Genome-Wide Association Study Identifies Genomic Regions for Important Morpho-Agronomic Traits in Mesoamerican Common Bean.

Douglas Mariani Zeffa,Paul Gepts,Luriam Aparecida Brandão Ribeiro,José Dos Santos Neto,Alison Fernando Nogueira,Jessica Delfini,Paulo Maurício Ruas,Vânia Moda-Cirino,Leandro Simões Azeredo Gonçalves

doi:10.3389/fpls.2021.748829

Abstract

The population growth trend in recent decades has resulted in continuing efforts to guarantee food security in which leguminous plants, such as the common bean (Phaseolus vulgaris L.), play a particularly important role as they are relatively cheap and have high nutritional value. To meet this demand for food, the main target for genetic improvement programs is to increase productivity, which is a complex quantitative trait influenced by many component traits. This research aims to identify Quantitative Trait Nucleotides (QTNs) associated with productivity and its components using multi-locus genome-wide association studies. Ten morpho-agronomic traits [plant height (PH), first pod insertion height (FPIH), number of nodules (NN), pod length (PL), total number of pods per plant (NPP), number of locules per pod (LP), number of seeds per pod (SP), total seed weight per plant (TSW), 100-seed weight (W100), and grain yield (YLD)] were evaluated in four environments for 178 Mesoamerican common bean domesticated accessions belonging to the Brazilian Diversity Panel. In order to identify stable QTNs, only those identified by multiple methods (mrMLM, FASTmrMLM, pLARmEB, and ISIS EM-BLASSO) or in multiple environments were selected. Among the identified QTNs, 64 were detected at least thrice by different methods or in different environments, and 39 showed significant phenotypic differences between their corresponding alleles. The alleles that positively increased the corresponding traits, except PH (for which lower values are desired), were considered favorable alleles. The most influenced trait by the accumulation of favorable alleles was PH, showing a 51.7% reduction, while NN, TSW, YLD, FPIH, and NPP increased between 18 and 34%. Identifying QTNs in several environments (four environments and overall adjusted mean) and by multiple methods reinforces the reliability of the associations obtained and the importance of conducting these studies in multiple environments. Using these QTNs through molecular techniques for genetic improvement, such as marker-assisted selection or genomic selection, can be a strategy to increase common bean production.

Highlights

More than 24 million tons of common beans (Phaseolus vulgaris L.) are produced per year worldwide, and the main producing countries are located in Asia and the Americas (Rawal and Navarro, 2019)
As for heritability estimates (h2), the total seed weight per plant (TSW), number of nodules (NN), number of pods per plant (NPP), and first pod insertion height (FPIH) traits presented moderate values, between 0.54 and 0.68, while high values were detected for the other traits, YLD, seeds per pod (SP), and locules per pod (LP) had h2-values between 0.71 and 0.77, and plant height (PH), pod length (PL), and W100 had the highest values, 0.88, 0.94, and 0.94, respectively
Several studies already identified Quantitative Trait Nucleotides (QTNs) associated with morpho-agronomic traits in common beans using Genome-Wide Association Studies (GWAS) (Nemli et al, 2014; Kamfwa et al, 2015; Moghaddam et al, 2016; Soltani et al, 2016; Nascimento et al, 2018; Resende et al, 2018; Lei et al, 2020; Wu et al, 2020), panels composed exclusively of common beans of Mesoamerican origin and adapted to environmental conditions in Brazil had not been sufficiently explored (Valdisser et al, 2020)

Summary

Introduction

More than 24 million tons of common beans (Phaseolus vulgaris L.) are produced per year worldwide, and the main producing countries are located in Asia and the Americas (Rawal and Navarro, 2019). This crop is mainly grown by small producers, often in low fertility areas with low-level technology, resulting in low mean productivity (Broughton et al, 2003). Increasing productivity is one of the main objectives of breeding programs. In this context, understanding the genetic constitution related to the productivity and of the production components are the basis for improvement (Kamfwa et al, 2015). Physiological and morphological characteristics such as days to flowering and maturity and resistance to pod shattering significantly impact adaptability, biomass, and productivity (Zhang et al, 2015; Parker et al, 2020a)

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