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Analysis of the sugarcane rizosphere metatranscriptome subjected to water stress

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Author(s):
Victor Marques de Oliveira Gambarini
Total Authors: 1
Document type: Master's Dissertation
Press: Campinas, SP.
Institution: Universidade Estadual de Campinas (UNICAMP). Instituto de Biologia
Defense date:
Examining board members:
Renato Vicentini; Marcelo Falsarella Carazzolle; Marco Aurélio Takita
Advisor: Renato Vicentini
Abstract

In view of climate changes, the pluviometric regime of the whole globe is expected to change, causing drought in certain regions and rainfall increase in others. In this sense, plants of great commercial interest such as sugarcane should be the subject of research in porsue of greater productivity and better adaptation conditions in the face of future climate changes. It is known that microorganisms that develop near the root of plants, or in the so-called rhizosphere, can influence the growth and development of plants through a variety of mechanisms, such as promoting the mobilization of nutrients, increasing mineral absorption, stimulating plant growth and suppressing pathogens. Thus, this study used bioinformatics methods to analyze data generated in large-scale sequencing of the sugarcane rhizosphere metatranscriptome subjected to water stress. In addition, the taxonomic and functional profile of the active microbiota was characterized, the differential gene expression induced by water stress was revealed, and finally, co-expression gene networks were generated from the data obtained. De novo assembly of the metatranscriptome resulted in 316,958 contigs from which 405,547 ORFs were predicted. The analysis of the taxonomic composition of the metatranscriptome revealed a predominance of the phyla Proteobacteria (52,2%), Actinobacteria (15,1%) and Bacteroidetes (10,6%). The four most abundant genera that had increased relative abundance after application of water stress were Actinomadura, Dongia, Sphingomonas and Vulgatibacter. The functional annotation in SEED was able to annotate 208,816 transcripts (51.5%) in 40 different functional categories. The functional categories that presented greater abundance in SEED were those responsible for essential microorganism¿s processes, such as carbohydrate, protein, amino acids, vitamins and RNA metabolism. Three SEED categories with an increase in abundance after the application of water stress were discovered, being related to the degradation of proteins to obtain energy (degradation of arginine and ornithine) and oxidizing enzymes acting in the aerobic respiratory chain (succinate dehydrogenase) and in fermentation processes (ketoisovalerate oxirreductase). Analysis of differential gene expression resulted in 43,716 differentially expressed transcripts and demonstrated that GO terms related to regulation of cellular respiration, ribosome biogenesis, protein folding, endocytosis, stress response and translation were down-regulated. On the other hand, the major GO terms enriched in up-regulated transcripts were benzoate catabolism, flagellum assembly, and pseudouridine tRNA synthesis. In addition, a gene co-expression network was generated from the differentially expressed transcripts which was composed of 582 clusters and, through the analyzes of this network, it could be observed that with the application of water stress, there was an increase in the expression of transcripts related to, for example, auto proteolysis, degradation of nucleic acids and transport of siderophores. The results obtained in this work help to understand the taxonomic and functional diversity of sugarcane rhizosphere and the effects caused by water stress. Finally, this work can be used as a basis for the development of applications for the knowledge generated here, aiming to adapt and increase the productivity of sugarcane in anticipation of global climate change (AU)

FAPESP's process: 16/08994-3 - Analysis of the metatranscriptome of sugarcane rhizosphere subjected to water stress
Grantee:Victor Marques de Oliveira Gambarini
Support Opportunities: Scholarships in Brazil - Master