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Methodology for single nucleotide polymorphism selection in promoter regions for clinical use. An example of its applicability.

ABSTRACT: Genetic variability in humans can explain many differences in disease risk factors. Polymorphism-related studies focus mainly on the single nucleotide polymorphisms (SNPs) of coding regions of the genes. SNPs on DNA binding motifs of the promoter region have been less explored. On a recent study of SNPs in patients with non-Hodgkin lymphomas we faced the problem of SNP selection from promoter regions and developed a practical methodology for clinical studies. The process consists in identifying SNPs in the coding and promoter regions of the antigen-processing system using the 'dbSNP' database. With the 'HapMap' program, we select SNPs with frequencies >20% in Caucasian populations. For coding regions, we sought biologically and clinically relevant SNPs described in the literature. For the promoter regions, we determined their chromosomal location on 'QiagenSABioscience' site database. The nucleotide sequence of ancestral and variant alleles is available in the 'dbSNP'. These sequences were used in 'Promoter TESS' to determine binding differences of transcription factors. Each sequence may have affinity to different TFs. Thus, SNP selection on the promoter regions was based in the differences on TF binding pattern between the old and the new allele. The potential clinical relevance of the new TFs was also evaluated before the final selection. With this approach, we found that almost half of the relevant SNP fall within the promoter region. In conclusion, we were able to develop a methodology of oriented selection of promoter regions of human genes, comparing the TF with affinity to the ancestral allele with the TF to a variant allele. We selected those SNPs that change the TF's affinity to a pattern with functional significance.

SUBMITTER: Marques H

PROVIDER: S-EPMC5069276 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Methodology for single nucleotide polymorphism selection in promoter regions for clinical use. An example of its applicability.

Marques Herlander H Freitas José J Medeiros Rui R Longatto-Filho Adhemar A

International journal of molecular epidemiology and genetics 20160930 3

Genetic variability in humans can explain many differences in disease risk factors. Polymorphism-related studies focus mainly on the single nucleotide polymorphisms (SNPs) of coding regions of the genes. SNPs on DNA binding motifs of the promoter region have been less explored. On a recent study of SNPs in patients with non-Hodgkin lymphomas we faced the problem of SNP selection from promoter regions and developed a practical methodology for clinical studies. The process consists in identifying ...[more]

PMID: 27766139

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Project description:BACKGROUND:Complex malaria infections are defined as those containing more than one genetically distinct lineage of Plasmodium parasite. Complexity of infection (COI) is a useful parameter to estimate from patient blood samples because it is associated with clinical outcome, epidemiology and disease transmission rate. This manuscript describes a method for estimating COI using likelihood, called COIL, from a panel of bi-allelic genotyping assays. METHODS:COIL assumes that distinct parasite lineages in complex infections are unrelated and that genotyped loci do not exhibit significant linkage disequilibrium. Using the population minor allele frequency (MAF) of the genotyped loci, COIL uses the binomial distribution to estimate the likelihood of a COI level given the prevalence of observed monomorphic or polymorphic genotypes within each sample. RESULTS:COIL reliably estimates COI up to a level of three or five with at least 24 or 96 unlinked genotyped loci, respectively, as determined by in silico simulation and empirical validation. Evaluation of COI levels greater than five in patient samples may require a very large collection of genotype data, making sequencing a more cost-effective approach for evaluating COI under conditions when disease transmission is extremely high. Performance of the method is positively correlated with the MAF of the genotyped loci. COI estimates from existing SNP genotype datasets create a more detailed portrait of disease than analyses based simply on the number of polymorphic genotypes observed within samples. CONCLUSIONS:The capacity to reliably estimate COI from a genome-wide panel of SNP genotypes provides a potentially more accurate alternative to methods relying on PCR amplification of a small number of loci for estimating COI. This approach will also increase the number of applications of SNP genotype data, providing additional motivation to employ SNP barcodes for studies of disease epidemiology or control measure efficacy. The COIL program is available for download from GitHub, and users may also upload their SNP genotype data to a web interface for simple and efficient determination of sample COI.

Dataset Information

Methodology for single nucleotide polymorphism selection in promoter regions for clinical use. An example of its applicability.

Publications

Methodology for single nucleotide polymorphism selection in promoter regions for clinical use. An example of its applicability.

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