Rice blast disease is one of the most serious and recurrent problems in rice-growing regions worldwide. Most resistance genes were identified by linkage mapping using genetic populations. We extensively examined 16 rice blast strains and a further genome-wide association study based on genotyping 0.8 million single nucleotide polymorphism variants across 366 diverse indica accessions. Totally, thirty associated loci were identified. The strongest signal (Chr11_6526998, P =1.17 × 10−17) was located within the gene Os11g0225100, one of the rice Pia-blast resistance gene. Another association signal (Chr11_30606558) was detected around the QTL Pif. Our study identified the gene Os11g0704100, a disease resistance protein containing nucleotide binding site-leucine rich repeat domain, as the main candidate gene of Pif. In order to explore the potential mechanism underlying the blast resistance, we further examined a locus in chromosome 12, which was associated with CH149 (P =7.53 × 10−15). The genes, Os12g0424700 and Os12g0427000, both described as kinase-like domain containing protein, were presumed to be required for the full function of this locus. Furthermore, we found some association on chromosome 3, in which it has not been reported any loci associated with rice blast resistance. In addition, we identified novel functional candidate genes, which might participate in the resistance regulation. This work provides the basis of further study of the potential function of these candidate genes. A subset of true associations would be weakly associated with outcome in any given GWAS; therefore, large-scale replication is necessary to confirm our results. Future research will focus on validating the effects of these candidate genes and their functional variants using genetic transformation and transferred DNA insertion mutant screens, to verify that these genes engender resistance to blast disease in rice.

The whitebacked planthopper (WBPH), Sogatella furcifera Horváth, is a serious rice pest in Asia. Ovicidal resistance is a natural rice defense mechanism against WBPH and is characterized by the formation of watery lesions (WLs) and increased egg mortality (EM) at the WBPH oviposition sites.

A region containing three genes on chromosome 1 of indica rice was associated with cold tolerance at the bud burst stage; these results may be useful for breeding cold-tolerant lines.

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.

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.