Grain size and shape are important components of grain yield and quality and have been under selection since cereals were first domesticated. Here, we show that a quantitative trait locus GW8 is synonymous with OsSPL16, which encodes a protein that is a positive regulator of cell proliferation. Higher expression of this gene promotes cell division and grain filling, with positive consequences for grain width and yield in rice. Conversely, a loss-of-function mutation in Basmati rice is associated with the formation of a more slender grain and better quality of appearance. The correlation between grain size and allelic variation at the GW8 locus suggests that mutations within the promoter region were likely selected in rice breeding programs. We also show that a marker-assisted strategy targeted at elite alleles of GS3 and OsSPL16 underlying grain size and shape can be effectively used to simultaneously improve grain quality and yield.

Naturally occurring allelic variations underlying complex traits are useful resources for the functional analysis of plant genes. To facilitate the genetic analysis of complex traits and the use of marker-assisted breeding in rice, we developed a wide population consisting of 217 chromosome single-segment substitution lines (SSSLs) using Oryza sativa L. 'Hua-Jing-Xian74' (HJX74), an elite Indica cultivar, as recipient, and 6 other accessions, including 2 Indica and 4 Japonica, as donors. Each SSSL contains a single substituted chromosome segment derived from 1 of the 6 donors in the genetic background of HJX74. The total size of the substituted segments in the SSSL population was 4695.0 cM, which was 3.1 times that of rice genome. To evaluate the potential application of these SSSLs for quantitative trait loci detection, phenotypic variations of the quantitative traits of days to heading and grain length in the population consisting of 210 SSSLs were observed under natural environmental conditions. The results demonstrated that there was a wide range of phenotypic variation in the traits in the SSSL population. These genetic materials will be powerful tools to dissect complex traits into a set of monogenic loci and to assign phenotypic values to different alleles at the locus of interest.

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A novel population consisting of 35 single-segment substitution lines (SSSLs) originating from crosses between the recipient parent, Hua-jing-xian 74 (HJX74), and 17 donor parents was evaluated in six cropping season environments to reveal the genetic basis of genetic main effect (G) and genotype-by-environment interaction effect (GE) for panicle number (PN) in rice. Subsets of lines were grown in up to six environments. An indirect analysis method was applied, in which the total genetic effect was first partitioned into G and GE by using the mixed linear-model approach, and then QTL (quantitative trait locus) analyses on these effects were conducted separately. At least 18 QTLs for PN in rice were detected and identified on 9 of 12 rice chromosomes. A single QTL effect (a + ae) ranging from -1.5 to 1.2 was divided into two components, additive effect (a) and additive x environment interaction effect (ae). A total number of 9 and 16 QTLs were identified with a ranging from -0.4 to 0.6 and ae ranging from -1.0 to 0.6, respectively, the former being stable but the latter unstable across environments. Three types of QTLs were suggested according to their effects expressed. Two QTLs (Pn-1b and Pn-6d) expressed stably across environments due to the association with only a, nine QTLs (Pn-1a, Pn-3c, Pn-3d, Pn-4, Pn-6a, Pn-6b, Pn-8, Pn-9 and Pn-12) with only ae were unstable, and the remaining seven of QTLs were identified with both a and ae, which also were unstable across environments. This is the first report on the detection of QE (QTL-by-environment interaction effect) of QTLs with SSSLs. Our results illustrate the efficiency of characterizing QTLs and analyzing action of QTLs through SSSLs, and further demonstrate that QE is an important property of many QTLs. Information provided in this paper could be used in the application of marker-assisted selection to manipulate PN in rice.

Background Stigma exsertion rate (SER) is a key determinant for the outcrossing ability of male sterility lines (MSLs) in hybrid rice seed production. In the process of domestication, the outcrossing ability of cultivated rice varieties decreased, while that of wild Oryza species kept strong. Here, we detected the quantitative trait loci (QTLs) controlling SER using a set of single-segment substitution lines (SSSLs) derived from O. glumaepatula, a wild Oryza species. Results Seven QTLs for SER were located on 5 chromosomes. qSER-1a and qSER-1b were located on chromosome 1. qSER-3a and qSER-3b were mapped on chromosome 3, and qSER-3b was further located at an estimated interval of 898.8 kb by secondary substitution mapping. qSER-5, qSER-9 and qSER-10 were identified on chromosomes 5, 9 and 10, respectively, and qSER-9 was delimited to an estimated region of 551.9 kb by secondary substitution mapping. The additive effects of the 7 QTLs ranged from 10.6% to 14.8%, which were higher than those of most loci for SER reported previously. Conclusions qSER-1a and qSER-1b are novel loci for SER on chromosome 1. All of the 7 QTLs have major effects on SER. The major QTLs of SER will help to develop MSLs with strong outcrossing ability.