Optimizing RNA‐seq studies to investigate herbicide resistance

Transcriptomic profiling, specifically via RNA sequencing (RNA‐seq), is becoming one of the more commonly used methods for investigating non‐target site resistance (NTSR) to herbicides due to its high throughput capabilities and utility in organisms with little to no previous sequence information. A review of the weed science RNA‐seq literature revealed some basic principles behind generating quality data from these types of studies. First, studies that included more replicates per biotype and took steps to control for genetic background had significantly better control of false positives and, consequently, shorter lists of potential resistance genes to sift through. Pooling of biological replicates prior to sequencing was successful in some cases, but likely contributed to an overall increase in the false discovery rate. Although the inclusion of herbicide‐treated samples was common across most of the studies, it ultimately introduced difficulties in interpretation of the final results due to challenges in capturing the right sampling window after treatment and to the induction of stress responses in the injured herbicide‐sensitive plants. RNA‐seq is an effective tool for NTSR gene discovery, but careful consideration should be given to finding the most powerful and cost‐effective balance between replicate number, sequencing depth and treatment number. © 2017 Society of Chemical Industry As RNA‐seq becomes a more prevalent tool for herbicide resistance research, lessons learned from previous studies can help researchers to generate high‐quality data through better experimental design.