DNA base-calling from a nanopore using a Viterbi algorithm

Nanopore-based DNA sequencing is the most promising third-generation sequencing method. It has superior read length, speed, and sample requirements compared with state-of-the-art second-generation methods. However, base-calling still presents substantial difficulty because the resolution of the technique is limited compared with the measured signal/noise ratio. Here we demonstrate a method to decode 3-bp-resolution nanopore electrical measurements into a DNA sequence using a Hidden Markov model. This method shows tremendous potential for accuracy (~98%), even with a poor signal/noise ratio.     

A genotype calling algorithm for affymetrix SNP arrays

MOTIVATION: A classification algorithm, based on a multi-chip, multi-SNP approach is proposed for Affymetrix SNP arrays. Current procedures for calling genotypes on SNP arrays process all the features associated with one chip and one SNP at a time. Using a large training sample where the genotype labels are known, we develop a supervised learning algorithm to obtain more accurate classification results on new data. The method we propose, RLMM, is based on a robustly fitted, linear model and uses the Mahalanobis distance for classification. The chip-to-chip non-biological variance is reduced through normalization. This model-based algorithm captures the similarities across genotype groups and probes, as well as across thousands of SNPs for accurate classification. In this paper, we apply RLMM to Affymetrix 100 K SNP array data, present classification results and compare them with genotype calls obtained from the Affymetrix procedure DM, as well as to the publicly available genotype calls from the HapMap project.     

A multi-array multi-SNP genotyping algorithm for Affymetrix SNP microarrays

MOTIVATION: Modern strategies for mapping disease loci require efficient genotyping of a large number of known polymorphic sites in the genome. The sensitive and high-throughput nature of hybridization-based DNA microarray technology provides an ideal platform for such an application by interrogating up to hundreds of thousands of single nucleotide polymorphisms (SNPs) in a single assay. Similar to the development of expression arrays, these genotyping arrays pose many data analytic challenges that are often platform specific. Affymetrix SNP arrays, e.g. use multiple sets of short oligonucleotide probes for each known SNP, and require effective statistical methods to combine these probe intensities in order to generate reliable and accurate genotype calls. RESULTS: We developed an integrated multi-SNP, multi-array genotype calling algorithm for Affymetrix SNP arrays, MAMS, that combines single-array multi-SNP (SAMS) and multi-array, single-SNP (MASS) calls to improve the accuracy of genotype calls, without the need for training data or computation-intensive normalization procedures as in other multi-array methods. The algorithm uses resampling techniques and model-based clustering to derive single array based genotype calls, which are subsequently refined by competitive genotype calls based on (MASS) clustering. The resampling scheme caps computation for single-array analysis and hence is readily scalable, important in view of expanding numbers of SNPs per array. The MASS update is designed to improve calls for atypical SNPs, harboring allele-imbalanced binding affinities, that are difficult to genotype without information from other arrays. Using a publicly available data set of HapMap samples from Affymetrix, and independent calls by alternative genotyping methods from the HapMap project, we show that our approach performs competitively to existing methods. AVAILABILITY: R functions are available upon request from the authors.     

A rapid, microplate SNP genotype assay for the leptinob allele

A nonsense mutation in the mouse leptin gene causes genetic obesity. As a result of extensive research in the field of obesity, the use of leptinob mice is widespread. This mutation renders mice sterile, creating the need to breed heterozygous mice. For this reason, leptinob genotyping is necessary. To date, gel-based assays have been used for genotyping. Using the Invader Plus assay for single nucleotide polymorphism (SNP) detection, we have developed a gel-free microplate SNP assay for genotyping leptinwt and leptinob alleles.     

A double classification tree search algorithm for index SNP selection

Background  

In population-based studies, it is generally recognized that single nucleotide polymorphism (SNP) markers are not independent. Rather, they are carried by haplotypes, groups of SNPs that tend to be coinherited. It is thus possible to choose a much smaller number of SNPs to use as indices for identifying haplotypes or haplotype blocks in genetic association studies. We refer to these characteristic SNPs as index SNPs. In order to reduce costs and work, a minimum number of index SNPs that can distinguish all SNP and haplotype patterns should be chosen. Unfortunately, this is an NP-complete problem, requiring brute force algorithms that are not feasible for large data sets.     

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.     

Rapid competitive PCR using melting curve analysis for DNA quantification.

A rapid competitive PCR method was developed to quantify DNA on the LightCycler. It rests on the quantitative information contained in the melting curves obtained after amplification in the presence of SYBR Green I. Specific hybridization probes are not required. Heterologous internal standards sharing the same primer binding sites and having different melting temperatures to the natural PCR products were used as competitors. After a co-amplification of known amounts of the competitor with a DNA-containing sample, the target DNA can be quantified from the ratio of the melting peak areas of competitor and target products. The method was developed using 16S rDNA fragments from Streptococcus mutans and E. coli and tested against existing PCR-based DNA quantification procedures. While kinetic analysis of real-time PCR is well established for the quantification of pure nucleic acids, competitive PCR on the LightCycler based on an internal standardization was found to represent a rapid and sensitive alternative DNA quantification method for analysis of complex biological samples that may contain PCR inhibitors.     

Computer simulations of the two-species model for the melting curve maximum

The existence of extrema, maximum and/or minimum and negative gradients of melting curves observed for several elements at high pressure is investigated by molecular dynamics simulation using the two-species model (TSM) proposed by Ogura et al. [1 OguraH, MatsudaH, OgawaT, OgitaN, UedaA. Computer simulation for the melting curve maximum phenomenon. Prog Theor Phys. 1977;58:419–433.[Crossref], [Web of Science ®] , [Google Scholar]]. TSM is a model which imitates the change in the electronic structure of an atom in terms of a species change in particles. The TSM phase diagram has two solid phases and one liquid phase with a solid–solid–liquid triple point which corresponds to the melting curve minimum. The melting curve has both a maximum and a minimum, and the gradient of the melting curve is negative between these extrema. These peculiar melting curve properties and phase diagram are common to alkali metals and some other elements.     

An effective way to determine the melting curve

A new ‘two-phase’ simulation method with which to accurately predict the melting curve is proposed. The method requires, as a starting configuration, generating a two-phase coexistence state by employing a suitable ensemble. Examining a change in volume ratio of the two phases upon varying temperature (pressure) under a fixed pressure (temperature) allows us to determine the phase transition point. The Clausius–Clapeyron relationship can then be implemented as a guide to predict the nearby phase transition point. The method was applied to determine the solid–liquid phase boundary of the modified Lennard–Jones system. A better accuracy, as that achieved by the non-equilibrium relaxation method (Asano Y, Fuchizaki K. J Phys Soc Jpn. 2017;86:025001), was obtained but with much less computational cost.     

Development of a 25-plex SNP assay for traceability in cattle

Single nucleotide polymorphisms (SNPs) are amenable to automation and therefore have become the marker of choice for DNA profiling. SNaPshot , a primer extension-based method, was used to multiplex 25 SNPs that have been previously validated as useful for identity control. Detection of extended products was based on four different fluorochromes and extension primers with oligonucleotide tails of differing lengths, thus controlling the concise length of the entire chromatogram to 81 bases. Allele frequencies for Holstein, Simmental, Limousin, Angus, Charolais and Tux Cattle were estimated and significant positive Pearson-correlation coefficients were obtained among the analysed breeds. The probability that two randomly unrelated individuals would share identical genotypes for all 25 loci varied from 10⁻⁸ to 10⁻¹⁰ for these breeds. For parentage control, the exclusion power was found to be 99.9% when the genotypes of both putative parents are known. A traceability test of duplicated samples indicated a high genotyping precision of >0.998. This was further corroborated by analysis of 60 cases of parent–sib pairs and trio families. The 25-plex SNaPshot assay is adapted for low- and high-throughput capacity and thus presents an alternative for DNA-based traceability in the major commercial cattle breeds.     

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.     

Assaying DNA methylation based on high-throughput melting curve approaches

Here we describe two high-throughput methods to assay DNA methylation, melting curve methylation specific PCR (McMSP) and melting curve combined bisulfite restriction analysis (McCOBRA), which adapt standard MSP and COBRA methods to a melting curve analysis based platform. We show that McMSP and McCOBRA can accurately determine methylation status in a high-throughput and gel-free manner. Moreover, McCOBRA can be used to quantitatively estimate the percent of methylated DNA at a specific CpG site within a heterogeneous sample. The accuracy of McMSP and McCOBRA was initially tested using the 5'-CpG site of the tumor-suppressor gene CDKN2A as a model system in homogeneous and heterogeneous controls, and cancer cell line samples. Furthermore, the robustness of McMSP and McCOBRA was validated in four additional loci. We demonstrate that McCOBRA and McMSP provide several advantages over existing methods, as they are simple, accurate, and high-throughput, which makes them widely applicable to large-scale methylation studies.     

Optimization of a SNP assay for genotyping Theobroma cacao under field conditions

The tropical tree crop Theobroma cacao L. is grown commercially for its beans, which are used in the production of cocoa butter and chocolate. Although the upper Amazon region is the center of origin for cacao, 70% of the world??s supply of cacao beans currently comes from small farms in West Africa. While cacao breeding programs in producer nations are the source of improved planting material, modern marker-based breeding is difficult to perform due to the lack of genotyping facilities in these countries. While DNA extraction can be routinely performed, the equipment needed to analyze simple sequence repeats (SSRs) is seldom available, forcing the outsourcing of genotyping to foreign laboratories and delaying the breeding process. We describe a 5?? nuclease (TaqMan)-based single nucleotide polymorphism (SNP) assay for genotyping cacao plants under conditions similar to those found in most cacao-producing areas. The assay was tested under field conditions by planting open pollinated seeds of seven pods from four different maternal plants. The resulting 171 seedlings were successfully genotyped with 18 SNP markers representing 12 loci. The ability to use temperature-stable reagents and rapid DNA extraction methods is also explored. Additionally, by examining the seedling genotypes for the SNP markers and 14 additional SSR markers, we investigated whether seeds in a pod are the result of single or multiple pollination events. This simple, effective method of genotyping cacao seedlings in the field should allow for more efficient resource management of seed gardens and is currently being implemented in Ghana.     

SNP panel identification assay (SPIA): a genetic-based assay for the identification of cell lines

Translational research hinges on the ability to make observations in model systems and to implement those findings into clinical applications, such as the development of diagnostic tools or targeted therapeutics. Tumor cell lines are commonly used to model carcinogenesis. The same tumor cell line can be simultaneously studied in multiple research laboratories throughout the world, theoretically generating results that are directly comparable. One important assumption in this paradigm is that researchers are working with the same cells. However, recent work using high throughput genomic analyses questions the accuracy of this assumption. Observations by our group and others suggest that experiments reported in the scientific literature may contain pre-analytic errors due to inaccurate identities of the cell lines employed. To address this problem, we developed a simple approach that enables an accurate determination of cell line identity by genotyping 34 single nucleotide polymorphisms (SNPs). Here, we describe the empirical development of a SNP panel identification assay (SPIA) compatible with routine use in the laboratory setting to ensure the identity of tumor cell lines and human tumor samples throughout the course of long term research use.     

Multiplex fluorescence melting curve analysis for mutation detection with dual-labeled, self-quenched probes

Probe-based fluorescence melting curve analysis (FMCA) is a powerful tool for mutation detection based on melting temperature generated by thermal denaturation of the probe-target hybrid. Nevertheless, the color multiplexing, probe design, and cross-platform compatibility remain to be limited by using existing probe chemistries. We hereby explored two dual-labeled, self-quenched probes, TaqMan and shared-stem molecular beacons, in their ability to conduct FMCA. Both probes could be directly used for FMCA and readily integrated with closed-tube amplicon hybridization under asymmetric PCR conditions. Improved flexibility of FMCA by using these probes was illustrated in three representative applications of FMCA: mutation scanning, mutation identification and mutation genotyping, all of which achieved improved color-multiplexing with easy probe design and versatile probe combination and all were validated with a large number of real clinical samples. The universal cross-platform compatibility of these probes-based FMCA was also demonstrated by a 4-color mutation genotyping assay performed on five different real-time PCR instruments. The dual-labeled, self-quenched probes offered unprecedented combined advantage of enhanced multiplexing, improved flexibility in probe design, and expanded cross-platform compatibility, which would substantially improve FMCA in mutation detection of various applications.     

Simple SNP typing assay using a base-discriminating fluorescent probe

We have developed a new concept involving a single-step homogeneous method for single-nucleotide polymorphism (SNP) typing. In this method, a probe containing base-discriminating fluorescent (BDF) bases is added to a sample solution. BDF base-containing DNA usually shows only a weak fluorescence, but emits a strong blue fluorescence when it recognizes a target base at a specific site in a hybridized strand. By utilizing this feature, a simple mix-and-read SNP typing assay was achieved without any tedious probe-designing or washing processes for exclusion of hybridization error or any addition of DNA-modifying enzymes. This is very different from conventional methods. We simultaneously analyzed a number of samples with ease, with a high accuracy, using our BDF assay.     

High-throughput SNP genotyping with the GoldenGate assay in maize

Single nucleotide polymorphisms (SNPs) are abundant and evenly distributed throughout the genomes of most plant species. They have become an ideal marker system for genetic research in many crops. Several high throughput platforms have been developed that allow rapid and simultaneous genotyping of up to a million SNP markers. In this study, a custom GoldenGate assay containing 1,536 SNPs was developed based on public SNP information for maize and used to genotype two recombinant inbred line (RIL) populations (Zong3 x 87-1, and B73 x By804) and a panel of 154 diverse inbred lines. Over 90% of the SNPs were successfully scored in the diversity panel and the two RIL populations, with a genotyping error rate of less than 2%. A total of 975 SNP markers detected polymorphism in at least one of the two mapping populations, with a polymorphic rate of 38.5% in Zong3 x 87-1 and 52.6% in B73 x By804. The polymorphic SNPs in B73 x By804 have been integrated with previously mapped simple sequence repeat markers to construct a high-density linkage map containing 662 markers with a total length of 1,673.7 cM and an average of 2.53 cM between two markers. The minor allelic frequency (MAF) was distributed evenly across 10 continued classes from 0.05 to 0.5, and about 16% of the SNP markers had a MAF below 10% in the diversity panel. Polymorphism rates for individual SNP markers in pair-wise comparisons of genotypes tested ranged from 0.3 to 63.8% with an average of 36.3%. Most SNPs used in this GoldenGate assay appear to be equally useful for diversity analysis, marker-trait association studies, and marker-aided breeding.