Pais Andrew L, Whetten Ross W, Xiang Qiu-Yun Jenny
Department of Plant and Microbial Biology North Carolina State University Raleigh NC USA.
Department of Forestry North Carolina State University Raleigh NC USA.
Ecol Evol. 2016 Dec 20;7(1):441-465. doi: 10.1002/ece3.2623. eCollection 2017 Jan.
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 (.) 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 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 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.
发现局部适应性、其遗传基础和环境驱动因素对于保护森林物种至关重要。生态基因组学方法与下一代测序相结合是检测非模式物种局部适应性并揭示其潜在遗传基础的有用手段。我们报告了一项对多花梾木树（.）进行的研究结果，该研究采用了简化基因组测序（GBS）技术。该物种对美国东部森林具有重要生态意义，但受到真菌病害的严重威胁。我们分析了北卡罗来纳州不同生态栖息地中的亚种群，以发现受局部选择且与环境功能性状或疾病感染相关的基因座。在此规模下，我们测试了在进行更广泛的全范围检查之前增加额外测序的效果。为了测试GBS的偏差，我们从三个生态栖息地的六个种群中独立对两个类似采样的文库进行了测序。我们获取了每个亚种群的环境功能性状，通过潜在因子混合模型（LFMM）和梯度森林分析来确定与基因型的关联。为了测试非生物压力的异质性是否导致了表明局部适应性的遗传分化，我们在考虑沿海亚种群和皮埃蒙特 - 山区亚种群之间遗传分化的同时评估了每个基因座。在两个文库中都有充分证据表明受到选择的54个候选基因座中，28 - 39个是Arlequin - BayeScan异常值。对于LFMM，45个候选基因座与气候相关（共54个），30个与土壤性质相关，4个与植物健康相关。对合并文库的重新分析表明，42个候选基因座仍显示出受到选择的证据。我们得出结论认为，环境驱动的对特定基因座的选择导致了对钾缺乏、温度、降水以及（在一定程度上）疾病的局部适应性。沿生态梯度的高等位基因周转率进一步支持了推测受到选择作用的基因座的适应性意义。
