Abstract
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.
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Acknowledgments
Research reported in this chapter was supported by the National Institute of General Medical Sciences (NIGMS) of the National Institutes of Health and the joint National Science Foundation/NIGMS Mathematical Biology Program under award number R01GM109458. The content is solely the responsibility of the author and does not necessarily represent the official views of the National Institutes of Health or the National Science Foundation.
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Lithio, A., Nettleton, D. Hierarchical Modeling and Differential Expression Analysis for RNA-seq Experiments with Inbred and Hybrid Genotypes. JABES 20, 598–613 (2015). https://doi.org/10.1007/s13253-015-0232-3
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DOI: https://doi.org/10.1007/s13253-015-0232-3