Exploring genetic architecture of grain yield and quality traits in a 16-way indica by japonica rice MAGIC global population

Sci Rep. 2019 Dec 20;9(1):19605. doi: 10.1038/s41598-019-55357-7.

Abstract

Identification of Quantitative Trait Loci (QTL) has been a challenge for complex traits due to the use of populations with narrow genetic base. Most of QTL mapping studies were carried out from crosses made within the subspecies, either indica × indica or japonica × japonica. In this study we report advantages of using Multi-parent Advanced Generation Inter-Crosses global population, derived from a combination of eight indica and eight japonica elite parents, in QTL discovery for yield and grain quality traits. Genome-wide association study and interval mapping identified 38 and 34 QTLs whereas Bayesian networking detected 60 QTLs with 22 marker-marker associations, 32 trait-trait associations and 65 marker-trait associations. Notably, nine known QTLs/genes qPH1/OsGA20ox2, qDF3/OsMADS50, PL, QDg1, qGW-5b, grb7-2, qGL3/GS3, Amy6/Wx gene and OsNAS3 were consistently identified by all approaches for nine traits whereas qDF3/OsMADS50 was co-located for both yield and days-to-flowering traits on chromosome 3. Moreover, we identified a number of candidate QTLs in either one or two analyses but further validations will be needed. The results indicate that this new population has enabled identifications of significant QTLs and interactions for 16 traits through multiple approaches. Pyramided recombinant inbred lines provide a valuable source for integration into future breeding programs.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bayes Theorem
  • Chromosome Mapping
  • Chromosomes, Plant
  • Crosses, Genetic
  • Edible Grain / genetics*
  • Edible Grain / growth & development
  • Flowers
  • Genetic Association Studies*
  • Genome, Plant
  • Genotype
  • Oryza / genetics*
  • Oryza / growth & development
  • Phenotype
  • Polymorphism, Single Nucleotide
  • Quantitative Trait Loci*
  • Species Specificity