QTL Analysis for Seven Quality Traits of&nbsp; japonica Rice&nbsp; Based on Three Genetic Statistical Models

LIU Qiangming1， JIANG Jianhua1,2， NIU Fuan1， HE Yingjun1，  HONG Delin1,*

doi:10.3969/j.issn.10017216.2012.03.005

Chinese Journal OF Rice Science >

2012 , Vol. 26 >Issue 3: 283 - 290

DOI: https://doi.org/10.3969/j.issn.10017216.2012.03.005

Research Papers

QTL Analysis for Seven Quality Traits of japonica Rice Based on Three Genetic Statistical Models

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¹ State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China; ² Institute of Crops, Anhui Academy of Agricultural Sciences, Hefei 230031, China;

Received date: 2011-06-07

Revised date: 2011-06-14

Online published: 2012-05-10

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Abstract

QTL mapping for seven quality traits was conducted by using 254 recombinant inbred lines derived from a japonicajaponica rice (Oryza sativa L.) cross of Xiushui 79/C Bao. The seven traits were grain length (GL), grain length to width ratio (LWR), percentage of grains with chalkiness (PGWC), degree of endosperm chalkiness (DEC), gelatinization temperature (GT), amylose content (AC) and gel consistency (GC) of headrice. Three mapping methods employed were composite interval mapping in QTLMapper 2.0 software based on mixed linear model (MCIM), the inclusive composite interval mapping in QTL IciMapping 3.0 software based on stepwise regression linear model (ICIM) and the multiple interval mapping with regression forward selection in Windows QTL Cartographer 2.5 based on multiple regression analysis (MIMR). Five QTLs with additive effect (AQTLs) were detected by all the three methods simultaneously, two by two methods simultaneously, and 23 by only one method. Five AQTLs were detected by MCIM, nine by ICIM and 28 by MIMR. The contribution rate of single AQTL ranged from 0.89% to 38.07%. All the QTLs with epistatic effect (EQTLs) detected by MIMR were not detected by the other two methods. Fourteen pairs of EQTLs were detected by both MCIM and ICIM, and 142 pairs of EQTLs were detected by only one method. Twentyfive pairs of EQTLs were detected by MCIM, 141 pairs by ICIM and four pairs by MIMR. The contribution rate of a single pair of EQTL was from 2.60% to 23.78%. In the XiuBao RIL population, epistatic effect played a major role in the variation of GL and DEC, and additive effect was the dominant in the variation of LWR, while epistatic effect and additive effect had equal importance in the variation of PGWC, AC, GT and GC. QTLs detected by two or more methods simultaneously were highly reliable, and could be applied to improvement of the quality in japonica hybrid rice.

Key words： japonica rice; rice quality trait; genetic statistical models; quantitative trait locus

Cite this article

LIU Qiangming1， JIANG Jianhua1,2， NIU Fuan1， HE Yingjun1， HONG Delin1,* . QTL Analysis for Seven Quality Traits of japonica Rice Based on Three Genetic Statistical Models[J]. Chinese Journal OF Rice Science, 2012 , 26(3) : 283 -290 . DOI: 10.3969/j.issn.10017216.2012.03.005

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