Summary: Stalk rot caused by Fusarium verticillioides (Fv) is one of the most destructive diseases in maize production. The defence response of root system to Fv invasion is important for plant growth and development. Dissection of root cell type‐specific response to Fv infection and its underlying transcription regulatory networks will aid in understanding the defence mechanism of maize roots to Fv invasion. Here, we reported the transcriptomes of 29 217 single cells derived from root tips of two maize inbred lines inoculated with Fv and mock condition, and identified seven major cell types with 21 transcriptionally distinct cell clusters. Through the weighted gene co‐expression network analysis, we identified 12 Fv‐responsive regulatory modules from 4049 differentially expressed genes (DEGs) that were activated or repressed by Fv infection in these seven cell types. Using a machining‐learning approach, we constructed six cell type‐specific immune regulatory networks by integrating Fv‐induced DEGs from the cell type‐specific transcriptomes, 16 known maize disease‐resistant genes, five experimentally validated genes (ZmWOX5b, ZmPIN1a, ZmPAL6, ZmCCoAOMT2, and ZmCOMT), and 42 QTL or QTN predicted genes that are associated with Fv resistance. Taken together, this study provides not only a global view of maize cell fate determination during root development but also insights into the immune regulatory networks in major cell types of maize root tips at single‐cell resolution, thus laying the foundation for dissecting molecular mechanisms underlying disease resistance in maize.

Key message : A comprehensive linkage atlas for seed yield in rapeseed. Most agronomic traits of interest for crop improvement (including seed yield) are highly complex quantitative traits controlled by numerous genetic loci, which brings challenges for comprehensively capturing associated markers/genes. We propose that multiple trait interactions underlie complex traits such as seed yield, and that considering these component traits and their interactions can dissect individual quantitative trait loci (QTL) effects more effectively and improve yield predictions. Using a segregating rapeseed (Brassica napus) population, we analyzed a large set of trait data generated in 19 independent experiments to investigate correlations between seed yield and other complex traits, and further identified QTL in this population with a SNP-based genetic bin map. A total of 1904 consensus QTL accounting for 22 traits, including 80 QTL directly affecting seed yield, were anchored to the B. napus reference sequence. Through trait association analysis and QTL meta-analysis, we identified a total of 525 indivisible QTL that either directly or indirectly contributed to seed yield, of which 295 QTL were detected across multiple environments. A majority (81.5%) of the 525 QTL were pleiotropic. By considering associations between traits, we identified 25 yield-related QTL previously ignored due to contrasting genetic effects, as well as 31 QTL with minor complementary effects. Implementation of the 525 QTL in genomic prediction models improved seed yield prediction accuracy. Dissecting the genetic and phenotypic interrelationships underlying complex quantitative traits using this method will provide valuable insights for genomics-based crop improvement.

Haloxylon ammodendron (C. A. Mey.) is widely distributed across a range of habitats, including gravel desert, clay desert, fixed and semi-fixed sand, and saline land in Asian and African deserts. To date, no genomic information or expressed sequence tag-simple sequence repeat (EST-SSR) marker has been reported for H. ammodendron plants. Using Illumina sequencing technology, we generated over two billion bases of high-quality sequence data on H. ammodendron and conducted de novo assembly and annotation of genes without prior genome information. These reads were assembled into 79,918 unigenes (mean length = 728 bp). Based on similarity searches comparing these unigenes with known proteins in the non-redundant (nr) protein database, 25,619 unigenes were functionally annotated with a cut-off E-value of 10-5. In addition, DGE reads were mapped to the assembled transcriptome for gene expression analysis under drought stress. In total, 1,060 differentially expressed genes were identified. Among these genes, 356 genes were upregulated after drought treatment, and 704 genes were downregulated. We used the KEGG database to annotate these drought-induced genes; 207 unigenes were identified in the KEGG pathway annotation, and approximately 12.1% of the unigenes with known function fell into categories related to fatty acid metabolism, starch and sucrose metabolism, and nitrogen metabolism, suggesting that these pathways or processes may be involved in the drought response. Together, a total of 35 drought-inducible transcription factors were identified, including WRKY, MYB and bZIP family members. Our study is the first to provide a transcriptome sequence resource for H. ammodendron plants and to determine its digital gene expression profile under drought conditions using the assembled transcriptome data for reference. These data provide a valuable resource for genetic and genomic studies of desert plants under abiotic conditions.

Based on the logistic growth model, the relationship between technology innovation and the evolution of economic forms was analyzed, and the main characteristics and basic laws of the five economic forms of hunter–gatherer, agriculture, industry, information, and bioeconomy were summarized. Based on a comprehensive and intensive scan of the latest bioeconomy development strategies of various countries, we summarized their two main driving forces from the technological supply side and economic and social demand side, as well as their four distinctive features, namely the comprehensiveness of science and technology innovation, the aggregation of industrial development, the globalization of development goals, and strong policy dependence. Finally, we proposed countermeasures to design the implementation path of the bioeconomy and improve the quality of the bioeconomy factor supply in terms of the development and application of biotechnology, the upgradation of bioindustry clusters, the positive policy environment, and the theorization of the bioeconomy.

Flax is an important field crop that can be used for either oilseed or fiber production. Plant height and technical length are important characters for flax. For linseed flax, plants usually have a short technical length and plant height than those for fiber flax. As an important agronomical character for fiber and linseed flax, plant height is usually a selection target for breeding. However, because of limited technologies and methods available, there has been little research focused on discovering the molecular mechanism controlling plant height. In this study, two related recombinant inbred line (RIL) populations developed from crosses of linseed and fiber parents were developed and phenotyped for plant height and technical length in four environments. A consensus linkage map based on two RIL populations was constructed using SNP markers generated by genotyping by sequencing (GBS) technology. A total of 4497 single nucleotide polymorphism (SNP) markers were included on 15 linkage groups with an average marker density of one marker every 2.71 cM. Quantitative trait locus (QTL) mapping analysis was performed for plant height and technical length using the two populations. A total of 19 QTLs were identified for plant height and technical length. For the MH population, eight plant height QTLs and seven technical length QTLs were identified, five of which were common QTLs for both traits. For the PH population, six plant height and three technical length QTLs were identified. By comparing the QTLs and candidate gene information in the two population, two common QTLs and three candidate genes were discovered. This study provides a foundation for map-based cloning of QTLs and marker-assisted selection for plant height-related traits in linseed and fiber flax.

Gene editing (GE) has become one of the mainstream bioengineering technologies over the past two decades, mainly fueled by the rapid development of the CRISPR/Cas system since 2012. To date, plenty of articles related to the progress and applications of GE have been published globally, but the objective, quantitative and comprehensive investigations of them are relatively few. Here, 13,980 research articles and reviews published since 1999 were collected by using GE-related queries in the Web of Science. We used bibliometric analysis to investigate the competitiveness and cooperation of leading countries, influential affiliations, and prolific authors. Text clustering methods were used to assess technical trends and research hotspots dynamically. The global application status and regulatory framework were also summarized. This analysis illustrates the bottleneck of the GE innovation and provides insights into the future trajectory of development and application of the technology in various fields, which will be helpful for the popularization of gene editing technology.