Abstract

Integration analysis of multi-omics data provides a comprehensive landscape for understanding biological systems and mechanisms. The abundance of high-quality multi-omics data (genomics, transcriptomics, methylomics and phenomics) for the model organism Arabidopsis thaliana enables scientists to study the genetic mechanism of many biological processes. However, no resource is available to provide comprehensive and systematic multi-omics associations for Arabidopsis. Here, we developed an Arabidopsis thaliana Multi-omics Association Database (AtMAD, http://www.megabionet.org/atmad), a public repository for large-scale measurements of associations between genome, transcriptome, methylome, pathway and phenotype in Arabidopsis, designed for facilitating identification of eQTL, emQTL, Pathway-mQTL, Phenotype-pathway, GWAS, TWAS and EWAS. Candidate variants/methylations/genes were identified in AtMAD for specific phenotypes or biological processes, many of them are supported by experimental evidence. Based on the multi-omics association strategy, we have identified 11 796 cis-eQTLs and 10 119 trans-eQTLs. Among them, 68 837 environment-eQTL associations and 149 622 GWAS-eQTL associations were identified and stored in AtMAD. For expression–methylation quantitative trait loci (emQTL), we identified 265 776 emQTLs and 122 344 pathway-mQTLs. For TWAS and EWAS, we obtained 62 754 significant phenotype-gene associations and 3 993 379 significant phenotype-methylation associations, respectively. Overall, the multi-omics associated network in AtMAD will provide new insights into exploring biological mechanisms of plants at multi-omics levels.

中文翻译：

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AtMAD：拟南芥多组学协会数据库

摘要

多组学数据的集成分析为理解生物学系统和机制提供了一个全面的前景。模式生物拟南芥的大量高质量多组学数据（基因组学，转录组学，甲基组学和表型学）使科学家能够研究许多生物过程的遗传机制。但是，没有资源可用于为拟南芥提供全面而系统的多组学协会。在这里，我们开发了拟南芥多组学协会数据库（AtMAD，http：//www.megabionet.org/atmad），用于对拟南芥中的基因组，转录组，甲基化组，途径和表型之间的关联进行大规模测量的公共存储库，旨在促进eQTL的鉴定，emQTL，Pathway-mQTL，表型-途径，GWAS，TWAS和EWAS。在AtMAD中针对特定表型或生物学过程鉴定了候选变体/甲基化/基因，其中许多都得到了实验证据的支持。基于多组学关联策略，我们确定了11 796个顺式-eQTL和10 119个反式-eQTL。其中，已识别出68 837个环境-eQTL关联和149 622个GWAS-eQTL关联并将其存储在AtMAD中。对于表达甲基化定量性状基因座（emQTL），我们鉴定了265 776个emQTL和122 344个途径mQTL。对于TWAS和EWAS，我们分别获得了62 754个显着的表型-基因关联和3 993 379个显着的表型-甲基化关联。总体而言，AtMAD中的多组学关联网络将为探索多组学水平的植物生物学机制提供新的见解。