Genetic architecture of variation in heading date among Asian rice accessions

BMC Plant Biol. 2015 May 8:15:115. doi: 10.1186/s12870-015-0501-x.

Abstract

Background: Heading date, a crucial factor determining regional and seasonal adaptation in rice (Oryza sativa L.), has been a major selection target in breeding programs. Although considerable progress has been made in our understanding of the molecular regulation of heading date in rice during last two decades, the previously isolated genes and identified quantitative trait loci (QTLs) cannot fully explain the natural variation for heading date in diverse rice accessions.

Results: To genetically dissect naturally occurring variation in rice heading date, we collected QTLs in advanced-backcross populations derived from multiple crosses of the japonica rice accession Koshihikari (as a common parental line) with 11 diverse rice accessions (5 indica, 3 aus, and 3 japonica) that originate from various regions of Asia. QTL analyses of over 14,000 backcrossed individuals revealed 255 QTLs distributed widely across the rice genome. Among the detected QTLs, 128 QTLs corresponded to genomic positions of heading date genes identified by previous studies, such as Hd1, Hd6, Hd3a, Ghd7, DTH8, and RFT1. The other 127 QTLs were detected in different chromosomal regions than heading date genes.

Conclusions: Our results indicate that advanced-backcross progeny allowed us to detect and confirm QTLs with relatively small additive effects, and the natural variation in rice heading date could result from combinations of large- and small-effect QTLs. We also found differences in the genetic architecture of heading date (flowering time) among maize, Arabidopsis, and rice.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Alleles
  • Chromosomes, Plant / genetics
  • Crosses, Genetic
  • Ecotype*
  • Flowers / genetics*
  • Flowers / physiology*
  • Models, Genetic
  • Oryza / genetics*
  • Oryza / physiology*
  • Photoperiod
  • Physical Chromosome Mapping
  • Quantitative Trait Loci / genetics
  • Reproducibility of Results