Rice yield is a complex trait controlled by quantitative trait loci (QTLs). In the past three decades, thousands of QTLs for rice yield traits have been detected, but only a very small percentage has been cloned to date, as identifying the QTL genes requires a substantial investment of time and money. Meta-analysis provides a simple, reliable, and economical method for integrating information from multiple QTL studies across various environmental and genetic backgrounds, detecting consistent QTLs powerfully and estimating their genetic positions precisely. In this study, we aimed to locate consistent QTL regions associated with rice panicle traits by applying a genome-wide QTL meta-analysis approach. We first conducted a QTL analysis of 5 rice panicle traits using 172 plants in 2011 and 138 plants in 2012 from an F2 population derived from a cross between Nipponbare and H71D rice cultivators. A total of 54 QTLs were detected, and these were combined with 1085 QTLs collected from 82 previous studies to perform a meta-analysis using BioMercator v4.2. The integration of 82 maps resulted in a consensus map with 6970 markers and a total map length of 1823.1 centimorgan (cM), on which 837 QTLs were projected. These QTLs were then integrated into 87 meta-quantitative trait loci (MQTLs) by meta-analysis, and the 95 % confidence intervals (CI) of them were smaller than the mean value of the original QTLs. Also, 30 MQTLs covered 47 of the 54 QTLs detected from the cross between Nipponbare and H71D in this study. Among them, the two major and stable QTLs, spp10.1 and sd10.1, were found to be included in MQTL10.4. The three other major QTLs, pl3.1, sb2.1, and sb10.1, were included in MQTL3.3, MQTL2.2, and MQTL10.3, respectively. A total of 21 of the 87 MQTLs’ phenotypic variation were >20 %. In total, 24 candidate genes were found in 15 MQTLs that spanned physical intervals <0.2 Mb, including genes that have been cloned previously, e.g., EP3, LP, MIP1, HTD1, DSH1, and OsPNH1. However, it would be beneficial to identify a greater number of candidate genes from these MQTLs. Mining new genes that modulate yield and its related traits would assist researchers to better understand the relevant molecular mechanisms. The MQTLs found in this study that have small physical and genetic intervals are useful not only for marker-assisted selection and pyramiding, but they also provide important information of rice yield and related gene mining for future research.

Genetic analysis revealed that narrow leaf, small panicle, thin and slender stems as well as low fertility rate of an Indica rice variety were recessive traits and controlled by a single gene. Applying map-based cloning strategy, a novel narrow leaf gene, which was named nal11 was delimited to an interval of 58.3 kb between the InDel markers N10 and InD5016. There are 9 genes in the mapping interval, and only a heat shock DNAJ protein encode gene (0s07g09450) has a specific G to T SNP, which was occurred at the last base of the second exon of 0s07g09450 in ZYX. 5' and 3' RACE result shown that there were two transcripts in NAL11, and the SNP in nal11 leads to a variable shear of mRNA. In addition, this type of mRNA alternative splicing together with a stop codon closely followed the SNP which caused termination of translation destroyed the DNAJ domain of nal11's product. These results suggested that the heat shock DNAJ gene was most likely to be the candidate gene of nal11. The results of RT-PCR and real-time PCR further verified that the SNP in the ZYX-nal11 gene affects mRNA splicing pattern. Phenotype of ZYX may be caused by a statistically significant reduction in the total number of small veins in leaf, size and number of small vascular bundles and cells in stems, similar to several previous reported mutations. The basic molecular information we provide here will be useful for further investigations of the physiological function of the heat shock DNAJ gene, which will be helpful in better understanding the role of the DNAJ family in regulation of plant type traits such as leaf width of rice. (C) 2016 Elsevier Inc. All rights reserved.

Genetic diversity of 299 inbred indica rice varieties, including 33 introduced varieties, applied in Guangdong Province of China were assessed using 20 ILP (intron length polymorphism) and 34 SSR (simple sequence repeat) markers. Totally, 154 loci were screened for the 299 varieties, with the average number of alleles (Na), rare alleles (Nr), and polymorphism information content (PIC) scored at 3.4, 0.7 and 0.32, respectively. The Nei's genetic distance (GD) was estimated ranging from 0 to 0.7529 with an average of 0.4797. There was no significant difference of Na, Nr, PIC or GDs between the introduced and local varieties. Neighbor-joining (NJ) analysis showed that the 299 varieties failed into three main distinct groups, and the 33 introduced varieties were distributed over all the groups or subgroups. Model-based cluster analysis demonstrated that only 73 (24.4%) of the 299 varieties and 7 (21.2%) of the 33 introduced varieties could be distinctly classified into the three groups. Analysis of molecular variance showed that within the groups divided by NJ analysis, the genetic variations revealed by ILP, SSR and these two combined were 7.7%, 5.6% and 6.6%, and within the groups divided by region (Guangdong local and the introduced varieties), the genetic variables were 2.1%, 4.6%, 5.4%, respectively. These results suggested that the genetic diversity of the 299 inbred rice varieties in Guangdong Province was low, simultaneously relationship among varieties was poor and close in all kind of groups. Hence, it is very necessary to extend the genetic diversity during the breeding and selection practical procedure.

To know the appearance of lesion mimic in a rice accession and understand the inheritance of its le-sion mimic,Kangbaiyouzhan (Kbyz),an indica rice landrace,was researched in this study.Lesion observation,ge-netic analysis and gene mapping were applied in this study.It was found that Kbyz showed brown lesions firstly on middle leaves of the plants from booting stage,no matter it was planted at early season or late season.By genetic a-nalysis,its lesion phenotype was found to be controlled by a single recessive gene,named lm-(t)tentatively,which was further mapped on the long arm of chromosome 1 1 using SSR and InDel markers.No genes response for rice le-sion mimic are reported from chromosome 1 1 thus far,the gene in this study may be a novel lesion mimic gene.

Rice yield potential is closely related to panicle traits. QTLs for five panicle traits including panicle length, number of primary branches, number of secondary branches, spikelets per panicle and seed setting density were identified by using 172 plants and 138 plants from a F2 population derived from a cross between Nipponbare and H71D in 2011 and 2012 respectively. A total of 38 QTLs were detected in the two trials, including 21 QTLs in 2011 and 17 QTLs in 2012, of them four QTLs(only 10.5%) were repeatedly detected in both years. Some QTLs controlling different traits shared the same maker interval on the chromosome with each other, which was consistent with their significant phenotypic correlations. QTLs with large effects are easily to be detected in kinds of populations and different environments. These QTLs provide useful information for meta-analysis and fine mapping, as well as MAS for high-yield rice breeding.