A KNOX â ¡ transcription factor suppresses the NLR immune receptor BRG8-mediated immunity in rice.

Nucleotide-binding site and leucine-rich repeat (NLR) proteins are activated by detecting pathogen effectors, which in turn trigger host defenses and cell death. Although many NLRs have been identified, the mechanism responsible for NLR-triggered defense responses are still poorly understood. In this study, through GWAS approach, we identified a novel NLR gene, Blast Resistance Gene 8 (BRG8), conferring resistance to rice blast and bacterial blight diseases. Consistently, the BRG8 overexpression and complementation lines exhibited enhanced resistance to both pathogens. Subcellular localization assays showed that BRG8 localized in both cytoplasm and nucleus. More evidence revealed that nuclear-localized BRG8 enhanced rice immunity without hypersensitive response (HR)-like phenotype. Furthermore, we also demonstrated the CC domain of BRG8 not only physically interacted with itself, but also interacted with the KNOX Ⅱ protein HOMEOBOX ORYZA SATIVA59 (HOS59). Knockout of HOS59 in BRG8 background showed enhanced resistance to M. oryzae strain CH171 and Xoo strain CR4, similar to BRG8 background. In contrast, overexpression of HOS59 in BRG8 background, compromised the HR-like phenotype and resistance response. Further analysis revealed that HOS59 promotes the degradation of BRG8 via the 26S proteasome pathway. Collectively, our study highlights HOS59 as NLR immune regulators, fine-tune BRG8-mediated immune responses against pathogens, and provides new insights into NLR association and function in plant immunity.

ScRNA-seq reveals dark- and light-induced differentially expressed gene atlases of seedling leaves in Arachis hypogaea L.

Although the regulatory mechanisms of dark and light-induced plant morphogenesis have been broadly investigated, the biological process in peanuts has not been systematically explored on single-cell resolution. Herein, 10 cell clusters were characterized using scRNA-seq-identified marker genes, based on 13 409 and 11 296 single cells from 1-week-old peanut seedling leaves grown under dark and light conditions. 6104 genes and 50 transcription factors (TFs) displayed significant expression patterns in distinct cell clusters, which provided gene resources for profiling dark/light-induced candidate genes. Further pseudo-time trajectory and cell cycle evidence supported that dark repressed the cell division and perturbed normal cell cycle, especially the PORA abundances correlated with 11 TFs highly enriched in mesophyll to restrict the chlorophyllide synthesis. Additionally, light repressed the epidermis cell developmental trajectory extending by inhibiting the growth hormone pathway, and 21 TFs probably contributed to the different genes transcriptional dynamic. Eventually, peanut AHL17 was identified from the profile of differentially expressed TFs, which encoded protein located in the nucleus promoted leaf epidermal cell enlargement when ectopically overexpressed in Arabidopsis through the regulatory phytohormone pathway. Overall, our study presents the different gene atlases in peanut etiolated and green seedlings, providing novel biological insights to elucidate light-induced leaf cell development at the single-cell level.

Integrating genome-wide association study into genomic selection for the prediction of agronomic traits in rice (Oryza sativa L.).

Accurately identifying varieties with targeted agronomic traits was thought to contribute to genetic selection and accelerate rice breeding progress. Genomic selection (GS) is a promising technique that uses markers covering the whole genome to predict the genomic-estimated breeding values (GEBV), with the ability to select before phenotypes are measured. To choose the appropriate GS models for breeding work, we analyzed the predictability of nine agronomic traits measured from a population of 459 diverse rice varieties. By the comparison of eight representative GS models, we found that the prediction accuracies ranged from 0.407 to 0.896, with reproducing kernel Hilbert space (RKHS) having the highest predictive ability in most traits. Further results demonstrated the predictivity of GS is altered by several factors. Moreover, we assessed the method of integrating genome-wide association study (GWAS) into various GS models. The predictabilities of GS combined peak-associated markers generated from six different GWAS models were significantly different; a recommendation of Mixed Linear Model (MLM)-RKHS was given for the GWAS-GS-integrated prediction. Finally, based on the above result, we experimented with applying the P-values obtained from optimal GWAS models into ridge regression best linear unbiased prediction (rrBLUP), which benefited the low predictive traits in rice. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-023-01423-y.

LG5, a Novel Allele of EUI1, Regulates Grain Size and Flag Leaf Angle in Rice.

Grain size and flag leaf angle are two important traits that determining grain yield in rice. However, the mechanisms regulating these two traits remain largely unknown. In this study, a rice long grain 5 (lg5) mutant with a large flag leaf angle was identified, and map-based cloning revealed that a single base substitution followed by a 2 bp insertion in the LOC_Os05g40384 gene resulted in larger grains, a larger flag leaf angle, and higher plant height than the wild type. Sequence analysis revealed that lg5 is a novel allele of elongated uppermost internode-1 (EUI1), which encodes a cytochrome P450 protein. Functional complementation and overexpression tests showed that LG5 can rescue the bigger grain size and larger flag leaf angle in the Xiushui11 (XS) background. Knockdown of the LG5 transcription level by RNA interference resulted in elevated grain size and flag leaf angle in the Nipponbare (NIP) background. Morphological and cellular analyses suggested that LG5 regulated grain size and flag leaf angle by promoting cell expansion and cell proliferation. Our results provided new insight into the functions of EUI1 in rice, especially in regulating grain size and flag leaf angle, indicating a potential target for the improvement of rice breeding.

Genomic insight into genetic changes and shaping of major inbred rice cultivars in China.

The annual planting area of major inbred rice (Oryza sativa) cultivars reach more than half of the total annual planting area of inbred rice cultivars in China. However, how the major inbred rice cultivars changed during decades of genetic improvement and why they can be prevalently cultivated in China remains unclear. Here, we investigated the underlying genetic changes of major inbred cultivars and the contributions of landraces and introduced cultivars during the improvement by resequencing a collection of 439 rice accessions including major inbred cultivars, landraces, and introduced cultivars. The results showed that landraces were the main genetic contribution sources of major inbred Xian (Indica) cultivars, while introduced cultivars were that of major inbred Geng (Japonica) cultivars. Selection scans and haplotype frequency analysis shed light on the reflections of some well-known genes in rice improvement, and breeders had different preferences for the Xian's and Geng's breeding. Six candidate regions associated with agronomic traits were identified by genome-wide association mapping, five of which were under positive selection in rice improvement. Our study provides a comprehensive insight into the development of major inbred rice cultivars and lays the foundation for genomics-based breeding in rice.

Single-cell RNA-seq describes the transcriptome landscape and identifies critical transcription factors in the leaf blade of the allotetraploid peanut (Arachis hypogaea L.).

Single-cell RNA-seq (scRNA-seq) has been highlighted as a powerful tool for the description of human cell transcriptome, but the technology has not been broadly applied in plant cells. Herein, we describe the successful development of a robust protoplast cell isolation system in the peanut leaf. A total of 6,815 single cells were divided into eight cell clusters based on reported marker genes by applying scRNA-seq. Further, a pseudo-time analysis was used to describe the developmental trajectory and interaction network of transcription factors (TFs) of distinct cell types during leaf growth. The trajectory enabled re-investigation of the primordium-driven development processes of the mesophyll and epidermis. These results suggest that palisade cells likely differentiate into spongy cells, while the epidermal cells originated earlier than the primordium. Subsequently, the developed method integrated multiple technologies to efficiently validate the scRNA-seq result in a homogenous cell population. The expression levels of several TFs were strongly correlated with epidermal ontogeny in accordance with obtained scRNA-seq values. Additionally, peanut AHL23 (AT-HOOK MOTIF NUCLEAR LOCALIZED PROTEIN 23), which is localized in nucleus, promoted leaf growth when ectopically expressed in Arabidopsis by modulating the phytohormone pathway. Together, our study displays that application of scRNA-seq can provide new hypotheses regarding cell differentiation in the leaf blade of Arachis hypogaea. We believe that this approach will enable significant advances in the functional study of leaf blade cells in the allotetraploid peanut and other plant species.