Breeding Science最新文献

Cytoplasmic male sterility (CMS) is widely used to control pollination in the production of commercial F₁ hybrid seed in sorghum. So far, 6 major fertility restorer genes, Rf1 to Rf6, have been reported in sorghum. Here, we fine-mapped the Rf5 locus on sorghum chromosome 5 using descendant populations of a 'Nakei MS-3A' × 'JN43' cross. The Rf5 locus was narrowed to a 140-kb region in BTx623 genome (161-kb in JN43) with 16 predicted genes, including 6 homologous to the rice fertility restorer Rf1 (PPR.1 to PPR.6). These 6 homologs have tandem pentatricopeptide repeat (PPR) motifs. Many Rf genes encode PPR proteins, which bind RNA transcripts and modulate gene expression at the RNA level. No PPR genes were detected at the Rf5 locus on the corresponding homologous chromosome of rice, foxtail millet, or maize, so this gene cluster may have originated by chromosome translocation and duplication after the divergence of sorghum from these species. Comparison of the sequences of these genes between fertile and CMS lines identified PPR.4 as the most plausible candidate gene for Rf5.

Wheat landraces have abundant genetic variation at the Glu-1 loci, which is desirable germplasms for genetic enhancement of modern wheat varieties, especially for quality improvement. In the current study, we analyzed the allelic variations of the Glu-1 loci of 597 landraces and 926 commercial wheat varieties from the four major wheat-growing regions in China using SDS-PAGE. As results, alleles Null, 7+8, and 2+12 were the dominant HMW-GSs in wheat landraces. Compared to landraces, the commercial varieties contain higher frequencies of high-quality alleles, including 1, 7+9, 14+15 and 5+10. The genetic diversity of the four commercial wheat populations (alleles per locus (A) = 7.33, percent polymorphic loci (P) = 1.00, effective number of alleles per locus (Ae) = 2.347 and expected heterozygosity (He) = 0.563) was significantly higher than that of the landraces population, with the highest genetic diversity found in the Southwestern Winter Wheat Region population. The genetic diversity of HMW-GS is mainly present within the landraces and commercial wheat populations instead of between populations. The landraces were rich in rare subunits or alleles may provide germplasm resources for improving the quality of modern wheat.

[This corrects the article DOI: 10.1270/jsbbs.20151.].

Plant phenotyping technology has been actively developed in recent years, but the introduction of these technologies into the field of agronomic research has not progressed as expected, in part due to the need for flexibility and low cost. "DIY" (Do It Yourself) methodologies are an efficient way to overcome such obstacles. Devices with modular functionality are critical to DIY experimentation, allowing researchers flexibility of design. In this study, we developed a plant conveyance system using a commercial AGV (Automated Guided Vehicle) as a case study of DIY plant phenotyping. The convey module consists of two devices, a running device and a plant-handling device. The running device was developed based on a commercial AGV Kit. The plant-handling device, plant stands, and pot attachments were originally designed and fabricated by us and our associates. Software was also developed for connecting the devices and operating the system. The run route was set with magnetic tape, which can be easily changed or rerouted. Our plant delivery system was developed with low cost and having high flexibility, as a unit that can contribute to others' DIY' plant research efforts as well as our own. It is expected that the developed devices will contribute to diverse phenotype observations of plants in the greenhouse as well as to other important functions in plant breeding and agricultural production.

Root system architecture (RSA) determines unevenly distributed water and nutrient availability in soil. Genetic improvement of RSA, therefore, is related to crop production. However, RSA phenotyping has been carried out less frequently than above-ground phenotyping because measuring roots in the soil is difficult and labor intensive. Recent advancements have led to the digitalization of plant measurements; this digital phenotyping has been widely used for measurements of both above-ground and RSA traits. Digital phenotyping for RSA is slower and more difficult than for above-ground traits because the roots are hidden underground. In this review, we summarized recent trends in digital phenotyping for RSA traits. We classified the sample types into three categories: soil block containing roots, section of soil block, and root sample. Examples of the use of digital phenotyping are presented for each category. We also discussed room for improvement in digital phenotyping in each category.

Metabolites play a central role in maintaining organismal life and in defining crop phenotypes, such as nutritional value, fragrance, color, and stress resistance. Among the 'omes' in biology, the metabolome is the closest to the phenotype. Consequently, metabolomics has been applied to crop improvement as method for monitoring changes in chemical compositions, clarifying the mechanisms underlying cellular functions, discovering markers and diagnostics, and phenotyping for mQTL, mGWAS, and metabolite-genome predictions. In this review, 359 reports of the most recent applications of metabolomics to plant breeding-related studies were examined. In addition to the major crops, more than 160 other crops including rare medicinal plants were considered. One bottleneck associated with using metabolomics is the wide array of instruments that are used to obtain data and the ambiguity associated with metabolite identification and quantification. To further the application of metabolomics to plant breeding, the features and perspectives of the technology are discussed.

Phenotyping is a critical process in plant breeding, especially when there is an increasing demand for streamlining a selection process in a breeding program. Since manual phenotyping has limited efficiency, high-throughput phenotyping methods are recently popularized owing to progress in sensor and image processing technologies. However, in a size-limited breeding field, which is common in Japan and other Asian countries, it is challenging to introduce large machinery in the field or fly unmanned aerial vehicles over the field. In this study, we developed a ground-based high-throughput field phenotyping rover that could be easily introduced to a field regardless of the scale and location of the field even without special facilities. We also made the field rover open-source hardware, making its system available to public for easy modification, so that anyone can build one for their own use at a low cost. The trial run of the field rover revealed that it allowed the collection of detailed remote-sensing images of plants and quantitative analyses based on the images. The results suggest that the field rover developed in this study could allow efficient phenotyping of plants especially in a small breeding field.

The morphological traits of plants contribute to many important functional features such as radiation interception, lodging tolerance, gas exchange efficiency, spatial competition between individuals and/or species, and disease resistance. Although the importance of plant phenotyping techniques is increasing with advances in molecular breeding strategies, there are barriers to its advancement, including the gap between measured data and phenotypic values, low quantitativity, and low throughput caused by the lack of models for representing morphological traits. In this review, we introduce morphological descriptors that can be used for phenotyping plant morphological traits. Geometric morphometric approaches pave the way to a general-purpose method applicable to single units. Hierarchical structures composed of an indefinite number of multiple elements, which is often observed in plants, can be quantified in terms of their multi-scale topological characteristics using topological data analysis. Theoretical morphological models capture specific anatomical structures, if recognized. These morphological descriptors provide us with the advantages of model-based plant phenotyping, including robust quantification of limited datasets. Moreover, we discuss the future possibilities that a system of model-based measurement and model refinement would solve the lack of morphological models and the difficulties in scaling out the phenotyping processes.