Genetic dissection of the relationships between grain yield components by genome-wide association mapping in a collection of tetraploid wheats

PLoS One. 2018 Jan 11;13(1):e0190162. doi: 10.1371/journal.pone.0190162. eCollection 2018.

Abstract

Increasing grain yield potential in wheat has been a major target of most breeding programs. Genetic advance has been frequently hindered by negative correlations among yield components that have been often observed in segregant populations and germplasm collections. A tetraploid wheat collection was evaluated in seven environments and genotyped with a 90K SNP assay to identify major and stable quantitative trait loci (QTL) for grain yield per spike (GYS), kernel number per spike (KNS) and thousand-kernel weight (TKW), and to analyse the genetic relationships between the yield components at QTL level. The genome-wide association analysis detected eight, eleven and ten QTL for KNS, TKW and GYS, respectively, significant in at least three environments or two environments and the mean across environments. Most of the QTL for TKW and KNS were found located in different marker intervals, indicating that they are genetically controlled independently by each other. Out of eight KNS QTL, three were associated to significant increases of GYS, while the increased grain number of five additional QTL was completely or partially compensated by decreases in grain weight, thus producing no or reduced effects on GYS. Similarly, four consistent and five suggestive TKW QTL resulted in visible increase of GYS, while seven additional QTL were associated to reduced effects in grain number and no effects on GYS. Our results showed that QTL analysis for detecting TKW or KNS alleles useful for improving grain yield potential should consider the pleiotropic effects of the QTL or the association to other QTLs.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Genes, Plant*
  • Genome-Wide Association Study*
  • Quantitative Trait Loci
  • Tetraploidy*
  • Triticum / genetics*

Grants and funding

This research was supported by grants from MIUR, Italy, projects ‘PON-01_01145 – ISCOCEM’ to AG.