Examinando por Materia "GENOMAS"

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    Análisis del genoma de influenza aviar H7N3 de la Epizootia 2012-2015 en México
    (Universidad EAFIT, 2017) Figueroa Varela, Paula Andrea; Martínez Barnetche, Jesús
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    Evaluating different computational routines for the assembly of mitochondrial genomes using long reads from Oxford Nanopore
    (Universidad EAFIT, 2022) Corrales Orozco, Mariana; Díaz Nieto, Juan Fernando
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    Genomic Prediction and Genome-Wide Association Analysis in Common Bean (Phaseolus vulgaris l.) × Tepary bean (P. acutifolius a. gray) Inter-specific Advanced Lines at the Caribbean Coast of Colombia
    (Universidad EAFIT, 2023) López Hernández, Luis Felipe; Villanueva Mejía, Diego Fernando; Cortés Vera, Andrés Javier
    The negative effects of the climate change are risking global food security with 828 million people facing hunger, which is almost 16 times the population of Colombia. Given this scenario, legumes as common bean has offered a nature-based solution to source nutrients for rural communities in Latin America thanks to their high content of nutrients. For this reason, it is imperative to speed up the molecular genetic breading of common beans so that they can be cultivated in regions affected by extreme climate change, one of which is coastal Colombian. Therefore, in order to bridge this gap, this study aimed coupling an advanced panel of common bean (Phaseolus vulgaris L.) × tepary bean (P. acutifolius A. Gray) inter-specific lines with Bayesian regression algorithms to identify novel sources of adaptation to the humid and dry sub-regions at the Caribbean coast of Colombia, where common bean typically exhibits maladaptation to extreme heat waves. A total of 87 advanced lines with inter-specific ancestries were genotyped by sequencing (GBS), leading to the discovery of 15,645 single-nucleotide polymorphism (SNP) markers. Three yield components and two biomass variables were recorded for each genotype and inputted in several Bayesian regression models to identify the top genotypes with the best genetic breeding values across three localities in coastal Colombia. We explored the comparative analysis of several regression approaches where the model with the best performance in all traits and environments was BayesC. Also, we compared the utilization of all markers and only those determined as associated by a priori GWAS models. Better prediction ability with the complete SNP set was indicative of missing heritability as part of GWAS reconstructions. Furthermore, optimal SNP sets per environment and trait were determined to the top 500 most explicative markers according to their β regression effects. These 500 SNPs on average overlapped in 5.24 % across localities, which reinforced the environmentally dependent nature of polygenic adaptation. Finally, we retrieved the genomic estimated breeding values (GEBVs), and selected the top 10 genotypes for each environment and trait as part of a recommendation scheme targeting narrow adaption. The genotypes and SNP markers identified in this study as candidates for abiotic stress have the potential to be used in the following cycles as part of the long-term bean breeding program for coastal tropical regions.