QTL mapping and multi-environment QTL analysis on a full-sib population of Megathyrsus maximus

• Ano de defesa: 2024
• Autor(a) principal: Ferreira, Getúlio Caixeta
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: Autopoliploide; Autopolyploid; Forage; Forrageira; Interação QTL-por-ambientes; Interaction QTL-by-environment; Mapeamento de QTL; QTL mapping
• Link de acesso: https://www.teses.usp.br/teses/disponiveis/11/11137/tde-06122024-082904/

Guinea grass (Megathyrsus maximus) is recognized for its high productivity and nutritional value. It is extensively used as livestock forage due to its ability to thrive in diverse environmental conditions and is an excellent alternative for intensive pasture systems. As a forage crop, breeding programs aim mainly to increase yield and improve nutritional quality for animal production. This study searched for QTLs associated with yield and nutritional traits in a full-sib population of M. maximus. These traits included total green matter, total dry matter, leaf dry matter, stem dry matter, leaf ratio, regrowth score, leaf growth rate, leaf width, canopy diameter, canopy height, leaf organic matter, leaf crude protein, leaf neutral detergent fiber, leaf acid detergent fiber, in vitro digestibility of leaf organic matter, leaf lignin, leaf cellulose, leaf silica, stem organic matter, stem crude protein, stem neutral detergent fiber, stem acid detergent fiber, in vitro digestibility of stem organic matter, stem lignin, stem cellulose and stem silica. The full-sib population comprised of 210 individuals generated from the crossing of Miage and S12 was evaluated in two locations and ten harvests. We performed the phenotypic analysis using three models to compute jointly adjusted means to QTL detection, within-location adjusted means to perform the multi-location QTL analysis, and finally, individually adjusted means (within locations and harvest) to perform the multi-harvest within-location QTL analysis. We detected 18 QTLs associated with 13 traits: five yield-related traits, two leaf nutritional-related traits, and six stem nutritional-related traits. We developed a model for QTL-by-environment analysis in autopolyploid species and used it to study the QTL-byenvironment interaction across locations and harvests. Most QTLs presented consistent responses across locations, and a few QTLs expressed effects in only one location. The interaction QTL-byharvest was more significant than the QTL-by-location for most of the QTLs investigated in this study. The insights provided in this study on the genetic architecture of relevant traits can help define strategies applied to the breeding of the crop.