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The impacts of read length and transcriptome complexity for de novo assembly: a simulation study.

ABSTRACT: Transcriptome assembly using RNA-seq data - particularly in non-model organisms has been dramatically improved, but only recently have the pre-assembly procedures, such as sequencing depth and error correction, been studied. Increasing read length is viewed as a crucial condition to further improve transcriptome assembly, but it is unknown whether the read length really matters. In addition, though many assembly tools are available now, it is unclear whether the existing assemblers perform well enough for all data with different transcriptome complexities. In this paper, we studied these two open problems using two high-performing assemblers, Velvet/Oases and Trinity, on several simulated datasets of human, mouse and S.cerevisiae. The results suggest that (1) the read length of paired reads does not matter once it exceeds a certain threshold, and interestingly, the threshold is distinct in different organisms; (2) the quality of de novo assembly decreases sharply with the increase of transcriptome complexity, all existing de novo assemblers tend to corrupt whenever the genes contain a large number of alternative splicing events.

SUBMITTER: Chang Z

PROVIDER: S-EPMC3988101 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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The impacts of read length and transcriptome complexity for de novo assembly: a simulation study.

Chang Zheng Z Wang Zhenjia Z Li Guojun G

PloS one 20140415 4

Transcriptome assembly using RNA-seq data - particularly in non-model organisms has been dramatically improved, but only recently have the pre-assembly procedures, such as sequencing depth and error correction, been studied. Increasing read length is viewed as a crucial condition to further improve transcriptome assembly, but it is unknown whether the read length really matters. In addition, though many assembly tools are available now, it is unclear whether the existing assemblers perform well ...[more]

PMID: 24736633

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Project description:Efficiently obtaining full-length cDNA for a target gene is the key step for functional studies and probing genetic variations. However, almost all sequenced domestic animal genomes are not 'finished'. Many functionally important genes are located in these gapped regions. It can be difficult to obtain full-length cDNA for which only partial amino acid/EST sequences exist. In this study we report a general pipeline to obtain full-length cDNA, and illustrate this approach for one important gene (Ovocleidin-17, OC-17) that is associated with chicken eggshell biomineralization. Chicken OC-17 is one of the best candidates to control and regulate the deposition of calcium carbonate in the calcified eggshell layer. OC-17 protein has been purified, sequenced, and has had its three-dimensional structure solved. However, researchers still cannot conduct OC-17 mRNA related studies because the mRNA sequence is unknown and the gene is absent from the current chicken genome. We used RNA-Seq to obtain the entire transcriptome of the adult hen uterus, and then conducted de novo transcriptome assembling with bioinformatics analysis to obtain candidate OC-17 transcripts. Based on this sequence, we used RACE and PCR cloning methods to successfully obtain the full-length OC-17 cDNA. Temporal and spatial OC-17 mRNA expression analyses were also performed to demonstrate that OC-17 is predominantly expressed in the adult hen uterus during the laying cycle and barely at immature developmental stages. Differential uterine expression of OC-17 was observed in hens laying eggs with weak versus strong eggshell, confirming its important role in the regulation of eggshell mineralization and providing a new tool for genetic selection for eggshell quality parameters. This study is the first one to report the full-length OC-17 cDNA sequence, and builds a foundation for OC-17 mRNA related studies. We provide a general method for biologists experiencing difficulty in obtaining candidate gene full-length cDNA sequences.

Dataset Information

The impacts of read length and transcriptome complexity for de novo assembly: a simulation study.

Publications

The impacts of read length and transcriptome complexity for de novo assembly: a simulation study.

Similar Datasets

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