Host plant associations and geography interact to shape diversification in a specialist insect herbivore
Host plant associations and geography interact to shape diversification in a specialist insect herbivore
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DOI：
10.1111/mec.15220
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发表时间：
2019-09-26
影响因子：
4.9
通讯作者：
Ott, James R.
中科院分区：
文献类型：
--
作者：
Driscoe, Amanda L.;Nice, Chris C.;Ott, James R.
解开生物多样性的地理和环境模式背后的过程挑战生物学家，因为这种模式出现从生态进化过程中混淆的样本单位之间的空间自相关。食草性昆虫，Belonocnema treatae（膜翅目：Cynipidae），表现出区域专业化的三种植物，其地理分布范围从同域通过allopatry在美国南部。使用跨越三种宿主植物的地理范围的全范围采样和1，217个个体的基因分型测序，我们测试了这种昆虫食草动物是否表现出与宿主植物相关的基因组分化，同时控制58个样本点之间的空间自相关。使用分层贝叶斯模型熵评估基于40，699个SNP的群体基因组结构，以将个体分配到遗传簇并估计混合比例。为了控制空间自相关，基于距离的莫兰的特征向量映射被用来构建回归变量，总结样本站点之间固有的空间结构。基于距离的冗余分析（dbRDA），将空间变量，然后应用分区寄主植物相关分化（HAD）的空间自相关。通过结合熵和dbRDA分析SNP数据，我们揭示了一个复杂的马赛克的高度结构化的分化内和之间的gall-former人口发现的证据表明，地理，HAD和空间自相关都发挥了重要作用，在解释模式的基因组分化B。treatae。虽然dbRDA确认主机协会作为一个显着的预测模式的基因组变异，空间自相关网站之间的解释最大比例的变化。我们的研究结果表明，dbRDA与层次结构分析相结合，分区基因组变异的空间/环境模式的价值。
Disentangling the processes underlying geographic and environmental patterns of biodiversity challenges biologists as such patterns emerge from eco-evolutionary processes confounded by spatial autocorrelation among sample units. The herbivorous insect, Belonocnema treatae (Hymenoptera: Cynipidae), exhibits regional specialization on three plant species whose geographic distributions range from sympatry through allopatry across the southern United States. Using range-wide sampling spanning the geographic ranges of the three host plants and genotyping-by-sequencing of 1,217 individuals, we tested whether this insect herbivore exhibited host plant-associated genomic differentiation while controlling for spatial autocorrelation among the 58 sample sites. Population genomic structure based on 40,699 SNPs was evaluated using the hierarchical Bayesian model entropy to assign individuals to genetic clusters and estimate admixture proportions. To control for spatial autocorrelation, distance-based Moran's eigenvector mapping was used to construct regression variables summarizing spatial structure inherent among sample sites. Distance-based redundancy analysis (dbRDA) incorporating the spatial variables was then applied to partition host plant-associated differentiation (HAD) from spatial autocorrelation. By combining entropy and dbRDA to analyse SNP data, we unveiled a complex mosaic of highly structured differentiation within and among gall-former populations finding evidence that geography, HAD and spatial autocorrelation all play significant roles in explaining patterns of genomic differentiation in B. treatae. While dbRDA confirmed host association as a significant predictor of patterns of genomic variation, spatial autocorrelation among sites explained the largest proportion of variation. Our results demonstrate the value of combining dbRDA with hierarchical structural analyses to partition spatial/environmental patterns of genomic variation.