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Integrative analysis of transcriptomics and epigenomics of metabolically modulated bovine embryos: a bioinformatics approach linking Cut&Tag and RNA-seq

Grant number: 22/14472-0
Support Opportunities:Scholarships abroad - Research Internship - Doctorate
Effective date (Start): April 01, 2023
Effective date (End): September 30, 2023
Field of knowledge:Biological Sciences - Genetics - Animal Genetics
Principal Investigator:Marcella Pecora Milazzotto
Grantee:Aldcejam Martins da Fonseca Junior
Supervisor: Haja Kadarmideen
Host Institution: Centro de Ciências Naturais e Humanas (CCNH). Universidade Federal do ABC (UFABC). Ministério da Educação (Brasil). Santo André , SP, Brazil
Research place: Technical University of Denmark (DTU), Denmark  
Associated to the scholarship:19/22025-1 - Modulation of the glycolitic pathway in bovine embryos in vitro produced: impacts in histone acetylation under the metaboloepigenetics view, BP.DR

Abstract

The epigenetic reprogramming that occurs during the earliest stages of the embryonic development has been described as crucial for the initial events of cell specification and differentiation. Recently, the metabolic status of the embryo has gained attention as one of the main factors coordinating epigenetic events. For this present proposal, we start from previous results with the hypothesis that the pharmacological modulation of the glycolytic pathway in bovine embryos produced in vitro could lead to different profiles of acetyl-CoA generation, interfering with the histone acetylation pattern, thus altering its metabolic profile and potency of the blastocyst cells. For this, it was proposed to promote the modulation of the glycolytic pathway in bovine IVP embryos with an inhibitor of the enzyme G3PD, as well as an inhibitor of phosphorylation of the enzyme PDH, from the time of major activation of the embryonic genome. RNA-sequencing and CUT&Tag (Cleavage Under Targets and Tagmentation) of chromatin state related to H3K27 acetylation of these embryos were performed and the challenge is to integrate the generated transcriptomics and epigenomics data in comprehensible results. Thus, we propose an exploratory and targeted approach for statistical and bioinformatics analysis of absolute and differential binding for RNA-seq and Cut&Tag data types and generate visual summaries in a variety of formats. Data integration will be performed with R software platform and machine learning will be applied for validation results as well as for predicting expression and external parameters. (AU)

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