Project description:A quantitative genetic analysis of the yeast replicative life span was carried out by sampling the natural genetic variation Genomic DNA was extracted from 39 recombinant lines from a cross between strains S96 and YJM 789.
Project description:Recently, it has been proposed that local DNA methylation profiles might be dictated by cis-regulatory DNA sequences that mainly operate via DNA-binding factors. Combining blood genome-wide DNA methylation profiles (Illumina Infinium MethylationEPIC BeadChiP), whole genome sequencing-derived single nucleotide variants (SNVs) along with predicted transcription factor binding site (TFBS), we were able to observe that rare regulatory variants, i.e, SNVs that disrupt TFBSs, are associated with DNA methylation at both local and, to a lesser extent, broader locations. Interestingly, we also observed that this directed DNA methylation can have consequences on genome regulation by altering expression levels of nearby genes.
Project description:Technology for crosslinking and immunoprecipitation followed by sequencing (CLIP-seq) has identified the transcriptomic targets of hundreds of RNA-binding proteins in cells. To improve the power of existing and future CLIP-seq datasets, we introduce Skipper, an end-to-end workflow that converts unprocessed reads into annotated binding sites using an improved statistical framework. Compared to existing methods, Skipper on average calls 3.1-4.2 times more transcriptomic binding sites and sometimes >10 times more sites, providing deeper insight into post-transcriptional gene regulation. Skipper also calls binding to annotated repetitive elements and identifies bound elements for 99% of enhanced CLIP experiments. We perform nine translation factor enhanced CLIPs and apply Skipper to learn determinants of translation factor occupancy including transcript region, sequence, and subcellular localization. Furthermore, we observe depletion of genetic variation in occupied sites and nominate transcripts subject to selective constraint because of translation factor occupancy. Skipper offers fast, easy, customizable analysis of CLIP-seq data.