Dataset Information

Integrative Meta-Assembly Pipeline (IMAP): Chromosome-level genome assembler combining multiple de novo assemblies.

ABSTRACT: BACKGROUND:Genomic data have become major resources to understand complex mechanisms at fine-scale temporal and spatial resolution in functional and evolutionary genetic studies, including human diseases, such as cancers. Recently, a large number of whole genomes of evolving populations of yeast (Saccharomyces cerevisiae W303 strain) were sequenced in a time-dependent manner to identify temporal evolutionary patterns. For this type of study, a chromosome-level sequence assembly of the strain or population at time zero is required to compare with the genomes derived later. However, there is no fully automated computational approach in experimental evolution studies to establish the chromosome-level genome assembly using unique features of sequencing data. METHODS AND RESULTS:In this study, we developed a new software pipeline, the integrative meta-assembly pipeline (IMAP), to build chromosome-level genome sequence assemblies by generating and combining multiple initial assemblies using three de novo assemblers from short-read sequencing data. We significantly improved the continuity and accuracy of the genome assembly using a large collection of sequencing data and hybrid assembly approaches. We validated our pipeline by generating chromosome-level assemblies of yeast strains W303 and SK1, and compared our results with assemblies built using long-read sequencing and various assembly evaluation metrics. We also constructed chromosome-level sequence assemblies of S. cerevisiae strain Sigma1278b, and three commonly used fungal strains: Aspergillus nidulans A713, Neurospora crassa 73, and Thielavia terrestris CBS 492.74, for which long-read sequencing data are not yet available. Finally, we examined the effect of IMAP parameters, such as reference and resolution, on the quality of the final assembly of the yeast strains W303 and SK1. CONCLUSIONS:We developed a cost-effective pipeline to generate chromosome-level sequence assemblies using only short-read sequencing data. Our pipeline combines the strengths of reference-guided and meta-assembly approaches. Our pipeline is available online at http://github.com/jkimlab/IMAP including a Docker image, as well as a Perl script, to help users install the IMAP package, including several prerequisite programs. Users can use IMAP to easily build the chromosome-level assembly for the genome of their interest.

SUBMITTER: Song G

PROVIDER: S-EPMC6711525 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Integrative Meta-Assembly Pipeline (IMAP): Chromosome-level genome assembler combining multiple de novo assemblies.

Song Giltae G Lee Jongin J Kim Juyeon J Kang Seokwoo S Lee Hoyong H Kwon Daehong D Lee Daehwan D Lang Gregory I GI Cherry J Michael JM Kim Jaebum J

PloS one 20190827 8

<h4>Background</h4>Genomic data have become major resources to understand complex mechanisms at fine-scale temporal and spatial resolution in functional and evolutionary genetic studies, including human diseases, such as cancers. Recently, a large number of whole genomes of evolving populations of yeast (Saccharomyces cerevisiae W303 strain) were sequenced in a time-dependent manner to identify temporal evolutionary patterns. For this type of study, a chromosome-level sequence assembly of the st ...[more]

PMID: 31454399

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Project description:Next-generation sequencing (NGS) technologies are arguably the most revolutionary technical development to join the list of tools available to molecular biologists since PCR. For researchers working with nonconventional model organisms one major problem with the currently dominant NGS platform (Illumina) stems from the obligatory fragmentation of nucleic acid material that occurs prior to sequencing during library preparation. This step creates a significant bioinformatic challenge for accurate de novo assembly of novel transcriptome data. This challenge becomes apparent when a variety of modern assembly tools (of which there is no shortage) are applied to the same raw NGS dataset. With the same assembly parameters these tools can generate markedly different assembly outputs.In this study we present an approach that generates an optimized consensus de novo assembly of eukaryotic coding transcriptomes. This approach does not represent a new assembler, rather it combines the outputs of a variety of established assembly packages, and removes redundancy via a series of clustering steps. We test and validate our approach using Illumina datasets from six phylogenetically diverse eukaryotes (three metazoans, two plants and a yeast) and two simulated datasets derived from metazoan reference genome annotations. All of these datasets were assembled using three currently popular assembly packages (CLC, Trinity and IDBA-tran). In addition, we experimentally demonstrate that transcripts unique to one particular assembly package are likely to be bioinformatic artefacts. For all eight datasets our pipeline generates more concise transcriptomes that in fact possess more unique annotatable protein domains than any of the three individual assemblers we employed. Another measure of assembly completeness (using the purpose built BUSCO databases) also confirmed that our approach yields more information.Our approach yields coding transcriptome assemblies that are more likely to be closer to biological reality than any of the three individual assembly packages we investigated. This approach (freely available as a simple perl script) will be of use to researchers working with species for which there is little or no reference data against which the assembly of a transcriptome can be performed.

Dataset Information

Integrative Meta-Assembly Pipeline (IMAP): Chromosome-level genome assembler combining multiple de novo assemblies.

Publications

Integrative Meta-Assembly Pipeline (IMAP): Chromosome-level genome assembler combining multiple de novo assemblies.

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