QTL Analysis of Rice Peduncle Vascular Bundle System and Panicle Traits

A double haploid (DH) population of rice (Oryza sativa L.) derived from anther culture of ZYQ8/JX17, a typical indica and japonica hybrid, was used for genetic analysis of rice peduncle vascular system and panicle traits. The number of large vascular bundles (LVB), the number of small vascular bundles (SVB) in the peduncle, and the panicle traits including the number of primary rachis branches (PRB), the number of spikelets per panicle (SNP), peduncle top diameter (PTD), and panicle length (PL) were investigated in the parents and DH lines. The quantitative trait loci (QTLs) for each trait were analyzed based on the constructed molecular linkage map of this population. Three QTLs for LVB (qLVB_1, qLVB_6 and qLVB_7) were detected on chromosomes 1, 6, and 7, respectively. Two putative QTLs for SVB (qSVB_4 and qSVB_6) were mapped on chromosomes 4 and 6 respectively. Four QTLs (qPRB_4a, qPRB_4b, qPRB_6 and qPRB_7) on chromosomes 4, 6, and 7, respectively, were detected for PRB. Three QTLs (qSPN_4a, qSPN_4b and qSPN_6) were identified on chromosomes 4 and 6, respectively, which could significantly affect SPN. Five QTLs for PTD (qPTD_2, qPTD_5, qPTD_6, qPTD_8 and qPTD_12) were identified on chromosomes 2, 5, 6, 8, and 12, respectively. Three QTLs for PL (qPL_4, qPL_6 and qPL_8) were detected on chromosomes 4, 6, and 8, respectively. Clustering of QTLs, such as qLVB_6, qSVB_6, qSNP_6, qPTD_6, and qPL_6 detected in the interval G122_G1314b on chromosome 6, was found. These results suggest that some QTLs for peduncle vascular bundle system are possibly responsible for the panicle traits.

Mapping QTLs for Panicle Traits Based on Rice RIL Population Derived from TD70 and Kasalath

Two hundred and forty recombinant inbred lines （RIL） derived from a cross TD70/Kasalath and its linkage map including 141 SSR markers were used to map QTLs controlling panicle length （PL）, total seeds per panicle （TSP） and grain density （GD） in 2010 and 2011. The results showed that a total of 23 QTLs controlling three panicle traits were detected on chromosomes 2, 3, 4, 6, 7, 8 and 10, respec- tively, including 5 QTLs controlling PL, 8 QTLs controlling TSP, 10 QTLs controlling GD, with the LOD value ranging between 2.5-9.3, and the QTLs explained the ob- served phenotypic by 4.0%-20.8%. The marker interval RM5699-RM424 on chro- mosome 2, RM489-RM1278 on chromosome 3, RM3367-RM1018 on chromosome 4, RM3343-RM412 on chromosome 6 were common marker intervals for TSP and GD; six QTLs （qPL3, qTSP4, qTSP6-2, qTSP7, qGD3-2 and qGDT） were detected in two years. Among these QTLs, the qPL3, qTSP6-2, qGD3-2 and qGD7 were major QTLs. All QTLs for PL mapped in the present study had been mapped QTLs previously by other research groups, 16 QTLs controlling TSP and GD were new ones which contributed the observed phenotypic variance range by 4%-9.5%. These results laid a founda^ion for further fine positioning or cloning these QTLs.

Combining Ability Analysis of Panicle Traits in Six CIMMYT Maize Inbred Lines

In this study, six CIMMYT maize inbred lines and five representative do- mestic maize inbred lines were used as parental lines. By using incomplete diallel cross design, 30 hybrid combinations were developed to analyze the general com- bining ability （GCA）, specific combining ability （SCA） and total combining ability （TCA） of seven panicle traits in six CIMMYT maize inbred lines. The results showed that CIMBL98 and GEMS13 were excellent inbred lines with good compre- hensive performance; CIMBL98 × 340 and GEMS13×Chang 7-2 were superior combinations.

QTLs analysis of rice peduncle vascular bundle and panicle traits

The vascular bundle in plants plays an important role intransportation of photosynthetic products, mineral nutri-ents, water, arid so on. Significant positive correlationswere found between grain yield, panicle traits and the No.of peduncle vascular bundles. So, it is very important tostudy the inheritance of peduncle vascular bundle, whichis a quantitative trait.

Genome-Wide Association Studies Reveal New Genetic Targets for Five Panicle Traits of International Rice Varieties

Narrow genetic background is a key limiting factor in breeding stable high-yielding rice. The introduction and utilization of international rice core germplasm is an important way to increase the genetic diversity of domestic rice varieties. We conducted a genome-wide association study on 5 panicle traits of 315 rice accessions introduced from the international rice micro-core germplasm bank. Based on the tests from Yangzhou of China and Arkansas of American, environment exhibited a significant impacts on panicle length and primary branch number, while grain length, grain width and grain length/width ratio were insensitive to environment changes. We discovered a total of 7, 5, 10, 8 and 6 chromosomal regions or single nucleotide polymorphism marker loci that were significantly associated with primary branch number, panicle length, grain length, grain width and grain length/width ratio, respectively. Among them, eleven regions were associated with grain shape and one region associated with primary branch number, showing the good consistence in two different environments. Significant linear correlation was discovered between the average trait value and the number of favorable alleles carried by the varieties in all associated loci. Among the associated loci, varieties in aromatic and tropical japonica sub-groups possessed most favorable alleles, while those in temperate japonica sub-group contained the least. The domestic varieties mainly harbored unfavorable alleles in six of the associated loci being detected. On the contrary, 15 varieties from 11 different countries harbored more favorable alleles （as many as 30 or more） than the others. Remarkably, all these 15 varieties belonged to the tropical japonica sub-group. In conclusion, our study demonstrates that varieties in the tropical japonica sub-group had high potentials for breeding stable high-yielding rice. Based on this discovery, we proposed a new approach for improving the panicle traits of domestic rice by using tropical japonica varieties.

An integrated rice panicle phenotyping method based on X-ray and RGB scanning and deep learning

Rice panicle phenotyping is required in rice breeding for high yield and grain quality.To fully evaluate spikelet and kernel traits without threshing and hulling,using X-ray and RGB scanning,we developed an integrated rice panicle phenotyping system and a corresponding image analysis pipeline.We compared five methods of counting spikelets and found that Faster R-CNN achieved high accuracy(R~2 of 0.99)and speed.Faster R-CNN was also applied to indica and japonica classification and achieved 91%accuracy.The proposed integrated panicle phenotyping method offers benefit for rice functional genetics and breeding.

Relationship between Grain Yield and Yield Components of Various Rice Cultivars

[Objective] The relationship between grain yield and yield components was investigated in .different rice cultivars at the target yield of 10.5-11.25 t/hm2, to provide theoretical basis for cultivation of high-yield rice. [Method] The yield performance of various super rice and non-super rice cultivars that were cultivated in large area in Sichuan Chengdu was studied under high-yielding cultivation conditions from 2006 to 2008. [Result] The rice yield was closely correlated with the productive panicle number, grain number per panicle, seed setting rate and 1 000-grain weight. The four yield components showed different influences on the yield of different rice culti- vars. By adopting the high yielding cultivation technology （that the seedlings were planted in a triangle shape） at the target yield of 10.5-11.25 t/hm~, we found that the rice yield of super rice cultivars was closely correlated with productive panicle number and 1 000-grain weight, negatively correlated with grain number per panicle, and significantly negatively correlated with seed setting rate; the grain yield of non- super rice cultivars was negatively correlated with grain number per panicle and seed setting rate, and significantly negatively correlated with the productive panicle number and 1 000-grain weight. [Conclusion] The results revealed the relationship between grain yield and yield components in different rice cultivars, which provided references for developing reasonable cultivation measures and thus to improve the yield of super rice in large acreage.

OsGRF4 controls grain shape, panicle length and seed shattering in rice

Traits such as grain shape, panicle length and seed shattering, play important roles in grain yield and harvest. In this study, the cloning and functional analysis of PANICLE TRAITS 2 （PT2）, a novel gene from the Indica rice Chuandali （CDL）, is reported. PT2 is synonymous with Growth-Regulating Factor 4 （OsGRF4）, which encodes a growth-regulating factor that positively regulates grain shape and panicle length and negatively regulates seed shattering. Higher expression of OsGRF4 is correlated with larger grain, longer panicle and lower seed shattering. A unique OsGRF4 mutation, which occurs at the OsmiRNA396 target site of OsGRF4, seems to be associated with high levels of OsGRF4 expression, and results in phenotypic difference. Further research showed that OsGRF4 regulated two cytokinin dehydrogenase precursor genes （CKX5 and CKX1） resulting in increased cytokinin levels, which might affect the panicle traits. High storage capacity and moderate seed shattering of OsGRF4 may be useful in high-yield breeding and mechanized harvesting of rice. Our findings provide additional insight into the molecular basis of panicle growth.

Novel pleiotropic loci controlling panicle architecture across environments in japonica rice (Oryza sativa L.)

To identify quantitative trait loci （QTLs） controlling panicle architecture in japonica rice, a genetic map was constructed based on simple sequence repeat （SSR） markers and 254 recombinant inbred lines （RILs） derived from a cross between cultivars Xiushui 79 and C Ban. Seven panicle traits were investigated under three environments. Single marker analysis indicated that a total of 27 SSR markers were highly associated with panicle traits in all the three environments. Percentage of phenotypic variation explained by single locus varied from 2% to 35%. Based on the mixed linear model, a total of 40 additive QTLs for seven panicle traits were detected by composite interval mapping, explaining 1.2%--35% ofphenotypic variation. Among the 9 QTLs with more than 10% of explained phenotypic variation, two QTLs were for the number of primary branches per panicle （NPB）, two for panicle length （PL）, two for spikelet density （SD）, one for the number of secondary branches per panicle （NSB）, one for secondary branch distribution density （SBD）, and one for the num- ber of spikelets per panicle （NS）, respectively, qPLSD-9-1 and qPLSD-9-2 were novel pleiotropic loci, showing effects on PL and SD simultaneously, qPLSD-9-1 explained 34.7% of the phenotypic variation for PL and 25.4% of the phenotypic variation for SD, respec- tively, qPLSD-9-2 explained 34.9% and 24.4% of the phenotypic variation for PL and SD, respectively. The C Bao alleles at the both QTLs showed positive effects on PL, and the Xiushui 79 alleles at the both QTLs showed positive effects on SD. Genetic variation of panicle traits are mainly attributed to additive effects. QTLx environment interactions were not significant for additive QTLs and additive x additive QTL pairs.