Among CRISPR-Cas genome editing systems, Streptococcus pyogenes Cas9 (SpCas9), sourced from a human pathogen, is the most widely used. Here, through in silico data mining, we have established an efficient plant genome engineering system using CRISPR-Cas9 from probiotic Lactobacillus rhamnosus. We have confirmed the predicted 5’-NGAAA-3’ PAM via a bacterial PAM depletion assay and showcased its exceptional editing efficiency in rice, wheat, tomato, and Larix cells, surpassing LbCas12a, SpCas9-NG, and SpRY when targeting the identical sequences. In stable rice lines, LrCas9 facilitates multiplexed gene knockout through coding sequence editing and achieves gene knockdown via targeted promoter deletion, demonstrating high specificity. We have also developed LrCas9-derived cytosine and adenine base editors, expanding base editing capabilities. Finally, by harnessing LrCas9’s A/T-rich PAM targeting preference, we have created efficient CRISPR interference and activation systems in plants. Together, our work establishes CRISPR-LrCas9 as an efficient and user-friendly genome engineering tool for diverse applications in crops and beyond.

To rationally utilize Morchella germplasm resources, this study investigated 13 phenotypic traits in 231 Chinese Morchella germplasm accessions. Accessions were grouped by cap color traits and analyzed using four sampling methods (simple proportion method, logarithmic proportion method, square root proportion method, and diversity proportion method) five sampling sizes (10%, 15%, 20%, 25%, and 30%), two genetic distances (Euclidean distance and Mahalanobis distance), and four clustering methods (class-means, minimum distance, maximum distance, and sum of squared deviations) to explore optimal sampling strategies and select core collection. Core collection for the optimal sampling strategy was selected based on six indicators: percentage difference in mean, percentage difference in variance, range conformity rate, coefficient of variation change rate, phenotypic frequency variance, and phenotypic retention ratio. Phenotypic traits of the core germplasm were evaluated using genetic diversity eigenvalues, t-tests, F-tests, and systematic clustering, with confirmation via principal component analysis. Results indicated that the logarithmic ratio method yielded optimal sampling, with 15% representing the optimal sample size. Euclidean distance outperformed Mahalanobis distance, and the maximum distance method proved optimal for clustering. Ultimately, 34 Morchella germplasm resources were selected, accounting for 14.72% of the total germplasm (original germplasm). Under the P < 0.05 probability threshold, the mean, standard deviation, coefficient of variation, and genetic diversity indices of the core collection showed no significant differences from the original germplasm. Cluster analysis revealed consistent grouping of germplasm resources and phenotypic trait clusters between the core and original germplasm. In principal component analysis, the eigenvalues and cumulative contribution rates of the first four principal components were higher for the core collection than for the original germplasm. This indicates that the core collection eliminated most genetic redundancy while retaining the genetic diversity of the original germplasm, demonstrating its representative selection. This study provides a reference basis for the effective utilization and germplasm innovation of Morchella germplasm resources.

To rationally utilize Morchella germplasm resources, this study investigated 13 phenotypic traits in 231 Chinese Morchella germplasm accessions. Accessions were stratified by cap color and subjected to comparative analyses using four sampling methods, five sampling intensities, two genetic distance metrics, and four hierarchical clustering algorithms to determine the optimal strategy for core collection construction. The optimal sampling strategy for core collection construction was identified using six evaluation. Phenotypic traits of the core collection were evaluated using genetic diversity eigenvalues, t-tests, F-tests, and systematic clustering, with confirmation via principal component analysis. The results indicate that the logarithmic ratio method yielded the smallest differences in group proportions, making it the optimal sampling method. A 15% sample intensity proved optimal, with Euclidean distance outperforming Mahalanobis distance. The longest-distance method was determined to be the optimal clustering approach. Within the optimal sampling strategy combination, the CR value reached its maximum (97.77%). Ultimately, 34 Morchella germplasm resources were extracted, accounting for 14.72% of the total germplasm (original germplasm). The mean values, standard deviations, and genetic diversity of phenotypic traits were similar between the original germplasm and the core collection. However, the coefficient of variation for quantitative traits showed significant differences. In the t-test, only the maturity period showed a significant difference. In the F-test, only the cap length/width and maturity period showed significant differences. Cluster analysis grouped the germplasm resources of the core collection and the original germplasm into relatively consistent clusters. In principal component analysis, the eigenvalues and cumulative contribution rates of the first four principal components were higher for the core collection than for the original germplasm. This indicates that the core collection eliminated most genetic redundancy while preserving the genetic diversity of the original germplasm. The core collection selection is representative and can be effectively utilized as breeding material. This study provides a reference for the effective utilization and germplasm innovation of Morchella germplasm resources.

Heavy metal contamination severely threatens soil ecosystems and edible fungi. Comparative analyses of three Morchella species under Pb stress identified Morchella sextelata as highly tolerant, warranting further investigation. Multi-omics analyses revealed that this resilience is mediated by an integrated post-transcriptional and metabolic regulatory system. A circRNA-miRNA-mRNA (ceRNA) network functions as a molecular switch to activate the core polyketide synthase gene MsPKS, redirecting metabolic flux toward defense pathways. This activation establishes a multi-dimensional defense network comprising: an enzymatic antioxidant shield via SOD; concurrent non-enzymatic biochemical buffering involving N-acetyl-D-cysteine and dTDP-sugars; and a structural barrier formed by PKS-derived pigments that sequester Pb and mitigate oxidative damage. Through this coordinated strategy, M. sextelata maintains cellular homeostasis while prioritizing survival under severe Pb stress. This study reveals a previously unrecognized link between post-transcriptional regulation and metabolite-driven heavy metal defense, providing a mechanistic basis for fungal adaptation and bioremediation potential.