School of Biological Sciences, Washington State University, Pullman, Washington.
School of Zoology, University of Tasmania, Hobart, Tasmania, Australia.
Mol Ecol. 2018 Nov;27(21):4189-4199. doi: 10.1111/mec.14853. Epub 2018 Oct 5.
Identifying the genetic architecture of complex phenotypes is a central goal of modern biology, particularly for disease-related traits. Genome-wide association methods are a classical approach for identifying the genomic basis of variation in disease phenotypes, but such analyses are particularly challenging in natural populations due to sample size difficulties. Extensive mark-recapture data, strong linkage disequilibrium and a lethal transmissible cancer make the Tasmanian devil (Sarcophilus harrisii) an ideal model for such an association study. We used a RAD-capture approach to genotype 624 devils at 16,000 loci and then used association analyses to assess the heritability of three cancer-related phenotypes: infection case-control (where cases were infected devils and controls were devils that were never infected), age of first infection and survival following infection. The SNP array explained much of the phenotypic variance for female survival (>80%) and female case-control (>61%). We found that a few large-effect SNPs explained much of the variance for female survival (5 SNPs explained >61% of the total variance), whereas more SNPs (56) of smaller effect explained less of the variance for female case-control (23% of the total variance). By contrast, these same SNPs did not account for a significant proportion of phenotypic variance in males, suggesting that the genetic bases of these traits and/or selection differ across sexes. Loci involved with cell adhesion and cell-cycle regulation underlay trait variation, suggesting that the devil immune system is rapidly evolving to recognize and potentially suppress cancer growth through these pathways. Overall, our study provided necessary data for genomics-based conservation and management in Tasmanian devils.
鉴定复杂表型的遗传结构是现代生物学的一个核心目标,特别是对于与疾病相关的特征。全基因组关联方法是鉴定疾病表型变异的基因组基础的经典方法,但由于样本量的困难,这种分析在自然种群中尤其具有挑战性。广泛的标记-重捕数据、强连锁不平衡和一种致命的可传播癌症,使塔斯马尼亚恶魔(Sarcophilus harrisii)成为这种关联研究的理想模型。我们使用 RAD 捕获方法对 624 只恶魔进行了约 16000 个位点的基因型分析,然后使用关联分析来评估三种与癌症相关的表型的遗传力:感染病例对照(病例为感染的恶魔,对照为从未感染的恶魔)、首次感染年龄和感染后的存活情况。SNP 阵列解释了雌性生存(>80%)和雌性病例对照(>61%)的大部分表型方差。我们发现少数几个大效应 SNP 解释了雌性生存的大部分方差(约 5 个 SNP 解释了总方差的>61%),而更多的小效应 SNP(~56 个)解释了雌性病例对照的方差较少(总方差的 23%)。相比之下,这些相同的 SNP 并没有解释雄性这些特征的表型方差的很大比例,这表明这些特征的遗传基础以及/或者选择在性别之间是不同的。参与细胞黏附和细胞周期调控的基因座是性状变异的基础,这表明恶魔的免疫系统正在迅速进化,通过这些途径识别并可能抑制癌症的生长。总的来说,我们的研究为塔斯马尼亚恶魔的基于基因组学的保护和管理提供了必要的数据。