Preliminary investigation of glyphosate resistance mechanism in giant ragweed using transcriptome analysis

Introduction

Giant ragweed (Ambrosia trifida) is a problematic annual weed in the United States and Canada, particularly in fields where corn and soybean are grown^1,2. Due to the extensive use of weed control measures such as the growth of genetically-modified glyphosate-resistant crops, giant ragweed populations have been kept in check³. But due to the overuse of glyphosate and strong selective pressure, resistant weeds have been reported across the world (http://www.weedscience.org)^4,5. The mechanism of resistance to glyphosate in other common weeds such as Malaysian goosegrass, Italian ryegrass, and rigid ryegrass have been identified^6–8. However, the glyphosate resistance mechanism in giant ragweed is still unknown. In this study, we compare gene expression differences between the glyphosate resistant and sensitive giant ragweed plants using a time course experiment and identify genes that could be involved in glyphosate resistance.

Methods

Glyphosate-resistant and glyphosate-sensitive seeds of giant ragweed were collected from Noble County, Indiana (N41° 28.470 W85° 29.371) and Darke County, Ohio (N40° 15.9 W84° 42.7) respectively. After seed germination, plants at the five-node growth stage were selected for herbicide treatment. mRNA was extracted from leaf disks following a protocol adapted from Eggermont et al. 2 cm diameter leaf disks from the first fully developed leaf were punched out, frozen in liquid nitrogen, and total RNA was extracted in a 2 ml test tube. mRNA was sequenced using Illumina TruSeq for four time points – pre-treatment (0 hour), 3 hours, 8 hours and 12 hours after treatment with glyphosate at a rate of 0.7kg ae ha^-1 (recommended field rate) sprayed using a compressed-air bench top track sprayer with a nozzle pressure of 249 kPa delivering a volume of 187 L of spray solution ha^-19. RNA sequences were assembled using the Trinity package (version r2012-10-05) from paired-end reads¹⁰.

RNA-seq reads were mapped to the transcriptome assembly, and the counts per million transcripts (CPM) value was determined using RSEM (version 1.2.8)¹¹. Since we observed clear systemic changes in gene expression even at the first time point, we used a set of genes previously published in rice analyses as controls to normalize the expression values¹². The consistent expression of these genes with respect to each other across the time course was verified (Table 1). Gene level counts that were less than 1 CPM in all time points were excluded from further analysis. Expression ratios were then calculated for each assembly, comparing the expression levels in the glyphosate resistant and sensitive strains at each time point. Numbers larger than 1 therefore reflect genes (transcript assemblies) with higher expression in the resistant variety. Sampling variation was controlled by the addition of a pseudo count of 0.5 CPM before calculating expression ratios. Assemblies with expression ratios greater than 4, or less than -4 were considered to be differentially expressed and were further examined. Annotations of the transcriptome were done using Trinotate (version r2013-02-25)¹³.

Results

There is a clear difference in gene expression patterns between the resistant and sensitive plants even before plants were treated with herbicide (Table 2). The top differentially expressed transcripts in resistant and sensitive plants before treatment are shown in Table 3 and Table 4. The response to glyphosate is rapid, and a large number of genes are significantly differentially expressed within the first three hours after treatment compared to pre-treatment expression levels (Table 5).

The genes with at least a four-fold change in expression level were identified in resistant and sensitive plants, and pathways associated with significantly over-represented genes identified using agriGO (cutoff P < 1e-7)^14,15. Pathways with terms such as “response to other organisms” and “lipid biosynthetic process”, both of which are known to be related to pathogen response, were the most significantly over-represented¹⁶. Contrastingly, pathways that are typically over-represented in the sensitive biotype are annotated with terms like “response to stress”, “response to oxidative stimulus” and “lignin biosynthesis”, which are known stress response indicators¹⁷. This leads us to speculate that, not only do resistant giant ragweed plants react to glyphosate treatment in a manner resembling pathogen defense reactions, but they are already primed by alterations in stress response processes to hyper-react. This is consistent with the rapid necrosis reaction observed in resistant giant ragweed biotypes used in this study.

Conclusion

The complete transcriptome assembly of giant ragweed has been deposited in the NCBI BioProject database (http://www.ncbi.nlm.nih.gov/bioproject/) and is publicly available under accession PRJNA267208. The preliminary time-course experiment presented here identified groups of genes that may explain glyphosate resistance in giant ragweed. A more extensive transcriptome analysis study, with multiple replicates of sensitive and resistant giant ragweed biotypes, from a broader range of geographic sources, and with shorter time intervals will be useful to overcome the limitations of this preliminary study.

Data availability

The transcriptome assembly is available in the NCBI BioProject database under accession PRJNA267208.

F1000Research: Dataset 1. Raw data of glyphosate resistance mechanism in giant ragweed using transcriptome analysis, 10.5256/f1000research.8932.d125530¹⁸