Seed storability (SS) is an important trait for agronomic production and germplasm preservation in rice (Oryza sativa L.).  Quantitative trait locus (QTL) for seed storability in three storage periods was identified using two sets of recombinant inbred lines (RILs) derived from the crosses with a common female parent Shennong 265 (SN265).  Ten QTLs for seed storability were detected on chromosomes 1, 2, 3, 4, 6, 8, and 12 in SL-RILs (SN265/Lijiangxingtuanheigui (LTH)), and a total of 12 QTLs were identified on chromosomes 2, 3, 4, 6, 9, and 10 in SH-RILs (SN265/Luhui 99 (LH99)) in different storage periods.  Among these QTLs, five major QTLs were identified in more than one storage period.  The qSS3-1, qSS3-2, qSS12-1, and qSS12-2 were detected in SL-RILs.  Similarly, qSS2-2, qSS2-3, qSS6-2, qSS6-3, qSS6-4, qSS9-1, and qSS9-2 were detected in SH-RILs.  In addition, the maximum phenotypic variation was derived from the qSS6-1 and qSS9-2, explaining 53.58 and 29.09%, respectively, while qSS6-1 was a new stable QTL for seed storability.  These results provide an opportunity for pyramiding and map-based cloning major QTLs for seed storability in rice.

japonica rice is mainly distributed in Northeast China and accounts for 44.6% of the total cultivated area of japonica rice in China.  The comprehensive using of inter-subspecies heterosis is the main breeding mode of super japonica rice varieties in this region.  Improving rice quality at relative high yielding level is the current research focus.  Performing crosses between indica and japonica lines allows for the recombination of regulatory genes and genetic backgrounds, leading to complicated genetic rice quality characteristics, which can be used to explore patterns of quality improvement.  In the present study, we utilize recombinant inbred lines (RILs) derived from indica-japonica hybridization to analyze the effect factors of rice quality derived from genetic factors, which contain both regulatory genes concerning rice quality and genetic backgrounds’ random introduction frequency coming from indica (Di value), and the improvement strategy was further discussed.  The regulatory genes involved in amylase content (Wx) and nitrogen utilization efficiency (NRT1.1B) were the major factors affecting the amylose content (AC) and protein content (PC) in RILs, respectively.  Both the Di value and the major grain width gene (GS5) had regulatory effects on milled rice width (MRW) in RILs, and their interaction explained the major variance of MRW in the RILs.  With the mediation of MRW and chalkiness degree (C), Di value had a further impact on head rice rate (HR), which was relatively poor when the Di value was over 40%.  In Northeast China, the Di value should be lowered by backcrossing or multiple crosses during the breeding of indica-japonica hybridization to maintain the whole better HR and further to emphasize the use of favorable genes in individual selection.

    Grain traits are major constraints in rice production, which are key factors in determining grain yield and market values. This study used two recombinant inbred line (RIL) populations, RIL-JJ (japonica/japonica) and RIL-IJ (indica/japonica) derived from the two crosses Shennong 265/Lijiangxintuanheigu (SN265/LTH) and Shennong 265/Luhui 99 (SN265/LH99). Sixty-eight quantitative trait loci (QTLs) associated with 10 grain traits were consistently detected on the 12 chromosomes across different populations and two environments. Although 61.75% of the QTLs clustered together across two populations, only 16.17% could be detected across two populations. Eight major QTLs were detected on the 9, 10 and 12 chromosomes in RIL-JJ under two environments, a novel QTL clustered on the 10 chromosome, qGT10, qBT10 and qTGW10, have a higher percentage of explained phenotypic variation (PVE) and additive effect; 15 major QTLs were detected on the 5, 8, 9, and 11 chromosomes in RIL-IJ under two environments, a novel clustered QTL, qGT8 and qTGW8, on the 8 chromosome have a higher additive effect. Finally, the analysis of major QTL-BSA mapping narrowed the qTGW10 to a 1.47-Mb region flanked by simple sequence repeat markers RM467 and RM6368 on chromosome 10. A comparison of QTLs for grain traits in two different genetic backgrounds recombinant inbred line populations confirmed that genetic background had a significant impact on grain traits. The identified QTLs were stable across different populations and various environments, and 29.42% of QTLs controlling grain traits were reliably detected in different environments. Fewer QTLs were detected for brown rice traits than for paddy rice traits, 7 and 17 QTLs brown rice out of 25 and 43 QTLs under RIL-JJ and RIL-IJ populations, respectively. The identification of genes constituting the QTLs will help to further our understanding of the molecular mechanisms underlying grain shape.

Abundant genetic diversity and rational population structure of germplasm benefit crop breeding greatly. To investigate genetic variation among geographically diverse set of japonica germplasm, we analyzed 233 japonica rice cultivars collected from Liaoning, Jilin and Heilongjiang provinces of China, which were released from 1970 to 2011 by using 62 simple sequence repeat (SSR) markers and 8 functional gene tags related to yield. A total of 195 alleles (Na) were detected with an average of 3.61 per locus, indicating a low level of genetic diversity level among all individuals. The genetic diversity of the cultivars from Jilin Province was the highest among the three geographic distribution zones. Moreover, the genetic diversity was increased slightly with the released period of cultivars from 1970 to 2011. The analysis of molecular variance (AMOVA) revealed that genetic differentiation was more diverse within the populations than that among the populations. The neighbor-joining (NJ) tree indicated that cultivar clusters based on geographic distribution represented three independent groups, among which the cluster of cultivars from Heilongjiang is distinctly different to the cluster of cultivars from Liaoning. For the examined functional genes, two or three allelic variations for each were detected, except for IPA1 and GW2, and most of elite genes had been introgressed in modern japonica rice varieties. These results provide a valuable evaluation for genetic backgrounds of current japonica rice and will be used directly for japonica rice breeding in future.