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.
Citations
More filters
TL;DR: This work discusses the importance of robust experimental design to allow for a more sophisticated characterization of transcriptomic responses and offers recommendations for future research, including integrating genomics with transcriptomics, testing gene regulatory networks, and comparing the equivalence of transcription to translation and the effects of environmental stress on the proteome.
Abstract: Physiological plasticity and adaptive evolution may facilitate persistence in a changing environment. As a result, there is an interest in understanding species' capacities for plastic and evolved responses, and the mechanisms by which these responses occur. Transcriptome sequencing has become a powerful tool for addressing these questions, providing insight into otherwise unobserved effects of changing conditions on organismal physiology and variation in these effects among individuals and populations. Here, we review recent studies using comparative transcriptomics to understand plastic and evolutionary responses to changing environments. We focus on 2 areas where transcriptomics has played an important role: first, in understanding the genetic basis for local adaptation to current gradients as a proxy for future adaptation, and second, in understanding organismal responses to multiple stressors. We find most studies examining multiple stressors have tested the effects of each stressor individually; the few studies testing multiple stressors simultaneously have found synergistic effects on gene expression that would not have been predicted from single stressor studies. We discuss the importance of robust experimental design to allow for a more sophisticated characterization of transcriptomic responses and conclude by offering recommendations for future research, including integrating genomics with transcriptomics, testing gene regulatory networks, and comparing the equivalence of transcription to translation and the effects of environmental stress on the proteome.
90 citations
Cites background from "RNA-Seq: a revolutionary tool for t..."
...Simultaneously, the advent of next generation sequencing has made genomic resources, especially transcriptomics (RNA-Seq), available to nonmodel organisms (Wang et al. 2009; Alvarez et al. 2015), allowing new ways to understand organismal responses to the environment....
[...]
TL;DR: The assembled transcriptome of litchi fruit provides a global description of expressed genes in litchesi fruit development, and could serve as an ideal repository for future functional characterization of specific genes.
Abstract: Background
Litchi (Litchi chinensis Sonn.) is one of the most important fruit trees cultivated in tropical and subtropical areas. However, a lack of transcriptomic and genomic information hinders our understanding of the molecular mechanisms underlying fruit set and fruit development in litchi. Shading during early fruit development decreases fruit growth and induces fruit abscission. Here, high-throughput RNA sequencing (RNA-Seq) was employed for the de novo assembly and characterization of the fruit transcriptome in litchi, and differentially regulated genes, which are responsive to shading, were also investigated using digital transcript abundance(DTA)profiling.
90 citations
Cites background from "RNA-Seq: a revolutionary tool for t..."
...Next generation sequencing technology (NGS), such as high-throughput paired-end RNA sequencing (RNASeq) and digital transcript abundance(DTA)tag profiling, has greatly facilitated investigation of the functional complexity of transcriptomes for non-model organisms without a reference genome [5-7]....
[...]
TL;DR: This work will present the status of the current capabilities to assess and predict catabolic potential of environmental sites by applying gene fingerprinting, catabolome arrays, metagenomics and complementary 'omics' technologies to understand the mechanisms taking place in large scale bioremediation treatments for aromatic decontamination.
Abstract: Microbial degradation is the main mechanism responsible for the recovery of contaminated sites, where a huge body of investigations is available in which most concentrate on single isolates from soils capable of mineralizing pollutants. The rapid development of molecular techniques in recent years allows immense insights into the processes in situ, including identification of organisms active in target sites, community member interactions and catabolic gene structures. Only a detailed understanding of the functioning and interactions within microbial communities will allow their rational manipulation for the purpose of optimizing bioremediation efforts. We will present the status of the current capabilities to assess and predict catabolic potential of environmental sites by applying gene fingerprinting, catabolome arrays, metagenomics and complementary 'omics' technologies. Collectively, this will allow tracking regulation and evolution within microbial communities ultimately aiming to understand the mechanisms taking place in large scale bioremediation treatments for aromatic decontamination.
89 citations
TL;DR: Next-generation sequencing technologies are used to sequence the transcriptome of the nickel hyperaccumulator Psychotria gabriellae of the Rubiaceae family and characterized the activity of three metal transporters, showing that PgIREG1 is able to confer nickel tolerance when expressed in yeast and in transgenic plants, where it localizes in the tonoplast.
Abstract: Nickel is an economically important metal and phytotechnologies are being developed to limit the impact of nickel mining on the environment. More than 300 plant species are known to hyperaccumulate nickel. However, our knowledge of the mechanisms involved in nickel accumulation in plants is very limited because it has not yet been possible to study these hyperaccumulators at the genomic level. Here, we used next-generation sequencing technologies to sequence the transcriptome of the nickel hyperaccumulator Psychotria gabriellae of the Rubiaceae family, and used yeast and Arabidopsis as heterologous systems to study the activity of identified metal transporters. We characterized the activity of three metal transporters from the NRAMP and IREG/FPN families. In particular, we showed that PgIREG1 is able to confer nickel tolerance when expressed in yeast and in transgenic plants, where it localizes in the tonoplast. In addition, PgIREG1 shows higher expression in P. gabriellae than in the related non-accumulator species Psychotria semperflorens. Our results designate PgIREG1 as a candidate gene for nickel tolerance and hyperaccumulation in P. gabriellae. These results also show how next-generation sequencing technologies can be used to access the transcriptome of non-model nickel hyperaccumulators to identify the underlying molecular mechanisms.
89 citations
TL;DR: This study provides a global view of the complexity of the pig transcriptome, and gives an extensive new knowledge about alternative splicing, gene boundaries and miRNAs in pigs.
Abstract: Elucidation of the pig transcriptome is essential for interpreting functional elements of the genome and understanding the genetic architecture of complex traits such as fat deposition, metabolism and growth. Here we used massive parallel high-throughput RNA sequencing to generate a high-resolution map of the porcine mRNA and miRNA transcriptome in liver, longissimus dorsi and abdominal fat from two full-sib F2 hybrid pigs with segregated phenotypes on growth, blood physiological and biochemical parameters, and fat deposition. We obtained 8,508,418-10,219,332 uniquely mapped reads that covered 78.0% of the current annotated transcripts and identified 48,045-122,931 novel transcript fragments, which constituted 17,085-29,499 novel transcriptional active regions in six tested samples. We found that about 18.8% of the annotated genes showed alternative splicing patterns, and alternative 3' splicing is the most common type of alternative splicing events in pigs. Cross-tissue comparison revealed that many transcriptional events are tissue-differential and related to important biological functions in their corresponding tissues. We also detected a total of 164 potential novel miRNAs, most of which were tissue-specifically identified. Integrated analysis of genome-wide association study and differential gene expression revealed interesting candidate genes for complex traits, such as IGF2, CYP1A1, CKM and CES1 for heart weight, hemoglobin, pork pH value and serum cholesterol, respectively. This study provides a global view of the complexity of the pig transcriptome, and gives an extensive new knowledge about alternative splicing, gene boundaries and miRNAs in pigs. Integrated analysis of genome wide association study and differential gene expression allows us to find important candidate genes for porcine complex traits.
89 citations
Cites background from "RNA-Seq: a revolutionary tool for t..."
...0%) at UCSC database [24] was covered by sequence reads, showing the sensitivity of RNA-seq in transcript discovery even for lowly expressed genes [48]....
[...]
References
More filters
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...
[...]