Simple Single Nucleotide Polymorphism Research Articles

Next‐generation sequencing: academic overkill or high‐resolution routine blood group genotyping?

Blood group genotyping (BGG) has been in routine clinical practice ever since the molecular determination of blood groups was achieved, during the early to mid 1990s. These early methods were dependent on allele‐specific PCR to detect simple single nucleotide polymorphisms (SNPs) responsible for blood group expression. As our knowledge regarding the molecular background of blood groups advanced, so did the numbers of SNPs requiring detection which necessitated the switch from allele‐specific PCR to array‐based technology, notably slide and bead‐based approaches. All these methods thus described are totally dependent on the predefined genetic basis of each SNP. Hybrid blood group genes (as found in RH, ABO and MNS systems) are difficult to define by all of these aforementioned techniques. With the arrival of cheap next‐generation sequencing (NGS) approaches in the past 5 years, we have conducted long‐range PCR (LR‐PCR) coupled with NGS determination of the major blood group genes. By analysis of these data using an Ion Torrent Personal Genome Machine™ (PGM™), it is readily apparent that NGS can highly effectively be applied with high resolution to blood grouping at costs no more than current array‐based platforms. However, the complexity of the data obtained need careful filtering for effective clinical utilization, but provides useful insight on the evolution of blood groups and their environmental impacts which will be of undoubted value as an academic exercise, but of minimal cost (if any) to the original testing.

SplitMEM: a graphical algorithm for pan-genome analysis with suffix skips.

Genomics is expanding from a single reference per species paradigm into a more comprehensive pan-genome approach that analyzes multiple individuals together. A compressed de Bruijn graph is a sophisticated data structure for representing the genomes of entire populations. It robustly encodes shared segments, simple single-nucleotide polymorphisms and complex structural variations far beyond what can be represented in a collection of linear sequences alone. We explore deep topological relationships between suffix trees and compressed de Bruijn graphs and introduce an algorithm, splitMEM, that directly constructs the compressed de Bruijn graph in time and space linear to the total number of genomes for a given maximum genome size. We introduce suffix skips to traverse several suffix links simultaneously and use them to efficiently decompose maximal exact matches into graph nodes. We demonstrate the utility of splitMEM by analyzing the nine-strain pan-genome of Bacillus anthracis and up to 62 strains of Escherichia coli, revealing their core-genome properties.

Development and Validation of Single‐nucleotide Polymorphism Markers in the Pacific Oyster, Crassostrea gigas, Using High‐resolution Melting Analysis

AbstractHigh‐resolution melting (HRM) has been considered as a fast and simple single‐nucleotide polymorphism (SNP) scanning and genotyping method for identifying differences in the shapes of melting curves between different genotypes. Fifty‐six SNPs were developed in the Pacific oyster, Crassostrea gigas by mining expressed sequence tags database, using the HRM method. The frequency of the SNPs was estimated at 1 per 113 bp of contig sequences. Analysis of segregation in a full‐sib family showed that 28 SNPs were polymorphic, with 15 in accordance to expected Mendelian ratios. Linkage grouping of the 28 markers resulted in six linkage groups. The combined power of exclusion of the 42 SNPs, which conformed to Hardy–Weinberg equilibrium, was greater than 99.98%, while the average polymorphic information content was 0.2223. The simulation results showed that the success rate of parentage analysis could be 97% with the 42 SNPs. These SNPs will be useful for pedigree analysis, association studies, and marker‐associated selection of this species.

Single nucleotide polymorphism detection method by temperature-gradient affinity chromatography using a single-stranded oligo-DNA coupled column

We developed an affinity chromatographic method for simple single nucleotide polymorphism (SNP) detection by use of a single-stranded DNA-coupled column and temperature gradient elution, utilizing the difference in thermal stability between hybridized double-stranded DNAs with and without mismatched base-pairs in the course of temperature gradient elution. We studied experimentally and theoretically the elution behavior of DNAs with and without SNPs in this chromatography and proposed a numerical calculation method based on a thermodynamic dissociation model. The effects of the column volume, flow rate of eluent and heating rate of the column on elution profiles were clarified. For designing DNA ligands, mismatched base-pair positions favorable for detection of SNPs were also explored by use of hybridized DNAs coding a part of the human TP53 gene.

DNA hybridization in nanostructural molecular assemblies enables detection of gene mutations without a fluorescent probe.

We have developed a simple single nucleotide polymorphisms (SNPs) analysis utilizing DNA hybridization in nanostructural molecular assemblies. The novel technique enables the detection of a single-base mismatch in a DNA sequence without a fluorescent probe. This report describes for the first time that DNA hybridization occurs in the nanostructural molecular assemblies (termed reverse micelles) formed in an organic medium. The restricted nanospace in the reverse micelles amplifies the differences in the hybridization rate between mismatched and perfectly matched DNA probes. For a model system, we hybridized a 20-mer based on the p53 gene sequence to 20-mer complementary oligonucleotides with various types of mismatches. Without any DNA labeling or electrochemical apparatus, we successfully detected the various oligonucleotide mismatches by simply measuring the UV absorbance at 260 nm.