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Integrating metataxonomics and host transcriptomics data in maize

Grant number: 23/11133-3
Support Opportunities:Scholarships abroad - Research Internship - Post-doctor
Effective date (Start): February 01, 2024
Effective date (End): January 31, 2025
Field of knowledge:Biological Sciences - Genetics - Plant Genetics
Principal Investigator:Diego Mauricio Riano Pachon
Grantee:Renato Augusto Corrêa dos Santos
Supervisor: Jason Wallace
Host Institution: Centro de Energia Nuclear na Agricultura (CENA). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
Research place: University of Georgia, Athens (UGA), United States  
Associated to the scholarship:21/11057-0 - Identifying gene co-expression modules with novel transcription factors involved in hemicellulose biosynthesis in C4 grasses, BP.PD

Abstract

CoNekT Grasses is a platform for comparative transcriptome analysis that enables researchers to have insights about gene expression based on expression profiles and co-expression networks. Approaches involving genomics, transcriptomics, and meta-taxonomics have been gaining importance for the understanding of host-microbiome interaction. Therefore, integration of such data in CoNekT Grasses would help us to better understand the host-microbiome system. The availability of paired datasets of gene expression and microbiome for the same samples enables the calculation of association metrics that potentially lead to unique and informative insights. Prof. Wallace's research group and his collaborators recently generated transcriptome and meta-taxonomic data from leaves for approximately 300 maize genotypes representing the genotypic and phenotypic diversity of modern crop varieties (Goodman Maize Association Panel), which are available for this project. Previously, associations between genotype and microbiome composition were analyzed for these samples. In this project, we have two aims, (i) to exploit associations between gene expression and microbiome composition, (ii) to extend CoNekT Grasses to incorporate meta-taxonomic data. The internship abroad comprises a valuable opportunity to study methods for exploiting the relationship between gene expression and microbiome data using maize as a model. Analyses in the platform after incorporating such functionalities will benefit important Brazilian crops in the future. (AU)

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