Split luciferase complementation assay to detect regulated protein-protein interactions in rice protoplasts in a large-scale format

Background

The rice interactome, in which a network of protein-protein interactions has been elucidated in rice, is a useful resource to identify functional modules of rice signal transduction pathways. Protein-protein interactions occur in cells in two ways, constitutive and regulative. While a yeast-based high-throughput method has been widely used to identify the constitutive interactions, a method to detect the regulated interactions is rarely developed for a large-scale analysis.

Results

A split luciferase complementation assay was applied to detect the regulated interactions in rice. A transformation method of rice protoplasts in a 96-well plate was first established for a large-scale analysis. In addition, an antibody that specifically recognizes a carboxyl-terminal fragment of Renilla luciferase was newly developed. A pair of antibodies that recognize amino- and carboxyl- terminal fragments of Renilla luciferase, respectively, was then used to monitor quality and quantity of interacting recombinant-proteins accumulated in the cells. For a proof-of-concept, the method was applied to detect the gibberellin-dependent interaction between GIBBERELLIN INSENSITIVE DWARF1 and SLENDER RICE 1.

Conclusions

A method to detect regulated protein-protein interactions was developed towards establishment of the rice interactome.     

Development of simple sequence repeat markers for the classification of the clubroot pathogen <Emphasis Type="Italic">Plasmodiophora brassicae</Emphasis>

Clubroot disease caused by Plasmodiophora brassicae is one of the most serious diseases in cruciferous crops. To classify isolates, we developed simple sequence repeat (SSR) markers for P. brassicae. Twenty-four Japanese isolates were used in this study: 12 isolates of an unknown pathotype from the Kyoto Prefecture, as well as 12 isolates of known pathotypes, including three single-spore lines. From the 12 isolates from Kyoto Prefecture, 11 were classified into either pathotype 2 (three isolates) or 4 (eight isolates). We designed 23 SSR markers based on the P. brassicae genome, of which 11 markers from intergenic regions showed polymorphisms in the 24 isolates. Many haploid isolates belonging to pathotypes 2 and 4 were monomorphic, and typical alleles were detected in some isolates not belonging to pathotype 4. Two bands were detected for eight SSR loci in five isolates, indicating that different genotypes were mixed in these isolates. We constructed a phylogram based on the 11 polymorphic SSRs. Pathotypes 2 and 4 formed a cluster, from which pathotypes 3 and 1 were successively placed. These results strongly suggest a close genetic relationship between isolates in pathotypes 2 and 4, consistent with our finding that isolates in these two pathotypes were found at one collection site. In combination with pathotype classification and other marker systems, the SSR markers can be used for more detailed analyses to improve the control of clubroot disease.     

Genomic evaluation using SNP‐ and haplotype‐based genomic relationship matrices in a closed line of Duroc pigs

A simulation analysis and real phenotype analysis were performed to evaluate the impact of three different relationship matrices on heritability estimation and prediction accuracy in a closed‐line breeding of Duroc pigs. The numerator relationship matrix (NRM), single nucleotide polymorphism (SNP)‐based genomic relationship matrix (GRM) (G_S), and haplotype‐based GRM (G_H) were applied in this study. We used PorcineSNP60 genotype array data (38 114 SNPs) of 831 Duroc pigs with four selection traits. In both heritability estimation and prediction accuracy, the accuracy depended on the number of animals with records. For heritability estimation, a large difference in the results among three relationship matrices was not shown, but the trend of the estimated heritabilities between GRMs, that is G_S < G_H, was shown in this population. For the accuracy of prediction values in test animals, the accuracies of prediction values obtained by two GRMs were higher than that by the NRM in this population. The accuracies obtained by GRMs using animals with no records were lower than that by the NRM using animals with their performance records, but were close to that by the NRM using animals with full‐sib testing records.     

Mapping the quantitative trait loci (QTL) for body shape and conformation measurements on BTA1 in Japanese Black cattle

The detection and mapping of segregating quantitative trait loci (QTL) that influence withers height, hip height, hip width, body length, chest width, chest depth, shoulder width, lumbar width, thurl width, pin bone width, rump length, cannon circumference, chest girth, abdominal width and abdominal girth at weaning was conducted on chromosomal regions of bovine chromosome one. The QTL analysis was performed by genotyping half‐sib progeny of five Japanese Black sires using microsatellite DNA markers. Probability coefficients of inheriting allele 1 or 2 from the sire at specific chromosomal locations were computed. The phenotypic data of progeny were regressed on these probability coefficients in a within‐common‐parent regression analysis using a linear model that included fixed effects of sex, parity and season of birth, as well as age as a covariate. F‐statistics were calculated every 1 cM on a linkage map. Permutation tests of 10 000 iterations were conducted to obtain chromosome‐wide significance thresholds. A significant QTL for chest width was detected at 91 cM in family 3. The detection of this QTL boosts the prospects of implementing marker‐assisted selection for body conformation traits in Japanese Black beef cattle.