Next-generation transcriptome assembly

By Jeffrey Martin, Zhong Wang. Nature reviews genetics, 2011

1,251 citations recorded by the source corpus.

Transcriptomics studies often rely on partial reference transcriptomes that fail to capture the full catalogue of transcripts and their variations. Recent advances in sequencing technologies and assembly algorithms have facilitated the reconstruction of the entire transcriptome by deep RNA sequencing (RNA-seq), even without a reference genome. However, transcriptome assembly from billions of RNA-seq reads, which are often very short, poses a significant informatics challenge. This Review summarizes the recent developments in transcriptome assembly approaches — reference-based, de novo and combined strategies — along with some perspectives on transcriptome assembly in the near future.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/bd760537cd6413b395c0d4d04dbc47b532105881

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Citations in the corpus

High-Throughput Genomic Data in Systematics and Phylogenetics (2013, background): “F or p er so na l u se o nl y. ES44CH06-Lemmon ARI 29 October 2013 10:2 UCE: ultraconserved element AE: anchored enrichment combinations of exons (Figure 2; Martin & Wang 2011, Ozsolak & Milos 2011, Cronn et al. 2012, Godden et al. 2012).”
Third generation sequencing: technology and its potential impact on evolutionary biodiversity research (2016, neutral): “Third generation sequencing has the potential to eliminate the step of transcriptome sequence assembly in general (Martin & Wang, 2011).”
RNA Sequencing Data: Hitchhiker's Guide to Expression Analysis (2018, background): “255 referencebased) transcriptome assembly [45] , allelespecific expression analyses [46] , expression quantitative trait loci mapping [47] , splicing [48] , analysis of gene regulatory networks [49] or pathway analyses [50,51] .”
TransRate: reference-free quality assessment of de novo transcriptome assemblies (2015, background): “It has been suggested that the transcriptomes from certain groups of organisms may be more difficult 264 to assemble than others (Martin and Wang, 2011).”
rnaSPAdes: a de novo transcriptome assembler and its application to RNA-Seq data (2018, neutral): “While transcriptome assembly may seem to be a simpler problem than genome assembly, RNA-Seq assemblers have to address the complications arising from highly uneven read cov-eragedepthcausedbyvariationsingeneexpressionlevels.”
De novo assembly of bacterial transcriptomes from RNA-seq data (2015, methodology): “Accuracy is the percentage of correctly assembled bases and is computed by aligning assembled transcripts to the corresponding genome and calculating, for those transcripts that align, the percentage of bases in the alignment that correspond to perfect matches as opposed to mismatches or gaps [4].”
Corset: enabling differential gene expression analysis for de novo assembled transcriptomes (2014, methodology): “When no reference genome is available, the transcriptome is de novo assembled directly from RNA-seq reads [3].”
Symbiodinium Functional Diversity in the Coral Siderastrea siderea Is Influenced by Thermal Stress and Reef Environment, but Not Ocean Acidification (2018, methodology): “Transcriptome contiguity analysis (Martin and Wang, 2011) and Benchmarking Universal Single-Copy Orthologs v2 (BUSCO; Simão et al.”