Dna Chips
Dna Chips - Related Videos
12:24
DNA-affinity-purified Chip (DAP-chip) Method to Determine Gene Targets for Bacterial Two component Regulatory Systems
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Cited by 10 •
2014
This video article describes an in vitro microarray based method to determine the gene targets and binding sites for two component system response regulators.
09:27
The ChIP-exo Method: Identifying Protein-DNA Interactions with Near Base Pair Precision
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Cited by 9 •
2016
Here, we present a protocol to achieve near base pair resolution of protein-DNA interactions. This is obtained by exonuclease treatment of DNA fragments selectively enriched by chromatin immunoprecipitation (ChIP-exo) followed by high throughput sequencing.
09:52
Generation of High Quality Chromatin Immunoprecipitation DNA Template for High-throughput Sequencing (ChIP-seq)
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Cited by 15 •
2013
The combination of chromatin immunoprecipitation and ultra-high-throughput sequencing (ChIP-seq) can identify and map protein-DNA interactions in a given tissue or cell line. Outlined is how to generate a high quality ChIP template for subsequent sequencing, using experience with the transcription factor TCF7L2 as an example.
09:14
Examination of Proteins Bound to Nascent DNA in Mammalian Cells Using BrdU-ChIP-Slot-Western Technique
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Cited by 4 •
2016
In this protocol, we describe a novel BrdU-ChIP-Slot-Western technique to examine proteins and histone modifications associated with newly synthesized or nascent DNA.
07:50
Chip-Based Digital PCR to Detect Rare Transcript Variants Using a Nanofluidic Chip
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2025
This video demonstrates chip-based digital PCR — a variation of the digital PCR technique that is useful in detecting rare transcript variants. The PCR reaction is partitioned into the chambers of a nanofluidic chip, each of which acts as an independent reaction. The detection of fluorescence signals from the chambers with amplified targets confirms the presence of rare transcript variants in the sample.
FAQs
Each immobilized probe is designed to associate with a complementary nucleic-acid sequence in the labeled sample. When binding occurs, the corresponding location produces a fluorescence signal. The resulting spatial pattern connects individual signals with particular genes or variants, allowing researchers to infer which sequences are present or represented in the sample.
Fluorescence converts molecular binding events into detectable signals. Researchers examine the intensity and distribution of these signals across the chip to identify patterns associated with genetic sequences or gene activity. Because the output is a broad fluorescence profile rather than a single observation, interpretation commonly depends on computational analysis to organize and compare the measurements.
The same probe-based platform can address different biological questions depending on the nucleic-acid sequences represented and the comparison being made. Expression studies examine patterns associated with genes being expressed, whereas genotyping focuses on sequence or variant differences. This flexibility lets one technology investigate cellular activity as well as inherited or acquired sequence changes.
A single chip can produce thousands of measurements, so the fluorescence pattern must be organized and analyzed to reveal meaningful genetic or expression differences. Computational analysis helps researchers interpret broad molecular profiles, compare biological samples, and identify patterns linked with cellular states. Independent validation remains important because chip results are not necessarily sufficient on their own.
A typical workflow places a labeled sample containing nucleic acids in contact with the chip’s immobilized probes, allowing complementary sequences to hybridize. Researchers then examine the resulting fluorescence pattern and use computational methods to interpret it. The workflow therefore moves from sequence-specific binding to signal detection and finally to biological comparison or classification.
Researchers can use DNA chips to identify molecular differences between healthy and diseased cells by comparing their gene-expression or genetic profiles. These comparisons may reveal altered regulatory pathways, distinguish biological states, and highlight molecular features associated with disease. The findings can then guide further investigation of potential targets rather than serving as a complete conclusion by themselves.
DNA chips can generate broad molecular profiles from relatively small samples, allowing researchers to examine many genes or variants together. Such profiles can reveal coordinated changes, support classification of biological states, and expose relationships among cellular processes. In biology, this systems-level view is useful for developing hypotheses about regulation and selecting targets for additional research.