AraGWAB

Network-based boosting of genome-wide association studies in Arabidopsis thaliana

Tak Lee, In suk Lee

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Genome-wide association studies (GWAS) have been applied for the genetic dissection of complex phenotypes in Arabidopsis thaliana. However, the significantly associated single-nucleotide polymorphisms (SNPs) could not explain all the phenotypic variations. A major reason for missing true phenotype-associated loci is the strict P-value threshold after adjustment for multiple hypothesis tests to reduce false positives. This statistical limitation can be partly overcome by increasing the sample size, but at a much higher cost. Alternatively, weak phenotype-association signals can be boosted by integrating other types of data. Here, we present a web application for network-based Ara bidopsis genome-wide association boosting - araGWAB - which augments the likelihood of association with the given phenotype by integrating GWAS summary statistics (SNP P-values) and co-functional gene network information. The integration utilized the inherent values of SNPs with subthreshold significance, thus substantially increasing the information usage of GWAS data. We found that araGWAB could more effectively retrieve genes known to be associated with various phenotypes relevant to defense against bacterial pathogens, flowering time regulation, and organ development in A. thaliana. We also found that many of the network-boosted candidate genes for the phenotypes were supported by previous publications. The araGWAB is freely available at http://www.inetbio.org/aragwab/.

Original languageEnglish
Article number2925
JournalScientific reports
Volume8
Issue number1
DOIs
Publication statusPublished - 2018 Dec 1

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Arabidopsis thaliana
phenotype
single nucleotide polymorphism
phenotypic variation
genome-wide association study
genes
statistics
flowering
loci
genome
pathogens
testing
sampling

All Science Journal Classification (ASJC) codes

  • General

Cite this

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abstract = "Genome-wide association studies (GWAS) have been applied for the genetic dissection of complex phenotypes in Arabidopsis thaliana. However, the significantly associated single-nucleotide polymorphisms (SNPs) could not explain all the phenotypic variations. A major reason for missing true phenotype-associated loci is the strict P-value threshold after adjustment for multiple hypothesis tests to reduce false positives. This statistical limitation can be partly overcome by increasing the sample size, but at a much higher cost. Alternatively, weak phenotype-association signals can be boosted by integrating other types of data. Here, we present a web application for network-based Ara bidopsis genome-wide association boosting - araGWAB - which augments the likelihood of association with the given phenotype by integrating GWAS summary statistics (SNP P-values) and co-functional gene network information. The integration utilized the inherent values of SNPs with subthreshold significance, thus substantially increasing the information usage of GWAS data. We found that araGWAB could more effectively retrieve genes known to be associated with various phenotypes relevant to defense against bacterial pathogens, flowering time regulation, and organ development in A. thaliana. We also found that many of the network-boosted candidate genes for the phenotypes were supported by previous publications. The araGWAB is freely available at http://www.inetbio.org/aragwab/.",
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AraGWAB : Network-based boosting of genome-wide association studies in Arabidopsis thaliana. / Lee, Tak; Lee, In suk.

In: Scientific reports, Vol. 8, No. 1, 2925, 01.12.2018.

Research output: Contribution to journalArticle

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