Estimated Haplotype Frequencies Research Articles

Belarusian experience of the use of FamLinkX for solving complex kinship cases involving X-STR markers

Use of X-STR markers extends and gives additional possibilities to a forensic DNA expert for kinship analysis. FamLinkX is software for the calculation of likelihood ratios (LRs) for kinship cases based on X-STR DNA profiles that takes linkage and linkage disequilibrium as well as mutations of X-STR markers into account. Belarusian haplotype frequencies database of 360 unrelated Belarusian males has been uploaded to FamLinkX. LR values for 6 deficient paternity cases and 2 forensic cases involving two putative full siblings, females, were calculated with different values of lambda (λ=1, 10, 100) in order to account for uncertainties in the haplotype frequency estimation. To demonstrate the ethnic sensitivity of X-STR markers and importance of the choice of the appropriate X-STR population database for LR calculation we calculated LR values for the same kinship cases using Belarusian and Swedish X-STR databases. LR values for the same kinship case differed from each other up to 6000 times depending on the chosen database. X-STRs genotyping lets us to determine relatedness successfully in all cases whereas the results of autosomal STR profiling and mitochondrial sequencing (for the cases where only the samples of putative full-siblings were available) were not sufficient to resolve family relationships issues. LR values were considered to be high enough in all cases.

Association of common filaggrin null mutations with atopy but not chronic rhinosinusitis

Association of common filaggrin null mutations with atopy but not chronic rhinosinusitis

Comparison of high-resolution human leukocyte antigen haplotype frequencies in different ethnic groups: Consequences of sampling fluctuation and haplotype frequency distribution tail truncation

High-resolution haplotype frequency estimations and descriptive metrics are becoming increasingly popular for accurately describing human leukocyte antigen diversity. In this study, we compared sample sets of publically available haplotype frequencies from different populations to characterize the consequences of unequal sample size on haplotype frequency estimation. We found that for low samples sizes (a few thousand), haplotype frequencies were overestimated, affecting all descriptive metrics of the underlying distribution, such as most frequent haplotype, the number of haplotypes, and the mean/median frequency. This overestimation was a result of random sample fluctuation and truncation of the tail end of the frequency distribution that comprises the least frequent haplotypes. Finally, we simulated balanced datasets through resampling and contrasted the disparities of descriptive metrics among equal and unequal datasets. This simulation resulted in the global description of the most frequent human leukocyte antigen haplotypes worldwide.

Variations in DEPDC5 gene and its association with chronic hepatitis C virus infection in Saudi Arabia.

BackgroundVariations at DEPDC5 gene have been recently reported as genetic markers associated with hepatocellular carcinoma (HCC) progression in chronic HCV-infected patients. This study was conducted to assess the association of DEPDC5 variants with advanced liver cirrhosis and HCC development among chronic HCV-infected patients in Saudi Arabian population.MethodsSix-hundred and one HCV-infected patients were genotyped for DEPDC5 polymorphisms (rs1012068 and rs5998152), in comparison with 592 non-infected healthy control subjects. The allelic frequency and genotype distribution of both DEPDC5 polymorphisms were determined followed by haplotype frequency estimation and multiple logistic regression analysis.ResultsThe frequency of the risk alleles of both rs1012068 and rs5998152 was shown to be more in healthy control subjects than in patients (p = 0.0001, OR = 0.704, CI = 0.591-0.839; p = 0.002, OR = 0.761, CI = 0. 0.639-0.907, respectively). Also, our results revealed that GT for SNP rs1012068 (OR =1.715; 95% CI 1.132-2.597; p = 0.0104) and CT for SNP rs5998152 (OR = 1.932; 95% CI 1.276-2.925; p = 0.0017) showed significant association with development of cirrhosis compared with the GG and CC genotypes, respectively. The data also revealed that subjects with the T allele of both SNPs appeared to have a lower susceptibility to HCV-related cirrhosis/HCC than those with the G allele of rs1012068 (p = 0.038, OR = 1.353, 95 % CI 1.017-1.800) and C allele of rs5998152 (p = 0.043, OR = 1.342, 95 % CI 1.010-1.784). Haplotype analysis showed that a combination of T-T alleles of rs1012068 and rs5998152 was significantly associated with liver cirrhosis (frequency = 71.3% and p = 0.027) and with cirrhosis/HCC (frequency = 71.4% and P = 0.045). Also, multiple logistic regression analysis showed that rs5998152 (OR = 2.844, 95% CI 1.333-6.069 and p = 0.007), rs1012068 (OR = 2.793, 95% CI 1.316-5.928 and p = 0.010), age (OR = 1.029, 95% CI 1.001-1.057 and p = 0.041) and HCV genotypes (OR = 0.247, 95% CI 0.097-0.630 and p = 0.003) were independently associated with chronicity of HCV infection.ConclusionGenetic variations in DEPDC5 gene region may influence HCV-associated liver cirrhosis and/or HCC development.

No shortcut solution to the problem of Y-STR match probability calculation

Match probability calculation is deemed much more intricate for lineage genetic markers, including Y-chromosomal short tandem repeats (Y-STRs), than for autosomal markers. This is because, owing to the lack of recombination, strong interdependence between markers is likely, which implies that haplotype frequency estimates cannot simply be obtained through the multiplication of allele frequency estimates. As yet, however, the practical relevance of this problem has not been studied in much detail using real data. In fact, such scrutiny appears well warranted because the high mutation rates of Y-STRs and the possibility of backward mutation should have worked against the statistical association of Y-STRs. We examined haplotype data of 21 markers included in the PowerPlex®Y23 set (PPY23, Promega Corporation, Madison, WI) originating from six different populations (four European and two Asian). Assessing the conditional entropies of the markers, given different subsets of markers from the same panel, we demonstrate that the PowerPlex®Y23 set cannot be decomposed into smaller marker subsets that would be (conditionally) independent. Nevertheless, in all six populations, >94% of the joint entropy of the 21 markers is explained by the seven most rapidly mutating markers. Although this result might render a reduction in marker number a sensible option for practical casework, the partial haplotypes would still be almost as diverse as the full haplotypes. Therefore, match probability calculation remains difficult and calls for the improvement of currently available methods of haplotype frequency estimation.

Accurate estimation of haplotype frequency from pooled sequencing data and cost-effective identification of rare haplotype carriers by overlapping pool sequencing.

A variety of hypotheses have been proposed for finding the missing heritability of complex diseases in genome-wide association studies. Studies have focused on the value of haplotype to improve the power of detecting associations with disease. To facilitate haplotype-based association analysis, it is necessary to accurately estimate haplotype frequencies of pooled samples. Taking advantage of databases that contain prior haplotypes, we present Ehapp based on the algorithm for solving the system of linear equations to estimate the frequencies of haplotypes from pooled sequencing data. Effects of various factors in sequencing on the performance are evaluated using simulated data. Our method could estimate the frequencies of haplotypes with only about 3% average relative difference for pooled sequencing of the mixture of 10 haplotypes with total coverage of 50×. When unknown haplotypes exist, our method maintains excellent performance for haplotypes with actual frequencies >0.05. Comparisons with present method on simulated data in conjunction with publicly available Illumina sequencing data indicate that our method is state of the art for many sequencing study designs. We also demonstrate the feasibility of applying overlapping pool sequencing to identify rare haplotype carriers cost-effectively. Ehapp (in Perl) for the Linux platforms is available online (http://bioinfo.seu.edu.cn/Ehapp/). xsun@seu.edu.cn Supplementary data are available at Bioinformatics online.

Full mtGenome reference data: development and characterization of 588 forensic-quality haplotypes representing three U.S. populations.

Though investigations into the use of massively parallel sequencing technologies for the generation of complete mitochondrial genome (mtGenome) profiles from difficult forensic specimens are well underway in multiple laboratories, the high quality population reference data necessary to support full mtGenome typing in the forensic context are lacking. To address this deficiency, we have developed 588 complete mtGenome haplotypes, spanning three U.S. population groups (African American, Caucasian and Hispanic) from anonymized, randomly-sampled specimens. Data production utilized an 8-amplicon, 135 sequencing reaction Sanger-based protocol, performed in semi-automated fashion on robotic instrumentation. Data review followed an intensive multi-step strategy that included a minimum of three independent reviews of the raw data at two laboratories; repeat screenings of all insertions, deletions, heteroplasmies, transversions and any additional private mutations; and a check for phylogenetic feasibility. For all three populations, nearly complete resolution of the haplotypes was achieved with full mtGenome sequences: 90.3-98.8% of haplotypes were unique per population, an improvement of 7.7-29.2% over control region sequencing alone, and zero haplotypes overlapped between populations. Inferred maternal biogeographic ancestry frequencies for each population and heteroplasmy rates in the control region were generally consistent with published datasets. In the coding region, nearly 90% of individuals exhibited length heteroplasmy in the 12418-12425 adenine homopolymer; and despite a relatively high rate of point heteroplasmy (23.8% of individuals across the entire molecule), coding region point heteroplasmies shared by more than one individual were notably absent, and transversion-type heteroplasmies were extremely rare. The ratio of nonsynonymous to synonymous changes among point heteroplasmies in the protein-coding genes (1:1.3) and average pathogenicity scores in comparison to data reported for complete substitutions in previous studies seem to provide some additional support for the role of purifying selection in the evolution of the human mtGenome. Overall, these thoroughly vetted full mtGenome population reference data can serve as a standard against which the quality and features of future mtGenome datasets (especially those developed via massively parallel sequencing) may be evaluated, and will provide a solid foundation for the generation of complete mtGenome haplotype frequency estimates for forensic applications.

Identifying the most likely contributors to a Y-STR mixture using the discrete Laplace method.

In some crime cases, the male part of the DNA in a stain can only be analysed using Y chromosomal markers, e.g. Y-STRs. This may be the case in e.g. rape cases, where the male components can only be detected as Y-STR profiles, because the fraction of male DNA is much smaller than that of female DNA, which can mask the male results when autosomal STRs are investigated. Sometimes, mixtures of Y-STRs are observed, e.g. in rape cases with multiple offenders. In such cases, Y-STR mixture analysis is required, e.g. by mixture deconvolution, to deduce the most likely DNA profiles from the contributors. We demonstrate how the discrete Laplace method can be used to separate a two person Y-STR mixture, where the Y-STR profiles of the true contributors are not present in the reference dataset, which is often the case for Y-STR profiles in real case work. We also briefly discuss how to calculate the weight of the evidence using the likelihood ratio principle when a suspect's Y-STR profile fits into a two person mixture. We used three datasets with between 7 and 21 Y-STR loci: Denmark (n=181), Somalia (n=201) and Germany (n=3443). The Danish dataset with 21 loci was truncated to 15 and 10 loci to examine the effect of the number of loci. For each of these datasets, an out of sample simulation study was performed: A total of 550 mixtures were composed by randomly sampling two haplotypes, h1 and h2, from the dataset. We then used the discrete Laplace method on the remaining data (excluding h1 and h2) to rank the contributor pairs by the product of the contributors' estimated haplotype frequencies. Successful separation of mixtures (defined by the observation that the true contributor pair was among the 10 most likely contributor pairs) was found in 42-52% of the cases for 21 loci, 69-75% for 15 loci and 92-99% for 10 loci or less depending on the dataset and how the discrete Laplace model was chosen. Y-STR mixtures with many loci are difficult to separate, but even haplotypes with 21 Y-STR loci can be separated.

A hidden Markov model for haplotype inference for present-absent data of clustered genes using identified haplotypes and haplotype patterns.

The majority of killer cell immunoglobin-like receptor (KIR) genes are detected as either present or absent using locus-specific genotyping technology. Ambiguity arises from the presence of a specific KIR gene since the exact copy number (one or two) of that gene is unknown. Therefore, haplotype inference for these genes is becoming more challenging due to such large portion of missing information. Meantime, many haplotypes and partial haplotype patterns have been previously identified due to tight linkage disequilibrium (LD) among these clustered genes thus can be incorporated to facilitate haplotype inference. In this paper, we developed a hidden Markov model (HMM) based method that can incorporate identified haplotypes or partial haplotype patterns for haplotype inference from present-absent data of clustered genes (e.g., KIR genes). We compared its performance with an expectation maximization (EM) based method previously developed in terms of haplotype assignments and haplotype frequency estimation through extensive simulations for KIR genes. The simulation results showed that the new HMM based method outperformed the previous method when some incorrect haplotypes were included as identified haplotypes and/or the standard deviation of haplotype frequencies were small. We also compared the performance of our method with two methods that do not use previously identified haplotypes and haplotype patterns, including an EM based method, HPALORE, and a HMM based method, MaCH. Our simulation results showed that the incorporation of identified haplotypes and partial haplotype patterns can improve accuracy for haplotype inference. The new software package HaploHMM is available and can be downloaded at http://www.soph.uab.edu/ssg/files/People/KZhang/HaploHMM/haplohmm-index.html.

Cluster analysis of European Y-chromosomal STR haplotypes using the discrete Laplace method.

The European Y-chromosomal short tandem repeat (STR) haplotype distribution has previously been analysed in various ways. Here, we introduce a new way of analysing population substructure using a new method based on clustering within the discrete Laplace exponential family that models the probability distribution of the Y-STR haplotypes. Creating a consistent statistical model of the haplotypes enables us to perform a wide range of analyses. Previously, haplotype frequency estimation using the discrete Laplace method has been validated. In this paper we investigate how the discrete Laplace method can be used for cluster analysis to further validate the discrete Laplace method. A very important practical fact is that the calculations can be performed on a normal computer. We identified two sub-clusters of the Eastern and Western European Y-STR haplotypes similar to results of previous studies. We also compared pairwise distances (between geographically separated samples) with those obtained using the AMOVA method and found good agreement. Further analyses that are impossible with AMOVA were made using the discrete Laplace method: analysis of the homogeneity in two different ways and calculating marginal STR distributions. We found that the Y-STR haplotypes from e.g. Finland were relatively homogeneous as opposed to the relatively heterogeneous Y-STR haplotypes from e.g. Lublin, Eastern Poland and Berlin, Germany. We demonstrated that the observed distributions of alleles at each locus were similar to the expected ones. We also compared pairwise distances between geographically separated samples from Africa with those obtained using the AMOVA method and found good agreement.

Estimation of malaria haplotype and genotype frequencies: a statistical approach to overcome the challenge associated with multiclonal infections

BackgroundReliable measures of anti-malarial resistance are crucial for malaria control. Resistance is typically a complex trait: multiple mutations in a single parasite (a haplotype or genotype) are necessary for elaboration of the resistant phenotype. The frequency of a genetic motif (proportion of parasite clones in the parasite population that carry a given allele, haplotype or genotype) is a useful measure of resistance. In areas of high endemicity, malaria patients generally harbour multiple parasite clones; they have multiplicities of infection (MOIs) greater than one. However, most standard experimental procedures only allow measurement of marker prevalence (proportion of patient blood samples that test positive for a given mutation or combination of mutations), not frequency. It is misleading to compare marker prevalence between sites that have different mean MOIs; frequencies are required instead.MethodsA Bayesian statistical model was developed to estimate Plasmodium falciparum genetic motif frequencies from prevalence data collected in the field. To assess model performance and computational speed, a detailed simulation study was implemented. Application of the model was tested using datasets from five sites in Uganda. The datasets included prevalence data on markers of resistance to sulphadoxine-pyrimethamine and an average MOI estimate for each study site.ResultsThe simulation study revealed that the genetic motif frequencies that were estimated using the model were more accurate and precise than conventional estimates based on direct counting. Importantly, the model did not require measurements of the MOI in each patient; it used the average MOI in the patient population. Furthermore, if a dataset included partially genotyped patient blood samples, the model imputed the data that were missing. Using the model and the Ugandan data, genotype frequencies were estimated and four biologically relevant genotypes were identified.ConclusionsThe model allows fast, accurate, reliable estimation of the frequency of genetic motifs associated with resistance to anti-malarials using prevalence data collected from malaria patients. The model does not require per-patient MOI measurements and can easily analyse data from five markers. The model will be a valuable tool for monitoring markers of anti-malarial drug resistance, including markers of resistance to artemisinin derivatives and partner drugs.

Inhibitor IκBα promoter functional polymorphisms in patients with multiple sclerosis

The aim of this study is to investigate the association of IκBα promoter polymorphisms with the development of Multiple Sclerosis (MS) disease in Iranian population. One hundred and fifty patients with MS along with 150 unrelated healthy controls were enrolled in this study. The IκBα -881A/G (rs3138053), -826C/T (rs2233406) and -519C/T (rs2233408) polymorphisms were determined by the polymerase chain reaction/restriction fragment length polymorphism method. This study demonstrated that the genotype frequencies of IκBα -881A/G and -826T/T, and allele frequencies of IκBα-881G were significantly higher in patients with MS with respect to as compared to the controls. We also found that the estimated haplotype frequency of IκBα promoter -881G-826T-519C was significantly increased in the patient with MS in comparison with that of the healthy individuals. This study reveals that polymorphisms in the IκBα promoter (-881 A/G, -826 C/T) are strongly associated with the susceptibility of Iranian MS patients.

Genome-Wide Association Study of Extreme Longevity in Drosophila melanogaster

Human genome-wide association studies (GWAS) of longevity attempt to identify alleles at different frequencies in the extremely old, relative to a younger control sample. Here, we apply a GWAS approach to “synthetic” populations of Drosophila melanogaster derived from a small number of inbred founders. We used next-generation DNA sequencing to estimate allele and haplotype frequencies in the oldest surviving individuals of an age cohort and compared these frequencies with those of randomly sampled individuals from the same cohort. We used this case–control strategy in four independent cohorts and identified eight significantly differentiated regions of the genome potentially harboring genes with relevance for longevity. By modeling the effects of local haplotypes, we have more power to detect regions enriched for longevity genes than marker-based GWAS. Most significant regions occur near chromosome ends or centromeres where recombination is infrequent, consistent with these regions harboring unconditionally deleterious alleles impacting longevity. Genes in regions of normal recombination are enriched for those relevant to immune function and a gene family involved in oxidative stress response. Genetic differentiation between our experimental cohorts is comparable to that between human populations, suggesting in turn that our results may help explain heterogeneous signals in human association studies of extreme longevity when panels have diverse ancestry.

Understanding Y haplotype matching probability

The Y haplotype population-genetic terrain is better explored from a fresh perspective rather than by analogy with the more familiar autosomal ideas. For haplotype matching probabilities, versus for autosomal matching probabilities, explicit attention to modelling - such as how evolution got us where we are - is much more important while consideration of population frequency is much less so. This paper explores, extends, and explains some of the concepts of "Fundamental problem of forensic mathematics - the evidential strength of a rare haplotype match". That earlier paper presented and validated a "kappa method" formula for the evidential strength when a suspect matches a previously unseen haplotype (such as a Y-haplotype) at the crime scene. Mathematical implications of the kappa method are intuitive and reasonable. Suspicions to the contrary raised in rest on elementary errors. Critical to deriving the kappa method or any sensible evidential calculation is understanding that thinking about haplotype population frequency is a red herring; the pivotal question is one of matching probability. But confusion between the two is unfortunately institutionalized in much of the forensic world. Examples make clear why (matching) probability is not (population) frequency and why uncertainty intervals on matching probabilities are merely confused thinking. Forensic matching calculations should be based on a model, on stipulated premises. The model inevitably only approximates reality, and any error in the results comes only from error in the model, the inexactness of the approximation. Sampling variation does not measure that inexactness and hence is not helpful in explaining evidence and is in fact an impediment. Alternative haplotype matching probability approaches that various authors have considered are reviewed. Some are based on no model and cannot be taken seriously. For the others, some evaluation of the models is discussed. Recent evidence supports the adequacy of the simple exchangability model on which the kappa method rests. However, to make progress toward forensic calculation of Y haplotype mixture evidence a different tack is needed. The "Laplace distribution" model of Andersen et al. [3] which estimates haplotype frequencies by identifying haplotype clusters in population data looks useful.

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Most HLA alleles described in the IMGT/HLA database are very rare. The Common and Well Documented (CWD) allele list was created in 2007 to identify the subset of HLA alleles likely to be observed again, and the CWD list was revised in 2013 (CWD2). Our aim was to identify which protein-level CWD2 alleles were estimated from US registry HLA data. We evaluated allele frequency coverage of CWD2 “Common” and “Well Documented” categories in estimated haplotype frequencies for A,C,B,DRB1,DQB1 loci derived from all DNA-based registry typings in 26 US populations (http://bioinformatics.nmdp.org/FullRegistryHaplo/). We also identified CWD2 alleles not present in the US frequencies, the most frequent non-CWD2 alleles, and percentage of single-pass SBT requiring additional typing to meet CWD2-based typing resolution requirements. Common CWD2 alleles constituted a minimum of 91.1% of allele frequency at any locus in any population. Inclusion of Well Documented CWD2 alleles reached 99.5% coverage. 5 CWD2 alleles, all Well Documented category, were not observed in US frequencies (B*40:22N, B*52:21 C*07:67, DRB1*04:12, DRB1*14:14), however all 5 were estimated in a preliminary 2012 global BMDW dataset. Additionally, there were haplotype frequency estimates for many non-CWD2 alleles (514 A, 257 C, 707 B, 276 DRB1, 49 DQB1). The estimated percent of single-pass SBT typings with CWD2 genotypic ambiguity was at most 16.6% at any locus in any population, up from 9.6% for CWD1. Available US haplotype frequencies offer near complete coverage of CWD2 alleles, and offer additional advantages of providing population-specific allele frequency and haplotype linkage information. Publication of global BMDW haplotype frequencies is a goal of an international collaborative effort by the World Marrow Donor Association (WMDA) Registry Diversity working group, and will cover all CWD2 alleles when complete. The most frequenct non-CWD alleles may predict future additions to the living CWD list.

Association of vitamin D receptor gene polymorphisms with chronic and aggressive periodontitis in Jordanian patients

Vitamin D acts through binding with vitamin D receptor (VDR) and is responsible for regulating bone metabolism and mineralization; it also suppresses the immune system. The aim of this study was to investigate if VDR gene polymorphisms are associated with chronic periodontitis (CP) and aggressive periodontitis (AgP) in a Jordanian population. A total of 99 patients with CP, 63 patients with AgP, and 126 controls were genotyped using PCR-restriction fragment length polymorphism (RFLP) for BsmI, ApaI, and TaqI single nucleotide polymorphisms (SNPs). The association was determined after correcting for confounding factors using multivariate logistic regression analysis. Estimation of haplotype frequencies was carried out using the EH program, and haplotypes were constructed using the phase 2.1 program. After correcting for confounding factors, multivariate logistic regression analysis revealed that inheritance of the BsmI bb genotype or the ApaI aa genotype was associated with increased risk of developing CP (OR = 2.4 and OR = 3.4, respectively) but with reduced risk of developing AgP (OR = 0.4 and OR = 0.3, respectively). This was further supported by association of the ba haplotype with CP but not with AgP. This study supports an association of VDR gene polymorphisms with CP and AgP in a Jordanian population; however, the pattern of association was different between the two diseases.

Genetic association of ADIPOQ gene variants with type 2 diabetes, obesity and serum adiponectin levels in south Indian population

ObjectiveTo investigate the genetic association of eight variants of the adiponectin gene with type 2 diabetes mellitus (T2DM), obesity and serum adiponectin level in the south Indian population. MethodsThe study comprised of 1100 normal glucose tolerant (NGT) and 1100 type 2 diabetic, unrelated subjects randomly selected from the Chennai Urban Rural Epidemiology Study (CURES), in southern India. Fasting serum adiponectin levels were measured by radioimmunoassay. The variants were screened by polymerase chain reaction-restriction fragment length polymorphism. Linkage disequilibrium was estimated from the estimates of haplotype frequencies. ResultsOf the 8 variants, four SNPs namely, +276 G/T (rs1501299), −4522 C/T (rs822393), −11365 C/G (rs266729), and +712 G/A (rs3774261) were significantly associated with T2DM in our study population. The −3971 A/G (rs822396) and −11391 G/A (rs17300539) SNPs' association with T2DM diabetes was mediated through obesity (where the association with type 2 diabetes was lost after adjusting for BMI). There was an independent association of +276 G/T (rs1501299) and −3971 A/G (rs822396) SNPs with generalized obesity and +349 A/G (rs2241767) with central obesity. Four SNPs, −3971 A/G (rs822396), +276 G/T (rs1501299), −4522 C/T (rs822393) and Y111H T/C (rs17366743) were significantly associated with hypoadiponectinemia. The haplotypes GCCATGAAT and AGCGTGGGT conferred lower risk of T2DM in this south Indian population. ConclusionThe adiponectin gene variants and haplotype contribute to the genetic risk towards the development of type 2 diabetes, obesity and hypoadiponectinemia in the south Indian population.

Next-Generation Sequencing of HIV-1 RNA Genomes: Determination of Error Rates and Minimizing Artificial Recombination

Next-generation sequencing (NGS) is a valuable tool for the detection and quantification of HIV-1 variants in vivo. However, these technologies require detailed characterization and control of artificially induced errors to be applicable for accurate haplotype reconstruction. To investigate the occurrence of substitutions, insertions, and deletions at the individual steps of RT-PCR and NGS, 454 pyrosequencing was performed on amplified and non-amplified HIV-1 genomes. Artificial recombination was explored by mixing five different HIV-1 clonal strains (5-virus-mix) and applying different RT-PCR conditions followed by 454 pyrosequencing. Error rates ranged from 0.04–0.66% and were similar in amplified and non-amplified samples. Discrepancies were observed between forward and reverse reads, indicating that most errors were introduced during the pyrosequencing step. Using the 5-virus-mix, non-optimized, standard RT-PCR conditions introduced artificial recombinants in a fraction of at least 30% of the reads that subsequently led to an underestimation of true haplotype frequencies. We minimized the fraction of recombinants down to 0.9–2.6% by optimized, artifact-reducing RT-PCR conditions. This approach enabled correct haplotype reconstruction and frequency estimations consistent with reference data obtained by single genome amplification. RT-PCR conditions are crucial for correct frequency estimation and analysis of haplotypes in heterogeneous virus populations. We developed an RT-PCR procedure to generate NGS data useful for reliable haplotype reconstruction and quantification.

Regional HLA Differences in Poland and Their Effect on Stem Cell Donor Registry Planning

Regional HLA frequency differences are of potential relevance for the optimization of stem cell donor recruitment. We analyzed a very large sample (n = 123,749) of registered Polish stem cell donors. Donor figures by 1-digit postal code regions ranged from n = 5,243 (region 9) to n = 19,661 (region 8). Simulations based on region-specific haplotype frequencies showed that donor recruitment in regions 0, 2, 3 and 4 (mainly located in the south-eastern part of Poland) resulted in an above-average increase of matching probabilities for Polish patients. Regions 1, 7, 8, 9 (mainly located in the northern part of Poland) showed an opposite behavior. However, HLA frequency differences between regions were generally small. A strong indication for regionally focused donor recruitment efforts can, therefore, not be derived from our analyses. Results of haplotype frequency estimations showed sample size effects even for sizes between n≈5,000 and n≈20,000. This observation deserves further attention as most published haplotype frequency estimations are based on much smaller samples.

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

BackgroundDNA 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.ResultsWe 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.ConclusionsWe 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.