FastD: fast detection of insecticide target-site insensitive mutations
and overexpressed detoxification genes in insect populations from
RNA-Seq data
Abstract
Target-site insensitive mutations and overexpression of detoxification
genes are two major mechanisms conferring insecticide resistance. Many
molecular assays were applied to detect these two kinds of resistance
genetic markers in insect populations. Unfortunately, these assays are
time-consuming and have high false-positive rates. RNA-Seq data, which
contains information on the variation within expressed regions of the
genome and expression information of detoxification genes, provides us a
valuable resource to detect resistance-associated markers. At present,
there is no corresponding method at present. Here, we collected 66
reported resistance mutations of four main insecticide targets (AChE,
VGSC, RyR, and nAChR) of 82 insect species. Next, we obtained 403
sequences of the four target genes and 12,665 sequences of three kinds
of detoxification genes including P450, GST, and CCE. Here, we developed
a Perl program, FastD, to detect insecticide target-site insensitive
mutations and overexpressed detoxification genes from RNA-Seq data, and
constructed a web server for FastD (http://www.insect-genome.com/fastd).
FastD program was then applied to detect two kinds of resistant markers
in five populations of two insects, Plutella xylostella and Aphis
gossypii. Results showed that RyR mutation G4946E was detected in all P.
xylostella populations, with higher frequencies in two resistant
populations, ZZ (66.1%) and CHR (94.55%), than a susceptible
population CHS (2.32%). CYP6a2 was overexpressed 10.82-fold in ZZ
population. As to A. gossypii, nAChR mutation R81T was detected in
resistant population KR with 49.85% frequency, but not in susceptible
population NS. CYP6CY22 and CYP6CY13 were overexpressed 39.61- and
22.04-fold respectively in KR population. FastD is a program using
RNA-Seq data to detect two types of resistance markers to estimate
resistance level of insect populations. Generally, resistance level
estimated by FastD were consistent with previous reports, confirming the
reliability of this program in predicting population resistance at
omics-level.