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

Optimizing sampling design and sequencing strategy for the genomic analysis of quantitative traits in natural populations

Mapping the genes underlying ecologically relevant traits in natural populations is fundamental to develop a molecular understanding of species adaptation. Current sequencing technologies enable the characterization of a species' genetic diversity across the landscape or even over its whole range. The relevant capture of the genetic diversity across the landscape is critical for a successful genetic mapping of traits and there are no clear guidelines on how to achieve an optimal sampling and which sequencing strategy to implement. Here we determine, through simulation, the sampling scheme that maximizes the power to map the genetic basis of a complex trait in an outbreeding species across an idealized landscape and draw genomic predictions for the trait, comparing individual and pool sequencing strategies. Our results show that quantitative trait locus detection power and prediction accuracy are higher when more populations over the landscape are sampled and this is more cost-effectively done with pool sequencing than with individual sequencing. Additionally, we recommend sampling populations from areas of high genetic diversity. As progress in sequencing enables the integration of trait-based functional ecology into landscape genomics studies, these findings will guide study designs allowing direct measures of genetic effects in natural populations across the environment.

Identification of novel alleles associated with insulin resistance in childhood obesity using pooled-DNA genome-wide association study approach

Background:

Recently, we witnessed great progress in the discovery of genetic variants associated with obesity and type 2 diabetes (T2D), especially in adults. Much less is known regarding genetic variants associated with insulin resistance (IR). We hypothesized that novel IR genes could be efficiently detected in a population of obese children and adolescents who may not exhibit comorbidities and other confounding factors.

Objectives:

This study aimed to determine whether a genome-wide association study (GWAS), using a DNA-pooling approach, could identify novel genes associated with IR.

Subjects:

The pooled-DNA GWAS analysis included Slovenian obese children and adolescents with and without IR matched for body mass index, gender and age. A replication study was conducted in another independent cohort with or without IR.

Methods:

For the pooled-DNA GWAS, we used HumanOmni5-Quad SNP array (Illumina). Allele frequency distributions were compared with modified t-tests and χ²-tests and ranked using PLINK. Top single nucleotide polymorphisms (SNPs) were validated using individual genotyping by high-resolution melting analysis and TaqMan assay.

Results:

We identified five top-ranking SNPs from the pooled-DNA GWAS analysis within the ECE1, IL1R2, GNPDA1, HLA-J and PYGB loci. All except SNP rs9261108 (HLA-J locus) were confirmed in the validation phase using individual genotyping. The SNP rs2258617 within PYGB remained statistically significant for both recessive and additive models in both cohorts and in a merged analysis of both cohorts and present the strongest novel candidate gene for IR.

Conclusion:

We report for the first time a pooled-DNA GWAS approach to identify five novel SNPs or genes for IR in a paediatric population. The four loci confirmed in the second validation phase study warrant further studies, especially the strongest SNP rs2258617 within PYGB, and provide targets for further basic research of IR mechanisms and for the development of potential new IR and T2D therapies.

Explorative results from multistep screening for potential genetic risk loci of Alzheimer's disease in the longitudinal VITA study cohort

Alzheimer's disease (AD) is a neurodegenerative disorder that preferentially affects individuals of advanced age. Heritability estimates for AD range between 60 and 80%, but only few genetic risk factors have been identified so far. In the present explorative study, we aimed at characterizing the genetic contribution to late-onset AD in participants of the Vienna Transdanube Aging (VITA) longitudinal birth cohort study in a two-step approach. First, we performed a genome-wide screen of pooled DNA samples (n = 588) to identify allele frequency differences between AD patients and non-AD individuals using life-time diagnoses made at the age of 80 (t = 60 months). This analysis suggested a high proportion of brain-expressed genes required for cell adhesion, cell signaling and cell morphogenesis, and also scored in known AD risk genes. In a second step, we confirmed associations using individual genotypes of top-ranked markers examining AD diagnoses as well as the dimensional scores: FULD and MMSE determined up to the age of 82.5 (t = 90 months). Taken together, our study proposes genes ANKS1B, ENST00000414107, LOC100505811, SLC22A14, QRFPR, ZDHHC8P1, ADAMTS3 and PPFIA1 as possible new candidates involved in the etiology of late-onset AD, with further research being needed to clarify their exact roles.

GWAS study using DNA pooling strategy identifies association of variant rs4910623 in OR52B4 gene with anti-VEGF treatment response in age-related macular degeneration

Pooled DNA based GWAS to determine genetic association of SNPs with visual acuity (VA) outcome in anti-vascular endothelial growth factor (anti-VEGF) treated neovascular age-related macular degeneration (nAMD) patients. We performed pooled DNA based GWAS on 285 anti-VEGF treated nAMD patients using high density Illumina 4.3 M array. Primary outcome was change in VA in Early Treatment Diabetic Retinopathy Study (ETDRS) letters after 6 months of anti-VEGF treatment (patients who lost ≥5 ETDRS letters classified as non-responders and all remaining classified as responders). GWAS analysis identified 44 SNPs of interest: 37 with strong evidence of association (p < 9 × 10⁻⁸), 2 in drug resistance genes (p < 5 × 10⁻⁶) and 5 nonsynonymous changes (p < 1 × 10⁻⁴). In the validation phase, individual genotyping of 44 variants showed three SNPs (rs4910623 p = 5.6 × 10⁻⁵, rs323085 p = 6.5 × 10⁻⁴ and rs10198937 p = 1.30 × 10⁻³) remained associated with VA response at 6 months. SNP rs4910623 also associated with treatment response at 3 months (p = 1.5 × 10⁻³). Replication of these three SNPs in 376 patients revealed association of rs4910623 with poor VA response after 3 and 6 months of treatment (p = 2.4 × 10⁻³ and p = 3.5 × 10⁻², respectively). Meta-analysis of both cohorts (673 samples) confirmed association of rs4910623 with poor VA response after 3 months (p = 1.2 × 10⁻⁵) and 6 months (p = 9.3 × 10⁻⁶) of treatment in nAMD patients.

Allele frequency calibration for SNP based genotyping of DNA pools: A regression based local-global error fusion method

BACKGROUND

The costs associated with developing high density microarray technologies are prohibitive for genotyping animals when there is low economic value associated with a single animal (e.g. prawns). DNA pooling is an attempt to address this issue by combining multiple DNA samples prior to genotyping. Instead of genotyping the DNA samples of the individuals, a mixture of DNA samples (i.e. the pool) from the individuals is genotyped only once. This greatly reduces the cost of genotyping. Pooled samples are subject to greater genotyping inaccuracies than individual samples. Wrong genotyping will lead to wrong biological conclusions. It is thus required to calibrate the resulting genotypes (allele frequencies).

METHODS

We present a regression based approach to translate raw array output to allele frequency. During training, few pools and the individuals that constitute the pools are genotyped. Given the genotypes of individuals that constitute the pool, we compute the true allele frequency. We then train a regression algorithm to produce a mapping between the raw array outputs to the true allele frequency. We test the algorithm using pool samples withheld from the training set. During prediction, we use this map to genotype pools with no prior knowledge of the individuals constituting the pools.

RESULTS AND DISCUSSION

After data quality control we have available a dataset comprised of 912 pools. We estimate allele frequency using three approaches: the raw data, a commonly used piecewise linear transformation, and the proposed local-global learner fusion method. The resulting RMS errors for the three approaches are 0.135, 0.120, and 0.080 respectively.

Mitochondrial genetic variants identified to be associated with posttraumatic stress disorder

Despite the fact that mitochondrial dysfunctions are increasingly recognized as key components in stress-related mental disorders, very little is known about the association between posttraumatic stress disorder (PTSD) and mitochondrial variants. To identify susceptibility mitochondrial genes for PTSD, we analyzed a total number of 978 mitochondrial single-nucleotide polymorphisms (mtSNPs) in a sample of 1238 individuals participating in the KORA (Cooperative Health Research in the Region of Augsburg) study. Participants were classified with 'no PTSD', 'partial PTSD' or 'full PTSD' by applying the Posttraumatic Diagnostic Scale and the Impact of Event Scale. To assess PTSD-mtSNP association while taking heteroplasmy into account, we used the raw signal intensity values measured on the microarray and applied linear regression. Significant associations were obtained between full versus no PTSD and two mtSNPs; mt8414C->T (β=-0.954±0.06, Padjusted=0.037) located in adenosine triphosphate (ATP) synthase subunit 8 (MT-ATP8) and mt12501G->A (β=-1.782±0.40, Padjusted=0.015) located in the NADH dehydrogenase subunits 5 (MT-ND5). Heteroplasmy for the two variants towards a larger number of the respective minor alleles increases the risk of having PTSD. NADH dehydrogenase and ATP synthase are both linked to the regulation of reactive oxygen species. Our results highlight the important role of the mitochondrial genome among the factors that contribute to the risk of PTSD. Mitochondrial genetic variants may be more important than has previously been assumed, leading to further insights regarding effects of existing medications, or even to the development of innovative treatments. As this is the first mitochondrial genome-wide association study for PTSDs, further analyses are needed to follow up on the present findings.

Genomewide association study of reproductive efficiency in female cattle

Reproductive efficiency is of economic importance in commercial beef cattle production, as failure to achieve pregnancy reduces the number of calves marketed per cow exposed. Identification of genetic markers with predictive merit for reproductive success would facilitate early selection of sires with daughters having improved reproductive rate without increasing generation intervals. To identify regions of the genome harboring variation affecting reproductive success, we applied a genomewide association study (GWAS) approach based on the >700,000 SNP marker assay, using a procedure based on genotyping multianimal pools of DNA to increase the number of animals that could be genotyped with available resources. Cows from several populations were classified according to reproductive efficiency, and DNA was pooled within population and phenotype prior to genotyping. Populations evaluated included a research population at the U.S. Meat Animal Research Center, 2 large commercial ranch populations, and a number of smaller populations (<100 head) across the United States. We detected 2 SNP with significant genomewide association (P ≤ 1.49 × 10(-7)), on BTA21 and BTA29, 3 SNP with suggestive associations (P ≤ 2.91 × 10(-6)) on BTA5, and 1 SNP with suggestive association each on BTA1 and BTA25. In addition to our novel findings, we confirmed previously published associations for SNP on BTA-X and all autosomes except 3 (BTA21, BTA22, and BTA28) encompassing substantial breed diversity including Bos indicus and Bos taurus breeds. The study identified regions of the genome associated with reproductive efficiency, which are being targeted for further analysis to develop robust marker systems, and demonstrated that DNA pooling can be used to substantially reduce the cost of GWAS in cattle.

Mitochondrial genetic variants identified to be associated with BMI in adults

It has been suggested that mitochondrial dysfunction plays a role in metabolic disorders including obesity, diabetes, and hypertension. The fact that mitochondrial defects can be accumulated over time as a normal part of aging may explain why some individuals can eat all sorts of foods and remain at normal weight while they are young. However, around the fourth decade of life there is a trend towards "middle-age spread" with weight gain and the body's decreasing ability to metabolize calories efficiently. To test the hypothesis that mitochondrial variants are associated with BMI in adults, we analyzed a total number of 984 mitochondrial single nucleotide polymorphisms (mtSNPs) in a sample of 6,528 individuals participating in the KORA studies. To assess mtSNP association while taking heteroplasmy into account we used the raw signal intensity values measured on the microarray and applied linear regression. Significant results were obtained for 2 mtSNPs located in the Cytochrome c oxidase subunit genes (MT-CO1: Padjusted = 0.0140 and MT-CO3: Padjusted = 0.0286) and 3 mtSNPs located in the NADH dehydrogenase subunit genes (MT-ND1, MT-ND2 and MT-ND4L: Padjusted = 0.0286). Polymorphisms located in the MT-CO3 and MT-ND4L genes have not been associated with BMI or related phenotypes in the past. Our results highlight the importance of the mitochondrial genome among the factors that contribute to the risk of high BMI. Focusing on mitochondrial variants may lead to further insights regarding effects of existing medications, or even to the development of innovative treatments.

Numerical analysis of intensity signals resulting from genotyping pooled DNA samples in beef cattle and broiler chicken

Pooled genomic DNA has been proposed as a cost-effective approach in genomewide association studies (GWAS). However, algorithms for genotype calling of biallelic SNP are not adequate with pooled DNA samples because they assume the presence of 2 fluorescent signals, 1 for each allele, and operate under the expectation that at most 2 copies of the variant allele can be found for any given SNP and DNA sample. We adapt analytical methodology from 2-channel gene expression microarray technology to SNP genotyping of pooled DNA samples. Using 5 datasets from beef cattle and broiler chicken of varying degrees of complexity in terms of design and phenotype, continuous and dichotomous, we show that both differential hybridization (M = green minus red intensity signal) and abundance (A = average of red and green intensities) provide useful information in the prediction of SNP allele frequencies. This is predominantly true when making inference about extreme SNP that are either nearly fixed or highly polymorphic. We propose the use of model-based clustering via mixtures of bivariate normal distributions as an optimal framework to capture the relationship between hybridization intensity and allele frequency from pooled DNA samples. The range of M and A values observed here are in agreement with those reported within the context of gene expression microarray and also with those from SNP array data within the context of analytical methodology for the identification of copy number variants. In particular, we confirm that highly polymorphic SNP yield a strong signal from both channels (red and green) while lowly or nonpolymorphic SNP yield a strong signal from 1 channel only. We further confirm that when the SNP allele frequencies are known, either because the individuals in the pools or from a closely related population are themselves genotyped, a multiple regression model with linear and quadratic components can be developed with high prediction accuracy. We conclude that when these approaches are applied to the estimation of allele frequencies, the resulting estimates allow for the development of cost-effective and reliable GWAS.

Association study of mitochondrial genetic polymorphisms in asthmatic children

It has been suggested that mitochondrial dysfunction plays a role in the pathogenesis of asthma. To test whether mitochondrial variants influence the risk of asthma, we analyzed 16,158 mtSNPs in a sample of 372 asthmatic children and 395 healthy children using the DNA pooling technique and genome wide association analysis. Stratified analysis by sex was performed to explain the differences observed between sexes in the etiology of asthma. Different variants were detected to be significant in the sample of girls and boys with the smallest adjusted p values being 1.4 × 10(-09) (mt5295) and 3.6 × 10(-12) (mt16158), respectively. Most of the significant locations found in boys are within the CYB gene and the non-coding region. For girls, most of the significant mtSNPs lie within NADH-dehydrogenase-subunits. The variants reported here have not previously been described in connection with asthma. Although further studies in other cohorts are needed to confirm these findings our study highlights the importance of the mitochondria among the factors that contribute to the risk of asthma.

KCNIP4 as a candidate gene for personality disorders and adult ADHD

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder in children with striking persistence into adulthood and a high co-morbidity with other psychiatric disorders, including personality disorders (PD). The 4p15.31 region was shown to be associated with ADHD in several genome wide association studies (GWAS). In the present study we also report association of the 4p15.31 locus with Cluster B and Cluster C PD as identified by a pooled genome-wide association study in 400 individuals suffering from PD. The gene coding for the Kv channel-interacting protein 4 (KCNIP4) is located in this region. KCNIP4 is an interaction partner of presenilin and plays a role in a negative feedback loop in the Wnt/β-catenin pathway. Thus, we reasoned it to be a promising candidate gene for ADHD as well as for PD. To clarify the role of KCNIP4 in those disorders, we conducted candidate gene based association studies in 594 patients suffering from adult ADHD and 630 PD patients as compared to 974 healthy control individuals. In the adult ADHD sample, six single markers and one haplotype block revealed to be associated with disease (p values from 0.0079 to 0.049). Seven markers within the KCNIP4 gene showed an association with PD (p values from 0.0043 to 0.0437). The results of these studies suggest a role of KCNIP4 in the etiology of ADHD, PD and other co-morbid disorders.

Cost-effective genome-wide estimation of allele frequencies from pooled DNA in Atlantic salmon (Salmo salar L.)

Background

New sequencing technologies have tremendously increased the number of known molecular markers (single nucleotide polymorphisms; SNPs) in a variety of species. Concurrently, improvements to genotyping technology have now made it possible to efficiently genotype large numbers of genome-wide distributed SNPs enabling genome wide association studies (GWAS). However, genotyping significant numbers of individuals with large number of SNPs remains prohibitively expensive for many research groups. A possible solution to this problem is to determine allele frequencies from pooled DNA samples, such ‘allelotyping’ has been presented as a cost-effective alternative to individual genotyping and has become popular in human GWAS. In this article we have tested the effectiveness of DNA pooling to obtain accurate allele frequency estimates for Atlantic salmon (Salmo salar L.) populations using an Illumina SNP-chip.

Results

In total, 56 Atlantic salmon DNA pools from 14 populations were analyzed on an Atlantic salmon SNP-chip containing probes for 5568 SNP markers, 3928 of which were bi-allelic. We developed an efficient quality control filter which enables exclusion of loci showing high error rate and minor allele frequency (MAF) close to zero. After applying multiple quality control filters we obtained allele frequency estimates for 3631 bi-allelic loci. We observed high concordance (r > 0.99) between allele frequency estimates derived from individual genotyping and DNA pools. Our results also indicate that even relatively small DNA pools (35 individuals) can provide accurate allele frequency estimates for a given sample.

Conclusions

Despite of higher level of variation associated with array replicates compared to pool construction, we suggest that both sources of variation should be taken into account. This study demonstrates that DNA pooling allows fast and high-throughput determination of allele frequencies in Atlantic salmon enabling cost-efficient identification of informative markers for discrimination of populations at various geographical scales, as well as identification of loci controlling ecologically and economically important traits.

Genome-wide association study for ovarian cancer susceptibility using pooled DNA

Recent Genome-Wide Association Studies (GWAS) have identified four low-penetrance ovarian cancer susceptibility loci. We hypothesized that further moderate- or low-penetrance variants exist among the subset of single-nucleotide polymorphisms (SNPs) not well tagged by the genotyping arrays used in the previous studies, which would account for some of the remaining risk. We therefore conducted a time- and cost-effective stage 1 GWAS on 342 invasive serous cases and 643 controls genotyped on pooled DNA using the high-density Illumina 1M-Duo array. We followed up 20 of the most significantly associated SNPs, which are not well tagged by the lower density arrays used by the published GWAS, and genotyping them on individual DNA. Most of the top 20 SNPs were clearly validated by individually genotyping the samples used in the pools. However, none of the 20 SNPs replicated when tested for association in a much larger stage 2 set of 4,651 cases and 6,966 controls from the Ovarian Cancer Association Consortium. Given that most of the top 20 SNPs from pooling were validated in the same samples by individual genotyping, the lack of replication is likely to be due to the relatively small sample size in our stage 1 GWAS rather than due to problems with the pooling approach. We conclude that there are unlikely to be any moderate or large effects on ovarian cancer risk untagged by less dense arrays. However, our study lacked power to make clear statements on the existence of hitherto untagged small-effect variants.

Practical capability and cost effectiveness of a DNA pool-based genome-wide association study using BovineSNP50 array in a cattle population

Genome-wide association mapping for complex traits in cattle populations is a powerful, but expensive, selection tool. The DNA pooling technique can potentially reduce the cost of genome-wide association studies. However, in DNA pooling design, the additional variance generated by pooling-specific errors must be taken into account. Therefore, this study aimed to investigate factors such as: (i) the accuracy of allele frequency estimation; (ii) the magnitude of errors in pooling construction and in the array; and (iii) the effect of the number of replicate arrays on P-values estimated by a genome-wide association study. Results showed that the Illumina correction method is the most effective method to correct the allele frequency estimation; pooling errors, especially array variance, should be taken into account in DNA pooling design; and the risk of a type I error can be reduced by using at least two replicate arrays. These results indicate the practical capability and cost-effectiveness of pool-based genome-wide association studies using the BovineSNP50 array in a cattle population.

Estimates of array and pool-construction variance for planning efficient DNA-pooling genome wide association studies

Background

Until recently, genome-wide association studies (GWAS) have been restricted to research groups with the budget necessary to genotype hundreds, if not thousands, of samples. Replacing individual genotyping with genotyping of DNA pools in Phase I of a GWAS has proven successful, and dramatically altered the financial feasibility of this approach. When conducting a pool-based GWAS, how well SNP allele frequency is estimated from a DNA pool will influence a study's power to detect associations. Here we address how to control the variance in allele frequency estimation when DNAs are pooled, and how to plan and conduct the most efficient well-powered pool-based GWAS.

Methods

By examining the variation in allele frequency estimation on SNP arrays between and within DNA pools we determine how array variance [var(e_array)] and pool-construction variance [var(e_construction)] contribute to the total variance of allele frequency estimation. This information is useful in deciding whether replicate arrays or replicate pools are most useful in reducing variance. Our analysis is based on 27 DNA pools ranging in size from 74 to 446 individual samples, genotyped on a collective total of 128 Illumina beadarrays: 24 1M-Single, 32 1M-Duo, and 72 660-Quad.

Results

For all three Illumina SNP array types our estimates of var(e_array) were similar, between 3-4 × 10^-4 for normalized data. Var(e_construction) accounted for between 20-40% of pooling variance across 27 pools in normalized data.

Conclusions

We conclude that relative to var(e_array), var(e_construction) is of less importance in reducing the variance in allele frequency estimation from DNA pools; however, our data suggests that on average it may be more important than previously thought. We have prepared a simple online tool, PoolingPlanner (available at http://www.kchew.ca/PoolingPlanner/), which calculates the effective sample size (ESS) of a DNA pool given a range of replicate array values. ESS can be used in a power calculator to perform pool-adjusted calculations. This allows one to quickly calculate the loss of power associated with a pooling experiment to make an informed decision on whether a pool-based GWAS is worth pursuing.

Association of polymorphisms in the hepatocyte growth factor gene promoter with keratoconus

PURPOSE

Keratoconus is a progressive disorder of the cornea that can lead to severe visual impairment or blindness. Although several genomic regions have been linked to rare familial forms of keratoconus, no genes have yet been definitively identified for common forms of the disease.

METHODS

Two genome-wide association scans were undertaken in parallel. The first used pooled DNA from an Australian cohort, followed by typing of top-ranked single-nucleotide polymorphisms (SNPs) in individual DNA samples. The second was conducted in individually genotyped patients, and controls from the USA. Tag SNPs around the hepatocyte growth factor (HGF) gene were typed in three additional replication cohorts. Serum levels of HGF protein in normal individuals were assessed with ELISA and correlated with genotype.

RESULTS

The only SNP observed to be associated in both the pooled discovery and primary replication cohort was rs1014091, located upstream of the HGF gene. The nearby SNP rs3735520 was found to be associated in the individually typed discovery cohort (P = 6.1 × 10(-7)). Genotyping of tag SNPs around HGF revealed association at rs3735520 and rs17501108/rs1014091 in four of the five cohorts. Meta-analysis of all five datasets together yielded suggestive P values for rs3735520 (P = 9.9 × 10(-7)) and rs17501108 (P = 9.9 × 10(-5)). In addition, SNP rs3735520 was found to be associated with serum HGF level in normal individuals (P = 0.036).

CONCLUSIONS

Taken together, these results implicate genetic variation at the HGF locus with keratoconus susceptibility.

Physiology and Endocrinology Symposium: How single nucleotide polymorphism chips will advance our knowledge of factors controlling puberty and aid in selecting replacement beef females

The promise of genomic selection is accurate prediction of the genetic potential of animals from their genotypes. Simple DNA tests might replace low-accuracy predictions for expensive or lowly heritable measures of puberty and fertility based on performance and pedigree. Knowing with some certainty which DNA variants (e.g., SNP) affect puberty and fertility is the best way to fulfill the promise. Several SNP from the BovineSNP50 assay have tentatively been associated with reproductive traits including age at puberty, antral follicle count, and pregnancy observed on different sets of heifers. However, sample sizes are too small and SNP density is too sparse to definitively determine genomic regions harboring causal variants affecting reproductive success. Additionally, associations between individual SNP and similar phenotypes are inconsistent across data sets, and genomic predictions do not appear to be globally applicable to cattle of different breeds. Discrepancies may be a result of different QTL segregating in the sampled populations, differences in linkage disequilibrium (LD) patterns such that the same SNP are not correlated with the same QTL, and spurious correlations with phenotype. Several approaches can be used independently or in combination to improve detection of genomic factors affecting heifer puberty and fertility. Larger samples and denser SNP will increase power to detect real associations with SNP having more consistent LD with underlying QTL. Meta-analysis combining results from different studies can also be used to effectively increase sample size. High-density genotyping with heifers pooled by pregnancy status or early and late puberty can be a cost-effective means to sample large numbers. Networks of genes, implicated by associations with multiple traits correlated with puberty and fertility, could provide insight into the complex nature of these traits, especially if corroborated by functional annotation, established gene interaction pathways, and transcript expression. Example analyses are provided to demonstrate how integrating information about gene function and regulation with statistical associations from whole-genome SNP genotyping assays might enhance knowledge of genomic mechanisms affecting puberty and fertility, enabling reliable DNA tests to guide heifer selection decisions.

Association of common variants in the human eyes shut ortholog (EYS) with statin-induced myopathy: evidence for additional functions of EYS

INTRODUCTION

Of the nearly 38 million people in the USA who receive statin therapy, 0.1-0.5% experience severe or life-threatening myopathic side effects.

METHODS

We performed a genome-wide association study (GWAS) in a group of patients with severe statin myopathy versus a statin-tolerant group to identify genetic susceptibility loci.

RESULTS

Replication studies in independent groups of severe statin myopathy (n = 190) and statin-tolerant controls (n = 130) resulted in the identification of three single-nucleotide polymorphisms (SNPs), rs9342288, rs1337512, and rs3857532, in the eyes shut homolog (EYS) on chromosome 6 suggestive of an association with risk for severe statin myopathy (P = 0.0003-0.0008). Analysis of EYS cDNA demonstrated that EYS gene products are complex and expressed with relative abundance in the spinal cord as well as in the retina.

CONCLUSION

Structural similarities of these EYS gene products to members of the Notch signaling pathway and to agrin suggest a possible functional role in the maintenance and regeneration of the structural integrity of skeletal muscle.

Predicting allele frequencies in DNA pools using high density SNP genotyping data

To evaluate the ability to use DNA pools with the Illumina Infinium genotyping platform, two sets of gradient pools were created using two pairs of highly inbred chicken lines. Replicate pools containing 0%, 10%, 20%, 40%, 60%, 80%, 90% and 100% of DNA from line A vs. B or line C vs. D were created, for a total of 28 pools. All pools were genotyped for 12,046 SNPs. Three frequency estimation methods proposed in the literature (standard, heterozygote-corrected and normalized) were compared with three alternate methods proposed herein based on mean square error (MSE), bias and variance of estimated vs. true allele frequencies and the fit of regression of estimated on true frequencies. The three new methods had average square root MSE of 4.6%, 4.6% and 4.7% compared to 5.2%, 5.5% and 11.2% for the three literature methods. Average absolute biases of the literature methods were 2.4%, 2.7% and 8.2% compared to 2.4% for all new methods. Standard deviations of estimates were also smaller for the new methods, at 3.1%, 3.2% and 3.2% compared to 3.5%, 4.0% and 5.0% for previously reported methods. In conclusion, intensity data from the Illumina Infinium Assay can be efficiently used to estimate allele frequencies in pools, in particular using any of the new methods proposed herein.

Novel quantitative real-time LCR for the sensitive detection of SNP frequencies in pooled DNA: method development, evaluation and application

Background

Single nucleotide polymorphisms (SNP) have proven to be powerful genetic markers for genetic applications in medicine, life science and agriculture. A variety of methods exist for SNP detection but few can quantify SNP frequencies when the mutated DNA molecules correspond to a small fraction of the wild-type DNA. Furthermore, there is no generally accepted gold standard for SNP quantification, and, in general, currently applied methods give inconsistent results in selected cohorts. In the present study we sought to develop a novel method for accurate detection and quantification of SNP in DNA pooled samples.

Methods

The development and evaluation of a novel Ligase Chain Reaction (LCR) protocol that uses a DNA-specific fluorescent dye to allow quantitative real-time analysis is described. Different reaction components and thermocycling parameters affecting the efficiency and specificity of LCR were examined. Several protocols, including gap-LCR modifications, were evaluated using plasmid standard and genomic DNA pools. A protocol of choice was identified and applied for the quantification of a polymorphism at codon 136 of the ovine PRNP gene that is associated with susceptibility to a transmissible spongiform encephalopathy in sheep.

Conclusions

The real-time LCR protocol developed in the present study showed high sensitivity, accuracy, reproducibility and a wide dynamic range of SNP quantification in different DNA pools. The limits of detection and quantification of SNP frequencies were 0.085% and 0.35%, respectively.

Significance

The proposed real-time LCR protocol is applicable when sensitive detection and accurate quantification of low copy number mutations in DNA pools is needed. Examples include oncogenes and tumour suppressor genes, infectious diseases, pathogenic bacteria, fungal species, viral mutants, drug resistance resulting from point mutations, and genetically modified organisms in food.

A genomewide association study of nicotine and alcohol dependence in Australian and Dutch populations

Persistent tobacco use and excessive alcohol consumption are major public health concerns worldwide. Both alcohol and nicotine dependence (AD, ND) are genetically influenced complex disorders that exhibit a high degree of comorbidity. To identify gene variants contributing to one or both of these addictions, we first conducted a pooling-based genomewide association study (GWAS) in an Australian population, using Illumina Infinium 1M arrays. Allele frequency differences were compared between pooled DNA from case and control groups for: (1) AD, 1224 cases and 1162 controls; (2) ND, 1273 cases and 1113 controls; and (3) comorbid AD and ND, 599 cases and 488 controls. Secondly, we carried out a GWAS in independent samples from the Netherlands for AD and for ND. Thirdly, we performed a meta-analysis of the 10,000 most significant AD- and ND-related SNPs from the Australian and Dutch samples. In the Australian GWAS, one SNP achieved genomewide significance (p < 5 x 10(-8)) for ND (rs964170 in ARHGAP10 on chromosome 4, p = 4.43 x 10(-8)) and three others for comorbid AD/ND (rs7530302 near MARK1 on chromosome 1 (p = 1.90 x 10(-9)), rs1784300 near DDX6 on chromosome 11 (p = 2.60 x 10(-9)) and rs12882384 in KIAA1409 on chromosome 14 (p = 4.86 x 10(-8))). None of the SNPs achieved genomewide significance in the Australian/Dutch meta-analysis, but a gene network diagram based on the top-results revealed overrepresentation of genes coding for ion-channels and cell adhesion molecules. Further studies will be required before the detailed causes of comorbidity between AD and ND are understood.

Common genetic variants near the Brittle Cornea Syndrome locus ZNF469 influence the blinding disease risk factor central corneal thickness

Central corneal thickness (CCT), one of the most highly heritable human traits (h² typically>0.9), is important for the diagnosis of glaucoma and a potential risk factor for glaucoma susceptibility. We conducted genome-wide association studies in five cohorts from Australia and the United Kingdom (total N = 5058). Three cohorts were based on individually genotyped twin collections, with the remaining two cohorts genotyped on pooled samples from singletons with extreme trait values. The pooled sample findings were validated by individual genotyping the pooled samples together with additional samples also within extreme quantiles. We describe methods for efficient combined analysis of the results from these different study designs. We have identified and replicated quantitative trait loci on chromosomes 13 and 16 for association with CCT. The locus on chromosome 13 (nearest gene FOXO1) had an overall meta-analysis p-value for all the individually genotyped samples of 4.6×10⁻¹⁰. The locus on chromosome 16 was associated with CCT with p = 8.95×10⁻¹¹. The nearest gene to the associated chromosome 16 SNPs was ZNF469, a locus recently implicated in Brittle Cornea Syndrome (BCS), a very rare disorder characterized by abnormal thin corneas. Our findings suggest that in addition to rare variants in ZNF469 underlying CCT variation in BCS patients, more common variants near this gene may contribute to CCT variation in the general population.

Central corneal thickness (CCT) is an important eye measurement. It has been considered as a prognosticator for the development of glaucoma, with a thin cornea potentially increasing the risk of developing a subtype known as open-angle glaucoma. CCT is highly heritable, yet its genetic determinants are poorly characterized. We have revealed two loci near gene FOXO1 and ZNF469 associated with CCT in this multi-stage genome-wide association study examining over 5,000 samples. It is of particular interest that, while rare mutations in ZNF469 cause Brittle Cornea Syndrome, more common variants near this gene also contribute to CCT variation in the general population. Furthermore, given the relation between CCT and glaucoma, results from our CCT studies will implement the search for the disease-susceptibility genes of glaucoma.

Rapid assessment of genetic ancestry in populations of unknown origin by genome-wide genotyping of pooled samples

As we move forward from the current generation of genome-wide association (GWA) studies, additional cohorts of different ancestries will be studied to increase power, fine map association signals, and generalize association results to additional populations. Knowledge of genetic ancestry as well as population substructure will become increasingly important for GWA studies in populations of unknown ancestry. Here we propose genotyping pooled DNA samples using genome-wide SNP arrays as a viable option to efficiently and inexpensively estimate admixture proportion and identify ancestry informative markers (AIMs) in populations of unknown origin. We constructed DNA pools from African American, Native Hawaiian, Latina, and Jamaican samples and genotyped them using the Affymetrix 6.0 array. Aided by individual genotype data from the African American cohort, we established quality control filters to remove poorly performing SNPs and estimated allele frequencies for the remaining SNPs in each panel. We then applied a regression-based method to estimate the proportion of admixture in each cohort using the allele frequencies estimated from pooling and populations from the International HapMap Consortium as reference panels, and identified AIMs unique to each population. In this study, we demonstrated that genotyping pooled DNA samples yields estimates of admixture proportion that are both consistent with our knowledge of population history and similar to those obtained by genotyping known AIMs. Furthermore, through validation by individual genotyping, we demonstrated that pooling is quite effective for identifying SNPs with large allele frequency differences (i.e., AIMs) and that these AIMs are able to differentiate two closely related populations (HapMap JPT and CHB).

Many association studies have been published looking for genetic variants contributing to a variety of human traits such as obesity, diabetes, and height. Because the frequency of genetic variants can differ across populations, it is important to have estimates of genetic ancestry in the individuals being studied. In this study, we were able to measure genetic ancestry in populations of mixed ancestry by genotyping pooled, rather than individual, DNA samples. This represents a rapid and inexpensive means for modeling genetic ancestry and thus could facilitate future association or population-genetic studies in populations of unknown ancestry for which whole-genome data do not already exist.

A Genomewide Association Study of Nicotine and Alcohol Dependence in Australian and Dutch Populations

Persistent tobacco use and excessive alcohol consumption are major public health concerns worldwide. Both alcohol and nicotine dependence (AD, ND) are genetically influenced complex disorders that exhibit a high degree of comorbidity. To identify gene variants contributing to one or both of these addictions, we first conducted a pooling-based genomewide association study (GWAS) in an Australian population, using Illumina Infinium 1M arrays. Allele frequency differences were compared between pooled DNA from case and control groups for: (1) AD, 1224 cases and 1162 controls; (2) ND, 1273 cases and 1113 controls; and (3) comorbid AD and ND, 599 cases and 488 controls. Secondly, we carried out a GWAS in independent samples from the Netherlands for AD and for ND. Thirdly, we performed a meta-analysis of the 10, 000 most significant AD- and ND-related SNPs from the Australian and Dutch samples. In the Australian GWAS, one SNP achieved genomewide significance (p < 5 x 10-8) for ND (rs964170 in ARHGAPlOon chromosome 4, p = 4.43 x 10”8) and three others for comorbid AD/ND (rs7530302 near MARK1 on chromosome 1 (p = 1.90 x 10-9), rs1784300 near DDX6 on chromosome 11 (p = 2.60 x 10-9) and rs12882384 in KIAA1409 on chromosome 14 (p = 4.86 x 10-8)). None of the SNPs achieved genomewide significance in the Australian/Dutch meta-analysis, but a gene network diagram based on the top-results revealed overrepre-sentation of genes coding for ion-channels and cell adhesion molecules. Further studies will be requirec before the detailed causes of comorbidity between AC and ND are understood.

Genome wide association for addiction: replicated results and comparisons of two analytic approaches

BACKGROUND

Vulnerabilities to dependence on addictive substances are substantially heritable complex disorders whose underlying genetic architecture is likely to be polygenic, with modest contributions from variants in many individual genes. "Nontemplate" genome wide association (GWA) approaches can identity groups of chromosomal regions and genes that, taken together, are much more likely to contain allelic variants that alter vulnerability to substance dependence than expected by chance.

METHODOLOGY/PRINCIPAL FINDINGS

We report pooled "nontemplate" genome-wide association studies of two independent samples of substance dependent vs control research volunteers (n = 1620), one European-American and the other African-American using 1 million SNP (single nucleotide polymorphism) Affymetrix genotyping arrays. We assess convergence between results from these two samples using two related methods that seek clustering of nominally-positive results and assess significance levels with Monte Carlo and permutation approaches. Both "converge then cluster" and "cluster then converge" analyses document convergence between the results obtained from these two independent datasets in ways that are virtually never found by chance. The genes identified in this fashion are also identified by individually-genotyped dbGAP data that compare allele frequencies in cocaine dependent vs control individuals.

CONCLUSIONS/SIGNIFICANCE

These overlapping results identify small chromosomal regions that are also identified by genome wide data from studies of other relevant samples to extents much greater than chance. These chromosomal regions contain more genes related to "cell adhesion" processes than expected by chance. They also contain a number of genes that encode potential targets for anti-addiction pharmacotherapeutics. "Nontemplate" GWA approaches that seek chromosomal regions in which nominally-positive associations are found in multiple independent samples are likely to complement classical, "template" GWA approaches in which "genome wide" levels of significance are sought for SNP data from single case vs control comparisons.

Validation of pooled genotyping on the Affymetrix 500 k and SNP6.0 genotyping platforms using the polynomial-based probe-specific correction

BACKGROUND

The use of pooled DNA on SNP microarrays (SNP-MaP) has been shown to be a cost effective and rapid manner to perform whole-genome association evaluations. While the accuracy of SNP-MaP was extensively evaluated on the early Affymetrix 10 k and 100 k platforms, there have not been as many similarly comprehensive studies on more recent platforms. In the present study, we used the data generated from the full Affymetrix 500 k SNP set together with the polynomial-based probe-specific correction (PPC) to derive allele frequency estimates. These estimates were compared to genotyping results of the same individuals on the same platform, as the basis to evaluate the reliability and accuracy of pooled genotyping on these high-throughput platforms. We subsequently extended this comparison to the new SNP6.0 platform capable of genotyping 1.8 million genetic variants.

RESULTS

We showed that pooled genotyping on the 500 k platform performed as well as those previously shown on the relatively lower throughput 10 k and 100 k array sets, with high levels of accuracy (correlation coefficient: 0.988) and low median error (0.036) in allele frequency estimates. Similar results were also obtained from the SNP6.0 array set. A novel pooling strategy of overlapping sub-pools was attempted and comparison of estimated allele frequencies showed this strategy to be as reliable as replicate pools. The importance of an appropriate reference genotyping data set for the application of the PPC algorithm was also evaluated; reference samples with similar ethnic background to the pooled samples were found to improve estimation of allele frequencies.

CONCLUSION

We conclude that use of the PPC algorithm to estimate allele frequencies obtained from pooled genotyping on the high throughput 500 k and SNP6.0 platforms is highly accurate and reproducible especially when a suitable reference sample set is used to estimate the beta values for PPC.

Rapid inexpensive genome-wide association using pooled whole blood

Genome-wide association studies (GWAS) have now successfully identified important genetic variants associated with many human traits and diseases. The high cost of genotyping arrays in large data sets remains the major barrier to wider utilization of GWAS. We have developed a novel method in which whole blood from cases and controls, respectively, is pooled prior to DNA extraction for genotyping. We demonstrate proof of principle by clearly identifying the associated variants for eye color, age-related macular degeneration, and pseudoexfoliation syndrome in cohorts not previously studied. Blood pooling has the potential to reduce GWAS cost by several orders of magnitude and dramatically shorten gene discovery time. This method has profound implications for translation of modern genetic approaches to a multitude of diseases and traits yet to be analyzed by GWAS, and will enable developing nations to participate in GWAS.

The SNPMaP package for R: a framework for genome-wide association using DNA pooling on microarrays

Summary: Large-scale genome-wide association (GWA) studies using thousands of high-density SNP microarrays are becoming an essential tool in the search for loci related to heritable variation in many phenotypes. However, the cost of GWA remains beyond the reach of many researchers. Fortunately, the majority of statistical power can still be obtained by estimating allele frequencies from DNA pools, reducing the cost to that of tens, rather than thousands of arrays. We present a set of software tools for processing SNPMaP (SNP microarrays and pooling) data from CEL files to Relative Allele Scores in the rich R statistical computing environment.

Availability: The SNPMaP package is available from http://cran.r-project.org/ under the GNU General Public License version 3 or later.

Contact:snpmap@iop.kcl.ac.uk

Supplementary information: Additional resources and test datasets are available at http://sgdp.iop.kcl.ac.uk/snpmap/

Applying polynomial standard curve method to correct bias encountered in estimating allele frequencies using DNA pooling strategy

DNA pooling approach is a cost-saving strategy which is crucial for multiple-SNP association study and particularly for laboratories with limited budget. However, the biased allele frequency estimates cannot be completely abolished by kappa correction. Using the SNaPshottrade mark, we systematically examined the relations between actual minor allele frequencies (AMiAFs) levels and estimates obtained from the pooling process for all six types of SNPs. We applied principle of polynomial standard curves method (PSCM) to produce allele frequency estimates in pooled DNA samples and compared it with the kappa method. The results showed that estimates derived from the PSCM were in general closer to AMiAFs than those from the kappa method, particularly for C/G and G/T polymorphisms at the range of AMiAF between 20-40%. We demonstrated that applying PSCM in the SNaPshottrade mark platform is suitable for multiple-SNP association study using pooling strategy, due to its cost effectiveness and estimation accuracy.

Multimarker analysis and imputation of multiple platform pooling-based genome-wide association studies

For many genome-wide association (GWA) studies individually genotyping one million or more SNPs provides a marginal increase in coverage at a substantial cost. Much of the information gained is redundant due to the correlation structure inherent in the human genome. Pooling-based GWA studies could benefit significantly by utilizing this redundancy to reduce noise, improve the accuracy of the observations and increase genomic coverage. We introduce a measure of correlation between individual genotyping and pooling, under the same framework that r(2) provides a measure of linkage disequilibrium (LD) between pairs of SNPs. We then report a new non-haplotype multimarker multi-loci method that leverages the correlation structure between SNPs in the human genome to increase the efficacy of pooling-based GWA studies. We first give a theoretical framework and derivation of our multimarker method. Next, we evaluate simulations using this multimarker approach in comparison to single marker analysis. Finally, we experimentally evaluate our method using different pools of HapMap individuals on the Illumina 450S Duo, Illumina 550K and Affymetrix 5.0 platforms for a combined total of 1 333 631 SNPs. Our results show that use of multimarker analysis reduces noise specific to pooling-based studies, allows for efficient integration of multiple microarray platforms and provides more accurate measures of significance than single marker analysis. Additionally, this approach can be extended to allow for imputing the association significance for SNPs not directly observed using neighboring SNPs in LD. This multimarker method can now be used to cost-effectively complete pooling-based GWA studies with multiple platforms across over one million SNPs and to impute neighboring SNPs weighted for the loss of information due to pooling.

Common sequence variants on 20q11.22 confer melanoma susceptibility

We conducted a genome-wide association pooling study for cutaneous melanoma and performed validation in samples totaling 2,019 cases and 2,105 controls. Using pooling, we identified a new melanoma risk locus on chromosome 20 (rs910873 and rs1885120), with replication in two further samples (combined P < 1 x 10(-15)). The per allele odds ratio was 1.75 (1.53, 2.01), with evidence for stronger association in early-onset cases.

MPDA: microarray pooled DNA analyzer

BACKGROUND

Microarray-based pooled DNA experiments that combine the merits of DNA pooling and gene chip technology constitute a pivotal advance in biotechnology. This new technique uses pooled DNA, thereby reducing costs associated with the typing of DNA from numerous individuals. Moreover, use of an oligonucleotide gene chip reduces costs related to processing various DNA segments (e.g., primers, reagents). Thus, the technique provides an overall cost-effective solution for large-scale genomic/genetic research. However, few publicly shared tools are available to systematically analyze the rapidly accumulating volume of whole-genome pooled DNA data.

RESULTS

We propose a generalized concept of pooled DNA and present a user-friendly tool named Microarray Pooled DNA Analyzer (MPDA) that we developed to analyze hybridization intensity data from microarray-based pooled DNA experiments. MPDA enables whole-genome DNA preferential amplification/hybridization analysis, allele frequency estimation, association mapping, allelic imbalance detection, and permits integration with shared data resources online. Graphic and numerical outputs from MPDA support global and detailed inspection of large amounts of genomic data. Four whole-genome data analyses are used to illustrate the major functionalities of MPDA. The first analysis shows that MPDA can characterize genomic patterns of preferential amplification/hybridization and provide calibration information for pooled DNA data analysis. The second analysis demonstrates that MPDA can accurately estimate allele frequencies. The third analysis indicates that MPDA is cost-effective and reliable for association mapping. The final analysis shows that MPDA can identify regions of chromosomal aberration in cancer without paired-normal tissue.

CONCLUSION

MPDA, the software that integrates pooled DNA association analysis and allelic imbalance analysis, provides a convenient analysis system for extensive whole-genome pooled DNA data analysis. The software, user manual and illustrated examples are freely available online at the MPDA website listed in the Availability and requirements section.

A whole genome association study of neuroticism using DNA pooling

We describe a multistage approach to identify single nucleotide polymorphisms (SNPs) associated with neuroticism, a personality trait that shares genetic determinants with major depression and anxiety disorders. Whole genome association with 452 574 SNPs was performed on DNA pools from approximately 2000 individuals selected on extremes of neuroticism scores from a cohort of 88 142 people from southwest England. The most significant SNPs were then genotyped on independent samples to replicate findings. We were able to replicate association of one SNP within the PDE4D gene in a second sample collected by our laboratory and in a family-based test in an independent sample; however, the SNP was not significantly associated with neuroticism in two other independent samples. We also observed an enrichment of low P-values in known regions of copy number variations. Simulation indicates that our study had approximately 80% power to identify neuroticism loci in the genome with odds ratio (OR)>2, and approximately 50% power to identify small effects (OR=1.5). Since we failed to find any loci accounting for more than 1% of the variance, the heritability of neuroticism probably arises from many loci each explaining much less than 1%. Our findings argue the need for much larger samples than anticipated in genetic association studies and that the biological basis of emotional disorders is extremely complex.

Highly cost-efficient genome-wide association studies using DNA pools and dense SNP arrays

Genome-wide association (GWA) studies to map genes for complex traits are powerful yet costly. DNA-pooling strategies have the potential to dramatically reduce the cost of GWA studies. Pooling using Affymetrix arrays has been proposed and used but the efficiency of these arrays has not been quantified. We compared and contrasted Affymetrix Genechip HindIII and Illumina HumanHap300 arrays on the same DNA pools and showed that the HumanHap300 arrays are substantially more efficient. In terms of effective sample size, HumanHap300-based pooling extracts >80% of the information available with individual genotyping (IG). In contrast, Genechip HindIII-based pooling only extracts approximately 30% of the available information. With HumanHap300 arrays concordance with IG data is excellent. Guidance is given on best study design and it is shown that even after taking into account pooling error, one stage scans can be performed for >100-fold reduced cost compared with IG. With appropriately designed two stage studies, IG can provide confirmation of pooling results whilst still providing approximately 20-fold reduction in total cost compared with IG-based alternatives. The large cost savings with Illumina HumanHap300-based pooling imply that future studies need only be limited by the availability of samples and not cost.

Genome-wide association identifies a common variant in the reelin gene that increases the risk of schizophrenia only in women

Sex differences in schizophrenia are well known, but their genetic basis has not been identified. We performed a genome-wide association scan for schizophrenia in an Ashkenazi Jewish population using DNA pooling. We found a female-specific association with rs7341475, a SNP in the fourth intron of the reelin (RELN) gene (p = 2.9 x 10(-5) in women), with a significant gene-sex effect (p = 1.8 x 10(-4)). We studied rs7341475 in four additional populations, totaling 2,274 cases and 4,401 controls. A significant effect was observed only in women, replicating the initial result (p = 2.1 x 10(-3) in women; p = 4.2 x 10(-3) for gene-sex interaction). Based on all populations the estimated relative risk of women carrying the common genotype is 1.58 (p = 8.8 x 10(-7); p = 1.6 x 10(-5) for gene-sex interaction). The female-specific association between RELN and schizophrenia is one of the few examples of a replicated sex-specific genetic association in any disease.

Gene expression variation in Down's syndrome mice allows prioritization of candidate genes

RNA from eight Ts65Dn mice (a model of Down syndrome) and eight euploid mice were analysed by real-time PCR to examine inter-individual gene expression levels as a function of trisomy.

Background

Down's syndrome (DS), or trisomy 21, is a complex developmental disorder that exhibits many clinical signs that vary in occurrence and severity among patients. The molecular mechanisms responsible for DS have thus far remained elusive. We argue here that normal variation in gene expression in the population contributes to the heterogeneous clinical picture of DS, and we estimated the amplitude of this variation in 50 mouse orthologs of chromosome 21 genes in brain regions of Ts65Dn (a mouse model of DS). We analyzed the RNAs of eight Ts65Dn and eight euploid mice by real-time polymerase chain reaction.

Results

In pooled RNAs, we confirmed that trisomic/euploid gene expression ratios were close to 1.5. However, we observed that inter-individual gene expression levels spanned a broad range of values. We identified three categories of genes: genes with expression levels consistently higher in Ts65Dn than in euploids (9, 17, and 7 genes in cerebellum, cortex, and midbrain, respectively); genes whose expression levels partially overlap between the two groups (10, 9, and 14 genes); and genes with intermingled expression, which cannot be used to differentiate trisomics from euploids (12, 5 and 9 genes). Of the genes in the first category, App, Cbr1, and Mrps6 exhibited tight regulation in the three tissues and are therefore attractive candidates for further research.

Conclusion

This is the first analysis addressing inter-individual gene expression levels as a function of trisomy. We propose a strategy allowing discrimination between candidates for the constant features of DS and those genes that may contribute to the partially penetrant signs of DS.

A generic research paradigm for identification and validation of early molecular diagnostics and new therapeutics in common disorders

Genetically complex disorders continue to confound investigators because of their many underlying factors, both genetic and environmental. In order to tease apart the heritable from the non-heritable contributions to disease, clinicians are relying on researchers in the rapidly expanding fields of high-throughput genomics to identify surrogate clinical endpoints, called biomarkers, that provide a measure of the probability that an individual will succumb to the disease in question. The goals of current biomedical research into complex disorders are to identify and utilize these biomarkers, not only for early detection, but also for personalized treatment with knowledge-guided therapeutics. As the identification of these biomarkers is basically a problem of discovery, we discuss new insights into biomarker detection utilizing the most current genomic technologies available. Additionally, we present here a generic paradigm for the validation of such molecular diagnostics as well as new treatment modalities for complex and increasingly common diseases. Lastly, we delve into the ways genomic biomarkers might be implemented in a clinical setting to allow the subsequent application of targeted therapeutics, which can help the ever expanding groups of individuals experiencing these insidious diseases.

Molecular genetics of nicotine dependence and abstinence: whole genome association using 520,000 SNPs

BACKGROUND

Classical genetic studies indicate that nicotine dependence is a substantially heritable complex disorder. Genetic vulnerabilities to nicotine dependence largely overlap with genetic vulnerabilities to dependence on other addictive substances. Successful abstinence from nicotine displays substantial heritable components as well. Some of the heritability for the ability to quit smoking appears to overlap with the genetics of nicotine dependence and some does not. We now report genome wide association studies of nicotine dependent individuals who were successful in abstaining from cigarette smoking, nicotine dependent individuals who were not successful in abstaining and ethnically-matched control subjects free from substantial lifetime use of any addictive substance.

RESULTS

These data, and their comparison with data that we have previously obtained from comparisons of four other substance dependent vs control samples support two main ideas: 1) Single nucleotide polymorphisms (SNPs) whose allele frequencies distinguish nicotine-dependent from control individuals identify a set of genes that overlaps significantly with the set of genes that contain markers whose allelic frequencies distinguish the four other substance dependent vs control groups (p < 0.018). 2) SNPs whose allelic frequencies distinguish successful vs unsuccessful abstainers cluster in small genomic regions in ways that are highly unlikely to be due to chance (Monte Carlo p < 0.00001).

CONCLUSION

These clustered SNPs nominate candidate genes for successful abstinence from smoking that are implicated in interesting functions: cell adhesion, enzymes, transcriptional regulators, neurotransmitters and receptors and regulation of DNA, RNA and proteins. As these observations are replicated, they will provide an increasingly-strong basis for understanding mechanisms of successful abstinence, for identifying individuals more or less likely to succeed in smoking cessation efforts and for tailoring therapies so that genotypes can help match smokers with the treatments that are most likely to benefit them.

Allelotyping of pooled DNA with 250 K SNP microarrays

Background

Genotyping technologies for whole genome association studies are now available. To perform such studies to an affordable price, pooled DNA can be used. Recent studies have shown that GeneChip Human Mapping 10 K and 50 K arrays are suitable for the estimation of the allele frequency in pooled DNA. In the present study, we tested the accuracy of the 250 K Nsp array, which is part of the 500 K array set representing 500,568 SNPs. Furthermore, we compared different algorithms to estimate allele frequencies of pooled DNA.

Results

We could confirm that the polynomial based probe specific correction (PPC) was the most accurate method for allele frequency estimation. However, a simple k-correction, using the relative allele signal (RAS) of heterozygous individuals, performed only slightly worse and provided results for more SNPs. Using four replicates of the 250 K array and the k-correction using heterozygous RAS values, we obtained results for 104.141 SNPs. The correlation between estimated and real allele frequency was 0.983 and the average error was 0.046, which was comparable to the results obtained with the 10 K array. Furthermore, we could show how the estimation accuracy depended on the SNP type (average error for A/T SNPs: 0.043 and for G/C SNPs: 0.052).

Conclusion

The combination of DNA pooling and analysis of single nucleotide polymorphisms (SNPs) on high density microarrays is a promising tool for whole genome association studies.

Most pooling variation in array-based DNA pooling is attributable to array error rather than pool construction error

Genome-wide association (GWA) approaches are important in complex disease gene mapping studies but are often prohibitively expensive. Array-based DNA pooling has been shown to offer substantial cost savings compared with individual genotyping. This reduced cost potentially brings well-powered GWA studies well within the reach of most laboratories. The main factor, which affects the efficiency of pooling compared with individual genotyping is the magnitude of the pooling error variance. By examining variation between and within pools it is shown that most of the error associated with pooling is attributable to array variation not pooling construction variation (assuming the pools are not small and the pools are accurately constructed). With Affymetrix HindIII 50K arrays used here the array-specific variance is seven times the pooling construction variance. This has important implications for optimal study design for array-based pooling. Given carefully constructed pools, resources should be allocated to increasing the number of arrays per sample rather than to constructing multiple pools.

Identification of the genetic basis for complex disorders by use of pooling-based genomewide single-nucleotide-polymorphism association studies

We report the development and validation of experimental methods, study designs, and analysis software for pooling-based genomewide association (GWA) studies that use high-throughput single-nucleotide-polymorphism (SNP) genotyping microarrays. We first describe a theoretical framework for establishing the effectiveness of pooling genomic DNA as a low-cost alternative to individually genotyping thousands of samples on high-density SNP microarrays. Next, we describe software called "GenePool," which directly analyzes SNP microarray probe intensity data and ranks SNPs by increased likelihood of being genetically associated with a trait or disorder. Finally, we apply these methods to experimental case-control data and demonstrate successful identification of published genetic susceptibility loci for a rare monogenic disease (sudden infant death with dysgenesis of the testes syndrome), a rare complex disease (progressive supranuclear palsy), and a common complex disease (Alzheimer disease) across multiple SNP genotyping platforms. On the basis of these theoretical calculations and their experimental validation, our results suggest that pooling-based GWA studies are a logical first step for determining whether major genetic associations exist in diseases with high heritability.

Addiction molecular genetics: 639,401 SNP whole genome association identifies many "cell adhesion" genes

Addictions are substantially heritable complex disorders. We now report whole genome association studies that identify 89 genes likely to contain variants that contribute to addiction vulnerability, using previously- and newly-validated microarray based pooling assays. Each gene contains clustered single nucleotide polymorphisms (SNPs) that display significant allele frequency differences between abusers and controls in each of the two samples studied with 639,401 SNP arrays and confirmatory SNPs from each of two other abuser/control samples. These genes are implicated in interesting functions, including "cell adhesion" processes that help to establish and maintain neuronal connections of special relevance to addiction's memory-like features.

A genome-wide study of preferential amplification/hybridization in microarray-based pooled DNA experiments

Microarray-based pooled DNA methods overcome the cost bottleneck of simultaneously genotyping more than 100 000 markers for numerous study individuals. The success of such methods relies on the proper adjustment of preferential amplification/hybridization to ensure accurate and reliable allele frequency estimation. We performed a hybridization-based genome-wide single nucleotide polymorphisms (SNPs) genotyping analysis to dissect preferential amplification/hybridization. The majority of SNPs had less than 2-fold signal amplification or suppression, and the lognormal distributions adequately modeled preferential amplification/hybridization across the human genome. Comparative analyses suggested that the distributions of preferential amplification/hybridization differed among genotypes and the GC content. Patterns among different ethnic populations were similar; nevertheless, there were striking differences for a small proportion of SNPs, and a slight ethnic heterogeneity was observed. To fulfill appropriate and gratuitous adjustments, databases of preferential amplification/hybridization for African Americans, Caucasians and Asians were constructed based on the Affymetrix GeneChip Human Mapping 100 K Set. The robustness of allele frequency estimation using this database was validated by a pooled DNA experiment. This study provides a genome-wide investigation of preferential amplification/hybridization and suggests guidance for the reliable use of the database. Our results constitute an objective foundation for theoretical development of preferential amplification/hybridization and provide important information for future pooled DNA analyses.