Development of new IL28B genotyping method using Invader Plus assay

IL28B polymorphism is associated with the response to pegylated interferon-α with ribavirin (PEG-IFN-α/RBV) treatment in chronic hepatitis C patients. As a genotyping assay for IL28B single nucleotide polymorphisms (SNPs) in clinical practice, the Invader Plus assay was developed. The accuracy, intra-assay, inter-assay precision, and the limit of detection of the Invader Plus assay were evaluated. Two SNPs (rs8099917 and rs12979860) associated with IL28B were genotyped by the Invader Plus and TaqMan assay in 512 Japanese patients. In comparison with direct sequencing, the Invader Plus assay showed 99% accuracy in rs8099917 and 100% accuracy in rs12979860. Intra-assay and inter-assay precision were sufficient to use in clinical practice and the detection limit was 1ngDNA/assay. Genotyping by rs8099917 showed that 361 (71%), 144 (28%) and seven (1%) of the patients were major homozygous, heterozygous and minor homozygous types, respectively. Five of the 512 cases (1%) had haplotype differences, but none showed differences between the two genotyping methods. For patients with HCV genotype 1, the prevalence of responders in the major homozygous type was 83.3%, and that of non-responders in the minor heterozygous/homozygous type was 72.5%. A convenient IL28B genotyping method using the Invader Plus assay could be useful to predict the treatment outcome in clinical practice.     

A comparison of simple sequence repeat and single nucleotide polymorphism marker technologies for the genotypic analysis of maize (<Emphasis Type="Italic">Zea mays</Emphasis> L.)

We report on the comparative utilities of simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers for characterizing maize germplasm in terms of their informativeness, levels of missing data, repeatability and the ability to detect expected alleles in hybrids and DNA pools. Two different SNP chemistries were compared; single-base extension detected by Sequenom MassARRAY, and invasive cleavage detected by Invader chemistry with PCR. A total of 58 maize inbreds and four hybrids were genotyped with 80 SSR markers, 69 Invader SNP markers and 118 MassARRAY SNP markers, with 64 SNP loci being common to the two SNP marker chemistries. Average expected heterozygosity values were 0.62 for SSRs, 0.43 for SNPs (pre-selected for their high level of polymorphism) and 0.63 for the underlying sequence haplotypes. All individual SNP markers within the same set of sequences had an average expected heterozygosity value of 0.26. SNP marker data had more than a fourfold lower level of missing data (2.1-3.1%) compared with SSRs (13.8%). Data repeatability was higher for SNPs (98.1% for MassARRAY SNPs and 99.3% for Invader) than for SSRs (91.7%). Parental alleles were observed in hybrid genotypes in 97.0% of the cases for MassARRAY SNPs, 95.5% for Invader SNPs and 81.9% for SSRs. In pooled samples with mixtures of alleles, SSRs, MassARRAY SNPs and Invader SNPs were equally capable of detecting alleles at mid to high frequencies. However, at low frequencies, alleles were least likely to be detected using Invader SNP markers, and this technology had the highest level of missing data. Collectively, these results showed that SNP technologies can provide increased marker data quality and quantity compared with SSRs. The relative loss in polymorphism compared with SSRs can be compensated by increasing SNP numbers and by using SNP haplotypes. Determining the most appropriate SNP chemistry will be dependent upon matching the technical features of the method within the context of application, particularly in consideration of whether genotypic samples will be pooled or assayed individually.     

Comparison of four flow cytometric SNP detection assays and their use in plant improvement

Single nucleotide polymorphisms (SNPs) are attractive DNA markers due to their abundance and potential for use in automated high-throughput genotyping. Numerous SNP genotyping assays have been developed, but it is unclear which assays are best suited and most efficient for various types of plant improvement research. The objective of this study was to compare the accuracy, efficiency, and cost of four SNP genotyping assays: single-base extension (SBE), allele-specific primer extension (ASPE), oligonucleotide ligation (OL), and direct hybridization (DH). All four assay methods used the same Luminex 100 flow cytometer platform. Fifty-eight F₂-derived soybean [Glycine max (L.) Merr.] lines from a cross between inbred lines G99-G725 and N00-3350 were genotyped at four SNPs. SBE and ASPE clearly differentiated between the two homozygotes and the heterozygote at each SNP. Results were in agreement with those identified using the SNaPshot minisequencing assay as a control. In contrast, the OL and DH assays were unable to differentiate between genotypes at some of the SNPs. However, when the cost per data point for the four different assays was compared, the cost of OL and DH was only about 70% of that for SBE, with DH requiring the least time of the four assays. On the basis of cost and labor, ASPE is more cost-effective and simpler than SBE, and would therefore be a good method for genetic mapping and diversity studies which require a large number of markers and a high level of multiplexing. DH appears to be the most economical assay for marker-assisted selection, though optimization for DH would be required for some SNP markers.     

Universal,robust, highly quantitative SNP allele frequency measurement in DNA pools

Detecting alleles that confer small increments in susceptibility to disease will require large-scale allelic association studies of single-nucleotide polymorphisms (SNPs) in candidate, or positional candidate, genes. However, current genotyping technologies are one to two orders of magnitude too expensive to permit the analysis of thousands of SNPs in large samples. We have developed and thoroughly validated a highly accurate protocol for SNP allele frequency estimation in DNA pools based upon the SNaPshot (Applied Biosystems) chemistry adaptation of primer extension. Using this assay, we were able to estimate the difference in allele frequencies between pooled cases and controls (Delta) with a mean error of 0.01. Moreover, when we genotyped seven different SNPs in a single multiplex reaction, the results were similar, with a mean error for Delta of 0.008. The assay performed well for alleles of low frequency alleles (f approximately 0.05) and was accurate even with relatively poor quality DNA template extracted from mouthwashes. Our assay conditions are generalisable, universal, robust and, therefore, for the first time, permit high-throughput association analysis at a realistic cost.     

A single multiplex PCR and SNaPshot minisequencing reaction of 42 SNPs to classify admixture populations into mitochondrial DNA haplogroups

SNaPshot minisequencing reaction is in increasing use because of its fast detection of many polymorphisms in a single assay. In this work we described a highly sensitive single nucleotide polymorphisms (SNPs) typing method with detection of 42 mitochondrial DNA (mtDNA) SNPs in a single PCR and SNaPshot multiplex reaction, in order to allow haplogroup classification in Latin American admixture population. We validated the panel typing 160 Brazilian individuals. Complete SNP profiles were obtained from 10 pg of total DNA. We conclude that it is possible to build and genotype more than forty mtDNA SNPs in a single multiplex PCR and SNaPshot reaction, with sensitivity and reliability, resolving haplogroup classification in admixture populations.     

Adaptation of a low-cost medium-throughput genotyping system for ovine prion protein gene polymorphims associated with scrapie

Resistance and susceptibility to scrapie in sheep have been associated with SNPs located at codons 136, 154 and 171 of the prion protein (PRNP) gene. Many countries have sheep breeding programs selecting for resistance to scrapie based on the genotyping of these SNPs. We adapted a fast and robust method for genotyping sheep flocks for these polymorphisms, with reduced costs. Ninety-six samples were genotyped using an adapted SNaPshot PRNP assay, and the results were checked by resequencing. The results showed 100% concordance, using a method that reduces genotyping costs by 70%, by reducing reagent concentrations in the three main steps of the assay (amplicon purification, base extension and final cleanup). This cost reduction should contribute to the development of selection criteria based on PRNP genotyping in countries where assay costs are an important limiting factor.     

Screening and scanning of single nucleotide polymorphisms in the pig melanocortin 1 receptor gene (MC1R) by pyrosequencing.

The increasing interest in the discovery and characterization of single nucleotide polymorphisms (SNPs) emphasis the need for high-throughput and cost effective scoring methods. Pyrosequencing is a novel method for screening SNPs. In this study we examine breed specific SNPs in the pig melanocortin 1 receptor gene (MC1R), some causing coat color phenotypes. A total of fifteen pigs representing eight breeds and crosses were analyzed by pyrosequencing. In addition to nine previously known SNPs, we also detected one new missense mutation by pyrosequencing. We here show that the SNPs were readily scored using standard reaction conditions. Insertions as well as substitutions were unambiguously detected and all genotypes were resolved in terms of homo- and heterozygozity.     

Rapid SNP allele frequency determination in genomic DNA pools by pyrosequencing

Individual genotyping of single nucleotide polymorphisms (SNPs) remains expensive, especially for linkage disequilibrium mapping strategies involving high-throughput SNP genotyping. On one hand, current methods may suit scientific and laboratory needs in regard to accuracy, reproducibility/robustness, and large-scale application. On the other hand, a cheaper and less time-consuming alternative to individual genotyping is the use of SNP allelefrequencies determined in DNA pools. We have developed an accurate and reproducible protocol for allele frequency determination using Pyrosequencing technology in large genomic DNA pools (374 individuals). The measured correlation (R2) in large DNA pools was 0.980. In the context of disease-associated SNPs studies, we compared the allele frequencies between the disease (e.g., type 2 diabetes and obesity) and control groups detected by either individual genotyping or Pyrosequencing of DNA pools. In large pools, the variation between the two methods was 1.5 +/- 0.9%. It may be concluded that the allele frequency determination protocol could reliably detect over 4% differences between populations. The method is economical in regard to amounts of DNA, PCR, and primer extension reagents required. Furthermore, it allows the rapid determination of allelefrequency differences in case/control groups for association studies and susceptibility gene discovery in complex diseases.     

Assessing allele frequencies of single nucleotide polymorphisms in DNA pools by pyrosequencing technology

Single nucleotide polymorphism (SNP) association studies searching for differences in allele frequencies between cases and controls have been widely used for genetic analysis. Individual genotyping is prohibitively expensive in large sample sizes. Pooling of samples provides the obvious advantage of higher throughput and lower cost. Here we report our results with the analysis of SNP allele frequencies in DNA pools using Pyrosequencing technology. For seven different SNPs, we observed a mean difference of 1.1 +/- 0.6% between allele frequencies determined in two different DNA pools (n = 150 cases and 150 controls) compared to individually genotyped samples.     

Accuracy of genotyping for single nucleotide polymorphisms by a microarray-based single nucleotide polymorphism typing method involving hybridization of short allele-specific oligonucleotides.

Advances in technologies for identifying genetic polymorphisms rapidly and accurately will dramatically accelerate the discovery of disease-related genes. Among a variety of newly described methods for rapid typing of single-nucleotide polymorphisms (SNPs), gene detection using DNA microarrays is gradually achieving widespread use. This method involves the use of short (11- to 13-mer) allele-specific oligonucleotides. This method allows simultaneous analysis of many SNPs in DNAs from a large number of individuals, in a single experiment. In this work, we evaluated the accuracy of a new microarray-based short allele-specific oligonucleotide (ASO) hybridization method. There is a 96-well formatted array on a single plate, in which up to 256 spots are included in each well. Fluorescent probes for our experiments were produced by multiplex PCR amplification often target SNP-containing regions. We genotyped 192 individuals across a panel of ten single base variations, which included an insertion/deletion polymorphism. For comparison, we genotyped the same individuals for the same SNPs by the method of single-base extension with fluorescence detection. The typing accuracies of the microarray-based PCR-ASO and single-base extension methods were calculated as 99.9% and 99.1%, respectively, on the basis of genotyping results determined by direct sequencing. We conclude that the microarray-based hybridization method using short ASO probes represents a potential breakthrough technology for typing large numbers of SNPs rapidly and efficiently.     

Detection, imputation, and association analysis of small deletions and null alleles on oligonucleotide arrays

Copy-number variation (CNV) is a major contributor to human genetic variation. Recently, CNV associations with human disease have been reported. Many genome-wide association (GWA) studies in complex diseases have been performed with sets of biallelic single-nucleotide polymorphisms (SNPs), but the available CNV methods are still limited. We present a new method (TriTyper) that can infer genotypes in case-control data sets for deletion CNVs, or SNPs with an extra, untyped allele at a high-resolution single SNP level. By accounting for linkage disequilibrium (LD), as well as intensity data, calling accuracy is improved. Analysis of 3102 unrelated individuals with European descent, genotyped with Illumina Infinium BeadChips, resulted in the identification of 1880 SNPs with a common untyped allele, and these SNPs are in strong LD with neighboring biallelic SNPs. Simulations indicate our method has superior power to detect associations compared to biallelic SNPs that are in LD with these SNPs, yet without increasing type I errors, as shown in a GWA analysis in celiac disease. Genotypes for 1204 triallelic SNPs could be fully imputed, with only biallelic-genotype calls, permitting association analysis of these SNPs in many published data sets. We estimate that 682 of the 1655 unique loci reflect deletions; this is on average 99 deletions per individual, four times greater than those detected by other methods. Whereas the identified loci are strongly enriched for known deletions, 61% have not been reported before. Genes overlapping with these loci more often have paralogs (p = 0.006) and biologically interact with fewer genes than expected (p = 0.004).     

A Flexible and Accurate Genotype Imputation Method for the Next Generation of Genome-Wide Association Studies

Genotype imputation methods are now being widely used in the analysis of genome-wide association studies. Most imputation analyses to date have used the HapMap as a reference dataset, but new reference panels (such as controls genotyped on multiple SNP chips and densely typed samples from the 1,000 Genomes Project) will soon allow a broader range of SNPs to be imputed with higher accuracy, thereby increasing power. We describe a genotype imputation method (IMPUTE version 2) that is designed to address the challenges presented by these new datasets. The main innovation of our approach is a flexible modelling framework that increases accuracy and combines information across multiple reference panels while remaining computationally feasible. We find that IMPUTE v2 attains higher accuracy than other methods when the HapMap provides the sole reference panel, but that the size of the panel constrains the improvements that can be made. We also find that imputation accuracy can be greatly enhanced by expanding the reference panel to contain thousands of chromosomes and that IMPUTE v2 outperforms other methods in this setting at both rare and common SNPs, with overall error rates that are 15%–20% lower than those of the closest competing method. One particularly challenging aspect of next-generation association studies is to integrate information across multiple reference panels genotyped on different sets of SNPs; we show that our approach to this problem has practical advantages over other suggested solutions.     

A simple method using PyrosequencingTM to identify de novo SNPs in pooled DNA samples

A practical way to reduce the cost of surveying single-nucleotide polymorphism (SNP) in a large number of individuals is to measure the allele frequencies in pooled DNA samples. Pyrosequencing(TM) has been frequently used for this application because signals generated by this approach are proportional to the amount of DNA templates. The Pyrosequencing(TM) pyrogram is determined by the dispensing order of dNTPs, which is usually designed based on the known SNPs to avoid asynchronistic extensions of heterozygous sequences. Therefore, utilizing the pyrogram signals to identify de novo SNPs in DNA pools has never been undertook. Here, in this study we developed an algorithm to address this issue. With the sequence and pyrogram of the wild-type allele known in advance, we could use the pyrogram obtained from the pooled DNA sample to predict the sequence of the unknown mutant allele (de novo SNP) and estimate its allele frequency. Both computational simulation and experimental Pyrosequencing(TM) test results suggested that our method performs well. The web interface of our method is available at http://life.nctu.edu.tw/～yslin/PSM/.     

Alternative ecotilling protocol for rapid, cost-effective single-nucleotide polymorphism discovery and genotyping in rice (Oryza sativa L.)

Ecotilling is a high-throughput method of discovery and analysis of single-nucleotide polymorphism (SNP) variations in natural populations, but it requires a substantial investment in sophisticated equipment, costly reagents, and specialized software programs and implementation of several time-consuming steps that limit its use in laboratories with modest financial resources. Moreover, labeling efficiency of PCR primers with fluorescent dyes during Ecotilling can be reduced by unwanted exonuclease activity of single strand-specific nucleases. A new alternative protocol involving a simplified gel system, unlabeled primers, DNA staining after single strand-specific nuclease digestion, and standard gel data analysis was optimized to address these constraints. Using this alternative protocol, we successfully identified four new SNPs verified by sequencing in a collection of 57 diverse rice accessions along with 2 previously reported SNPs in a 922-bp DNA region from thealk gene. An SNP cluster containing a deletion within a 472-bp fragment of thewaxy gene was also characterized. In addition, 4 previously reported SNPs in thealk andwaxy genes were faithfully genotyped among the 57 accessions based on comparisons with sequencing results. Associations between the genotyped SNPs and amylose class and starch gelatinization temperature were as anticipated. These results, along with detailed time and cost comparisons between the 2 methods, suggest that alternative Ecotilling is a simple and reproducible method for SNP discovery and genotyping in rice that leads to substantial savings in equipment, reagents, software, and time compared with the standard Ecotilling procedure. Approved for publication by the Director of the Louisiana Agricultural Experiment Station as paper No. 06-14-0237.     

Multiplex minisequencing screening for PTC genotype associated with bitter taste perception

Sensitivity to phenylthiocarbamide (PTC) has a bimodal distribution pattern and the genotype of the TAS2R38 gene, which is composed of combinations of three coding single nucleotide polymorphisms (SNPs), p.A49P (c.145G>C), p.V262A (c.785T>C) and p.I296 V (c.886A>G), determines the ability or inability to taste PTC. In this study, we developed a tool for genotyping of these SNPs in the TAS2R38 gene using SNaPshot minisequencing and investigated the accuracy of the tool in 100 subjects who were genotyped by Sanger sequencing. The minor allele frequencies of the three SNPs were 0.39, and these genotypes corresponded to those determined by direct sequencing. In conclusion, we successfully developed a precise and rapid genetic tool for analysis of PTC genotype associated with bitter taste perception.     

Genomic Selection Using Low-Density Marker Panels

Genomic selection (GS) using high-density single-nucleotide polymorphisms (SNPs) is promising to improve response to selection in populations that are under artificial selection. High-density SNP genotyping of all selection candidates each generation, however, may not be cost effective. Smaller panels with SNPs that show strong associations with phenotype can be used, but this may require separate SNPs for each trait and each population. As an alternative, we propose to use a panel of evenly spaced low-density SNPs across the genome to estimate genome-assisted breeding values of selection candidates in pedigreed populations. The principle of this approach is to utilize cosegregation information from low-density SNPs to track effects of high-density SNP alleles within families. Simulations were used to analyze the loss of accuracy of estimated breeding values from using evenly spaced and selected SNP panels compared to using all high-density SNPs in a Bayesian analysis. Forward stepwise selection and a Bayesian approach were used to select SNPs. Loss of accuracy was nearly independent of the number of simulated quantitative trait loci (QTL) with evenly spaced SNPs, but increased with number of QTL for the selected SNP panels. Loss of accuracy with evenly spaced SNPs increased steadily over generations but was constant when the smaller number individuals that are selected for breeding each generation were also genotyped using the high-density SNP panel. With equal numbers of low-density SNPs, panels with SNPs selected on the basis of the Bayesian approach had the smallest loss in accuracy for a single trait, but a panel with evenly spaced SNPs at 10 cM was only slightly worse, whereas a panel with SNPs selected by forward stepwise selection was inferior. Panels with evenly spaced SNPs can, however, be used across traits and populations and their performance is independent of the number of QTL affecting the trait and of the methods used to estimate effects in the training data and are, therefore, preferred for broad applications in pedigreed populations under artificial selection.     

Multiplex automated primer extension analysis: simultaneous genotyping of several polymorphisms.

Accurate and fast genotyping of single nucleotide polymorphisms (SNPs) is of significant scientific importance for linkage and association studies. We report here an automated fluorescent method we call multiplex automated primer extension analysis (MAPA) that can accurately genotype multiple known SNPs simultaneously. This is achieved by substantially improving a commercially available protocol (SNaPshot). This protocol relies on the extension of a primer that ends one nucleotide 5'of a given SNP with fluorescent dideoxy-NTPs (minisequencing), followed by analysis on an ABI PRisMS 377 Semi-Automated DNA Sequencer Our modification works by multiplexing the initial reaction that produces the DNA template for primer extension and/or multiplexing several primers (corresponding to several SNPs) in the same primer extension reaction. Then, we run each multiplexed reaction on a single gel lane. We demonstrate that MAPA can be used to genotype up to four SNPs simultaneously, even in compound heterozygote samples, with complete accuracy (based on concordance with sequencing results). We also show that primer design, unlike the DNA template purification method, can significantly affect genotyping accuracy, and we suggest useful guidelines for quick optimization.     

Estimation of single nucleotide polymorphism allele frequency in DNA pools by using Pyrosequencing

Positional cloning of genes underlying complex diseases, such as type 2 diabetes mellitus (T2DM), typically follows a two-tiered process in which a chromosomal region is first identified by genome-wide linkage scanning, followed by association analyses using densely spaced single nucleotide polymorphic markers to identify the causal variant(s). The success of genome-wide single nucleotide polymorphism (SNP) detection has resulted in a vast number of potential markers available for use in the construction of such dense SNP maps. However, the cost of genotyping large numbers of SNPs in appropriately sized samples is nearly prohibitive. We have explored pooled DNA genotyping as a means of identifying differences in allele frequency between pools of individuals with T2DM and unaffected controls by using Pyrosequencing technology. We found that allele frequencies in pooled DNA were strongly correlated with those in individuals (r=0.99, P<0.0001) across a wide range of allele frequencies (0.02-0.50). We further investigated the sensitivity of this method to detect allele frequency differences between contrived pools, also over a wide range of allele frequencies. We found that Pyrosequencing was able to detect an allele frequency difference of less than 2% between pools, indicating that this method may be sensitive enough for use in association studies involving complex diseases where a small difference in allele frequency between cases and controls is expected.     

Large-scale genotyping of complex DNA

Genetic studies aimed at understanding the molecular basis of complex human phenotypes require the genotyping of many thousands of single-nucleotide polymorphisms (SNPs) across large numbers of individuals. Public efforts have so far identified over two million common human SNPs; however, the scoring of these SNPs is labor-intensive and requires a substantial amount of automation. Here we describe a simple but effective approach, termed whole-genome sampling analysis (WGSA), for genotyping thousands of SNPs simultaneously in a complex DNA sample without locus-specific primers or automation. Our method amplifies highly reproducible fractions of the genome across multiple DNA samples and calls genotypes at >99% accuracy. We rapidly genotyped 14,548 SNPs in three different human populations and identified a subset of them with significant allele frequency differences between groups. We also determined the ancestral allele for 8,386 SNPs by genotyping chimpanzee and gorilla DNA. WGSA is highly scaleable and enables the creation of ultrahigh density SNP maps for use in genetic studies.