Microarray in the context of Bio-MEMS

Transcriptomics technologies are the techniques used to study an organism's transcriptome, the sum of all of its RNA transcripts. The information content of an organism is recorded in the DNA of its genome and expressed through transcription. Here, mRNA serves as a transient intermediary molecule in the information network, whilst non-coding RNAs perform additional diverse functions. A transcriptome captures a snapshot in time of the total transcripts present in a cell. Transcriptomics technologies provide a broad account of which cellular processes are active and which are dormant.A major challenge in molecular biology is to understand how a single genome gives rise to a variety of cells. Another is how gene expression is regulated.

The first attempts to study whole transcriptomes began in the early 1990s. Subsequent technological advances since the late 1990s have repeatedly transformed the field and made transcriptomics a widespread discipline in biological sciences. There are two key contemporary techniques in the field: microarrays, which quantify a set of predetermined sequences, and RNA-Seq, which uses high-throughput sequencing to record all transcripts. As the technology improved, the volume of data produced by each transcriptome experiment increased. As a result, data analysis methods have steadily been adapted to more accurately and efficiently analyse increasingly large volumes of data. Transcriptome databases have consequently been growing bigger and more useful as transcriptomes continue to be collected and shared by researchers. It would be almost impossible to interpret the information contained in a transcriptome without the knowledge of previous experiments.

In genetics, complementary DNA (cDNA) is DNA that was reverse transcribed (via reverse transcriptase) from an RNA (e.g., messenger RNA or microRNA). cDNA exists in both single-stranded and double-stranded forms and in both natural and engineered forms.

In engineered forms, it often is a copy (replicate) of the naturally occurring DNA from any particular organism's natural genome; the organism's own mRNA was naturally transcribed from its DNA, and the cDNA is reverse transcribed from the mRNA, yielding a duplicate of the original DNA. Engineered cDNA is often used to express a specific protein in a cell that does not normally express that protein (i.e., heterologous expression), or to sequence or quantify mRNA molecules using DNA based methods (qPCR, RNA-seq). cDNA that codes for a specific protein can be transferred to a recipient cell for expression as part of recombinant DNA, often bacterial or yeast expression systems. cDNA is also generated to analyze transcriptomic profiles in bulk tissue, single cells, or single nuclei in assays such as microarrays, qPCR, and RNA-seq.

A DNA microarray (also commonly known as a DNA chip or biochip) is a collection of microscopic DNA spots attached to a solid surface. Scientists use DNA microarrays to measure the expression levels of large numbers of genes simultaneously or to genotype multiple regions of a genome. Each DNA spot contains picomoles (10 moles) of a specific DNA sequence, known as probes (or reporters or oligos). These can be a short section of a gene or other DNA element that are used to hybridize a cDNA or cRNA (also called anti-sense RNA) sample (called target) under high-stringency conditions. Probe-target hybridization is usually detected and quantified by detection of fluorophore-, silver-, or chemiluminescence-labeled targets to determine relative abundance of nucleic acid sequences in the target. The original nucleic acid arrays were macro arrays approximately 9 cm × 12 cm and the first computerized image based analysis was published in 1981. It was invented by Patrick O. Brown. An example of its application is in SNPs arrays for polymorphisms in cardiovascular diseases, cancer, pathogens and GWAS analysis. It is also used for the identification of structural variations and the measurement of gene expression.

Biological databases are libraries of biological sciences, collected from scientific experiments, published literature, high-throughput experiment technology, and computational analysis. They contain information from research areas including genomics, proteomics, metabolomics, microarray gene expression, and phylogenetics. Information contained in biological databases includes gene function, structure, localization (both cellular and chromosomal), clinical effects of mutations as well as similarities of biological sequences and structures.

Biological databases can be classified by the kind of data they collect (see below). Broadly, there are molecular databases (for sequences, molecules, etc.), functional databases (for physiology, enzyme activities, phenotypes, ecology etc), taxonomic databases (for species and other taxonomic ranks), images and other media, or specimens (for museum collections etc.)