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Abraham, Leen Nanchira
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Abraham, Leen Nanchira
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- PublicationAccès libreGenome-wide association mapping reveals genes underlying population-level metabolome diversity in a fungal crop pathogen(2022)
;Nikhil Kumar Singh ;Sabina Moser Tralamazza; ; Abstract Background Fungi produce a wide range of specialized metabolites (SMs) involved in biotic interactions. Pathways for the production of SMs are often encoded in clusters of tightly arranged genes identified as biosynthetic gene clusters. Such gene clusters can undergo horizontal gene transfers between species and rapid evolutionary change within species. The acquisition, rearrangement, and deletion of gene clusters can generate significant metabolome diversity. However, the genetic basis underlying variation in SM production remains poorly understood. Results Here, we analyzed the metabolite production of a large population of the fungal pathogen of wheat, Zymoseptoria tritici. The pathogen causes major yield losses and shows variation in gene clusters. We performed untargeted ultra-high performance liquid chromatography-high resolution mass spectrometry to profile the metabolite diversity among 102 isolates of the same species. We found substantial variation in the abundance of the detected metabolites among isolates. Integrating whole-genome sequencing data, we performed metabolite genome-wide association mapping to identify loci underlying variation in metabolite production (i.e., metabolite-GWAS). We found that significantly associated SNPs reside mostly in coding and gene regulatory regions. Associated genes encode mainly transport and catalytic activities. The metabolite-GWAS identified also a polymorphism in the 3′UTR region of a virulence gene related to metabolite production and showing expression variation. Conclusions Taken together, our study provides a significant resource to unravel polymorphism underlying metabolome diversity within a species. Integrating metabolome screens should be feasible for a range of different plant pathogens and help prioritize molecular studies. - PublicationAccès libreHistone H3K27 Methylation Perturbs Transcriptional Robustness and Underpins Dispensability of Highly Conserved Genes in Fungi(2021)
;Sabina Moser Tralamazza; ;Claudia Sarai Reyes-Avila ;Benedito Corrêa; Jeffrey TownsendAbstractEpigenetic modifications are key regulators of gene expression and underpin genome integrity. Yet, how epigenetic changes affect the evolution and transcriptional robustness of genes remains largely unknown. Here, we show how the repressive histone mark H3K27me3 underpins the trajectory of highly conserved genes in fungi. We first performed transcriptomic profiling on closely related species of the plant pathogen Fusarium graminearum species complex. We determined transcriptional responsiveness of genes across environmental conditions to determine expression robustness. To infer evolutionary conservation, we used a framework of 23 species across the Fusarium genus including three species covered with histone methylation data. Gene expression variation is negatively correlated with gene conservation confirming that highly conserved genes show higher expression robustness. In contrast, genes marked by H3K27me3 do not show such associations. Furthermore, highly conserved genes marked by H3K27me3 encode smaller proteins, exhibit weaker codon usage bias, higher levels of hydrophobicity, show lower intrinsically disordered regions, and are enriched for functions related to regulation and membrane transport. The evolutionary age of conserved genes with H3K27me3 histone marks falls typically within the origins of the Fusarium genus. We show that highly conserved genes marked by H3K27me3 are more likely to be dispensable for survival during host infection. Lastly, we show that conserved genes exposed to repressive H3K27me3 marks across distantly related Fusarium fungi are associated with transcriptional perturbation at the microevolutionary scale. In conclusion, we show how repressive histone marks are entangled in the evolutionary fate of highly conserved genes across evolutionary timescales.