Data from: 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 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 analyzed. 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 andVgR-816) with very good fitting degree. We found that 29% of the phenotypic variation in fecundity could be accounted for by only 2 markers. Using two laboratory populations and a complete independent field population, the predictive accuracy were 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.

鉴定自然种群中复杂数量性状的分子标记，有望为适应的遗传机制提供全新见解，并助力种群动态预测。本研究采用候选基因法，对经产卵力分化选育的褐飞虱（brown planthopper, BPH）Nilaparvata lugens Stål（半翅目：飞虱科）的高、低产卵力种群开展单核苷酸多态性（single nucleotide polymorphisms, SNPs）分析，同时探究了是否可通过少量SNPs预测种群产卵力。针对作为水稻重大害虫的褐飞虱，我们对7个基因（ACE、fizzy、HMGCR、LpR、Sxl、Vg及VgR）开展了SNPs筛查；通过对这些候选基因的互补DNA及启动子序列进行直接测序，在高、低产卵力褐飞虱种群中共鉴定出1033个SNPs。我们筛选出121个候选SNPs，并对来自2个实验室种群（HFP与LFP）及3个田间种群（GZP、SGP与ZSP）的215个个体进行了基因分型。在关联分析之前，我们先对3个田间种群的种群结构及连锁不平衡（linkage disequilibrium, LD）展开了分析。关联分析结果显示，共有7个SNPs与褐飞虱的种群产卵力显著相关。我们将这些显著关联的SNPs用于构建逐步回归通用线性模型，最优预测模型由2个SNPs（ACE-862与VgR-816）构成，拟合度极佳。研究发现，仅需这2个分子标记即可解释产卵力表型变异的29%。利用2个实验室种群及1个完全独立的田间种群进行验证，模型的预测准确率可达84.35%~92.39%。该预测模型为田间褐飞虱种群产卵力的预测提供了一种高效的分子手段，同时也为昆虫种群治理提供了全新的研究视角。