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: This paper mainly focuses on recent progress in the use of molecular approaches in Al tolerance research, and suggests Gene-specific molecular markers offer better options for marker-assisted selection in breeding programs than linked marker strategies.
Abstract: Acid soil is a worldwide problem to plant production. Acid toxicity is mainly caused by a lack of essential nutrients in the soil and excessive toxic metals in the plant root zone. Of the toxic metals, aluminum (Al) is the most prevalent and most toxic. Plant species have evolved to variable levels of tolerance to aluminum enabling breeding of high Al-tolerant cultivars. Physiological and molecular approaches have revealed some mechanisms of Al toxicity in higher plants. Mechanisms of plant tolerance to Al stress include: 1) exclusion of Al from the root tips, and 2) absorbance, but tolerance of Al in root cells. Organic acid exudation to chelate Al is a feature shared by many higher plants. The future challenge for Al tolerance studies is the identification of novel tolerance mechanisms and the combination of different mechanisms to achieve higher tolerance. Molecular approaches have led to significant progress in explaining mechanisms and detection of genes responsible for Al tolerance. Gene-specific molecular markers offer better options for marker-assisted selection in breeding programs than linked marker strategies. This paper mainly focuses on recent progress in the use of molecular approaches in Al tolerance research.
127 citations
Cites background from "RNA-Seq: a revolutionary tool for t..."
...Transcriptional approaches, such as transcriptional profiling, RT-PCR, RNAi, Northern blotting, and RNA sequencing [154] facilitated the identification of pathway-related genes and verification of gene function in Al tolerance....
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TL;DR: A snapshot of eukaryotic gene expression in the muskoxen rumen is provided, and a number of candidate genes coding for potentially valuable lignocellulolytic enzymes are identified.
Abstract: Background
Herbivores rely on digestive tract lignocellulolytic microorganisms, including bacteria, fungi and protozoa, to derive energy and carbon from plant cell wall polysaccharides. Culture independent metagenomic studies have been used to reveal the genetic content of the bacterial species within gut microbiomes. However, the nature of the genes encoded by eukaryotic protozoa and fungi within these environments has not been explored using metagenomic or metatranscriptomic approaches.
Methodology/Principal Findings
In this study, a metatranscriptomic approach was used to investigate the functional diversity of the eukaryotic microorganisms within the rumen of muskoxen (Ovibos moschatus), with a focus on plant cell wall degrading enzymes. Polyadenylated RNA (mRNA) was sequenced on the Illumina Genome Analyzer II system and 2.8 gigabases of sequences were obtained and 59129 contigs assembled. Plant cell wall degrading enzyme modules including glycoside hydrolases, carbohydrate esterases and polysaccharide lyases were identified from over 2500 contigs. These included a number of glycoside hydrolase family 6 (GH6), GH48 and swollenin modules, which have rarely been described in previous gut metagenomic studies.
Conclusions/Significance
The muskoxen rumen metatranscriptome demonstrates a much higher percentage of cellulase enzyme discovery and an 8.7x higher rate of total carbohydrate active enzyme discovery per gigabase of sequence than previous rumen metagenomes. This study provides a snapshot of eukaryotic gene expression in the muskoxen rumen, and identifies a number of candidate genes coding for potentially valuable lignocellulolytic enzymes.
127 citations
Cites methods from "RNA-Seq: a revolutionary tool for t..."
...In the present study we applied mRNA-Seq technology [22] to target the polyadenylated eukaryotic mRNA from the muskoxen (Ovibos moschatus) rumen microbial consortium....
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TL;DR: Observations suggest CASC2 as a ceRNA plays an important role in CRC pathogenesis and may serve as a potential target for cancer diagnosis and treatment.
Abstract: Recent evidence highlights the crucial regulatory roles of long noncoding RNAs (lncRNA) in tumor biology. In colorectal cancer (CRC), the expression of several lncRNAs is dysregulated and play essential roles in CRC tumorigenesis. However, the potential biological roles and regulatory mechanisms of the novel human lncRNA, CASC2 (cancer susceptibility candidate 2), in tumor biology are poorly understood. In this study, CASC2 expression was significantly decreased in CRC tissues and CRC cell lines, and decreased expression was significantly more frequent in patients with advanced tumor-node-metastasis stage disease (TNM III and IV) (P = 0.028). Further functional experiments indicate that CASC2 could directly upregulate PIAS3 expression by functioning as a competing endogenous RNA (ceRNA) for miR-18a. This interactions leads to the de-repression of genes downstream of STAT3 and consequentially inhibition of CRC cell proliferation and tumor growth in vitro and in vivo by extending the G0/G1-S phase transition. Taken together, these observations suggest CASC2 as a ceRNA plays an important role in CRC pathogenesis and may serve as a potential target for cancer diagnosis and treatment.
127 citations
TL;DR: RNA sequencing and microarray platforms are used to quantify gene expression from labeled cells isolated by fluorescence-activated cell sorting to generate cell-type-specific transcriptomes during development of an adult stem-cell lineage in the Arabidopsis leaf.
127 citations
Cites background from "RNA-Seq: a revolutionary tool for t..."
...…non-significant stomatal index increase relative to WT. expression profiling; in each of these cases, there is discussion about which platform provides the most accurate results (Wang et al., 2009, 2014; Zhao et al., 2014), but as yet, there are no sophisticatedmethods for cross-platform analyses....
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TL;DR: The current report presents principles that underlie NGS including sequencing library preparation, sequencing chemistries, and an introduction to NGS data analysis, as well as a case study using NGS for targeted resequencing of genes implicated in hypertrophic cardiomyopathy.
127 citations
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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