Identification of nodulation‐related genes in Medicago truncatula using genome‐wide association studies and co‐expression networks

Abstract

Abstract Genome‐wide association studies (GWAS) have proven to be a valuable approach for identifying genetic intervals associated with phenotypic variation in Medicago truncatula. These intervals can vary in size, depending on the historical local recombination. Typically, significant intervals span numerous gene models, limiting the ability to resolve high‐confidence candidate genes underlying the trait of interest. Additional genomic data, including gene co‐expression networks, can be combined with the genetic mapping information to successfully identify candidate genes. Co‐expression network analysis provides information about the functional relationships of each gene through its similarity of expression patterns to other well‐defined clusters of genes. In this study, we integrated data from GWAS and co‐expression networks to pinpoint candidate genes that may be associated with nodule‐related phenotypes in M. truncatula. We further investigated a subset of these genes and confirmed that several had existing evidence linking them nodulation, including MEDTR2G101090 (PEN3‐like), a previously validated gene associated with nodule number.

Keywords

• bioinformatics
• co‐expression
• genome‐wide association studies
• Medicago
• nodulation