Peaksat: An R package for ChIP-seq peak saturation analysis
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE197960 | GEO | 2022/03/07
REPOSITORIES: GEO
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Project description:BackgroundEpigenomic profiling assays such as ChIP-seq have been widely used to map the genome-wide enrichment profiles of chromatin-associated proteins and posttranslational histone modifications. Sequencing depth is a key parameter in experimental design and quality control. However, due to variable sequencing depth requirements across experimental conditions, it can be challenging to determine optimal sequencing depth, particularly for projects involving multiple targets or cell types.ResultsWe developed the peaksat R package to provide target read depth estimates for epigenomic experiments based on the analysis of peak saturation curves. We applied peaksat to establish the distinctive read depth requirements for ChIP-seq studies of histone modifications in different cell lines. Using peaksat, we were able to estimate the target read depth required per library to obtain high-quality peak calls for downstream analysis. In addition, peaksat was applied to other sequence-enrichment methods including CUT&RUN and ATAC-seq.Conclusionpeaksat addresses a need for researchers to make informed decisions about whether their sequencing data has been generated to an adequate depth and subsequently sufficient meaningful peaks, and failing that, how many more reads would be required per library. peaksat is applicable to other sequence-based methods that include calling peaks in their analysis.
| S-EPMC9878872 | biostudies-literature
Project description:The expression levels of tRNA-derived small RNA, known as tsRNA, were interrogated in the following parental cell lines: MCF10A normal-like mammary epithelial cell, MCF7, MCF10AT1, MCF10CA1a, and MDA-MB-231 breast cancer cells. In addition, tsRNA expression was determined after shRNA-inhibition of RUNX1 in MCF10A cells or RUNX1 induction in MCF10CA1a cells.
2020-01-01 | GSE142382 | GEO
Project description:Peaksat: An R package for ChIP-seq peak saturation analysis
| PRJNA812937 | ENA
Project description:We attempted to identify alterations in gene expression that occur during the progression from normal breast to ductal carcinoma in situ (DCIS) with the aim to elucidate significant genes and pathways underlying the premalignant transformation. To determine the expression changes that are common to multiple DCIS models (MCF10.DCIS, SUM102 and SUM225) and normal mammary epithelial cells (MCF10A), we grew the cells in three dimensional overlay culture with reconstituted basement membrane and used the extracted RNA for 76 cycles of deep sequencing (mRNA-Seq) using Illumina Genome Analyzer GAIIx. Analysis of mRNA-Seq results showed 295 consistently differentially expressed transcripts in DCIS models as compared to MCF10A. These differentially expressed genes are associated with a number of signaling pathways such as integrin, fibroblast growth factor and TGFM-CM-^_ signaling. Many differentially expressed transcripts in DCIS were found to be involved in cell-cell signaling, cell-cell adhesion and cell proliferation. We further investigated ALDH5A1 gene that encodes for the enzyme, aldehyde dehydrogenase 5A1, which is involved in glutamate metabolism. Further, inhibition of ALDH5A1 with different pharmacological drugs resulted in significant inhibition of cell growth and proliferation in the DCIS models. Four cell lines examined: normal mammary epithelial cell line (one sample) and three ductal carcinoma in situ cell lines (three samples). Each sample has two duplicates
2012-03-28 | E-GEOD-36863 | biostudies-arrayexpress
Project description:High-resolution methods such as 4C and Capture-C enable the study of chromatin loops such as those formed between promoters and enhancers or CTCF/cohesin binding sites. An important aspect of 4C/CapC analyses is the identification of robust peaks in the data for the identification of chromatin loops. Here we present an R package for the analysis of 4C/CapC data. We generated 4C data for 10 viewpoints in 2 tissues in triplicate to test our methods. We developed a non-parametric peak caller based on rank-products. Sampling analysis shows that not read depth but template quality is the most important determinant of success in 4C experiments. By performing peak calling on single experiments we show that the peak calling results are similar to the replicate experiments, but that false positive rates are significantly reduced by performing replicates.
2018-05-14 | GSE105177 | GEO
Project description:The Runx1 transcription factor is essential for hematopoietic differentiation and mutations underlie various leukemias. Here we demonstrate a role for Runx1 in the MCF10 cell series model of breast cancer progression. The highest level of Runx1 that occurs in normal like mammary epithelial cells (MCF10A) is decreased in tumorigenic (MCF10AT1) and metastatic (MCF10CA1a) breast cancer cells. We show that depletion of Runx1 in MCF10A cells results in striking changes in cell morphology and induction of epithelial-mesenchymal transition (EMT) via several signaling pathways. Analyses of breast tumors and patient survival data reveal that loss of Runx1 is associated with poor prognosis and decreased survival. Re-expressing Runx1 in MCF10AT1 breast cancer cells restores the epithelial phenotype. These results identify a novel function for Runx1 in sustaining normal epithelial morphology and preventing EMT. These mechanisms suggest Runx1 levels in early stage tumors can be used as a prognostic indicator of tumor progression.
2017-04-17 | GSE85857 | GEO
Project description:We attempted to identify alterations in gene expression that occur during the progression from normal breast to ductal carcinoma in situ (DCIS) with the aim to elucidate significant genes and pathways underlying the premalignant transformation. To determine the expression changes that are common to multiple DCIS models (MCF10.DCIS, SUM102 and SUM225) and normal mammary epithelial cells (MCF10A), we grew the cells in three dimensional overlay culture with reconstituted basement membrane and used the extracted RNA for 76 cycles of deep sequencing (mRNA-Seq) using Illumina Genome Analyzer GAIIx. Analysis of mRNA-Seq results showed 295 consistently differentially expressed transcripts in DCIS models as compared to MCF10A. These differentially expressed genes are associated with a number of signaling pathways such as integrin, fibroblast growth factor and TGFß signaling. Many differentially expressed transcripts in DCIS were found to be involved in cell-cell signaling, cell-cell adhesion and cell proliferation. We further investigated ALDH5A1 gene that encodes for the enzyme, aldehyde dehydrogenase 5A1, which is involved in glutamate metabolism. Further, inhibition of ALDH5A1 with different pharmacological drugs resulted in significant inhibition of cell growth and proliferation in the DCIS models.
2012-03-29 | GSE36863 | GEO
Project description:Genome wide DNA methylation profiling of human mammary epithelial MCF10A cell line treated with vehicle control (ethanol) and with RSV (resveratrol). The Illumina Infinium 450K Human DNA methylation Beadchip v1.2 was used to obtain DNA methylation profiles across approximately 450,000 CpGs in human cell lines exposed to described treatments. Samples included biological triplicate of MCF10A control (ethanol treated), biological triplicate of MCF10A treated with RSV.
2022-01-31 | GSE113299 | GEO
Project description:MCF10A series is one of the few human models of breast tumor progression. A derivative of MCF10A cells is the MCFDCIS, which reproducibly forms comedo DCIS-like lesions that spontaneously progress to invasive tumors. We used this model to explore the relative importance of myoepithelial cells and stromal fibroblasts in the in situ to invasive breast carcinoma transition. We use Affymetrix 11K XbaI or 250K StyI SNP arrays to analyze the MCF10A series cells and MCFDCIS derived xenografts for copy number changes and LOH (loss of heterozygosity). Keywords: Cell line, xenografts of time course/co-injection groups, different cell types isolated from xenografts
2008-03-07 | GSE10747 | GEO
Project description:To better understand the tumour-modelling efficacy of cell lines, we performed RNA-seq analyses on 2D and 3D cultures of tumourigenic MCF7 and non-tumourigenic MCF10A and augmented our data with published datasets. To our knowledge, this was the first RNA-seq dataset comprising 2D and 3D cultures of MCF7 and MCF10A within the same experiment. We then compared tumourigenesis within cell lines (MCF7-vs-MCF10A) and tumourigenesis within clinical tissues (Luminal A-vs-Normal) from the TCGA-BRCA dataset and considered whether the same cancer-related processes could be observed.
2022-11-08 | GSE208731 | GEO