The performance of inbred and hybrid genotypes is of interest in plant breeding and genetics. High-throughput sequencing of RNA (RNA-seq) has proven to be a useful tool in the study of the molecular genetic responses of inbreds and hybrids to environmental stresses. Commonly used experimental designs and sequencing methods lead to complex data structures that require careful attention in data analysis. We demonstrate an analysis of RNA-seq data from a split-plot design involving drought stress applied to two inbred genotypes and two hybrids formed by crosses between the inbreds. Our generalized linear modeling strategy incorporates random effects for whole-plot experimental units and uses negative binomial distributions to allow for overdispersion in count responses for split-plot experimental units. Variations in gene length and base content, as well as differences in sequencing intensity across experimental units, are also accounted for. Hierarchical modeling with thoughtful parameterization and prior specification allows for borrowing of information across genes to improve estimation of dispersion parameters, genotype effects, treatment effects, and interaction effects of primary interest.

中文翻译：

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自交和杂种基因型RNA序列实验的分层建模和差异表达分析。

近交和杂种基因型的表现在植物育种和遗传学中很重要。RNA高通量测序（RNA-seq）已被证明是研究近交和杂种对环境胁迫的分子遗传反应的有用工具。常用的实验设计和排序方法会导致复杂的数据结构，在数据分析中需要特别注意。我们证明了从裂区设计中分析RNA-seq数据的分析，涉及干旱胁迫，将干旱胁迫应用于两个近交基因型和两个近交之间杂交形成的杂种。我们的广义线性建模策略结合了整图实验单元的随机效应，并使用负二项式分布以允许对分裂图实验单元的计数响应进行过度分散。基因长度和碱基含量的变化，以及不同实验单位的测序强度差异也应考虑在内。具有深思熟虑的参数化和先验规范的分层建模允许跨基因借用信息，以改善对分散参数，基因型效应，治疗效应和主要关注的相互作用效应的估计。