Data from: Ecological genomics of local adaptation in Cornus florida L. by genotyping by sequencing

Discovering local adaptation, its genetic underpinnings, and environmental drivers is important for conserving forest species. Ecological genomic approaches coupled with next-generation sequencing are useful means to detect local adaptation and uncover its underlying genetic basis in nonmodel species. We report results from a study on flowering dogwood trees (Cornus florida L.) using genotyping by sequencing (GBS). This species is ecologically important to eastern US forests but is severely threatened by fungal diseases. We analyzed subpopulations in divergent ecological habitats within North Carolina to uncover loci under local selection and associated with environmental–functional traits or disease infection. At this scale, we tested the effect of incorporating additional sequencing before scaling for a broader examination of the entire range. To test for biases of GBS, we sequenced two similarly sampled libraries independently from six populations of three ecological habitats. We obtained environmental–functional traits for each subpopulation to identify associations with genotypes via latent factor mixed modeling (LFMM) and gradient forests analysis. To test whether heterogeneity of abiotic pressures resulted in genetic differentiation indicative of local adaptation, we evaluated Fst per locus while accounting for genetic differentiation between coastal subpopulations and Piedmont-Mountain subpopulations. Of the 54 candidate loci with sufficient evidence of being under selection among both libraries, 28–39 were Arlequin–BayeScan Fst outliers. For LFMM, 45 candidates were associated with climate (of 54), 30 were associated with soil properties, and four were associated with plant health. Reanalysis of combined libraries showed that 42 candidate loci still showed evidence of being under selection. We conclude environment-driven selection on specific loci has resulted in local adaptation in response to potassium deficiencies, temperature, precipitation, and (to a marginal extent) disease. High allele turnover along ecological gradients further supports the adaptive significance of loci speculated to be under selection.

解析本地适应的现象、其遗传基础与环境驱动因子，对于森林物种的保护具有重要意义。结合下一代测序（next-generation sequencing）的生态基因组学方法，是检测非模式物种本地适应现象并揭示其潜在遗传基础的有效手段。本研究以大花四照花（Cornus florida L.）为对象，采用测序分型（genotyping by sequencing, GBS）技术开展实验，现将研究结果报道如下。该物种对于美国东部森林生态系统具有重要的生态价值，但目前正受到真菌病害的严重威胁。我们对北卡罗来纳州内不同生态生境中的亚种群展开分析，以筛选受到本地选择作用、且与环境功能性状或病害侵染相关的基因座。在此研究尺度下，我们测试了增加测序量的效果，为后续拓展至该物种全分布区的大范围研究提供参考。为了检测测序分型（GBS）技术的偏倚，我们从3种生态生境的6个种群中独立构建了两份采样方案一致的测序文库，并进行测序。我们获取了每个亚种群的环境功能性状数据，通过潜因子混合模型（latent factor mixed modeling, LFMM）与梯度森林分析，筛选与基因型存在关联的位点。为了验证非生物胁迫的异质性是否会引发指示本地适应的遗传分化，我们在评估海岸亚种群与皮埃蒙特-山地亚种群之间遗传分化的同时，对每个基因座的Fst值进行了计算分析。在两份文库中共筛选出54个具有显著选择证据的候选基因座，其中28~39个为Arlequin与BayeScan分析检出的Fst离群位点。通过潜因子混合模型（LFMM）分析，54个候选基因座中有45个与气候因子相关、30个与土壤属性相关、4个与植物健康状态相关。对合并后的两份测序文库进行重新分析，结果显示仍有42个候选基因座存在选择作用的证据。综上，本研究认为，针对特定基因座的环境驱动选择，使得大花四照花演化出针对钾缺乏、温度、降水以及（在较小程度上）真菌病害的本地适应策略。沿生态梯度呈现的高等位基因周转现象，进一步为推测受到选择作用的基因座的适应意义提供了支持。