Project description:Determination of the complete genome of European mountain ash ringspot-associated emaravirus from Sorbus intermedia reveals two additional genome segments
Project description:ASH-1 orthologs are H3K36-specific methyltransferases that are conserved from fungi to humans but are poorly understood, in part because they are typically essential for viability. Here we examine the H3K36 methylation pathway of Neurospora crassa, which we find has just two H3K36 methyltransferases, ASH-1 and RNA polymerase II-associated SET-2. Our investigation of the interplay between SET-2 and ASH-1 uncovered a regulatory mechanism connecting ASH-1-catalyzed H3K36 methylation to repression of poorly transcribed genes. Our findings provide new insight into ASH-1 function, H3K27me2/3 establishment, and repression at facultative heterochromatin.
Project description:We used RNA-seq in a derived European Drosophila melanogaster population from Germany (MU) to examine coding gene expression variation in the larval fat body during the late wandering third instar stage.
Project description:Topical treatment with N-nitrosotris-(2-chloroethyl)urea (NTCU) induces lung squamous cell carcinoma in mouse. The aim of this study is to analyze the expression profile of the mouse NTCU-induced SCC compared to normal lung to identify gene expression changes in the SCC cells. NIH Swiss mice presenting lung SCC and control healthy mice were used for laser capture microdissection (LCM). LCM was performed in a LMD7000 microscope (Leica Microsystems GmbH, Wetzlar, Germany). RNA was extracted using the RNeasy FFPE kit (Qiagen, Hilden, Germany) and libraries were prepared from using the SMARTer Stranded Total RNA-Seq Kit – Pico Input Mammalian (Clontech Laboratories, Inc., Mountain View, CA, USA). Sequencing was performed using an Illumina HiSeq 2500 generating 50 base pair paired end reads. Reads of low quality were filtered, and adapters trimmed using Cutadapt v1.9.1. Alignment to the reference genome (UCSC mm10) was performed using TopHat v2.0.1, and RNA counts were generated for each gene using the Python package HTSeq v0.6.1, employing the “intersection-strict” overlap mode. DESeq2 was used to normalize and transform the data, examine the relationship between samples (by plotting the first two principal components) and to test for differential expression
