RESUMEN
Chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) is an invaluable tool for mapping chromatin-associated proteins. Current barcoding strategies aim to improve assay throughput and scalability but intense sample handling and lack of standardization over cell types, cell numbers and epitopes hinder wide-spread use in the field. Here, we present a barcoding method to enable high-throughput ChIP-seq using common molecular biology techniques. The method, called RELACS (restriction enzyme-based labeling of chromatin in situ) relies on standardized nuclei extraction from any source and employs chromatin cutting and barcoding within intact nuclei. Barcoded nuclei are pooled and processed within the same ChIP reaction, for maximal comparability and workload reduction. The innovative barcoding concept is particularly user-friendly and suitable for implementation to standardized large-scale clinical studies and scarce samples. Aiming to maximize universality and scalability, RELACS can generate ChIP-seq libraries for transcription factors and histone modifications from hundreds of samples within three days.
RESUMEN
BACKGROUND: DNA methylation changes are associated with a wide array of biological processes. Bisulfite conversion of DNA followed by high-throughput sequencing is increasingly being used to assess genome-wide methylation at single-base resolution. The relative slowness of most commonly used aligners for processing such data introduces an unnecessarily long delay between receipt of raw data and statistical analysis. While this process can be sped-up by using computer clusters, current tools are not designed with them in mind and end-users must create such implementations themselves. RESULTS: Here, we present a novel BS-seq aligner, Bison, which exploits multiple nodes of a computer cluster to speed up this process and also has increased accuracy. Bison is accompanied by a variety of helper programs and scripts to ease, as much as possible, the process of quality control and preparing results for statistical analysis by a variety of popular R packages. Bison is also accompanied by bison_herd, a variant of Bison with the same output but that can scale to a semi-arbitrary number of nodes, with concomitant increased demands on the underlying message passing interface implementation. CONCLUSIONS: Bison is a new bisulfite-converted short-read aligner providing end users easier scalability for performance gains, more accurate alignments, and a convenient pathway for quality controlling alignments and converting methylation calls into a form appropriate for statistical analysis. Bison and the more scalable bison_herd are natively able to utilize multiple nodes of a computer cluster simultaneously and serve to simplify to the process of creating analysis pipelines.