Common questions

What does ChIP-seq do?

What does ChIP-seq do?

ChIP-Seq identifies the binding sites of DNA-associated proteins and can be used to map global binding sites for a given protein. The DNA is extracted and sequenced, giving high-resolution sequences of the protein-binding sites.

Is ChIP-seq expensive?

For high-resolution profiling of an entire large genome, ChIP-Seq is already less expensive than ChIP-chip; but depending on the genome size and the depth of sequencing needed, a ChIP-chip experiment on carefully selected regions using a customized microarray may yield as much biological understanding.

Why is ChIP-seq important?

ChIP-seq can be used to survey interactions accurately between protein, DNA, and RNA, enabling the interpretation of regulation events central to many biological processes and disease states. Since ChIP-seq provides the actual DNA sequences of the precipitated fragments, the data obtained is of higher resolution.

How long does it take to do ChIP-seq?

Unlike similar methods, which can take up to four days to complete, ATAC-seq preparation can be completed in under three hours. Lower starting cell number than other open chromatin assays (500 to 50K cells recommended for human).

What is ChIP qPCR?

Introduction to ChIP-qPCR Quantitative real-time PCR (qPCR) allows you to quantify DNA concentrations from multiple samples in real time by analyzing fluorescent signal intensities that are proportional to the amount of amplicon after completing the chromatin immunoprecipitation (ChIP) assay and sample purification.

How much does single cell Rnaseq cost?

We typically aim for ~450 million reads per 10x genomics well for standard single cell RNA-Seq projects. Based on this sequencing costs typically average $1750, but can vary based on project goals.

What is input DNA in ChIP?

Input DNA is essentially the DNA purified by cell lysis and sonication. It is the same DNA that is run on a gel to test the efficiency of cell lysis and sonication. Input DNA is the DNA that went through the process without any specific selection for fragments related to binding of transcription factors.

What is the difference between ATAC seq and ChIP-seq?

ChIP-seq alone may be challenging to find meaningful regulatory elements when comparing two or more samples. In this regard, ATAC-seq has the advantage of high resolution and high signal-to-noise ratio, which allows researchers to identify differentially regulated sequences, such as enhancers.

What can using ChIP seq uncover that using ATAC-seq Cannot?

By sequencing regions of open chromatin, ATAC-Seq can help you uncover how chromatin packaging and other factors affect gene expression. ATAC-Seq does not require prior knowledge of regulatory elements, making it a powerful epigenetic discovery tool.

Do you need to optimize sonication with ChIP seq?

With our end-to-end ChIP-Seq services, you don’t need to worry about optimizing sonication to get efficient chromatin shearing or testing multiple antibodies to try to find one that works because we take care of all of that for you.

How does active motif work with ChIP seq?

Using our ChIP-Seq services is simple. You just submit your cell or tissue samples to Active Motif and receive the analyzed data and publication-ready figures back within a matter of weeks. Identify histone modification profiles on a genome-wide scale. Genome-scale analysis of transcription factor binding sites.

Which is the best service provider for ChIP sequencing?

Active Motif has been offering chromatin immunoprecipitation services for well over a decade, and we have more experience performing ChIP assays than any other service provider. Our Epigenetic Services scientists have optimized protocols for many different sample types, including primary cells, T cells, fresh frozen tissues, and FFPE samples.

Why is peak calling complicated in ChIP seq?

Peak calling is complicated by the fact that different algorithms are required for accurate peak calling depending on the antibody used. Thousands to tens of thousands of binding sites must then be exported into a meaningful output that relates the data to genes and allows for multiple samples to be compared to one another.

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