Analysis of protein-protein interaction and weighted co-expression networks revealed key modules and genes in multiple tissues of Agave sisalana

Research Square (Research Square)(2022)

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Abstract
Abstract Agave plants are well-known for their drought resilience and commercial applications. Among them, Agave sisalana (sisal) is the species most used to produce hard fibers, and it is of great importance for semiarid regions. Agaves also show potential as bioenergy feedstocks, as they can accumulate large amounts of biomass and fermentable sugar. This study aimed to reconstruct the A. sisalana interactome, and identify key genes and modules involved in multiple plant tissues (root, stem, and leaf) through RNA-Seq analysis. We integrated A. sisalana transcriptome sequences and gene expression generated from stem, leaf, and root tissues to build global and conditional co-expression networks across the entire transcriptome. By combining the co-expression network, module classification, and function enrichment tools, we identified 20 functional modules related to at least one A. sisalana tissue, covering functions such as photosynthesis, leaf formation, auxin-activated signaling pathway, floral organ abscission, response to farnesol, brassinosteroid mediated signaling pathway, and light-harvesting. The final interactome of A. sisalana contains 2,582 nodes and 15,083 edges. In the reconstructed interactome, we identified submodules related to plant processes to validate the reconstruction. In addition, we identified 6 hub genes that were searched for in the co-expression modules. The intersection of hub genes identified by both the protein-protein interaction networks (PPI networks) and co-expression analyses using gene significance and module membership revealed six potential candidate genes for key genes. In conclusion, we identified six potential key genes for specific studies in Agave transcriptome atlas studies, biological processes related to plant survival in unfavorable environments, and provide strategies for breeding programs.
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Key words
genes,protein-protein,co-expression
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