Advancing Plant Breeding with Next-Generation Technologies: Insights from Recent Research.

Genetic resources are the cornerstone of our food supply and play a pivotal role in developing new crop varieties that ensure sustainable agricultural production amid the challenges of climate change [...].

Optimal Planting Time for Summer Tomatoes (Lycopersicon esculentum Mill.) Cropping in Korea: Growth, Yield, and Photosynthetic Efficiency in a Semi-Closed Greenhouse.

In Korea, greenhouses are traditionally used for crop cultivation in the winter. However, due to diverse consumer demands, climate change, and advancements in agricultural technology, more farms are aiming for year-round production. Nonetheless, summer cropping poses challenges such as high temperatures, humidity from the monsoon season, and low light conditions, which make it difficult to grow crops. Therefore, this study aimed to determine the best planting time for summer tomato cultivation in a Korean semi-closed greenhouse that can be both air-conditioned and heated. The experiment was conducted in the Advanced Digital Greenhouse, built by the National Institute of Agricultural Sciences. The tomato seedlings were planted in April, May, and June 2022. Growth parameters such as stem diameter, flowering position, stem growth rate, and leaf shape index were measured, and harvesting was carried out once or twice weekly per treatment from 65 days to 265 days after planting. The light use efficiency and yield per unit area at each planting time was measured. Tomatoes planted in April showed a maximum of 42.9% higher light use efficiency for fruit production and a maximum of 33.3% higher yield. Furthermore, the growth form of the crops was closest to the reproductive growth type. Therefore, among April, May, and June, April is considered the most suitable planting time for summer cultivation, which is expected to contribute to reducing labor costs due to decreased workload and increasing farm income through increased yields. Future research should explore optimizing greenhouse microclimates and developing crop varieties tailored for summer cultivation to further enhance productivity and sustainability in year-round agricultural practices.

Microcystis abundance is predictable through ambient bacterial communities: A data-oriented approach.

The number of cyanobacterial harmful algal blooms (cyanoHABs) has increased, leading to the widespread development of prediction models for cyanoHABs. Although bacteria interact closely with cyanobacteria and directly affect cyanoHABs occurrence, related modeling studies have rarely utilized microbial community data compared to environmental data such as water quality. In this study, we built a machine learning model, the multilayer perceptron (MLP), for the prediction of Microcystis dynamics using both bacterial community and weekly water quality data from the Daechung Reservoir and Nakdong River, South Korea. The modeling performance, indicated by the R2 value, improved to 0.97 in the model combining bacterial community data with environmental factors, compared to 0.78 in the model using only environmental factors. This underscores the importance of microbial communities in cyanoHABs prediction. Through the post-hoc analysis of the MLP models, we revealed that nitrogen sources played a more critical role than phosphorus sources in Microcystis blooms, whereas the bacterial amplicon sequence variants did not have significant differences in their contribution to each other. Similar to the MLP model results, bacterial data also had higher predictability in multiple linear regression (MLR) than environmental data. In both the MLP and MLR models, Microscillaceae showed the strongest association with Microcystis. This modeling approach provides a better understanding of the interactions between bacteria and cyanoHABs, facilitating the development of more accurate and reliable models for cyanoHABs prediction using ambient bacterial data.

Response of particle-attached and free-living bacterial communities to Microcystis blooms.

The massive proliferation of Microcystis threatens freshwater ecosystems and degrades water quality globally. Understanding the mechanisms that contribute to Microcystis growth is crucial for managing Microcystis blooms. The lifestyles of bacteria can be classified generally into two groups: particle-attached (PA; > 3 µm) and free-living (FL; 0.2-3.0 µm). However, little is known about the response of PA and FL bacteria to Microcystis blooms. Using 16S rRNA gene high-throughput sequencing, we investigated the stability, assembly process, and co-occurrence patterns of PA and FL bacterial communities during distinct bloom stages. PA bacteria were phylogenetically different from their FL counterparts. Microcystis blooms substantially influenced bacterial communities. The time decay relationship model revealed that Microcystis blooms might increase the stability of both PA and FL bacterial communities. A contrasting community assembly mechanism was observed between the PA and FL bacterial communities. Throughout Microcystis blooms, homogeneous selection was the major assembly process that impacted the PA bacterial community, whereas drift explained much of the turnover of the FL bacterial community. Both PA and FL bacterial communities could be separated into modules related to different phases of Microcystis blooms. Microcystis blooms altered the assembly process of PA and FL bacterial communities. PA bacterial community appeared to be more responsive to Microcystis blooms than FL bacteria. Decomposition of Microcystis blooms may enhance cooperation among bacteria. Our findings highlight the importance of studying bacterial lifestyles to understand their functions in regulating Microcystis blooms. KEY POINTS: • Microcystis blooms alter the assembly process of PA and FL bacterial communities • Microcystis blooms increase the stability of both PA and FL bacterial communities • PA bacteria seem to be more responsive to Microcystis blooms than FL bacteria.

Dynamic response of bacterial communities to Microcystis blooms: A three-year study.

Although nutrient availability is widely recognized as the driving force behind Microcystis blooms, identifying the microorganisms that play a pivotal role in their formation is a challenging task. Our understanding of the contribution of bacterial communities to the development of Microcystis blooms remains incomplete, despite the fact that the relationship between Microcystis and bacterial communities has been extensively investigated. Most studies have focused on their interaction for a single year rather than for multiple years. To determine key bacteria crucial for the formation of Microcystis blooms, we collected samples from three sites in the Daechung Reservoir (Chuso, Hoenam, and Janggye) over three years (2017, 2019, and 2020). Our results indicated that Microcystis bloom-associated bacterial communities were more conserved across stations than across years. Bacterial communities could be separated into modules corresponding to the different phases of Microcystis blooms. Dolichospermum and Aphanizomenon belonged to the same module, whereas the module of Microcystis was distinct. The microbial recurrent association network (MRAN) showed that amplicon sequence variants (ASVs) directly linked to Microcystis belonged to Pseudanabaena, Microscillaceae, Sutterellaceae, Flavobacterium, Candidatus Aquiluna, Bryobacter, and DSSD61. These ASVs were also identified as key indicators of the bloom stage, indicating that they were fundamental biological elements in the development of Microcystis blooms. Overall, our study highlights that, although bacterial communities change annually, they continue to share core ASVs that may be crucial for the formation and maintenance of Microcystis blooms.

QTL Mapping of Tiller Number in Korean Japonica Rice Varieties.

Tiller number is an important trait associated with yield in rice. Tiller number in Korean japonica rice was analyzed under greenhouse conditions in 160 recombinant inbred lines (RILs) derived from a cross between the temperate japonica varieties Odae and Unbong40 to identify quantitative trait loci (QTLs). A genetic map comprising 239 kompetitive allele-specific PCR (KASP) and 57 cleaved amplified polymorphic sequence markers was constructed. qTN3, a major QTL for tiller number, was identified at 132.4 cm on chromosome 3. This QTL was also detected under field conditions in a backcross population; thus, qTN3 was stable across generations and environments. qTN3 co-located with QTLs associated with panicle number per plant and culm diameter, indicating it had pleiotropic effects. The qTN3 regions of Odae and Unbong40 differed in a known functional variant (4 bp TGTG insertion/deletion) in the 5' UTR of OsTB1, a gene underlying variation in tiller number and culm strength. Investigation of variation in genotype and tiller number revealed that varieties with the insertion genotype had lower tiller numbers than those with the reference genotype. A high-resolution melting marker was developed to enable efficient marker-assisted selection. The QTL qTN3 will therefore be useful in breeding programs developing japonica varieties with optimal tiller numbers for increased yield.

From crop specific to variety specific in crop modeling for the smart farm: A case study with blueberry.

Facility cultivation has been evolved from greenhouses to smart farms using artificial intelligence (AI) that simulates big data to maximize production. However, the big data for AI in smart farm is not studied well; the effect of differences among varieties within a crop remains unclear. Therefore, the response of two varieties of blueberry, 'Suziblue' and 'Star', to light was tested using SAPD meter in order to demonstrate the environmental responses could be different among varieties within the same species. The results showed that those two varieties had significant differences in SPAD values based on the leaf's position and time, whereas 'Star' did not. This indicates that the effect of light depends on the variety, which implies that other traits and other crops may show similar differences. These results are based on a simple experiment. However, it is enough to elucidate that it is extremely important to characterize responses to the environment not only for each crop but also for each variety to collect data for smart farming to increase accuracy for modeling; consequently, to maximize the efficiency of these facilities.

Identification of the Capsicum baccatum NLR Protein CbAR9 Conferring Disease Resistance to Anthracnose.

Anthracnose is caused by Colletotrichum species and is one of the most virulent fungal diseases affecting chili pepper (Capsicum) yield globally. However, the noble genes conferring resistance to Colletotrichum species remain largely elusive. In this study, we identified CbAR9 as the causal locus underlying the large effect quantitative trait locus CcR9 from the anthracnose-resistant chili pepper variety PBC80. CbAR9 encodes a nucleotide-binding and leucine-rich repeat (NLR) protein related to defense-associated NLRs in several other plant species. CbAR9 transcript levels were induced dramatically after Colletotrichum capsici infection. To explore the biological function, we generated transgenic Nicotiana benthamiana lines overexpressing CbAR9, which showed enhanced resistance to C. capsici relative to wild-type plants. Transcript levels of pathogenesis-related (PR) genes increased markedly in CbAR9-overexpressing N. benthamiana plants. Moreover, resistance to anthracnose and transcript levels of PR1 and PR2 were markedly reduced in CbAR9-silenced chili pepper fruits after C. capsici infection. Our results revealed that CbAR9 contributes to innate immunity against C. capsici.

The Capsicum baccatum-Specific Truncated NLR Protein CbCN Enhances the Innate Immunity against Colletotrichum acutatum.

Chili pepper (Capsicumannuum) is an important fruit and spice used globally, but its yield is seriously threatened by anthracnose. Capsicum baccatum is particularly valuable as it carries advantageous disease resistance genes. However, most of the genes remain to be identified. In this study, we identified the C. baccatum-specific gene CbCN, which encodes a truncated nucleotide-binding and leucine-rich repeat protein in the anthracnose resistant chili pepper variety PBC80. The transcription of CbCN was greater in PBC80 than it was in the susceptible variety An-S after Colletotrichum acutatum inoculation. In order to investigate the biological function of CbCN, we generated transgenic tobacco lines constitutively expressing CbCN. Notably, CbCN-overexpressing transgenic plants exhibited enhanced resistance to C. acutatum compared to wild-type plants. Moreover, the expression of pathogenesis-related (PR) genes was remarkably increased in a CbCN-overexpressing tobacco plants. In order to confirm these results in chili pepper, we silenced the CbCN gene using the virus-induced gene silencing system. The anthracnose resistance and expressions of PR1, PR2, and NPR1 were significantly reduced in CbCN-silenced chili peppers after C. acutatum inoculations. These results indicate that CbCN enhances the innate immunity against anthracnose caused by C. acutatum by regulating defense response genes.

A multi-commodity network model for optimal quantum reversible circuit synthesis.

Quantum computing is a newly emerging computing environment that has recently attracted intense research interest in improving the output fidelity, fully utilizing its high computing power from both hardware and software perspectives. In particular, several attempts have been made to reduce the errors in quantum computing algorithms through the efficient synthesis of quantum circuits. In this study, we present an application of an optimization model for synthesizing quantum circuits with minimum implementation costs to lower the error rates by forming a simpler circuit. Our model has a unique structure that combines the arc-subset selection problem with a conventional multi-commodity network flow model. The model targets the circuit synthesis with multiple control Toffoli gates to implement Boolean reversible functions that are often used as a key component in many quantum algorithms. Compared to previous studies, the proposed model has a unifying yet straightforward structure for exploiting the operational characteristics of quantum gates. Our computational experiment shows the potential of the proposed model, obtaining quantum circuits with significantly lower quantum costs compared to prior studies. The proposed model is also applicable to various other fields where reversible logic is utilized, such as low-power computing, fault-tolerant designs, and DNA computing. In addition, our model can be applied to network-based problems, such as logistics distribution and time-stage network problems.

Development of 454 New Kompetitive Allele-Specific PCR (KASP) Markers for Temperate japonica Rice Varieties.

Temperate japonica rice varieties exhibit wide variation in the phenotypes of several important agronomic traits, including disease resistance, pre-harvest sprouting resistance, plant architecture, and grain quality, indicating the presence of genes contributing to favorable agronomic traits. However, gene mapping and molecular breeding has been hampered as a result of the low genetic diversity among cultivars and scarcity of polymorphic DNA markers. Single nucleotide polymorphism (SNP)-based kompetitive allele-specific PCR (KASP) markers allow high-throughput genotyping for marker-assisted selection and quantitative trait loci (QTL) mapping within closely related populations. Previously, we identified 740,566 SNPs and developed 771 KASP markers for Korean temperate japonica rice varieties. However, additional markers were needed to provide sufficient genome coverage to support breeding programs. In this study, the 740,566 SNPs were categorized according to their predicted impacts on gene function. The high-impact, moderate-impact, modifier, and low-impact groups contained 703 (0.1%), 20,179 (2.7%), 699,866 (94.5%), and 19,818 (2.7%) SNPs, respectively. A subset of 357 SNPs from the high-impact group was selected for initial KASP marker development, resulting in 283 polymorphic KASP markers. After incorporation of the 283 markers with the 771 existing markers in a physical map, additional markers were developed to fill genomic regions with large gaps between markers, and 171 polymorphic KASP markers were successfully developed from 284 SNPs. Overall, a set of 1225 KASP markers was produced. The markers were evenly distributed across the rice genome, with average marker density of 3.3 KASP markers per Mbp. The 1225 KASP markers will facilitate QTL/gene mapping and marker-assisted selection in temperate japonica rice breeding programs.

High-throughput phenotyping platform for analyzing drought tolerance in rice.

MAIN CONCLUSION: A new imaging platform was constructed to analyze drought-tolerant traits of rice. Rice was used to quantify drought phenotypes through image-based parameters and analyzing tools. Climate change has increased the frequency and severity of drought, which limits crop production worldwide. Developing new cultivars with increased drought tolerance and short breeding cycles is critical. However, achieving this goal requires phenotyping a large number of breeding populations in a short time and in an accurate manner. Novel cutting-edge technologies such as those based on remote sensors are being applied to solve this problem. In this study, new technologies were applied to obtain and analyze imaging data and establish efficient screening platforms for drought tolerance in rice using the drought-tolerant mutant osphyb. Red-Green-Blue images were used to predict plant area, color, and compactness. Near-infrared imaging was used to determine the water content of rice, infrared was used to assess plant temperature, and fluorescence was used to examine photosynthesis efficiency. DroughtSpotter technology was used to determine water use efficiency, plant water loss rate, and transpiration rate. The results indicate that these methods can detect the difference between tolerant and susceptible plants, suggesting their value as high-throughput phenotyping methods for short breeding cycles as well as for functional genetic studies of tolerance to drought stress.

QTL mapping for pre-harvest sprouting resistance in japonica rice varieties utilizing genome re-sequencing.

Pre-harvest sprouting (PHS) leads to serious economic losses because of reductions in yield and quality. To analyze the quantitative trait loci (QTLs) for PHS resistance in japonica rice, PHS rates on panicles were measured in 160 recombinant inbred lines (RILs) derived from a cross between the temperate japonica varieties Odae (PHS resistant) and Unbong40 (PHS susceptible) under two different environmental conditions-field (summer) and greenhouse (winter) environments. Genome re-sequencing of the parental varieties detected 266,773 DNA polymorphisms including 248,255 single nucleotide polymorphisms and 18,518 insertions/deletions. We constructed a genetic map comprising 239 kompetitive allele-specific PCR and 49 cleaved amplified polymorphic sequence markers. In the field environment, two major QTLs, qPHS-3FD and qPHS-11FD, were identified on chromosomes 3 and 11, respectively, whereas three major QTLs, qPHS-3GH, qPHS-4GH, and qPHS-11GH, were identified on chromosomes 3, 4, and 11, respectively, in the greenhouse environment. qPHS-11GH and qPHS-11FD had similar locations on chromosome 11, suggesting the existence of a gene conferring stable PHS resistance effects under different environmental conditions. The QTLs identified in this study can be used to improve the PHS resistance of japonica varieties, and they may improve our understanding of the genetic basis of PHS resistance.

High Throughput Phenotyping for Various Traits on Soybean Seeds Using Image Analysis.

Data phenotyping traits on soybean seeds such as shape and color has been obscure because it is difficult to define them clearly. Further, it takes too much time and effort to have sufficient number of samplings especially length and width. These difficulties prevented seed morphology to be incorporated into efficient breeding program. Here, we propose methods for an image acquisition, a data processing, and analysis for the morphology and color of soybean seeds by high-throughput method using images analysis. As results, quantitative values for colors and various types of morphological traits could be screened to create a standard for subsequent evaluation of the genotype. Phenotyping method in the current study could define the morphology and color of soybean seeds in highly accurate and reliable manner. Further, this method enables the measurement and analysis of large amounts of plant seed phenotype data in a short time, which was not possible before. Fast and precise phenotype data obtained here may facilitate Genome Wide Association Study for the gene function analysis as well as for development of the elite varieties having desirable seed traits.

Network analysis reveals succession of Microcystis genotypes accompanying distinctive microbial modules with recurrent patterns.

Every member of the ecological community is connected via a network of vital and complex relationships, called the web of life. To elucidate the ecological network and interactions among producers, consumers, and decomposers in the Daechung Reservoir, Korea, during cyanobacterial harmful algal blooms (cyanoHAB), especially those involving Microcystis, we investigated the diversity and compositions of the cyanobacterial (16S rRNA gene), including the genotypes of Microcystis (cpcBA-IGS gene), non-cyanobacterial (16S), and eukaryotic (18S) communities through high-throughput sequencing. Microcystis blooms were divided into the Summer Major Bloom and Autumn Minor Bloom with different dominant genotypes of Microcystis. Network analysis demonstrated that the modules involved in the different phases of the Microcystis blooms were categorized into the Pre-Bloom, Bloom, Post-Bloom, and Non-Bloom Groups at all sampling stations. In addition, the non-cyanobacterial components of each Group were classified, while the same Group showed similarity across all stations, suggesting that Microcystis and other microbes were highly interdependent and organized into cyanoHAB-related module units. Importantly, the Microcystis genotype-based sub-network uncovered that Pirellula, Pseudanabaena, and Vampirovibrionales preferred to interact with specific Microcystis genotypes in the Summer Major Bloom than with other genotypes in the Autumn Minor Bloom, while the copepod Skistodiaptomus exhibited the opposite pattern. In conclusion, the transition patterns of cyanoHAB-related modules and their key components could be crucial in the succession of Microcystis genotypes and to enhance the understanding of microbial ecology in an aquatic environment.

Mutations in the microRNA172 binding site of SUPERNUMERARY BRACT (SNB) suppress internode elongation in rice.

BACKGROUND: Internode elongation is an important agronomic trait in rice that determines culm length, which is related to lodging, panicle exsertion, and biomass. sui4 (shortened uppermost internode 4) mutants show reduced internode length and a dwarf phenotype due to shortened internodes; the uppermost internode is particularly severely affected. The present study was performed to identify the molecular nature and function of the SUI4 gene during internode elongation. RESULTS: Our previous study showed that the SUI4 gene was mapped to a 1.1-Mb interval on chromosome 7 (Ji et al. 2014). In order to isolate the gene responsible for the sui4 phenotype, genomic DNA resequencing of sui4 mutants and wild-type plants and reciprocal transformation of wild-type and mutant alleles of the putative SUI4 gene was performed. The data revealed that the causative mutation of sui4 was a T to A nucleotide substitution at the microRNA172 binding site of Os07g0235800, and that SUI4 is a new allele of the previously reported gene SUPERNUMERARY BRACT (SNB), which affects flower structure. In order to understand the effect of this mutation on expression of the SUI4/SNB gene, SUI4/SNB native promoter-fuzed GUS transgenics were examined, along with qRT-PCR analysis at various developmental stages. In sui4 mutants, the SUI4/SNB gene was upregulated in the leaves, culms, and panicles, especially when internodes were elongated. In culms, SUI4/SNB was expressed in the nodes and the lower parts of elongating internodes. In order to further explore the molecular nature of SUI4/SNB during internode elongation, RNA-seq and qRT-PCR analysis were performed with RNAs from the culms of sui4 mutants and wild-type plants in the booting stage. The data showed that in sui4 mutants, genes deactivating bioactive gibberellins and cytokinin were upregulated while genes related to cell expansion and cell wall synthesis were downregulated. CONCLUSION: In summary, this paper shows that interaction between SUI4/SNB and microRNA172 could determine internode elongation during the reproductive stage in rice plants. Due to a mutation at the microRNA172 binding site in sui4 mutants, the expression of SUI4/SNB was enhanced, which lowered the activities of cell expansion and cell wall synthesis and consequently resulted in shortened internodes.

The opening of phenome-assisted selection era in the early seedling stage.

Faster and more efficient breeding cycle is not an option to deal with unpredictable and fast global climate changes. Phenomics for collecting huge number of individuals in accurate manner could be an answer to solve this problem. We collected image data to measure plant height and manual data for shoot length to be compared. QTLs clustered of plant height and shoot length were detected in 2-week old seedlings, which was consistent with many other reports using various genetic resources in matured stage. Further, these traits are highly correlated with yield by pleiotropism or tight linkage of those traits. It implies the "phenome-assisted selection" can be applied for yield trait in rice in the very early stage to shorten the breeding cycle significantly in fast but low-cost manner.

Rice Genome Resequencing Reveals a Major Quantitative Trait Locus for Resistance to Bakanae Disease Caused by Fusarium fujikuroi.

Bakanae disease (BD), caused by the fungal pathogen Fusarium fujikuroi, has become a serious threat in rice-cultivating regions worldwide. In the present study, quantitative trait locus (QTL) mapping was performed using F2 and F3 plants derived after crossing a BD-resistant and a BD-susceptible Korean japonica rice variety, 'Samgwang' and 'Junam', respectively. Resequencing of 'Junam' and 'Samgwang' genomes revealed 151,916 DNA polymorphisms between the two varieties. After genotyping 188 F2 plants, we constructed a genetic map comprising 184 markers, including 175 kompetitive allele-specific PCR markers, eight cleaved amplified polymorphic sequence (CAPS) markers, and a derived CAPS (dCAPS) marker. The degree of BD susceptibility of each F2 plant was evaluated on the basis of the mortality rate measured with corresponding F3 progeny seedlings by in vitro screening. Consequently, qFfR9, a major QTL, was discovered at 30.1 centimorgan (cM) on chromosome 9 with a logarithm of the odds score of 60.3. For the QTL interval, 95% probability lay within a 7.24-7.56 Mbp interval. In this interval, we found that eight genes exhibited non-synonymous single nucleotide polymorphisms (SNPs) by comparing the 'Junam' and 'Samgwang' genome sequence data, and are possibly candidate genes for qFfR9; therefore, qFfR9 could be utilized as a valuable resource for breeding BD-resistant rice varieties.

Mapping of a major quantitative trait locus for bakanae disease resistance in rice by genome resequencing.

Bakanae disease (BD) has emerged as a serious threat in almost all rice cultivation regions worldwide. Nampyeong is a Korean japonica rice variety known to be resistant to BD. In this study, quantitative trait locus (QTL) mapping was performed with F2 and F3 plants derived from a cross between the Nampyeong variety and a susceptible Korean japonica line, DongjinAD. First, resequencing of Nampyeong and DongjinAD was performed, which identified 171,035 single nucleotide polymorphisms (SNPs) between the two parental varieties. Using these SNPs, 161 cleaved amplified polymorphic sequence (CAPS) markers and six derived CAPS markers were developed; then, a genetic map was constructed from the genotypes of 180 plants from the DongjinAD/Nampyeong F2 plants. The total length of the constructed genetic map was 1386 cM, with an average interval of 8.9 cM between markers. The BD mortality rates of each F3 family were measured by testing 40 F3 progenies using in vitro seedling screening method. QTL analysis based on the genetic map and mortality rate data revealed a major QTL, qFfR1, on rice chromosome 1. qFfR1 was located at 89.8 cM with a logarithm of the odds (LOD) score of 22.7. Further, there were three markers at this point: JNS01033, JNS01037, and JNS01041. A total of 15 genes were identified with annotations related to defense against plant diseases among the 179 genes in the qFfR1 interval at 95% probability, thereby providing potential candidate genes for qFfR1. qFfR1 and its closely linked markers will be useful in breeding rice varieties resistant to BD.