Seed shape and size are among the most important agronomic traits because they affect yield and market price. To obtain accurate seed size data, a large number of measurements are needed because there is little difference in size among seeds from one plant. To promote genetic analysis and selection for seed shape in plant breeding, efficient, reliable, high-throughput seed phenotyping methods are required. We developed SmartGrain software for high-throughput measurement of seed shape. This software uses a new image analysis method to reduce the time taken in the preparation of seeds and in image capture. Outlines of seeds are automatically recognized from digital images, and several shape parameters, such as seed length, width, area, and perimeter length, are calculated. To validate the software, we performed a quantitative trait locus (QTL) analysis for rice (Oryza sativa) seed shape using backcrossed inbred lines derived from a cross between japonica cultivars Koshihikari and Nipponbare, which showed small differences in seed shape. SmartGrain removed areas of awns and pedicels automatically, and several QTLs were detected for six shape parameters. The allelic effect of a QTL for seed length detected on chromosome 11 was confirmed in advanced backcross progeny; the cv Nipponbare allele increased seed length and, thus, seed weight. High-throughput measurement with SmartGrain reduced sampling error and made it possible to distinguish between lines with small differences in seed shape. SmartGrain could accurately recognize seed not only of rice but also of several other species, including Arabidopsis (Arabidopsis thaliana). The software is free to researchers.

The alteration of photoperiod sensitivity has let breeders diversify flowering time in Oryza sativa (rice) and develop cultivars adjusted to a range of growing season periods. Map-based cloning revealed that the rice flowering-time quantitative trait locus (QTL) Heading date 16 (Hd16) encodes a casein kinase-I protein. One non-synonymous substitution in Hd16 resulted in decreased photoperiod sensitivity in rice, and this substitution occurred naturally in an old rice cultivar. By using near-isogenic lines with functional or deficient alleles of several rice flowering-time genes, we observed significant digenetic interactions between Hd16 and four other flowering-time genes (Ghd7, Hd1, DTH8 and Hd2). In a near-isogenic line with the weak-photoperiod-sensitivity allele of Hd16, transcription levels of Ehd1, Hd3a, and RFT1 increased under long-day conditions, and transcription levels of Hd3a and RFT1 decreased under short-day conditions. Expression analysis under continuous light and dark conditions showed that Hd16 was not likely to be associated with circadian clock regulation. Biochemical characterization indicated that the functional Hd16 recombinant protein specifically phosphorylated Ghd7. These results demonstrate that Hd16 acts as an inhibitor in the rice flowering pathway by enhancing the photoperiod response as a result of the phosphorylation of Ghd7.

Full-length cDNA (FLcDNA) libraries consisting of 172,000 clones were constructed from a two-row malting barley cultivar (Hordeum vulgare 'Haruna Nijo') under normal and stressed conditions. After sequencing the clones from both ends and clustering the sequences, a total of 24,783 complete sequences were produced. By removing duplicates between these and publicly available sequences, 22,651 representative sequences were obtained: 17,773 were novel barley FLcDNAs, and 1,699 were barley specific. Highly conserved genes were found in the barley FLcDNA sequences for 721 of 881 rice (Oryza sativa) trait genes with 50% or greater identity. These FLcDNA resources from our Haruna Nijo cDNA libraries and the full-length sequences of representative clones will improve our understanding of the biological functions of genes in barley, which is the cereal crop with the fourth highest production in the world, and will provide a powerful tool for annotating the barley genome sequences that will become available in the near future.

Climate change affects agricultural productivity worldwide. Increased prices of food commodities are the initial indication of drastic edible yield loss, which is expected to increase further due to global warming. This situation has compelled plant scientists to develop climate change-resilient crops, which can withstand broad-spectrum stresses such as drought, heat, cold, salinity, flood, submergence and pests, thus helping to deliver increased productivity. Genomics appears to be a promising tool for deciphering the stress responsiveness of crop species with adaptation traits or in wild relatives toward identifying underlying genes, alleles or quantitative trait loci. Molecular breeding approaches have proven helpful in enhancing the stress adaptation of crop plants, and recent advances in high-throughput sequencing and phenotyping platforms have transformed molecular breeding to genomics-assisted breeding (GAB). In view of this, the present review elaborates the progress and prospects of GAB for improving climate change resilience in crops, which is likely to play an ever increasing role in the effort to ensure global food security.

Flowering time of rice depends strongly on photoperiodic responses. We previously identified a quantitative trait locus, Heading date 17 (Hd17), that is associated with a difference in flowering time between Japanese rice (Oryza sativa L.) cultivars. Here, we show that the difference may result from a single nucleotide polymorphism within a putative gene that encodes a homolog of the Arabidopsis EARLY FLOWERING 3 protein, which plays important roles in maintaining circadian rhythms. Our results demonstrate that natural variation in Hd17 may change the transcription level of a flowering repressor, Grain number, plant height and heading date 7 (Ghd7), suggesting that Hd17 is part of rice's photoperiodic flowering pathway.

Over the past two decades, genetic dissection of complex phenotypes of economic and biological interest has revealed the chromosomal locations of many quantitative trait loci (QTLs) in rice and their contributions to phenotypic variation. Mapping resolution has varied considerably among QTL studies owing to differences in population size and number of DNA markers used. Additionally, the same QTLs have often been reported with different locus designations. This situation has made it difficult to determine allelic relationships among QTLs and to compare their positions. To facilitate reliable comparisons of rice QTLs, we extracted QTL information from published research papers and constructed a database of 1,051 representative QTLs, which we classified into 21 trait categories. This database (QTL Annotation Rice Online database; Q-TARO, http://qtaro.abr.affrc.go.jp/) consists of two web interfaces. One interface is a table containing information on the mapping of each QTL and its genetic parameters. The other interface is a genome viewer for viewing genomic locations of the QTLs. Q-TARO clearly displays the co-localization of QTLs and distribution of QTL clusters on the rice genome.

SummaryAgriculture is now facing the ‘perfect storm’ of climate change, increasing costs of fertilizer and rising food demands from a larger and wealthier human population. These factors point to a global food deficit unless the efficiency and resilience of crop production is increased. The intensification of agriculture has focused on improving production under optimized conditions, with significant agronomic inputs. Furthermore, the intensive cultivation of a limited number of crops has drastically narrowed the number of plant species humans rely on. A new agricultural paradigm is required, reducing dependence on high inputs and increasing crop diversity, yield stability and environmental resilience. Genomics offers unprecedented opportunities to increase crop yield, quality and stability of production through advanced breeding strategies, enhancing the resilience of major crops to climate variability, and increasing the productivity and range of minor crops to diversify the food supply. Here we review the state of the art of genomic‐assisted breeding for the most important staples that feed the world, and how to use and adapt such genomic tools to accelerate development of both major and minor crops with desired traits that enhance adaptation to, or mitigate the effects of climate change.

Target-site and non-target-site herbicide tolerance are caused by the prevention of herbicide binding to the target enzyme and the reduction to a nonlethal dose of herbicide reaching the target enzyme, respectively. There is little information on the molecular mechanisms involved in non-target-site herbicide tolerance, although it poses the greater threat in the evolution of herbicide-resistant weeds and could potentially be useful for the production of herbicide-tolerant crops because it is often involved in tolerance to multiherbicides. Bispyribac sodium (BS) is an herbicide that inhibits the activity of acetolactate synthase. Rice (Oryza sativa) of the indica variety show BS tolerance, while japonica rice varieties are BS sensitive. Map-based cloning and complementation tests revealed that a novel cytochrome P450 monooxygenase, CYP72A31, is involved in BS tolerance. Interestingly, BS tolerance was correlated with CYP72A31 messenger RNA levels in transgenic plants of rice and Arabidopsis (Arabidopsis thaliana). Moreover, Arabidopsis overexpressing CYP72A31 showed tolerance to bensulfuron-methyl (BSM), which belongs to a different class of acetolactate synthase-inhibiting herbicides, suggesting that CYP72A31 can metabolize BS and BSM to a compound with reduced phytotoxicity. On the other hand, we showed that the cytochrome P450 monooxygenase CYP81A6, which has been reported to confer BSM tolerance, is barely involved, if at all, in BS tolerance, suggesting that the CYP72A31 enzyme has different herbicide specificities compared with CYP81A6. Thus, the CYP72A31 gene is a potentially useful genetic resource in the fields of weed control, herbicide development, and molecular breeding in a broad range of crop species.