Toward High Utilization of Heterogeneous Computing Resources in SNP Detection

Single nucleotide polymorphisms (SNPs) constitute the most common types of genetic variations in the human genome. A number of SNPs have been linked to the development of life threatening diseases including cancer, cardiovascular diseases and neurodegenerative diseases. The ability for ultrasensitive and accurate detection of low abundant disease-related SNPs in bodily fluids (e.g. blood, serum, etc.) holds a significant value in the development of non-invasive future biodiagnostic tools. Over the past two decades, nanomaterials have been utilized in a myriad of biosensing applications due to their ability of detecting extremely low quantities of biologically important biomarkers with high sensitivity and accuracy. Of particular interest is the application of such technologies in the detection of SNPs. The use of various nanomaterials, coupled with different powerful signal amplification strategies, has paved the way for a new generation of ultrasensitive SNP biodiagnostic assays. Over the past few years, several ultrasensitive SNP biosensors capable of detecting specific targets down to the ultra-low regimes (ca. aM and below) and therefore holding great promises for early clinical diagnosis of diseases have been developed. This mini review will highlight some of the most recent, significant advances in nanomaterial-based ultrasensitive SNP sensing technologies capable of detecting specific targets on the attomolar (10(-18) M) regime or below. In particular, the design of novel, powerful signal amplification strategies that hold the key to the ultrasensitivity is highlighted.

DNA sequence alignment and single-nucleotide polymorphism (SNP) detection are two important tasks in genomics research. A common genome resequencing analysis workflow is to first perform sequence alignment and then detect SNPs among the aligned sequences. In practice, the performance bottleneck in this workflow is usually the intermediate result I/O due to the separation of the two components, especially when the in-memory computation has been accelerated, e.g., by graphics processors. To address this bottleneck, we propose to integrate the two tasks tightly so as to eliminate the I/O of intermediate results in the workflow. Specifically, we make the following three changes for the tight integration: (1) we adopt a partition-based approach so that the external sorting of alignment results, which was required for SNP detection, is eliminated; (2) we perform customized compression on alignment results to reduce memory footprint; and (3) we move the computation of a global matrix from SNP detection to sequence alignment to save a file scan. We have developed a GPU-accelerated system that tightly integrates sequence alignment and SNP detection. Our results with human genome data sets show that our GPU-acceleration of individual components in the traditional workflow improves the overall performance by 18 times and that the tight integration further improves the performance of the GPU-accelerated system by 2.3 times.

Detection of nucleic acids and single nucleotide polymorphisms (SNPs) is of pivotal importance in biology and medicine. Given that the biological effect of SNPs often is enhanced in combination with other SNPs, multiplexed SNP detection is desirable. We show proof of concept of the multiplexed detection of SNPs based on the template-directed native chemical ligation (NCL) of PNA-probes carrying a metal tag allowing detection using ICP-MS. For the detection of ssDNA oligonucleotides (30 bases), two probes, one carrying the metal tag and a second one carrying biotin for purification, are covalently ligated. The methodological limit of detection is of 29 pM with RSD of 6.7% at 50 pM (n=5). Detection of SNPs is performed with the combination of two sets of reporter probes. The first probe set targets the SNP, and its yield is compared with a second set of probes targeting a neighboring sequence. The assay was used to simultaneously differentiate between alleles of three SNPs at 5-nM concentration.

Alzheimer's disease (AD) is one of the most serious neurodegenerative diseases in the world and has a strong genetic predisposition. At present, there is still no effective method for the early diagnosis and prevention of AD. Accumulating evidence shows the association of several loci with AD risk, such as apolipoprotein E (APOE) and translocase of outer mitochondrial membrane 40 (TOMM40). However, for routine disease diagnosis in clinics, genotype detection methods based on gene sequencing technology are time-consuming and excessively costly. Thus, in this study, we developed a high-sensitivity, low-cost, and convenient single nucleotide polymorphism(SNP) detection assay method based on allele-specific quantitative polymerase chain reaction (AS-qPCR) technology, which can be used to determine the SNP genotype in APOE and TOMM40. A total of 40 patients were recruited from the outpatient department of the memory clinic of Dongzhimen Hospital, Beijing University of Chinese Medicine. The SNP detection assay method includes three steps. First, positive plasmids with different genotypes (TT/CC/TC) in APOE rs429358, rs7412, and TOMM40 rs11556505 were prepared. Second, 3'-T/3'-C primers were designed to amplify these positive plasmids for each SNP site. Finally, we calculated the log10 of the copy number ratio for each positive plasmid, and the genotype interpretation interval was established. Based on this method, we investigated whether the SNPs in 40 patients could be accurately calculated using AS-qPCR technology. The accuracy of SNP detection was verified by PCR-Pooling sequencing. The results showed that SNP genotypes assessed by AS-qPCR technology corresponded perfectly to the results obtained by conventional DNA sequencing. We have developed a genotype detection method for AD based on AS-qPCR, which can be performed easily, rapidly, accurately, and at low cost. The method will contribute to the early diagnosis of patients with late-onset Alzheimer's and the detection of large clinical samples in the future.

Assessment of genetic diversity, detection of strain-specific single nucleotide polymorphisms and identification of the Bangladesh and Vietnam strain of Channa striata by PCR-RFLP analysis of the mitochondrial COI gene fragment

BackgroundAmplicon re-sequencing based on the automated Sanger method remains popular for detection of single nucleotide polymorphisms (SNPs) and insertion-deletion polymorphisms (InDels) for a spectrum of genetics applications. However, existing software tools for detecting intra-individual SNPs and InDels in direct amplicon sequencing of diploid samples are insufficient in analyzing single traces and their accuracy is still limited.ResultsWe developed a novel computation tool, named DiSNPindel, to improve the detection of intra-individual SNPs and InDels in direct amplicon sequencing of a diploid. Neither reference sequence nor additional sample was required. Using two real datasets, we demonstrated the usefulness of DiSNPindel in its ability to improve largely the true SNP and InDel discovery rates and reduce largely the missed and false positive rates as compared with existing detection methods.ConclusionsThe software DiSNPindel presented here provides an efficient tool for intra-individual SNP and InDel detection in diploid amplicon sequencing. It will also be useful for identification of DNA variations in expressed sequence tag (EST) re-sequencing.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-015-0790-y) contains supplementary material, which is available to authorized users.

Progress in single nucleotide polymorphism (SNP) detection technologies has provided information for SNP-based studies, such as identification of candidate genes for the complex genetic diseases, pharmacogenetic analysis, drug development, population genetics, evolutionary studies, and forensic investigations. SNP detection is performed by many methods, including hybridization, allele-specific polymerase chain reaction (PCR), primer extension, oligonucleotide ligation, direct DNA sequencing, and endonuclease cleavage. Each of these methods has its specific advantages and disadvantages. Here we introduce the PCR-restriction fragment length polymorphism (RFLP) method, which has certain advantages over many other techniques used for analysis of SNPs. The PCR-RFLP method allows very rapid, simple, and inexpensive detection of point mutations within the sequences of PCR products. The mutation is discriminated by the specific restriction endonuclease and is identified by gel electrophoresis followed by staining with ethidium bromide. This convenient and simple method is useful in a small basic research study.

The detection of single nucleotide polymorphisms (SNPs) is of great significance in the early diagnosis of diseases and the rational use of drugs. Thus, a novel biosensor based on the quenching effect of fluorescence-embedded SYBR Green I (SG) dye and graphene oxide (GO) was introduced in this study. The probe DNA forms a double helix structure with perfectly complementary DNA (pcDNA) and 15 single-base mismatch DNA (smDNA) respectively. SG is highly intercalated with perfectly complementary dsDNA (pc-dsDNA) and exhibits strong fluorescence emission. Single-base mismatch dsDNA (SNPs) has a loose double-stranded structure and exhibits poor SG intercalation and low fluorescence sensing. At this time, the sensor still showed poor SNP discrimination. GO has a strong effect on single-stranded DNA (ssDNA), which can reduce the fluorescence response of probe DNA and eliminate background interference. And competitively combined with ssDNA in SNPs, quenching the fluorescence of SG/SNP, while the fluorescence value of pc-dsDNA was retained, increasing the signal-to-noise ratio. At this time, the sensor has obtained excellent SNP resolution. Different SNPs detect different intensities of fluorescence in the near-infrared region to evaluate the sensor's identification of SNPs. The experimental parameters such as incubation time, incubation temperature and salt concentration were optimized. Under optimal conditions, 1 nM DNA with 0–10 nM linear range and differentiate 5% SNP were achieved. The detection method does not require labeling, is low cost, simple in operation, exhibits high SNP discrimination and can be distinguished by SNP at room temperature.

409 Background: The X-ray repair cross-complementing protein 1 (XRCC1) gene plays an important role in DNA damage repair; and the R194W and R399Q single nucleotide polymorphisms (SNPs) are associated with attenuated DNA repair activity. Our objective was to determine whether XRCC1 SNPs were associated with response to neoadjuvant chemoradiation therapy (CRT) in rectal cancer patients. Methods: We conducted a prospective multicenter phase II trial to investigate the effect of additional chemotherapy with a longer CRT-to-surgery interval on treatment response in patients with rectal cancer. Paired normal and rectal cancer tissues were prospectively collected from enrolled patients (n=110). DNA was extracted from normal rectal mucosa and analyzed for XRCC1 R194W and R399Q by polymerase chain reaction and sequencing. Each SNP was compared to response to CRT. Response to CRT was determined by a central pathologist. Results: Of the 110 patients, 25% (n=27) achieved a pathologic complete response (pCR). We examined the XRCC1 R194W SNP and observed that the allelic frequency of patients with the R/R genotype was 84% (n=92), the R/W genotype was 14% (n=16), the W/W genotype was 1% (n=2). By Fisher's Exact test, patients harboring either the R/W or W/W genotype, had a significantly higher rate of pCR compared to patients with the R/R genotype (44% vs. 21%, respectively; p=0.04). We then examined the R399Q SNP and observed that the allelic frequency of patients with the R/R genotype was 34% (n=37), the R/Q genotype was 49% (n=54), and the Q/Q genotype was 17% (n=19). In contrast, the detection of XRCC1 R399Q SNPs was not associated with pCR. Conclusions: We demonstrate that XRCC1 R194W SNP is associated with increased rate of pCR in our prospective multi-center trial. Although the detection of XRCC1 R399Q SNP is not associated with pCR, the detection of XRCC1 SNPs that predict treatment response may help identify patients who are unlikely to respond to CRT and therefore may potentially avoid treatment-associated morbidities. No significant financial relationships to disclose.

DNA single-nucleotide polymorphism (SNP) detection has attracted much attention due to mutation-related diseases. Various fluorescence methods for SNP detection have been proposed and many are already in use. However, fluorescence enhancement for signal-on SNP identification without label modification still remains a challenge. Here, we find that the abasic site (AP site) in a DNA duplex can be developed as a binding pocket favorable for the occurrence of the excited-state intramolecular proton transfer (ESIPT) of a 3-hydroxyflavone, fisetin, which is used as a proof of concept for effective SNP identification. Fisetin binding at the AP site is highly selective for target thymine or cytosine facing the AP site by observation of a drastic increase in the ESIPT emission band. In addition, the target recognition selectivity based on this ESIPT process is not affected by flanking bases of the AP site. The binding selectivity of fisetin at the AP site is also confirmed by measurements of fluorescence resonance energy transfer, emission lifetime and DNA melting. The fluorescent signal-on sensing for SNP based on this fluorophore is substantially advantageous over the previously used fluorophores such as the AP site-specific signal-off organic ligands with a similar fluorescing mechanism before and after binding to DNA with hydrogen bonding interaction. We expect that this approach will be employed to develop a practical SNP detection method by locating an AP site toward a target and employing an ESIPT probe as readout.

BackgroundIntegration of genomic variation with phenotypic information is an effective approach for uncovering genotype-phenotype associations. This requires an accurate identification of the different types of variation in individual genomes.ResultsWe report the integration of the whole genome sequence of a single Holstein Friesian bull with data from single nucleotide polymorphism (SNP) and comparative genomic hybridization (CGH) array technologies to determine a comprehensive spectrum of genomic variation. The performance of resequencing SNP detection was assessed by combining SNPs that were identified to be either in identity by descent (IBD) or in copy number variation (CNV) with results from SNP array genotyping. Coding insertions and deletions (indels) were found to be enriched for size in multiples of 3 and were located near the N- and C-termini of proteins. For larger indels, a combination of split-read and read-pair approaches proved to be complementary in finding different signatures. CNVs were identified on the basis of the depth of sequenced reads, and by using SNP and CGH arrays.ConclusionsOur results provide high resolution mapping of diverse classes of genomic variation in an individual bovine genome and demonstrate that structural variation surpasses sequence variation as the main component of genomic variability. Better accuracy of SNP detection was achieved with little loss of sensitivity when algorithms that implemented mapping quality were used. IBD regions were found to be instrumental for calculating resequencing SNP accuracy, while SNP detection within CNVs tended to be less reliable. CNV discovery was affected dramatically by platform resolution and coverage biases. The combined data for this study showed that at a moderate level of sequencing coverage, an ensemble of platforms and tools can be applied together to maximize the accurate detection of sequence and structural variants.

SNP (single nucleotide polymorphism) is a popular tool for the study of genetic diversity, evolution, and other areas. Therefore, it is necessary to develop a convenient, utility, robust, rapid, and open source detecting-SNP tool for all researchers. Since the detection of SNPs needs special software and series steps including alignment, detection, analysis and present, the study of SNPs is limited for nonprofessional users. CsSNP (Comparative segments SNP, http://biodb.sdau.edu.cn/cssnp/ ) is a freely available web tool based on the Blat, Blast, and Perl programs to detect comparative segments SNPs and to show the detail information of SNPs. The results are filtered and presented in the statistics figure and a Gbrowse map. This platform contains the reference genomic sequences and coding sequences of 60 plant species, and also provides new opportunities for the users to detect SNPs easily. CsSNP is provided a convenient tool for nonprofessional users to find comparative segments SNPs in their own sequences, and give the users the information and the analysis of SNPs, and display these data in a dynamic map. It provides a new method to detect SNPs and may accelerate related studies.

Detection of point mutations or single nucleotide polymorphisms (SNPs) is important in relation to disease susceptibility or detection in pathogens of mutations determining drug resistance or host range. There is an emergent need for rapid detection methods amenable to point-of-care applications. The purpose of this study was to reduce to practice a novel method for SNP detection and to demonstrate that this technology can be used downstream of nucleic acid amplification. The authors used a model system to develop an oligonucleotide-based SNP detection system on nitrocellulose lateral flow strips. To optimize the assay they used cloned sequences of the herpes simplex virus-1 (HSV-1) DNA polymerase gene into which they introduced a point mutation. The assay system uses chimeric polymerase chain reaction (PCR) primers that incorporate hexameric repeat tags (hexapet tags). The chimeric sequences allow capture of amplified products to predefined positions on a lateral flow strip. These sequences have minimal cross-reactivity and allow specific hybridization-based capture of the PCR products at room temperature onto lateral flow strips that have been striped with complementary hexapet tags. The allele-specific amplification was carried out with both mutant and wild-type primer sets present in the PCR mix (competitive format). The resulting PCR products carried a hexapet tag that corresponded with either a wild-type or mutant sequence. The lateral flow strips are dropped into the PCR reaction tube, and mutant sequence and wild-type sequences diffuse along the strip and are captured at the corresponding position on the strip. A red line indicative of a positive reaction is visible after 1 minute. Unlike other systems that require separate reactions and strips for each target sequence, this system allows multiplex PCR reactions and multiplex detection on a single strip or other suitable substrates. Unambiguous visual discrimination of a point mutation under room temperature hybridization conditions was achieved with this model system in 10 minutes after PCR. The authors have developed a capture-based hybridization method for the detection and discrimination of HSV-1 DNA polymerase genes that contain a single nucleotide change. It has been demonstrated that the hexapet oligonucleotides can be adapted for hybridization on the lateral flow strip platform for discrimination of SNPs. This is the first step in demonstrating SNP detection on lateral flow using the hexapet oligonucleotide capture system. It is anticipated that this novel system can be widely used in point-of-care settings.

Next-generation sequencing technologies have made it possible to sequence targeted regions of the human genome in hundreds of individuals. Deep sequencing represents a powerful approach for the discovery of the complete spectrum of DNA sequence variants in functionally important genomic intervals. Current methods for single nucleotide polymorphism (SNP) detection are designed to detect SNPs from single individual sequence data sets. Here, we describe a novel method SNIP-Seq (single nucleotide polymorphism identification from population sequence data) that leverages sequence data from a population of individuals to detect SNPs and assign genotypes to individuals. To evaluate our method, we utilized sequence data from a 200-kilobase (kb) region on chromosome 9p21 of the human genome. This region was sequenced in 48 individuals (five sequenced in duplicate) using the Illumina GA platform. Using this data set, we demonstrate that our method is highly accurate for detecting variants and can filter out false SNPs that are attributable to sequencing errors. The concordance of sequencing-based genotype assignments between duplicate samples was 98.8%. The 200-kb region was independently sequenced to a high depth of coverage using two sequence pools containing the 48 individuals. Many of the novel SNPs identified by SNIP-Seq from the individual sequencing were validated by the pooled sequencing data and were subsequently confirmed by Sanger sequencing. We estimate that SNIP-Seq achieves a low false-positive rate of approximately 2%, improving upon the higher false-positive rate for existing methods that do not utilize population sequence data. Collectively, these results suggest that analysis of population sequencing data is a powerful approach for the accurate detection of SNPs and the assignment of genotypes to individual samples.

Single nucleotide polymorphisms (SNPs) are essential parameters in molecular diagnostics and can be used for the early detection and clinical prognosis in various diseases. Available methods for SNP detection are still labor-intensive and require a complex laboratory infrastructure, which are not suitable for the usage in resource-limited settings. Thus, there is an urgent need for a simple, reliable and rapid approach. In this paper we modified the previously developed competitive reporter monitored amplification (CMA) technique for the detection of resistance mediating SNPs in Mycobacterium tuberculosis complex (MTBC) strains. As a proof-of-principle for the application of the CMA-based SNP assay in routine molecular tuberculosis diagnostic, we show that the assay recognizes resistance mediating SNPs for rifampicin, isoniazid and ethambutol from either isolated DNA or heat inactivated M. tuberculosis cell cultures. The CMA-based SNP assay can identify the most prevalent resistance mediating mutations in the genes rpoB, katG, embB, and the promotor region of inhA within one hour.