Ontology highlight
ABSTRACT:
PROVIDER: PRJNA956080 | ENA |
REPOSITORIES: ENA
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Project description:The utility of RADseq in an experimental setting is also demonstrated, based on our chasacterisation of an APOBEC mutation signature in an APOBEC3A transfected mouse cell line. 0D5 cells, derived from SSM3 cells, were co-transfected with a mixture containing pcDNA3.1 vectors expressing either APOBEC3A or APOBEC3B (kindly donated by Vincent Caval), pcDNA3.1 construct expressing deaminase null APOBEC3A linked to a uracil deglycosylase construct and a plasmid encoding mutant GFP and WT mCherry that is a reporter for APOBEC mutagenesis. Cells were grown, and gDNA extracted, prior to preparation of RADseq libraries using a PstI- MspI double-digest. Libraries underwent a Pippin Prep to select fragments in the size range of 220-520 bp (genomic sequence plus 148 bp of adapters). Single-end sequencing (1x101bp) was performed on an Illumina NovaSeq6000 utilizing v1.5 chemistry. Reads were aligned to mm10 using bwa mem and variants called using the GATK4 pipeline.
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Project description:ChIP-Seq, which combines chromatin immunoprecipitation (ChIP) with high-throughput massively parallel sequencing, is increasingly being used for identification of protein–DNA interactions in-vivo in the genome. In general, current algorithms for ChIP-seq reads employ artificial estimation of the average length of DNA fragments for peak finding, leading to uncertain prediction of DNA-protein binding sites. Here, we present SIPeS (Site Identification from Paired-end Sequencing), a novel algorithm for precise identification of binding sites from short reads generated from paired-end Solexa ChIP-Seq technology. SIPeS uses a dynamic baseline directly via ‘piling up’ the corresponding fragments defined by the paired reads to efficiently find peaks corresponding to binding sites. The performance of SIPeS is demonstrated by analyzing the ChIP-Seq data of the Arabidopsis basic helix-loop-helix transcription factor ABORTED MICROSPORES (AMS). The robustness of SIPeS was demonstrated in higher sensitivity and spatial resolution in peak finding compared to three existing peak detection algorithms. Keywords: transcription factors (protein-DNA interactions)
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