Gene co-expression networks highlight key nodes associated with Ammonium nitrate in sugarcane

Abstract

Gene co-expression network analysis offers valuable insights into complex biological processes in plants. In this study, we investigated the molecular mechanisms underlying nitrogen utilization efficiency (NUE) in sugarcane by analyzing transcriptome data from two contrasting genotypes (responsive and non-responsive) across different leaf segments under varying nitrogen conditions. RNA-seq analysis of 48 samples identified 2,723 differentially expressed genes. The responsive genotype showed enrichment in carbon metabolism and defense response pathways under high nitrogen conditions, while the non-responsive genotype prioritized photosynthesis and stress response mechanisms. Differentially expressed genes were used to construct a co-expression network which revealed 199 distinct modules. 44 modules correlating to nitrogen availability and 20 to genotype. Notably, Module 20, containing a high proportion of MYB/MYB-related transcription factors, emerged as a potential key regulator of nitrogen response in both genotypes. Several modules showed correlation with important metabolic markers such as RUBISCO, chlorophyll, and PEPCASE. Additionally, we identified novel candidate genes, including uncharacterized transcripts with strong genotype-specific expression patterns. These findings provide potential targets for understanding and improving nitrogen use efficiency in sugarcane breeding programs.Competing Interest StatementThe authors have declared no competing interest.Conselho Nacional de Desenvolvimento Cientı́fico e Tecnológico, Brasilia, BR, 311558/2021-6, 442529/2014-7Fundação de Amparo à Pesquisa do Estado de São Paulo, 2013/15576-5, 2012/23345-0Coordenação de Aperfeicoamento de Pessoal de Nv́el Superior, Finance Code 001

Jorge Mario Muñoz Pérez

PhD student - PPG - Ciências CENA/USP - Sugarcane Co-expression networks

I am PhD student at PPG - Ciências at the Center for Nuclear Energy in Agriculture, University of São Paulo. I am interested in the intersection of Plant Biology, Programing and Mathemathics. I have worked in Plant Biotechnology, Population Genomics, Machine Learning applied to the discovery of anti-microbial peptides. Currenlty i turned into Sugarcane omics, focusing on genomic resources and gene Co-expression network analysis.

Diego Mauricio Riaño-Pachón

Assistant Professor (MS3.2) in Computational, Evolutionary and Sistems Biology

I am a computational biologist/bioinformatician at the University of São Paulo, Campus Luiz de Queiroz (Piracicaba/SP, Brazil).