micron-scale-phenotyping-techniques-maize-vascular-bundles-based-on-x

Micron-scale Phenotyping Techniques of Maize Vascular Bundles Based on X-ray Microcomputed Tomography

It is necessary to accurately quantify the anatomical structures of maize materials based on high-throughput image analysis techniques. Here, we provide a ...

Beijing Academy of Agriculture and Forestry Sciences

Although many gene expression profiling studies of maize leaves infected with Ustilago maydis have been published, heterogeneity of the results, caused by various data processing methods and pathogenic strains in different data sets, remains strong. Hence, we conducted a combined analysis of six genome-wide expression data sets of maize leaves infected with five different U. maydis strains by using the same pre-processing and quality control procedures. Six data sets were regrouped into five groups according to pathogenic strain used. Subsequently, each group of data set was processed by Multi-array Average for pre-processing and by pair-wise Pearson correlation for quality control. The differentially expressed genes were calculated by a standard linear mixed-effect model and then validated by various sensitivity analysis and multiple evidences. Finally, 44 unique differentially expressed genes were identified. Pathway enrichment analysis indicated that these genes related to response to fungus, oxidation-reduction, transferase activity, and several carbohydrate metabolic and catabolic processes. In addition, the hub genes within protein-protein interaction networks showed high relevance with the basic pathogenesis. We report a highly credible differentially expressed list, and the genes with multiple validations may denote a common signature of U. maydis in maize, which provides a new window for disease-resistant protection of maize plants.

Xiaodi Pan

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