High concordance of bovine single nucleotide polymorphism genotypes generated using two independent genotyping strategies

Single nucleotide polymorphisms (SNPs) represent the most common form of DNA sequence variation in mammalian livestock genomes. While the past decade has witnessed major advances in SNP genotyping technologies, genotyping errors caused, in part, by the biochemistry underlying the genotyping platform used, can occur. These errors can distort project results and conclusions and can result in incorrect decisions in animal management and breeding programs; hence, SNP genotype calls must be accurate and reliable. In this study, 263 Bos spp. samples were genotyped commercially for a total of 16 SNPs. Of the total possible 4,208 SNP genotypes, 4,179 SNP genotypes were generated, yielding a genotype call rate of 99.31% (standard deviation?±?0.93%). Between 110 and 263 samples were subsequently re-genotyped by us for all 16 markers using a custom-designed SNP genotyping platform, and of the possible 3,819 genotypes a total of 3,768 genotypes were generated (98.70% genotype call rate, SD?±?1.89%). A total of 3,744 duplicate genotypes were generated for both genotyping platforms, and comparison of the genotype calls for both methods revealed 3,741 concordant SNP genotype call rates (99.92% SNP genotype concordance rate). These data indicate that both genotyping methods used can provide livestock geneticists with reliable, reproducible SNP genotypic data for in-depth statistical analysis.     

High Concordance of Bovine Single Nucleotide Polymorphism Genotypes Generated Using Two Independent Genotyping Strategies

Single nucleotide polymorphisms (SNPs) represent the most common form of DNA sequence variation in mammalian livestock genomes. While the past decade has witnessed major advances in SNP genotyping technologies, genotyping errors caused, in part, by the biochemistry underlying the genotyping platform used, can occur. These errors can distort project results and conclusions and can result in incorrect decisions in animal management and breeding programs; hence, SNP genotype calls must be accurate and reliable. In this study, 263 Bos spp. samples were genotyped commercially for a total of 16 SNPs. Of the total possible 4,208 SNP genotypes, 4,179 SNP genotypes were generated, yielding a genotype call rate of 99.31% (standard deviation ± 0.93%). Between 110 and 263 samples were subsequently re-genotyped by us for all 16 markers using a custom-designed SNP genotyping platform, and of the possible 3,819 genotypes a total of 3,768 genotypes were generated (98.70% genotype call rate, SD ± 1.89%). A total of 3,744 duplicate genotypes were generated for both genotyping platforms, and comparison of the genotype calls for both methods revealed 3,741 concordant SNP genotype call rates (99.92% SNP genotype concordance rate). These data indicate that both genotyping methods used can provide livestock geneticists with reliable, reproducible SNP genotypic data for in-depth statistical analysis.     

Universal SNP genotyping assay with fluorescence polarization detection

The degree of fluorescence polarization (FP) of a fluorescent molecule is a reflection of its molecular weight (Mr). FP is therefore a useful detection methodfor homogeneous assays in which the starting reagents and products differ significantly in Mr. We have previously shown that FP is a good detection method for the single-base extension and the 5'-nuclease assays. In this report, we describe a universal, optimized single-base extension assay for genotyping single nucleotide polymorphisms (SNPs). This assay, which we named the template-directed dye-terminator incorporation assay with fluorescence polarization detection (FP-TDI), uses four spectrally distinct dye terminators to achieve universal assay conditions. Even without optimization, approximately 70% of all SNP markers tested yielded robust assays. The addition of an E. coli ssDNA-binding protein just before the FP reading significantly increased FP values of the products and brought the success rate of FP-TDI assays up to 90%. Increasing the amount of dye terminators and reducing the number of thermal cycles in the single-base extension step of the assay increased the separation of the FP values benveen the products corresponding to different genotypes and improved the success rate of the assay to 100%. In this study the genomic DNA samples of 90 individuals were typed for a total of 38 FP-TDI assays (using both the sense and antisense TDI primers for 19 SNP markers). With the previously described modifications, the FP-TDI assay gave unambiguous genotyping data for all the samples tested in the 38 FP-TDI assays. When the genotypes determined by the FP-TDI and 5'-nuclease assays were compared, they were in 100% concordance for all experiments (a total of 3420 genotypes). The four-dye-terminator master mixture described here can be used for assaying any SNP marker and greatly simplifies the SNP genotyping assay design.     

High throughput SNP genotyping with two mini-sequencing assays

Single nucleotide polymorphisms (SNPs) are veryimportant markers that can be used in many areas such asevolutionary genetics [1], disease-susceptibility genes[2,3], personalized medicine and forensics. Only about20% of human polymorphisms are length polymorphisms,whereas about 80% of human polymorphisms areSNPs. Kruglyak et al. [4] reported that there were about11,000,000 SNPs in the world population. There are many kinds of SNP genotyping technology[5,6]: some are only suitable to low …     

FP-TDI SNP scoring by manual and statistical procedures: a study of error rates and types

For technologies that are commonly used in ordinary laboratories such as fluorescence-polarization detection with template-directed, dye-terminator incorporation (FP-TDI), SNP genotype scoring is usually done manually. Here we study rates of errors and missing genotypes obtained with this procedure. We also introduce three statistical genotype scoring methods to examine whether they form a viable alternative. Data consisted of eight SNPs typed in about 1400 individuals from 268 pedigrees. The statistical procedures performed better on several internal criteria, such as the number of Mendelian errors, and showed much higher agreement with discrepant genotypes re-scored by two raters. The best results were obtained with the statistical procedure that incorporated information about regularities in the error structure of the FP-TDI data. We estimated that there were about 1.6% more errors if genotypes were scored manually. About 0.6% of these errors could be explained by data manipulation errors, leaving 1% as the result of possible incorrect scoring. There were 3.3% more missing genotypes in the manual scoring due to errors in data manipulation (1.7%) and conservative scoring (1.6%).     

应用FP-TDI技术进行高通量单核苷酸多态分型

FP-TDI (fluorescence polarization template-directed dye-terminator incorporation）是一种操作简单、实验投入少、适于高通量反应的单核苷酸多态等位基因分型技术.使用两种评价分型图像质量的数值指标,可以有效地对分型结果进行评价,使该技术得到了改进.在此基础上优化了实验条件,并应用该技术,对人类基因组3号染色体上随机选取的337个单核苷酸多态性位点进行了高通量分型,反应的一次成功率达到59.94%.     

Family-based association tests for genomewide association scans

With millions of single-nucleotide polymorphisms (SNPs) identified and characterized, genomewide association studies have begun to identify susceptibility genes for complex traits and diseases. These studies involve the characterization and analysis of very-high-resolution SNP genotype data for hundreds or thousands of individuals. We describe a computationally efficient approach to testing association between SNPs and quantitative phenotypes, which can be applied to whole-genome association scans. In addition to observed genotypes, our approach allows estimation of missing genotypes, resulting in substantial increases in power when genotyping resources are limited. We estimate missing genotypes probabilistically using the Lander-Green or Elston-Stewart algorithms and combine high-resolution SNP genotypes for a subset of individuals in each pedigree with sparser marker data for the remaining individuals. We show that power is increased whenever phenotype information for ungenotyped individuals is included in analyses and that high-density genotyping of just three carefully selected individuals in a nuclear family can recover >90% of the information available if every individual were genotyped, for a fraction of the cost and experimental effort. To aid in study design, we evaluate the power of strategies that genotype different subsets of individuals in each pedigree and make recommendations about which individuals should be genotyped at a high density. To illustrate our method, we performed genomewide association analysis for 27 gene-expression phenotypes in 3-generation families (Centre d'Etude du Polymorphisme Humain pedigrees), in which genotypes for ~860,000 SNPs in 90 grandparents and parents are complemented by genotypes for ~6,700 SNPs in a total of 168 individuals. In addition to increasing the evidence of association at 15 previously identified cis-acting associated alleles, our genotype-inference algorithm allowed us to identify associated alleles at 4 cis-acting loci that were missed when analysis was restricted to individuals with the high-density SNP data. Our genotype-inference algorithm and the proposed association tests are implemented in software that is available for free.     

The TDI-FP assay in human Y chromosome SNP haplotyping

One of the many commercial technologies for genotyping single nucleotide polymorphisms (SNPs) is template direct dye-terminator incorporation with fluorescence-polarization (TDI-FP assay). It is a single-base extension assay followed by reading the fluorescence polarization values in an appropriate instrument. We have evaluated the suitability of the TDI-FP technique to detect haploid uniparentally inherited DNA polymorphisms on the nonrecombining portion of the Y chromosome. A sample of 47 individuals has been genotyped for 8 Y chromosome biallelic markers. The SNP typing was blindly duplicated by the denaturing high-performance liquid chromatography (DHPLC) technique for comparison. In the cases under examination the TDI-FP assay was able to resolve an allelic state fully. Such a result showed 100% concordance indicating how efficiently the TDI assay can be used to genotype Y chromosome DNA SNPs. However, a percentage of indeterminate genotypes remained unresolved by simple visual inspection: it varied from 0% to 11% depending on the SNP locus and on the success of amplification. This is consistent with previous findings. A maximum likelihood classificatory analysis allowed some of the indeterminate genotypes to be assigned and some potentially misclassified samples to be identified. Their percentage remains relatively high despite retyping and therefore alternative techniques for these noncompliant situations are required.     

Automated SNP genotype clustering algorithm to improve data completeness in high-throughput SNP genotyping datasets from custom arrays

High-throughput SNP genotyping platforms use automated genotype calling algorithms to assign genotypes. While these algorithms work efficiently for individual platforms, they are not compatible with other platforms, and have individual biases that result in missed genotype calls. Here we present data on the use of a second complementary SNP genotype clustering algorithm. The algorithm was originally designed for individual fluorescent SNP genotyping assays, and has been optimized to permit the clustering of large datasets generated from custom-designed Affymetrix SNP panels. In an analysis of data from a 3K array genotyped on 1,560 samples, the additional analysis increased the overall number of genotypes by over 45,000, significantly improving the completeness of the experimental data. This analysis suggests that the use of multiple genotype calling algorithms may be advisable in high-throughput SNP genotyping experiments. The software is written in Perl and is available from the corresponding author.     

Automated SNP Genotype Clustering Algorithm to Improve Data Completeness in High-Throughput SNP Genotyping Datasets from Custom Arrays

High-throughput SNP genotyping platforms use automated genotype calling algo- rithms to assign genotypes. While these algorithms work efficiently for individual platforms, they are not compatible with other platforms, and have individual biases that result in missed genotype calls. Here we present data on the use of a second complementary SNP genotype clustering algorithm. The algorithm was originally designed for individual fluorescent SNP genotyping assays, and has been opti- mized to permit the clustering of large datasets generated from custom-designed Affymetrix SNP panels. In an analysis of data from a 3K array genotyped on 1,560 samples, the additional analysis increased the overall number of genotypes by over 45,000, significantly improving the completeness of the experimental data. This analysis suggests that the use of multiple genotype calling algorithms may be ad- visable in high-throughput SNP genotyping experiments. The software is written in Perl and is available from the corresponding author.     

Automated SNP Genotype Clustering Algorithm to Improve Data Completeness in High-Throughput SNP Genotyping Datasets from Custom Arrays

High-throughput SNP genotyping platforms use automated genotype calling algo- rithms to assign genotypes. While these algorithms work efficiently for individual platforms, they are not compatible with other platforms, and have individual biases that result in missed genotype calls. Here we present data on the use of a second complementary SNP genotype clustering algorithm. The algorithm was originally designed for individual fluorescent SNP genotyping assays, and has been opti- mized to permit the clustering of large datasets generated from custom-designed Affymetrix SNP panels. In an analysis of data from a 3K array genotyped on 1,560 samples, the additional analysis increased the overall number of genotypes by over 45,000, significantly improving the completeness of the experimental data. This analysis suggests that the use of multiple genotype calling algorithms may be ad- visable in high-throughput SNP genotyping experiments. The software is written in Perl and is available from the corresponding author.     

Single-nucleotide-polymorphism genotyping of Coxiella burnetii during a Q fever outbreak in The Netherlands

Coxiella burnetii is the etiological agent of Q fever. Currently, the Netherlands is facing the largest Q fever epidemic ever, with almost 4,000 notified human cases. Although the presence of a hypervirulent strain is hypothesized, epidemiological evidence, such as the animal reservoir(s) and genotype of the C. burnetii strain(s) involved, is still lacking. We developed a single-nucleotide-polymorphism (SNP) genotyping assay directly applicable to clinical samples. Ten discriminatory SNPs were carefully selected and detected by real-time PCR. SNP genotyping appeared to be highly suitable for discrimination of C. burnetii strains and easy to perform with clinical samples. With this new method, we show that the Dutch outbreak is caused by at least 5 different C. burnetii genotypes. SNP typing of 14 human samples from the outbreak revealed the presence of 3 dissimilar genotypes. Two genotypes were also present in livestock at 9 farms in the outbreak area. SNP analyses of bulk milk from 5 other farms, commercial cow milk, and cow colostrum revealed 2 additional genotypes that were not detected in humans. SNP genotyping data from clinical samples clearly demonstrate that at least 5 different C. burnetii genotypes are involved in the Dutch outbreak.     

<Emphasis Type="Italic">In silico</Emphasis> genotyping of the maize nested association mapping population

Nested Association Mapping (NAM) has been proposed as a means to combine the power of linkage mapping with the resolution of association mapping. It is enabled through sequencing or array genotyping of parental inbred lines while using low-cost, low-density genotyping technologies for their segregating progenies. For purposes of data analyses of NAM populations, parental genotypes at a large number of Single Nucleotide Polymorphic (SNP) loci need to be projected to their segregating progeny. Herein we demonstrate how approximately 0.5 million SNPs that have been genotyped in 26 parental lines of the publicly available maize NAM population can be projected onto their segregating progeny using only 1,106 SNP loci that have been genotyped in both the parents and their 5,000 progeny. The challenge is to estimate both the genotype and genetic location of the parental SNP genotypes in segregating progeny. Both challenges were met by estimating their expected genotypic values conditional on observed flanking markers through the use of both physical and linkage maps. About 90%, of 500,000 genotyped SNPs from the maize HapMap project, were assigned linkage map positions using linear interpolation between the maize Accessioned Gold Path (AGP) and NAM linkage maps. Of these, almost 70% provided high probability estimates of genotypes in almost 5,000 recombinant inbred lines.     

A family-based likelihood ratio test for general pedigree structures that allows for genotyping error and missing data

The purpose of this work is the development of a family-based association test that allows for random genotyping errors and missing data and makes use of information on affected and unaffected pedigree members. We derive the conditional likelihood functions of the general nuclear family for the following scenarios: complete parental genotype data and no genotyping errors; only one genotyped parent and no genotyping errors; no parental genotype data and no genotyping errors; and no parental genotype data with genotyping errors. We find maximum likelihood estimates of the marker locus parameters, including the penetrances and population genotype frequencies under the null hypothesis that all penetrance values are equal and under the alternative hypothesis. We then compute the likelihood ratio test. We perform simulations to assess the adequacy of the central chi-square distribution approximation when the null hypothesis is true. We also perform simulations to compare the power of the TDT and this likelihood-based method. Finally, we apply our method to 23 SNPs genotyped in nuclear families from a recently published study of idiopathic scoliosis (IS). Our simulations suggest that this likelihood ratio test statistic follows a central chi-square distribution with 1 degree of freedom under the null hypothesis, even in the presence of missing data and genotyping errors. The power comparison shows that this likelihood ratio test is more powerful than the original TDT for the simulations considered. For the IS data, the marker rs7843033 shows the most significant evidence for our method (p = 0.0003), which is consistent with a previous report, which found rs7843033 to be the 2nd most significant TDTae p value among a set of 23 SNPs.     

ALG: automated genotype calling of Luminex assays

Single nucleotide polymorphisms (SNPs) are the most commonly used polymorphic markers in genetics studies. Among the different platforms for SNP genotyping, Luminex is one of the less exploited mainly due to the lack of a robust (semi-automated and replicable) freely available genotype calling software. Here we describe a clustering algorithm that provides automated SNP calls for Luminex genotyping assays. We genotyped 3 SNPs in a cohort of 330 childhood leukemia patients, 200 parents of patient and 325 healthy individuals and used the Automated Luminex Genotyping (ALG) algorithm for SNP calling. ALG genotypes were called twice to test for reproducibility and were compared to sequencing data to test for accuracy. Globally, this analysis demonstrates the accuracy (99.6%) of the method, its reproducibility (99.8%) and the low level of no genotyping calls (3.4%). The high efficiency of the method proves that ALG is a suitable alternative to the current commercial software. ALG is semi-automated, and provides numerical measures of confidence for each SNP called, as well as an effective graphical plot. Moreover ALG can be used either through a graphical user interface, requiring no specific informatics knowledge, or through command line with access to the open source code. The ALG software has been implemented in R and is freely available for non-commercial use either at http://alg.sourceforge.net or by request to mathieu.bourgey@umontreal.ca.     

SNP genotyping on a genome-wide amplified DOP-PCR template

With the increasing demand for higher throughput single nucleotide polymorphism (SNP) genotyping, the quantity of genomic DNA often falls short of the number of assays required. We investigated the use of degenerate oligonucleotide primed polymerase chain reaction (DOP-PCR) to generate a template for our SNP genotyping methodology of fluorescence polarization template-directed dye-terminator incorporation detection. DOP-PCR employs a degenerate primer (5′-CCGACTCGAGNNNNNNATGTGG-3′) to produce non-specific uniform amplification of DNA. This approach has been successfully applied to microsatellite genotyping. We compared genotyping of DOP-PCR-amplified genomic DNA to genomic DNA as a template. Results were analyzed with respect to feasibility, allele loss of alleles, genotyping accuracy and storage conditions in a high-throughput genotyping environment. DOP-PCR yielded overall satisfactory results, with a certain loss in accuracy and quality of the genotype assignments. Accuracy and quality of genotypes generated from the DOP-PCR template also depended on storage conditions. Adding carrier DNA to a final concentration of 10 ng/µl improved results. In conclusion, we have successfully used DOP-PCR to amplify our genomic DNA collection for subsequent SNP genotyping as a standard process.     

Evaluating the effects of imputation on the power, coverage, and cost efficiency of genome-wide SNP platforms

Genotype imputation is potentially a zero-cost method for bridging gaps in coverage and power between genotyping platforms. Here, we quantify these gains in power and coverage by using 1,376 population controls that are from the 1958 British Birth Cohort and were genotyped by the Wellcome Trust Case-Control Consortium with the Illumina HumanHap 550 and Affymetrix SNP Array 5.0 platforms. Approximately 50% of genotypes at single-nucleotide polymorphisms (SNPs) exclusively on the HumanHap 550 can be accurately imputed from direct genotypes on the SNP Array 5.0 or Illumina HumanHap 300. This roughly halves differences in coverage and power between the platforms. When the relative cost of currently available genome-wide SNP platforms is accounted for, and finances are limited but sample size is not, the highest-powered strategy in European populations is to genotype a larger number of individuals with the HumanHap 300 platform and carry out imputation. Platforms consisting of around 1 million SNPs offer poor cost efficiency for SNP association in European populations.     

Sequence-based genotyping for marker discovery and co-dominant scoring in germplasm and populations

Conventional marker-based genotyping platforms are widely available, but not without their limitations. In this context, we developed Sequence-Based Genotyping (SBG), a technology for simultaneous marker discovery and co-dominant scoring, using next-generation sequencing. SBG offers users several advantages including a generic sample preparation method, a highly robust genome complexity reduction strategy to facilitate de novo marker discovery across entire genomes, and a uniform bioinformatics workflow strategy to achieve genotyping goals tailored to individual species, regardless of the availability of a reference sequence. The most distinguishing features of this technology are the ability to genotype any population structure, regardless whether parental data is included, and the ability to co-dominantly score SNP markers segregating in populations. To demonstrate the capabilities of SBG, we performed marker discovery and genotyping in Arabidopsis thaliana and lettuce, two plant species of diverse genetic complexity and backgrounds. Initially we obtained 1,409 SNPs for arabidopsis, and 5,583 SNPs for lettuce. Further filtering of the SNP dataset produced over 1,000 high quality SNP markers for each species. We obtained a genotyping rate of 201.2 genotypes/SNP and 58.3 genotypes/SNP for arabidopsis (n?=?222 samples) and lettuce (n?=?87 samples), respectively. Linkage mapping using these SNPs resulted in stable map configurations. We have therefore shown that the SBG approach presented provides users with the utmost flexibility in garnering high quality markers that can be directly used for genotyping and downstream applications. Until advances and costs will allow for routine whole-genome sequencing of populations, we expect that sequence-based genotyping technologies such as SBG will be essential for genotyping of model and non-model genomes alike.     

SNP genotyping in melons: genetic variation, population structure, and linkage disequilibrium

Novel sequencing technologies were recently used to generate sequences from multiple melon (Cucumis melo L.) genotypes, enabling the in silico identification of large single nucleotide polymorphism (SNP) collections. In order to optimize the use of these markers, SNP validation and large-scale genotyping are necessary. In this paper, we present the first validated design for a genotyping array with 768 SNPs that are evenly distributed throughout the melon genome. This customized Illumina GoldenGate assay was used to genotype a collection of 74 accessions, representing most of the botanical groups of the species. Of the assayed loci, 91 % were successfully genotyped. The array provided a large number of polymorphic SNPs within and across accessions. This set of SNPs detected high levels of variation in accessions from this crop’s center of origin as well as from several other areas of melon diversification. Allele distribution throughout the genome revealed regions that distinguished between the two main groups of cultivated accessions (inodorus and cantalupensis). Population structure analysis showed a subdivision into five subpopulations, reflecting the history of the crop. A considerably low level of LD was detected, which decayed rapidly within a few kilobases. Our results show that the GoldenGate assay can be used successfully for high-throughput SNP genotyping in melon. Since many of the genotyped accessions are currently being used as the parents of breeding populations in various programs, this set of mapped markers could be used for future mapping and breeding efforts.     

Kinetic FP-TDI assay for SNP allele frequency determination

Strategies for identifying genetic risk factors in complex diseases by association studies require the comparison of allele frequencies of numerous SNPs between affected and control populations. Theoretically, hundreds of thousands of SNP markers across the genome will have to be genotyped in these studies. Genotyping SNPs one sample at a time is extremely costly and time consuming. To streamline whole genome association studies, some have proposed to screen SNPs by pooling the DNA samples initially for allele frequency determination and perform individual genotyping only when there is a significant discrepancy in allele frequencies between the affected and control populations. Here we describe a new method for determining the allele frequency of SNPs in pooled DNA samples using a two-color primer extension assay with real-time monitoring of fluorescence polarization (named kinetic FP-TDI assay). By comparing the ratio of the rate of incorporation of the two allele-specific dye-terminators, one can calculate the relative amounts of each allele in the pooled sample. The accuracy of allele frequency determination with pooled samples is within 3.3 +/- 0.8% of that determined by genotyping individual samples that make up the pool.