Analysis of pooled DNA samples on high density arrays without prior knowledge of differential hybridization rates

Array based DNA pooling techniques facilitate genome-wide scale genotyping of large samples. We describe a structured analysis method for pooled data using internal replication information in large scale genotyping sets. The method takes advantage of information from single nucleotide polymorphisms (SNPs) typed in parallel on a high density array to construct a test statistic with desirable statistical properties. We utilize a general linear model to appropriately account for the structured multiple measurements available with array data. The method does not require the use of additional arrays for the estimation of unequal hybridization rates and hence scales readily to accommodate arrays with several hundred thousand SNPs. Tests for differences between cases and controls can be conducted with very few arrays. We demonstrate the method on 384 endometriosis cases and controls, typed using Affymetrix Genechip© HindIII 50 K arrays. For a subset of this data there were accurate measures of hybridization rates available. Assuming equal hybridization rates is shown to have a negligible effect upon the results. With a total of only six arrays, the method extracted one-third of the information (in terms of equivalent sample size) available with individual genotyping (requiring 768 arrays). With 20 arrays (10 for cases, 10 for controls), over half of the information could be extracted from this sample.     

DigiTag assay for multiplex single nucleotide polymorphism typing with high success rate

As a consequence of Human Genome Project and single nucleotide polymorphism (SNP) discovery projects, several millions of SNPs, which include possible susceptibility SNPs for multifactorial diseases, have been revealed. Accordingly, there has been a strong drive to perform the investigation with all candidate SNPs for a certain disease without decreasing the number of analyzed SNPs. We developed DigiTag assay, which uses well-designed oligonucleotides called DNA coded numbers (DCNs) in multiplex SNP genotype analysis. During the analysis, the information of a genotype is converted to one of the DCNs in a one to one manner using oligonucleotide ligation assay (encoding). After the encoding reaction, only the DCNs regions and not the SNP specific regions are amplified using the universal primers and then SNP genotype is read out using DNA capillary arrays. DigiTag assay was found to be successful in SNP genotyping, giving a high success rate (24 of 27 SNPs) for randomly chosen SNPs. Moreover, this assay has the potential to analyze almost all kinds of the target SNPs by applying mismatch-induced probes and redesigned primer pairs at a low-cost.     

Precision-mapping and statistical validation of quantitative trait loci by machine learning

Background

DNA sequence diversity within the human genome may be more greatly affected by copy number variations (CNVs) than single nucleotide polymorphisms (SNPs). Although the importance of CNVs in genome wide association studies (GWAS) is becoming widely accepted, the optimal methods for identifying these variants are still under evaluation. We have previously reported a comprehensive view of CNVs in the HapMap DNA collection using high density 500 K EA (Early Access) SNP genotyping arrays which revealed greater than 1,000 CNVs ranging in size from 1 kb to over 3 Mb. Although the arrays used most commonly for GWAS predominantly interrogate SNPs, CNV identification and detection does not necessarily require the use of DNA probes centered on polymorphic nucleotides and may even be hindered by the dependence on a successful SNP genotyping assay.

Results

In this study, we have designed and evaluated a high density array predicated on the use of non-polymorphic oligonucleotide probes for CNV detection. This approach effectively uncouples copy number detection from SNP genotyping and thus has the potential to significantly improve probe coverage for genome-wide CNV identification. This array, in conjunction with PCR-based, complexity-reduced DNA target, queries over 1.3 M independent NspI restriction enzyme fragments in the 200 bp to 1100 bp size range, which is a several fold increase in marker density as compared to the 500 K EA array. In addition, a novel algorithm was developed and validated to extract CNV regions and boundaries.

Conclusion

Using a well-characterized pair of DNA samples, close to 200 CNVs were identified, of which nearly 50% appear novel yet were independently validated using quantitative PCR. The results indicate that non-polymorphic probes provide a robust approach for CNV identification, and the increasing precision of CNV boundary delineation should allow a more complete analysis of their genomic organization.     

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.     

SNPkit: an efficient approach to systematic evaluation of candidate single nucleotide polymorphisms in public databases

There is widespread interest in devising genotyping methods for SNPs that are robust, inexpensive, and simple to perform. Although several high-throughput SNP genotyping technologies have been developed, including the oligonucleotide ligation assay, real-time PCR, and mass spectrometry, the issues of simplicity and cost-effectiveness have not been adequately addressed. Here we describe the application of a novel computer software package, SNPkit, which designs SNP genotyping assays based on a classical approach for discriminating alleles, restriction enzyme digestion. SNPkit can be used in genotyping assays for almost any SNPs including those that do not alter "natural" restriction sites. Using this method, 164 SNPs have been evaluated in DNA samples from 48 immortalized cell lines of randomly selected Chinese subjects. Sixty-two (37.8%) of the SNPs appeared to be common (frequencies of the minor alleles are > or = 5%) and were subsequently applied to a larger population-based sample. Overall, by using SNPkit, we have been able to validate and genotype accurately a large fraction of publicly available SNPs without sophisticated instrumentation.     

Design and coverage of high throughput genotyping arrays optimized for individuals of East Asian, African American, and Latino race/ethnicity using imputation and a novel hybrid SNP selection algorithm

Four custom Axiom genotyping arrays were designed for a genome-wide association (GWA) study of 100,000 participants from the Kaiser Permanente Research Program on Genes, Environment and Health. The array optimized for individuals of European race/ethnicity was previously described. Here we detail the development of three additional microarrays optimized for individuals of East Asian, African American, and Latino race/ethnicity. For these arrays, we decreased redundancy of high-performing SNPs to increase SNP capacity. The East Asian array was designed using greedy pairwise SNP selection. However, removing SNPs from the target set based on imputation coverage is more efficient than pairwise tagging. Therefore, we developed a novel hybrid SNP selection method for the African American and Latino arrays utilizing rounds of greedy pairwise SNP selection, followed by removal from the target set of SNPs covered by imputation. The arrays provide excellent genome-wide coverage and are valuable additions for large-scale GWA studies.     

SNPstream UHT: ultra-high throughput SNP genotyping for pharmacogenomics and drug discovery

Single nucleotide polymorphism (SNP) genotyping is playing an increasing role in genome mapping, pharmacogenetic studies, and drug discovery. To date, genome-wide scans and studies involving thousands of SNPs and samples have been hampered by the lack of a system that can perform genotyping with cost-effective throughput, accuracy, and reliability. To address this need, Orrhid has developed an automated, ultra-high throughput system, SNPstream UHT, which uses multiplexed PCR in conjunction with our next generation SNP-IT tag array single base extension genotyping technology The system employs oligonucleotide microarrays manufactured in a 384-well format on a novel glass-bottomed plate. Multiplexed PCR and genotyping are performed in homogeneous reactions, and assay results are read by direct two-color fluorescence on the SNPstream UHTArray Imager. The systems flexibility enables large projects involving thousands of SNPs and thousands of samples as well as small projects that have hundreds of SNPs and hundreds of samples to be done cost effectively. We have successfully demonstrated this system in greater than 1,000,000 genotyping assays with >96% of samples giving genotypes with >99% accuracy     

Improved allelic differentiation using sequence-specific oligonucleotide hybridization incorporating an additional base-analogue mismatch

Sequence-specific oligonucleotide hybridization (SSOH, 'dot-blotting') is a widely employed method of typing single nucleotide polymorphisms (SNPs), but it is often compromised by lack of allelic differentiation. We describe a novel improvement to SSOH that incorporates an additional mismatch into the oligonucleotide probe using the universal base analogue 3-nitropyrrole. This method greatly increases allelic differentiation compared to standard SSOH where oligonucleotides contain only SNP-defining base changes. Moreover, stringency of the hybridisation is predictably maintained over a wide range of temperatures, which can be calculated empirically, thus facilitating the genotyping of multiple SNPs using similar conditions. This improved method increases the usefulness of hybridisation-based methods of rapid genotyping of SNPs and may have implications for array methodologies.     

Tool for genomic selection and breeding to evolutionary adaptation: Development of a 100K single nucleotide polymorphism array for the honey bee

High‐throughput high‐density genotyping arrays continue to be a fast, accurate, and cost‐effective method for genotyping thousands of polymorphisms in high numbers of individuals. Here, we have developed a new high‐density SNP genotyping array (103,270 SNPs) for honey bees, one of the most ecologically and economically important pollinators worldwide. SNPs were detected by conducting whole‐genome resequencing of 61 honey bee drones (haploid males) from throughout Europe. Selection of SNPs for the chip was done in multiple steps using several criteria. The majority of SNPs were selected based on their location within known candidate regions or genes underlying a range of honey bee traits, including hygienic behavior against pathogens, foraging, and subspecies. Additionally, markers from a GWAS of hygienic behavior against the major honey bee parasite Varroa destructor were brought over. The chip also includes SNPs associated with each of three major breeding objectives—honey yield, gentleness, and Varroa resistance. We validated the chip and make recommendations for its use by determining error rates in repeat genotypings, examining the genotyping performance of different tissues, and by testing how well different sample types represent the queen's genotype. The latter is a key test because it is highly beneficial to be able to determine the queen's genotype by nonlethal means. The array is now publicly available and we suggest it will be a useful tool in genomic selection and honey bee breeding, as well as for GWAS of different traits, and for population genomic, adaptation, and conservation questions.     

Photolithographic synthesis of high-density oligonucleotide probe arrays

High-density DNA probe arrays provide a massively parallel approach to nucleic acid sequence analysis that is transforming gene-based biomedical research and diagnostics. Light-directed combinatorial oligonucleotide synthesis has enabled the large-scale production of GeneChip probe arrays which contain several hundred of thousand oligonucleotide sequences on glass "chips" about one cm2 in size. Due to their very high information content, GeneChip probe arrays are finding widespread use in the hybridization-based detection and analysis of mutations and polymorphisms ("genotyping"), and in a wide range of gene expression studies. The manufacturing process integrates solid-phase photochemical oligonucleotide synthesis with lithographic techniques adapted from the microelectronics industry. The present-generation methodology employs MeNPOC photo-activatable nucleoside monomers with proximity photolithography, and is currently capable of printing individual 10 microns 2 probe features at a density of 10(6) probes/cm2.     

Improved Allelic Differentiation Using Sequence‐Specific Oligonucleotide Hybridization Incorporating an Additional Base‐Analogue Mismatch

Sequence‐specific oligonucleotide hybridization (SSOH, ‘dot‐blotting’) is a widely employed method of typing single nucleotide polymorphisms (SNPs), but it is often compromised by lack of allelic differentiation. We describe a novel improvement to SSOH that incorporates an additional mismatch into the oligonucleotide probe using the universal base analogue 3‐nitropyrrole. This method greatly increases allelic differentiation compared to standard SSOH where oligonucleotides contain only SNP‐defining base changes. Moreover, stringency of the hybridisation is predictably maintained over a wide range of temperatures, which can be calculated empirically, thus facilitating the genotyping of multiple SNPs using similar conditions. This improved method increases the usefulness of hybridisation‐based methods of rapid genotyping of SNPs and may have implications for array methodologies.     

MARA: a novel approach for highly multiplexed locus-specific SNP genotyping using high-density DNA oligonucleotide arrays

We have developed a locus-specific DNA target preparation method for highly multiplexed single nucleotide polymorphism (SNP) genotyping called MARA (Multiplexed Anchored Runoff Amplification). The approach uses a single primer per SNP in conjunction with restriction enzyme digested, adapter-ligated human genomic DNA. Each primer is composed of common sequence at the 5′ end followed by locus-specific sequence at the 3′ end. Following a primary reaction in which locus-specific products are generated, a secondary universal amplification is carried out using a generic primer pair corresponding to the oligonucleotide and genomic DNA adapter sequences. Allele discrimination is achieved by hybridization to high-density DNA oligonucleotide arrays. Initial multiplex reactions containing either 250 primers or 750 primers across nine DNA samples demonstrated an average sample call rate of ~95% for 250- and 750-plex MARA. We have also evaluated >1000- and 4000-primer plex MARA to genotype SNPs from human chromosome 21. We have identified a subset of SNPs corresponding to a primer conversion rate of ~75%, which show an average call rate over 95% and concordance >99% across seven DNA samples. Thus, MARA may potentially improve the throughput of SNP genotyping when coupled with allele discrimination on high-density arrays by allowing levels of multiplexing during target generation that far exceed the capacity of traditional multiplex PCR.     

PHOTOLITHOGRAPHIC SYNTHESIS OF HIGH-DENSITY OLIGONUCLEOTIDE PROBE ARRAYS

High-density DNA probe arrays provide a massively parallel approach to nucleic acid sequence analysis that is transforming gene-based biomedical research and diagnostics. Light-directed combinatorial oligonucleotide synthesis has enabled the large-scale production of GeneChip® probe arrays which contain several hundred of thousand oligonucleotide sequences on glass “chips” about one cm² in size. Due to their very high information content, GeneChip® probe arrays are finding widespread use in the hybridization-based detection and analysis of mutations and polymorphisms (“genotyping”), and in a wide range of gene expression studies. The manufacturing process integrates solid-phase photochemical oligonucleotide synthesis with lithographic techniques adapted from the microelectronics industry. The present-generation methodology employs MeNPOC photo-activatable nucleoside monomers with proximity photolithography, and is currently capable of printing individual 10 μm² probe features at a density of 10⁶ probes/cm².     

The Wheat 660K SNP array demonstrates great potential for marker‐assisted selection in polyploid wheat

The rapid development and application of molecular marker assays have facilitated genomic selection and genome‐wide linkage and association studies in wheat breeding. Although PCR‐based markers (e.g. simple sequence repeats and functional markers) and genotyping by sequencing have contributed greatly to gene discovery and marker‐assisted selection, the release of a more accurate and complete bread wheat reference genome has resulted in the design of single‐nucleotide polymorphism (SNP) arrays based on different densities or application targets. Here, we evaluated seven types of wheat SNP arrays in terms of their SNP number, distribution, density, associated genes, heterozygosity and application. The results suggested that the Wheat 660K SNP array contained the highest percentage (99.05%) of genome‐specific SNPs with reliable physical positions. SNP density analysis indicated that the SNPs were almost evenly distributed across the whole genome. In addition, 229 266 SNPs in the Wheat 660K SNP array were located in 66 834 annotated gene or promoter intervals. The annotated genes revealed by the Wheat 660K SNP array almost covered all genes revealed by the Wheat 35K (97.44%), 55K (99.73%), 90K (86.9%) and 820K (85.3%) SNP arrays. Therefore, the Wheat 660K SNP array could act as a substitute for other 6 arrays and shows promise for a wide range of possible applications. In summary, the Wheat 660K SNP array is reliable and cost‐effective and may be the best choice for targeted genotyping and marker‐assisted selection in wheat genetic improvement.     

SNP discovery and population structure analysis in Lassi and Marecha camel breeds using a genotyping by sequencing method

Pakistani camels have been classified socio-geographically into 20 breeds, but they have not yet been subjected to substantial selective pressures and the genetic basis for these breeds is not understood. However, it should be possible to distinguish them by use of molecular data. This study investigated the genetic diversity and population structure within and between two major Pakistani camel breeds, Marecha and Lassi. As no SNP array is currently available, we first identified 63 619 SNPs using a genotyping by sequencing approach. After quality control, a panel of 36 926 SNPs was used in the analysis. Population structure was investigated with a principal coordinate analysis as well as a cluster analysis using NetView , and multilocus heterozygosity analysis to explore between- and within-breed genetic variation. In addition, between-breed variation was explored using the fixation index, F_ST. We also compared relationship matrices computed using the VanRaden SNP-based method and a method developed specifically for genotyping by sequencing data. Among the two camel breeds, Lassi showed a lower level of genetic diversity whereas Marecha showed a higher level. As a genotyping platform has not yet been developed for the camel, the SNPs discovered in this study will be useful in future genetic studies in camels.     

Characterization of polyploid wheat genomic diversity using a high‐density 90 000 single nucleotide polymorphism array

High‐density single nucleotide polymorphism (SNP) genotyping arrays are a powerful tool for studying genomic patterns of diversity, inferring ancestral relationships between individuals in populations and studying marker–trait associations in mapping experiments. We developed a genotyping array including about 90 000 gene‐associated SNPs and used it to characterize genetic variation in allohexaploid and allotetraploid wheat populations. The array includes a significant fraction of common genome‐wide distributed SNPs that are represented in populations of diverse geographical origin. We used density‐based spatial clustering algorithms to enable high‐throughput genotype calling in complex data sets obtained for polyploid wheat. We show that these model‐free clustering algorithms provide accurate genotype calling in the presence of multiple clusters including clusters with low signal intensity resulting from significant sequence divergence at the target SNP site or gene deletions. Assays that detect low‐intensity clusters can provide insight into the distribution of presence–absence variation (PAV) in wheat populations. A total of 46 977 SNPs from the wheat 90K array were genetically mapped using a combination of eight mapping populations. The developed array and cluster identification algorithms provide an opportunity to infer detailed haplotype structure in polyploid wheat and will serve as an invaluable resource for diversity studies and investigating the genetic basis of trait variation in wheat.     

Development of a 135K SNP genotyping array for Actinidia arguta and its applications for genetic mapping and QTL analysis in kiwifruit

Kiwifruit (Actinidia spp) is a woody, perennial and deciduous vine. In this genus, there are multiple ploidy levels but the main cultivated cultivars are polyploid. Despite the availability of many genomic resources in kiwifruit, SNP genotyping is still a challenge given these different levels of polyploidy. Recent advances in SNP array technologies have offered a high-throughput genotyping platform for genome-wide DNA polymorphisms. In this study, we developed a high-density SNP genotyping array to facilitate genetic studies and breeding applications in kiwifruit. SNP discovery was performed by genome-wide DNA sequencing of 40 kiwifruit genotypes. The identified SNPs were stringently filtered for sequence quality, predicted conversion performance and distribution over the available Actinidia chinensis genome. A total of 134 729 unique SNPs were put on the array. The array was evaluated by genotyping 400 kiwifruit individuals. We performed a multidimensional scaling analysis to assess the diversity of kiwifruit germplasm, showing that the array was effective to distinguish kiwifruit accessions. Using a tetraploid F1 population, we constructed an integrated linkage map covering 3060.9 cM across 29 linkage groups and performed QTL analysis for the sex locus that has been identified on Linkage Group 3 (LG3) in Actinidia arguta. Finally, our dataset presented evidence of tetrasomic inheritance with partial preferential pairing in A. arguta. In conclusion, we developed and evaluated a 135K SNP genotyping array for kiwifruit. It has the advantage of a comprehensive design that can be an effective tool in genetic studies and breeding applications in this high-value crop.     

Evaluation of SNP Data from the Malus Infinium Array Identifies Challenges for Genetic Analysis of Complex Genomes of Polyploid Origin

High throughput arrays for the simultaneous genotyping of thousands of single-nucleotide polymorphisms (SNPs) have made the rapid genetic characterisation of plant genomes and the development of saturated linkage maps a realistic prospect for many plant species of agronomic importance. However, the correct calling of SNP genotypes in divergent polyploid genomes using array technology can be problematic due to paralogy, and to divergence in probe sequences causing changes in probe binding efficiencies. An Illumina Infinium II whole-genome genotyping array was recently developed for the cultivated apple and used to develop a molecular linkage map for an apple rootstock progeny (M432), but a large proportion of segregating SNPs were not mapped in the progeny, due to unexpected genotype clustering patterns. To investigate the causes of this unexpected clustering we performed BLAST analysis of all probe sequences against the ‘Golden Delicious’ genome sequence and discovered evidence for paralogous annealing sites and probe sequence divergence for a high proportion of probes contained on the array. Following visual re-evaluation of the genotyping data generated for 8,788 SNPs for the M432 progeny using the array, we manually re-scored genotypes at 818 loci and mapped a further 797 markers to the M432 linkage map. The newly mapped markers included the majority of those that could not be mapped previously, as well as loci that were previously scored as monomorphic, but which segregated due to divergence leading to heterozygosity in probe annealing sites. An evaluation of the 8,788 probes in a diverse collection of Malus germplasm showed that more than half the probes returned genotype clustering patterns that were difficult or impossible to interpret reliably, highlighting implications for the use of the array in genome-wide association studies.