Functional Genomic Studies
Functional Genomic Studies - Related Videos
22:27
Hi-C: A Method to Study the Three-dimensional Architecture of Genomes.
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Cited by 517 •
2010
The Hi-C method allows unbiased, genome-wide identification of chromatin interactions (1). Hi-C couples proximity ligation and massively parallel sequencing. The resulting data can be used to study genomic architecture at multiple scales: initial results identified features such as chromosome territories, segregation of open and closed chromatin, and chromatin structure at the megabase scale.
12:36
Genomic MRI - a Public Resource for Studying Sequence Patterns within Genomic DNA
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Cited by 2 •
2011
We present a public computational web site for the analysis of genomic sequences. It detects DNA sequence patterns with various non-random nucleotide compositions. This resource also generates randomized sequences with diverse levels of complexity.
12:20
Bacterial Artificial Chromosomes: A Functional Genomics Tool for the Study of Positive-strand RNA Viruses
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Cited by 5 •
2015
Here, a protocol is presented for creating an infectious bacterial artificial chromosome containing a full-length cDNA of the positive-strand genomic RNA of Japanese encephalitis virus. This protocol can be used to construct a functional cDNA of other positive-strand RNA viruses, making it a powerful genomic tool for studying virus biology.
08:31
Isolation and Genome Analysis of Single Virions using 'Single Virus Genomics'
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Cited by 2 •
2013
Single Virus Genomics (SVG) is a method to isolate and amplify the genomes of single virons. Viral suspensions of a mixed assemblage are sorted using flow cytometry onto a microscope slide with discrete wells containing agarose, thereby capturing the virion and reducing genome shearing during downstream processing. Whole genome amplification is achieved using multiple displacement amplification (MDA) resulting in genomic material that is suitable for sequencing.
09:52
Genetic Manipulation in Δku80 Strains for Functional Genomic Analysis of Toxoplasma gondii
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Cited by 20 •
2013
Here we report a method for using type I and type II Δku80 strains of Toxoplasma gondii to efficiently generate targeted gene deletions and gene replacements for functional genomic analysis.
FAQs
They link measurements of genetic activity with observed molecular or cellular changes. Gene expression profiling can show which genes are active, while sequencing and phenotype analysis provide complementary evidence about genomic features and resulting traits. Combining these data helps researchers move from an association between a gene and an outcome toward a more informative model of biological function.
CRISPR-based perturbation changes the activity of selected genes or regulatory elements, allowing researchers to examine consequences of that alteration. Gene expression profiling instead measures patterns of activity across many genes. Used together, these approaches can connect a deliberate genomic change with downstream expression shifts and cellular phenotypes, helping clarify regulatory relationships rather than only identifying correlations.
Regulatory elements influence how genetic information is used, so their effects may appear through changes in gene activity rather than through altered protein-coding sequences alone. Studying these elements alongside expression data and phenotype analysis can reveal how genes are controlled and how that control contributes to cellular processes or observable traits. This is especially relevant when investigating gene regulation.
A study can begin by selecting genes or regulatory elements, followed by measuring activity or applying a CRISPR-based perturbation. Sequencing and gene expression profiling then capture molecular consequences, while phenotype analysis assesses cellular or observable effects. Researchers integrate these results to identify relationships among genomic features, regulatory activity, cellular processes, and traits.
These studies are useful when researchers need to move from disease-associated genomic features toward biological mechanisms. By combining perturbation, sequencing, expression measurements, and phenotype analysis, they can clarify disease-associated pathways, investigate how regulation contributes to disease mechanisms, and evaluate potential therapeutic targets. The resulting evidence can help prioritize biological processes for further study.
The framework also contributes to developmental and evolutionary biology by examining how genomic activity relates to changing cellular processes and traits. In precision medicine, the same integrative approach can support investigation of biologically relevant genomic features in individual or disease-related contexts. Its value comes from connecting genetic information with functional outcomes across multiple areas of biology.