Optimizing RNA-seq studies to investigate herbicide resistance

Darci A. Giacomini, Todd Gaines, Roland Beffa, Patrick J Tranel

Research output: Contribution to journalReview article

Abstract

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.

Original languageEnglish (US)
Pages (from-to)2260-2264
Number of pages5
JournalPest Management Science
Volume74
Issue number10
DOIs
StatePublished - Oct 2018

Fingerprint

herbicide resistance
sequence analysis
herbicides
weed science
biotypes
transcriptomics
genetic background
stress response
genes
sampling
organisms
methodology

Keywords

  • NTSR
  • RNA-seq
  • herbicide resistance
  • pooling
  • replicates
  • transcriptomics

ASJC Scopus subject areas

  • Agronomy and Crop Science
  • Insect Science

Cite this

Optimizing RNA-seq studies to investigate herbicide resistance. / Giacomini, Darci A.; Gaines, Todd; Beffa, Roland; Tranel, Patrick J.

In: Pest Management Science, Vol. 74, No. 10, 10.2018, p. 2260-2264.

Research output: Contribution to journalReview article

Giacomini, Darci A. ; Gaines, Todd ; Beffa, Roland ; Tranel, Patrick J. / Optimizing RNA-seq studies to investigate herbicide resistance. In: Pest Management Science. 2018 ; Vol. 74, No. 10. pp. 2260-2264.
@article{ccc5e1c8629642a7af14f828cf8632b5,
title = "Optimizing RNA-seq studies to investigate herbicide resistance",
abstract = "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.",
keywords = "NTSR, RNA-seq, herbicide resistance, pooling, replicates, transcriptomics",
author = "Giacomini, {Darci A.} and Todd Gaines and Roland Beffa and Tranel, {Patrick J}",
year = "2018",
month = "10",
doi = "10.1002/ps.4822",
language = "English (US)",
volume = "74",
pages = "2260--2264",
journal = "Pest Management Science",
issn = "1526-498X",
publisher = "John Wiley and Sons Ltd",
number = "10",

}

TY - JOUR

T1 - Optimizing RNA-seq studies to investigate herbicide resistance

AU - Giacomini, Darci A.

AU - Gaines, Todd

AU - Beffa, Roland

AU - Tranel, Patrick J

PY - 2018/10

Y1 - 2018/10

N2 - 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.

AB - 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.

KW - NTSR

KW - RNA-seq

KW - herbicide resistance

KW - pooling

KW - replicates

KW - transcriptomics

UR - http://www.scopus.com/inward/record.url?scp=85052927310&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85052927310&partnerID=8YFLogxK

U2 - 10.1002/ps.4822

DO - 10.1002/ps.4822

M3 - Review article

C2 - 29222921

AN - SCOPUS:85052927310

VL - 74

SP - 2260

EP - 2264

JO - Pest Management Science

JF - Pest Management Science

SN - 1526-498X

IS - 10

ER -