The human genome is a vast set of instructions. While we are all remarkably similar, tiny differences in our DNA, known as genetic variants, make each of us unique. A genetic variant is a change in the DNA sequence compared to a standard or reference sequence. These variations are a normal part of being human and can be inherited or arise spontaneously.
Variant analysis is the process of identifying and studying these genetic differences. By examining an individual’s DNA, this analysis can uncover variants that may influence traits, affect health, or be associated with disease. The goal is to understand how these small changes in DNA contribute to human diversity and health.
The Process of Identifying Genetic Variants
The process of variant analysis begins with collecting a biological sample, such as blood or saliva, from which DNA is extracted in a laboratory. This isolates the DNA from other cellular components, preparing it to be read.
With the DNA isolated, scientists use technologies like Next-Generation Sequencing (NGS). NGS machines read the millions of DNA building blocks, known as nucleotides, that make up a person’s genome. This sequencing process generates a massive amount of data representing the individual’s specific DNA sequence.
The next step is alignment, where the raw sequence data is made sense of. The individual’s sequenced DNA is computationally compared to a standardized human reference genome. This reference acts as a template, allowing scientists to spot any differences. It is much like comparing a new edition of a very long book to the original manuscript to find any changes, typos, or edits that have been made.
Through this comparison, any discrepancies between the individual’s DNA and the reference genome are flagged as variants. These variants are compiled into a file for investigation. The process of finding where sequenced reads differ from the reference is often called “variant calling.”
Types of Genetic Variants
Variants are categorized based on their structure. The most common type is the Single Nucleotide Variant (SNV), where a single letter in the DNA code is replaced with another. This is like a single typographical error in a word. While many SNVs have no effect, their location can alter biological functions.
Another category involves insertions and deletions, often grouped as “indels.” An insertion adds a piece of DNA into the sequence, while a deletion removes a piece. This can be compared to adding or removing a word from a sentence, which can change its meaning.
Larger-scale variants include Copy Number Variations (CNVs). CNVs occur when a long segment of DNA is either duplicated, creating extra copies, or deleted entirely. This is like copying and pasting an entire paragraph in a book or removing it, which can have a substantial impact.
Interpreting Variant Significance
After a variant is identified, the next step is to interpret its potential impact on health by classifying it into one of five categories. This system provides a standardized framework for understanding a variant’s clinical relevance.
The first two categories are for variants linked to disease. “Pathogenic” variants are known to cause a specific medical condition based on extensive scientific evidence. “Likely Pathogenic” variants have a very high likelihood of causing disease, though the evidence is less conclusive.
On the other end of the spectrum are variants not associated with disease. “Benign” variants are known to be harmless and are often common in the general population. “Likely Benign” variants are considered highly unlikely to have a negative health impact.
Many variants fall into the middle category: “Variant of Uncertain Significance” (VUS). This classification is used when there is not enough evidence to determine if the variant is harmful or harmless. A VUS result can be confusing, but it does not mean a person has an undiagnosed disease. It simply means that science does not yet have a clear understanding of that specific variant’s effect, and further research is needed.
Applications in Health and Research
Variant analysis has wide-ranging applications in healthcare and research. In clinical settings, it is used for diagnosing genetic disorders. For conditions like cystic fibrosis or Huntington’s disease, identifying a pathogenic variant in a known gene can confirm a diagnosis and inform treatment.
Another application is in pharmacogenomics, which uses a person’s genetic variants to predict their response to medications. By understanding how genetics affects drug metabolism, doctors can select the most effective drug and dosage while minimizing adverse reactions.
Variant analysis is also used for carrier screening, which helps prospective parents understand their chances of passing a genetic condition to their children. By testing for variants associated with specific recessive disorders, individuals can learn if they are carriers and make informed family planning decisions.
Beyond patient care, variant analysis is a tool in scientific research. Studying genetic variants across large populations helps scientists identify genetic factors that contribute to complex diseases like diabetes, heart disease, and cancer. This research helps to uncover the biological pathways underlying these conditions, paving the way for new preventive strategies and treatments.