Transcriptional differentiation driving Cucumis sativus-Botrytis cinerea interactions based on the Skellam model and Bayesian networks.

ABSTRACT: Robust statistical tools such as the Skellam model and Bayesian networks can capture the count properties of transcriptome sequencing data and clusters of genes among treatments, thereby improving our knowledge of gene functions and networks. In this study, we successfully implemented a model to analyze a transcriptome dataset of Cucumis sativus and Botrytis cinerea before and after their interaction. First, 4200 differentially expressed genes (DEGs) from C. sativus were clustered into 17 distinct groups, and 670 DEGs from B. cinerea were clustered into 12 groups. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were applied on these DEGs to assess the interactions between C. sativus and B. cinerea. In C. sativus, more DEGs were divided into terms i

SUBMITTER: Zhang Q 

PROVIDER: S-EPMC8528924 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature