Search

Societal Impact Statement: Multiple cropping, the cultivation of several crops on the same land in a year, occupied an important part of Taiwan's agricultural research from 1950 to 1970. This research originated in the context of Taiwan's land reform and diversification programs and their connections to the government's political ambition to maximize food production. The study of how multiple cropping was politicized and depoliticized by different actors helps to expand the narratives of the Green Revolution in Asia, analyze their legacies, and highlight Taiwan's role in the international exchange of visions of agricultural development during the Cold War. Summary: Scholars have recently expanded the history of the Green Revolution to move beyond the narrative of North–South technological diffusion. This article enriches the scholarship with the case of multiple cropping in Taiwan and its connection to Cold War geopolitics.Rice productivity in postwar Taiwan was boosted through a land reform launched by the Sino‐American Joint Commission on Rural Reconstruction (JCRR) in the 1950s. Backed by American aid and staffed by scientists from the Republic of China (ROC) government, the JCRR envisioned to turn tenant farmers into landowners so as to encourage labor input and adoption of seeds and fertilizers.By 1960, the JCRR presented its reform as a "bloodless social revolution" and extended its focus to multiple cropping through a diversification program. The JCRR further created the Asian Vegetable Research and Development Center (AVRDC) in 1971 to spread Taiwan's breeding and cropping techniques. The ROC's diplomatic isolation in the 1970s, however, prompted the center to reinterpret Taiwan's success in multiple cropping from a political achievement to a technological triumph, thus reinforcing the technology‐driven narrative used by the International Rice Research Institute (IRRI).Through Taiwan's influences on IRRI's rice breeding and multiple cropping research, this paper illustrates that the history of the Green Revolution requires more complex narratives. In addition, with Taiwan's political and economic transition since the 1980s, farmers began to reclaim their voice and influence agricultural policies. The case thus highlights the need of democratic participation in agricultural research, a concern that remains relevant today. [ABSTRACT FROM AUTHOR]

ABSTRACT Prime editing is a versatile CRISPR/Cas‐based precise genome‐editing technique for crop breeding. Four new types of prime editors (PEs) named PE6a–d were recently generated using evolved and engineered reverse transcriptase (RT) variants from three different sources. In this study, we tested the editing efficiencies of four PE6 variants and two additional PE6 constructs with double‐RT modules in transgenic rice (Oryza sativa) plants. PE6c, with an evolved and engineered RT variant from the yeast Tf1 retrotransposon, yielded the highest prime‐editing efficiency. The average fold change in the editing efficiency of PE6c compared with PEmax exceeded 3.5 across 18 agronomically important target sites from 15 genes. We also demonstrated the feasibility of using two RT modules to improve prime‐editing efficiency. Our results suggest that PE6c or its derivatives would be an excellent choice for prime editing in monocot plants. In addition, our findings have laid a foundation for prime‐editing‐based breeding of rice varieties with enhanced agronomically important traits. [ABSTRACT FROM AUTHOR]

The article discusses the development of a new rice variety called MR&HY rice, which was created using multigene transformation and gene editing techniques. The researchers aimed to make the rice resistant to pests, diseases, and herbicides while also increasing its yield. By incorporating six resistance genes and editing a gene related to growth stage, the resulting rice variety showed resistance to various pests and diseases and had a significant increase in yield. This research has the potential to address global food security challenges and reduce the need for pesticides. The document includes two appendices providing additional information on the process and primers used in the study. [Extracted from the article]

This article, published in the Journal of Integrative Plant Biology, discusses the molecular bases for the three-line hybrid rice breeding system. The authors focus on the fertility restoration gene Rf4 and its impact on the Wild Abortive (WA) cytoplasmic male sterility type three-line system. They identify a two-copy haplotype of Rf4 (H1) as the most valuable for future hybrid rice breeding. The study provides insights into the evolutionary trajectory of Rf genes and the origin of cytoplasmic male sterility and fertility restoration systems in rice breeding. The findings contribute to our understanding of the CMS/Rf system and offer guidance for the molecular design breeding of three-line hybrid rice. [Extracted from the article]

Summary: In rice breeding, thermosensitive genic male sterility (TGMS) lines based on the tms5 locus have been extensively employed. Here, we reported a novel rice TGMS line ostms15 (Oryza sativa ssp. japonica ZH11) which show male sterility under high temperature and fertility under low temperature. Field evaluation from 2018 to 2021 revealed that its sterility under high temperature is more stable than that of tms5 (ZH11), even with occasional low temperature periods, indicating its considerable value for rice breeding. OsTMS15 encodes an LRR‐RLK protein MULTIPLE SPOROCYTE1 (MSP1) which was reported to interact with its ligand to initiate tapetum development for pollen formation. In ostms15, a point mutation from GTA (Val) to GAA (Glu) in its TIR motif of the LRR region led to the TGMS phenotype. Cellular observation and gene expression analysis showed that the tapetum is still present in ostms15, while its function was substantially impaired under high temperature. However, its tapetum function was restored under low temperature. The interaction between mOsTMS15 and its ligand was reduced while this interaction was partially restored under low temperature. Slow development was reported to be a general mechanism of P/TGMS fertility restoration. We propose that the recovered protein interaction together with slow development under low temperature compensates for the defective tapetum initiation, which further restores ostms15 fertility. We used base editing to create a number of TGMS lines with different base substitutions based on the OsTMS15 locus. This work may also facilitate the mechanistic investigation and breeding of other crops. [ABSTRACT FROM AUTHOR]

Genotype by environment interaction (GEI) is one of the main challenges in plant breeding. A complete characterization of it is necessary to decide on proper breeding strategies. Random regression models (RRMs) allow a genotype‐specific response to each regressor factor. RRMs that include selected environmental variables represent a promising approach to deal with GEI in genomic prediction. They enable to predict for both tested and untested environments, but their utility in a plant breeding scenario remains to be shown. We used phenotypic, climatic, pedigree, and genomic data from two public subtropical rice (Oryza sativa L.) breeding programs; one manages the indica population and the other manages the japonica population. First, we characterized GEI for grain yield (GY) with a set of tools: variance component estimation, mega‐environment (ME) definition, and correlation between locations, sowing periods, and MEs. Then, we identified the most influential climatic variables related to GY and its GEI and used them in RRMs for single‐step genomic prediction. Finally, we evaluated the predictive ability of these models for GY prediction in tested and untested years and environments using the complete dataset and within each ME. Our results suggest large GEI in both populations while larger in indica than in japonica. In indica, early sowing periods showed crossover (i.e., rank‐change) GEI with other sowing periods. Climatic variables related to temperature, radiation, wind, and precipitation affecting GY were identified and differed in each population. RRMs with selected climatic covariates improved the predictive ability in both tested and untested years and environments. Prediction using the complete dataset performed better than predicting within each ME. Core Ideas: Random regression models improved the predictive ability for grain yield in a realistic plant breeding scenario.Prediction using the complete dataset performed better than predicting within mega‐environments.Large amounts of genotype by environment interaction affect grain yield in both indica and japonica populations.Indica genotype ranking drastically changed in early sowing compared with intermediate and late sowing.Climatic variables affecting grain yield are different between our indica and japonica rice breeding populations. [ABSTRACT FROM AUTHOR]

SUMMARY: Cold stress is a major factor limiting the production and geographical distribution of rice (Oryza sativa) varieties. However, the molecular mechanisms underlying cold tolerance remain to be elucidated. Here, we report that ornithine δ‐aminotransferase (OsOAT) contributes to cold tolerance during the vegetative and reproductive development of rice. osoat mutant was identified as a temperature‐sensitive male sterile mutant with deformed floral organs and seedlings sensitive to cold stress. Comparative transcriptome analysis showed that OsOAT mutation and cold treatment of the wild‐type plant led to similar changes in the global gene expression profiles in anthers. OsOAT genes in indica rice Huanghuazhan (HHZ) and japonica rice Wuyungeng (WYG) are different in gene structure and response to cold. OsOAT is cold‐inducible in WYG but cold‐irresponsive in HHZ. Further studies showed that indica varieties carry both WYG‐type and HHZ‐type OsOAT, whereas japonica varieties mostly carry WYG‐type OsOAT. Cultivars carrying HHZ‐type OsOAT are mainly distributed in low‐latitude regions, whereas varieties carrying WYG‐type OsOAT are distributed in both low‐ and high‐latitude regions. Moreover, indica varieties carrying WYG‐type OsOAT generally have higher seed‐setting rates than those carrying HHZ‐type OsOAT under cold stress at reproductive stage, highlighting the favorable selection for WYG‐type OsOAT during domestication and breeding to cope with low temperatures. Significance Statement: The identification of genes important for cold tolerance can promote the molecular breeding of cold‐tolerant rice varieties. This study discovered two major natural alleles of OsOAT that conferred different levels of cold tolerance, thereby providing a good candidate gene for breeding of rice plants with enhanced cold tolerance. [ABSTRACT FROM AUTHOR]

Summary: Plant architecture and stress tolerance play important roles in rice breeding. Specific leaf morphologies and ideal plant architecture can effectively improve both abiotic stress resistance and rice grain yield. However, the mechanism by which plants simultaneously regulate leaf morphogenesis and stress resistance remains elusive. Here, we report that SRL10, which encodes a double‐stranded RNA‐binding protein, regulates leaf morphology and thermotolerance in rice through alteration of microRNA biogenesis. The srl10 mutant had a semi‐rolled leaf phenotype and elevated sensitivity to high temperature. SRL10 directly interacted with catalase isozyme B (CATB), and the two proteins mutually increased one other's stability to enhance hydrogen peroxide (H2O2) scavenging, thereby contributing to thermotolerance. The natural Hap3 (AGC) type of SRL10 allele was found to be present in the majority of aus rice accessions, and was identified as a thermotolerant allele under high temperature stress in both the field and the growth chamber. Moreover, the seed‐setting rate was 3.19 times higher and grain yield per plant was 1.68 times higher in near‐isogenic line (NIL) carrying Hap3 allele compared to plants carrying Hap1 allele under heat stress. Collectively, these results reveal a new locus of interest and define a novel SRL10–CATB based regulatory mechanism for developing cultivars with high temperature tolerance and stable yield. Furthermore, our findings provide a theoretical basis for simultaneous breeding for plant architecture and stress resistance. [ABSTRACT FROM AUTHOR]

BACKGROUND: Rice is an important food crop plant in the world and is also a model plant for genetics and breeding research. The germination rate is an important indicator that measures the performance of rice seeds. Currently, solutions involving image processing techniques have substantial challenges in the identification of seed germination. The detection of rice seed germination without human intervention involves challenges because the rice seeds are small and densely distributed. RESULTS: In this article, we develop a convolutional neural network (YOLO‐r) that can detect the germination status of rice seeds and automatically evaluate the total number of germinations. Image partition, the Transformer encoder, a small target detection layer, and CDIoU loss are exploited in YOLO‐r to improve the detection accuracy. A total of 21 429 seeds were collected, which have different phenotypic characteristics in length, shape, and color. The results show that the mean average precision of YOLO‐r is 0.9539, which is higher than the compared models. Moreover, the average detection time per image of YOLO‐r was 0.011 s, which meets the real‐time requirements. The experimental results demonstrate that YOLO‐r is robust to complex situations such as water stains, impurities, awns, adhesion, and so on. The results also show that the mean absolute error of the predicted germination rate mainly exists within 0.1. CONCLUSIONS: Numerous experimental studies have demonstrated that YOLO‐r can predict rice germination rate in a fast, easy, and accurate manner. © 2022 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

SUMMARY: Excessive nitrogen fertilizer application is harmful to the environment and reduces the quality of cereal crops. Maintaining crop yields under low nitrogen (LN) conditions and improving quality are important goals for cereal crop breeding. Although the effects of nitrogen assimilation on crop nitrogen‐use efficiency (NUE) have been intensively studied, natural variations of the key assimilation genes underlying grain development and quality are largely unclear. Here, we identified an NUE‐associated gene, OsGS1;1, encoding glutamine synthase, through genome‐wide association analysis, followed by validation experiments and functional analysis. Fifteen single‐nucleotide polymorphisms in the OsGS1;1 region led to alternative splicing that generated two functional transcripts: OsGS1;1a and OsGS1;1b. The elite haplotype of OsGS1;1 showed high OsGS1;1b activity, which improved NUE, affected grain development, and reduced amylose content. The results show that OsGS1;1, which is induced under LN conditions, affects grain formation by regulating sugar metabolism and may provide a new avenue for the breeding of high‐yield and high‐quality rice (Oryza sativa). Significance Statement: OsGS1;1 affects grain formation by regulating sugar metabolism and may provide a new avenue for the breeding of high‐yield and high‐quality rice. [ABSTRACT FROM AUTHOR]

SUMMARY: Plant height (PH) is an important trait affecting the plant architecture, seed yield, and harvest index. However, the molecular mechanisms underlying PH heterosis remain unclear. In addition, useful PH‐related genes must be urgently identified to facilitate ideal plant architecture breeding in rice (Oryza sativa L.). In the present study, to explore rice quantitative trait loci (QTLs) and heterosis‐related loci of PH in rice, we developed a high‐generation (>F15) population of 272 recombinant inbred lines (RIL) from a cross of two elite varieties, Luohui 9 (indica/xian) × RPY geng (japonica/geng), and two testcross hybrid populations derived from the crosses of RILs and two cytoplasmic male sterile lines (YTA [indica] and Z7A [japonica]). Using deep resequencing data, a high‐density genetic map containing 4758 bin markers was constructed, with a total map distance of 2356.41 cM. Finally, 31 PH‐related QTLs for different PH component lengths or tiller numbers across five seasons were identified. Two major environment‐specific PH QTLs were stably detected in Hainan (qPH‐3.1) or Hubei (qPH‐5.1), which have undergone significant functional alterations in rice with changes in geographical environment. Based on comparative genomics, gene function annotation, homolog identification, and existing literature (pioneering studies), candidate genes for multiple QTLs were fine‐mapped, and the candidate genes qPH‐3.1 and qPH‐5.1 for PH were further validated using CRISPR–Cas9 gene editing. Specifically, qPH‐3.1 was characterized as a pleiotropic gene, and the qPH‐3.1 knockout line showed reduced PH, delayed heading, a decreased seed setting rate, and increased tiller numbers. Importantly, 10 PH heterosis‐related QTLs were identified in the testcross populations, and a better‐parent heterosis locus (qBPH‐5.2) completely covered qPH‐5.1. Furthermore, the cross results of fixed‐genotype RILs verified the dominant effects of qPH‐3.1 and qPH‐5.1. Together, these findings further our understanding of the genetic mechanisms of PH and offer multiple highly reliable gene targets for breeding rice varieties with ideal architecture and high yield potential in the immediate future. Significance Statement: In the present study we constructed a high‐density genetic map containing 4758 bin markers of a high‐generation recombinant inbred line population from a cross of two elite rice (Oryza sativa L.) varieties, Luohui 9 (indica/xian) × RPY geng (japonica/geng). Two major environment‐specific QTLs of plant height were discovered and experimentally validated. [ABSTRACT FROM AUTHOR]

Greater nitrogen efficiency would substantially reduce the economic, energy and environmental costs of rice production. We hypothesized that synergistic balancing of the costs and benefits for soil exploration among root architectural phenes is beneficial under suboptimal nitrogen availability. An enhanced implementation of the functional–structural model OpenSimRoot for rice integrated with the ORYZA_v3 crop model was used to evaluate the utility of combinations of root architectural phenes, namely nodal root angle, the proportion of smaller diameter nodal roots, nodal root number; and L‐type and S‐type lateral branching densities, for plant growth under low nitrogen. Multiple integrated root phenotypes were identified with greater shoot biomass under low nitrogen than the reference cultivar IR64. The superiority of these phenotypes was due to synergism among root phenes rather than the expected additive effects of phene states. Representative optimal phenotypes were predicted to have up to 80% greater grain yield with low N supply in the rainfed dry direct‐seeded agroecosystem over future weather conditions, compared to IR64. These phenotypes merit consideration as root ideotypes for breeding rice cultivars with improved yield under rainfed dry direct‐seeded conditions with limited nitrogen availability. The importance of phene synergism for the performance of integrated phenotypes has implications for crop breeding. Summary Statement: Multiscale mechanistic modelling identified several integrated root phenotypes in rice with superior yield under low N availability. Synergism among root phenes was an important component of phenotypic performance. [ABSTRACT FROM AUTHOR]

Adoption of new plant varieties has played a significant role in eradicating global hunger. Previous research has mainly focused on farmer adoption and impact of new crop varieties, although upstream adoption of technologies in plant breeding can generate substantial multiplier effects on downstream impacts. This study moves upstream in the innovation system to generate policy advice on adoption and transfer of accelerated rice breeding technologies. More specifically, we assess the determinants of global adoption of rapid generation advance (RGA) through a sample of 158 rice breeders operating in various research institutes worldwide. Moving upstream in the innovation system has important theoretical and empirical implications due to the smaller number of decision‐making units in the adoption process and the increasing role of institutional and managerial factors that may overrule individual adoption motivations. We revisit multi‐stage models and devise the most robust estimation method that can be used in this situation. To generate insights on the impact of individual versus institutional adopter characteristics on upstream technology adoption, we juxtapose the response curves of the determinants of RGA adoption in rice breeding among alternative adoption stages, levels of conditionality and model specifications. Our findings confirm the importance of institutional and managerial factors and suggest that adoption and transfer of breeding technologies require breeding institutes to provide an enabling environment in which breeders are encouraged to take risks and are given sufficient freedom to experiment with and implement new technologies. [ABSTRACT FROM AUTHOR]

Understanding heritability has historically been critical to the incorporation of traits of interest into plant breeding programmes for improvement. In our previous study, we assessed the heritability of several photosynthetic traits in indica rice, including biochemical limitations of photosynthesis. Here, we discuss that even without directly evaluating sink limitation, there is still great value in this study for understanding how photosynthetic traits in rice could be incorporated into a breeding programme and which traits could be given priority. Additionally, we assert that limitation by Jmax will likely be more relevant than TPU limitation in the immediate future and could be a valuable factor for selection. However, we agree with Fabre and Dingkuhn (2022, https://doi.org/10.1111/pbr.13000) that sink limitation should be further examined within the context of plant improvement in the future. [ABSTRACT FROM AUTHOR]

Embrapa has led breeding programs for irrigated and upland rice (Oryza sativa L.) since 1977, generating a large amount of pedigree and phenotypic data. However, there were no systematic standards for data recording nor long‐term data preservation and reuse strategies. With the new aim of making data reuse practical, we recovered all data available and structured it into the Embrapa Rice Breeding Dataset (ERBD). In its current version, the ERBD includes 20,504 crosses involving 9,974 parents, the pedigrees of most of the 4,532 inbred lines that took part in advanced field trials, and phenotypic data from 2,711 field trials (1,118 irrigated, 1,593 upland trials), representing 226,458 field plots. Those trials were conducted over 38 years (1982–2019), in 247 locations, in latitudes ranging from 3°N to 33°S. Phenotypic traits included grain yield, days to flowering, plant height, canopy lodging, and five important fungal diseases: leaf blast, panicle blast, brown spot, leaf scald, and grain discoloration. The total number of data points surpasses 1.27 million. Descriptive statistics were computed over the dataset, split by cropping systems (irrigated or upland). The mean heritability of grain yield was high for both systems, at around.7, whereas the mean coefficient of variation was 13.9% for irrigated trials and 18.7% for upland trials. The ERBD offers the possibility of conducting studies on different aspects of rice breeding and genetics, including genetic gain, G×E analysis, genome‐wide association studies and genomic prediction. Core Ideas: Historical datasets are useful for genetic research and development of breeding tools.Phenotypic data from crop breeding programs connect elite genotypes with target environments.Converting available records in analyzable format is a worthwhile investment. [ABSTRACT FROM AUTHOR]

The dynamic changes in agricultural practices have negatively impacted rice cultivation resulting in serious weedy rice (Oryza sativa L.) infestations. In this study, field surveys were conducted at six granaries to evaluate the abundance, spatial‐distribution patterns, and morphological characteristics of weedy rice in Peninsular Malaysia. An average of 5.28 plants/m2 weedy rice density was recorded, with coverage area that ranged from 29% to 66% and occurrence at >67% frequency. Seed morphological characteristics identified the existence of at least 18 biotypes. A total of 134 weedy rice samples were characterized morphologically, and Principle Component Analysis results showed that these samples are highly diverse and are dispersed across Peninsular Malaysia. These genetically diverse reservoir of weedy rice characteristics present opportunities of exploitation in the future, especially through rice breeding and crop improvement. Weedy rice from Kelantan and Selangor displayed unique clusters in the PCA plot which suggest higher tendencies for environmental adaptation although the influencing factors have yet to be determined. Dispersion studies based on Lloyd patchiness index revealed that more than 50% of surveyed field blocks in five states displayed uniform distribution as opposed to cluster distribution observed in the remaining field blocks. These variations in dispersion suggested that farmers in Peninsular Malaysia employed inconsistent weedy rice management practices in every granary and farm block. Observation of weedy rice infestation pattern via spatial distribution suggested that weed management requires proper coordination of control efforts among farmers to ensure the degree of infestation is maintained under a controlled level. [ABSTRACT FROM AUTHOR]

Parallel domestication has been widely acknowledged but its genetic basis remains largely unclear. As an important rice ecotype, upland rice was assumedly domesticated multiple times in two rice subspecies (Indica and Japonica) and provides a feasible system to explore the genetic basis of parallel domestication. To uncover the genome‐wide pattern of genetic differentiation between upland and lowland rice and explore the parallelism of genetic changes during upland rice domestication, we obtained whole‐genome sequences of 95 rice landraces and yielded genome‐wide expression data for five tissues of representative accessions of upland and lowland rice. Our phylogenetic analyses confirmed multiple domestications of the upland ecotype in two rice subspecies. Genomic scans based on resequencing data identified substantial differentiation between the upland and lowland ecotypes with 11.4% and 14.8% of the genome diverged between the two ecotypes in Indica and Japonica, respectively. Further genome‐wide gene expression analyses found that 30% of effectively expressed genes were significantly differentiated between two ecotypes, indicating the importance of regulation changes in the domestication of upland rice. Importantly, we found that only 1.8% of differentiated genomes and 1.6% of differentially expressed genes were shared by upland Indica and upland Japonica, suggestive of largely unparallel genetic alterations during upland rice domestication. These findings not only provide new insights into the genetic basis of parallel domestication at the genome scale but could also facilitate genetic improvement and breeding of rice and crops in general. [ABSTRACT FROM AUTHOR]

Summary: Hybrid breeding has been shown to effectively increase rice productivity. However, identifying desirable hybrids out of numerous potential combinations is a daunting challenge. Genomic selection holds great promise for accelerating hybrid breeding by enabling early selection before phenotypes are measured. With the recent advances in multi‐omic technologies, hybrid prediction based on transcriptomic and metabolomic data has received increasing attention. However, the current omic‐based hybrid prediction has ignored parental phenotypic information, which is of fundamental importance in plant breeding. In this study, we integrated parental phenotypic information into various multi‐omic prediction models applied in hybrid breeding of rice and compared the predictabilities of 15 combinations from four sets of predictors from the parents, that is genome, transcriptome, metabolome and phenome. The predictability for each combination was evaluated using the best linear unbiased prediction and a modified fast HAT method. We found significant interactions between predictors and traits in predictability, but joint prediction with various combinations of the predictors significantly improved predictability relative to prediction of any single source omic data for each trait investigated. Incorporation of parental phenotypic data into various omic predictors increased the predictability, averagely by 13.6%, 54.5%, 19.9% and 8.3%, for grain yield, number of tillers per plant, number of grains per panicle and 1000 grain weight, respectively. Among nine models of incorporating parental traits, the AD‐All model was the most effective one. This novel strategy of incorporating parental phenotypic data into multi‐omic prediction is expected to improve hybrid breeding progress, especially with the development of high‐throughput phenotyping technologies. [ABSTRACT FROM AUTHOR]

The rice crop is affected by diseases throughout its cycle, impacting negatively on grain yield and quality. The control of the disease impact can be accomplished via crop breeding, using highly multiple resistant genotypes. This study aimed to evaluate the efficiency of multiple‐character and specific selection of multiple resistance to major culture‐associated diseases (neck blast, leaf scald and grain discoloration) in rice lines of the Upland Rice Genetic Breeding Program. The experiments were conducted in 35 sites during 12 agricultural years, where 124 lines were evaluated for the severity of fungal diseases, under natural field conditions. Multiple parameters were calculated based on the diseases´ scores: genetic, phenotypic and environmental variances, heritability, selection gain, renewal rate, and genetic and renewal progress. Genetic variance for the disease resistance was identified in the population, and the selection gain for multiple‐character selection was of 3.16 year−1 throughout the breeding process with a renewal rate of over 35%. The programme has showed efficiency in selecting multiple resistant genotypes to the mentioned diseases, highlighting genotypes with high potential for market release. [ABSTRACT FROM AUTHOR]

SUMMARY: Advancements in ‐omics techniques provide powerful tools to assess the potential effects in composition of a plant at the RNA, protein and metabolite levels. These technologies can thus be deployed to assess whether genetic engineering (GE) causes changes in plants that go beyond the changes introduced by conventional plant breeding. Here, we compare the extent of transcriptome and metabolome modification occurring in leaves of four GE rice lines expressing Bacillus thuringiensis genes developed by GE and seven rice lines developed by conventional cross‐breeding. The results showed that both types of crop breeding methods can bring changes at transcriptomic and metabolic levels, but the differences were comparable between the two methods, and were less than those between conventional non‐GE lines were. Metabolome profiling analysis found several new metabolites in GE rice lines when compared with the closest non‐GE parental lines, but these compounds were also found in several of the conventionally bred rice lines. Functional analyses suggest that the differentially expressed genes and metabolites caused by both GE and conventional cross‐breeding do not involve detrimental metabolic pathways. The study successfully employed RNA‐sequencing and high‐performance liquid chromatography mass spectrometry technology to assess the unintended changes in new rice varieties, and the results suggest that GE does not cause unintended effects that go beyond conventional cross‐breeding in rice. Significance Statement: We compared the biological variation at mRNA and metabolite levels among four genetically engineered rice lines and nine conventionally bred rice cultivars that represent a range of genetic and phenotypic diversity in rice. The results provide evidence that genetic engineering does not cause unintended effects that go beyond conventional cross‐breeding in rice. [ABSTRACT FROM AUTHOR]

BACKGROUND: Promoters play a key role in driving insect‐resistant genes during breeding of transgenic plants. In current transgenic procedures for breeding rice resistance to striped stem borer (Chilo suppressalis Walker, SSB), the constitutive promoter is used to drive the insect‐resistant gene. To reduce the burden of constitutive promoters on plant growth, isolation and identification of insect‐inducible promoters are particularly important. However, few promoters are induced specifically by insect feeding. RESULTS: We found rice hydroperoxide lyase gene (OsHPL2) (LOC_Os02g12680) was upregulated after feeding by SSB. We subsequently cloned the promoter of OsHPL2 and analysed its expression pattern using the β‐glucuronidase (GUS) reporter gene. Histochemical assays and quantitative analyses of GUS activity confirmed that PHPL2:GUS was activated by SSB, but did not respond to brown planthopper (Nilaparvata lugens Stål, BPH) infestation, mechanical wounding or phytohormone treatments. A series of 5′ truncated assays were conducted and three positive regulatory regions (−1452 to −1213, −903 to −624, and −376 to −176) induced by SSB infestation were identified. P2R123‐min 35S and P2TR2‐min 35S promoters linked with cry1C of transgenic plants showed the highest levels of Cry1C protein expression and SSB larval mortality. CONCLUSION: We identified an SSB‐inducible promoter and three positive internal regions. Transgenic rice plants with the OsHPL2 promoter and its positive regions driving cry1C exhibited the expected larvicidal effect on SSB. Our study is the first report of an SSB‐inducible promoter that could be used as a potential resource for breeding insect‐resistant transgenic crops. © 2020 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

Routine estimation of the rate of genetic gain (ΔGt) realized by a breeding program has been proposed as a means to monitor its effectiveness. Several methods of realized ΔGt estimation have been used in other studies, but none have been objectively evaluated in a plant breeding context. Stochastic simulations of 80 rice (Oryza sativa L.) breeding programs over 28 yr were done to generate data used to evaluate five methods of realized ΔGt estimation in terms of error, precision, efficiency, and correlation between true and predicted annual mean breeding values. Two indicators of ΔGt, the expected ΔGt, and the average number of equivalent complete generations (EqCg), were described and evaluated. At best, estimates of realized ΔGt were over or underestimated by 15 and 27% when considering all 28 yr and the past 15 yr of breeding, respectively. The best methods were the estimated breeding value, control population, and era trial methods. Among these, correlations between true and estimated ΔGt were at best 0.59, indicating that these methods cannot very accurately rank breeding programs in terms of realized ΔGt. The expected ΔGt and the average EqCg were shown to be useful indicators for determining if a nonzero genetic gain is expected. Determining which of the three best realized ΔGt estimation methods evaluated, if any, would be appropriate for any given breeding program should be done with careful consideration of the objectives, resources, seed stocks, and structure of the data available. [ABSTRACT FROM AUTHOR]

Rice is an important staple food and cash crop. Although many varieties of rice have been developed to date, few are adopted possibly because researchers did not take into account farmers’ preferences and perceptions on varieties during the development process. Because farmers increasingly rely on low-yielding landraces, production fails to meet demand. To provide an understanding of farmers’ preferences for rice cultivars and perceptions on drought stress and management practices as inputs to rice breeding research, this study was conducted in the Sikasso region of Mali in September 2005 using participatory rural appraisal approach. A total number of 125 farmers were randomly selected from 10 villages in three ecologies and interviewed individually and in groups. Results showed that farmers’ preferences, crop management practices and ranking of production constraints differed significantly across ecologies. Whereas farmers in the irrigated ecologies preferred high-yielding, long duration rice varieties, those in the upland and lowland ecologies preferred tall plants of short duration. While upland and lowland farmers preferred red and white long grains, respectively, irrigated ecologies were indifferent about grain colour. Farmers appeared willing to trade-off yield for grain quality and plant height, inconsistent with traditional breeders’ selection criteria. The high preference for tall varieties among farmers in the upland and lowland ecologies also contrasted sharply with the model of dwarf rice varieties responsible for the green revolution in Asia. The implication of these findings for rice breeders is that different plant idiotypes complemented by effective drought management practices should target different ecologies to increase impact. [ABSTRACT FROM AUTHOR]