Genome-wide Interactions
Genome-wide Interactions - Related Videos
10:05
Genome-wide Mapping of Drug-DNA Interactions in Cells with COSMIC (Crosslinking of Small Molecules to Isolate Chromatin)
0 Views •
Cited by 5 •
2016
Identifying the direct targets of genome-targeting molecules remains a major challenge. To understand how DNA-binding molecules engage the genome, we developed a method that relies on crosslinking of small molecules to isolate chromatin (COSMIC).
10:43
Genome-wide Mapping of Protein-DNA Interactions with ChEC-seq in Saccharomyces cerevisiae
0 Views •
Cited by 11 •
2017
We describe chromatin endogenous cleavage coupled with high-throughput sequencing (ChEC-seq), a chromatin immunoprecipitation (ChIP)-orthogonal method for mapping protein binding sites genome-wide with micrococcal nuclease (MNase) fusion proteins.
10:16
Promoter Capture Hi-C: High-resolution, Genome-wide Profiling of Promoter Interactions
0 Views •
Cited by 115 •
2018
DNA regulatory elements, such as enhancers, control gene expression by physically contacting target gene promoters, often through long-range chromosomal interactions spanning large genomic distances. Promoter Capture Hi-C (PCHi-C) identifies significant interactions between promoters and distal regions, enabling the assignment of potential regulatory sequences to their target genes.
14:26
Genome-wide Purification of Extrachromosomal Circular DNA from Eukaryotic Cells
0 Views •
Cited by 59 •
2016
This paper presents a sensitive method called Circle-Seq for purifying extrachromosomal circular DNA (eccDNA). The method encompasses column purification, removal of remaining linear chromosomal DNA, rolling-circle amplification and high-throughput sequencing. Circle-Seq is applicable to genome-scale screening of eukaryotic eccDNA and studying genome instability and copy-number variation.
10:23
Genome-wide Snapshot of Chromatin Regulators and States in Xenopus Embryos by ChIP-Seq
0 Views •
Cited by 15 •
2015
The question of how chromatin regulators and chromatin states affect the genome in vivo is key to our understanding of how early cell fate decisions are made in the developing embryo. ChIP-Seq—the most popular approach to investigate chromatin features at a global level—is outlined here for Xenopus embryos.
FAQs
Genome-wide interaction analyses look for statistical dependence among genes, variants, regulatory regions, and other genomic elements across the genome. This perspective can reveal coordinated effects that would be missed when each element is considered in isolation. The resulting relationships help connect genomic patterns with biological functions that emerge from combined activity rather than from one element alone.
A non-additive genetic effect means that the combined influence of genetic factors is not adequately represented by simply adding their separate effects. Detecting such effects allows researchers to examine how variants act together in relation to complex traits or disease risk. This matters because biological outcomes may reflect interactions among factors instead of independent contributions.
Physical and regulatory contacts provide a way to relate genomic regions to one another beyond statistical association. When analyses connect genetic variation with these relationships, they can help clarify how a variant alters gene regulation and, in turn, influences a cellular phenotype. This connects genome-scale patterns to mechanisms affecting cellular function.
A typical analysis begins with large-scale genomic data, then searches for statistical dependence, non-additive effects, or physical and regulatory contacts among genomic elements. Researchers interpret the detected relationships in the context of biological functions, pathways, complex traits, disease risk, or cellular phenotypes. The workflow therefore moves from genome-wide measurement to relationship detection and biological interpretation.
In biology, these analyses can help identify pathways that influence complex traits and disease risk. They also support investigation of how genetic variation changes gene regulation and contributes to cellular phenotypes. By examining many genomic relationships together, researchers gain evidence for coordinated biological processes rather than relying only on isolated genetic effects.
Genome-wide interaction studies contribute to systems biology and functional genomics by supplying relationships that can be integrated into broader models of biological processes. Their relevance extends beyond cataloging genomic elements: the results help explain how coordinated effects produce phenotypes and support more accurate representations of biological processes.