Naturally variable regulatory networks control different biological processes including reproduction and defense. This variation within regulatory networks enables plants to optimize defense and reproduction in different environments. In this study we investigate the ability of two enzyme-encoding genes in the glucosinolate pathway, AOP2 and AOP3, to affect glucosinolate accumulation and flowering time. We have introduced the two highly similar enzymes into two different AOPnull accessions, Col-0 and Cph-0, and found that the genes differ in their ability to affect glucosinolate levels and flowering time across the accessions. This indicated that the different glucosinolates produced by AOP2 and AOP3 serve specific regulatory roles in controlling these phenotypes. While the changes in glucosinolate levels were similar in both accessions, the effect on flowering time was dependent on the genetic background pointing to natural variation in cross-talk between defense chemistry and onset of flowering. This variation likely reflects an adaptation to survival in different environments.
Identification of enzymes, regulators and transporters involved in different metabolic processes is the foundation to understand how organisms function. There are, however, many difficulties in identifying candidate genes as well as in proving their in vivo roles. In this review, we describe different approaches utilized in Arabidopsis thaliana to identify gene candidates and experiments required to prove the function of a given candidate. For example, we use the production of methionine-derived aliphatic glucosinolates that represent major defence compounds in A. thaliana. Nearly all biosynthetic genes, as well as the first sets of regulators and transporters, have been identified. An array of approaches, i.e. classical mapping, quantitative trait loci (QTL) mapping, eQTL mapping, co-expression, genome wide association studies (GWAS), mutant screens and phylogenetic analyses, has been exploited to increase the number of identified genes. Here we summarize the lessons learned from the different approaches used over the years with the aim to help designing and combining new approaches in the future.
Quantitative trait loci (QTL) mapping studies enable identification of loci that are part of regulatory networks controlling various phenotypes. Detailed investigations of genes within these loci are required to ultimately understand the function of individual genes and how they interact with other players in the network. In this study, we use transgenic plants in combination with natural variation to investigate the regulatory role of the AOP3 gene found in GS-AOP locus previously suggested to contribute to the regulation of glucosinolate defense compounds. Phenotypic analysis and QTL mapping in F2 populations with different AOP3 transgenes support that the enzymatic function and the AOP3 RNA both play a significant role in controlling glucosinolate accumulation. Furthermore, we find different loci interacting with either the enzymatic activity or the RNA of AOP3 and thereby extend the regulatory network controlling glucosinolate accumulation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.