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Development of high-throughput approaches for the study of quantitative traits loci related to robustness of industrial yeasts (Saccharomyces cerevisiae)

Grant number: 16/02506-7
Support type:Program for Research on Bioenergy (BIOEN) - Regular Program Grants
Duration: September 01, 2016 - August 31, 2018
Field of knowledge:Biological Sciences - Genetics
Principal Investigator:Gleidson Silva Teixeira
Grantee:Gleidson Silva Teixeira
Home Institution: Instituto de Biologia (IB). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
Assoc. researchers:Gonçalo Amarante Guimarães Pereira ; Marcelo Falsarella Carazzolle

Abstract

The greater awareness of the environmental consequences resulting from fossil fuels usage leads to an increased interest in the development of renewable energy sources. In this scenario, the production of lignocellulosic ethanol stands out due to the possibility of better utilization of natural resources. However, the economic viability of industrial processes is multifactorial and depends, among other things, on the performance of the yeast used. For this reason, yeasts adapted to industrial conditions - industrial yeasts - have been considered ideal platforms for the development of strains, as well as targets for the study of genes which provide tolerance to stresses observed under industrial conditions. Understanding the genetic basis that confer robustness to these yeasts will contribute to the improvement of existing strains and to the development of new ones. However, these characteristics are generally determined by multiple genes - Quantitative Trait Loci (QTL) - whose identification requires the phenotypic analysis of a high number of segregants and validation of candidate alleles related to the studied phenotype. In this context, this project aims to develop tools that make the QTLs study more accurate, less laborious and more cost-effective, accelerating the development of strains applied to industrial processes. In order to accomplish this, we intend to do the following: optimization of flow cytometry-based procedures for analysis and dissection of tetrads; development of automated high-throughput methods for phenotyping of segregants; implementation of bioinformatics tools for QTL mapping and; optimization of CRISPR/Cas9-based approaches for the validation of candidate alleles related to the studied phenotypes. (AU)

Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
NAGAMATSU, SHEILA TIEMI; TEIXEIRA, GLEIDSON SILVA; BEZERRA DE MELLO, FELLIPE DA SILVEIRA; GALVAO TIZEI, PEDRO AUGUSTO; GRICHOSWSKI NAKAGAWA, BRUNA TATSUE; DE CARVALHO, LUCAS MIGUEL; GUIMARAES PEREIRA, GONCALO AMARANTE; CARAZZOLLE, MARCELO FALSARELLA. Genome Assembly of a Highly Aldehyde-Resistant Saccharomyces cerevisiae SA1-Derived Industrial Strain. MICROBIOLOGY RESOURCE ANNOUNCEMENTS, v. 8, n. 13 MAR 2019. Web of Science Citations: 1.
BEZERRA DE MELLO, FELLIPE DA SILVEIRA; VENEGA CORADINI, ALESSANDRO LUIS; GALVAO TIZEI, PEDRO AUGUSTO; CARAZZOLLE, MARCELO FALSARELLA; GUIMARAES PEREIRA, GONCALO AMARANTE; TEIXEIRA, GLEIDSON SILVA. Static microplate fermentation and automated growth analysis approaches identified a highly-aldehyde resistant Saccharomyces cerevisiae strain. BIOMASS & BIOENERGY, v. 120, p. 49-58, JAN 2019. Web of Science Citations: 3.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.