Genomics Proteomics
Genomics Proteomics - Related Videos
09:29
Skeletal Muscle Gender Dimorphism from Proteomics
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Cited by 4 •
2011
A straight-forward set of methods to isolate and determine the identity of the most abundant proteins expressed in skeletal muscle. About 800 spots are discerned on a two-dimensional gel from 10 mg muscle; this allows for the determination of gender-specific protein expression. These methods will give equivalent results in most tissues.
07:35
Laser Microdissection-Based Protocol for the LC-MS/MS Analysis of the Proteomic Profile of Neuromelanin Granules
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Cited by 4 •
2021
A robust protocol is presented here for isolating neuromelanin granules from human post-mortem substantia nigra pars compacta tissue via laser microdissection. This revised and optimized protocol massively minimizes the required time for sample collection, reduces the required sample amount, and enhances the identification and quantification of proteins by LC-MS/MS analysis.
09:20
Proteomic Sample Preparation from Formalin Fixed and Paraffin Embedded Tissue
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Cited by 48 •
2013
Archival formalin fixed and paraffin embedded (FFPE) clinical samples are valuable material for investigation of diseases. Here we demonstrate a sample preparation workflow allowing in-depth proteomic analysis of microdissected FFPE tissue.
14:23
Bottom-up and Shotgun Proteomics to Identify a Comprehensive Cochlear Proteome
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Cited by 7 •
2014
Proteome analysis of the cochlear sensory epithelium can be challenging due to its small size and because membrane proteins are difficult to isolate and identify. Both membrane and soluble proteins can be identified by combining multiple preparative methods and separation techniques along with high-resolution mass spectrometry.
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.
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Integration links a DNA variant to its downstream molecular consequences. Sequencing identifies differences in genetic material, while protein measurements can show whether those differences coincide with altered protein abundance, modification, or interactions. Mapping these results onto cellular pathways helps researchers move from an associated genetic change toward a more informative account of biological function.
Proteomic measurements add functional detail that a DNA sequence alone cannot provide. Protein abundance indicates how much of a protein is present, whereas modifications and interactions reveal changes in protein state or relationships. These measurements help distinguish genetic information from its effects at the protein level, making it possible to examine cellular activity more directly.
Computational analysis is the connecting layer between the two data types. Genomic sequencing requires comparison of DNA sequences and variation, while proteomic measurements require bioinformatics to organize and interpret protein-related results. Combining these analyses supports functional annotation, which assigns biological meaning to genetic findings by relating them to proteins and cellular pathways.
A combined study can begin by sequencing DNA to characterize genetic material and variation, followed by protein measurement using mass spectrometry. Researchers then analyze the results with computational comparison and bioinformatics, looking for relationships between genetic differences and protein changes. This workflow produces an integrated view rather than treating genomic and proteomic findings as separate observations.
Genomics proteomics analyses support disease-gene discovery and biomarker identification by examining genetic differences alongside protein abundance, modification, and interaction data. This combined evidence connects candidate genetic findings with cellular pathways and molecular mechanisms. As a result, researchers can evaluate disease-related biology at both the genetic and protein levels rather than relying on either type of evidence alone.
In genetics research, the combined perspective can clarify how inherited traits arise from molecular mechanisms. DNA variation provides information about the genetic basis, while protein-level findings show changes in the molecules associated with cellular function. Considering both levels helps researchers connect inherited differences with pathway activity and develop a more precise interpretation of trait biology.