Meta-QTL Analysis for Yield Components in Common Bean (Phaseolus vulgaris L.)

Abstract

Common bean is one of the most important legumes produced and consumed worldwide because it is a highly valuable food for the human diet. However, its production is mainly carried out by small farmers, who obtain average grain yields below the potential yield of the species. In this sense, numerous mapping studies have been conducted to identify quantitative trait loci (QTL) associated with yield components in common bean. Meta-QTL (MQTL) analysis is a useful approach to combine data sets and for creating consensus positions for the QTL detected in independent studies. Consequently, the objective of this study was to perform a MQTL analysis to identify the most reliable and stable genomic regions associated with yield-related traits of common bean. A total of 667 QTL associated with yield-related traits reported in 21 different studies were collected. A total of 42 MQTL associated with yield-related traits were identified, in which the average confidence interval (CI) of the MQTL was 3.41 times lower than the CIs of the original QTL. Most of the MQTL (28) identified in this study contain QTL associated with yield and phenological traits; therefore, these MQTL can be useful in common bean breeding programs. Finally, a total of 18 candidate genes were identified and associated with grain yield within these MQTL, with functions related to ubiquitin ligase complex, response to auxin, and translation elongation factor activity.

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

“…for all QTL (394) and QTN (349) included in this study allowed for the comparison from independent experiments and environments and made an ideal dataset for MQTL analyses due to the high reliability of the physical markers position on the latest genome reference v2.1. One other MQTL analysis for yield and yield components is available in dry beans (Arriagada et al., 2023). However, the MQTL positions of this study were reported using the physical location of the P. vulgaris v1 genome on the genetic map Stampede x Red Hawk (Song et al., 2015), which limits the comparison across studies using the latest P. vulgaris v2.1 genome.…”

Genetic control of pod morphological traits and pod edibility in a common bean RIL population

“…A recent study mapped 42 meta-QTL associated with phenological parameters and yield components in common bean (Arriagada et al. 2022 ), where the genomic positions of QTL Yd_MQTL1.2, Yd_MQTL4.2, and Yd_MQTL4.3 overlapped with three consensus QTL (Pod1.8 Pv , Pod4.1 Pv , and Pod4.2 Pv , respectively) and the meta-QTL Yd_MQTL6.2 was located close to the consensus region Pod6.1 Pv (approximately 0.3 Mpb). The traits SW and NSP were the primary components of yield (Sinclair 2021 ); therefore, the association demonstrated the role of these regions in pod morphotypes of the common bean.…”

Genetic erosion within the Fabada dry bean market class revealed by high‐throughput genotyping

“…The lines Xana, X4562, A2806, and A4804 were originally derived from line A25 (Ferreira et al, 2017), and they carry new genes on chromosomes Pv01 (gene fin), Pv02 (gene I), Pv04 (gene Pm1), and Pv11 (gene Co-2). Major quantitative trait loci (QTLs) associated with seed weight have been reported in the 11 bean chromosomes (Arriagada et al, 2022). However, most of the Pv01, Pv09, and Pv10 regions did not show variation within the Fabada marker class (Figure S5), whereas high concentrations of SNPs were observed in regions of the chromosomes The Plant Genome Pv04,Pv05,Pv06,Pv07,Pv08,and Pv11.…”