Epigenome-wide Screening
Epigenome-wide Screening - Related Videos
12:25
Epigenome-Wide CRISPR-Cas9-Based Knockout Screens on Chemoresistant Cells
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2026
Here, we present a protocol for generating chemoresistant cells using a dose-escalation approach, followed by a CRISPR/Cas9-based screen using a focused sgRNA library targeting epigenetic modifiers to identify regulators of acquired chemoresistance. The protocol also provides multiple optimization points tailored to chemoresistant cell models, offering a robust framework for researchers investigating resistance mechanisms.
08:40
Genome-wide Screen for miRNA Targets Using the MISSION Target ID Library
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Cited by 1 •
2012
The Target ID Library is a plasmid-based, genome-wide collection of cloned cDNA used to identify miRNA targets. Here we demonstrate its use and application.
10:58
Quantitative and Automated High-throughput Genome-wide RNAi Screens in C. elegans
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Cited by 25 •
2012
We describe a protocol using C. elegans and RNAi feeding libraries that allows automated measurement of multiple parameters such as fluorescence, size and opacity of individual worms in a population. We give one example of a screen to identify genes involved in anti-fungal innate immunity in C. elegans.
08:32
Genome-Wide CRISPR Screen for Unveiling Radiosensitive and Radioresistant Genes
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2025
A meticulous and structured approach is given to select resistant and sensitive genes of radiation through the application of a genome-wide CRISPR/Cas9 screen method. This protocol also has the potential to serve as a versatile framework for other research endeavors investigating the mechanisms of resistance to clinically administered chemical drugs.
12:39
A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
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Cited by 6 •
2012
Our Bayesian Change Point (BCP) algorithm builds on state-of-the-art advances in modeling change-points via Hidden Markov Models and applies them to chromatin immunoprecipitation sequencing (ChIPseq) data analysis. BCP performs well in both broad and punctate data types, but excels in accurately identifying robust, reproducible islands of diffuse histone enrichment.
FAQs
DNA methylation, histone modifications, and chromatin accessibility provide different views of regulatory state. Together, they indicate whether genomic regions have altered regulatory characteristics rather than merely showing changes in DNA sequence. This matters because cancer-associated epigenetic patterns can connect specific regions with disrupted control of gene activity and broader regulatory pathways.
Comparing tumor with normal tissue helps distinguish alterations associated with cancer from epigenetic states present in nonmalignant tissue. High-throughput measurements are then evaluated for regions showing significant differences between the groups. Those regions become candidates for studying cancer-related regulatory disruption and developing markers that separate tumor-associated patterns from normal tissue patterns.
Each assay captures a different epigenetic feature: DNA methylation, histone modification, or chromatin accessibility. Because these measurements describe distinct aspects of regulatory state, using more than one can provide a broader view of how cancer-associated regulation is altered across genomic regions. This combined perspective may help connect regional differences with disrupted regulatory pathways.
Researchers compare tumor and normal samples with high-throughput assays that measure selected epigenetic features across the genome. They then identify regions with significant differences in epigenetic state and interpret those regions in relation to cancer-associated regulation. The resulting profile can be examined for biomarker potential, altered pathways, and treatment-relevant signals.
These profiles can support several cancer research goals: identifying biomarkers for early detection, distinguishing tumor classes, assessing prognosis, and studying treatment response. They also point to regulatory pathways altered in tumors, so the same dataset can connect diagnostic or predictive uses with mechanistic questions about how cancer develops and progresses.
By revealing altered regulatory regions and disrupted pathways, Epigenome-wide Screening can suggest candidate targets for epigenetic therapies. The profiles can guide questions about which regulatory abnormalities might be therapeutically relevant rather than serving only as descriptions of tumor state. This supports more precise investigation of cancer biology and potentially more targeted patient care.