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Accurately identifying varieties with targeted agronomic traits was thought to contribute to genetic selection and accelerate rice breeding progress. Genomic selection (GS) is a promising technique that uses markers covering the whole genome to predict the genomic-estimated breeding values (GEBV), with the ability to select before phenotypes are measured. To choose the appropriate GS models for breeding work, we analyzed the predictability of nine agronomic traits measured from a population of 459 diverse rice varieties. By the comparison of eight representative GS models, we found that the prediction accuracies ranged from 0.407 to 0.896, with reproducing kernel Hilbert space (RKHS) having the highest predictive ability in most traits. Further results demonstrated the predictivity of GS is altered by several factors. Moreover, we assessed the method of integrating genome-wide association study (GWAS) into various GS models. The predictabilities of GS combined peak-associated markers generated from six different GWAS models were significantly different; a recommendation of Mixed Linear Model (MLM)-RKHS was given for the GWAS-GS-integrated prediction. Finally, based on the above result, we experimented with applying the P-values obtained from optimal GWAS models into ridge regression best linear unbiased prediction (rrBLUP), which benefited the low predictive traits in rice. [ABSTRACT FROM AUTHOR]

Grain size and flag leaf angle are two important traits that determining grain yield in rice. However, the mechanisms regulating these two traits remain largely unknown. In this study, a rice long grain 5 (lg5) mutant with a large flag leaf angle was identified, and map-based cloning revealed that a single base substitution followed by a 2 bp insertion in the LOC_Os05g40384 gene resulted in larger grains, a larger flag leaf angle, and higher plant height than the wild type. Sequence analysis revealed that lg5 is a novel allele of elongated uppermost internode-1 (EUI1), which encodes a cytochrome P450 protein. Functional complementation and overexpression tests showed that LG5 can rescue the bigger grain size and larger flag leaf angle in the Xiushui11 (XS) background. Knockdown of the LG5 transcription level by RNA interference resulted in elevated grain size and flag leaf angle in the Nipponbare (NIP) background. Morphological and cellular analyses suggested that LG5 regulated grain size and flag leaf angle by promoting cell expansion and cell proliferation. Our results provided new insight into the functions of EUI1 in rice, especially in regulating grain size and flag leaf angle, indicating a potential target for the improvement of rice breeding. [ABSTRACT FROM AUTHOR]

Summary: The annual planting area of major inbred rice (Oryza sativa) cultivars reach more than half of the total annual planting area of inbred rice cultivars in China. However, how the major inbred rice cultivars changed during decades of genetic improvement and why they can be prevalently cultivated in China remains unclear.Here, we investigated the underlying genetic changes of major inbred cultivars and the contributions of landraces and introduced cultivars during the improvement by resequencing a collection of 439 rice accessions including major inbred cultivars, landraces, and introduced cultivars.The results showed that landraces were the main genetic contribution sources of major inbred Xian (Indica) cultivars, while introduced cultivars were that of major inbred Geng (Japonica) cultivars. Selection scans and haplotype frequency analysis shed light on the reflections of some well‐known genes in rice improvement, and breeders had different preferences for the Xian's and Geng's breeding. Six candidate regions associated with agronomic traits were identified by genome‐wide association mapping, five of which were under positive selection in rice improvement.Our study provides a comprehensive insight into the development of major inbred rice cultivars and lays the foundation for genomics‐based breeding in rice. [ABSTRACT FROM AUTHOR]

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Background: Rice rooting ability is a complex agronomical trait that displays heterosis and plays an important role in rice growth and production. Only a few quantitative trait loci (QTLs) have been identified by bi-parental population. More genes or QTLs are required to dissect the genetic architecture of rice rooting ability. Results: To characterize the genetic basis for rice rooting ability, we used a natural rice population, genotyped by a 90 K single nucleotide polymorphism (SNP) array, to identify the loci associated with rooting-related traits through the genome-wide association study (GWAS). Population structure analysis divided the natural population into two subgroups: indica and japonica. We measured four traits for evaluating rice rooting ability, namely root growth ability (RGA), maximum root length (MRL), root length (RL), and root number (RN). Using the association study in three panels consisting of one for the full population, one for indica, and one for japonica, 24 SNPs associated with rooting ability-related traits were identified. Through comparison of the relative expression levels and DNA sequences between germplasm with extreme phenotypes, results showed that LOC_Os05g11810 had non-synonymous variations at the coding region, which may cause differences in root number, and that the expression levels of LOC_Os04g09900 and LOC_Os04g10060 are closely associated with root length variation. Conclusions: Through evaluation of the rice rooting ability-related traits and the association mapping, we provided useful information for understanding the genetic basis of rice rooting ability and also identified some candidate genes and molecular markers for rice root breeding. [ABSTRACT FROM AUTHOR]

The japonica rice in Northeast China is famous because of its high quality. Eating and cooking qualities (ECQs) are the most important factors that determine cooked rice quality. However, the genetic basis of ECQ of japonica varieties in Northeast China needs further study. In this study, 200 japonica varieties that are widely distributed in Northeast China were collected to evaluate the physicochemical indices of grain ECQs. The distribution of each trait was concentrated without large variations. Correlation analysis indicated that gel consistency (GC) had a significantly negative correlation with gelatinization temperature (GT). By integrating various analyses including kinship calculation, principal component analysis (PCA), linkage disequilibrium (LD) analysis, and original parent investigation, we found that the japonica varieties in Northeast China exhibited a narrow genetic basis. An association study for grain ECQs was performed and eight quantitative trait loci (QTLs) were detected. ALK was the major locus that regulated GT and also significantly affecting GC. Through the linkage disequilibrium (LD) and expression pattern analysis, one possible candidate gene (LOC_Os02g29980) was predicted and required further research for validation. Additionally, a different allele of Wx was identified in the variety CH4126, and ALK was not fixed in these japonica varieties. These results further elucidate the genetic basis of ECQs of japonica varieties in Northeast China and provide local breeders some assistance for improving ECQs of rice grain in rice breeding. [ABSTRACT FROM AUTHOR]