Diversity of Gibberellin 2-oxidase genes in the barley genome offers opportunities for genetic improvement.

INTRODUCTION: Gibberellin (GA) is a vital phytohormone in regulating plant growth and development. During the "Green Revolution", modification of GA-related genes created semi-dwarfing phenotype in cereal crops but adversely affected grain weight. Gibberellin 2-oxidases (GA2oxs) in barley act as key catabolic enzymes in deactivating GA, but their functions are still less known. OBJECTIVES: This study investigates the physiological function of two HvGA2ox genes in barley and identifies novel semi-dwarf alleles with minimum impacts on other agronomic traits. METHODS: Virus-induced gene silencing and CRISPR/Cas9 technology were used to manipulate gene expression of HvGA2ox9 and HvGA2ox8a in barley and RNA-seq was conducted to compare the transcriptome between wild type and mutants. Also, field trials in multiple environments were performed to detect the functional haplotypes. RESULTS: There were ten GA2oxs that distinctly expressed in shoot, tiller, inflorescence, grain, embryo and root. Knockdown of HvGA2ox9 did not affect plant height, while ga2ox8a mutants generated by CRISPR/Cas9 increased plant height and significantly altered seed width and weight due to the increased bioactive GA4 level. RNA-seq analysis revealed that genes involved in starch and sucrose metabolism were significantly decreased in the inflorescence of ga2ox8a mutants. Furthermore, haplotype analysis revealed one naturally occurring HvGA2ox8a haplotype was associated with decreased plant height, early flowering and wider and heavier seed. CONCLUSION: Our results demonstrate the potential of manipulating GA2ox genes to fine tune GA signalling and biofunctions in desired plant tissues and open a promising avenue for minimising the trade-off effects of Green Revolution semi-dwarfing genes on grain size and weight. The knowledge will promote the development of next generation barley cultivars with better adaptation to a changing climate.

New semi-dwarfing alleles with increased coleoptile length by gene editing of gibberellin 3-oxidase 1 using CRISPR-Cas9 in barley (Hordeum vulgare L.).

The green revolution was based on genetic modification of the gibberellin (GA) hormone system with "dwarfing" gene mutations that reduces GA signals, conferring shorter stature, thus enabling plant adaptation to modern farming conditions. Strong GA-related mutants with shorter stature often have reduced coleoptile length, discounting yield gain due to their unsatisfactory seedling emergence under drought conditions. Here we present gibberellin (GA) 3-oxidase1 (GA3ox1) as an alternative semi-dwarfing gene in barley that combines an optimal reduction in plant height without restricting coleoptile and seedling growth. Using large-scale field trials with an extensive collection of barley accessions, we showed that a natural GA3ox1 haplotype moderately reduced plant height by 5-10 cm. We used CRISPR/Cas9 technology, generated several novel GA3ox1 mutants and validated the function of GA3ox1. We showed that altered GA3ox1 activities changed the level of active GA isoforms and consequently increased coleoptile length by an average of 8.2 mm, which could provide essential adaptation to maintain yield under climate change. We revealed that CRISPR/Cas9-induced GA3ox1 mutations increased seed dormancy to an ideal level that could benefit the malting industry. We conclude that selecting HvGA3ox1 alleles offers a new opportunity for developing barley varieties with optimal stature, longer coleoptile and additional agronomic traits.

Manipulating GA-Related Genes for Cereal Crop Improvement.

The global population is projected to experience a rapid increase in the future, which poses a challenge to global food sustainability. The "Green Revolution" beginning in the 1960s allowed grain yield to reach two billion tons in 2000 due to the introduction of semi-dwarfing genes in cereal crops. Semi-dwarfing genes reduce the gibberellin (GA) signal, leading to short plant stature, which improves the lodging resistance and harvest index under modern fertilization practices. Here, we reviewed the literature on the function of GA in plant growth and development, and the role of GA-related genes in controlling key agronomic traits that contribute to grain yield in cereal crops. We showed that: (1) GA is a significant phytohormone in regulating plant development and reproduction; (2) GA metabolism and GA signalling pathways are two key components in GA-regulated plant growth; (3) GA interacts with other phytohormones manipulating plant development and reproduction; and (4) targeting GA signalling pathways is an effective genetic solution to improve agronomic traits in cereal crops. We suggest that the modification of GA-related genes and the identification of novel alleles without a negative impact on yield and adaptation are significant in cereal crop breeding for plant architecture improvement. We observed that an increasing number of GA-related genes and their mutants have been functionally validated, but only a limited number of GA-related genes have been genetically modified through conventional breeding tools and are widely used in crop breeding successfully. New genome editing technologies, such as the CRISPR/Cas9 system, hold the promise of validating the effectiveness of GA-related genes in crop development and opening a new venue for efficient and accelerated crop breeding.

Quantitative Risk Assessment of Vibrio parahaemolyticus in Shellfish from Retail to Consumption in Coastal Cities of Eastern China.

ABSTRACT: Vibrio parahaemolyticus is the main foodborne pathogen worldwide that causes acute gastroenteritis. A quantitative microbiological risk assessment (QMRA) was conducted to evaluate the health risk associated with V. parahaemolyticus in shellfish in the coastal cities in the eastern part of the People's Republic of China. The QMRA framework was established from shellfish at retail to cooking at home to consumption. The prevalence and level of V. parahaemolyticus in shellfish, cooking methods, storage temperature, time after purchase, shellfish consumption frequency, and consumption amount were analyzed in the exposure assessment. The results of the exposure assessment were introduced into the beta-Poisson dose-response model, and Monte Carlo analysis was used to calculate the risk of gastroenteritis from shellfish consumption. The probability of illness caused by V. parahaemolyticus from shellfish consumption per person per year (Pill,yr) was 3.49E-05. Seasonal differences were noted in the Pill/meal; the maximum was 4.81E-06 in summer and the minimum was 2.27E-07 in winter. The sensitivity analysis revealed that the level of V. parahaemolyticus in shellfish and the amount of shellfish consumed per meal were main factors contributing to illness. This QMRA provided valuable information such as the probability of illness associated with the consumption of shellfish and reference points for prevention strategies and control standards of V. parahaemolyticus in shellfish.

Preliminary Quantitative Risk Assessment of Norovirus in Shellfish in the Yellow Sea and Bohai Sea of China.

Norovirus (NoV) is a main foodborne pathogen of acute gastroenteritis in the world. A preliminary quantitative risk assessment (QRA) was conducted to evaluate the health risk caused by this virus in shellfish in the Yellow Sea and Bohai Sea of China. The QRA framework was established from the process of shellfish at retail through cooking at home to consumer consumption. The prevalence and quantity of NoVs in shellfish, cooking methods, internal temperature and time of shellfish in different cooking conditions, shellfish consumption frequency, and consumption amount were analyzed in the exposure assessment. The results of exposure assessment were introduced into the beta-Poisson dose-response model, and Monte Carlo analysis was used to calculate the risk of gastroenteritis caused by shellfish consumption in the cities around the Yellow Sea and Bohai Sea of China. The results showed that the probability of illness caused by NoVs due to shellfish consumption per year (Pill,yr) was 1.86 × 10-5. It was estimated that the annual number of patients with gastroenteritis per 1,000,000 general population (Nexp,mil) was 0.10, 1.23, 16.90, and 0.38 for population aged 0-4, 5-18, 19-64, and >65 years, respectively. This assessment provides valuable information such as the probability of illness associated with the consumption of shellfish and it also provides a reference for further in-depth QRA of NoVs in shellfish or other foods.

Deep learning based image reconstruction algorithm for limited-angle translational computed tomography.

As a low-end computed tomography (CT) system, translational CT (TCT) is in urgent demand in developing countries. Under some circumstances, in order to reduce the scan time, decrease the X-ray radiation or scan long objects, furthermore, to avoid the inconsistency of the detector for the large angle scanning, we use the limited-angle TCT scanning mode to scan an object within a limited angular range. However, this scanning mode introduces some additional noise and limited-angle artifacts that seriously degrade the imaging quality and affect the diagnosis accuracy. To reconstruct a high-quality image for the limited-angle TCT scanning mode, we develop a limited-angle TCT image reconstruction algorithm based on a U-net convolutional neural network (CNN). First, we use the SART method to the limited-angle TCT projection data, then we import the image reconstructed by SART method to a well-trained CNN which can suppress the artifacts and preserve the structures to obtain a better reconstructed image. Some simulation experiments are implemented to demonstrate the performance of the developed algorithm for the limited-angle TCT scanning mode. Compared with some state-of-the-art methods, the developed algorithm can effectively suppress the noise and the limited-angle artifacts while preserving the image structures.

Genetic Analysis of Fusarium Head Blight Resistance in CIMMYT Bread Wheat Line C615 Using Traditional and Conditional QTL Mapping.

Fusarium head blight (FHB) is a destructive wheat disease present throughout the world, and host resistance is an effective and economical strategy used to control FHB. Lack of adequate resistance resource is still a main bottleneck for FHB genetics and wheat breeding research. The synthetic-derived bread wheat line C615, which does not carry the Fhb1 gene, is a promising source of FHB resistance for breeding. A population of 198 recombinant inbred lines (RILs) produced by crossing C615 with the susceptible cultivar Yangmai 13 was evaluated for FHB response using point and spray inoculations. As the disease phenotype is frequently complicated by other agronomic traits, we used both traditional and multivariate conditional QTL mapping approaches to investigate the genetic relationships (at the individual QTL level) between FHB resistance and plant height (PH), spike compactness (SC), and days to flowering (FD). A linkage map was constructed from 3,901 polymorphic SNP markers, which covered 2,549.2 cM. Traditional and conditional QTL mapping analyses found 13 and 22 QTL for FHB, respectively; 10 were identified by both methods. Among these 10, three QTL from C615 were detected in multiple years; these QTL were located on chromosomes 2AL, 2DS, and 2DL. Conditional QTL mapping analysis indicated that, at the QTL level, SC strongly influenced FHB in point inoculation; whereas PH and SC contributed more to FHB than did FD in spray inoculation. The three stable QTL (QFhbs-jaas.2AL, QFhbp-jaas.2DS, and QFhbp-jaas.2DL) for FHB were partly affected by or were independent of the three agronomic traits. The QTL detected in this study improve our understanding of the genetic relationships between FHB response and related traits at the QTL level and provide useful information for marker-assisted selection for the improvement of FHB resistance in breeding.

Transcriptomic studies reveal a key metabolic pathway contributing to a well-maintained photosynthetic system under drought stress in foxtail millet (Setaria italica L.).

Drought stress is one of the most important abiotic factors limiting crop productivity. A better understanding of the effects of drought on millet (Setaria italica L.) production, a model crop for studying drought tolerance, and the underlying molecular mechanisms responsible for drought stress responses is vital to improvement of agricultural production. In this study, we exposed the drought resistant F1 hybrid, M79, and its parental lines E1 and H1 to drought stress. Subsequent physiological analysis demonstrated that M79 showed higher photosynthetic energy conversion efficiency and drought tolerance than its parents. A transcriptomic study using leaves collected six days after drought treatment, when the soil water content was about ∼20%, identified 3066, 1895, and 2148 differentially expressed genes (DEGs) in M79, E1 and H1 compared to the respective untreated controls, respectively. Further analysis revealed 17 Gene Ontology (GO) enrichments and 14 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways in M79, including photosystem II (PSII) oxygen-evolving complex, peroxidase (POD) activity, plant hormone signal transduction, and chlorophyll biosynthesis. Co-regulation analysis suggested that these DEGs in M79 contributed to the formation of a regulatory network involving multiple biological processes and pathways including photosynthesis, signal transduction, transcriptional regulation, redox regulation, hormonal signaling, and osmotic regulation. RNA-seq analysis also showed that some photosynthesis-related DEGs were highly expressed in M79 compared to its parental lines under drought stress. These results indicate that various molecular pathways, including photosynthesis, respond to drought stress in M79, and provide abundant molecular information for further analysis of the underlying mechanism responding to this stress.

Association of yield-related traits in founder genotypes and derivatives of common wheat (Triticum aestivum L.).

BACKGROUND: Yield improvement is an ever-important objective of wheat breeding. Studying and understanding the phenotypes and genotypes of yield-related traits has potential for genetic improvement of crops. RESULTS: The genotypes of 215 wheat cultivars including 11 founder parents and 106 derivatives were analyzed by the 9 K wheat SNP iSelect assay. A total of 4138 polymorphic single nucleotide polymorphism (SNP) loci were detected on 21 chromosomes, of which 3792 were mapped to single chromosome locations. All genotypes were phenotyped for six yield-related traits including plant height (PH), spike length (SL), spikelet number per spike (SNPS), kernel number per spike (KNPS), kernel weight per spike (KWPS), and thousand kernel weight (TKW) in six irrigated environments. Genome-wide association analysis detected 117 significant associations of 76 SNPs on 15 chromosomes with phenotypic explanation rates (R 2 ) ranging from 2.03 to 12.76%. In comparing allelic variation between founder parents and their derivatives (106) and other cultivars (98) using the 76 associated SNPs, we found that the region 116.0-133.2 cM on chromosome 5A in founder parents and derivatives carried alleles positively influencing kernel weight per spike (KWPS), rarely found in other cultivars. CONCLUSION: The identified favorable alleles could mark important chromosome regions in derivatives that were inherited from founder parents. Our results unravel the genetic of yield in founder genotypes, and provide tools for marker-assisted selection for yield improvement.

A Combined Association Mapping and Linkage Analysis of Kernel Number Per Spike in Common Wheat (Triticum aestivum L.).

Kernel number per spike (KNPS) in wheat is a key factor that limits yield improvement. In this study, we genotyped a set of 264 cultivars, and a RIL population derived from the cross Yangmai 13/C615 using the 90 K wheat iSelect SNP array. We detected 62 significantly associated signals for KNPS at 47 single nucleotide polymorphism (SNP) loci through genome-wide association analysis of data obtained from multiple environments. These loci were on 19 chromosomes, and the phenotypic variation attributable to each one ranged from 1.53 to 39.52%. Twelve (25.53%) of the loci were also significantly associated with KNPS in the RIL population grown in multiple environments. For example, BS00022896_51-2ATT , BobWhite_c10539_201-2DAA , Excalibur_c73633_120-3BGG , and Kukri_c35508_426-7DTT were significantly associated with KNPS in all environments. Our findings demonstrate the effective integration of association mapping and linkage analysis for KNPS, and underpin KNPS as a target trait for marker-assisted selection and genetic fine mapping.