Technologies used in functional genomic studies

High-throughput technologies

Functional genomic studies frequently rely on high-throughput technologies such as microarrays (animation produced by McGraw-Hill Companies) and high-throughput sequencing (HTS). Examples of these include:

Microarrays

• Expression-profiling – used to measure the expression of thousands of genes at once, using oligonucleotide probes (usually ≤50 basepairs in length) designed from transcript cDNA or exon sequences across the genome.
• Tiling microarrays – often used for mapping transcription factor binding sites or locations of epigenetic marks (e.g. histone modifications). They use overlapping oligonucleotide probes (usually ≤50bp) covering several megabases of genomic sequences.

High-throughput sequencing (HTS)

• RNA sequencing (RNA-Seq) – is used to sequence cDNA in order to get information about a sample’s RNA content.
• ChIP sequencing (ChIP-Seq) – uses Chromatin ImmunoPrecipitation (ChIP) with DNA sequencing to identify protein-binding sites on DNA. 

You can learn more about these applications in this review article (1). 

These studies produce massive amounts of data, e.g. expression values from tens of microarray chips, each with thousands of probes, or tens of millions of very short sequence reads from HTS machines. These data can only help us gain insight into underlying biological processes, if they are carefully recorded and stored in databases, along with the experimental workflows employed and annotated detail for each sample. This will then allow the data to be queried, compared, analysed, interpreted and shared (2) by the research community. Recently, the advent of more sophisticated applications of HTS technology, such as single-cell RNA-seq (sequencing one cell at a time instead of a population of cells) calls for even more meticulous documentation.

As a result, functional genomics databases, such as ArrayExpress in BioStudies, were set up to provide easy access to functional genomics data which have been annotated sufficiently to capture the biology underpinning the experiments. Moreover, the databases distribute the annotated data in a structured and standardised format, facilitating information sharing and automated programmatic data-mining.

Learn more about the technologies used in functional genomics experiments in our course Functional genomics (II): Common technologies and data analysis methods