On the discovery of genes involved in metabolism-based resistance to herbicides using RNA-Seq transcriptome analysis in Lolium rigidum

Weed control failures due to herbicide resistance are an increasing and worldwide problem significantly impacting crop yields. Herbicide resistance due to increased herbicide metabolism in weeds is not well characterized at the genetic level. An RNA-Seq transcriptome analysis was used to identify genes conferring metabolism-based herbicide resistance (MBHR) in a population (R) of a major global weed (Lolium rigidum), in which resistance to the herbicide diclofop-methyl was experimentally evolved through recurrent selection from a susceptible (S) progenitor population. A reference transcriptome of 19,623 contigs was assembled using 454 sequencing technology on a cDNA library and annotated using UniProt and Pfam databases. Transcriptomic-level gene expression was measured using Illumina 100 bp reads from untreated control, mock, and diclofop-methyl treatments of R and S. Due to the established importance of cytochrome P450 (CytP450), glutathione-S-transferase (GST), and glucosyltransferase (GT) genes in MBHR, 11 contigs with these annotations and higher constitutive expression in untreated R than in untreated S were selected as candidate genes for hypothesis testing, along with 17 additional differentially expressed contigs with annotations related to metabolism or signal transduction. In a forward genetics validation experiment, higher constitutive expression of nine contigs co-segregated with the resistance phenotype in an F2 population, including 3 CytP450, 3 GST, and 1 GT. At least nine genes with heritable increased constitutive expression are associated with MBHR trait. In a physiological validation experiment where 2, 4-D pre-treatment induced diclofop-methyl protection in S individuals due to increased metabolism, seven of the nine genetically-validated contigs were significantly induced. These data help explain accumulation of resistance-endowing genes and rapid evolution of MBHR, and provide the opportunity to improve diagnostics of MBHR using molecular tools such as transcriptional markers.