The paste viscosity attributes of starch, measured by rapid visco analyzer (RVA), are important factors for the evaluation of the cooking and eating qualities of rice in breeding programs.  To determine the genetic roots of the paste viscosity attributes of rice grains, quantitative trait loci (QTLs) associated with the paste viscosity attributes were mapped, using a double haploid (DH) population derived from Zhongjiazao 17 (YK17), a super rice variety, crossed with D50, a tropic japonica variety.  Fifty-four QTLs, for seven parameters of the RVA profiles, were identified in three planting seasons.  The 54 QTLs were located on all of the 12 chromosomes, with a single QTL explaining 5.99 to 47.11% of phenotypic variation.  From the QTLs identified, four were repeatedly detected under three environmental conditions and the other four QTLs were repeated under two environments.  Most of the QTLs detected for peak viscosity (PKV), trough viscosity (TV), cool paste viscosity (CPV), breakdown viscosity (BDV), setback viscosity (SBV), and peak time (PeT) were located in the interval of RM6775–RM3805 under all three environmental conditions, with the exception of pasting temperature (PaT).  For digenic interactions, eight QTLs with six traits were identified for additive×environment interactions in all three planting environments.  The epistatic interactions were estimated only for PKV, SBV and PaT.  The present study will facilitate further understanding of the genetic architecture of eating and cooking quality (ECQ) in the rice quality improvement program.

 

Cadmium (Cd) contamination in rice has been a hot topic of research because of its potential risk to human health.  In this study, a double haploid (DH) population derived from Zhongjiazao 17 (YK17) (an early-season indica cultivar)×D50 (a tropical japonica cultivar) was used to identify quantitative trait loci (QTLs) associated with Cd concentration in brown rice (CCBR) and Cd concentration in milled rice (CCMR).  Continuous and wide variation for CCBR and CCMR were observed among the DH population.  Correlation analysis revealed a positive and highly significant correlation between the two traits.  A total of 18 QTLs for CCBR and 14 QTLs for CCMR were identified in five different pot and field trials.  Two pairs of QTLs for CCBR (qCCBR2-1 and qCCBR2-2, qCCBR9-1 and qCCBR9-2) and one pair of QTLs for CCMR (qCCMR5-1 and qCCMR5-2) were detected in multiple trials.  The alleles increasing CCBR at the qCCBR2-1/qCCBR2-2 and qCCBR9-1/qCCBR9-2 QTLs were contributed by YK17 and D50, respectively, whereas the D50 allele at the qCCMR5-1/qCCMR5-2 QTLs increased CCMR.  Eight pairs of QTLs for CCBR and CCMR, qCCBR2-2 and qCCMR2-2, qCCBR3 and qCCMR3, qCCBR4-2 and qCCMR4-1, qCCBR4-3 and qCCMR4-2, qCCBR4-4 and qCCMR4-3, qCCBR5 and qCCMR5-2, qCCBR7 and qCCMR7, and qCCBR11-1 and qCCMR11-2, co-localized on chromosomes 2, 3, 4, 5, 7, and 11, respectively.  For all of these QTL pairs, except qCCBR5/qCCMR5-2, the additive effects came from YK17.  In addition, four CCMR QTLs showing significant additive×environment interaction and two pairs of CCMR QTLs with bi-allelic epistatic interactions were identified.  The results of this study could facilitate marker-assisted selection of breeding rice varieties with low Cd accumulation in grain.