Bioresearch Highlights on Single Nucleotide Polymorphisms (SNPs), and their Applications
Bhawanpreet Kaur1 and CS Mukhopadhyay2*
1Ph.D. Scholar, College of Animal Biotechnology, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, Punjab, India
2Senior Scientist, Department of Bioinformatics, College of Animal Biotechnology, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, Punjab, India
*Corresponding Author: CS Mukhopadhyay, Senior Scientist, Department of Bioinformatics, College of Animal Biotechnology, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, Punjab, India.
August 05, 2022; Published: August 29, 2022
Single nucleotide polymorphisms (SNPs) are an important type of genetic variation that occurs due to differences in one nucleotide between individuals. SNPs are distributed throughout the genome and can occur in both coding as well as non-coding regions. Different SNPs databases and tools for predicting protein-altering variants are available with huge information. For detecting the synonymous and nonsynonmous SNPs for genome-wide studies online and offline tools are accessible. In bioinformatics, SNPs are crucial to understanding the molecular mechanisms of sequence evolution, association with human diseases, and variation between individuals in response to drugs and can be used to make personalized medicines. Therefore, in this systematic review, we also discuss the vital role of SNPs in genetic mapping, pharmacogenomics, gene discovery, pharmacogenetics, diseases, evolution, nutrigenetics, nutrigenomics, and strong biological markers.
Keywords: Single Nucleotide Polymorphism; Genome; Markers; Databases; Mutation
- Agrafioti I., et al. “SNPSTR: a database of compound microsatellite-SNP markers”. Nucleic Acids Research 35 (2017): D71-D75.
- Altshuler D., et al. “The common PPARgamma Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes”. Nature Genetics 26 (2000): 76-80.
- Bao L., et al. “nsSNPAnalyzer: identifying disease-associated nonsynonymous single nucleotide polymorphisms”. Nucleic Acids Research 33 (2005): W480-W482.
- , et al. “Natural selection has driven population differentiation in modern humans”. Nature Genetics 40 (2000): 340-345.
- Beaney KE., et al. “Clinical utility of a coronary heart disease risk prediction gene score in UK healthy middle-aged men and in the Pakistani population”. PLoS ONE7 (2015): e0130754.
- Capriotti E., et al. “I-Mutant2. 0: predicting stability changes upon mutation from the protein sequence or structure”. Nucleic Acids Research2 (2005): W306-W310.
- Capriotti E and Fariselli P. “PhD-SNPg: a webserver and lightweight tool for scoring single nucleotide variants”. Nucleic Acids Research W1 (2017): W247-W252.
- Chang H., et al. “PicSNP: a browsable catalog of nonsynonymous single nucleotide polymorphisms in the human genome”. Biochemical and Biophysical Research Communications 1 (2001): 288-291.
- Cheng J., et al. “Prediction of Protein Stability Changes for Single Site Mutations Using Support Vector Machines”. Proteins4 (2006): 1125-1132.
- Choi Y., et al. “Predicting the functional effect of amino acid substitutions and indels”. PLoS One 10 (2012): e46688.
- Cox A., et al. “Common coding variant in CASP8 is associated with breast cancer risk”. Nature Genetics 39 (2007): 352-358.
- Drake T., et a “Integrating genetic and gene expression data: application to cardiovascular and metabolic traits in mice”. Mammalian Genome 17 (2006): 466-479.
- Evans WE and Johnson JA. “Pharmacogenomics: the inherited basis for interindividual differences in drug response”. Annual Review of Genomics and Human Genetics 2 (2001): 9-39.
- Fredman D., et al. “HGVbase: a human sequence variation database emphasizing data quality and a broad spectrum of data sources”. Nucleic Acids Research1 (2002): 387-391.
- Garcia-Closas M., et al. “Heterogeneity of breast cancer associations with five susceptibility loci by clinical and pathological characteristics”. PLoS Genet 4 (2008): 1000054.
- George AW., et al. “Eagle for better genome-wide association mapping”. G3 (Bethesda)9 (2001): 204.
- Goyette P., et al. “Human methylenetetrahydrofolatereductase isolation of cDNA, mapping and mutation identification”. Nature Genetics 7 (1994): 195-200.
- Gray IC., et al. “Single nucleotide polymorphism as tools in human genetics”. Human Molecular Genetics 9 (2000): 2403-2408.
- Hamosh A., et al. “Online Mendelian Inheritance in Man (OMIM), aknowledgebase of human genes and genetic disorders”. Nucleic Acids Research 33 (2005): 514-D517.
- , et al. “SNP2NMD: a database of human single nucleotide polymorphisms causing nonsense-mediated mRNA decay”. Bioinformatics 23.3 (2007): 397-399.
- Hirschhorn JN and Daly MJ. “Genome-wide association studies for common diseases and complex traits”. Nature Reviews Genetics 6 (2005): 95-108.
- Joshua S., et al. “CanPredict: a computational tool for predicting cancer-associated missense mutations”. Nucleic Acids Research2 (2007): W595-W598.
- Kammerer S., et al. “Association of the NuMA region on chromosome 11q13 with breast cancer susceptibility”. Proceedings of the National Academy of Sciences of the United States of America 102 (2005): 2004-2009.
- Karchin R., et al. “LS-SNP: large-scale annotation of coding non-synonymous SNPs based on multiple information sources”. Bioinformatics 21 (2005): 2814-2820.
- Karolchik D., et al. “The UCSC Genome Browser Database”. Nucleic Acids Research 31.1 (2003).
- Khan AU., et al. “Modulation of brain tumor risk by genetic SNPs in PARP1gene: Hospital based case control study”. Plos one 10 (2015): e0223882.
- Kim SK., et al. “A genome-wide association study for shoulder impingement and rotator cuff disease”. Journal of Shoulder and Elbow Surgery 9 (2021): 2134-2145.
- Kumar D., et al. “A functional SNP associated with atopic dermatitis controls cell type specific methylation of the VSTM1 gene locus”. Genome Medicine 9 (2017): 18.
- Li F., et al. “A Brassica rapa linkage map of EST-based SNP markers for identification of candidate genes controlling flowering time and leaf morphological traits”. DNA Research 6 (2009): 311-323.
- Martin ER., et al. “SNPing away at complex diseases: analysis of single-nucleotide polymorphisms around APOE in Alzheimer disease”. The American Journal of Human Genetics 67 (2000): 383-394.
- Masoodi TA., et al. "Screening and Evaluation of Deleterious SNPs in APOE Gene of Alzheimer’s Disease". Neurology Research International 2012 (2012): 8.
- Mi H., et al. “The PANTHER database of protein families, subfamilies, functions and pathways”. Nucleic Acids Research 33 (2005): D284-D288.
- Moffatt MF., et al. “A large-scale, consortium-based genomewide association study of asthma”. The New England Journal of Medicine 13 (2010): 1211-1221.
- Ng PC and Henikoff S. “SIFT: predicting amino acid changes that affect protein function”. Nucleic Acids Research 31 (2003): 3812-3814.
- Noureddine MA., et al. “Association between the neuron-specific RNA-binding protein ELAVL4 and Parkinson disease”. Human Genetics 117 (2005): 27-33.
- Ordovas JM and Mooser V. “Nutrigenomics and nutrigenetics”. Current Opinion in Lipidology 15 (2004): 101-108.
- Ozaki K., et al. “Functional SNPs in the lymphotoxin-alpha gene that are associated with susceptibility to myocardial infarction". Nature Genetics4 (2002): 650-654.
- Prots I., et al. “Association of the IL4R single-nucleotide polymorphism I50V with rapidly erosive rheumatoid arthritis”. Arthritis and Rheumatology 54 (2006): 1491-1500.
- Ramensky V., et al. “Human non-synonymous SNPs: server and survey”. Nucleic Acids Research 30 (2002): 3894-3900.
- Rozanov DV., et al. “The low-density lipoprotein receptor-related protein LRP is regulated by membrane type-1 matrix metalloproteinase (MT1-MMP) proteolysis in malignant cells”. Journal of Biological Chemistry 279 (2004): 4260-4268.
- Sherry ST., et al. “DbSNP: the NCBI database of genetic variation”. Nucleic Acids Research1 (2001): 308-311.
- Sleiman PM., et al. “Variants of DENND1B associated with asthma in children”. The New England Journal of Medicine 1 (2010): 36-44.
- Subbiah MT. “Nutrigenetics and nutriceuticals: the next wave riding on personalized medicine”. Translational Research 149 (2007): 55-61.
- Tegelberg P., et al. “A genome-wide association study for shoulder impingement and rotator cuff disease”. PBMC Oral Health1 (2021): 611.
- Thorisson GA., et al. “The International HapMap Project Web site”. Genome Research 15.11 (2005): 1592-1593.
- Tian J., et al. “Predicting the phenotypic effects of non-synonymous single nucleotide polymorphisms based on support vector machines”. BMC Bioinformatics 8 (2007): 450.
- Van den Maagdenberg AM., et al. “Migraine: gene mutations and functional consequences”. Current Opinion in Neurology 20 (2007): 299-305.
- Vyshkina T and Kalman B. “Haplotypes within genes of beta-chemokines in 17q11 are associated with multiple sclerosis: a second phase study”. Human Genetics 118 (2005): 67-75.
- Xie W., et al. “Parent-independent genotyping for constructing an ultrahigh-density linkage map based on population sequencing”. Proceedings of the National Academy of Sciences of the United States of America 23 (2010): 10578-10583.