Dataset Information

Effects of short read quality and quantity on a de novo vertebrate transcriptome assembly.

ABSTRACT: For many researchers, next generation sequencing data holds the key to answering a category of questions previously unassailable. One of the important and challenging steps in achieving these goals is accurately assembling the massive quantity of short sequencing reads into full nucleic acid sequences. For research groups working with non-model or wild systems, short read assembly can pose a significant challenge due to the lack of pre-existing EST or genome reference libraries. While many publications describe the overall process of sequencing and assembly, few address the topic of how many and what types of reads are best for assembly. The goal of this project was use real world data to explore the effects of read quantity and short read quality scores on the resulting de novo assemblies. Using several samples of short reads of various sizes and qualities we produced many assemblies in an automated manner. We observe how the properties of read length, read quality, and read quantity affect the resulting assemblies and provide some general recommendations based on our real-world data set.

SUBMITTER: Garcia TI

PROVIDER: S-EPMC3223268 | biostudies-literature | 2012 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Effects of short read quality and quantity on a de novo vertebrate transcriptome assembly.

Garcia T I TI Shen Y Y Catchen J J Amores A A Schartl M M Postlethwait J J Walter R B RB

Comparative biochemistry and physiology. Toxicology & pharmacology : CBP 20110601 1

For many researchers, next generation sequencing data holds the key to answering a category of questions previously unassailable. One of the important and challenging steps in achieving these goals is accurately assembling the massive quantity of short sequencing reads into full nucleic acid sequences. For research groups working with non-model or wild systems, short read assembly can pose a significant challenge due to the lack of pre-existing EST or genome reference libraries. While many publi ...[more]

PMID: 21651990

Similar Datasets

Project description:BACKGROUND: RNA-seq has shown huge potential for phylogenomic inferences in non-model organisms. However, error, incompleteness, and redundant assembled transcripts for each gene in de novo assembly of short reads cause noise in analyses and a large amount of missing data in the aligned matrix. To address these problems, we compare de novo assemblies of paired end 90 bp RNA-seq reads using Oases, Trinity, Trans-ABySS and SOAPdenovo-Trans to transcripts from genome annotation of the model plant Ricinus communis. By doing so we evaluate strategies for optimizing total gene coverage and minimizing assembly chimeras and redundancy. RESULTS: We found that the frequency and structure of chimeras vary dramatically among different software packages. The differences were largely due to the number of trans-self chimeras that contain repeats in the opposite direction. More than half of the total chimeras in Oases and Trinity were trans-self chimeras. Within each package, we found a trade-off between maximizing reference coverage and minimizing redundancy and chimera rate. In order to reduce redundancy, we investigated three methods: 1) using cap3 and CD-HIT-EST to combine highly similar transcripts, 2) only retaining the transcript with the highest read coverage, or removing the transcript with the lowest read coverage for each subcomponent in Trinity, and 3) filtering Oases single k-mer assemblies by number of transcripts per locus and relative transcript length, and then finding the transcript with the highest read coverage. We then utilized results from blastx against model protein sequences to effectively remove trans chimeras. After optimization, seven assembly strategies among all four packages successfully assembled 42.9-47.1% of reference genes to more than 200 bp, with a chimera rate of 0.92-2.21%, and on average 1.8-3.1 transcripts per reference gene assembled. CONCLUSIONS: With rapidly improving sequencing and assembly tools, our study provides a framework to benchmark and optimize performance before choosing tools or parameter combinations for analyzing short-read RNA-seq data. Our study demonstrates that choice of assembly package, k-mer sizes, post-assembly redundancy-reduction and chimera cleanup, and strand-specific RNA-seq library preparation and assembly dramatically improves gene coverage by non-redundant and non-chimeric transcripts that are optimized for downstream phylogenomic analyses.

Dataset Information

Effects of short read quality and quantity on a de novo vertebrate transcriptome assembly.

Publications

Effects of short read quality and quantity on a de novo vertebrate transcriptome assembly.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets