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Contact a health care provider if you have questions about your health. What are single nucleotide polymorphisms SNPs? From Genetics Home Reference. Topics in the Genomic Research chapter What are the next steps in genomic research?

While such analyses are intended to identify complex variants, related to disease susceptibility and efficacy of drug responses, they have blurred the definitions of mutation and polymorphism. In the era of personal genomics, it is critical to establish clear guidelines regarding the use of a reference genome.

Nowadays DNA variants are called as differences in comparison to a reference. The alternative use of the two terms mutation or polymorphism for the same event a difference as compared with a reference can lead to problems of classification.

These problems can impact the accuracy of the interpretation and the functional relationship between a disease state and a genomic sequence.

We propose to solve this nomenclature dilemma by defining mutations as DNA variants obtained in a paired sequencing project including the germline DNA of the same individual as a reference. Moreover, the term mutation should be accompanied by a qualifying prefix indicating whether the mutation occurs only in somatic cells somatic mutation or also in the germline germline mutation. We believe this distinction in definition will help avoid confusion among researchers and support the practice of sequencing the germline and somatic tissues in parallel to classify the DNA variants thus defined as mutations.

The human genome consists of over 3 billion base pairs which reside in every nucleated cell of the body [ 1 , 2 ]. The genome, which has remained well conserved throughout evolution, is at least Modern genomic tools have revealed that it is more complex, diverse, and dynamic than previously thought, even though the genetic variation is limited to between 0.

Sequence variations, even in non-protein coding regions of the DNA, have begun to alter our understanding of the human genome. While some studies have linked certain variants to being predictive of disease susceptibility and drug response, the majority of diseases have a very complex genetic signature reviewed in [ 8 , 9 ]. Biomedical research is shifting towards understanding the functional importance of many such variations and their association with human diseases.

At the heart of these novel discoveries are the modern DNA sequencing tools, which continue to evolve at a rapid pace. The new sequencing technologies continue to become cheaper and more precise, and facilitate novel medical and biological breakthroughs all over the world [ 10 , 11 ].

Scientific research has become nearly inconceivable without employing sequencing technology but, with the progress of technology and the increasing sequencing of individuals, a massive amount of data is being generated. However, any data without context and analysis is useless. The data from sequencing must be carefully annotated, securely stored, and easily accessible from repositories when needed.

Such arduous tasks require functional collaboration among clinicians, researchers, and health professionals [ 12 ]. In a recent thread in the ResearchGate portal [ 13 ], an ongoing discussion on the difference between a mutation and a polymorphism elicited a response from more than three hundred participants from various scientific backgrounds.

The variety of responses prompted us to write this document as a paper aimed at stimulating the discussion further and possibly finding a consensus on the usage of the terms mutation and polymorphism in the context of a reference sequence in a personal genome project.

Established in , the Human Genome Project was one of the most expensive and collaborative ventures ever undertaken in science. Ten years since its completion, it has continued to provide a wealth of novel information, the implications of which are not yet fully understood [ 8 ].

The open-access nature of the project has stimulated scientists, as well as scientific companies, to develop better sequencing tools and accompanying analytical software. Sequencing tools will play an important role in the development of personalized medicine. Some sequencing technologies are already used in clinics to test genetic conditions, diagnose complex diseases, or screen patient samples for rare variants.

These tests allow health professionals to accurately diagnose a disease and prescribe appropriate medication specific to the patient [ 15 , 16 ]. With the recent support of NIH grants in the US, neonatal sequencing is being explored to probe rare and complex disorders of newborn babies [ 17 , 18 ].

There are technologies in development that allow non-invasive ways of sequencing a genome of an unborn child [ 19 ]. Personalized genome sequencing will transform the future of the healthcare landscape. However, the rise in the number of sequenced genomes is creating new problems. In particular, the way the genome analysis software works is through comparison of the obtained sequences with a reference. Because the human genome is different between different individuals, what is the reference sequence?

What is the threshold to distinguish common from rare DNA variants? Amid all these interesting implications of genome sequencing, the debate concerning the correct use of scientific terminology remains. From a strictly grammatical and etymological point of view, a mutation is an event of mutating and a polymorphism is a condition or quality of being polymorphic ; but these terms by extension quickly came to mean the resulting event or condition itself.

Since no clear rules are available, currently used software tools used for genome sequencing make no assignment and label the difference simply as DNA variant, blurring the distinction between the two categories.

The uniform and unequivocal description of sequence variants in human DNA and protein sequences mutations, polymorphisms were initiated by two papers published in [ 20 , 21 ]. This change in the nucleotide sequence may or may not cause phenotypic changes.

Mutations can be inherited from parents germline mutations or acquired over the life of an individual somatic mutations , the latter being the principal driver of human diseases like cancer. Germline mutations occur in the gametes. Since the offspring is initially derived from the fusion of an egg and a sperm, germline mutations of parents may also be found in each nucleated cell of their progeny.

Mutations usually arise from unrepaired DNA damage, replication errors, or mobile genetic elements. There are several major classes of DNA mutations.

A point mutation occurs when a single nucleotide is added, deleted or substituted. Along with point mutations, the whole structure of a chromosome can be altered, with chromosomal regions being flipped, deleted, duplicated, or translocated [ 23 ].

In this case, the expression of a gene is amplified or reduced through increased decreased copy number of a locus allele [ 24 , 25 ]. The higher incidence in the population suggests that a polymorphism is naturally occurring, with either a neutral or beneficial effect.

Polymorphisms can also be of one or more nucleotide changes, just like mutations. However, SNPs can also occur in coding sequences, introns, or in intergenic regions [ 27 ]. SNPs are used as genetic signatures in populations to study the predisposition to certain traits, including diseases [ 29 ]. In the era of advanced DNA sequencing tools and personal genomics, these earlier definitions of mutation and polymorphism are antiquated.

Before multiple parallel sequencing was developed, it was impossible to sequence multiple times the genome of the same patient.

For these reasons at that time it was required to use a reference sequence coming from the assembly of multiple genomes. The threshold being arbitrary, redefining the population itself may affect the classification, with rare variants becoming polymorphisms or polymorphisms becoming rare variants according to the population analyzed.

For decades, the use of this frequency to develop population models was preferred to the use of sequencing tools, which at that time were error-prone and labor-intensive. With the advent of new sequencing technologies and the subsequent sequencing of individuals, a very different picture of population dynamics has begun to emerge. Even more surprising, there is a lack of association of some of these rare mutations with human diseases.

When comparing populations separated by geographic and physical barriers, a disease-causing mutation in one population is found to be harmless in another, and vice versa [ 32 ].

For instance, sickle-cell anemia is caused by a nucleotide change SNP rs in a gene coding for the beta chain of the hemoglobin protein [ 33 ]. The disease manifests in people who have two copies of the mutated gene rs T;T genotype. However, the heterozygous form of the gene rs A;T genotype is persistent in populations of Africa, India, and other developing nations, where malaria is endemic [ 33 ]. In these geographic locations, heterozygote carriers of rs have a survival advantage against the malaria pathogen, and therefore this beneficial mutation is passed through the offspring to succeeding generations [ 35 — 37 ].

Here, a rare variant, which in one population developed nations causes a severe disease in homozygosis, can persist in another population to confer a survival advantage as a polymorphism in heterozygosis [ 38 ]. Such exceptions are increasing and show the need to redefine the terms mutation and polymorphism.

The distinction between mutation and polymorphism on the basis of their disease-causing capacity is further complicated. Although thought to be naturally occurring, recent research into SNPs has shown that they can be associated with diseases like diabetes and cancers.

At least 40 SNPs have been shown to associate with type-2 diabetes alone [ 39 ]. In short, it is not possible to classify the functional role of variations according to frequency in the population or their capability to cause a disease. Multiple international collaborative projects like ENCODE Encyclopedia of DNA elements and HapMap Haplotype Map have ensued to map all the genes, genetic variation, and regulatory elements of the genome, to find associations with human biology, personal traits, and diseases [ 40 ].

In this climate, commercial companies like Illumina and Roche are developing advanced and robust platforms that tailor to the need of both small and large research facilities.

The increasing competition among these companies has resulted in many different technologies, which are now available to facilitate new insights into genomics [ 11 ].

Similarly, advanced genomic tools and analytical software have been developed that can function independently of the particular platform.

Researchers using tools like CLC genomics, Next Gene and Geno Matrix, can access and download sequencing datasets for their own streamlined research. The primary goal of such research is to look for subtle, complex, and dynamic sequence variations. The lack of consistent definitions and a uniform scientific language can hamper this upcoming field, where genomic platforms may formulate incorrect hypotheses and researchers may misinterpret data based on earlier definitions.

The problem is particularly important in the case of precision medicine and personalized treatments. For example, one of the main reasons to sequence the genome of a cancer consists in the identification of unique genetic features of cancer cells which may then be targeted with a personalized treatment [ 41 ]. Accordingly, it is required to classify the somatic mutations of the cancer cells and use such knowledge to exploit therapeutically all the differences between cancer and noncancerous cells.

Therefore, in order to be treated with a targeted agent a cancer patient needs to express the target originated by the specific mutation occurring in cancer cells. However, should a difference be misclassified, it becomes possible for a polymorphism present in all the cells of the patient to be taken as a somatic mutation. The result could be a toxic effect, since the targeted treatment will impact both cancer and noncancerous cells carrying the same genetic variant.