Single Nucleotide Polymorphism

Single nucleotide polymorphisms (SNPs) are alternative bases that occur at a single position within a genomic DNA sequence and may also be considered alleles, or variations at a specific locus or position in relation to a particular gene or genetic marker. Biotechnology has significantly influenced modern biology, particularly in terms of studies in the areas of molecular biology and genetics. Massive genetic data at various levels and resolutions have been generated in the past few decades, such as DNA sequences, genotypic information, haplotypes, and expression levels at the mRNA and protein levels. One of the most important applications of genetic data is in identifying polymorphisms or changes in nucleotide bases in relation to the development of various human diseases such as cancer, heart disease, diabetes, and neurological disorders. One of the most significant types of genetic data includes SNPs, which generally occur about once in every 1,000 nucleotides on average in a person’s genome.

Background

Early large-scale SNP studies were associated with the Human Genome Project and The SNP Consortium, which was an internationally funded initiative to sequence and map the human genome and identify human genes. In addition to these goals, the Human Genome Project also aimed to detect all types of polymorphisms that possibly contribute to various diseases. These polymorphisms are identified by comparing DNA sequences among individuals. SNPs are the most common type of polymorphism, representing around 90 percent of DNA variation in humans.

An SNP was first described as a diallelic marker, thus involving only two types of alleles. For example, the nucleotides adenine (A) and guanine (G) may occur at a particular location, which in turn may result in three genotypes, namely, AA, AG, and GG. However, DNA is double-stranded; therefore, if A and G occur on one strand, T and C occur on the complementary strand. The general frequency of a single base difference in a particular location in the genome of two chromosomes therefore represents nucleotide diversity, which is approximately 1/1,000 base pairs (bp). SNPs occur about once in every 1,000 nucleotides on average in a person’s genome.

SNPs have been calculated to occur at intervals of 1,000 bp across the entire human genome. However, there are certain regions within the human genome that may vary; SNPs may therefore occur within the range of once to 100-fold higher in certain regions of the genome. In addition, SNPs are also present in various regions of the human genome, including coding regions (exons), non-coding regions (introns), and upstream regions of genes (promoters). In general, SNPs are often detected within introns, which are regions that do not encode any protein product. Finally, the most common SNP involves nucleotides C and T. The years following the completion of the Human Genome Project have witnessed attempts to establish patterns of occurrence of SNPs in specific diseases by using case-control studies.

Impact

The ideal situation for utilizing SNPs is to compare the sequences of large populations of healthy control individuals with those of a particular disease. The advent of high-throughput sequencing technologies has facilitated these research investigations. These efforts have resulted in reports that describe the occurrence of around 1.42 million SNPs within the human genome, which are distributed in particular patterns across specific regions of the genome. A common method in performing comparative studies involves case-control research investigations and assessing the occurrence of specific SNP patterns. The best scenario for case-control studies is to include a large number of study participants and control subjects, thereby generating results with stronger statistical power. In addition, the data gathered from these case-control studies are deposited into a public database for SNPs such as the dbSNP, which houses approximately 1.2 billion human RefSNP records. The dbSNP database also houses SNP information for other species, such as the mouse and chicken, and major parasites and pathogens. To further support studies, the National Center for Biotechnology Information (NCBI) of the National Institutes of Health in Bethesda, Maryland, has led efforts in cross-annotating various resources, including PubMed and GenBank, to the dbSNP. dbSNP releases integrate data from major genomic resources such as gnomAD, TOPMed, ALFA, and the 1000 Genomes Project, providing improved allele-frequency information for genetic research and precision medicine applications.

The information available in various SNP databases serves as a valuable resource for genomic investigations. However, SNP information is also largely influenced by the quality and the coverage of the sequences in the genome. Because there may be hundreds of institutions that submit SNP information to these databases, it is highly likely that certain entries are also of low quality. It thus appears that the most important issue that has to be resolved with regards to SNPs is to determine whether a detected single-base change is real. There are also growing issues with the density of SNPs in genic (protein-coding genomic regions) and non-genic (non-protein-coding genomic regions). Researchers have suggested that the density of SNPs is apparently higher in non-genic regions, possibly because these are less likely to result in amino acid changes. On the other hand, SNPs occurring within genic regions may be strategically positioned at places that are less highly conserved, so that modifications in a single nucleotide may not be as deleterious to the final protein product.

Another approach in determining whether a specific SNP is real is to screen several unrelated individuals and find out if that particular SNP also exists in these subjects. For example, a research group may lead a sequencing project for a specific SNP in two hundred healthy controls. If the SNP of interest is detected in 1 percent of the study participants, then that particular SNP may then be considered real. To date, several population studies have been conducted to screen larger groups of individuals for particular SNPs. These include the 1,000 Genomes Project, whose final phase included 2,504 individuals from 26 populations. Other SNP projects include the Exome Sequencing Project (ESP) and the Exome Aggregation Consortium (ExAC).

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