RNA-Seq for Transcriptome Analysis in Non-model Plants
TL;DR: The aim is to provide a quick start guide to the nonexpert researchers for NGS-based transcriptome analysis, including various strategies of transcriptome assembly, which need substantial consideration for a successful RNA-seq experiment.
Abstract: Sequencing of mRNA using next-generation sequencing (NGS) technologies (RNA-seq) has the potential to reveal unprecedented complexity of the transcriptomes. The transcriptome sequencing of an organism provides quick insights into the gene space, opportunity to isolate genes of interest, development of functional markers, quantitation of gene expression, and comparative genomic studies. Although becoming cheaper, transcriptome sequencing still remains an expensive endeavor. Further, the assembly of millions and billions of RNA-seq reads to construct the complete transcriptome poses great informatics challenges. Here, first we outline various important issues from experimental design to data analysis, including various strategies of transcriptome assembly, which need substantial consideration for a successful RNA-seq experiment. Further, we describe a method for using RNA-seq to characterize the transcriptome of a plant species, taking the example of a legume crop plant chickpea. Our aim is to provide a quick start guide to the nonexpert researchers for NGS-based transcriptome analysis.
Citations
More filters
TL;DR: This resource has allowed identification of the pea orthologs of major nodulation genes characterized in recent years in model species, as a major step towards deciphering unresolved pea nodulation phenotypes.
Abstract: Next-generation sequencing technologies allow an almost exhaustive survey of the transcriptome, even in species with no available genome sequence. To produce a Unigene set representing most of the expressed genes of pea, 20 cDNA libraries produced from various plant tissues harvested at various developmental stages from plants grown under contrasting nitrogen conditions were sequenced. Around one billion reads and 100 Gb of sequence were de novo assembled. Following several steps of redundancy reduction, 46 099 contigs with N50 length of 1667 nt were identified. These constitute the 'Cameor' Unigene set. The high depth of sequencing allowed identification of rare transcripts and detected expression for approximately 80% of contigs in each library. The Unigene set is now available online (http://bios.dijon.inra.fr/FATAL/cgi/pscam.cgi), allowing (i) searches for pea orthologs of candidate genes based on gene sequences from other species, or based on annotation, (ii) determination of transcript expression patterns using various metrics, (iii) identification of uncharacterized genes with interesting patterns of expression, and (iv) comparison of gene ontology pathways between tissues. This resource has allowed identification of the pea orthologs of major nodulation genes characterized in recent years in model species, as a major step towards deciphering unresolved pea nodulation phenotypes. In addition to a remarkable conservation of the early transcriptome nodulation apparatus between pea and Medicago truncatula, some specific features were highlighted. The resource provides a reference for the pea exome, and will facilitate transcriptome and proteome approaches as well as SNP discovery in pea.
151 citations
TL;DR: An overview of the recent achievements regarding abiotic stress resistance in a wide range of legume crops is provided and the transcriptomic and miRNA approaches that have been used are highlighted.
Abstract: Grain legumes are an important source of nutrition and income for billions of consumers and farmers around the world. However, the low productivity of new legume varieties, due to the limited genetic diversity available for legume breeding programmes and poor policymaker support, combined with an increasingly unpredictable global climate is resulting in a large gap between current yields and the increasing demand for legumes as food. Hence, there is a need for novel approaches to develop new high-yielding legume cultivars that are able to cope with a range of environmental stressors. Next-generation technologies are providing the tools that could enable the more rapid and cost-effective genomic and transcriptomic studies for most major crops, allowing the identification of key functional and regulatory genes involved in abiotic stress resistance. In this review, we provide an overview of the recent achievements regarding abiotic stress resistance in a wide range of legume crops and highlight the transcriptomic and miRNA approaches that have been used. In addition, we critically evaluate the availability and importance of legume genetic resources with desirable abiotic stress resistance traits.
85 citations
TL;DR: This review compares the marker systems used for fine mapping and QTL cloning in the pre- and post-NGS era, and discusses how different NGS platforms in combination with advanced experimental designs have improved trait analysis and fine mapping.
Abstract: Improvement in traits of agronomic importance is the top breeding priority of crop improvement programs. Majority of these agronomic traits show complex quantitative inheritance. Identification of quantitative trait loci (QTLs) followed by fine mapping QTLs and cloning of candidate genes/QTLs is central to trait analysis. Advances in genomic technologies revolutionized our understanding of genetics of complex traits, and genomic regions associated with traits were employed in marker-assisted breeding or cloning of QTLs/genes. Next-generation sequencing (NGS) technologies have enabled genome-wide methodologies for the development of ultra-high-density genetic linkage maps in different crops, thus allowing placement of candidate loci within few kbs in genomes. In this review, we compare the marker systems used for fine mapping and QTL cloning in the pre- and post-NGS era. We then discuss how different NGS platforms in combination with advanced experimental designs have improved trait analysis and fine mapping. We opine that efficient genotyping/sequencing assays may circumvent the need for cumbersome procedures that were earlier used for fine mapping. A deeper understanding of the trait architectures of agricultural significance will be crucial to accelerate crop improvement.
84 citations
Cites background from "RNA-Seq for Transcriptome Analysis ..."
...2011; Garg and Jain 2013; Goodwin et al....
[...]
...As these techniques are adequately reviewed elsewhere, they are not discussed in detail in this review (Davey et al. 2011; Garg and Jain 2013; Goodwin et al. 2016)....
[...]
TL;DR: An in-depth overview of the transcriptomes of both soybean and white lupin is provided, illustrating the power of next-generation sequencing and bioinformatic analyses in elucidating the gene networks underlying biological processes.
53 citations
Cites background from "RNA-Seq for Transcriptome Analysis ..."
...However, the aforementioned approaches to transcript studies have major limitations including: (1) sample size and normalization; (2) speed; (3) sensitivity; (4) cost; and (5) limited dynamic range (Wang et al., 2009; L. Wang et al., 2010; Ozsolak and Milos, 2011; Schneeberger and Weigel, 2011; Garg and Jain, 2013)....
[...]
...…approaches to transcript studies have major limitations including: (1) sample size and normalization; (2) speed; (3) sensitivity; (4) cost; and (5) limited dynamic range (Wang et al., 2009; L. Wang et al., 2010; Ozsolak and Milos, 2011; Schneeberger and Weigel, 2011; Garg and Jain, 2013)....
[...]
...Unprecedented advances in high-throughput nextgeneration RNA-seq have resulted in a paradigm shift in transcriptome studies (Lister et al., 2008; Mochida and Shinozaki, 2011; Garg and Jain, 2013)....
[...]
TL;DR: The use of FMs in breeding for development of elite crop cultivars to enhance global food security goals is described and the latest methods in FM development are reviewed.
Abstract: Advances in molecular biology including genomics, high-throughput sequencing, and genome editing enable increasingly faster and more precise cultivar development. Identifying genes and functional markers (FMs) that are highly associated with plant phenotypic variation is a grand challenge. Functional genomics approaches such as transcriptomics, targeting induced local lesions in genomes (TILLING), homologous recombinant (HR), association mapping, and allele mining are all strategies to identify FMs for breeding goals, such as agronomic traits and biotic and abiotic stress resistance. The advantage of FMs over other markers used in plant breeding is the close genomic association of an FM with a phenotype. Thereby, FMs may facilitate the direct selection of genes associated with phenotypic traits, which serves to increase selection efficiencies to develop varieties. Herein, we review the latest methods in FM development and how FMs are being used in precision breeding for agronomic and quality traits as well as in breeding for biotic and abiotic stress resistance using marker assisted selection (MAS) methods. In summary, this article describes the use of FMs in breeding for development of elite crop cultivars to enhance global food security goals.
50 citations
References
More filters
TL;DR: The results suggest that Cufflinks can illuminate the substantial regulatory flexibility and complexity in even this well-studied model of muscle development and that it can improve transcriptome-based genome annotation.
Abstract: High-throughput mRNA sequencing (RNA-Seq) promises simultaneous transcript discovery and abundance estimation. However, this would require algorithms that are not restricted by prior gene annotations and that account for alternative transcription and splicing. Here we introduce such algorithms in an open-source software program called Cufflinks. To test Cufflinks, we sequenced and analyzed >430 million paired 75-bp RNA-Seq reads from a mouse myoblast cell line over a differentiation time series. We detected 13,692 known transcripts and 3,724 previously unannotated ones, 62% of which are supported by independent expression data or by homologous genes in other species. Over the time series, 330 genes showed complete switches in the dominant transcription start site (TSS) or splice isoform, and we observed more subtle shifts in 1,304 other genes. These results suggest that Cufflinks can illuminate the substantial regulatory flexibility and complexity in even this well-studied model of muscle development and that it can improve transcriptome-based genome annotation.
13,337 citations
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.
11,528 citations
TL;DR: This protocol begins with raw sequencing reads and produces a transcriptome assembly, lists of differentially expressed and regulated genes and transcripts, and publication-quality visualizations of analysis results, which takes less than 1 d of computer time for typical experiments and ∼1 h of hands-on time.
Abstract: Recent advances in high-throughput cDNA sequencing (RNA-seq) can reveal new genes and splice variants and quantify expression genome-wide in a single assay. The volume and complexity of data from RNA-seq experiments necessitate scalable, fast and mathematically principled analysis software. TopHat and Cufflinks are free, open-source software tools for gene discovery and comprehensive expression analysis of high-throughput mRNA sequencing (RNA-seq) data. Together, they allow biologists to identify new genes and new splice variants of known ones, as well as compare gene and transcript expression under two or more conditions. This protocol describes in detail how to use TopHat and Cufflinks to perform such analyses. It also covers several accessory tools and utilities that aid in managing data, including CummeRbund, a tool for visualizing RNA-seq analysis results. Although the procedure assumes basic informatics skills, these tools assume little to no background with RNA-seq analysis and are meant for novices and experts alike. The protocol begins with raw sequencing reads and produces a transcriptome assembly, lists of differentially expressed and regulated genes and transcripts, and publication-quality visualizations of analysis results. The protocol's execution time depends on the volume of transcriptome sequencing data and available computing resources but takes less than 1 d of computer time for typical experiments and ∼1 h of hands-on time.
10,913 citations
TL;DR: Velvet represents a new approach to assembly that can leverage very short reads in combination with read pairs to produce useful assemblies and is in close agreement with simulated results without read-pair information.
Abstract: We have developed a new set of algorithms, collectively called "Velvet," to manipulate de Bruijn graphs for genomic sequence assembly. A de Bruijn graph is a compact representation based on short words (k-mers) that is ideal for high coverage, very short read (25-50 bp) data sets. Applying Velvet to very short reads and paired-ends information only, one can produce contigs of significant length, up to 50-kb N50 length in simulations of prokaryotic data and 3-kb N50 on simulated mammalian BACs. When applied to real Solexa data sets without read pairs, Velvet generated contigs of approximately 8 kb in a prokaryote and 2 kb in a mammalian BAC, in close agreement with our simulated results without read-pair information. Velvet represents a new approach to assembly that can leverage very short reads in combination with read pairs to produce useful assemblies.
9,389 citations
TL;DR: A scalable, highly parallel sequencing system with raw throughput significantly greater than that of state-of-the-art capillary electrophoresis instruments with 96% coverage at 99.96% accuracy in one run of the machine is described.
Abstract: The proliferation of large-scale DNA-sequencing projects in recent years has driven a search for alternative methods to reduce time and cost. Here we describe a scalable, highly parallel sequencing system with raw throughput significantly greater than that of state-of-the-art capillary electrophoresis instruments. The apparatus uses a novel fibre-optic slide of individual wells and is able to sequence 25 million bases, at 99% or better accuracy, in one four-hour run. To achieve an approximately 100-fold increase in throughput over current Sanger sequencing technology, we have developed an emulsion method for DNA amplification and an instrument for sequencing by synthesis using a pyrosequencing protocol optimized for solid support and picolitre-scale volumes. Here we show the utility, throughput, accuracy and robustness of this system by shotgun sequencing and de novo assembly of the Mycoplasma genitalium genome with 96% coverage at 99.96% accuracy in one run of the machine.
8,434 citations