Abstract
Environmental factors, including different stresses, can have an impact on the expression of genes and subsequently the phenotype and development of plants. Since a large number of genes are involved in response to the perturbation of the environment, identifying groups of co-expressed genes is meaningful. The gene co-expression network models can be used for the exploration, interpretation, and identification of genes responding to environmental changes. Once a gene co-expression network is constructed, one can determine gene modules and the association of gene modules to the phenotypic response. To link modules to phenotype, one approach is to find the correlated eigengenes of given modules or to integrate all eigengenes in regularized linear model. This manuscript describes the method from construction of co-expression network, module discovery, association between modules and phenotypic data, and finally to annotation/visualization.
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Acknowledgments
The work is supported by funding under the National Science Foundation (Awards OIA-1557417 to CZ, DBI-1564621 to CZ HW and QZ, and OIA-1736192 to CZ HW and QZ). This work was completed utilizing the Holland Computing Center of the University of Nebraska.
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Du, Q. et al. (2022). Gene Co-expression Network Analysis and Linking Modules to Phenotyping Response in Plants. In: Lorence, A., Medina Jimenez, K. (eds) High-Throughput Plant Phenotyping. Methods in Molecular Biology, vol 2539. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2537-8_20
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DOI: https://doi.org/10.1007/978-1-0716-2537-8_20
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