ChIP-Seq Analysis

Understanding the gene regulatory mechanisms by RUNX1

Understanding the gene regulatory mechanisms orchestrated by transcription factors is paramount for deciphering complex biological processes, including cancer development and progression. In this analysis, we delve into the role of RUNX1, a pivotal transcription factor implicated in various cellular functions, particularly in breast cancer biology. This study builds upon the comprehensive research conducted by Barutcu et al. (2016), where they employed a multi-omics approach, including RNA-seq, ChIP-seq, and Hi-C analyses, to elucidate the regulatory landscape governed by RUNX1 in breast cancer. While their study provided invaluable insights into the molecular mechanisms underlying breast cancer pathogenesis, we narrow our focus to the ChIP-seq aspect, aiming to unravel the genome-wide binding sites of RUNX1 within the MCF7 genome.

Methods

Raw sequencing data were organized using a sample sheet sample_sheet.csv and retrieved via the wget_files rule. Subsequent quality control involved FastQC (v.0.12.1) for assessing read quality, followed by adapter trimming using Trimmomatic (v0.39). Alignment to the GRCh38 reference genome was achieved with Bowtie2 (v2.5.3), while SAMtools (v1.20) facilitated sorting and indexing of resultant BAM files. Quality metrics were obtained using SAMtools flagstat, and a comprehensive report was generated via MultiQC (v1.21). Read coverage across the genome was computed using deepTools' bamCoverage (v3.5.4), with Pearson correlation coefficients visualized using plotCorrelation. Peak calling was executed using HOMER (v4.11), with BEDTools (v2.31.0) employed for peak intersection analysis. Peaks were subsequently annotated using HOMER's annotatePeaks.pl script with a GTF file, and motif enrichment analysis was performed using HOMER's findMotifsGenome.pl. Visualization of read coverage around peak regions was accomplished with plotProfile. All these methods were orchestrated within a Snakemake workflow, facilitating automation and reproducibility of the analysis pipeline.

References

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