Genetic Correlation Between Fe and Zn Biofortification and Yield Components in a Common Bean (Phaseolus vulgaris L.)

Abstract

Common bean (Phaseolus vulgaris L.) is the most important legume for direct human consumption worldwide. It is a rich and relatively inexpensive source of proteins and micronutrients, especially iron and zinc. Bean is a target for biofortification to develop new cultivars with high Fe/Zn levels that help to ameliorate malnutrition mainly in developing countries. A strong negative phenotypic correlation between Fe/Zn concentration and yield is usually reported, posing a significant challenge for breeders. The objective of this study was to investigate the genetic relationship between Fe/Zn. We used Quantitative Trait Loci (QTLs) mapping and Genome-Wide Association Studies (GWAS) analysis in three bi-parental populations that included biofortified parents, identifying genomic regions associated with yield and micromineral accumulation. Significant negative correlations were observed between agronomic traits (pod harvest index, PHI; pod number, PdN; seed number, SdN; 100 seed weight, 100SdW; and seed per pod, Sd/Pd) and micronutrient concentration traits (SdFe and SdZn), especially between pod harvest index (PHI) and SdFe and SdZn. PHI presented a higher correlation with SdN than PdN. Seventy-nine QTLs were identified for the three populations: 14 for SdFe, 12 for SdZn, 13 for PHI, 11 for SdN, 14 for PdN, 6 for 100SdW, and 9 for Sd/Pd. Twenty-three hotspot regions were identified in which several QTLs were co-located, of which 13 hotpots displayed QTL of opposite effect for yield components and Fe/Zn accumulation. In contrast, eight QTLs for SdFe and six QTLs for SdZn were observed that segregated independently of QTL of yield components. The selection of these QTLs will enable enhanced levels of Fe/Zn and will not affect the yield performance of new cultivars focused on biofortification.

Combination of meta‐analysis of QTL and GWAS to uncover the genetic architecture of seed yield and seed yield components in common bean

“…Although the reported correlation between SW with PHI is not strong (Diaz et al, 2022), and sometimes negative (Kamfwa et al, 2015), we identified that 80% (25) of the MQTL-YC that involved QTL for PHI overlap with QTL reported for SW. Furthermore, a strong correlation between PHI and seed number has been reported (Teran et al, 2019;Diaz et al, 2022), indicating that sink strength is higher for seed number than for seed weight.…”

“…Although the reported correlation between SW with PHI is not strong (Diaz et al, 2022), and sometimes negative (Kamfwa et al, 2015), we identified that 80% (25) of the MQTL-YC that involved QTL for PHI overlap with QTL reported for SW. Furthermore, a strong correlation between PHI and seed number has been reported (Teran et al, 2019;Diaz et al, 2022), indicating that sink strength is higher for seed number than for seed weight. However, the number of seeds per pod is more sensitive to abiotic stresses such as drought and heat, (Teran et al, 2019;Diaz et al, 2022), which could lead to partitioning in a reduced number of seeds increasing the seed size under drought stress (Diaz et al, 2020;Mukeshimana et al, 2014).…”

“…Furthermore, a strong correlation between PHI and seed number has been reported (Teran et al, 2019;Diaz et al, 2022), indicating that sink strength is higher for seed number than for seed weight. However, the number of seeds per pod is more sensitive to abiotic stresses such as drought and heat, (Teran et al, 2019;Diaz et al, 2022), which could lead to partitioning in a reduced number of seeds increasing the seed size under drought stress (Diaz et al, 2020;Mukeshimana et al, 2014). Middle American genotypes tend to have more pods, more seeds and a greater ability to mobilize photosynthates to pod production and seed filling compared with Andean genotypes (Kelly, 2001;, while Andean cultivars tend to have larger seeds than Middle American (Kelly, 2001).…”

Phenotype based clustering, and diversity of common bean genotypes in seed iron concentration and cooking time

“…This is because the negative association of FESEED and ZNSEED to YDHA may not allow a single population improvement strategy without any penalties. Thirteen co-located quantitative trait loci (QTL) that would negatively influence yield components and FESEED and ZNSEED were reported, but several QTL for FESEED (eight) and ZNSEED (six) also segregated independently of yield components, which showed the possibility of improving the three traits concurrently [ 44 ]. For COOKT and YDHA, the weak correlation [r = -0.01] showed unlikely yield penalty during breeding for fast cooking beans if careful breeding and selection decisions are made.…”

Breeding implications of nodulation performance and root structure under natural inoculation for soil fertility enhancement and sustainable cowpea production

“…These results suggest that improvement in any of these traits will lead to an increase through indirect selection for grain yield of cowpea in marginal environments. Kashiwagi et al (2006) and Diaz et al (2022) reported that grain yield significantly and positively correlated with root length and density in chickpeas under terminal drought stress. Moreover, grain yield was significantly positively correlated (phenotypic correlation) with stem diameter, total number of basal roots, taproot width and taproot branching density.…”