Integration of new alternative reference strain genome sequences into the<i>Saccharomyces</i>genome database

Song, Giltae; Balakrishnan, Rama; Binkley, Gail; Costanzo, Maria C.; Dalusag, Kyla S.; Demeter, János; Engel, Stacia R.; Hellerstedt, Sage T.; Karra, Kalpana; Hitz, Benjamin; Nash, Robert S.; Paskov, Kelley; Sheppard, Travis K; Skrzypek, Marek S.; Weng, Shuai; Wong, Edith D.; Cherry, J. Michael

doi:10.1093/database/baw074

Cited by 13 publications

(11 citation statements)

References 33 publications

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“…This is because S. cerevisiae can be easily grown, easily manipulated and many of its genes, proteins, cellular structures and signaling pathways resemble those found in the cells of higher eukaryotes. Hundreds of S. cerevisiae strains are known, of which more than 50 have been fully sequenced (1). The most commonly studied isolate of S. cerevisiae is S288C, a lab derived strain (2).…”

Section: Introductionmentioning

confidence: 99%

YMDB 2.0: a significantly expanded version of the yeast metabolome database

et al. 2016

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YMDB or the Yeast Metabolome Database (http://www.ymdb.ca/) is a comprehensive database containing extensive information on the genome and metabolome of Saccharomyces cerevisiae. Initially released in 2012, the YMDB has gone through a significant expansion and a number of improvements over the past 4 years. This manuscript describes the most recent version of YMDB (YMDB 2.0). More specifically, it provides an updated description of the database that was previously described in the 2012 NAR Database Issue and it details many of the additions and improvements made to the YMDB over that time. Some of the most important changes include a 7-fold increase in the number of compounds in the database (from 2007 to 16 042), a 430-fold increase in the number of metabolic and signaling pathway diagrams (from 66 to 28 734), a 16-fold increase in the number of compounds linked to pathways (from 742 to 12 733), a 17-fold increase in the numbers of compounds with nuclear magnetic resonance or MS spectra (from 783 to 13 173) and an increase in both the number of data fields and the number of links to external databases. In addition to these database expansions, a number of improvements to YMDB's web interface and its data visualization tools have been made. These additions and improvements should greatly improve the ease, the speed and the quantity of data that can be extracted, searched or viewed within YMDB. Overall, we believe these improvements should not only improve the understanding of the metabolism of S. cerevisiae, but also allow more in-depth exploration of its extensive metabolic networks, signaling pathways and biochemistry.

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Section: Introductionmentioning

confidence: 99%

YMDB 2.0: a significantly expanded version of the yeast metabolome database

et al. 2016

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“…We applied IMAP to the S . cerevisiae strain W303, one of the most commonly used strains in yeast studies [33]. We relied on W303 short-read sequence data from an experimental evolution study [4] that is available at NCBI SRA with Bioproject ID PRJNA205542.…”

Section: Resultsmentioning

confidence: 99%

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

et al. 2019

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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.

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“…The remainder of the boundary differences appear valid upon viewing the sequence; we know that some start and stop codons differ between strains (e.g. AQY1 /YPR192W as described in Song et al , ( 15 )). As further experimental data become available, we will refine these annotations appropriately.…”

Section: Methodsmentioning

confidence: 99%

From one to many: expanding theSaccharomyces cerevisiaereference genome panel

et al. 2016

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In recent years, thousands of Saccharomyces cerevisiae genomes have been sequenced to varying degrees of completion. The Saccharomyces Genome Database (SGD) has long been the keeper of the original eukaryotic reference genome sequence, which was derived primarily from S. cerevisiae strain S288C. Because new technologies are pushing S. cerevisiae annotation past the limits of any system based exclusively on a single reference sequence, SGD is actively working to expand the original S. cerevisiae systematic reference sequence from a single genome to a multi-genome reference panel. We first commissioned the sequencing of additional genomes and their automated analysis using the AGAPE pipeline. Here we describe our curation strategy to produce manually reviewed high-quality genome annotations in order to elevate 11 of these additional genomes to Reference status.Database URL: http://www.yeastgenome.org/

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Integration of new alternative reference strain genome sequences into theSaccharomycesgenome database

Cited by 13 publications

References 33 publications

YMDB 2.0: a significantly expanded version of the yeast metabolome database

YMDB 2.0: a significantly expanded version of the yeast metabolome database

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

From one to many: expanding theSaccharomyces cerevisiaereference genome panel

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