Marker Allele Frequencies Research Articles

Effect of Population Stratification on False Positive Rates of Population‐Based Association Analyses of Quantitative Traits

It is now well established that population stratification can result in spurious association findings in genetic case-control studies. However, very few studies have addressed similar issues for mapping quantitative traits. Because quantitative phenotypes are often precursors of clinical endpoint traits and carry more information on within-genotype trait variability, it has been argued that studying these quantitative traits may be a more powerful strategy to map genes than the binary clinical endpoints. Thus, it is of interest to evaluate the adverse effects of population stratification on the analyses of quantitative traits. The popular statistical tests of association for quantitative traits using population level data are ANOVA, linear regression with an additive allelic effect and Kruskal-Wallis. We have theoretically studied the marginal effects of genetic heterogeneity and phenotypic heterogeneity as well as their joint effects on the false positive rates of these three tests. We have carried out extensive simulations under different genetic models and probability distributions of quantitative traits to assess the rate of false positives in the presence of population stratification. We find that the rate of false positives increases very quickly with simultaneous increase in differences in the standardized phenotypic means and marker allele frequencies in the subpopulations.

Exploring correlations among copy number variants

There have been a great many recent studies investigating the extent of Copy Number Variation in the genomes of various species such as human, cattle, dogs and many others. The results from these studies indicate that the extent of the Copy Number Variation in the genome is considerable, and that in humans and in cattle, frequencies of different Copy Number Variants may differ in different breeds/ethnicities. This is not entirely unexpected as allele frequencies of certain loci vary with different breeds/ ethnicities/species and many known Copy Number Variants behave similarly to ordinary markers as regards Mendelian segregation. It is also well known in many instances, species/breeds/ethnicities show variation not only in marker allele frequencies, but also in the extent of Linkage Disequilibrium between markers. Thus it is worth investigating the extent of association between Copy Number Variants in different populations. In this paper we will investigate the extent of correlations between selected Copy Number Variants in different human populations and show that statistically significant correlations exist and are strongly population dependent.

New Insights in the Pathogenesis of MGUS, Multiple Myeloma (MM) and Waldenström‘s Macroglobulinemia (WM): Chronic Antigenic Stimulation by Autoantigenic Targets of Paraproteins Is Mediated by CD4+ t-Cells

Abstract 472Hyperphosphorylated paratarg-7 (pP-7) is the target of paraproteins in 15% of Caucasian, 4.5% of Asian and 28% of Afro-American patients with MGUS/MM. Carriers of pP-7 have an 8 to 13 times increased risk to develop IgA/IgG-MGUS and multiple myeloma (Grass et al., Lancet Oncology 2009; 10:950–956) and a 6.5 times increased risk to develop IgM-MGUS and Waldenstrom‘s macroglobulinemia (Grass et al., Blood. 2011 Mar 10;117(10):2918–23.). Analysis of affected families showed that pP-7 is inherited in a dominant fashion, explaining cases of familial MGUS/MM/WM. Since paratarg-7 is hyperphosphorylated and inherited in a dominant fashion, we extended our studies to investigate the prevalence of further antigenic targets of paraproteins and their phosphorylation state. All (8/8) autoantigenic paraprotein target (paratargs no. 2, 5, 6, 7, 8, 9, 10, and 11) moleculary defined to date were shown to be hyperphosphorylated in the respective patients compared to normal controls, and the hyperphosphorylation state of the respective paraproteins targets was shown to be inherited in a dominant fashion for all autoantigenic paraprotein targets for which enough family members were available for such an analysis. The consistent finding of hyperphosphorylation of autoantigenic paraprotein targets suggests a common underlying mechanism associated with the pathogenesis of MGUS/MM, and implies a significant role of the hyperphosphorylation state in the pathogenesis of these neoplasms. Co-immunoprecipitation identified PKCzeta as the kinase responsible for the phosphorylation of most and PP2A as the phosphatase responsible for the dephosphorylation of all hyperphosphorylated autoantigenic targets of paraproteins. SNPs or mutations of PKCzeta and PP2A as the reason for the abnormal phosphorylation of the paraproteins targets were excluded. However, PP2A was shown to be inactivated by phosphorylation of its catalytic subunit at Y307. To determine the SNP or mutation which is associated with the inactivation of PP2A we carried out a genome-wide linkage analysis. We found strong evidence for a parametric linkage (full penetrant autosomal dominant model; disease marker allele frequency=0.02) with a LOD score of 5.9 on chromosome 4q35.For pP-7 hyperphosphorylation we demonstrated that the hyperphosphrylation is due to an single additional phosphorylation at serine 17, which is located in the paraprotein-binding epitope of pP-7. Analysis of the T-cell response against normo- and hyperphosphorylated paratarg-7 derived peptides in affected and non-affected family members demonstrated that pP-7, but not wild-type p-7 induces a strong and specific CD4+ T-cell response in the patients with pP-7, which was shown to be HLA-DQ and HLA-DR restricted. This suggests that pP-7 confers a chronic antigenic stimulation which is mediated by CD4+ T-cells and that these pP-7 specific CD4+ T-cells stimulate a B-cell clone with the same specificity, eventually resulting in the clonal evolution of this B-cell clone. In summary, our results support the hypothesis of a role of chronic autoantigenic stimulation in the pathogenesis of MGUS/MM/WM. Indviduals carrying pP-7 are at particular risk, if their MHC-II haplotype allows the recognition of pP-7 derived antigenic peptides by their CD4+ T cells. We suggest that the different prevalence of pP-7 carriers and defined MHC-II haplotypes explain the different incidence rates of MGUS/MM/WM in different ethnic groups. Disclosures:Preuss:Ludwig Institute for Cancer Research: Patents & Royalties. Pfreundschuh:Ludwig Institute for Cancer Research: Patents & Royalties.

Translation Initiator EIF4G1 Mutations in Familial Parkinson Disease

Genome-wide analysis of a multi-incident family with autosomal-dominant parkinsonism has implicated a locus on chromosomal region 3q26-q28. Linkage and disease segregation is explained by a missense mutation c.3614G>A (p.Arg1205His) in eukaryotic translation initiation factor 4-gamma (EIF4G1). Subsequent sequence and genotype analysis identified EIF4G1 c.1505C>T (p.Ala502Val), c.2056G>T (p.Gly686Cys), c.3490A>C (p.Ser1164Arg), c.3589C>T (p.Arg1197Trp) and c.3614G>A (p.Arg1205His) substitutions in affected subjects with familial parkinsonism and idiopathic Lewy body disease but not in control subjects. Despite different countries of origin, persons with EIF4G1 c.1505C>T (p.Ala502Val) or c.3614G>A (p.Arg1205His) mutations appear to share haplotypes consistent with ancestral founders. eIF4G1 p.Ala502Val and p.Arg1205His disrupt eIF4E or eIF3e binding, although the wild-type protein does not, and render mutant cells more vulnerable to reactive oxidative species. EIF4G1 mutations implicate mRNA translation initiation in familial parkinsonism and highlight a convergent pathway for monogenic, toxin and perhaps virally-induced Parkinson disease.

Optimal use of regression models in genome‐wide association studies

The performance of linear regression models in genome-wide association studies is influenced by how marker information is parameterized in the model. Considering the impact of parameterization is especially important when using information from multiple markers to test for association. Properties of the population, such as linkage disequilibrium (LD) and allele frequencies, will also affect the ability of a model to provide statistical support for an underlying quantitative trait locus (QTL). Thus, for a given location in the genome, the relationship between population properties and model parameterization is expected to influence the performance of the model in providing evidence for the position of a QTL. As LD and allele frequencies vary throughout the genome and between populations, understanding the relationship between these properties and model parameterization is of considerable importance in order to make optimal use of available genomic data. Here, we evaluate the performance of regression-based association models using genotype and haplotype information across the full spectrum of allele frequency and LD scenarios. Genetic marker data from 200 broiler chickens were used to simulate genomic conditions by selecting individual markers to act as surrogate QTL (sQTL) and then investigating the ability of surrounding markers to estimate sQTL genotypes and provide statistical support for their location. The LD and allele frequencies of markers and sQTL are shown to have a strong effect on the performance of models relative to one another. Our results provide an indication of the best choice of model parameterization given certain scenarios of marker and QTL LD and allele frequencies. We demonstrate a clear advantage of haplotype-based models, which account for phase uncertainty over other models tested, particularly for QTL with low minor allele frequencies. We show that the greatest advantage of haplotype models over single-marker models occurs when LD between markers and the causal locus is low. Under these situations, haplotype models have a greater accuracy of predicting the location of the QTL than other models tested.

Mapping Mendelian traits in asexual progeny using changes in marker allele frequency.

Linkage between markers and genes that affect a phenotype of interest may be determined by examining differences in marker allele frequency in the extreme progeny of a cross between two inbred lines. This strategy is usually employed when pooling is used to reduce genotyping costs. When the cross progeny are asexual, the extreme progeny may be selected by multiple generations of asexual reproduction and selection. We analyse this method of measuring phenotype in asexual progeny and examine the changes in marker allele frequency due to selection over many generations. Stochasticity in marker frequency in the selected population arises due to the finite initial population size. We derive the distribution of marker frequency as a result of selection at a single major locus, and show that in order to avoid spurious changes in marker allele frequency in the selected population, the initial population size should be in the low to mid hundreds.

Family-Based Genetic Association Tests

INTRODUCTIONGenetic studies in families have historically focused on tests of linkage. These tests measure the concordance between the pattern of segregation of a genetic marker allele with the occurrence of a disease phenotype within families and provide information about the amount of genetic recombination between a marker locus and a putative disease locus. Thus, linkage is a statement about transmission of gametes from parents to offspring. In contrast, association is a statement about the population of gametes. Frequencies of marker alleles in disease and nondisease individuals give us information about the amount of association, or correlation, between marker allele and disease status. Family data not only provide us information about linkage by looking at transmissions within families, but also give us information about association by looking at allelic state and the presence of disease phenotype across families. This chapter describes the evolution of family-based tests of association as well as the variety of applications for these tests.

Case–case genome-wide association analysis shows markers differentially associated with schizophrenia and bipolar disorder and implicates calcium channel genes

There are theoretical reasons why comparing marker allele frequencies between cases of different diseases, rather than with controls, may offer benefits. The samples may be better matched, especially for background risk factors common to both diseases. Genetic loci may also be detected which influence which of the two diseases occurs if common risk factors are present. We used samples of UK bipolar and schizophrenic cases that had earlier been subject to genome-wide association studies and compared marker allele frequencies between the two samples. When these differed for a marker, we compared the case sample allele frequencies with those of a control sample. Eight markers were significant at P value of less than 10(-5). Of these, the most interesting finding was for rs17645023, which was significant at P value of less than 10(-6) and which lies 36 kb from CACNG5. Control allele frequencies for this marker were intermediate between those for bipolar and schizophrenic cases. The application of this approach suggests that it does have some merits. The finding for CACNG5, taken together with the earlier implication of CACNA1C and CACNA1B, strongly suggests a key role for voltage-dependent calcium channel genes in the susceptibility to bipolar disorder and/or schizophrenia.

Population-Specific Documentation of Pharmacogenomic Markers and Their Allelic Frequencies in Findbase

Population and ethnic group-specific allele frequencies of pharmacogenomic markers are poorly documented and not systematically collected in structured data repositories. We developed the Frequency of Inherited Disorders Pharmacogenomics database (FINDbase-PGx), a separate module of the FINDbase, aiming to systematically document pharmacogenomic allele frequencies in various populations and ethnic groups worldwide. We critically collected and curated 214 scientific articles reporting pharmacogenomic markers allele frequencies in various populations and ethnic groups worldwide. Subsequently, in order to host the curated data, support data visualization and data mining, we developed a website application, utilizing Microsoft™ PivotViewer software. Curated allelic frequency data pertaining to 144 pharmacogenomic markers across 14 genes, representing approximately 87,000 individuals from 150 populations worldwide, are currently included in FINDbase-PGx. A user-friendly query interface allows for easy data querying, based on numerous content criteria, such as population, ethnic group, geographical region, gene, drug and rare allele frequency. FINDbase-PGx is a comprehensive database, which, unlike other pharmacogenomic knowledgebases, fulfills the much needed requirement to systematically document pharmacogenomic allelic frequencies in various populations and ethnic groups worldwide.

Investigation of the interleukin-1 gene cluster polymorphisms in Jordanian patients with chronic and aggressive periodontitis

Objective Interleukin-1 (IL-1) is a proinflammatory cytokine that is highly elevated in response to bacterial biofilms and is a potential risk factor for periodontal diseases. IL-1 gene polymorphisms have been associated with the IL-1 level. The aim of this study was to investigate if IL-1 gene cluster polymorphisms are associated with chronic (CP) and aggressive (AgP) periodontitis in a Jordanian population. Methods A total of 100 CP, 80 AgP patients and 80 controls were genotyped using PCR for IL-1RN-86-bp VNTR and PCR-RFLP for IL-1A-889, IL-1B-511, -35, +3953, and IL-1RN +8006, +9589, +11100 SNPs. The distribution of alleles and genotypes between groups was compared using χ 2 analysis. Estimation of haplotype frequencies was carried out using the EH programme. Results The IL-1RN8006 SNP and the IL-1RN-VNTR were associated with CP but not with AgP. The C allele and TC genotype of IL-1RN8006 were increased in CP ( P corr = 0.002, 0.00026 respectively). The A1 allele and A1/A1 genotype of the IL1-RN-VNTR were significantly increased in CP ( P corr = 0.0007, <0.0001 respectively). The CA1 haplotype formed by both markers was present in 29 CP patients but not in any of the controls ( P < 0.0001). No significant differences were found in the distribution of allele and genotype frequencies of the other markers between CP and AgP cases and controls. Conclusions IL-1RN 8006 and IL-1RN VNTR were associated with CP but not AgP in a Jordanian population, whilst other investigated markers in IL-1A, IL-1B and IL-1RN were not associated with either CP or AgP.

NordicDB: a Nordic pool and portal for genome-wide control data

A cost-efficient way to increase power in a genetic association study is to pool controls from different sources. The genotyping effort can then be directed to large case series. The Nordic Control database, NordicDB, has been set up as a unique resource in the Nordic area and the data are available for authorized users through the web portal (http://www.nordicdb.org). The current version of NordicDB pools together high-density genome-wide SNP information from ∼5000 controls originating from Finnish, Swedish and Danish studies and shows country-specific allele frequencies for SNP markers. The genetic homogeneity of the samples was investigated using multidimensional scaling (MDS) analysis and pairwise allele frequency differences between the studies. The plot of the first two MDS components showed excellent resemblance to the geographical placement of the samples, with a clear NW-SE gradient. We advise researchers to assess the impact of population structure when incorporating NordicDB controls in association studies. This harmonized Nordic database presents a unique genome-wide resource for future genetic association studies in the Nordic countries.

Long-term genetic stability and population dynamics of laboratory strains of Schistosoma mansoni.

Measures of genetic differentiation between populations are useful tools for understanding the long-term dynamics of parasite communities. We followed the allele frequencies of microsatellite markers in samples taken over a period of 16 yr from the Case Western Reserve University-Naval Medical Research Institute (CWRU-NMRI) laboratory strain of Schistosoma mansoni. DNA was isolated from pooled samples of adults, eggs, or cercariae collected at 46 time points and genotyped for 14 tri- or tetranucleotide microsatellite markers. For comparison, 2 S. mansoni reference strains (Biomedical Research Institute-NMRI, which has a common origin with the CWRU line, and PR-1) were analyzed over shorter periods of time. We observed that the long-term allele frequencies are generally stable in large laboratory populations of this parasite, and a high degree of similarity was observed between the allele frequencies of consecutive samples from different developmental stages. The CWRU strain, however, showed 2 periods of marked deviation from stability as demonstrated using genetic differentiation measures. The first period corresponds to an admixture event with the BRI strain in which a new equilibrium was established as the "migrants" became blended into the existing CWRU population, consistent with 23% admixture from BRI. The second corresponds to a period of genetic drift when the CWRU population size was greatly reduced with an accompanying loss in genetic diversity. Having demonstrated the utility of pooled samples for the genetic analysis of population dynamics in laboratory strains of schistosomes, this approach will be useful for analyzing field samples to determine the impact of schistosomiasis control programs on parasite population structure. Accounting only for the intensity or prevalence of parasite populations may fail to register significant changes in population structure that could have implications for resistance, morbidity, and the design of control measures.

Abstract 1169: Paratarg-7, the first autosomal-dominantly inherited risk factor for hematological malignancies: single nucelotide poylmorphism- and microsatellite-based genome-wide linkage analysis

Abstract Background: Antigenic targets of paraproteins in monoclonal gammopathy of undetermined significance (MGUS), multiple Myeloma (MM) and Waldenstrom's macroglobulinemia (WM) might play a role in the pathogenesis of these neoplasms by chronic antigenic stimulation, but very few have been identified, of which most were specific for one individual paraprotein only. In contrast, we recently described paratarg-7, a protein of unknown function which is expressed in all human tissues as the target of 15% of IgA and IgG paraproteins in MGUS and MM. Mutations or polymorphisms of paratarg-7 were not found, but hyperphosphorylation was detected in 35/252 (14%) of MGUS/MM patients and in 18/161 (11%) of WM patients, all of whom had an anti-paratarg-7 specific paraprotein. Analysis of 16 families demonstrated that hyperphosphorylated paratarg-7 is inherited in a dominant fashion and carriers of hyperphosphorylated paratarg-7 have an increased risk of developing MGUS/MM/WM (odds ratio 7.9; 95% CI: 2.8-22.6, p=0.0001). The aim of this study was to identify chromosome regions linked to hyperphosphorylated paratarg-7, a frequent antigenic target of paraproteins in MGUS/MM/WM. Methods: Serum and peripheral blood cells were obtained from 90 relatives of 16 families of patients with MGUS/MM/WM. We used a high density, single nucleotide polymorphism genotyping assay, the Illumina SentrixR BeadChip Array, the HumanHap300-Duo Bead Chip, comprising 318.000 tag single nucleotide polymorphisms to perform a genome-wide linkage analysis of 48 relatives of 4 families by filtering 23211 SNP markers with a spacing of &amp;gt; 100kb and an allele frequency &amp;gt; 0.15. Additionally, we carried out non-parametric as well as parametric analyses based on the genotypes of different microsatellite markers. Results: We found strong evidence for parametric linkage (full penetrant autosomal dominant model; disease marker allele frequency=0.02; LOD= 5.9) and non-parametric linkage (Zmean= 5.1; P&amp;lt;10−5) on chromosome 4q35. Conclusions: Hyperphosphorylated paratarg-7 is a highly significant risk factor for MGUS, WM and MM, with the highest odds ratio of any risk factor reported to date for these diseases. We report the first genome-wide linkage study of a new molecularly defined risk factor of MGUS//MM/WM and novel loci on 4q35 linked to hyperphosphorylated paratarg-7. Identification of novel causative genes for MGUS/MM/WM will now advance our understanding of the pathogenesis in these diseases. Note: This abstract was not presented at the AACR 101st Annual Meeting 2010 because the presenter was unable to attend. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1169.

Beyond MHC: signals of elevated selection pressure on Atlantic salmon (Salmo salar) immune‐relevant loci

Using Atlantic salmon (Salmo salar) as a model system, we investigated whether 18 microsatellites tightly linked to immune-relevant genes have experienced different selection pressures than 76 loci with no obvious association with immune function. Immune-relevant loci were identified as outliers by two outlier tests significantly more often than nonimmune linked loci (22% vs. 1.6%). In addition, the allele frequencies of immune relevant markers were more often correlated with latitude and temperature. Combined, these results support the hypothesis that immune-relevant loci more frequently exhibit footprints of selection than other loci. They also indicate that the correlation between immune-relevant loci and latitude may be due to temperature-induced differences in pathogen-driven selection or some other environmental factor correlated with latitude.

Correcting for cryptic relatedness by a regression-based genomic control method

BackgroundGenomic control (GC) method is a useful tool to correct for the cryptic relatedness in population-based association studies. It was originally proposed for correcting for the variance inflation of Cochran-Armitage's additive trend test by using information from unlinked null markers, and was later generalized to be applicable to other tests with the additional requirement that the null markers are matched with the candidate marker in allele frequencies. However, matching allele frequencies limits the number of available null markers and thus limits the applicability of the GC method. On the other hand, errors in genotype/allele frequencies may cause further bias and variance inflation and thereby aggravate the effect of GC correction.ResultsIn this paper, we propose a regression-based GC method using null markers that are not necessarily matched in allele frequencies with the candidate marker. Variation of allele frequencies of the null markers is adjusted by a regression method.ConclusionThe proposed method can be readily applied to the Cochran-Armitage's trend tests other than the additive trend test, the Pearson's chi-square test and other robust efficiency tests. Simulation results show that the proposed method is effective in controlling type I error in the presence of population substructure.

Pop.STR—An online population frequency browser for established and new forensic STRs

We recently produced allele frequency data for 20 forensic STRs in more than 50 worldwide populations. The STRs characterized include 5 new European Standard Set (ESS) STRs where novel low frequency and intermediate-repeat genotypes found were confirmed by sequence analysis. Data for the 20 STRs has been collated into an open-access online frequency browser at: http://spsmart.cesga.es/popstr.php that allows users to combine populations into groups to generate re-calculated allele frequency estimates from the merged genotype data. The flexibility to combine populations in this way and the graphical summaries provided for each marker's allele frequencies offers the forensic analyst an informative system to consult STR variability in a global range of populations.

이환 형제 자료에 대한 유전적 연관성 분석 방법의 비교

질적 형질에 대한 유전적 연관성 분석은 크게 두 가지로 구분 할 수 있는데, 모형 기반분석과 그렇지 않은 모형 무관 분석 방법이다. 복합질병의 경우 멘델의 유전법칙을 잘 따르지 않기 때문에 모형 기반 분석 방법을 사용하는 것보다 모형 무관 분석 방법을 사용하는 것이 효율적이라고 알려져 있다. 이러한 모형 무관 분석 방법 중 이환 형제 쌍 자료를 이용한 분석 방법은 형제 쌍 간의 유전적 일치 비율을 기준으로 공유하고 있는 대립유전자의 분포를 이용하는 것으로 크게 proportion test, mean test, minmax test로 구분 할 수 있다. 본 연구에서는 형제집단자료로 확장된 경우, 유전 형식에 상관없이 로버스트한 방법으로 알려진 minmax test에 형제 쌍의 가중치를 고려할 수 있는 방법들 즉, 동일 가중 방법, Suarez의 방법, Hodge의 방법, Sham 등의 방법을 적용하여 그 성능을 비교하였다. 모의실험 자료를 이용하여 비교한 결과 표식유전자의 빈도, 형질의 유전 형식, 형제수에 상관없이 Suarez의 방법이 가장 검정력이 높은 방법으로 드러났다. 또한, 동일 가중 방법을 제외하고는 표식유전자의 빈도가 높아질수록, 형제수가 많아질수록 더 높은 검정력을 보였고, 이러한 현상은 우성 유전 형식을 가정한 자료에서 더욱 두드러지게 나타났다. For complex diseases such as diabetes, hypertension, it is believed that model-free methods might work better because they do not require a precise knowledge of the mode of inheritance controlling the disease trait. This is done by estimating the sharing probabilities that a pair shares zero, one, or two alleles identical by descent(IBD) and has some specific branches of test procedure, i.e., the mean test, the proportion test, and the minmax test. Among them, the minmax test is known to be more robust than others regardless of genetic mode of inheritance in current use. In this study, we compared the power of the methods which are based on minmax test and considering weighting schemes for sib-pairs to analyze sibship data. In simulation result, we found that the method based on Suarez' was more powerful than any others without respect to marker allele frequency, genetic mode of inheritance, sibship size. Also, The power of both Suarez- and Hodge-based methods was higher when marker allele frequency and sibship size were higher, and this result was remarkable in dominant mode of inheritance especially.

Ancestral Recombination Graphs under Non-Random Ascertainment, with Applications to Gene Mapping

Consider a sample of apparently unrelated individuals, for which marker genotype and phenotype data is available. When individuals are sampled on phenotypes, we propose an ascertained ancestral recombination graph (ARG) that models shared ancestry of the sample chromosomes given phenotype data along a region that possibly harbors a disease susceptibility gene. The ascertained ARG is used to define a gene mapping algorithm by means of a lod score and associated p-values based on permutation testing. Under certain modeling simplifications, the lod score and p-values can be computed exactly, without any Monte Carlo approximations, even for unphased chromosome genotype data. Our method handles incomplete penetrance, varying marker allele frequencies and neutral mutations, and is based on a Hidden Markov algorithm for subsets of disease mutated chromosomes. The performance of the method is investigated in a simulation study and for a real data set from a case-control study of breast cancer.

QTL detection with bidirectional and unidirectional selective genotyping: marker-based and trait-based analyses

Selective genotyping of one or both phenotypic extremes of a population can be used to detect linkage between markers and quantitative trait loci (QTL) in situations in which full-population genotyping is too costly or not feasible, or where the objective is to rapidly screen large numbers of potential donors for useful alleles with large effects. Data may be subjected to 'trait-based' analysis, in which marker allele frequencies are compared between classes of progeny defined based on trait values, or to 'marker-based' analysis, in which trait means are compared between progeny classes defined based on marker genotypes. Here, bidirectional and unidirectional selective genotyping were simulated, using population sizes and selection intensities relevant to cereal breeding. Control of Type I error was usually adequate with marker-based analysis of variance or trait-based testing using the normal approximation of the binomial distribution. Bidirectional selective genotyping was more powerful than unidirectional. Trait-based analysis and marker-based analysis of variance were about equally powerful. With genotyping of the best 30 out of 500 lines (6%), a QTL explaining 15% of the phenotypic variance could be detected with a power of 0.8 when tests were conducted at a marker 10 cM from the QTL. With bidirectional selective genotyping, QTL with smaller effects and (or) QTL farther from the nearest marker could be detected. Similar QTL detection approaches were applied to data from a population of 436 recombinant inbred rice lines segregating for a large-effect QTL affecting grain yield under drought stress. That QTL was reliably detected by genotyping as few as 20 selected lines (4.5%). In experimental populations, selective genotyping can reduce costs of QTL detection, allowing larger numbers of potential donors to be screened for useful alleles with effects across different backgrounds. In plant breeding programs, selective genotyping can make it possible to detect QTL using even a limited number of progeny that have been retained after selection.

Diabetes-specific genetic effects on obesity traits in American Indian populations: the Strong Heart Family Study

BackgroundBody fat mass distribution and deposition are determined by multiple environmental and genetic factors. Obesity is associated with insulin resistance, hyperinsulinemia, and type 2 diabetes. We previously identified evidence for genotype-by-diabetes interaction on obesity traits in Strong Heart Family Study (SHFS) participants. To localize these genetic effects, we conducted genome-wide linkage scans of obesity traits in individuals with and without type 2 diabetes, and in the combined sample while modeling interaction with diabetes using maximum likelihood methods (SOLAR 2.1.4).MethodsSHFS recruited American Indians from Arizona, North and South Dakota, and Oklahoma. Anthropometric measures and diabetes status were obtained during a clinic visit. Marker allele frequencies were derived using maximum likelihood methods estimated from all individuals and multipoint identity by descent sharing was estimated using Loki. We used variance component linkage analysis to localize quantitative trait loci (QTLs) influencing obesity traits. We tested for evidence of additive and QTL-specific genotype-by-diabetes interactions using the regions identified in the diabetes-stratified analyses.ResultsAmong 245 diabetic and 704 non-diabetic American Indian individuals, we detected significant additive gene-by-diabetes interaction for weight and BMI (P < 0.02). In analysis accounting for QTL-specific interaction (P < 0.001), we detected a QTL for weight on chromosome 1 at 242 cM (LOD = 3.7). This chromosome region harbors the adiponectin receptor 1 gene, which has been previously associated with obesity.ConclusionThese results suggest distinct genetic effects on body mass in individuals with diabetes compared to those without diabetes, and a possible role for one or more genes on chromosome 1 in the pathogenesis of obesity.