Search

As one of the most widely grown crops in the world, rice is not only a staple food but also a source of calorie intake for more than half of the world’s population, occupying an important position in China’s agricultural production. Thus, determining the inner potential connections between the genetic mechanisms and phenotypes of rice using dynamic analyses with high-throughput, nondestructive, and accurate methods based on high-throughput crop phenotyping facilities associated with rice genetics and breeding research is of vital importance. In this work, we developed a strategy for acquiring and analyzing 58 image-based traits (i-traits) during the whole growth period of rice. Up to 84.8% of the phenotypic variance of the rice yield could be explained by these i-traits. A total of 285 putative quantitative trait loci (QTLs) were detected for the i-traits, and principal components analysis was applied on the basis of the i-traits in the temporal and organ dimensions, in combination with a genome-wide association study that also isolated QTLs. Moreover, the differences among the different population structures and breeding regions of rice with regard to its phenotypic traits demonstrated good environmental adaptability, and the crop growth and development model also showed high inosculation in terms of the breeding-region latitude. In summary, the strategy developed here for the acquisition and analysis of image-based rice phenomes can provide a new approach and a different thinking direction for the extraction and analysis of crop phenotypes across the whole growth period and can thus be useful for future genetic improvements in rice.

The traits of rice panicles play important roles in yield assessment, variety classification, rice breeding, and cultivation management. Most traditional grain phenotyping methods require threshing and thus are time-consuming and labor-intensive; moreover, these methods cannot obtain 3D grain traits. In this work, based on X-ray computed tomography, we proposed an image analysis method to extract twenty-two 3D grain traits. After 104 samples were tested, the R2 values between the extracted and manual measurements of the grain number and grain length were 0.980 and 0.960, respectively. We also found a high correlation between the total grain volume and weight. In addition, the extracted 3D grain traits were used to classify the rice varieties, and the support vector machine classifier had a higher recognition accuracy than the stepwise discriminant analysis and random forest classifiers. In conclusion, we developed a 3D image analysis pipeline to extract rice grain traits using X-ray computed tomography that can provide more 3D grain information and could benefit future research on rice functional genomics and rice breeding.

Abstract We cloned and characterized the full-length coding sequence of a small heat shock (sHSP) gene, PfHSP17.2, from Primula forrestii leaves following heat stress treatment. Homology and phylogenetic analysis suggested that PfHSP17.2 is a cytosolic class II sHSP, which was further supported by the cytosolic localization of transient expression of PfHSP17.2 fused with green fluorescent protein reporter. Expression analysis showed that PfHSP17.2 was highly inducible by heat stress in almost all the vegetative and generative tissues and was expressed under salt, cold, and oxidative stress conditions as well. Moreover, the expression of PfHSP17.2 in P. forrestii was detected in certain developmental growth stages. Transgenic Arabidopsis thaliana constitutively expressing PfHSP17.2 displayed increased thermotolerance and higher resistance to salt and cold compared with wild type plants. It is suggested that PfHSP17.2 plays a key role in heat and other abiotic stresses.

Background: Influenza is a global public health problem for its detrimental impact on human health. Annual vaccination is the most effective prevention of influenza infection. Identifying host genetic factors associated with the responsiveness to influenza vaccines can provide clues for developing more effective influenza vaccines. In this study, we aimed to explore whether the single nucleotide polymorphisms in BAT2 are associated with the antibody responses to influenza vaccines.Method: A nested case-control study was conducted in this research. 1968 healthy volunteers were enrolled and 1,582 of them from a Chinese Han population were eligible for further research. According to the hemagglutination inhibition titers of subjects against all influenza vaccine strains, a total of 227 low responders and 365 responders were included in the analysis. Six tag single nucleotide polymorphisms in the coding region of BAT2 were selected and genotyped using the MassARRAY technology platform. Univariable and multivariable analyses were conducted to evaluate the relationship between variants and antibody responses to influenza vaccination.Results: Multivariable logistic regression analysis showed that, compared with the BAT2 rs1046089GG genotype, the GA + AA genotype was correlated with decreased risk of low responsiveness to influenza vaccines after adjusting for gender and age (p = 1.12E-03, OR = .562, 95%CI: .398–.795). rs9366785 GA + AA genotype was associated with a higher risk of low responsiveness to influenza vaccination compared with the GG genotype (p = .003, OR = 1.854, 95%CI: 1.229–2.799). The haplotype consisting of BAT2 rs2280801-rs10885-rs1046089-rs2736158-rs1046080-rs9366785 CCAGAG was correlated with a higher level of antibody response to influenza vaccines compared with haplotype CCGGAG (p < .001, OR = .37, 95%CI: .23–.58).Conclusion: Genetic variants in BAT2 were statistically associated with the immune response to influenza vaccination among the Chinese population. Identifying these variants will provide clues for further research on novel broad-spectrum influenza vaccines, and improve the individualized influenza vaccination scheme.