Fenômica e integração de transcritômica e metabolômica na análise das respostas de Gliricidia sepium (Jacq.) Steud. E Portulaca oleracea L. ao estresse salino

• Ano de defesa: 2021
• Autor(a) principal: Silva, Thalliton Luiz Carvalho da
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Lavras; Programa de Pós-Graduação em Biotecnologia Vegetal; UFLA; brasil; Não especifica vinculação com nenhum departamento
• Palavras-chave em Português: Solos - Salinidade; Multi-ômica; Salinidade; Estresse abiótico; Soils - Salinity; Multi-omics; Abiotic stress; Genética Vegetal
• Link de acesso: http://repositorio.ufla.br/jspui/handle/1/48315

Soil salinity is one of the abiotic stresses that most threaten agriculture. This stress is present in over 100 countries around the world. Due to an estimated global population increase to around 9 billion people in 2050, and the consequent increase in the demand for agricultural products, the pressure to use these areas has increased. The general objective of the present study was to apply single and integrated analysis strategies of omics data from transcriptomics and metabolomics to gain knowledge about the molecular mechanisms responsible for the salinity tolerance observed in Gliricidia sepium and Portulaca oleracea. To this end, data from the "Sal da Terra" database, belonging to the RD&I program of the same name developed at Embrapa Agroenergia, was used, which includes phenomic, ionomic, genomic, transcriptomic (mRNA and microRNA), metabolomic and proteomic data featuring the response of oil palm (Elaeis guineensis), purslane (Portulaca oleracea) and gliricidia (Gliricidia sepium) to salt stress. The transcriptome samples were submitted to an RNA-Seq analysis using an Illumina HiSeq platform using the paired-end strategy and the data analysis with the OmicsBox software version 1.3. Metabolome samples were analyzed on a UHPLC system equipped with a reversed-phase column. High-resolution mass spectrometry (HRMS) was performed on a Q-TOF analyzer using an electrospray source in ESI (+) - MS and ESI (-) - MS. The acquired data was pre-processed using XCMS Online and later exported to MetaboAnalyst for statistical analysis, annotation, and observation of metabolic pathways. The Omics Fusion platform was used to perform the integrative analysis between transcripts and metabolites. The results have allowed us to correlate and differentiate groups of plants subjected to salt stress, revealing genes/transcripts, metabolites, and responsive pathways to this stress, both in gliricidia and purslane.