Project description:The LRGASP challenge encompasses different human, mouse, and manatee samples sequenced using multiple combinations of protocols and platforms. Different challenges will use distinct subsets of the samples for evaluation. The long-read sequencing platforms used in these challenges are the Pacific Biosciences (PacBio) Sequel II, Oxford Nanopore (ONT) MinION and PromethION. Samples will also be sequenced on the Illumina HiSeq 2500. The primary LRGASP library prep protocols are “standard” cDNA sequencing, direct RNA sequencing, R2C2, and CapTrap. Each sample will also include Lexogen SIRV-Set 4 spike-ins. We will also provide simulated PacBio and ONT data as part of the evaluations. This particular study focuses on single strand CAGE sequencing of human iPSCs, defining CAGE peaks from Illumina HiSeq 2500 (SR: 150 cycles) of two biological replicates for use in the LRGASP challenge.
Project description:We comprehensively benchmarked CUT&Tag for H3K27ac and H3K27me3 against published ChIP-seq profiles from ENCODE in K562 cells. Across a total of 30 new and 6 published CUT&Tag datasets we found that no experiment recovers more than 50% of known ENCODE peaks, regardless of the histone mark. We tested peak callers MACS2 and SEACR, identifying optimal peak calling parameters. Balancing both precision and recall of known ENCODE peaks, SEACR without retention of duplicates showed the best performance. We found that reducing PCR cycles during library preparation lowered duplication rates at the expense of ENCODE peak recovery. Despite the moderate ENCODE peak recovery, peaks identified by CUT&Tag represent the strongest ENCODE peaks and show the same functional and biological enrichments as ChIP-seq peaks identified by ENCODE. Our workflow systematically evaluates the merits of methodological adjustments and will facilitate future efforts to apply CUT&Tag in human tissues and single cells.
Project description:We present a tool for processing NGS DNA-seq BAM files to quantify peaks and create coverage tracks from ChIP-seq, NS-seq, ATAC-seq, OK-seq, END-seq and replication timing data
Project description:Motivation: Detection of changes in DNA-protein interactions from ChIP-seq data is a crucial step in unraveling the regulatory networks behind biological processes. The simplest variation of this problem is the differential peak calling problem. Here one has to find genomic regions with ChIP-seq signal changes between two cellular conditions in the interaction of a protein with DNA. The great majority of peak calling methods can only analyse one ChIP-seq signal at a time and are unable to perform differential peak calling. Recently, a few approaches based on the combination of these peak callers with statistical tests for detecting differential digital expression have been proposed. However, these methods fail to detect detailed changes of protein-DNA interactions. Results: We propose ODIN; an HMM-based approach to detect and analyse differential peaks in pairs of ChIP-seq data. ODIN performs genomic signal processing, peak calling and p-value calculation in an integrated framework. We also propose an evaluation methodology to compare ODIN with competing methods. The evaluation method is based on the association of differential peaks with expression changes in the same cellular conditions. Our empirical study based on several ChIP-seq experiments from transcription factors, histone modifications and simulated data shows that ODIN outperforms considered competing methods in most scenarios. H3K4me1 and PU.1 occupancy in MPP, CDP, cDC and pDC
Project description:We applied ChIP-seq to map the chromosomal binding sites for two nucleosome remodeling complexes containing the ATPase ISWI, ACF and RSF, in Drosophila embryos. Employing a panel of polyclonal and monoclonal antibodies directed against their signature subunits, ACF1 and RSF1, robust profiles were obtained indicating that both remodelers co-occupied a large set of active promoters. For further validation we repeated the mapping using chromatin of mutant embryos that do not express ACF1 or RSF1. Surprisingly, the ChIP-seq profiles were unchanged, suggesting that they were not due to specific immunoprecipitation. Conservative analysis lists about 3000 chromosomal loci, mostly active promoters that are prone to non-specific enrichment in ChIP and give rise to ‘Phantom Peaks’. These peaks are not obtained with pre-immune serum and are not prominent in input chromatin. Examination of various ACF1 and RSF1 antibodies in Drosophila melanogaster embryos which are wildtype or mutant for the antibody targets.
Project description:We utilized DNase-Seq to identify open chromatin regions within Schwann cells. This data was used in conjunction with sequence conservation and transcription factor binding site prediction to identify putative cis-regulatory elements critical for Schwann cells. We used three independent biological replicates, and for our studies used sample 'barcode4' as a representative sample for all three. DNase HSS peaks were identified using F-Seq and HOMER, and overlapped to prioritize candidate regions. These regions were then verified using luciferase assays.
Project description:Meiotic DNA double stranded breaks (DSBs) initiate genetic recombination in discrete areas of the genome called recombination hotspots. Although DSBs can be directly mapped using ChIP-Seq and antibody against ssDNA-associated proteins, genome-wide mapping of recombination hotspots in mammals is still a challenge due to the low frequency of recombination, high heterogeneity of the germ cell population and the relatively low efficiency of ChIP. To overcome these limitations we have developed a novel method, single-stranded DNA (ssDNA) sequencing (SSDS), that specifically detects protein-bound single-stranded DNA at DSB ends. SSDS consists of a computational framework for the specific detection of ssDNA-derived reads in a sequencing library and a new library preparation procedure for the enrichment of fragments originating from ssDNA. When applied to mapping meiotic DSBs, the use of SSDS reduces the non-specific dsDNA background more than ten-fold. Our method can be extended to other systems where the identification of ssDNA or DSBs is desired. Development and validation of the method, SSDS, for the specific detection of ssDNA-derived and dsDNA-derived fragments in sequencing libraries and enrichment of ssDNA-derived fragments. SSDS was used to detect meiotic DSBs in 9R/13R mice.