
Selection of reference genes for qRT ‐ PCR and expression analysis of high‐altitude‐related genes in grassland caterpillars (Lepidoptera: Erebidae: Gynaephora ) along an altitude gradient
Author(s) -
Zhang Li,
Zhang QiLin,
Wang XiaoTong,
Yang XingZhuo,
Li XiaoPeng,
Yuan MingLong
Publication year - 2017
Publication title -
ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.17
H-Index - 63
ISSN - 2045-7758
DOI - 10.1002/ece3.3431
Subject(s) - biology , reference genes , gene , adaptation (eye) , gene expression , genetics , selection (genetic algorithm) , ecology , computational biology , evolutionary biology , neuroscience , artificial intelligence , computer science
Changes in gene expression patterns can reflect the adaptation of organisms to divergent environments. Quantitative real‐time PCR ( qRT ‐ PCR ) is an important tool for ecological adaptation studies at the gene expression level. The quality of the results of qRT ‐ PCR analysis largely depends on the availability of reliable reference genes ( RG s). To date, reliable RG s have not been determined for adaptive evolution studies in insects using a standard approach. Here, we evaluated the reliability of 17 candidate RG s for five Gynaephora populations inhabiting various altitudes of the Tibetan Plateau ( TP ) using four independent (geNorm, NormFinder, BestKeeper, and the deltaCt method) and one comprehensive (RefFinder) algorithms. Our results showed that EF 1‐ α, RPS 15 , and RPS 13 were the top three most suitable RG s, and a combination of these three RG s was the most optimal for normalization. Conversely, RPS 2 , ACT , and RPL 27 were the most unstable RG s. The expression profiles of two target genes ( HSP 70 and HSP 90 ) were used to confirm the reliability of the chosen RG s. Additionally, the expression patterns of four other genes ( GPI , HIF 1A , HSP 20 , and USP ) associated with adaptation to extreme environments were assessed to explore the adaptive mechanisms of TP Gynaephora species to divergent environments. Each of these six target genes showed discrepant expression patterns among the five populations, suggesting that the observed expression differences may be associated with the local adaptation of Gynaephora to divergent altitudinal environments. This study is a useful resource for studying the adaptive evolution of TP Gynaephora to divergent environments using qRT ‐ PCR , and it also acts as a guide for selecting suitable RG s for ecological and evolutionary studies in insects.