FastD: Fast detection of insecticide target‐site mutations and overexpressed detoxification genes in insect populations from RNA‐Seq data
Abstract Target‐site mutations and detoxification gene overexpression are two major mechanisms conferring insecticide resistance. Molecular assays applied to detect these resistance genetic markers are time‐consuming and with high false‐positive rates. RNA‐Seq data contains information on the variat...
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doaj-a0e7604618f543cda02b51bbe669f2282021-06-04T07:10:38ZengWileyEcology and Evolution2045-77582020-12-011024143461435810.1002/ece3.7037FastD: Fast detection of insecticide target‐site mutations and overexpressed detoxification genes in insect populations from RNA‐Seq dataLongfei Chen0Kun Lang1Yang Mei2Zhenmin Shi3Kang He4Fei Li5Huamei Xiao6Gongyin Ye7Zhaojun Han8Institute of Insect Sciences College of Agriculture and Biotechnology Zhejiang University Hangzhou ChinaInstitute of Insect Sciences College of Agriculture and Biotechnology Zhejiang University Hangzhou ChinaInstitute of Insect Sciences College of Agriculture and Biotechnology Zhejiang University Hangzhou ChinaInstitute of Insect Sciences College of Agriculture and Biotechnology Zhejiang University Hangzhou ChinaInstitute of Insect Sciences College of Agriculture and Biotechnology Zhejiang University Hangzhou ChinaInstitute of Insect Sciences College of Agriculture and Biotechnology Zhejiang University Hangzhou ChinaInstitute of Insect Sciences College of Agriculture and Biotechnology Zhejiang University Hangzhou ChinaInstitute of Insect Sciences College of Agriculture and Biotechnology Zhejiang University Hangzhou ChinaDepartment of Entomology Nanjing Agricultural University Nanjing ChinaAbstract Target‐site mutations and detoxification gene overexpression are two major mechanisms conferring insecticide resistance. Molecular assays applied to detect these resistance genetic markers are time‐consuming and with high false‐positive rates. RNA‐Seq data contains information on the variations within expressed genomic regions and expression of detoxification genes. However, there is no corresponding method to detect resistance markers at present. Here, we collected 66 reported resistance mutations of four insecticide targets (AChE, VGSC, RyR, and nAChR) from 82 insect species. Next, we obtained 403 sequences of the four target genes and 12,665 sequences of three kinds of detoxification genes including P450s, GSTs, and CCEs. Then, we developed a Perl program, FastD, to detect target‐site mutations and overexpressed detoxification genes from RNA‐Seq data and constructed a web server for FastD (http://www.insect-genome.com/fastd). The estimation of FastD on simulated RNA‐Seq data showed high sensitivity and specificity. We applied FastD to detect resistant markers in 15 populations of six insects, Plutella xylostella, Aphis gossypii, Anopheles arabiensis, Musca domestica, Leptinotarsa decemlineata and Apis mellifera. Results showed that 11 RyR mutations in P. xylostella, one nAChR mutation in A. gossypii, one VGSC mutation in A. arabiensis and five VGSC mutations in M. domestica were found to be with frequency difference >40% between resistant and susceptible populations including previously confirmed mutations G4946E in RyR, R81T in nAChR and L1014F in VGSC. And 49 detoxification genes were found to be overexpressed in resistant populations compared with susceptible populations including previously confirmed detoxification genes CYP6BG1, CYP6CY22, CYP6CY13, CYP6P3, CYP6M2, CYP6P4 and CYP4G16. The candidate target‐site mutations and detoxification genes were worth further validation. Resistance estimates according to confirmed markers were consistent with population phenotypes, confirming the reliability of this program in predicting population resistance at omics‐level.https://doi.org/10.1002/ece3.7037detoxification genesinsecticide resistanceRNA‐Seqtarget‐site mutationswebserver |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Longfei Chen Kun Lang Yang Mei Zhenmin Shi Kang He Fei Li Huamei Xiao Gongyin Ye Zhaojun Han |
spellingShingle |
Longfei Chen Kun Lang Yang Mei Zhenmin Shi Kang He Fei Li Huamei Xiao Gongyin Ye Zhaojun Han FastD: Fast detection of insecticide target‐site mutations and overexpressed detoxification genes in insect populations from RNA‐Seq data Ecology and Evolution detoxification genes insecticide resistance RNA‐Seq target‐site mutations webserver |
author_facet |
Longfei Chen Kun Lang Yang Mei Zhenmin Shi Kang He Fei Li Huamei Xiao Gongyin Ye Zhaojun Han |
author_sort |
Longfei Chen |
title |
FastD: Fast detection of insecticide target‐site mutations and overexpressed detoxification genes in insect populations from RNA‐Seq data |
title_short |
FastD: Fast detection of insecticide target‐site mutations and overexpressed detoxification genes in insect populations from RNA‐Seq data |
title_full |
FastD: Fast detection of insecticide target‐site mutations and overexpressed detoxification genes in insect populations from RNA‐Seq data |
title_fullStr |
FastD: Fast detection of insecticide target‐site mutations and overexpressed detoxification genes in insect populations from RNA‐Seq data |
title_full_unstemmed |
FastD: Fast detection of insecticide target‐site mutations and overexpressed detoxification genes in insect populations from RNA‐Seq data |
title_sort |
fastd: fast detection of insecticide target‐site mutations and overexpressed detoxification genes in insect populations from rna‐seq data |
publisher |
Wiley |
series |
Ecology and Evolution |
issn |
2045-7758 |
publishDate |
2020-12-01 |
description |
Abstract Target‐site mutations and detoxification gene overexpression are two major mechanisms conferring insecticide resistance. Molecular assays applied to detect these resistance genetic markers are time‐consuming and with high false‐positive rates. RNA‐Seq data contains information on the variations within expressed genomic regions and expression of detoxification genes. However, there is no corresponding method to detect resistance markers at present. Here, we collected 66 reported resistance mutations of four insecticide targets (AChE, VGSC, RyR, and nAChR) from 82 insect species. Next, we obtained 403 sequences of the four target genes and 12,665 sequences of three kinds of detoxification genes including P450s, GSTs, and CCEs. Then, we developed a Perl program, FastD, to detect target‐site mutations and overexpressed detoxification genes from RNA‐Seq data and constructed a web server for FastD (http://www.insect-genome.com/fastd). The estimation of FastD on simulated RNA‐Seq data showed high sensitivity and specificity. We applied FastD to detect resistant markers in 15 populations of six insects, Plutella xylostella, Aphis gossypii, Anopheles arabiensis, Musca domestica, Leptinotarsa decemlineata and Apis mellifera. Results showed that 11 RyR mutations in P. xylostella, one nAChR mutation in A. gossypii, one VGSC mutation in A. arabiensis and five VGSC mutations in M. domestica were found to be with frequency difference >40% between resistant and susceptible populations including previously confirmed mutations G4946E in RyR, R81T in nAChR and L1014F in VGSC. And 49 detoxification genes were found to be overexpressed in resistant populations compared with susceptible populations including previously confirmed detoxification genes CYP6BG1, CYP6CY22, CYP6CY13, CYP6P3, CYP6M2, CYP6P4 and CYP4G16. The candidate target‐site mutations and detoxification genes were worth further validation. Resistance estimates according to confirmed markers were consistent with population phenotypes, confirming the reliability of this program in predicting population resistance at omics‐level. |
topic |
detoxification genes insecticide resistance RNA‐Seq target‐site mutations webserver |
url |
https://doi.org/10.1002/ece3.7037 |
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