
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Ribosome profiling: new views of translation, from single codons to genome scale

TL;DR: It is shown that ribosome profiling is an emerging technique that uses deep sequencing to monitor in vivo translation and provides new insights into the identity and the amount of proteins that are produced by cells, as well as detailed views into the mechanism of protein synthesis itself.
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Chemical Ecology of Endophytic Fungi: Origins of Secondary Metabolites

TL;DR: The possible current and future strategies of understanding the chemical communication of endophytic fungi with other endophytes and with their host plants might not only allow the discovery and sustainable production of desirable natural products but also other mostly overlooked bioactive secondary metabolites.
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Removing technical variability in RNA-seq data using conditional quantile normalization

TL;DR: A statistical methodology is described that improves precision by 42% without loss of accuracy and combines robust generalized regression to remove systematic bias introduced by deterministic features such as GC-content and quantile normalization to correct for global distortions.
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Revisiting Global Gene Expression Analysis

TL;DR: In this article, the authors discuss common assumptions currently embedded in experimental and analytical practices that can lead to misinterpretation of global gene expression data and describe solutions that should minimize erroneous interpretation of gene expression from multiple analysis platforms.
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Ribosome Profiling Reveals Pervasive Translation Outside of Annotated Protein-Coding Genes

TL;DR: Hallmarks of translation in ribosome footprints are shown: copurification with the large ribosomal subunit, response to drugs targeting elongation, trinucleotide periodicity, and initiation at early AUGs.
References
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Journal ArticleDOI

Mapping and quantifying mammalian transcriptomes by RNA-Seq.

TL;DR: 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.
PatentDOI

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TL;DR: Serial analysis of gene expression (SAGE) should provide a broadly applicable means for the quantitative cataloging and comparison of expressed genes in a variety of normal, developmental, and disease states.
Journal ArticleDOI

Mapping short DNA sequencing reads and calling variants using mapping quality scores

TL;DR: This work describes the software MAQ, software that can build assemblies by mapping shotgun short reads to a reference genome, using quality scores to derive genotype calls of the consensus sequence of a diploid genome, e.g., from a human sample.
Journal ArticleDOI

RNA-seq: An assessment of technical reproducibility and comparison with gene expression arrays

TL;DR: It is found that the Illumina sequencing data are highly replicable, with relatively little technical variation, and thus, for many purposes, it may suffice to sequence each mRNA sample only once (i.e., using one lane).
Journal ArticleDOI

SOAP: short oligonucleotide alignment program

TL;DR: The program SOAP is designed to handle the huge amounts of short reads generated by parallel sequencing using the new generation Illumina-Solexa sequencing technology, which supports multi-threaded parallel computing and has a batch module for multiple query sets.
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