DNA Microarray Basics Quiz

Study Notes

Functional genomics aims to understand the roles of genetic sequences (DNA and RNA) within a species.
Researchers study genes in large groups to analyze their interactions in metabolic pathways.
This research describes how gene products interact for cellular processes.

Proteomics is the study of the entire protein collection (proteome) of a cell or organism.
Scientists aim to understand the functions and interactions of proteins.
The goal is to determine the traits of a species.
Proteomics involves experimental and computational approaches.

Bioinformatics uses computers, mathematical tools, and statistics to analyze biological information.
This field examines genetic data (e.g., DNA sequences) and other biological information.
Bioinformatics plays a crucial role in functional genomics and proteomics.

DNA microarrays, also called gene chips, quantify gene expression in thousands of genes concurrently.
A small slide holds thousands of DNA sequences corresponding to different genes.
Using fluorescently labeled cDNA, the amount of a gene's transcription can be measured.
High fluorescence intensity signifies a large mRNA presence linked to that specific DNA spot.

RNA-Seq is a newer transcriptome analysis method using next-generation sequencing.
It sequences cDNA produced from RNA to identify specific RNAs and their concentrations.
RNA-Seq compares transcriptomes across different cell types, disease states, or environmental conditions.

Gene knockout collections are useful in determining gene functions.
Researchers inactivate individual genes one at a time to observe the resulting phenotypes.
This approach aids in understanding cellular pathways and complex traits associated with genes.
Transposable elements and CRISPR-Cas technology are used for gene knockout collections.

2-DE is a protein separation technique.
Separates proteins in a gel based on isoelectric point (charge) and molecular mass.
Identifies and isolates thousands of different proteins within a single sample.

Mass spectrometry precisely determines molecule masses, including fragments of proteins.
Tandem mass spectrometry sequences peptides to identify whole proteins.
Used to identify proteins from 2-DE spots and further study protein covalent modifications.

Protein microarrays provide a platform for examining protein expression and function.
Using tiny spots of purified proteins from a cell, researchers can analyze protein-ligand interactions (e.g., drug interactions).
Antibody microarrays and functional protein arrays are two types.

Bioinformatics integrates computer science, mathematics and statistics to analyze biological data (e.g. sequences).
Sequences are stored in computer data files which are then analyzed by computer programs.
Sequence recognition, pattern recognition and sequence element (motif) identification are computational strategies used in sequence analysis.
Gene prediction identifies protein-coding DNA segments.
Computational tools identify sequences of particular meaning or function.

Databases are organized collections of biological data like DNA, RNA and protein sequences.
These databases store genetic sequences, additional information (annotations) and references.
Examples include GenBank, EMBL and DDBJ (nucleotide sequences), UniProt, SwissProt, and PIR (amino acid sequences).
Clinical databases, such as OMIM and ClinVar provide crucial genetic information related to human diseases.

Homology refers to similarities in organisms or molecules due to shared ancestry.
Homologous genes are derivates of a common ancestral gene.
Orthologs serve the same function in different species, whereas paralogs carry out different functions in the same species.
Computer programs, such as BLAST, identify similar sequences from a database search which can help predict gene function.
Multiple sequence alignment compares homologous sequences to find conserved sites which may be functionally important.