The genetic basis of population fecundity prediction across multiple field populations of Nilaparvata lugens
Identifying the molecular markers for complex quantitative traits in natural populations promises to provide novel insight into genetic mechanisms of adaptation and to aid in forecasting population dynamics. In this study, we investigated single nucleotide polymorphisms (SNPs) using candidate gene a...
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Published in | Molecular ecology Vol. 24; no. 4; pp. 771 - 784 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
England
Blackwell Publishing Ltd
01.02.2015
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Subjects | |
Online Access | Get full text |
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Summary: | Identifying the molecular markers for complex quantitative traits in natural populations promises to provide novel insight into genetic mechanisms of adaptation and to aid in forecasting population dynamics. In this study, we investigated single nucleotide polymorphisms (SNPs) using candidate gene approach from high‐ and low‐fecundity populations of the brown planthopper (BPH) Nilaparvata lugens Stål (Hemiptera: Delphacidae) divergently selected for fecundity. We also tested whether the population fecundity can be predicted by a few SNPs. Seven genes (ACE, fizzy, HMGCR, LpR, Sxl, Vg and VgR) were inspected for SNPs in N. lugens, which is a serious insect pest of rice. By direct sequencing of the complementary DNA and promoter sequences of these candidate genes, 1033 SNPs were discovered within high‐ and low‐fecundity BPH populations. A panel of 121 candidate SNPs were selected and genotyped in 215 individuals from 2 laboratory populations (HFP and LFP) and 3 field populations (GZP, SGP and ZSP). Prior to association tests, population structure and linkage disequilibrium (LD) among the 3 field populations were analysed. The association results showed that 7 SNPs were significantly associated with population fecundity in BPH. These significant SNPs were used for constructing general liner models with stepwise regression. The best predictive model was composed of 2 SNPs (ACE‐862 and VgR‐816) with very good fitting degree. We found that 29% of the phenotypic variation in fecundity could be accounted for by only two markers. Using two laboratory populations and a complete independent field population, the predictive accuracy was 84.35–92.39%. The predictive model provides an efficient molecular method to predict BPH fecundity of field populations and provides novel insights for insect population management. |
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Bibliography: | Fig. S1 Mutation Surveyor software detected a mutant allele in two sequences traces. The arrow indicates a CC to CA mutation. Table S1 Information on the 7 candidate genes. Table S2 Nested PCR primers for scanning 7 genes for SNPs. Table S3 Screening process of SNP selection. Table S4 PCR primers for genotyping of ACE-862, VgR-816 and VgR-274 in QYP. Table S5 Primers for qRT-PCR and the constructed standard curves. Table S6 The final 121 SNPs selected for genotyping using the iPLEX Sequenom MassARRAY platform. istex:BBAA4E7AB8515A5CE9B6F05E70C2D46B72963082 ArticleID:MEC13069 National Natural Science Foundation of China - No. 30930061 National Basic Research Program of China - No. 2010CB126200 ark:/67375/WNG-KFWC0RKD-W ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0962-1083 1365-294X |
DOI: | 10.1111/mec.13069 |