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Current systems to screen for transgenic soybeans (Glycine max) involve laborious molecular assays or the expression of fluorescent markers that are difficult to see in soybean plants. Therefore, a visual system for early screening of transgenic plants would increase the efficiency of crop improvement by genome editing. The RUBY reporter system, which consists of three genes encoding betalain biosynthetic enzymes, leading to the accumulation of purple pigment in transgenic tissue, has been employed in some plants and dikaryon fungi. Here, we assessed the RUBY reporter for visual verification during soybean transformation. We show that RUBY can be expressed in soybean, allowing for visual confirmation of transgenic events without the need for specialized equipment. Plants with visible accumulation of purple pigment in any tissue were successfully transformed, confirming the accuracy of the RUBY system as a visual indicator. We also assessed the genetic stability of the transgene across generations, which can be performed very early, using the cotyledons of the progeny. Transgene-free seedlings have a distinct green color, facilitating the selection of genome-edited but transgene-free soybean seedlings for harvest. Using the RUBY system, we quickly identified a transgene-free Gmwaxy mutant in the T1 generation. This system thus provides an efficient and convenient tool for soybean genome editing.

Besides providing energy to sustain life, mitochondria also play crucial roles in stress response and programmed cell death. The mitochondrial hallmark lipid, cardiolipin (CL), is essential to the maintenance of mitochondrial structure and function. However, how mitochondria and CL are involved in stress response is not as well defined in plants as in animal and yeast cells. We previously revealed a role for CL in mitochondrial fission and in heat stress response in Arabidopsis. To further determine the involvement of mitochondria and CL in plant heat response, here we treated Arabidopsis seedlings with varied lengths of acute heat stress. These treatments resulted in decreases in mitochondrial membrane potential, disruption of mitochondrial ultrastructure, accumulation of mitochondrial reactive-oxygen species (ROS), and redistribution of CL to the outer mitochondrial membrane and to a novel type of vesicle. The level of the observed changes correlated with the severeness of the heat stress, indicating the strong relevance of these processes to stress response. Our findings provide the basis for studying mechanisms underpinning the role of mitochondria and CL in plant stress response.

Plant height is an important agronomic trait that affects high-density tolerance and lodging resistance. However, the regulators and their underlying molecular mechanisms controlling plant height in maize remain understudied. Here, we report that knockout mutants of the calcium-dependent protein kinase gene ZmCPK39 (ZmCPK39-KO) exhibit dramatically reduced plant height, characterized by shorter internodes and a slight decrease in node numbers. Furthermore, we identified a ZmCPK39-interacting protein, the knotted-related homeobox (ZmKnox2), and observed that plant height was also significantly reduced in a mutator transposon-inserted mutant of ZmKnox2 (ZmKnox2-Mu). Combined analysis of transcriptomic and metabonomic data indicates that multiple phytohormone signaling and photosynthesis pathways are disrupted in both ZmCPK39-KO and ZmKnox2-Mu mutants. Taken together, these results provide new insights into the function of ZmCPK39 and identify potential targets for breeding lodging-resistant and high-density tolerant maize cultivars.

Genome editing is a promising technique that has been broadly utilized for basic gene function studies and trait improvements. Simultaneously, the exponential growth of computational power and big data now promote the application of machine learning for biological research. In this regard, machine learning shows great potential in the refinement of genome editing systems and crop improvement. Here, we review the advances of machine learning to genome editing optimization, with emphasis placed on editing efficiency and specificity enhancement. Additionally, we demonstrate how machine learning bridges genome editing and crop breeding, by accurate key site detection and guide RNA design. Finally, we discuss the current challenges and prospects of these two techniques in crop improvement. By integrating advanced genome editing techniques with machine learning, progress in crop breeding will be further accelerated in the future.

Bread wheat (Triticum aestivum) is an important crop and serves as a significant source of protein and calories for humans, worldwide. Nevertheless, its large and allopolyploid genome poses constraints on genetic improvement. The complex reticulate evolutionary history and the intricacy of genomic resources make the deciphering of the functional genome considerably more challenging. Recently, we have developed a comprehensive list of versatile computational tools with the integration of statistical models for dissecting the polyploid wheat genome. Here, we summarize the methodological innovations and applications of these tools and databases. A series of step-by-step examples illustrates how these tools can be utilized for dissecting wheat germplasm resources and unveiling functional genes associated with important agronomic traits. Furthermore, we outline future perspectives on new advanced tools and databases, taking into consideration the unique features of bread wheat, to accelerate genomic-assisted wheat breeding.

Rice yield and disease resistance are two crucial factors in determining the suitability of a gene for agricultural breeding. Decreased grain size1 (DGS1), encoding an RING-type E3 ligase, has been found to have a positive effect on rice yield by regulating rice grain number and 1000-grain weight. However, the role of DGS1 in rice blast resistance is still unknown. In this study, we report that DGS1 enhances disease resistance by improving PTI responses, including stronger ROS burst and MAPK activation, and also increased expression of defense-related genes. Furthermore, DGS1 works in conjunction with ubiquitin conjugating enzyme OsUBC45 as an E2–E3 pair to facilitate the ubiquitin-dependent degradation of OsGSK3 and OsPIP2;1, thereby influencing rice yield and immunity, respectively. Therefore, the DGS1-OsUBC45 module has the potential in facilitating rice agricultural breeding.

Genomic data serve as an invaluable resource for unraveling the intricacies of the higher plant systems, including the constituent elements within and among species. Through various efforts in genomic data archiving, integrative analysis and value-added curation, the National Genomics Data Center (NGDC), which is a part of the China National Center for Bioinformation (CNCB), has successfully established and currently maintains a vast amount of database resources. This dedicated initiative of the NGDC facilitates a data-rich ecosystem that greatly strengthens and supports genomic research efforts. Here, we present a comprehensive overview of central repositories dedicated to archiving, presenting, and sharing plant omics data, introduce knowledgebases focused on variants or gene-based functional insights, highlight species-specific multiple omics database resources, and briefly review the online application tools. We intend that this review can be used as a guide map for plant researchers wishing to select effective data resources from the NGDC for their specific areas of study.

The garden pea (Pisum sativum L.) is a significant cool-season legume, serving as crucial food sources, animal feed, and industrial raw materials. The advancement of functional genomics over the past two decades has provided substantial theoretical foundations and progress to pea breeding. Notably, the release of the pea reference genome has enhanced our understanding of plant architecture, symbiotic nitrogen fixation (SNF), flowering time, floral organ development, seed development, and stress resistance. However, a considerable gap remains between pea functional genomics and molecular breeding. This review summarizes the current advancements in pea functional genomics and breeding while highlighting the future challenges in pea molecular breeding.

The CRISPR/Cas9 technology revolutionizes targeted gene knockout in diverse organisms including plants. However, screening edited alleles, particularly those with multiplex editing, from herbicide- or antibiotic-resistant transgenic plants and segregating out the Cas9 transgene represent two laborious processes. Current solutions to facilitate these processes rely on different selection markers. Here, by taking advantage of the opposite functions of a d-amino acid oxidase (DAO) in detoxifying d-serine and in metabolizing non-toxic d-valine to a cytotoxic product, we develop a DAO-based selection system that simultaneously enables the enrichment of multigene edited alleles and elimination of Cas9-containing progeny in Arabidopsis thaliana. Among five DAOs tested in Escherichia coli, the one encoded by Trigonopsis variabilis (TvDAO) could confer slightly stronger d-serine resistance than other homologs. Transgenic expression of TvDAO in Arabidopsis allowed a clear distinction between transgenic and non-transgenic plants in both d-serine-conditioned positive selection and d-valine-conditioned negative selection. As a proof of concept, we combined CRISPR-induced single-strand annealing repair of a dead TvDAO with d-serine-based positive selection to help identify transgenic plants with multiplex editing, where d-serine-resistant plants exhibited considerably higher co-editing frequencies at three endogenous target genes than those selected by hygromycin. Subsequently, d-valine-based negative selection successfully removed Cas9 and TvDAO transgenes from the survival offspring carrying inherited mutations. Collectively, this work provides a novel strategy to ease CRISPR mutant identification and Cas9 transgene elimination using a single selection marker, which promises more efficient and simplified multiplex CRISPR editing in plants.