Dataset Information

Common workflow language (CWL)-based software pipeline for de novo genome assembly from long- and short-read data.

ABSTRACT: BACKGROUND:Here, we created an automated pipeline for the de novoassembly of genomes from Pacific Biosciences long-read and Illumina short-read data using common workflow language (CWL). To evaluate the performance of this pipeline, we assembled the nuclear genomes of the eukaryotes Caenorhabditis elegans (?100 Mb), Drosophila melanogaster (?138 Mb), and Plasmodium falciparum (?23 Mb) directly from publicly accessible nucleotide sequence datasets and assessed the quality of the assemblies against curated reference genomes. FINDINGS:We showed a dependency of the accuracy of assembly on sequencing technology and GC content and repeatedly achieved assemblies that meet the high standards set by the National Human Genome Research Institute, being applicable to gene prediction and subsequent genomic analyses. CONCLUSIONS:This CWL pipeline overcomes current challenges of achieving repeatability and reproducibility of assembly results and offers a platform for the re-use of the workflow and the integration of diverse datasets. This workflow is publicly available via GitHub (https://github.com/vetscience/Assemblosis) and is currently applicable to the assembly of haploid and diploid genomes of eukaryotes.

SUBMITTER: Korhonen PK

PROVIDER: S-EPMC6451199 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Common workflow language (CWL)-based software pipeline for de novo genome assembly from long- and short-read data.

Korhonen Pasi K PK Hall Ross S RS Young Neil D ND Gasser Robin B RB

GigaScience 20190401 4

<h4>Background</h4>Here, we created an automated pipeline for the de novoassembly of genomes from Pacific Biosciences long-read and Illumina short-read data using common workflow language (CWL). To evaluate the performance of this pipeline, we assembled the nuclear genomes of the eukaryotes Caenorhabditis elegans (∼100 Mb), Drosophila melanogaster (∼138 Mb), and Plasmodium falciparum (∼23 Mb) directly from publicly accessible nucleotide sequence datasets and assessed the quality of the assemblie ...[more]

PMID: 30821816

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

Common workflow language (CWL)-based software pipeline for de novo genome assembly from long- and short-read data.

Publications

Common workflow language (CWL)-based software pipeline for de novo genome assembly from long- and short-read data.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets