Mutations in a barley cytochrome P450 gene enhances pathogen induced programmed cell death and cutin layer instability

Multiple, Single Trait GWAS and Supervised Machine Learning Reveal the Genetic Architecture of Fraxinus excelsior Tolerance to Ash Dieback in Europe

Common ash (Fraxinus excelsior) is under intensive attack from the invasive alien pathogenic fungus Hymenoscyphus fraxineus, causing ash dieback at epidemic levels throughout Europe. Previous studies have found significant genetic variation among genotypes in ash dieback susceptibility and that host phenology, such as autumn yellowing, is correlated with susceptibility of ash trees to H. fraxineus; however, the genomic basis of ash dieback tolerance in F. excelsior requires further investigation. Here, we integrate quantitative genetics based on multiple replicates and genome-wide association analyses with machine learning to reveal the genetic architecture of ash dieback tolerance and of phenological traits in F. excelsior populations in six European countries (Austria, Denmark, Germany, Ireland, Lithuania, Sweden). Based on phenotypic data of 486 F. excelsior replicated genotypes we observed negative genotypic correlations between crown damage caused by ash dieback and intensity of autumn leaf yellowing within multiple sampling sites. Our results suggest that the examined traits are polygenic and using genomic prediction models, with ranked single nucleotide polymorphisms (SNPs) based on GWAS associations as input, a large proportion of the variation was predicted by unlinked SNPs. Based on 100 unlinked SNPs, we can predict 55% of the variation in disease tolerance among genotypes (as phenotyped in genetic trials), increasing to a maximum of 63% when predicted from 9155 SNPs. In autumn leaf yellowing, 52% of variation is predicted by 100 unlinked SNPs, reaching a peak of 72% using 3740 SNPs. Based on feature permutations within genomic prediction models, a total of eight nonsynonymous SNPs linked to ash dieback crown damage and autumn leaf yellowing (three and five SNPs, respectively) were identified, these were located within genes related to plant defence (pattern triggered immunity, pathogen detection) and phenology (regulation of flowering and seed maturation, auxin transport). We did not find an overlap between genes associated with crown damage level and autumn leaf yellowing. Hence, our results shed light on the difference in the genomic basis of ADB tolerance and autumn leaf yellowing despite these two traits being correlated in quantitative genetic analysis. Overall, our methods show the applicability of genomic prediction models when combined with GWAS to reveal the genomic architecture of polygenic disease tolerance enabling the identification of ash dieback tolerant trees for breeding or conservation purposes.

Variability in Chromosome 1 of Select Moroccan Pyrenophora teres f. teres Isolates Overcomes a Highly Effective Barley Chromosome 6H Source of Resistance

Barley net form net blotch (NFNB) is a destructive foliar disease caused by Pyrenophora teres f. teres. Barley line CIho5791, which harbors the broadly effective chromosome 6H resistance gene Rpt5, displays dominant resistance to P. teres f. teres. To genetically characterize P. teres f. teres avirulence/virulence on the barley line CIho5791, we generated a P. teres f. teres mapping population using a cross between the Moroccan CIho5791-virulent isolate MorSM40-3 and the avirulent reference isolate 0-1. Full genome sequences were generated for 103 progenies. Saturated chromosome-level genetic maps were generated, and quantitative trait locus (QTL) mapping identified two major QTL associated with P. teres f. teres avirulence/virulence on CIho5791. The most significant QTL mapped to chromosome (Ch) 1, where the virulent allele was contributed by MorSM40-3. A second QTL mapped to Ch8; however, this virulent allele was contributed by the avirulent parent 0-1. The Ch1 and Ch8 loci accounted for 27 and 15% of the disease variation, respectively, and the avirulent allele at the Ch1 locus was epistatic over the virulent allele at the Ch8 locus. As a validation, we used a natural P. teres f. teres population in a genome-wide association study that identified the same Ch1 and Ch8 loci. We then generated a new reference quality genome assembly of parental isolate MorSM40-3 with annotation supported by deep transcriptome sequencing of infection time points. The annotation identified candidate genes predicted to encode small, secreted proteins, one or more of which are likely responsible for overcoming the CIho5791 resistance. [Formula: see text] The author(s) have dedicated the work to the public domain under the Creative Commons CC0 "No Rights Reserved" license by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law, 2024.

Integration of transcriptomics, metabolomics, and hormone analysis revealed the formation of lesion spots inhibited by GA and CTK was related to cell death and disease resistance in bread wheat (Triticum aestivum L.)

BACKGROUND

Wheat is one of the important grain crops in the world. The formation of lesion spots related to cell death is involved in disease resistance, whereas the regulatory pathway of lesion spot production and resistance mechanism to pathogens in wheat is largely unknown.

RESULTS

In this study, a pair of NILs (NIL-Lm5W and NIL-Lm5M) was constructed from the BC1F4 population by the wheat lesion mimic mutant MC21 and its wild genotype Chuannong 16. The formation of lesion spots in NIL-Lm5M significantly increased its resistance to stripe rust, and NIL-Lm5M showed superiour agronomic traits than NIL-Lm5W under stripe rust infection.Whereafter, the NILs were subjected to transcriptomic (stage N: no spots; stage S, only a few spots; and stage M, numerous spots), metabolomic (stage N and S), and hormone analysis (stage S), with samples taken from normal plants in the field. Transcriptomic analysis showed that the differentially expressed genes were enriched in plant-pathogen interaction, and defense-related genes were significantly upregulated following the formation of lesion spots. Metabolomic analysis showed that the differentially accumulated metabolites were enriched in energy metabolism, including amino acid metabolism, carbohydrate metabolism, and lipid metabolism. Correlation network diagrams of transcriptomic and metabolomic showed that they were both enriched in energy metabolism. Additionally, the contents of gibberellin A7, cis-Zeatin, and abscisic acid were decreased in leaves upon lesion spot formation, whereas the lesion spots in NIL-Lm5M leaves were restrained by spaying GA and cytokinin (CTK, trans-zeatin) in the field.

CONCLUSION

The formation of lesion spots can result in cell death and enhance strip rust resistance by protein degradation pathway and defense-related genes overexpression in wheat. Besides, the formation of lesion spots was significantly affected by GA and CTK. Altogether, these results may contribute to the understanding of lesion spot formation in wheat and laid a foundation for regulating the resistance mechanism to stripe rust.

Functional annotation and meta-analysis of maize transcriptomes reveal genes involved in biotic and abiotic stress

BACKGROUND

Environmental stress factors, such as biotic and abiotic stress, are becoming more common due to climate variability, significantly affecting global maize yield. Transcriptome profiling studies provide insights into the molecular mechanisms underlying stress response in maize, though the functions of many genes are still unknown. To enhance the functional annotation of maize-specific genes, MaizeGDB has outlined a data-driven approach with an emphasis on identifying genes and traits related to biotic and abiotic stress.

RESULTS

We mapped high-quality RNA-Seq expression reads from 24 different publicly available datasets (17 abiotic and seven biotic studies) generated from the B73 cultivar to the recent version of the reference genome B73 (B73v5) and deduced stress-related functional annotation of maize gene models. We conducted a robust meta-analysis of the transcriptome profiles from the datasets to identify maize loci responsive to stress, identifying 3,230 differentially expressed genes (DEGs): 2,555 DEGs regulated in response to abiotic stress, 408 DEGs regulated during biotic stress, and 267 common DEGs (co-DEGs) that overlap between abiotic and biotic stress. We discovered hub genes from network analyses, and among the hub genes of the co-DEGs we identified a putative NAC domain transcription factor superfamily protein (Zm00001eb369060) IDP275, which previously responded to herbivory and drought stress. IDP275 was up-regulated in our analysis in response to eight different abiotic and four different biotic stresses. A gene set enrichment and pathway analysis of hub genes of the co-DEGs revealed hormone-mediated signaling processes and phenylpropanoid biosynthesis pathways, respectively. Using phylostratigraphic analysis, we also demonstrated how abiotic and biotic stress genes differentially evolve to adapt to changing environments.

CONCLUSIONS

These results will help facilitate the functional annotation of multiple stress response gene models and annotation in maize. Data can be accessed and downloaded at the Maize Genetics and Genomics Database (MaizeGDB).

A mitochondria-targeted far-red AIE fluorescent probe for distinguishing between mitophagy and ferroptosis in cancer cells

A mitochondria-targeted far-red fluorescent probe LY-1 with AIE character was formulated to track cell viscosity alterations with excellent sensitivity and selectivity, which was used to discriminate between mitophagy and ferroptosis in cancer cells. Probe LY-1 is expected to be an effective vehicle for the diagnosis of mitochondrial viscosity relevant diseases.

LESION MIMIC MUTANT 1 confers basal resistance to Sclerotinia sclerotiorum in rapeseed via a salicylic acid-dependent pathway

Rapeseed (Brassica napus) is a major edible oilseed crop consumed worldwide. However, its yield is seriously affected by infection from the broad-spectrum non-obligate pathogen Sclerotinia sclerotiorum due to a lack of highly resistant germplasm. Here, we identified a Sclerotinia-resistant and light-dependent lesion mimic mutant from an ethyl methanesulfonate-mutagenized population of the rapeseed inbred Zhongshuang 11 (ZS11) named lesion mimic mutant 1 (lmm1). The phenotype of lmm1 is controlled by a single recessive gene, named LESION MIMIC MUTANT 1 (LMM1), which mapped onto chromosome C04 by bulked segregant analysis within a 2.71-Mb interval. Histochemical analysis indicated that H2O2 strongly accumulated and cell death occurred around the lesion mimic spots. Among 877 differentially expressed genes (DEGs) between ZS11 and lmm1 leaves, 188 DEGs were enriched in the defense response, including 95 DEGs involved in systemic acquired resistance, which is consistent with the higher salicylic acid levels in lmm1. Combining bulked segregant analysis and transcriptome analysis, we identified a significantly up-regulated gene, BnaC4.PR2, which encodes β-1,3-glucanase, as the candidate gene for LMM1. Overexpression of BnaC4.PR2 may induce a reactive oxygen species burst to trigger partial cell death and systemic acquired resistance. Our study provides a new genetic resource for S. sclerotiorum resistance as well as new insights into disease resistance breeding in B. napus.

Comparative transcriptome meta-analysis reveals a set of genes involved in the responses to multiple pathogens in maize

Maize production is constantly threatened by the presence of different fungal pathogens worldwide. Genetic resistance is the most favorable approach to reducing yield losses resulted from fungal diseases. The molecular mechanism underlying disease resistance in maize remains largely unknown. The objective of this study was to identify key genes/pathways that are consistently associated with multiple fungal pathogen infections in maize. Here, we conducted a meta-analysis of gene expression profiles from seven publicly available RNA-seq datasets of different fungal pathogen infections in maize. We identified 267 common differentially expressed genes (co-DEGs) in the four maize leaf infection experiments and 115 co-DEGs in all the seven experiments. Functional enrichment analysis showed that the co-DEGs were mainly involved in the biosynthesis of diterpenoid and phenylpropanoid. Further investigation revealed a set of genes associated with terpenoid phytoalexin and lignin biosynthesis, as well as potential pattern recognition receptors and nutrient transporter genes, which were consistently up-regulated after inoculation with different pathogens. In addition, we constructed a weighted gene co-expression network and identified several hub genes encoding transcription factors and protein kinases. Our results provide valuable insights into the pathways and genes influenced by different fungal pathogens, which might facilitate mining multiple disease resistance genes in maize.