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: An electrochemical approach for the detection of cancer-derived exosomal miRNAs in human serum samples by selectively isolating the target miRNA using magnetic beads pre-functionalized with capture probes and then directly adsorbing the targets onto a gold electrode surface is reported.
Abstract: Recent evidence suggests that small non-coding RNAs such as microRNA (miRNA) encapsulated in exosomes represent an important mechanism of communication between the cells Exosomal miRNAs play an important role in carcinogenesis via enhancing the cell to cell communication and targeting the cell growth molecular pathways which in turn facilitate metastasis in cancers Despite progressive advances, the current methods for the exosomal miRNA detection mostly rely on labor-intensive sequencing approaches which are often prone to amplification bias and require costly and bulky equipment Herein, we report an electrochemical approach for the detection of cancer-derived exosomal miRNAs in human serum samples by selectively isolating the target miRNA using magnetic beads pre-functionalized with capture probes and then directly adsorbing the targets onto a gold electrode surface The level of adsorbed miRNA is detected electrochemically in the presence of an [Fe(CN)6]4-/3- redox system This method enabled an excellent detection sensitivity of 10 pM with a relative standard deviation (%RSD) of <55% in cancer cells and serum samples (n = 8) collected from patients with colorectal adenocarcinoma (CRC) We believe that our approach could be useful in clinical settings for the quantification of exosomal miRNA in cancer patients
101 citations
TL;DR: ReadXplorer is a software offering straightforward visualization and extensive analysis functions for genomic and transcriptomic DNA sequences mapped on a reference, which covers RNA secondary structure prediction, single nucleotide polymorphism and deletion–insertion polymorphism detection, genomic feature and general coverage analysis.
Abstract: Motivation: Fast algorithms and well-arranged visualizations are required for the comprehensive analysis of the ever-growing size of genomic and transcriptomic next-generation sequencing data.
Results: ReadXplorer is a software offering straightforward visualization and extensive analysis functions for genomic and transcriptomic DNA sequences mapped on a reference. A unique specialty of ReadXplorer is the quality classification of the read mappings. It is incorporated in all analysis functions and displayed in ReadXplorer's various synchronized data viewers for (i) the reference sequence, its base coverage as (ii) normalizable plot and (iii) histogram, (iv) read alignments and (v) read pairs. ReadXplorer's analysis capability covers RNA secondary structure prediction, single nucleotide polymorphism and deletion–insertion polymorphism detection, genomic feature and general coverage analysis. Especially for RNA-Seq data, it offers differential gene expression analysis, transcription start site and operon detection as well as RPKM value and read count calculations. Furthermore, ReadXplorer can combine or superimpose coverage of different datasets.
Availability and implementation: ReadXplorer is available as open-source software at http://www.readxplorer.org along with a detailed manual.
Contact: ed.nesseig-inu.dem.oiborkim@reklihr
Supplementary information: Supplementary data are available at Bioinformatics online.
101 citations
TL;DR: This comprehensive molecular atlas elucidates the biochemical functions of lung cell types and the cell-selective transcription factors and optimal markers for making and monitoring them; defines the cell targets of circulating hormones and predicts local signaling interactions; and identifies the cell types directly affected by lung disease genes.
Abstract: Although single cell RNA sequencing studies have begun providing compendia of cell expression profiles, it has proven more difficult to systematically identify and localize all molecular cell types in individual organs to create a full molecular cell atlas. Here we describe droplet- and plate-based single cell RNA sequencing applied to ∼70,000 human lung and blood cells, combined with a multi-pronged cell annotation approach, which have allowed us to define the gene expression profiles and anatomical locations of 58 cell populations in the human lung, including 41 of 45 previously known cell types or subtypes and 14 new ones. This comprehensive molecular atlas elucidates the biochemical functions of lung cell types and the cell-selective transcription factors and optimal markers for making and monitoring them; defines the cell targets of circulating hormones and predicts local signaling interactions including sources and targets of chemokines in immune cell trafficking and expression changes on lung homing; and identifies the cell types directly affected by lung disease genes. Comparison to mouse identified 17 molecular types that appear to have been gained or lost during lung evolution and others whose expression profiles have been substantially altered, revealing extensive plasticity of cell types and cell-type-specific gene expression during organ evolution including expression switches between cell types. This lung atlas provides the molecular foundation for investigating how lung cell identities, functions, and interactions are achieved in development and tissue engineering and altered in disease and evolution.
100 citations
TL;DR: This review focuses on the recent progress in understanding of alternative splicing brought about by the unprecedented explosive growth of genomic data and highlights the relevance of human splicing variation on disease and therapy.
Abstract: Alternative splicing is a major cellular mechanism in metazoans for generating proteomic diversity. A large proportion of protein-coding genes in multicellular organisms undergo alternative splicing, and in humans, it has been estimated that nearly 90 % of protein-coding genes—much larger than expected—are subject to alternative splicing. Genomic analyses of alternative splicing have illuminated its universal role in shaping the evolution of genomes, in the control of developmental processes, and in the dynamic regulation of the transcriptome to influence phenotype. Disruption of the splicing machinery has been found to drive pathophysiology, and indeed reprogramming of aberrant splicing can provide novel approaches to the development of molecular therapy. This review focuses on the recent progress in our understanding of alternative splicing brought about by the unprecedented explosive growth of genomic data and highlights the relevance of human splicing variation on disease and therapy.
100 citations
Cites background from "RNA-Seq: a revolutionary tool for t..."
...Deep sequencing of the transcriptome (facilitated by rapid technological advances) (wang et al. 2009) and the considerable progress in genome-scale mapping of traitassociated loci (brought about by GwaS) (Hindorff et al. 2009) promise to advance our understanding of the genetic mechanisms…...
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TL;DR: Analysis of transcript differences between libraries from the early and late seedling developmental stages demonstrated that starch and sucrose metabolism and phenylpropanoid biosynthesis may be the dominant metabolic events during tuberous root formation and plant hormones probably play critical roles in regulation of this developmental process.
Abstract: The tuberous root of radish is an important vegetable, but insufficient transcriptomic and genomic data are currently available to understand the molecular mechanisms underlying tuberous root formation and development. High-throughput transcriptomic sequencing is essential to generate a large transcript sequence data set for gene discovery and molecular marker development. In this study, a total of 107.3 million clean reads were generated using Illumina paired-end sequencing technology. De novo assembly generated 61,554 unigenes with an average length of 820 bp. Based on a sequence similarity search with known proteins or nucleotides, 85.51 % (52,634), 90.18 % (55,507) and 54 % (33,242) consensus sequences showed homology with sequences in the Nr, Nt and Swiss-Prot databases, respectively. Of these annotated unigenes, 21,109 and 17,343 unigenes were assigned to gene ontology categories and clusters of orthologous groups, respectively. A total of 27,809 unigenes were assigned to 123 pathways in the Kyoto Encyclopedia of Genes and Genomes database. Analysis of transcript differences between libraries from the early and late seedling developmental stages demonstrated that starch and sucrose metabolism and phenylpropanoid biosynthesis may be the dominant metabolic events during tuberous root formation and plant hormones probably play critical roles in regulation of this developmental process. In total, 14,641 potential EST-SSRs were identified among the unigenes, and 12,733 primer pairs for 2,511 SSR were obtained. Summarily, this study gave us a clue to understand the radish tuberous root formation and development, and also provided us with a valuable sequence resource for novel gene discovery and marker-assisted selective breeding in radish. De novo assembled and characterized the radish tuberous root transcriptome; explored the mechanism of radish tuberous root formation; development of EST-SSR markers in radish.
100 citations
Cites background or methods from "RNA-Seq: a revolutionary tool for t..."
...Because RNA fragmentation produces a more even sequence read distribution than cDNA fragmentation (Wang et al. 2009), the mRNA was first sheared into short fragments using divalent cations at 94 C for exactly 5 min before cDNA synthesis....
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...…research in many areas, including resequencing, microRNA expression profiling, DNA methylation and de novo transcriptome sequencing for non-model organisms (Barakat et al. 2009; Hale et al. 2009; Meyer et al. 2009; Wang et al. 2009, 2010b, c; Sun et al. 2010; Huang et al. 2010; Wei et al. 2011)....
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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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