Diversidad genética y estructura poblacional en maíz templado argentino a través de métodos de filogenética computacional

In maize, genetic diversity and population structure assessment by using new sequencing technologies is crucial since inbreeding reduces not only the fitness, but also the production-associated traits. The present work aims to evaluate the genetic diversity and genetic structure of a panel of 191 in...

Descripción completa

Detalles Bibliográficos
Autores principales: Perdomo, Santiago I., Baricalla, Agustín Ariel, Iglesias, Juliana
Formato: Conferencia
Lenguaje:Español
Publicado: Asociación de Ingenieros Agrónomos del Norte de la Provincia de Buenos Aires 2024
Materias:
Acceso en línea:http://hdl.handle.net/20.500.12123/16790
Descripción
Sumario:In maize, genetic diversity and population structure assessment by using new sequencing technologies is crucial since inbreeding reduces not only the fitness, but also the production-associated traits. The present work aims to evaluate the genetic diversity and genetic structure of a panel of 191 inbred lines from the Maize Breeding Program at EEA INTA Pergamino with the widely-used Illumina MaizeSNP50 BeadChip. To that end, two different Bayesian methodologies were investigated: STRUCTURE and fastSTRUCTURE altogether with NJ and UPGMA clustering methods. t-SNE was used for data visualization. Clustering results were validated by comparison with pedigree and heterotic pattern information. Population structure analysis provided an estimated K=10 groups (subpopulations) constituted by genotypes derived from families of syn. hybrid Pioneer, syn. BS13P, syn. 34 from INTA Leales, from AX882(F2) and M11 (F2), lines derived from P465 among some other mixed groups. Fst values from the 10-subpopulations ranged from 0.43-0.75, with an overall Fst=0.6 indicating a medium to a high amount of genetic differentiation. Therefore, inbreds from each subpopulation can be crossed and tested for heterosis. Overall, these results showed substantial genetic variability that could be exploited to obtain new maize varieties to meet future challenges. Important information is also provided for future genome wide association studies and marker-assisted selection.