Transcriptome analysis; Proteomics Flashcards
Transcriptome analysis attempts to
catalog and quantify the total RNA content of a cell, tissue, or organism.
Transcriptome analysis reveals gene-expression profiles that, for the same genome, may
vary from cell to cell or from tissue type to tissue type
Transcriptome analysis provides insights into:
■ normal patterns of gene expression that are important for understanding how a cell or tissue type differentiates during development
■ how gene expression dictates and controls the physiology of differentiated cells
■ mechanisms of disease development that result from or cause gene-expression changes in cells.
For example, examining gene-expression profiles in a cancerous tumor can help diagnose tumor type, determine the likelihood of tumor metastasis (spreading), and develop the most effective treatment strategy.
Transcriptome analysis also called
transcriptomics or global analysis of gene expression
Transcriptome analysis studies the expression of genes in a genome
both qualitatively and quantitatively.
Qualitatively
- by identifying which genes are expressed or not expressed.
Quantitatively
- by measuring varying levels of expression for different genes.
For nearly two decades DNA microarray analysis has been widely used because it
enables researchers to analyse all of a sample’s expressed genes simultaneously.
A single microarray can have over 20,000 different spots of DNA, each containing
a unique sequence that serves as a probe* for a different gene.
Probe
need to have sequence information about the genes of interest
PCR-based methods - such as reverse transcription PCR (RT-PCR) and quantitative real-time PCR (qPCR) are useful because
of their ability to detect genes expressed at low levels.
Now, RNA-Seq has superseded arrays – totally dominate expression analysis.
Qualitative and quantitative for totally unknown samples.
Microarray Analysis
DNA Microarray Analysis – How does one interpret an experiment?
In this experiment a microarray was used to analyse gene expression patterns as a plant was infected with a pathogen – over a period of 290 min (4.8 hours). Assume it was an Arabidopsis plant and we used the Affymetrix gene chip (picture to the right). Looking more closely we see on the chip (picture on the left), specific clusters of genes being up- or down-regulated as the infection progresses. This gives us valuable information as to how Arabidopsis responds to a pathogen infection.
Microarrays are limited
As they can only study the expression of the genes with probes on the chip.
Direct RNA sequencing (RNA-seq) - called whole-transcriptome shotgun sequencing - allows for
quantitative analysis of all RNAs expressed in a particular tissue and, also provides actual sequence data.
Proteomics
the identification, characterisation, and quantitative analysis of proteomes
The Proteome is defined as
the complete set of proteins encoded by a given genome
Studying the proteome can yield valuable information about:
A protein’s structure and function
Posttranslational modifications
Protein-protein, protein-nucleic acid, and protein-metabolite interactions
Cellular localisation of proteins
Protein stability and aspects of translational and post-translational levels of gene-expression regulation
Relationships (shared domains, evolutionary history) to other proteins
Proteomes are larger than genomes
[Sequencing of mRNAs from human tissues found that over 95 % of protein-coding genes with more than one exon are alternatively spliced.]
Different transcriptional start sites
Alternative mRNA splicing
RNA editing
Post-translational modifications (> 100 mechanisms are known)
Human Proteome Map (HPM) – to cataloque the human proteome (2014)
About __________ of the Drosophila proteome has been well catalogued using proteomics.
two-thirds
Proteomics is also of clinical value because it
allows comparison of proteins in normal and diseased tissues, which can lead to the identification of proteins (or smallRNAs) as bio-markers for disease conditions.
Genes can have multiple transcription start sites that produce several different types of RNA transcripts.
Alternative splicing and editing of pre-mRNA molecules can generate dozens of different proteins from a single gene.