A systems genomics and genetics approach to identify the genetic regulatory network for lignin content in Brassica napus seeds

TL;DR

This study uses systems genetics to uncover the genetic network controlling lignin content in oilseed rape seeds, identifying key genes and modules that could help improve seed quality.

Contribution

The study introduces a systems genetics approach to identify causal regulatory networks and genes for lignin content in Brassica napus seeds.

Findings

Four QTLs were identified for lignin content on two chromosomes in B. napus.

Three gene modules with 910 genes were found to be associated with lignin content.

Four cis-eQTL genes, including CCR1 and TRANSPARENT TESTA genes, were identified as causal genes.

Abstract

Seed quality traits of oilseed rape, Brassica napus (B. napus), exhibit quantitative inheritance determined by its genetic makeup and the environment via the mediation of a complex genetic architecture of hundreds to thousands of genes. Thus, instead of single gene analysis, network-based systems genomics and genetics approaches that combine genotype, phenotype, and molecular phenotypes offer a promising alternative to uncover this complex genetic architecture. In the current study, systems genetics approaches were used to explore the genetic regulation of lignin traits in B. napus seeds. Four QTL (qLignin_A09_1, qLignin_A09_2, qLignin_A09_3, and qLignin_C08) distributed on two chromosomes were identified for lignin content. The qLignin_A09_2 and qLignin_C08 loci were homologous QTL from the A and C subgenomes, respectively. Genome-wide gene regulatory network analysis identified eighty-three subnetworks (or modules); and three modules with 910 genes in total, were associated with lignin content, which was confirmed by network QTL analysis. eQTL (expression quantitative trait loci) analysis revealed four cis-eQTL genes including lignin and flavonoid pathway genes, cinnamoyl-CoA-reductase (CCR1), and TRANSPARENT TESTA genes TT4, TT6, TT8, as causal genes. The findings validated the power of systems genetics to identify causal regulatory networks and genes underlying complex traits. Moreover, this information may enable the research community to explore new breeding strategies, such as network selection or gene engineering, to rewire networks to develop climate resilience crops with better seed quality.

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