Lee Tak, Lee Insuk
Department of Biotechnology, College of Life Sciences and Biotechnology, Yonsei University, Seoul, 03722, Korea.
Sci Rep. 2018 Feb 13;8(1):2925. doi: 10.1038/s41598-018-21301-4.
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 Arabidopsis 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/ .
全基因组关联研究（GWAS）已被应用于拟南芥复杂表型的遗传剖析。然而，显著相关的单核苷酸多态性（SNP）并不能解释所有的表型变异。遗漏真正与表型相关位点的一个主要原因是在对多重假设检验进行校正后设置了严格的P值阈值，以减少假阳性。这种统计限制可以通过增加样本量来部分克服，但成本要高得多。或者，可以通过整合其他类型的数据来增强弱表型关联信号。在这里，我们展示了一个基于网络的拟南芥全基因组关联增强网络应用程序——araGWAB，它通过整合GWAS汇总统计信息（SNP P值）和共功能基因网络信息，增加了与给定表型关联的可能性。这种整合利用了具有亚阈值显著性的SNP的固有值，从而大大增加了GWAS数据的信息利用率。我们发现araGWAB可以更有效地检索已知与拟南芥中与防御细菌病原体、开花时间调控和器官发育等各种表型相关的基因。我们还发现，许多通过网络增强的表型候选基因得到了先前出版物的支持。araGWAB可在http://www.inetbio.org/aragwab/ 免费获取。
