Location: Crop Improvement and Genetics ResearchTitle: Co-expression pan-network reveals genes involved in complex traits within maize pan-genome
Submitted to: BMC Plant Biology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/7/2022
Publication Date: 12/19/2022
Citation: Cagirici, B.H., Andorf, C.M., Sen, T.Z. 2022. Co-expression pan-network reveals genes involved in complex traits within maize pan-genome. BMC Plant Biology. 22. Article 595. https://doi.org/10.1186/s12870-022-03985-z.
Interpretive Summary: As one of the first of pan-genome gene co-expression studies, our work unravels the effects of regulatory networks on important phenotypic traits that are of high agronomic and biological importance in maize. Complex traits in maize are regulated by a set of variations with minor effects, making the identification of the causal variations and regulatory networks challenging. Genes exhibiting coordinated expression across different samples are likely to be biologically co-regulated. Thus, co-expression networks have the potential to infer the regulatory network of genes. We report co-expressed gene-pairs at the pan-genome level and show case studies with Tassel Branch Number and Starch to better understand the gene regulatory mechanisms at the pan-genome level.
Technical Abstract: With the advances in the high throughput next generation sequencing technologies, genome-wide association studies (GWAS) have identified a large set of variants associated with complex phenotypic traits at a very fine scale. Despite the progress in GWAS, identification of genotype-phenotype relationship remains challenging in maize due to its nature with dozens of variants controlling the same trait. To address these challenges, we incorporated the gene expression and GWAS-driven traits to extend the knowledge of genotype-phenotype relationships and transcriptional regulatory mechanisms behind the phenotypes. Gene co-expression networks are often used to extract meaningful information about groups of co-regulated genes that play a central role in regulatory processes. We constructed a large collection of gene co-expression networks to find gene associations underlying complex traits in the maize pan-genome. We identified more than 2 million co-expressing gene pairs in the GWAS-driven pan-network where more than half belong to individual genomes of the nested association mapping (NAM) population. Strikingly, the private-network contained almost all the genes in the pan-network but lacked half of the interactions. The core-network, on the other hand, captured only ~1% of the interactions in the pan-network. We performed gene ontology (GO) enrichment analysis for the pan-, core-, and private- networks and compared the contributions of variants overlapping with genes and promoters to the GWAS-driven pan-network. Pan-network approach enabled us to visualize the global view of the gene regulatory network for the studied system that could not be well inferred by the core-network alone.