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认知，并助力种群动态预测。本研究以针对繁殖力进行分化选育的褐飞虱（brown planthopper, BPH）*Nilaparvata lugens* Stål（半翅目：飞虱科）的高繁殖力种群与低繁殖力种群为材料，采用候选基因法探究单核苷酸多态性（single nucleotide polymorphisms, SNPs）。本研究同时探究了能否通过少量SNPs实现种群繁殖力的预测。作为一种重要水稻害虫，本研究针对褐飞虱的7个基因（ACE、fizzy、HMGCR、LpR、Sxl、Vg及VgR）开展了SNPs检测。通过对上述候选基因的互补DNA（complementary DNA, cDNA）及启动子序列进行直接测序，本研究在高、低繁殖力褐飞虱种群中共检测到1033个SNPs。研究人员选取了121个候选SNPs，对来自2个实验室种群（HFP、LFP）与3个田间种群（GZP、SGP、ZSP）的215个个体进行了基因分型。在关联分析之前，本研究首先对3个田间种群的种群结构及连锁不平衡（linkage disequilibrium, LD）水平进行了分析。关联分析结果显示，共有7个SNPs与褐飞虱的种群繁殖力显著相关。研究人员以这些显著关联的SNPs为基础，通过逐步回归构建广义线性模型。最优预测模型仅包含2个SNPs（ACE-862与VgR-816），且拟合效果极佳。本研究发现，仅需这2个分子标记即可解释繁殖力相关表型变异的29%。利用2个实验室种群与1个完全独立的田间种群进行验证，该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繁殖力的预测提供了一种高效的分子检测方法，同时也为昆虫种群治理提供了全新的研究视角。