Association mapping of disease loci, by use of a pooled DNA genomic screen

Deciphering the Genetic Diversity of Landraces With High-Throughput SNP Genotyping of DNA Bulks: Methodology and Application to the Maize 50k Array

Genebanks harbor original landraces carrying many original favorable alleles for mitigating biotic and abiotic stresses. Their genetic diversity remains, however, poorly characterized due to their large within genetic diversity. We developed a high-throughput, cheap and labor saving DNA bulk approach based on single-nucleotide polymorphism (SNP) Illumina Infinium HD array to genotype landraces. Samples were gathered for each landrace by mixing equal weights from young leaves, from which DNA was extracted. We then estimated allelic frequencies in each DNA bulk based on fluorescent intensity ratio (FIR) between two alleles at each SNP using a two step-approach. We first tested either whether the DNA bulk was monomorphic or polymorphic according to the two FIR distributions of individuals homozygous for allele A or B, respectively. If the DNA bulk was polymorphic, we estimated its allelic frequency by using a predictive equation calibrated on FIR from DNA bulks with known allelic frequencies. Our approach: (i) gives accurate allelic frequency estimations that are highly reproducible across laboratories, (ii) protects against false detection of allele fixation within landraces. We estimated allelic frequencies of 23,412 SNPs in 156 landraces representing American and European maize diversity. Modified Roger's genetic Distance between 156 landraces estimated from 23,412 SNPs and 17 simple sequence repeats using the same DNA bulks were highly correlated, suggesting that the ascertainment bias is low. Our approach is affordable, easy to implement and does not require specific bioinformatics support and laboratory equipment, and therefore should be highly relevant for large-scale characterization of genebanks for a wide range of species.

Specific Differentially Methylated and Expressed Genes in People with Longevity Family History

Background

We attempt to identify specific differentially methylated and expressed genes in people with longevity family history, it will contribute to discover significant features about human longevity.

Methods

A prevalence study was conducted during October 2017 to January 2019 in Bama County of Guangxi, China and individuals were recruited and grouped into longevity family (n=60) and non-longevity family (n=60) to identify differentially methylated genes (DMGs). The expression profile dataset GSE16717 was downloaded from the GEO database in which individuals were divided into 3 groups, namely longevity (n=50), longevity offspring (n=50) and control (n=50) for identifying differentially expressed genes (DEGs). It was considered significantly different when P or adjusted P≤0.05.

Results

In total, 117 longevity-related hypermethylated genes enriched in interleukin secretion/production regulation, chemokine signaling pathway and natural killer cell-mediated cytotoxicity. Another 296 significant key longevity-related DEGs primarily involved in protein binding, nucleus, cytoplasm, T cell receptor signaling pathway and Metabolic pathway, H19 and PFKFB4 were found to be both methylated and downregulated in people with longevity family history.

Conclusion

Human longevity-specific genes involve in many immunity regulations and cellular immunity pathways, H19 and PFKFB4 show hypermethylated and suppressed status in people with longevity family history and might serve as longevity candidate genes.

A logical relationship for schizophrenia, bipolar, and major depressive disorder. Part 1: Evidence from chromosome 1 high density association screen

Familial clustering of schizophrenia (SCZ), bipolar disorder (BPD), and major depressive disorder (MDD) was investigated systematically (Aukes et al., Genetics in Medicine, 2012, 14, 338-341) and any two or even three of these disorders could coexist in some families. Furthermore, evidence from symptomatology and psychopharmacology also imply the existence of intrinsic connections between these three major psychiatric disorders. A total of 71,445 SNPs on chromosome 1 were genotyped on 119 SCZ, 253 BPD (type-I), 177 MDD cases and 1000 controls and further validated in 986 SCZ patients in the population of Shandong province of China. Outstanding psychosis genes are systematically revealed( ATP1A4, ELTD1, FAM5C, HHAT, KIF26B, LMX1A, NEGR1, NFIA, NR5A2, NTNG1, PAPPA2, PDE4B, PEX14, RYR2, SYT6, TGFBR3, TTLL7, and USH2A). Unexpectedly, flanking genes for up to 97.09% of the associated SNPs were also replicated in an enlarged cohort of 986 SCZ patients. From the perspective of etiological rather than clinical psychiatry, bipolar, and major depressive disorder could be subtypes of schizophrenia. Meanwhile, the varied clinical feature and prognosis might be the result of interaction of genetics and epigenetics, for example, irreversible or reversible shut down, and over or insufficient expression of certain genes, which may gives other aspects of these severe mental disorders.

A Partially Phase-Separated Genome Sequence Assembly of the Vitis Rootstock 'Börner' (Vitis riparia × Vitis cinerea) and Its Exploitation for Marker Development and Targeted Mapping

Grapevine breeding has become highly relevant due to upcoming challenges like climate change, a decrease in the number of available fungicides, increasing public concern about plant protection, and the demand for a sustainable production. Downy mildew caused by Plasmopara viticola is one of the most devastating diseases worldwide of cultivated Vitis vinifera. In modern breeding programs, therefore, genetic marker technologies and genomic data are used to develop new cultivars with defined and stacked resistance loci. Potential sources of resistance are wild species of American or Asian origin. The interspecific hybrid of Vitis riparia Gm 183 x Vitis cinerea Arnold, available as the rootstock cultivar 'Börner,' carries several relevant resistance loci. We applied next-generation sequencing to enable the reliable identification of simple sequence repeats (SSR), and we also generated a draft genome sequence assembly of 'Börner' to access genome-wide sequence variations in a comprehensive and highly reliable way. These data were used to cover the 'Börner' genome with genetic marker positions. A subset of these marker positions was used for targeted mapping of the P. viticola resistance locus, Rpv14, to validate the marker position list. Based on the reference genome sequence PN40024, the position of this resistance locus can be narrowed down to less than 0.5 Mbp on chromosome 5.

A novel relationship for schizophrenia, bipolar and major depressive disorder Part 3: Evidence from chromosome 3 high density association screen

Familial clustering of schizophrenia (SCZ), bipolar disorder (BPD), and major depressive disorder (MDD) was systematically reported (Aukes et al, Genet Med 2012, 14, 338-341) and convergent evidence from genetics, symptomatology, and psychopharmacology imply that there are intrinsic connections between these three major psychiatric disorders, for example, any two or even three of these disorders could co-exist in some families. A total of 60, 838 single-nucleotide polymorphisms (SNPs) on chromosome 3 were genotyped by Affymetrix Genome-Wide Human SNP array 6.0 on 119 SCZ, 253 BPD (type-I), 177 MDD patients and 1,000 controls. The population of Shandong province was formed in 14 century and believed that it belongs to homogenous population. Associated SNPs were systematically revealed and outstanding susceptibility genes (CADPS, GRM7,KALRN, LSAMP, NLGN1, PRICKLE2, ROBO2) were identified. Unexpectedly, flanking genes for the associated SNPs distinctive for BPD and/or MDD were replicated in an enlarged cohort of 986 SCZ patients. The evidence from this chromosome 3 analysis supports the notion that both of bipolar and MDD might be subtypes of schizophrenia rather than independent disease entity. Also, a similar finding was detected on chromosome 5, 6, 7, and 8 (Chen et al. Am J Transl Res 2017;9 (5):2473-2491; Curr Mol Med 2016;16(9):840-854; Behav Brain Res 2015;293:241-251; Mol Neurobiol 2016. doi: 10.1007/s12035-016-0102-1). Furthermore, PRICKLE2 play an important role in the pathogenesis of three major psychoses in this population.

Genome-wide association study for mandibular prognathism using microsatellite and pooled DNA method

INTRODUCTION

The purpose of this study was to extend an association study from chromosome 1 to the whole genome (genome-wide association study) to find susceptibility loci of mandibular prognathism.

METHODS

Two hundred forty patients diagnosed with mandibular prognathism and 360 healthy controls of Japanese descent were recruited. The typing of microsatellites covering the whole genome was conducted using a pooled DNA method. Upon completion of the first and second screenings with pooled DNA, the positive microsatellite markers from both the first and second typings were retyped using individual-subject DNA samples to confirm the significance of allele frequency.

RESULTS

Six microsatellites (D1S0411i, D1S1358i, D3S0810i, D6S0827i, D7S0133i, and D15S0154i) showed differences between allele frequencies of the subjects and controls at P <0.001. D1S0411i, D1S1358i, D3S0810i, D6S0827i, D7S0133i, and D15S0154i were located on chromosomes 1p22.3, 1q32.2, 3q23, 6q23.2, 7q11.22, and 15q22.22, respectively. SSX2IP, PLXNA2, RASA2, TCF21, CALN1, and RORA were suggested as candidate genes.

CONCLUSIONS

The genome-wide association study using microsatellites suggested that 6 loci (1p22.3, 1q32.2, 3q23, 6q23.2, 7q11.22, and 15q22.22) were susceptibility regions of mandibular prognathism. The locus 1p22.3 was supported by a previous linkage analysis, and the other 5 were novel loci.

A novel relationship for schizophrenia, bipolar and major depressive disorder Part 5: a hint from chromosome 5 high density association screen

Familial clustering of schizophrenia (SCZ), bipolar disorder (BPD), and major depressive disorder (MDD) was systematically reported (Aukes, M. F. Genet Med 2012, 14, 338-341) and any two or even three of these disorders could co-exist in some families. In addition, evidence from symptomatology and psychopharmacology also imply that there are intrinsic connections between these three major disorders. A total of 56,569 single nucleotide polymorphism (SNPs) on chromosome 5 were genotyped by Affymetrix Genome-Wide Human SNP array 6.0 on 119 SCZ, 253 BPD (type-I), 177 MDD patients and 1000 controls. Associated SNPs and flanking genes was screen out systematically, and cadherin pathway genes (CDH6, CDH9, CDH10, CDH12, and CDH18) belong to outstanding genes. Unexpectedly, nearly all flanking genes of the associated SNPs distinctive for BPD and MDD were replicated in an enlarged cohort of 986 SCZ patients (P ≤ 9.9E-8). Considering multiple bits of evidence, our chromosome 5 analyses implicated that bipolar and major depressive disorder might be subtypes of schizophrenia rather than two independent disease entities. Also, cadherin pathway genes play important roles in the pathogenesis of the three major mental disorders.

A novel relationship for schizophrenia, bipolar and major depressive disorder Part 7: A hint from chromosome 7 high density association screen

Convergent evidence from genetics, symptology and psychopharmacology imply that there are intrinsic connection between schizophrenia (SCZ), bipolar disorder (BPD) and major depressive disorder (MDD). Also, any two or even three of these disorders could co-existe in some families. A total of 47,144 single nucleotide polymorphism (SNPs) on chromosome 7 were genotyped by Affymetrix Genome-Wide Human SNP array 6.0 on 119 SCZ, 253 BPD (type-I), 177 MDD, and 1000 controls. Associated SNP loci were comprehensively revealed and outstanding susceptibility genes were identified including CNTNAP2. a neurexin family gene. Unexpectedly, flanking genes for up to 94.74 % of of the associated SNPs were replicated (P≤9.9 E-8) in an enlarged cohort of 986 SCZ patients. Considering other convergent evidence, our results further implicate that BPD and MDD are subtypes of SCZ.

Microsatellite genome-wide association study for mandibular prognathism

INTRODUCTION

Attempts have been made to identify susceptibility genes of mandibular prognathism by genome-wide linkage studies, but the results of susceptibility loci are inconsistent. There has been no genome-wide association study of mandibular prognathism. Our objective was to perform a genome-wide association study using 23,465 microsatellite markers to detect mandibular prognathism susceptibility regions.

METHODS

The study was based on the pooled DNA method, including 2 steps of screening on the whole genome and subsequent individual genotyping, with 240 experimental subjects and 360 control subjects from the Japanese population.

RESULTS

Two suggestive associations on chromosomes 1q32.2 (D1S1358i: P = 4.22 × 10(-4)) and 1p22.3 (D1S0411i: P = 6.66 × 10(-4)) were shown, and PLXNA2 and SSX2IP were suggested to be candidate genes; 1p22.3 flanked the region indicated by previous linkage analysis.

CONCLUSIONS

The results of the genome-wide association study showed that 2 loci (1q32.2 and 1p22.3) are likely to be susceptibility regions of mandibular prognathism: 1p32.2 is a novel locus, and identification of 1p22.3 supports the results of previous linkage analysis.

COLD-PCR enriches low-level variant DNA sequences and increases the sensitivity of genetic testing

Detection of low-level mutations is important for cancer biomarker and therapy targets discovery, but reliable detection remains a technical challenge. The newly developed method of CO-amplification at Lower Denaturation temperature PCR (COLD-PCR) helps to circumvent this issue. This PCR-based technology preferentially enriches minor known or unknown variants present in samples with a high background of wild type DNA which often hampers the accurate identification of these minority alleles. This is a simple process that consists of lowering the temperature at the denaturation step during the PCR-cycling protocol (critical denaturation temperature, T c) and inducing DNA heteroduplexing during an intermediate step. COLD-PCR in its simplest forms does not need additional reagents or specific instrumentation and thus, can easily replace conventional PCR and at the same time improve the mutation detection sensitivity limit of downstream technologies. COLD-PCR can be applied in two basic formats: fast-COLD-PCR that can enrich T m-reducing mutations and full-COLD-PCR that can enrich all mutations, though it requires an intermediate cross-hybridization step that lengthens the thermocycling program. An improved version of full-COLD-PCR (improved and complete enrichment, ice-COLD-PCR) has also been described. Finally, most recently, we developed yet another form of COLD-PCR, temperature-tolerant-COLD-PCR, which gradually increases the denaturation temperature during the COLD-PCR reaction, enriching diverse targets using a single cycling program. This report describes practical considerations for application of fast-, full-, ice-, and temperature-tolerant-COLD-PCR for enrichment of mutations prior to downstream screening.

An evaluation of allele frequency estimation accuracy using pooled sequencing data

Next generation sequencing technology has matured, and with its current affordability, will replace the SNP chip as the genotyping tool of choice. Even with the current affordability of NGS, large scale studies will require careful study design to reduce cost. In this study, we designed an experiment to assess the accuracy of allele frequency estimated from pooled sequencing data. We compared the allele frequency estimated from sequencing data with the allele frequency estimated from individual SNP chip data and observed high correlations between them. However, by calculating error rate, we found that many SNPs had their allele frequency estimated from sequencing data significantly different from allele frequency estimated from SNP chip data. In conclusion, we found correlation is not an ideal measurement for comparing allele frequencies. And for the purpose of estimating allele frequency, we do not recommend using pooling with NGS as a cheaper alternative to genotype each sample individually.

Maximum-parsimony haplotype frequencies inference based on a joint constrained sparse representation of pooled DNA

BACKGROUND

DNA pooling constitutes a cost effective alternative in genome wide association studies. In DNA pooling, equimolar amounts of DNA from different individuals are mixed into one sample and the frequency of each allele in each position is observed in a single genotype experiment. The identification of haplotype frequencies from pooled data in addition to single locus analysis is of separate interest within these studies as haplotypes could increase statistical power and provide additional insight.

RESULTS

We developed a method for maximum-parsimony haplotype frequency estimation from pooled DNA data based on the sparse representation of the DNA pools in a dictionary of haplotypes. Extensions to scenarios where data is noisy or even missing are also presented. The resulting method is first applied to simulated data based on the haplotypes and their associated frequencies of the AGT gene. We further evaluate our methodology on datasets consisting of SNPs from the first 7Mb of the HapMap CEU population. Noise and missing data were further introduced in the datasets in order to test the extensions of the proposed method. Both HIPPO and HAPLOPOOL were also applied to these datasets to compare performances.

CONCLUSIONS

We evaluate our methodology on scenarios where pooling is more efficient relative to individual genotyping; that is, in datasets that contain pools with a small number of individuals. We show that in such scenarios our methodology outperforms state-of-the-art methods such as HIPPO and HAPLOPOOL.

Evaluation of allele frequency estimation using pooled sequencing data simulation

Next-generation sequencing (NGS) technology has provided researchers with opportunities to study the genome in unprecedented detail. In particular, NGS is applied to disease association studies. Unlike genotyping chips, NGS is not limited to a fixed set of SNPs. Prices for NGS are now comparable to the SNP chip, although for large studies the cost can be substantial. Pooling techniques are often used to reduce the overall cost of large-scale studies. In this study, we designed a rigorous simulation model to test the practicability of estimating allele frequency from pooled sequencing data. We took crucial factors into consideration, including pool size, overall depth, average depth per sample, pooling variation, and sampling variation. We used real data to demonstrate and measure reference allele preference in DNAseq data and implemented this bias in our simulation model. We found that pooled sequencing data can introduce high levels of relative error rate (defined as error rate divided by targeted allele frequency) and that the error rate is more severe for low minor allele frequency SNPs than for high minor allele frequency SNPs. In order to overcome the error introduced by pooling, we recommend a large pool size and high average depth per sample.

Fast and accurate haplotype frequency estimation for large haplotype vectors from pooled DNA data

Background

Typically, the first phase of a genome wide association study (GWAS) includes genotyping across hundreds of individuals and validation of the most significant SNPs. Allelotyping of pooled genomic DNA is a common approach to reduce the overall cost of the study. Knowledge of haplotype structure can provide additional information to single locus analyses. Several methods have been proposed for estimating haplotype frequencies in a population from pooled DNA data.

Results

We introduce a technique for haplotype frequency estimation in a population from pooled DNA samples focusing on datasets containing a small number of individuals per pool (2 or 3 individuals) and a large number of markers. We compare our method with the publicly available state-of-the-art algorithms HIPPO and HAPLOPOOL on datasets of varying number of pools and marker sizes. We demonstrate that our algorithm provides improvements in terms of accuracy and computational time over competing methods for large number of markers while demonstrating comparable performance for smaller marker sizes. Our method is implemented in the "Tree-Based Deterministic Sampling Pool" (TDSPool) package which is available for download at http://www.ee.columbia.edu/~anastas/tdspool.

Conclusions

Using a tree-based determinstic sampling technique we present an algorithm for haplotype frequency estimation from pooled data. Our method demonstrates superior performance in datasets with large number of markers and could be the method of choice for haplotype frequency estimation in such datasets.

[Genetic scanning on chromosome 8 loci for coronary heart disease]

At present, genome-wide association study on coronary heart disease (CHD) has been carried out in several major medical research centers worldwide. Most studies of CHD susceptibility loci or regions focused on chromosome 1, 3, 9, 11 and 16, while studies on chromosome 8 are rare. To the best of our knowledge, the genome study on chromosome 8 about CHD in Chinese Han population has never been reported before. We aimed to identify CHD susceptibility loci or regions in the Chinese Han population. First, two separated DNA pooling samples were prepared from 156 CHD cases and 1000 normal controls. Then, a total of 13 microsatellite markers at an interval of 10 cM on chromosome 8 were selected for genetic scanning. Finally, the difference of allele frequency at each locus between two pooled samples was analyzed by Chi-square test. Significant differences were found between cases and controls at D8S264(8p23.3-p23.2) and D8S285(8q12.1) (both P<0.05). Therefore, 8p23.3-p23.2 and 8q12.1 are possible to be associated with CHD and further study is needed to screen susceptible genes around these regions.

Measuring molecular biomarkers in epidemiologic studies: laboratory techniques and biospecimen considerations

The future of personalized medicine depends on the ability to efficiently and rapidly elucidate a reliable set of disease-specific molecular biomarkers. High-throughput molecular biomarker analysis methods have been developed to identify disease risk, diagnostic, prognostic, and therapeutic targets in human clinical samples. Currently, high throughput screening allows us to analyze thousands of markers from one sample or one marker from thousands of samples and will eventually allow us to analyze thousands of markers from thousands of samples. Unfortunately, the inherent nature of current high throughput methodologies, clinical specimens, and cost of analysis is often prohibitive for extensive high throughput biomarker analysis. This review summarizes the current state of high throughput biomarker screening of clinical specimens applicable to genetic epidemiology and longitudinal population-based studies with a focus on considerations related to biospecimens, laboratory techniques, and sample pooling.

Optimality of group testing in the presence of misclassification

Several optimality properties of Dorfman's (1943) group testing procedure are derived for estimation of the prevalence of a rare disease whose status is classified with error. Exact ranges of disease prevalence are obtained for which group testing provides more efficient estimation when group size increases.

Ice-COLD-PCR enables rapid amplification and robust enrichment for low-abundance unknown DNA mutations

Identifying low-abundance mutations within wild-type DNA is important in several fields of medicine, including cancer, prenatal diagnosis and infectious diseases. However, utilizing the clinical and diagnostic potential of rare mutations is limited by sensitivity of the molecular techniques employed, especially when the type and position of mutations are unknown. We have developed a novel platform that incorporates a synthetic reference sequence within a polymerase chain reaction (PCR) reaction, designed to enhance amplification of unknown mutant sequences during COLD-PCR (CO-amplification at Lower Denaturation temperature). This new platform enables an Improved and Complete Enrichment (ice-COLD-PCR) for all mutation types and eliminates shortcomings of previous formats of COLD-PCR. We evaluated ice-COLD-PCR enrichment in regions of TP53 in serially diluted mutant and wild-type DNA mixtures. Conventional-PCR, COLD-PCR and ice-COLD-PCR amplicons were run in parallel and sequenced to determine final mutation abundance for a range of mutations representing all possible single base changes. Amplification by ice-COLD-PCR enriched all mutation types and allowed identification of mutation abundances down to 1%, and 0.1% by Sanger sequencing or pyrosequencing, respectively, surpassing the capabilities of other forms of PCR. Ice-COLD-PCR will help elucidate the clinical significance of low-abundance mutations and our understanding of cancer origin, evolution, recurrence-risk and treatment diagnostics.

A study of the efficiency of pooling in haplotype estimation

MOTIVATION

It has been claimed in the literature that pooling DNA samples is efficient in estimating haplotype frequencies. There is, however, no theoretical justification based on calculation of statistical efficiency. In fact, the limited evidence given so far is based on simulation studies with small numbers of loci. With rapid advance in technology, it is of interest to see if pooling is still efficient when the number of loci increases.

METHODS

Instead of resorting to simulation studies, we make use of asymptotic statistical theory to perform exact calculation of the efficiency of pooling relative to no pooling in the estimation of haplotype frequencies. As an intermediate step, we use the log-linear formulation of the haplotype probabilities and derive the asymptotic variance-covariance matrix of the maximum likelihood estimators of the canonical parameters of the log-linear model.

RESULTS

Based on our calculations under linkage equilibrium, pooling can suffer huge loss in efficiency relative to no pooling when there are more than three independent loci and the alleles are not rare. Pooling works better for rare alleles. In particular, if all the minor allele frequencies are 0.05, pooling maintains an advantage over no pooling until the number of independent loci reaches 6. High linkage disequilibrium effectively reduces the number of independent loci by ruling out certain haplotypes from occurring. Similar calculations of efficiency for the case of no pooling justify the common belief that it is not worthwhile to use molecular methods to resolve the phase ambiguity of individual genotype data.

AVAILABILITY

The R codes for the calculation are available at http://www.stat.nus.edu.sg/∼staxj/pooling

CONTACT

stakuka@nus.edu.sg.

[Genome-wide association study on complex diseases: study design and genetic markers]

Genome-wide association study used to be a dream of geneticists years ago, but now it came true. Since the first paper reported the finding of genetic variation contributing to human age-related macular degeneration by genome-wide association study in 2005, a numbers of whole genome studies have been published. The present paper reviewed some common comments in whole genome association study on complex diseases, including achievements of genome-wide association studies on complex traits or diseases, principles of study design, selection of genetic marker in genome, and comparisons of different commercial products for whole genome association study. Finally a newly defined genetic variation, copy number variation, was briefly introduced. This paper also summarized the shortcomings of current genome-wide association studies and perspectives of its future.

Computationally feasible estimation of haplotype frequencies from pooled DNA with and without Hardy-Weinberg equilibrium

MOTIVATION

Pooling large number of DNA samples is a common practice in association study, especially for initial screening. However, the use of expectation-maximization (EM)-type algorithms in estimating haplotype distributions for even moderate pool sizes is hampered by the computational complexity involved. A novel constrained EM algorithm called PoooL has been proposed recently to bypass the difficulty via the use of asymptotic normality of the pooled allele frequencies. The resulting estimates are, however, not maximum likelihood estimates and hence not optimal. Furthermore, the assumption of Hardy-Weinberg equilibrium (HWE) made may not be realistic in practice.

METHODS

Rather than carrying out constrained maximization as in PoooL, we revert to the usual EM algorithm but make it computationally feasible by using normal approximations. The resulting algorithm is much simpler to implement than PoooL because there is no need to invoke sophisticated iterative scaling methods as in PoooL. We also develop an estimating equation analogue of the EM algorithm for the case of Hardy-Weinberg disequilibrium (HWD) by conditioning on the haplotypes of both chromosomes of the same individual. Incorporated into the method is a way of estimating the inbreeding coefficient by relating it to overdispersion.

RESULTS

Simulation study assuming HWE shows that our simplified implementation of the EM algorithm leads to estimates with substantially smaller SDs than PoooL estimates. Further simulations show that ignoring HWD will induce biases in the estimates. Our extended method with estimation of inbreeding coefficient incorporated is able to reduce the bias leading to estimates with substantially smaller mean square errors. We also present results to suggest that our method can cope with a certain degree of locus-specific inbreeding as well as additional overdispersion not caused by inbreeding.

AVAILABILITY

http://staff.ustc.edu.cn/ approximately ynyang/aem-aes

Impact and quantification of the sources of error in DNA pooling designs

The analysis of genome wide variation offers the possibility of unravelling the genes involved in the pathogenesis of disease. Genome wide association studies are also particularly useful for identifying and validating targets for therapeutic intervention as well as for detecting markers for drug efficacy and side effects. The cost of such large-scale genetic association studies may be reduced substantially by the analysis of pooled DNA from multiple individuals. However, experimental errors inherent in pooling studies lead to a potential increase in the false positive rate and a loss in power compared to individual genotyping. Here we quantify various sources of experimental error using empirical data from typical pooling experiments and corresponding individual genotyping counts using two statistical methods. We provide analytical formulas for calculating these different errors in the absence of complete information, such as replicate pool formation, and for adjusting for the errors in the statistical analysis. We demonstrate that DNA pooling has the potential of estimating allele frequencies accurately, and adjusting the pooled allele frequency estimates for differential allelic amplification considerably improves accuracy. Estimates of the components of error show that differential allelic amplification is the most important contributor to the error variance in absolute allele frequency estimation, followed by allele frequency measurement and pool formation errors. Our results emphasise the importance of minimising experimental errors and obtaining correct error estimates in genetic association studies.

Molecular genetics of addiction and related heritable phenotypes: genome-wide association approaches identify "connectivity constellation" and drug target genes with pleiotropic effects

Genome-wide association (GWA) can elucidate molecular genetic bases for human individual differences in complex phenotypes that include vulnerability to addiction. Here, we review (a) evidence that supports polygenic models with (at least) modest heterogeneity for the genetic architectures of addiction and several related phenotypes; (b) technical and ethical aspects of importance for understanding GWA data, including genotyping in individual samples versus DNA pools, analytic approaches, power estimation, and ethical issues in genotyping individuals with illegal behaviors; (c) the samples and the data that shape our current understanding of the molecular genetics of individual differences in vulnerability to substance dependence and related phenotypes; (d) overlaps between GWA data sets for dependence on different substances; and (e) overlaps between GWA data for addictions versus other heritable, brain-based phenotypes that include bipolar disorder, cognitive ability, frontal lobe brain volume, the ability to successfully quit smoking, neuroticism, and Alzheimer's disease. These convergent results identify potential targets for drugs that might modify addictions and play roles in these other phenotypes. They add to evidence that individual differences in the quality and quantity of brain connections make pleiotropic contributions to individual differences in vulnerability to addictions and to related brain disorders and phenotypes. A "connectivity constellation" of brain phenotypes and disorders appears to receive substantial pathogenic contributions from individual differences in a constellation of genes whose variants provide individual differences in the specification of brain connectivities during development and in adulthood. Heritable brain differences that underlie addiction vulnerability thus lie squarely in the midst of the repertoire of heritable brain differences that underlie vulnerability to other common brain disorders and phenotypes.

The immunogenetics of multiple sclerosis

The discoveries in the 1970s of strong associations between various diseases and certain human leukocyte antigen (HLA) factors were a revolution within genetic epidemiology in the last century by demonstrating for the first time how genetic markers can help unravel the genetics of disorders with complex genetic backgrounds. HLA controls immune response genes and HLA associations indicate the involvement of autoimmunity. Multiple sclerosis (MS) was one of the first conditions proven to be HLA associated involving primarily HLA class II factors. We review how HLA studies give fundamental information on the genetics of the susceptibility to MS, on the importance of linkage disequilibrium in association studies, and on the pathogenesis of MS. The HLA-DRB1*1501 molecule may explain about 50% of MS cases and its role in the pathogenesis is supported by studies of transgenic mice. Studies of polymorphic non-HLA genetic markers are discussed based on linkage studies and candidate gene approaches including complete genome scans. No other markers have so far rivaled the importance of HLA in the genetic susceptibility to MS. Recently, large international collaborations provided strong evidence for the involvement of polymorphism of two cytokine receptor genes in the pathogenesis of MS: the interleukin 7 receptor alpha chain gene (IL7RA) on chromosome 5p13 and the interleukin 2 receptor alpha chain gene (IL2RA (=CD25)) on chromosome 10p15. It is estimated that the C allele of a single nucleotide polymorphism, rs6897932, within the alternative spliced exon 6 of IL7RA is involved in about 30% of MS cases.

Genes implicated in multiple sclerosis pathogenesis from consilience of genotyping and expression profiles in relapse and remission

Background

Multiple sclerosis (MS) is an inflammatory demyelinating disease of the central nervous system (CNS). Although the pathogenesis of MS remains unknown, it is widely regarded as an autoimmune disease mediated by T-lymphocytes directed against myelin proteins and/or other oligodendrocyte epitopes.

Methods

In this study we investigated the gene expression profiles of peripheral blood cells from patients with RRMS during the relapse and the remission phases utilizing gene microarray technology. Dysregulated genes encoded in regions associated with MS susceptibility from genomic screens or previous trancriptomic studies were identified. The proximal promoter region polymorphisms of two genes were tested for association with disease and expression level.

Results

Distinct sets of dysregulated genes during the relapse and remission phases were identified including genes involved in apoptosis and inflammation. Three of these dysregulated genes have been previously implicated with MS susceptibility in genomic screens: TGFβ1, CD58 and DBC1. TGFβ1 has one common SNP in the proximal promoter: -508 T>C (rs1800469). Genotyping two Australian trio sets (total 620 families) found a trend for over-transmission of the T allele in MS in females (p < 0.13). Upregulation of CD58 and DBC1 in remission is consistent with their putative roles in promoting regulatory T cells and reducing cell proliferation, respectively. A fourth gene, ALOX5, is consistently found over-expressed in MS. Two common genetic variants were confirmed in the ALOX5 putatve promoter: -557 T>C (rs12762303) and a 6 bp tandem repeat polymorphism (GGGCGG) between position -147 and -176; but no evidence for transmission distortion found.

Conclusion

The dysregulation of these genes tags their metabolic pathways for further investigation for potential therapeutic intervention.

A review of current approaches to identifying human genes involved in myopia

The prevalence of myopia is high in many parts of the world, particularly among the Orientals such as Chinese and Japanese. Like other complex diseases such as diabetes and hypertension, myopia is likely to be caused by both genetic and environmental factors, and possibly their interactions. Owing to multiple genes with small effects, genetic heterogeneity and phenotypic complexity, the study of the genetics of myopia poses a complex challenge. This paper reviews the current approaches to the genetic analysis of complex diseases and how these can be applied to the identification of genes that predispose humans to myopia. These approaches include parametric linkage analysis, non-parametric linkage analysis like allele-sharing methods and genetic association studies. Basic concepts, advantages and disadvantages of these approaches are discussed and explained using examples from the literature on myopia. Microsatellites and single nucleotide polymorphisms are common genetic markers in the human genome and are indispensable tools for gene mapping. High throughput genotyping of millions of such markers has become feasible and efficient with recent technological advances. In turn, this makes the identification of myopia susceptibility genes a reality.

Association study in the 5q31-32 linkage region for schizophrenia using pooled DNA genotyping

BACKGROUND

Several linkage studies suggest that chromosome 5q31-32 might contain risk loci for schizophrenia (SZ). We wanted to identify susceptibility genes for schizophrenia within this region.

METHODS

We saturated the interval between markers D5S666 and D5S436 with 90 polymorphic microsatellite markers and genotyped two sets of DNA pools consisting of 300 SZ patients of Bulgarian origin and their 600 parents. Positive associations were followed-up with SNP genotyping.

RESULTS

Nominally significant evidence for association (p < 0.05) was found for seven markers (D5S0023i, IL9, RH60252, 5Q3133_33, D5S2017, D5S1481, D5S0711i) which were then individually genotyped in the trios. The predicted associations were confirmed for two of the markers: D5S2017, localised in the SPRY4-FGF1 locus (p = 0.004) and IL9, localized within the IL9 gene (p = 0.014). Fine mapping was performed using single nucleotide polymorphisms (SNPs) around D5S2017 and IL9. In each region four SNPs were chosen and individually genotyped in our full sample of 615 SZ trios. Two SNPs showed significant evidence for association: rs7715300 (p = 0.001) and rs6897690 (p = 0.032). Rs7715300 is localised between the TGFBI and SMAD5 genes and rs6897690 is within the SPRY4 gene.

CONCLUSION

Our screening of 5q31-32 implicates three potential candidate genes for SZ: SMAD5, TGFBI and SPRY4.

A genome-wide association scan for asthma in a general Australian population

To date, almost every chromosome has been implicated in genetic susceptibility to asthma to some degree. When compared with single nucleotide polymorphism, microsatellite markers exhibit high levels of heterozygosity and therefore provide higher statistical power in association. The objective of this study was to perform a genome-wide association study using 23,465 in-house microsatellite markers to detect asthma susceptibility regions in the Busselton population. In this study, three separate pooled DNA screenings yielded 18 markers with significantly different estimated frequencies in the three separate "case and control" pools: each pool consisting of 60 males and 60 females. These markers were evaluated by individual typing in 360 cases and 360 controls. Two markers showed significant differences between cases and controls (P = 0.001 and P = 0.003). Regions surrounding the two markers were subjected to high-density association mapping with a total of 14 additional markers. We were able to confirm and fine map the association in these two regions by typing 14 additional microsatellite markers (1805A09 (D18S0325i), P = 0.002; 1806D05 (D18S0181i), P = 0.001). Each region contains a predicted gene that showed strong associations with asthma. Further studies are underway to characterize the novel candidate asthma susceptibility genes identified in this genome-wide study.

Association mapping using pooled DNA

The genetic dissection of complex disorders via genetic marker data has gained popularity in the postgenome era. Methods for typing genetic markers on human chromosomes continue to improve. Compared with the popular individual genotyping experiment, a pooled-DNA experiment (alleotyping experiment) is more cost effective when carrying out genetic typing. This chapter provides an overview of association mapping using pooled DNA and describes a five-stage study design including the preliminary calibration of peak intensities, estimation of allele frequency, single-locus association mapping, multilocus association mapping, and a confirmation study. Software and an analysis of authentic data are presented. The strengths and weaknesses of pooled-DNA analyses, as well as possible future applications for this method, are discussed.

HaploPool: improving haplotype frequency estimation through DNA pools and phylogenetic modeling

MOTIVATION

The search for genetic variants that are linked to complex diseases such as cancer, Parkinson's;, or Alzheimer's; disease, may lead to better treatments. Since haplotypes can serve as proxies for hidden variants, one method of finding the linked variants is to look for case-control associations between the haplotypes and disease. Finding these associations requires a high-quality estimation of the haplotype frequencies in the population. To this end, we present, HaploPool, a method of estimating haplotype frequencies from blocks of consecutive SNPs.

RESULTS

HaploPool leverages the efficiency of DNA pools and estimates the population haplotype frequencies from pools of disjoint sets, each containing two or three unrelated individuals. We study the trade-off between pooling efficiency and accuracy of haplotype frequency estimates. For a fixed genotyping budget, HaploPool performs favorably on pools of two individuals as compared with a state-of-the-art non-pooled phasing method, PHASE. Of independent interest, HaploPool can be used to phase non-pooled genotype data with an accuracy approaching that of PHASE. We compared our algorithm to three programs that estimate haplotype frequencies from pooled data. HaploPool is an order of magnitude more efficient (at least six times faster), and considerably more accurate than previous methods. In contrast to previous methods, HaploPool performs well with missing data, genotyping errors and long haplotype blocks (of between 5 and 25 SNPs).

The Finnish lapphund retinal atrophy locus maps to the centromeric region of CFA9

BACKGROUND

Dogs have the second largest number of genetic diseases, after humans. Among the diseases present in dogs, progressive retinal atrophy has been reported in more than a hundred breeds. In some of them, the mutation has been identified and genetic tests have allowed the identification of carriers, thus enabling a drastic reduction in the incidence of the disease. The Finnish lapphund is a dog breed presenting late-onset progressive retinal atrophy for which the disease locus remains unknown.

RESULTS

In this study we mapped the progressive retinal atrophy locus in the Finnish lapphund using a DNA pooling approach, assuming that all affected dogs within the breed share the same identical-by descent-mutation as the cause of the disease (genetic homogeneity). Autosomal recessive inheritance was also assumed, after ruling out, from pedigree analysis, dominant and X-linked inheritance. DNA from 12 Finnish lapphund cases was mixed in one pool, and DNA from 12 first-degree relatives of these cases was mixed to serve as the control pool. The 2 pools were tested with 133 microsatellite markers, 3 of which showed a shift towards homozygosity in the cases. Individual genotyping with these 3 markers confirmed homozygosity for the GALK1 microsatellite only (chromosome 9). Further individual genotyping with additional samples (4 cases and 59 controls) confirmed the association between this marker and the disease locus (p < 0.001). Closely related to this breed are the Swedish lapphund and the Lapponian herder for which a small number of retinal atrophy cases have been reported. Swedish lapphund cases, but not Lapponian herder cases, had the same GALK1 microsatellite genotype as Finnish lapphund cases.

CONCLUSION

The locus for progressive rod-cone degeneration is known to be close to the GALK1 locus, on the telomeric region of chromosome 9, where the retinal atrophy locus of the Finnish lapphund has been mapped. This suggests that the disease in this breed, as well as in the Swedish lapphund, may correspond to progressive rod-cone degeneration. This would increase the number of known dog breeds having this particular form of progressive retinal atrophy.

Applicability of DNA pools on 500 K SNP microarrays for cost-effective initial screens in genomewide association studies

Background

Genetic influences underpinning complex traits are thought to involve multiple quantitative trait loci (QTLs) of small effect size. Detection of such QTL associations requires systematic screening of large numbers of DNA markers within large sample populations. Using pooled DNA on SNP microarrays to screen for allelic frequency differences between groups such as cases and controls (called SNP Microarray and Pooling, or SNP-MaP) has been validated as an efficient solution on both 10 k and 100 k platforms. We demonstrate that this approach can be effectively applied to the truly genomewide Affymetrix GeneChip^® Mapping 500 K Array.

Results

In comparisons between five independent DNA pools (N ~200 per pool) on separate Affymetrix GeneChip^® Mapping 500 K Array sets, we show that, for SNPs with minor allele frequencies > 0.05, the reliability of the rank order of estimated allele frequencies, assessed as the average correlation between allele frequency estimates across the DNA pools, was 0.948 (average mean difference across the five pools = 0.069). Similarly, validity of the SNP-MaP approach was demonstrated by a rank-order correlation of 0.937 (average mean difference = 0.095) between the average DNA pool allele frequency estimates and the allele frequencies of an independent (CEPH) sample of 60 unrelated individually genotyped subjects.

Conclusion

We conclude that SNP-MaP can be extended for use on the Affymetrix GeneChip^® Mapping 500 K Array, providing a cost-effective, reliable and valid initial screen of 500 K SNP microarrays in genomewide association scans.

High-resolution mapping for essential hypertension using microsatellite markers

During the past decade, considerable efforts and resources have been devoted to elucidating the multiple genetic and environmental determinants responsible for hypertension and its associated cardiovascular diseases. The success of positional cloning, fine mapping, and linkage analysis based on whole-genome screening, however, has been limited in identifying multiple genetic determinants affecting diseases, suggesting that new research strategies for genome-wide typing may be helpful. Disease association (case-control) studies using microsatellite markers, distributed every 150 kb across the human genome, may have some advantages over linkage, candidate, and single nucleotide polymorphism typing methods in terms of statistical power and linkage disequilibrium for finding genomic regions harboring candidate disease genes, although it is not proven. We have carried out genome-wide mapping using 18,977 microsatellite markers in a Japanese population composed of 385 hypertensive patients and 385 normotensive control subjects. Pooled sample analysis was conducted in a 3-stage genomic screen of 3 independent case-control populations, and 54 markers were extracted from the original 18,977 microsatellite markers. As a final step, each single positive marker was confirmed by individual typing, and only 19 markers passed this test. We identified 19 allelic loci that were significantly different between the cases of essential hypertension and the controls.

A new era in the genetic analysis of multiple sclerosis

PURPOSE OF REVIEW

This review covers the latest developments in the genetic analysis of multiple sclerosis in the context of advancing knowledge about the nature of complex disease. This year has seen rapid progress dominated by early applications of high-throughput single-nucleotide polymorphism typing technology.

RECENT FINDINGS

The last 12 months have seen the completion of what is probably a definitive screen for linkage, together with the beginnings of indirect full-genome screens for association with common variants. Alongside this the first ever systematic admixture mapping effort has also been completed, suggesting a possible explanation for the apparent excess of the condition in Europeans and implicating a novel susceptibility locus on chromosome 1.

SUMMARY

It is now clear that association-based studies in large cohorts will be needed to unravel the genetic basis of susceptibility to multiple sclerosis. Importantly it is also clear that the necessary tools have now arrived and that the next few years are likely to see exciting developments.

Pooled association genome scanning for alcohol dependence using 104,268 SNPs: validation and use to identify alcoholism vulnerability loci in unrelated individuals from the collaborative study on the genetics of alcoholism

Association genome scanning can identify markers for the allelic variants that contribute to vulnerability to complex disorders, including alcohol dependence. To improve the power and feasibility of this approach, we report validation of "100k" microarray-based allelic frequency assessments in pooled DNA samples. We then use this approach with unrelated alcohol-dependent versus control individuals sampled from pedigrees collected by the Collaborative Study on the Genetics of Alcoholism (COGA). Allele frequency differences between alcohol-dependent and control individuals are assessed in quadruplicate at 104,268 autosomal SNPs in pooled samples. One hundred eighty-eight SNPs provide (1) the largest allele frequency differences between dependent versus control individuals; (2) t values >or= 3 for these differences; and (3) clustering, so that 51 relatively small chromosomal regions contain at least three SNPs that satisfy criteria 1 and 2 above (Monte Carlo P = 0.00034). These positive SNP clusters nominate interesting genes whose products are implicated in cellular signaling, gene regulation, development, "cell adhesion," and Mendelian disorders. The results converge with linkage and association results for alcohol and other addictive phenotypes. The data support polygenic contributions to vulnerability to alcohol dependence. These SNPs provide new tools to aid the understanding, prevention, and treatment of alcohol abuse and dependence.

Bayesian method for gene detection and mapping, using a case and control design and DNA pooling

Association mapping studies aim to determine the genetic basis of a trait. A common experimental design uses a sample of unrelated individuals classified into 2 groups, for example cases and controls. If the trait has a complex genetic basis, consisting of many quantitative trait loci (QTLs), each group needs to be large. Each group must be genotyped at marker loci covering the region of interest; for dense coverage of a large candidate region, or a whole-genome scan, the number of markers will be very large. The total amount of genotyping required for such a study is formidable. A laboratory effort efficient technique called DNA pooling could reduce the amount of genotyping required, but the data generated are less informative and require novel methods for efficient analysis. In this paper, a Bayesian statistical analysis of the classic model of McPeek and Strahs is proposed. In contrast to previous work on this model, I assume that data are collected using DNA pooling, so individual genotypes are not directly observed, and also account for experimental errors. A complete analysis can be performed using analytical integration, a propagation algorithm for a hidden Markov model, and quadrature. The method developed here is both statistically and computationally efficient. It allows simultaneous detection and mapping of a QTL, in a large-scale association mapping study, using data from pooled DNA. The method is shown to perform well on data sets simulated under a realistic coalescent-with-recombination model, and is shown to outperform classical single-point methods. The method is illustrated on data consisting of 27 markers in an 880-kb region around the CYP2D6 gene.

Linkage disequilibrium screening for multiple sclerosis implicates JAG1 and POU2AF1 as susceptibility genes in Europeans

By combining all the data available from the Genetic Analysis of Multiple sclerosis in EuropeanS (GAMES) project, we have been able to identify 17 microsatellite markers showing consistent evidence for apparent association. As might be expected five of these markers map within the Major Histocompatibility Complex (MHC) and are in LD with HLA-DRB1. Individual genotyping of the 12 non-MHC markers confirmed association for three of them--D11S1986, D19S552 and D20S894. Association mapping across the candidate genes implicated by these markers in 937 UK trio families revealed modestly associated haplotypes in JAG1 (p=0.019) on chromosome 20p12.2 and POU2AF1 (p=0.003) on chromosome 11q23.1.

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.

Genomewide association analysis of human narcolepsy and a new resistance gene

Human narcolepsy is a hypersomnia that is affected by multiple genetic and environmental factors. One genetic factor strongly associated with narcolepsy is the HLA-DRB1*1501-DQB1*0602 haplotype in the human leukocyte antigen region on chromosome 6, whereas the other genetic factors are not clear. To discover additional candidate regions for susceptibility or resistance to human narcolepsy, we performed a genomewide association study, using 23,244 microsatellite markers. Two rounds of screening with the use of pooled DNAs yielded 96 microsatellite markers (including 16 markers on chromosome 6) with significantly different estimated frequencies in case and control pools. Markers not located on chromosome 6 were evaluated by the individual typing of 95 cases and 95 controls; 30 markers still showed significant associations. A strong association was displayed by a marker on chromosome 21 (21q22.3). The surrounding region was subjected to high-density association mapping with 14 additional microsatellite markers and 74 SNPs. One microsatellite marker (D21S0012m) and two SNPs (rs13048981 and rs13046884) showed strong associations (P < .0005; odds ratios 0.19-0.33). These polymorphisms were in a strong linkage disequilibrium, and no other polymorphism in the region showed a stronger association with narcolepsy. The region contains three predicted genes--NLC1-A, NLC1-B, and NLC1-C--tentatively named "narcolepsy candidate-region 1 genes," and NLC1-A and NLC1-C were expressed in human hypothalamus. Reporter-gene assays showed that the marker D21S0012m in the promoter region and the SNP rs13046884 in the intron of NLC1-A significantly affected expression levels. Therefore, NLC1-A is considered to be a new resistance gene for human narcolepsy.

Quantify single nucleotide polymorphism (SNP) ratio in pooled DNA based on normalized fluorescence real-time PCR

Background

Conventional real-time PCR to quantify the allele ratio in pooled DNA mainly depends on PCR amplification efficiency determination and Ct value, which is defined as the PCR cycle number at which the fluorescence emission exceeds the fixed threshold. Because of the nature of exponential calculation, slight errors are multiplied and the variations of the results seem too large. We have developed a new PCR data point analysis strategy for allele ratio quantification based on normalized fluorescence ratio.

Results

In our method, initial reaction background fluorescence was determined based upon fitting of raw fluorescence data to four-parametric sigmoid function. After that, each fluorescence data point was first subtracted by respective background fluorescence and then each subtracted fluorescence data point was divided by the specific background fluorescence to get normalized fluorescence. By relating the normalized fluorescence ratio to the premixed known allele ratio of two alleles in standard samples, standard linear regression equation was generated, from which unknown specimens allele ratios were extrapolated using the measured normalized fluorescence ratio. In this article, we have compared the results of the proposed method with those of baseline subtracted fluorescence ratio method and conventional Ct method.

Conclusion

Results demonstrated that the proposed method could improve the reliability, precision, and repeatability for quantifying allele ratios. At the same time, it has the potential of fully automatic allelic ratio quantification.

Two-stage designs in case-control association analysis

DNA pooling is a cost-effective approach for collecting information on marker allele frequency in genetic studies. It is often suggested as a screening tool to identify a subset of candidate markers from a very large number of markers to be followed up by more accurate and informative individual genotyping. In this article, we investigate several statistical properties and design issues related to this two-stage design, including the selection of the candidate markers for second-stage analysis, statistical power of this design, and the probability that truly disease-associated markers are ranked among the top after second-stage analysis. We have derived analytical results on the proportion of markers to be selected for second-stage analysis. For example, to detect disease-associated markers with an allele frequency difference of 0.05 between the cases and controls through an initial sample of 1000 cases and 1000 controls, our results suggest that when the measurement errors are small (0.005), approximately 3% of the markers should be selected. For the statistical power to identify disease-associated markers, we find that the measurement errors associated with DNA pooling have little effect on its power. This is in contrast to the one-stage pooling scheme where measurement errors may have large effect on statistical power. As for the probability that the disease-associated markers are ranked among the top in the second stage, we show that there is a high probability that at least one disease-associated marker is ranked among the top when the allele frequency differences between the cases and controls are not <0.05 for reasonably large sample sizes, even though the errors associated with DNA pooling in the first stage are not small. Therefore, the two-stage design with DNA pooling as a screening tool offers an efficient strategy in genomewide association studies, even when the measurement errors associated with DNA pooling are nonnegligible. For any disease model, we find that all the statistical results essentially depend on the population allele frequency and the allele frequency differences between the cases and controls at the disease-associated markers. The general conclusions hold whether the second stage uses an entirely independent sample or includes both the samples used in the first stage and an independent set of samples.

Evaluation of DNA pooling for the estimation of microsatellite allele frequencies: a case study using striped bass (Morone saxatilis)

Using striped bass (Morone saxatilis) and six multiplexed microsatellite markers, we evaluated procedures for estimating allele frequencies by pooling DNA from multiple individuals, a method suggested as cost-effective relative to individual genotyping. Using moment-based estimators, we estimated allele frequencies in experimental DNA pools and found that the three primary laboratory steps, DNA quantitation and pooling, PCR amplification, and electrophoresis, accounted for 23, 48, and 29%, respectively, of the technical variance of estimates in pools containing DNA from 2-24 individuals. Exact allele-frequency estimates could be made for pools of sizes 2-8, depending on the locus, by using an integer-valued estimator. Larger pools of size 12 and 24 tended to yield biased estimates; however, replicates of these estimates detected allele frequency differences among pools with different allelic compositions. We also derive an unbiased estimator of Hardy-Weinberg disequilibrium coefficients that uses multiple DNA pools and analyze the cost-efficiency of DNA pooling. DNA pooling yields the most potential cost savings when a large number of loci are employed using a large number of individuals, a situation becoming increasingly common as microsatellite loci are developed in increasing numbers of taxa.