We have already discussed DNA sequencing methods, i.e. next-generation sequencing (NGS) methods, and said that they are quite comprehensive but rather expensive. But what if you want to quickly check the gene expression of specific genes or assess the presence of a specific set of mutations? In this topic, we discuss microarrays, small chips that help you with such simple tasks.
How microarray works
A microarray is a molecular biology technique that allows you to analyze the expression levels of hundreds or thousands of genes or other molecules simultaneously. It is a small glass slide or a membrane on which DNA, RNA, protein, or antibody molecules are attached in a specific pattern.
Microarrays work by using a sample labeled with a fluorescent dye. You can use different dyes depending on molecule type: Cy3 (yellow-green color), Cy5 (red color), and Alexa Fluor (range of colors) dyes can be used for DNA or RNA samples, fluorescein isothiocyanate (FITC or green color) or phycoerythrin (PE or red color) are used for protein samples. Alexa Fluor and FITC dyes are more photostable than Cy family and PE dyes respectively. This is the exact reason why the former dyes are used more frequently than the latter ones.
Let's see how DNA and RNA microarrays work. The labeled sample is applied to the microarray, which has hundreds or thousands of tiny spots, each of which contains a specific set of oligonucleotide sequences that often represent genes. If the sample molecule and microarray-binded match one another, hybridization occurs. Fluorescent dye binding to sample molecule allows you to detect the amount of RNA or DNA present in the sample that corresponds to each gene.
Protein microarrays work similarly, but instead of oligonucleotide antibodies – proteins are used. To analyze the microarray, you can use a special microscope or scanner to detect the fluorescence at each spot on the microarray. The intensity of the fluorescence is proportional to the amount of RNA or DNA present in the sample for each gene. By comparing the fluorescence intensity at each spot on the microarray, you can determine which genes are more or less highly expressed in the sample.
Types of microarrays
There are a lot of subtypes of microarrays, though three major subtypes – DNA, protein, and SNP (single nucleotide polymorphism) — are the most frequently used. DNA microarrays are used to study gene expression by measuring the amount of RNA transcribed from a gene. DNA microarrays typically use complementary DNA (cDNA) probes that correspond to specific genes.
Protein microarrays are used to study protein abundance in a sample using attached antibodies or proteins to microarray instead of oligonucleotides. For detailed information about protein microarrays using antibodies, you can look at the Introduction to immunoassay technology topic. The subtype of protein microarrays using proteins on a slide is called reverse phase because instead of antibodies you can use proteins that typically come from a lysate of cells (i.e. cells that were broken down) on a slide. Proteins can be attached to a slide using specific chemistry. Reverse-phase microarrays are quite more sensitive than antibody microarrays and require less biological material to perform analysis.
An SNP microarray is used to detect and genotype SNPs in DNA sequences. SNP microarrays contain DNA probes that are designed to bind specifically to certain nucleotide sequences, and they are used to identify the presence or absence of specific SNPs in a sample. So, SNP microarray gives you a qualitative result, the presence or absence of the mutation, though DNA microarray gives a quantitative output, the expression value of a certain gene.
Applications
Let's see examples below of how DNA, SNP, and protein microarrays can be used.
DNA microarrays can be used for identifying differentially expressed genes in disease. For example, measuring an expression level in tumor and normal tissues will show genes that are overexpressed or underexpressed in the disease, which can help to diagnose the disease and identify potential therapeutic targets. Also, you can use DNA microarrays to study how drugs affect gene expression in cells or tissues. DNA microarrays can help study the microorganisms that live in the human body, including bacteria, viruses, and fungi.
Protein microarray applications are quite similar to DNA ones. Protein microarrays can be used to compare the presence and quantity of molecules in a sample. Also, DNA or RNA-protein interaction can be studied.
SNP microarrays can be used to analyze the genetic makeup of an individual patient and identify variations that may influence their response to a particular treatment. This can help to make specific treatment strategies for individual patients, leading to more effective and personalized healthcare. Also, you can identify genetic mutations that may cause inherited disorders. By comparing the DNA sequence of a patient with a reference genome, you can identify variations that may be responsible for a genetic disorder.
Pros and cons of microarrays
As we discussed above microarrays have versatile applications, can use different types of molecules as an input, and are quite cost-effective, especially compared to NGS techniques. This method is still compatible with NGS techniques for specific needs like circular RNA profiling or studying DNA methylation. A lot of great approaches were designed using microarrays like discovering unknown exons, studying copy number variations of specific genes, identifying DNA sequences to which specific proteins can bind, and so on.
However, there are issues with the method that can make it unusable in certain circumstances. Whatever sample you use, it always contains fluorescent dye, so it can be quite hard to get rid of background fluorescence. Also, this method is not as sensitive as NGS techniques, so you cannot see subtle differences in gene expression using microarrays. To make changes in the analysis, you need to redesign the whole slide (i.e. use another one).
Conclusion
The microarray technique is a useful tool that allows you to analyze gene expression or mutation profiles of hundreds or thousands of genes at the same time. It can be used in many ways such as assessing differential expressed genes between a healthy person and a person with a disease, researching the effect of drugs on gene expression, and studying microbiomes and SNPs. However, like any method, this one has some issues — background fluorescence, insensitivity to subtle changes in gene expression, and poor scalability. Next time we will discuss how to analyze microarray data and specific databases in which microarray data is stored.