Evidence map›Paper›PMID 25781462›Full record

ArticlePloS one2015

AGAPE (Automated Genome Analysis PipelinE) for pan-genome analysis of Saccharomyces cerevisiae.

Giltae Song, Benjamin J A Dickins, Janos Demeter, Stacia Engel, Jennifer Gallagher, Kisurb Choe, Barbara Dunn, Michael Snyder, J Michael Cherry

Erratum issuedAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

40 citing papers in PubMed.

  1. Article
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  4. Isolation and characterization of haploid heterothallic beer yeasts.Applied microbiology and biotechnology · 2025
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  5. Article
  6. Article
  7. Article
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  10. Polymorphism ofInternational journal of molecular sciences · 2023
    Article
  11. Article
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  13. Article
  14. Article
  15. Article
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  18. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Giltae SongDepartment of Genetics, Stanford University School of Medicine, Stanford, California, United States of America.
Benjamin J A DickinsSchool of Science and Technology, Nottingham Trent University, Nottingham, United Kingdom.
Janos DemeterDepartment of Genetics, Stanford University School of Medicine, Stanford, California, United States of America.
Stacia EngelDepartment of Genetics, Stanford University School of Medicine, Stanford, California, United States of America.
Jennifer Gallagher
Kisurb Choe
Barbara DunnDepartment of Genetics, Stanford University School of Medicine, Stanford, California, United States of America.
Michael Snyder
J Michael CherryDepartment of Genetics, Stanford University School of Medicine, Stanford, California, United States of America.

Funding

GENOMIC DATABASE FOR THE YEAST SACCHAROMYCESP41HG001315 · NHGRI · STANFORD UNIVERSITY · PI CHERRY, J. MICHAEL · 1995 to 2010
$27.1M
Genomic Resource for the Yeast SaccharomycesU41HG001315 · NHGRI · STANFORD UNIVERSITY · PI CHERRY, J. MICHAEL · 2011 to 2020
$26.4M
Genomic Resource for the Yeast SaccharomycesU24HG001315 · NHGRI · STANFORD UNIVERSITY · PI Stacia Engel, Gavin J Sherlock · 2021 to 2026
$10.9M
NHGRI NIH HHS P41 HG001315NHGRI NIH HHS U24 HG001315NHGRI NIH HHS U41 HG001315
6 · The paper itself

Abstract

The characterization and public release of genome sequences from thousands of organisms is expanding the scope for genetic variation studies. However, understanding the phenotypic consequences of genetic variation remains a challenge in eukaryotes due to the complexity of the genotype-phenotype map. One approach to this is the intensive study of model systems for which diverse sources of information can be accumulated and integrated. Saccharomyces cerevisiae is an extensively studied model organism, with well-known protein functions and thoroughly curated phenotype data. To develop and expand the available resources linking genomic variation with function in yeast, we aim to model the pan-genome of S. cerevisiae. To initiate the yeast pan-genome, we newly sequenced or re-sequenced the genomes of 25 strains that are commonly used in the yeast research community using advanced sequencing technology at high quality. We also developed a pipeline for automated pan-genome analysis, which integrates the steps of assembly, annotation, and variation calling. To assign strain-specific functional annotations, we identified genes that were not present in the reference genome. We classified these according to their presence or absence across strains and characterized each group of genes with known functional and phenotypic features. The functional roles of novel genes not found in the reference genome and associated with strains or groups of strains appear to be consistent with anticipated adaptations in specific lineages. As more S. cerevisiae strain genomes are released, our analysis can be used to collate genome data and relate it to lineage-specific patterns of genome evolution. Our new tool set will enhance our understanding of genomic and functional evolution in S. cerevisiae, and will be available to the yeast genetics and molecular biology community.

Indexed as

Genome, FungalSoftwareContig MappingSaccharomyces cerevisiaeSequence Analysis, DNA

Identifiers

PMID25781462
PMCPMC4363492

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.