1. Comprehensive Analysis of Breast Cancer Cell Lines: Genome-wide Insights from ChIP-seq Analysis
- Author
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Tanishq Sahu and Ruchi Yadav
- Subjects
binding sites ,breast cancer ,chip-seq ,galaxy ,genomics ,motif ,Biotechnology ,TP248.13-248.65 - Abstract
Context: Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is the central system in epigenomic exploration. Chromatin immunoprecipitation coupled with sequencing (ChIP-seq) is an important technology to identify the genome-wide location of DNA-binding proteins such as histones proteins, transcription factors, RNA polymerase, or any protein of interest. ChIP-seq has been used to study the binding sites and efficacy of drugs in cancer cell lines etc. Aims: In current research, breast cancer cell line data have been used to study the effect PADI2 (peptidyl arginine deiminase) gene in the progression of breast cancer. Further, this ChIP-seq data have also been used to study the binding site of Amanitin drug in breast cancer. Settings and Design: Breast cancer ChIP-seq data have been retrieved from the European Nucleotide Archive database with project Id PRJNA415426 short read archive. Four samples of FASTQ files were used and analyzed for the genome-wide analysis. Materials and Methods: Galaxy server (https://usegalaxy.org/) was used for complete ChIP-seq data analysis; different tools such as fast-quality control (QC), multi-QC, Bowtie2, model-based analysis of ChIP-sequencing, and ChIPseeker tools were used for motif enrichment and functional analysis. Motif analysis was done through the Multiple Expectation maximizations for Motif Elicitation database (https://meme-suite.org/meme/db/motifs). Results: Computational investigation demonstrates the binding sequences of the T47-D breast cancer cell line as TTTTGTATTTTTAGT, and this motif occurs 2123 times in the Homo Sapiens reference genome that is hg19. Conclusions: This research classifies the binding site and affinity of the T47-D human breast cancer cell line. Further, wet laboratory studies are required to verify the function of the predicted motifs and their importance in drug development or research in breast cancer.
- Published
- 2024
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