RNA-Seq: a revolutionary tool for transcriptomics
TL;DR: 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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TL;DR: Transcription in bacteria resembles that in eukaryotes in terms of complexity more closely than was previously thought.
Abstract: Over the past 3 years, bacterial transcriptomics has undergone a massive revolution. Increased sequencing capacity and novel tools have made it possible to explore the bacterial transcriptome to an unprecedented depth, which has revealed that the transcriptome is more complex and dynamic than expected. Alternative transcripts within operons challenge the classic operon definition, and many small RNAs involved in the regulation of transcription, translation and pathogenesis have been discovered. Furthermore, mRNAs may localize to specific areas in the cell, and the spatial organization and dynamics of the chromosome have been shown to be important for transcription. Epigenetic modifications of DNA also affect transcription, and RNA processing affects translation. Therefore, transcription in bacteria resembles that in eukaryotes in terms of complexity more closely than was previously thought. Here we will discuss the contribution of 'omics' approaches to these discoveries as well as the possible impact that they are expected to have in the future.
136 citations
Cites methods from "RNA-Seq: a revolutionary tool for t..."
...In 2008, RNA-seq was introduced, which involves deep sequencing of cDNA generated from RNA preparation...
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TL;DR: This first application of RNA-seq to dissect durable blast resistance supports a crucial role of the prompt induction of a battery of responses including defence-related genes as well as members of gene families involved in signalling and pathogen-related gene expression regulation.
Abstract: Durable resistance to blast, the most significant fungal disease of rice, represents an agronomically relevant character. Gigante Vercelli (GV) and Vialone Nano (VN) are two old temperate japonica Italian rice cultivars with contrasting response to blast infection: GV displays durable and broad resistance while VN is highly susceptible. RNA-seq was used to dissect the early molecular processes deployed during the resistance response of GV at 24 h after blast inoculation. Differential gene expression analysis identified 1,070 and 1,484 modulated genes, of which 726 and 699 were up regulated in response to infection in GV and VN, respectively. Gene ontology (GO) enrichment analyses revealed a set of GO terms enriched in both varieties but, despite this commonality, the gene sets contributing to common GO enriched terms were dissimilar. The expression patterns of genes grouped in GV-specific enriched GO terms were examined in detail including at the transcript isoform level. GV exhibited a dramatic up-regulation of genes encoding diterpene phytoalexin biosynthetic enzymes, flavin-containing monooxygenase, class I chitinase and glycosyl hydrolase 17. The sensitivity and high dynamic range of RNA-seq allowed the identification of genes critically involved in conferring GV resistance during the early steps of defence perception-signalling. These included chitin oligosaccharides sensing factors, wall associated kinases, MAPK cascades and WRKY transcription factors. Candidate genes with expression patterns consistent with a potential role as GV-specific functional resistance (R) gene(s) were also identified. This first application of RNA-seq to dissect durable blast resistance supports a crucial role of the prompt induction of a battery of responses including defence-related genes as well as members of gene families involved in signalling and pathogen-related gene expression regulation.
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TL;DR: A Web-based system, Plant MetGenMAP, which can comprehensively integrate and analyze large-scale gene expression and metabolite profile data sets along with diverse biological information and provides a unique function that can identify candidate promoter motifs associated with the regulation of specific biochemical pathways.
Abstract: The information and resources generated from diverse “omics” technologies provide opportunities for producing novel biological knowledge. It is essential to integrate various kinds of biological information and large-scale omics data sets through systematic analysis in order to describe and understand complex biological phenomena. For this purpose, we have developed a Web-based system, Plant MetGenMAP, which can comprehensively integrate and analyze large-scale gene expression and metabolite profile data sets along with diverse biological information. Using this system, significantly altered biochemical pathways and biological processes under given conditions can be retrieved rapidly and efficiently, and transcriptional events and/or metabolic changes in a pathway can be easily visualized. In addition, the system provides a unique function that can identify candidate promoter motifs associated with the regulation of specific biochemical pathways. We demonstrate the functions and application of the system using data sets from Arabidopsis (Arabidopsis thaliana) and tomato (Solanum lycopersicum), respectively. The results obtained by Plant MetGenMAP can aid in a better understanding of the mechanisms that underlie interesting biological phenomena and provide novel insights into the biochemical changes associated with them at the gene and metabolite levels. Plant MetGenMAP is freely available at http://bioinfo.bti.cornell.edu/tool/MetGenMAP.
136 citations
Cites background from "RNA-Seq: a revolutionary tool for t..."
...Microarrays and recently emerged RNA-Seq technology have proven to be crucial tools in producing transcriptional data sets by simultaneously detecting the expression of thousands of genes (Wang et al., 2009)....
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TL;DR: It is demonstrated that the identification and characterization of functional lncRNAs associated with kidney disease may represent a promising research direction into renal disorder and may lead to the development of new lncRNA therapies for kidney diseases.
Abstract: We have previously shown that transforming growth factor-β/Smad3-dependent miRNAs play a critical role in renal inflammation and fibrosis. However, off-target effects of miRNAs limit their therapeutic application. Recently, emerging roles of long noncoding RNAs (lncRNAs) in diseases have been recognized. In this study, we used high-throughput RNA sequencing to identify the Smad3-dependent lncRNAs related to renal inflammation and fibrosis in Smad3 knockout mouse models of unilateral ureteral obstructive nephropathy and immunologically induced anti-glomerular basement membrane glomerulonephritis. Compared with wild-type mice, 151 lncRNAs in the unilateral ureteral obstructive nephropathy kidney and 413 lncRNAs in kidneys with anti-glomerular basement membrane glomerulonephritis were significantly altered in Smad3 knockout mice. Among them, 21 common lncRNAs were up-regulated in wild-type, but down-regulated in Smad3 knockout, kidneys in both disease models in which progressive renal inflammation and fibrosis were abolished when the Smad3 gene was deleted or suppressed. Real-time PCR confirmed these findings and revealed the functional link between Smad3-dependent lncRNAs np_5318/np_17856 and progressive kidney injury. Results demonstrate that the identification and characterization of functional lncRNAs associated with kidney disease may represent a promising research direction into renal disorder and may lead to the development of new lncRNA therapies for kidney diseases.
136 citations
TL;DR: A comprehensive view of the effect of a glucocorticoid on the ASM transcriptome is offered and CRISPLD2 is identified as an asthma pharmacogenetics candidate gene that regulates anti-inflammatory effects of glucoc Corticorticoids in the AsM.
Abstract: Asthma is a chronic inflammatory respiratory disease that affects over 300 million people worldwide. Glucocorticoids are a mainstay therapy for asthma because they exert anti-inflammatory effects in multiple lung tissues, including the airway smooth muscle (ASM). However, the mechanism by which glucocorticoids suppress inflammation in ASM remains poorly understood. Using RNA-Seq, a high-throughput sequencing method, we characterized transcriptomic changes in four primary human ASM cell lines that were treated with dexamethasone—a potent synthetic glucocorticoid (1 µM for 18 hours). Based on a Benjamini-Hochberg corrected p-value <0.05, we identified 316 differentially expressed genes, including both well known (DUSP1, KLF15, PER1, TSC22D3) and less investigated (C7, CCDC69, CRISPLD2) glucocorticoid-responsive genes. CRISPLD2, which encodes a secreted protein previously implicated in lung development and endotoxin regulation, was found to have SNPs that were moderately associated with inhaled corticosteroid resistance and bronchodilator response among asthma patients in two previously conducted genome-wide association studies. Quantitative RT-PCR and Western blotting showed that dexamethasone treatment significantly increased CRISPLD2 mRNA and protein expression in ASM cells. CRISPLD2 expression was also induced by the inflammatory cytokine IL1β, and small interfering RNA-mediated knockdown of CRISPLD2 further increased IL1β-induced expression of IL6 and IL8. Our findings offer a comprehensive view of the effect of a glucocorticoid on the ASM transcriptome and identify CRISPLD2 as an asthma pharmacogenetics candidate gene that regulates anti-inflammatory effects of glucocorticoids in the ASM.
136 citations
Cites methods from "RNA-Seq: a revolutionary tool for t..."
...Recent advances in sequencing technologies have made possible the comprehensive and in-depth characterization of transcriptomes via a technique known as RNA-Seq [19–21]....
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References
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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.
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). Other
12,293 citations
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.
Abstract: PROBLEM TO BE SOLVED: To provide a method for preparing a short nucleotide sequence (tag) which is useful to identify a cDNA oligonucleotide and is derived from a restricted position in a mRNA or a cDNA. SOLUTION: This is the method of preparing a tag for identifying the cDNA oligonucleotide. The above method comprises preparing the cDNA oligonucleotide bearing 5' and 3' terminals, collecting cDNA fragments by cutting the cDNA oligonucleotide with a restriction enzyme at the first restriction endonuclease site, separating a cDNA oligonucleotide bearing 5' or 3' terminal and connecting an oligonucleotide linker to the isolated cDNA fragment bearing the cDNA oligonucleotide 5' or 3' terminal. Here, the oligonucleotide linker contains the recognition site of the second restriction endonuclease enzyme and the isolated cDNA fragment is cut with the second restriction endonuclease enzyme which cuts the cDNA fragment in a section separated from the recognition site to obtain the tag for identifying the cDNA oligonucleotide.
4,437 citations
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.
Abstract: New sequencing technologies promise a new era in the use of DNA sequence. However, some of these technologies produce very short reads, typically of a few tens of base pairs, and to use these reads effectively requires new algorithms and software. In particular, there is a major issue in efficiently aligning short reads to a reference genome and handling ambiguity or lack of accuracy in this alignment. Here we introduce the concept of mapping quality, a measure of the confidence that a read actually comes from the position it is aligned to by the mapping algorithm. We describe the software MAQ 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. MAQ makes full use of mate-pair information and estimates the error probability of each read alignment. Error probabilities are also derived for the final genotype calls, using a Bayesian statistical model that incorporates the mapping qualities, error probabilities from the raw sequence quality scores, sampling of the two haplotypes, and an empirical model for correlated errors at a site. Both read mapping and genotype calling are evaluated on simulated data and real data. MAQ is accurate, efficient, versatile, and user-friendly. It is freely available at http://maq.sourceforge.net.
2,927 citations
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).
Abstract: Ultra-high-throughput sequencing is emerging as an attractive alternative to microarrays for genotyping, analysis of methylation patterns, and identification of transcription factor binding sites. Here, we describe an application of the Illumina sequencing (formerly Solexa sequencing) platform to study mRNA expression levels. Our goals were to estimate technical variance associated with Illumina sequencing in this context and to compare its ability to identify differentially expressed genes with existing array technologies. To do so, we estimated gene expression differences between liver and kidney RNA samples using multiple sequencing replicates, and compared the sequencing data to results obtained from Affymetrix arrays using the same RNA samples. We find 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). The information in a single lane of Illumina sequencing data appears comparable to that in a single array in enabling identification of differentially expressed genes, while allowing for additional analyses such as detection of low-expressed genes, alternative splice variants, and novel transcripts. Based on our observations, we propose an empirical protocol and a statistical framework for the analysis of gene expression using ultra-high-throughput sequencing technology.
2,834 citations
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.
Abstract: Summary: We have developed a program SOAP for efficient gapped and ungapped alignment of short oligonucleotides onto reference sequences. The program is designed to handle the huge amounts of short reads generated by parallel sequencing using the new generation Illumina-Solexa sequencing technology. SOAP is compatible with numerous applications, including single-read or pair-end resequencing, small RNA discovery and mRNA tag sequence mapping. SOAP is a command-driven program, which supports multi-threaded parallel computing, and has a batch module for multiple query sets. Availability: http://soap.genomics.org.cn Contact: soap@genomics.org.cn
2,729 citations
"RNA-Seq: a revolutionary tool for t..." refers methods in this paper
...There are several programs for mapping reads to the genome, including ELAND, SOA...
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