Genetic diversity and population structure of the natural population of Helicoverpa armigera in Northwest China using Genotyping by Sequencing (GBS) technology
Abstract
Characterizing the genetic diversity and population structure can determine whether there is gene flow of the natural population of Helicoverpa armigera (Hübner) under disparate climate and habitat conditions in Northwest China. In this paper, H. armigera was genotyped in various regions of Xinjiang using Genotyping-by-Sequencing (GBS). The samples were compared using the single nucleotide polymorphism (SNP) and insertion deletion (InDel) marker data. The SNPs were used to analyze the population structure and five subgroups were obtained, which was further confirmed by principal component analysis (PCA). The phylogenetic tree identified five cluster populations of H. armigera . The average values of polymorphic information content (PIC) and genetic differentiation index (Fst) are 0.1783 and 0.1293, respectively, which are at a high level. The phylogenetic tree differentiation also indicates that the genetic diversity of cotton bollworm populations in different regions of Xinjiang is low diversity, moderate differentiation, and widespread gene flow. According to correlation analysis of the source of feeding on host plants (Bt cotton and non Bt crops) of H. armigera, seven SNPs with significant differences were obtained. The most significant SNP sequence was compared with the whole genome of H. armigera , and 10 candidate genes were screened. Whether the candidate genes function are related to Bt resistance needs further verification. This study can provide scientific basis for screening Bt resistance genes and formulating refuge strategy of H. armigera in Northwest China.
Article Details
Authors (11)
Zhongxiong Ning
Jiali He
Jianhao Dong
Weizheng Li
Jiangsu Engineering Laboratory of Novel Functional Polymeric Materials, Jiangsu Key Laboratory of Advanced Negative Carbon Technologies, Suzhou Key Laboratory of Soft Material and New Energy, College of Chemistry, Chemical Engineering and Materials Science, Soochow University
Ruihao Li
State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering & Institute of Artificial Intelligence & Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province (IKKEM)
Zhengzhen Gao
Dongmei Wang
Haiqiang Li
Bing Liu
Yujiao Wang
Wei Lu