Project description:Affinity capture of DNA methylation combined with high-throughput sequencing strikes a good balance between the high cost of whole genome bisulfite sequencing and the low coverage of methylation arrays. We present BayMeth, an empirical Bayes approach that uses a fully methylated control sample to transform observed read counts into regional methylation levels. In our model, inefficient capture can readily be distinguished from low methylation levels. BayMeth improves on existing methods, allows explicit modeling of copy number variation, and offers computationally-efficient analytical mean and variance estimators. BayMeth is available in the Repitools Bioconductor package. Benchmarking samples to compare MBD- and MeDIP-seq [GSE38679, GSE24546; PMID 21045081] datasets against 450k measurements
Project description:<p>Malignant hyperthermia (MH) is a genetic disorder that causes a profound metabolic derangement following exposure to certain anesthetics. While approximately half of all cases are associated with ryanodine receptor-1 gene (RYR1) mutations, many cases have an unknown genetic cause. We sought to identify rare variants in novel MH candidate genes by sequencing the protein-coding regions of the genomes of individuals whose disease was either ruled in or out by the gold-standard diagnostic test. We also carefully selected individuals from well-characterized families to use gene-sharing information and maximize efficiency in the study design. Exome sequencing has helped identify the causes of over a dozen Mendelian disorders, has high power at low sample sizes, and is cost-efficient compared to whole-genome sequencing.</p>
Project description:Affinity capture of DNA methylation combined with high-throughput sequencing strikes a good balance between the high cost of whole genome bisulfite sequencing and the low coverage of methylation arrays. We present BayMeth, an empirical Bayes approach that uses a fully methylated control sample to transform observed read counts into regional methylation levels. In our model, inefficient capture can readily be distinguished from low methylation levels. BayMeth improves on existing methods, allows explicit modeling of copy number variation, and offers computationally-efficient analytical mean and variance estimators. BayMeth is available in the Repitools Bioconductor package.
Project description:The recent development of a semiconductor-based, non-optical DNA sequencing technology promises scalable, low-cost and rapid sequence data production. The technology has previously been applied mainly to genomic sequencing and targeted re-sequencing. Here, we demonstrate the utility of Ion Torrent semiconductor-based sequencing for sensitive, efficient and rapid chromatin immunoprecipitation followed by sequencing (ChIP-seq) through the application of sample preparation methods that are optimized for ChIP-seq on the Ion Torrent platform. We leverage this method for epigenetic profiling of tumor tissues. Examination of histone modifications in mouse dendentic cells stimulated with LPS, matched melanoma derived cell line, melanoma tumor tissue
Project description:Many crop species have polyploid genomes that are unlikely to be sequenced to a high standard in the near future, representing a barrier to genomics-based breeding. As an exemplar, we sequenced the leaf transcriptome to analyse both sequence variation1 and transcript abundance across a mapping population of oilseed rape (Brassica napus), together with representatives of ancestors of the parents of the population. Twin SNP linkage maps were constructed, comprising 23,037 markers in all. These were used to analyse the genome for alignment to that of a related species, Arabidopsis thaliana, and to genome sequence assemblies of the progenitor species of B. napus. Methods were developed that enabled us to detect genome rearrangements and track inheritance of genomic segments, including the outcome of an inter-specific cross. This transformative advance, enabling economical high-resolution dissection of the genomes of most, if not all, crop species, will enable us to understand the genetic consequences of breeding and domestication, and will underpin the development of efficient predictive breeding strategies.
