Single-nucleotide polymorphism identification and genotyping in Camelina sativa.
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ABSTRACT:
SUBMITTER: Singh R
PROVIDER: S-EPMC4300397 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Establishing low-cost, high-throughput, simple, and accurate single nucleotide polymorphism (SNP) genotyping techniques is beneficial for understanding the intrinsic relationship between individual genetic variations and their biological functions on a genomic scale. Here, a straightforward and reliable single-molecule approach is demonstrated for precise SNP authentication by directly measuring the fluctuations in electrical signals in an electronic circuit, which is fabricated from a high-gain field-effect silicon nanowire decorated with a single hairpin DNA, in the presence of different target DNAs. By simply comparing the proportion difference of a probe-target duplex structure throughout the process, this study implements allele-specific and accurate SNP detection. These results are supported by the statistical analyses of different dynamic parameters such as the mean lifetime and the unwinding probability of the duplex conformation. In comparison with conventional polymerase chain reaction and optical methods, this convenient and label-free method is complementary to existing optical methods and also shows several advantages, such as simple operation and no requirement for fluorescent labeling, thus promising a futuristic route toward the next-generation genotyping technique.
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Project description:Single-nucleotide polymorphisms (SNPs) are the most abundant type of genetic variations; they provide the genetic fingerprint of individuals and are essential for genetic biomarker discoveries. Accurate detection of SNPs is of great significance for disease prevention, diagnosis and prognosis, and for prediction of drug response and clinical outcomes in patients. Nevertheless, conventional SNP genotyping methods are still limited by insufficient accuracy or labor-, time-, and resource-intensive procedures. Microfluidics has been increasingly utilized to improve efficiency; however, the currently available microfluidic genotyping systems still have shortcomings in accuracy, sensitivity, throughput and multiplexing capability. To address these challenges, we developed a multi-step SNP genotyping microfluidic device, which performs single-base extension of SNP specific primers and solid-phase purification of the extension products on a temperature-controlled chip. The products are ready for immediate detection by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), providing identification of the alleles at the target loci. The integrated device enables efficient and automated operation, while maintaining the high accuracy and sensitivity provided by MS. The multiplex genotyping capability was validated by performing rapid, accurate and simultaneous detection of 4 loci on a synthetic template. The microfluidic device has the potential to perform automatic, accurate, quantitative and high-throughput assays covering a broad spectrum of applications in biological and clinical research, drug development and forensics.
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Project description:We investigated the application of an oligonucleotide microarray to (i) specifically detect Cryptosporidium spp., (ii) differentiate between closely related C. parvum isolates and Cryptosporidium species, and (iii) differentiate between principle genotypes known to infect humans. A microarray of 68 capture probes targeting seven single-nucleotide polymorphisms (SNPs) within a 190-bp region of the hsp70 gene of Cryptosporidium parvum was constructed. Labeled hsp70 targets were generated by PCR with biotin- or Cy3-labeled primers. Hybridization conditions were optimized for hybridization time, temperature, and salt concentration. Two genotype I C. parvum isolates (TU502 and UG502), two C. parvum genotype II isolates (Iowa and GCH1), and DNAs from 22 non-Cryptosporidium sp. organisms were used to test method specificity. Only DNAs from C. parvum isolates produced labeled amplicons that could be hybridized to and detected on the array. Hybridization patterns between genotypes were visually distinct, but identification of SNPs required statistical analysis of the signal intensity data. The results indicated that correct mismatch discrimination could be achieved for all seven SNPs for the UG502 isolate, five of seven SNPs for the TU502 isolate, and six of seven SNPs for both the Iowa and GCH1 isolates. Even without perfect mismatch discrimination, the microarray method unambiguously distinguished between genotype I and genotype II isolates and demonstrated the potential to differentiate between other isolates and species on a single microarray. This method may provide a powerful new tool for water utilities and public health officials for assessing point and nonpoint source contamination of water supplies.
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Project description:Single nucleotide polymorphisms (SNPs) have emerged as the genetic marker of choice for mapping disease loci and candidate gene association studies, because of their high density and relatively even distribution in the human genomes. There is a need for systems allowing medium multiplexing (ten to hundreds of SNPs) with high throughput, which can efficiently and cost-effectively generate genotypes for a very large sample set (thousands of individuals). Methods that are flexible, fast, accurate and cost-effective are urgently needed. This is also important for those who work on high throughput genotyping in non-model systems where off-the-shelf assays are not available and a flexible platform is needed.We demonstrate the use of a nanofluidic Integrated Fluidic Circuit (IFC) - based genotyping system for medium-throughput multiplexing known as the Dynamic Array, by genotyping 994 individual human DNA samples on 47 different SNP assays, using nanoliter volumes of reagents. Call rates of greater than 99.5% and call accuracies of greater than 99.8% were achieved from our study, which demonstrates that this is a formidable genotyping platform. The experimental set up is very simple, with a time-to-result for each sample of about 3 hours.Our results demonstrate that the Dynamic Array is an excellent genotyping system for medium-throughput multiplexing (30-300 SNPs), which is simple to use and combines rapid throughput with excellent call rates, high concordance and low cost. The exceptional call rates and call accuracy obtained may be of particular interest to those working on validation and replication of genome- wide- association (GWA) studies.
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Project description:Single-nucleotide polymorphisms (SNPs) constitute the bulk of human genetic variation and provide excellent markers to identify genetic factors contributing to complex disease susceptibility. A rapid, sensitive, and inexpensive assay is important for large-scale SNP scoring. Here we report the development of a multiplex SNP detection system using silicon chips coated to create a thin-film optical biosensor. Allele-discriminating, aldehyde-labeled oligonucleotides are arrayed and covalently attached to a hydrazinederivatized chip surface. Target sequences (e.g., PCR amplicons) then are hybridized in the presence of a mixture of biotinylated detector probes, one for each SNP, and a thermostable DNA ligase. After a stringent wash (0.01 M NaOH), ligation of biotinylated detector probes to perfectly matched capture oligomers is visualized as a color change on the chip surface (gold to blue/purple) after brief incubations with an anti-biotin IgG-horseradish peroxidase conjugate and a precipitable horseradish peroxidase substrate. Testing of PCR fragments is completed in 30-40 min. Up to several hundred SNPs can be assayed on a 36-mm2 chip, and SNP scoring can be done by eye or with a simple digital-camera system. This assay is extremely robust, exhibits high sensitivity and specificity, and is format-flexible and economical. In studies of mutations associated with risk for venous thrombosis and genotyping/haplotyping of African-American samples, we document high-fidelity analysis with 0 misassignments in 500 assays performed in duplicate.
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Project description:Identification of Anopheles gambiae s.s. and Anopheles arabiensis from field-collected Anopheles gambiae s.l. is often necessary in basic and applied research, and in operational control programmes. The currently accepted method involves use of standard polymerase chain reaction amplification of ribosomal DNA (rDNA) from the 3' 28S to 5' intergenic spacer region of the genome, and visual confirmation of amplicons of predicted size on agarose gels, after electrophoresis. This report describes development and evaluation of an automated, quantitative PCR method based upon TaqMan single nucleotide polymorphism (SNP) genotyping.Standard PCR, and TaqMan SNP genotyping with newly designed primers and fluorophore-labeled probes hybridizing to sequences of complementary rDNA specific for either An. gambiae s.s. or An. arabiensis, were conducted in three experiments involving field-collected An. gambiae s.l. from western Kenya, and defined laboratory strains. DNA extraction was from a single leg, sonicated for five minutes in buffer in wells of 96-well PCR plates.TaqMan SNP genotyping showed a reaction success rate, sensitivity, and species specificity comparable to that of standard PCR. In an extensive field study, only 29 of 3,041 (0.95%) were determined to be hybrids by TaqMan (i.e., having rDNA sequences from both species), however, all but one were An. arabiensis by standard PCR, suggesting an acceptably low (ca. 1%) error rate for TaqMan genotyping in mistakenly identifying species hybrids.TaqMan SNP genotyping proved to be a sensitive and rapid method for identification of An. gambiae s.l. and An. arabiensis, with a high success rate, specific results, and congruence with the standard PCR method.
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Project description:BACKGROUND:The September 11, 2001 attacks on the World Trade Center and the Pentagon increased the concern about the potential for terrorist attacks on many vulnerable sectors of the US, including agriculture. The concentrated nature of crops, easily obtainable biological agents, and highly detrimental impacts make agroterrorism a potential threat. Although procedures for an effective criminal investigation and attribution following such an attack are available, important enhancements are still needed, one of which is the capability for fine discrimination among pathogen strains. The purpose of this study was to develop a molecular typing assay for use in a forensic investigation, using Wheat streak mosaic virus (WSMV) as a model plant virus. METHOD:This genotyping technique utilizes single base primer extension to generate a genetic fingerprint. Fifteen single nucleotide polymorphisms (SNPs) within the coat protein and helper component-protease genes were selected as the genetic markers for this assay. Assay optimization and sensitivity testing was conducted using synthetic targets. WSMV strains and field isolates were collected from regions around the world and used to evaluate the assay for discrimination. The assay specificity was tested against a panel of near-neighbors consisting of genetic and environmental near-neighbors. RESULT:Each WSMV strain or field isolate tested produced a unique SNP fingerprint, with the exception of three isolates collected within the same geographic location that produced indistinguishable fingerprints. The results were consistent among replicates, demonstrating the reproducibility of the assay. No SNP fingerprints were generated from organisms included in the near-neighbor panel, suggesting the assay is specific for WSMV. Using synthetic targets, a complete profile could be generated from as low as 7.15 fmoles of cDNA. CONCLUSION:The molecular typing method presented is one tool that could be incorporated into the forensic science tool box after a thorough validation study. This method incorporates molecular biology techniques that are already well established in research and diagnostic laboratories, allowing for an easy introduction of this method into existing laboratories. KEYWORDS:single nucleotide polymorphisms, genotyping, plant pathology, viruses, microbial forensics, Single base primer extension, SNaPshot Multiplex Kit.
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Project description:Typing of Mycobacterium avium subspecies paratuberculosis strains presents a challenge, since they are genetically monomorphic and traditional molecular techniques have limited discriminatory power. The recent advances and availability of whole-genome sequencing have extended possibilities for the characterization of Mycobacterium avium subspecies paratuberculosis, and whole-genome sequencing can provide a phylogenetic context to facilitate global epidemiology studies. In this study, we developed a single nucleotide polymorphism (SNP) assay based on PCR and restriction enzyme digestion or sequencing of the amplified product. The SNP analysis was performed using genome sequence data from 133 Mycobacterium avium subspecies paratuberculosis isolates with different genotypes from 8 different host species and 17 distinct geographic regions around the world. A total of 28,402 SNPs were identified among all of the isolates. The minimum number of SNPs required to distinguish between all of the 133 genomes was 93 and between only the type C isolates was 41. To reduce the number of SNPs and PCRs required, we adopted an approach based on sequential detection of SNPs and a decision tree. By the analysis of 14 SNPs Mycobacterium avium subspecies paratuberculosis isolates can be characterized within 14 phylogenetic groups with a higher discriminatory power than mycobacterial interspersed repetitive unit-variable number tandem repeat assay and other typing methods. Continuous updating of genome sequences is needed in order to better characterize new phylogenetic groups and SNP profiles. The novel SNP assay is a discriminative, simple, reproducible method and requires only basic laboratory equipment for the large-scale global typing of Mycobacterium avium subspecies paratuberculosis isolates.
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Project description:Single nucleotide polymorphisms (SNPs) are indispensable in such applications as association mapping and construction of high-density genetic maps. These applications usually require genotyping of thousands of SNPs in a large number of individuals. Although a number of SNP genotyping assays are available, most of them are designed for SNP genotyping in diploid individuals. Here, we demonstrate that the Illumina GoldenGate assay could be used for SNP genotyping of homozygous tetraploid and hexaploid wheat lines. Genotyping reactions could be carried out directly on genomic DNA without the necessity of preliminary PCR amplification. A total of 53 tetraploid and 38 hexaploid homozygous wheat lines were genotyped at 96 SNP loci. The genotyping error rate estimated after removal of low-quality data was 0 and 1% for tetraploid and hexaploid wheat, respectively. Developed SNP genotyping assays were shown to be useful for genotyping wheat cultivars. This study demonstrated that the GoldenGate assay is a very efficient tool for high-throughput genotyping of polyploid wheat, opening new possibilities for the analysis of genetic variation in wheat and dissection of genetic basis of complex traits using association mapping approach.
| S-EPMC2715469 | biostudies-literature
Project description:BackgroundThe identification of copy number aberration in the human genome is an important area in cancer research. We develop a model for determining genomic copy numbers using high-density single nucleotide polymorphism genotyping microarrays. The method is based on a Bayesian spatial normal mixture model with an unknown number of components corresponding to true copy numbers. A reversible jump Markov chain Monte Carlo algorithm is used to implement the model and perform posterior inference.ResultsThe performance of the algorithm is examined on both simulated and real cancer data, and it is compared with the popular CNAG algorithm for copy number detection.ConclusionsWe demonstrate that our Bayesian mixture model performs at least as well as the hidden Markov model based CNAG algorithm and in certain cases does better. One of the added advantages of our method is the flexibility of modeling normal cell contamination in tumor samples.
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