Mapping QTLs for improving grain yield using the USDA rice mini-core collection

Xiaobai Li, Wengui Yan, Hesham Agrama, Limeng Jia, Xihong Shen, Aaron Jackson, Karen Moldenhauer, Kathleen Yeater, Anna McClung, Dianxing Wu

Research output: Contribution to journalArticle

54 Citations (Scopus)

Abstract

Yield is the most important and complex trait for genetic improvement in crops, and marker-assisted selection enhances the improvement efficiency. The USDA rice mini-core collection derived from over 18,000 accessions of global origins is an ideal panel for association mapping. We phenotyped 203 O. sativa accessions for 14 agronomic traits and identified 5 that were highly and significantly correlated with grain yield per plant: plant height, plant weight, tillers, panicle length, and kernels/branch. Genotyping with 155 genome-wide molecular markers demonstrated 5 main cluster groups. Linkage disequilibrium (LD) decayed at least 20 cM and marker pairs with significant LD ranged from 4.64 to 6.06% in four main groups. Model comparisons revealed that different dimensions of principal component analysis affected yield and its correlated traits for mapping accuracy, and kinship did not improve the mapping in this collection. Thirty marker-trait associations were highly significant, 4 for yield, 3 for plant height, 6 for plant weight, 9 for tillers, 5 for panicle length and 3 for kernels/branch. Twenty-one markers contributed to the 30 associations, because 8 markers were co-associated with 2 or more traits. Allelic analysis of OSR13, RM471 and RM7003 for their co-associations with yield traits demonstrated that allele 126 bp of RM471 and 108 bp of RM7003 should receive greater attention, because they had the greatest positive effect on yield traits. Tagging the QTLs responsible for multiple yield traits may simultaneously help dissect the complex yield traits and elevate the efficiency to improve grain yield using marker-assisted selection in rice.

Original languageEnglish
Pages (from-to)347-361
Number of pages15
JournalPlanta
Volume234
Issue number2
DOIs
Publication statusPublished - Aug 2011

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United States Department of Agriculture
USDA
quantitative trait loci
grain yield
rice
Linkage Disequilibrium
linkage disequilibrium
tillers
marker-assisted selection
branches
Weights and Measures
Principal Component Analysis
kinship
Alleles
Oryza
seeds
Genome
agronomic traits
genotyping
genetic improvement

Keywords

  • Association mapping
  • Germplasm
  • Grain yield
  • Linkage disequilibrium (LD)
  • Rice

ASJC Scopus subject areas

  • Plant Science
  • Genetics

Cite this

Mapping QTLs for improving grain yield using the USDA rice mini-core collection. / Li, Xiaobai; Yan, Wengui; Agrama, Hesham; Jia, Limeng; Shen, Xihong; Jackson, Aaron; Moldenhauer, Karen; Yeater, Kathleen; McClung, Anna; Wu, Dianxing.

In: Planta, Vol. 234, No. 2, 08.2011, p. 347-361.

Research output: Contribution to journalArticle

Li, X, Yan, W, Agrama, H, Jia, L, Shen, X, Jackson, A, Moldenhauer, K, Yeater, K, McClung, A & Wu, D 2011, 'Mapping QTLs for improving grain yield using the USDA rice mini-core collection', Planta, vol. 234, no. 2, pp. 347-361. https://doi.org/10.1007/s00425-011-1405-0
Li, Xiaobai ; Yan, Wengui ; Agrama, Hesham ; Jia, Limeng ; Shen, Xihong ; Jackson, Aaron ; Moldenhauer, Karen ; Yeater, Kathleen ; McClung, Anna ; Wu, Dianxing. / Mapping QTLs for improving grain yield using the USDA rice mini-core collection. In: Planta. 2011 ; Vol. 234, No. 2. pp. 347-361.
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