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BackgroundLong non-coding RNAs (lncRNAs) may regulate gene expression in numerous biological processes including cellular response to xenobiotics. The exposure of living organisms to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), a persistent environmental contaminant, results in reproductive defects in many species including pigs. The aims of the study were to identify and characterize lncRNAs in porcine granulosa cells as well as to examine the effects of TCDD on the lncRNA expression profile in the cells.ResultsOne thousand six hundred sixty-six lncRNAs were identified and characterized in porcine granulosa cells. The identified lncRNAs were found to be shorter than mRNAs. In addition, the number of exons was lower in lncRNAs than in mRNAs and their exons were longer. TCDD affected the expression of 22 lncRNAs (differentially expressed lncRNAs [DELs]; log2 fold change  ≥ 1, P-adjusted < 0.05) in the examined cells. Potential functions of DELs were indirectly predicted via searching their target cis- and trans-regulated protein-coding genes. The co-expression analysis revealed that DELs may influence the expression of numerous genes, including those involved in cellular response to xenobiotics, dioxin metabolism, endoplasmic reticulum stress and cell proliferation. Aryl hydrocarbon receptor (AhR) and cytochrome P450 1A1 (CYP1A1) were found among the trans-regulated genes.ConclusionsThese findings indicate that the identified lncRNAs may constitute a part of the regulatory mechanism of TCDD action in granulosa cells. To our knowledge, this is the first study describing lncRNAs in porcine granulosa cells as well as TCDD effects on the lncRNA expression profile. These results may trigger new research directions leading to better understanding of molecular processes induced by xenobiotics in the ovary.Electronic supplementary materialThe online version of this article (10.1186/s40104-018-0288-3) contains supplementary material, which is available to authorized users.

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Much of the mitogenome variation observed in fungal lineages seems driven by mobile genetic elements (MGEs), which have invaded their genomes throughout evolution. The variation in the distribution and nucleotide diversity of these elements appears to be the main distinction between different fungal taxa, making them promising candidates for diagnostic purposes. Fungi of the genus Fusarium display a high variation in MGE content, from MGE-poor (Fusarium oxysporum and Fusarium fujikuroi species complex) to MGE-rich mitogenomes found in the important cereal pathogens F. culmorum and F. graminearum sensu stricto. In this study, we investigated the MGE variation in these latter two species by mitogenome analysis of geographically diverse strains. In addition, a smaller set of F. cerealis and F. pseudograminearum strains was included for comparison. Forty-seven introns harboring from 0 to 3 endonucleases (HEGs) were identified in the standard set of mitochondrial protein-coding genes. Most of them belonged to the group I intron family and harbored either LAGLIDADG or GIY-YIG HEGs. Among a total of 53 HEGs, 27 were shared by all fungal strains. Most of the optional HEGs were irregularly distributed among fungal strains/species indicating ancestral mosaicism in MGEs. However, among optional MGEs, one exhibited species-specific

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Recent improvements in microbiology and molecular epidemiology were largely stimulated by whole- genome sequencing (WGS), which provides an unprecedented resolution in discriminating highly related genetic backgrounds. WGS is becoming the method of choice in epidemiology of fungal diseases, but its application is still in a pioneer stage, mainly due to the limited number of available genomes. Fungal pathogens often belong to complexes composed of numerous cryptic species. Detecting cryptic diversity is fundamental to understand the dynamics and the evolutionary relationships underlying disease outbreaks. In this study, we explore the value of whole-genome SNP analyses in identification of the pandemic pathogen Fusarium graminearum sensu stricto (F.g.). This species is responsible for cereal diseases and negatively impacts grain production worldwide. The fungus belongs to the monophyletic fungal complex referred to as F. graminearum species complex including at least sixteen cryptic species, a few among them may be involved in cereal diseases in certain agricultural areas. We analyzed WGS data from a collection of 99 F.g. strains and 33 strains representing all known cryptic species belonging to the FGSC complex. As a first step, we performed a phylogenomic analysis to reveal species-specific clustering. A RAxML maximum likelihood tree grouped all analyzed strains of F.g. into a single clade, supporting the clustering-based identification approach. Although, phylogenetic reconstructions are essential in detecting cryptic species, a phylogenomic tree does not fulfill the criteria for rapid and cost-effective approach for identification of fungi, due to the time-consuming nature of the analysis. As an alternative, analysis of WGS information by mapping sequence data from individual strains against reference genomes may provide useful markers for the rapid identification of fungi. We provide a robust framework for typing F.g. through the web-based PhaME workflow available at EDGE bioinformatics. The method was validated through multiple comparisons of assembly genomes to F.g. reference strain PH-1. We showed that the difference between intra- and interspecies variability was at least two times higher than intraspecific variation facilitating successful typing of F.g. This is the first study which employs WGS data for typing plant pathogenic fusaria.