Tools for building de novo transcriptome assembly

Geniza, Matthew; Jaiswal, Pankaj

doi:10.1016/j.cpb.2017.12.004

Cited by 48 publications

(37 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Full-length cDNA sequencing with SMRT technology (Iso-Seq) can be used to rapidly reconstruct the grape berry transcriptome, enabling the identification of cultivar-specific isoforms, refinement of the Cabernet Sauvignon genome annotation, and the creation of a reference for transcriptome-wide expression profiling. In contrast to transcriptome reconstruction using short-read sequencing that requires de novo assembly, Iso-Seq delivers fulllength transcripts that eliminate the introduction of assembly errors and artefacts like chimeric transcripts and incomplete fragments due to PolyA capture (Chang et al 2014;Huang et al 2016;Moreton et al 2016;Smith-Unna et al 2016;Geniza and Jaiswal 2017;Ungaro et al 2017). The incorporation of high-coverage short-read sequencing is still necessary to benefit from the complete transcript sequencing enable by Iso-Seq.…”

Section: Discussionmentioning

confidence: 99%

Iso-Seq allows genome-independent transcriptome profiling of grape berry development

Minio

Massonnet

Vondras

et al. 2018

Preprint

View full text Add to dashboard Cite

ABSTRACTseveral ab initio and evidence-based methods. The Iso-Seq information also helped identify 563 additional 27 genes, 4,803 new alternative transcripts, and the 5' and 3' UTRs in the majority of predicted genes. 28Comparisons with the gene content of other grape cultivars identified 549 Cabernet Sauvignon-specific genes, 29 including 65 genes differentially regulated during ripening. Some of these genes were potentially associated 30 with the phenylpropanoid and flavonoid pathways, which may influence unique Cabernet Sauvignon berry 31 attributes. Over 23% of the 36,687 annotated genes in Cabernet Sauvignon had two or more alternative 32 isoforms, predominantly due to intron retention and alternative acceptor and donor sites. We profiled the 33 expression of all isoforms using short read sequencing and identified 252 genes whose alternative transcripts 34 showed different expression patterns during berry development.

show abstract

Section: Discussionmentioning

confidence: 99%

Iso-Seq allows genome-independent transcriptome profiling of grape berry development

Minio

Massonnet

Vondras

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…However, other options do exist for de novo transcriptome assembly. For a plant-focused summary of these tools and other resources, see Geniza and Jaiswal (2017). Additionally, refer to Honaas et al (2016) for a comparative analysis of transcriptomes generated from different assemblers for the model plants rice and Arabidopsis.…”

Section: Comparison Of the Bioinformatic Workflow With Current Methodsmentioning

confidence: 99%

Prediction and Characterization of miRNA/Target Pairs in Non‐Model Plants Using RNA‐seq

2019

View full text Add to dashboard Cite

Plant microRNAs (miRNAs) are ∼20‐ to 24‐nucleotide small RNAs that post‐transcriptionally regulate gene expression of mRNA targets. Here, we present a workflow to characterize the miRNA transcriptome of a non‐model plant, focusing on miRNAs and targets that are differentially expressed under one experimental treatment. We cover RNA‐seq experimental design to create paired small RNA and mRNA libraries and perform quality control of raw data, de novo mRNA transcriptome assembly and annotation, miRNA prediction, differential expression, target identification, and functional enrichment analysis. Additionally, we include validation of differential expression and miRNA‐induced target cleavage using qRT‐PCR and modified RNA ligase–mediated 5′ rapid amplification of cDNA ends, respectively. Our procedure relies on freely available software and web resources. It is intended for users that lack programming skills but can navigate a command‐line interface. To enable an understanding of formatting requirements and anticipated results, we provide sample RNA‐seq data and key input/output files for each stage. © 2019 The Authors. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

show abstract

“…The majority of transcriptome evaluation metrics collected for each sample were higher in Trinity-based DIB re-assemblies than for the Trans-ABySS-based NCGR assemblies, 'cds' versions (1). The Transrate score from the "nt" version of the assemblies were higher in NCGR vs. DIB, whereas compared to the 'cds' version, the DIB re-assemblies were higher (Supplemental Figure 1 [43]).…”

Section: Erences In Available Evaluation Metrics Between Ncgr and mentioning

confidence: 99%

“…The DIB re-assemblies had more contigs than the NCGR assemblies in 83.5% of the samples (1). The mean number of contigs in the DIB re-assemblies was 48,361 ± 35,703 while the mean number of contigs in the NCGR 'nt' assemblies was 30,532 ± 21,353 (2).…”

Section: Erences In Available Evaluation Metrics Between Ncgr and mentioning

confidence: 99%

“…The analysis of gene expression from high-throughput nucleic acid sequence data relies on the presence of a high quality reference genome or transcriptome. When there is no reference genome or transcriptome for an organism of interest, raw RNA sequence data (RNAseq) must be assembled de novo into a transcriptome [1]. This type of analysis is ubiquitous across many elds, including: evolutionary developmental biology [2], cancer biology [3], agriculture [4,5], ecological physiology [6,7], and biological oceanography [8].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Re-assembly, quality evaluation, and annotation of 678 microbial eukaryotic reference transcriptomes

Johnson

Alexander

Brown

2018

Preprint

View full text Add to dashboard Cite

Background De novo transcriptome assemblies are required prior to analyzing RNAseq data from a species without an existing reference genome or transcriptome. Despite the prevalence of transcriptomic studies, the e ects of using di erent work ows, or "pipelines", on the resulting assemblies are poorly understood. Here, a pipeline was programmatically automated and used to assemble and annotate raw transcriptomic short read data collected by the Marine Microbial Eukaryotic Transcriptome Sequencing Project (MMETSP). The resulting transcriptome assemblies were evaluated and compared against assemblies that were previously generated with a di erent pipeline developed by the National Center for Genome Research (NCGR). Results New transcriptome assemblies contained the majority of previous contigs as well as new content. On average, 7.8% of the annotated contigs in the new assemblies were novel gene names not found in the previous assemblies. Taxonomic trends were observed in the assembly metrics, with assemblies from the Dino agellata and Ciliophora phyla showing a higher percentage of open reading frames and number of contigs than transcriptomes from other phyla. Conclusions Given current bioinformatics approaches, there is no single 'best' reference transcriptome for a particular set of raw data. As the optimum transcriptome is a moving target, improving (or not) with new tools and approaches, automated and programmable pipelines are invaluable for managing the computationally-intensive tasks required for re-processing large sets of samples with revised pipelines and ensuring a common evaluation work ow is applied to all samples. Thus, re-assembling existing data with new tools using automated and programmable pipelines may yield more accurate identi cation of taxon-speci c trends across samples in addition to novel and useful products for the community.• Re-assembly with new tools can yield new results • Automated and programmable pipelines can be used to process arbitrarily many samples. • Analyzing many samples using a common pipeline identi es taxon-speci c trends.

show abstract

Tools for building de novo transcriptome assembly

Cited by 48 publications

References 34 publications

Iso-Seq allows genome-independent transcriptome profiling of grape berry development

Iso-Seq allows genome-independent transcriptome profiling of grape berry development

Prediction and Characterization of miRNA/Target Pairs in Non‐Model Plants Using RNA‐seq

Re-assembly, quality evaluation, and annotation of 678 microbial eukaryotic reference transcriptomes

Contact Info

Product

Resources

About