Unraveling the complex trait of harvest index with association mapping in rice (Oryza sativa L.)

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

Research output: Contribution to journalArticle

54 Citations (Scopus)

Abstract

Harvest index is a measure of success in partitioning assimilated photosynthate. An improvement of harvest index means an increase in the economic portion of the plant. Our objective was to identify genetic markers associated with harvest index traits using 203 O. sativa accessions. The phenotyping for 14 traits was conducted in both temperate (Arkansas) and subtropical (Texas) climates and the genotyping used 154 SSRs and an indel marker. Heading, plant height and weight, and panicle length had negative correlations, while seed set and grain weight/panicle had positive correlations with harvest index across both locations. Subsequent genetic diversity and population structure analyses identified five groups in this collection, which corresponded to their geographic origins. Model comparisons revealed that different dimensions of principal components analysis (PCA) affected harvest index traits for mapping accuracy, and kinship did not help. In total, 36 markers in Arkansas and 28 markers in Texas were identified to be significantly associated with harvest index traits. Seven and two markers were consistently associated with two or more harvest index correlated traits in Arkansas and Texas, respectively. Additionally, four markers were constitutively identified at both locations, while 32 and 24 markers were identified specifically in Arkansas and Texas, respectively. Allelic analysis of four constitutive markers demonstrated that allele 253 bp of RM431 had significantly greater effect on decreasing plant height, and 390 bp of RM24011 had the greatest effect on decreasing panicle length across both locations. Many of these identified markers are located either nearby or flanking the regions where the QTLs for harvest index have been reported. Thus, the results from this association mapping study complement and enrich the information from linkage-based QTL studies and will be the basis for improving harvest index directly and indirectly in rice.

Original languageEnglish
Article numbere29350
JournalPLoS One
Volume7
Issue number1
DOIs
Publication statusPublished - Jan 23 2012

Fingerprint

harvest index
chromosome mapping
Oryza sativa
rice
Weights and Measures
Principal component analysis
Seed
Principal Component Analysis
Climate
Genetic Markers
Seeds
Economics
quantitative trait loci
Alleles
Oryza
kinship
photosynthates
Population
seed set
heading

ASJC Scopus subject areas

  • Medicine(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

Cite this

Unraveling the complex trait of harvest index with association mapping in rice (Oryza sativa L.). / Li, Xiaobai; Yan, Wengui; Agrama, Hesham; Jia, Limeng; Jackson, Aaron; Moldenhauer, Karen; Yeater, Kathleen; McClung, Anna; Wu, Dianxing.

In: PLoS One, Vol. 7, No. 1, e29350, 23.01.2012.

Research output: Contribution to journalArticle

Li, X, Yan, W, Agrama, H, Jia, L, Jackson, A, Moldenhauer, K, Yeater, K, McClung, A & Wu, D 2012, 'Unraveling the complex trait of harvest index with association mapping in rice (Oryza sativa L.)', PLoS One, vol. 7, no. 1, e29350. https://doi.org/10.1371/journal.pone.0029350
Li, Xiaobai ; Yan, Wengui ; Agrama, Hesham ; Jia, Limeng ; Jackson, Aaron ; Moldenhauer, Karen ; Yeater, Kathleen ; McClung, Anna ; Wu, Dianxing. / Unraveling the complex trait of harvest index with association mapping in rice (Oryza sativa L.). In: PLoS One. 2012 ; Vol. 7, No. 1.
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