Project description:The draft genome of L. sativa (lettuce) cv. Tizian was sequenced in two Illumina sequencing runs, mate pair and shotgun. This entry contains the RAW sequencing data.
Project description:During mycoparasitism, a fungus—the host—is parasitized by another fungus—the mycoparasite. The genetic underpinnings of these relationships have been best characterized in Ascomycete fungi. However, within Basidiomycete fungi, there are rare instances of mushroom-forming species parasitizing the reproductive structures, or sporocarps, of other mushroom-forming species. One of the most enigmatic of these occurs between Entoloma abortivum and species of Armillaria, where hyphae of E. abortivum are hypothesized to disrupt the development of Armillaria sporocarps, resulting in the formation of carpophoroids. However, it remains unknown whether carpophoroids are the direct result of a mycoparasitic relationship. To address the nature of this unique interaction, we analyzed gene expression of field-collected Armillaria and E. abortivum sporocarps and carpophoroids. Transcripts in the carpophoroids are primarily from E. abortivum, supporting the hypothesis that this species is parasitizing Armillaria. Most notably, we identified differentially expressed E. abortivum β-trefoil-type lectins in the carpophoroid, which we hypothesize bind to Armillaria cell wall galactomannoproteins, thereby mediating recognition between the mycoparasite and the host. The most significantly upregulated E. abortivum transcripts in the carpophoroid code for oxalate decarboxylases—enzymes that degrade oxalic acid. Oxalic acid is a virulence factor in many plant pathogens, including Armillaria species, however, E. abortivum has evolved a sophisticated strategy to overcome this defense mechanism. The number of gene models and genes that code for carbohydrate-active enzymes in the E. abortivum transcriptome were reduced compared to other closely related species, perhaps as a result of the specialized nature of this interaction.
Project description:Genome graphs, including the recently released draft human pangenome graph, can represent the breadth of genetic diversity and thus transcend the limits of traditional linear reference genomes. However, there are no genome-graph-compatible tools for analyzing whole genome bisulfite sequencing (WGBS) data. To close this gap, we introduce methylGrapher, a tool tailored for accurate DNA methylation analysis by mapping WGBS data to a genome graph. Notably, methylGrapher can reconstruct methylation patterns along haplotype paths precisely and efficiently. To demonstrate the utility of methylGrapher, we analyzed the WGBS data derived from five individuals whose genomes were included in the first Human Pangenome draft as well as WGBS data from ENCODE (EN-TEx). Along with standard performance benchmarking, we show that methylGrapher fully recapitulates DNA methylation patterns defined by classic linear genome analysis approaches. Importantly, methylGrapher captures a substantial number of CpG sites that are missed by linear methods, and improves overall genome coverage while reducing alignment reference bias. Thus, methylGrapher is a first step towards unlocking the full potential of Human Pangenome graphs in genomic DNA methylation analysis.