Comparative genomics and stable isotope analysis reveal the saprotrophic-pathogenic lifestyle of a neotropical fungus.

Unlabelled: In terrestrial forested ecosystems, fungi may interact with trees in at least three distinct ways: (i) associated with roots as symbionts; (ii) as pathogens in roots, trunks, leaves, flowers, and fruits; or (iii) decomposing dead tree tissues on soil or even on dead tissues in living trees. Distinguishing the latter two nutrition modes is rather difficult in Hymenochaetaceae (Basidiomycota) species. Herein, we have used an integrative approach of comparative genomics, stable isotopes, host tree association, and bioclimatic data to investigate the lifestyle ecology of the scarcely known neotropical genus , focusing on the unique species .

Multivariate adaptive shrinkage improves cross-population transcriptome prediction and association studies in underrepresented populations.

Transcriptome prediction models built with data from European-descent individuals are less accurate when applied to different populations because of differences in linkage disequilibrium patterns and allele frequencies. We hypothesized that methods that leverage shared regulatory effects across different conditions, in this case, across different populations, may improve cross-population transcriptome prediction. To test this hypothesis, we made transcriptome prediction models for use in transcriptome-wide association studies (TWASs) using different methods (elastic net, joint-tissue imputation [JTI], matrix expression quantitative trait loci [Matrix eQTL], multivariate adaptive shrinkage in R [MASHR], and transcriptome-integrated genetic association resource [TIGAR]) and tested their out-of-sample transcriptome prediction accuracy in population-matched and cross-population scenarios.

Multivariate adaptive shrinkage improves cross-population transcriptome prediction for transcriptome-wide association studies in underrepresented populations.

Transcriptome prediction models built with data from European-descent individuals are less accurate when applied to different populations because of differences in linkage disequilibrium patterns and allele frequencies. We hypothesized methods that leverage shared regulatory effects across different conditions, in this case, across different populations may improve cross-population transcriptome prediction. To test this hypothesis, we made transcriptome prediction models for use in transcriptome-wide association studies (TWAS) using different methods (Elastic Net, Joint-Tissue Imputation (JTI), Matrix eQTL, Multivariate Adaptive Shrinkage in R (MASHR), and Transcriptome-Integrated Genetic Association Resource (TIGAR)) and tested their out-of-sample transcriptome prediction accuracy in population-matched and cross-population scenarios.

Unraveling the Secrets of a Double-Life Fungus by Genomics: CCMB661 Displays Molecular Machinery for Both Parasitic and Endophytic Lifestyles.

(Ascomycota, Hypocreales, Ophiocordycipitaceae) is a classic entomopathogenic fungus that parasitizes ants (Hymenoptera, Ponerinae, Ponerini). Nonetheless, according to our results, this fungal species also exhibits a complete set of genes coding for plant cell wall degrading Carbohydrate-Active enZymes (CAZymes), enabling a full endophytic stage and, consequently, its dual ability to both parasitize insects and live inside plant tissue. The main objective of our study was the sequencing and full characterization of the genome of the fungal strain of (CCMB661) and its predicted secretome.

Phylogenomics and gene selection in Aspergillus welwitschiae: Possible implications in the pathogenicity in Agave sisalana.

Aspergillus welwitschiae causes bole rot disease in sisal (Agave sisalana and related species) which affects the production of natural fibers in Brazil, the main worldwide producer of sisal fibers. This fungus is a saprotroph with a broad host range. Previous research established A.

Genetic and environmental variation impact transferability of polygenic risk scores.

Even when polygenic risk scores (PRSs) are trained in African ancestral populations, Kamiza and colleagues showed that genetic and environmental variation within sub-Saharan African populations impacts prediction performance, highlighting the challenges of clinical implementation of PRSs for risk assessment.

Global Characterization of Fungal Mitogenomes: New Insights on Genomic Diversity and Dynamism of Coding Genes and Accessory Elements.

Fungi comprise a great diversity of species with distinct ecological functions and lifestyles. Similar to other eukaryotes, fungi rely on interactions with prokaryotes and one of the most important symbiotic events was the acquisition of mitochondria. Mitochondria are organelles found in eukaryotic cells whose main function is to generate energy through aerobic respiration.

Comparative mitogenomics of Agaricomycetes: Diversity, abundance, impact and coding potential of putative open-reading frames.

The mitochondrion is an organelle found in eukaryote organisms, and it is vital for different cellular pathways. The mitochondrion has its own DNA molecule and, because its genetic content is relatively conserved, despite the variation of size and structure, mitogenome sequences have been widely used as a promising molecular biomarker for taxonomy and evolution in fungi. In this study, the mitogenomes of two fungal species of Agaricomycetes class, Phellinotus piptadeniae and Trametes villosa, were assembled and annotated for the first time.

Clustering cancer gene expression data: a comparative study.

Background: The use of clustering methods for the discovery of cancer subtypes has drawn a great deal of attention in the scientific community. While bioinformaticians have proposed new clustering methods that take advantage of characteristics of the gene expression data, the medical community has a preference for using "classic" clustering methods. There have been no studies thus far performing a large-scale evaluation of different clustering methods in this context.