Estimated Haplotype Frequencies Research Articles

HLA alleles, haplotypes frequencies, and their association with hematological disorders: a report from 1550 families whose patients underwent allogeneic bone marrow transplantation in Egypt.

HLA alleles are representative of ethnicities and may play important roles in predisposition to hematological disorders. We analyzed DNA samples for HLA-A, -B, -C, -DRB1, and -DQB1 loci, from 1550 patients and 4450 potential related donors by PCR-SSO (Polymerase chain reaction sequence-specific oligonucleotides) and estimated allele frequencies in donors and patients from 1550 families who underwent bone marrow transplantation (BMT) in Egypt. We also studied the association between HLA allele frequencies and incidence of acute myeloid leukemia, acute lymphoblastic leukemia, and severe aplastic anemia. The most frequently observed HLA class I alleles were HLA- A*01:01 (16.9%), A*02:01 (16.1%), B*41:01 (8.7%), B*49:01 (7.3%), C*06:02 (25.1%), and C*07:01 (25.1%), and the most frequently observed class II alleles were HLA-DRB1*11:01 (11.8%), DRB1*03:01 (11.6%), DQB1*03:01 (27.5%), and DQB1*05:01 (18.9%). The most frequently observed haplotypes were A*33:01~B*14:02 ~ DRB1*01:02 (2.35%) and A*01:01~B*52:01~DRB1*15:01 (2.11%). HLA-DRB1*07:01 was associated with higher AML odds (OR, 1.26; 95% CI, 1.02-1.55; p = 0.030). Only HLA-B38 antigen showed a trend towards increased odds of ALL (OR, 1.52; 95% CI, 1.00-2.30; p = 0.049) HLA-A*02:01, -B*14:02, and -DRB1*15:01 were associated with higher odds of SAA (A*02:01: OR, 1.35; 95% CI, 1.07-1.70; p = 0.010; B*14:02: OR, 1.43; 95% CI, 1.06-1.93; p = 0.020; DRB1*15:01: OR, 1.32; 95% CI, 1.07-1.64; p = 0.011). This study provides estimates of HLA allele and haplotype frequencies and their association with hematological disorders in an Egyptian population.

Estimating Haplotype Structure and Frequencies: A Bayesian Approach to Unknown Design in Pooled Genomic Data.

The estimation of haplotype structure and frequencies provides crucial information about the composition of genomes. Techniques, such as single-individual haplotyping, aim to reconstruct individual haplotypes from diploid genome sequencing data. However, our focus is distinct. We address the challenge of reconstructing haplotype structure and frequencies from pooled sequencing samples where multiple individuals are sequenced simultaneously. A frequentist method to address this issue has recently been proposed. In contrast to this and other methods that compute point estimates, our proposed Bayesian hierarchical model delivers a posterior that permits us to also quantify uncertainty. Since matching permutations in both haplotype structure and corresponding frequency matrix lead to the same reconstruction of their product, we introduce an order-preserving shrinkage prior that ensures identifiability with respect to permutations. For inference, we introduce a blocked Gibbs sampler that enforces the required constraints. In a simulation study, we assessed the performance of our method. Furthermore, by using our approach on two distinct sets of real data, we demonstrate that our Bayesian approach can reconstruct the dominant haplotypes in a challenging, high-dimensional set-up.

Optimisation of global stem cell donor recruitment based on analysis of unsuccessful donor searches.

Despite over 41 million registered potential volunteer stem cell donors worldwide, many patients in need of a transplant do not find an HLA-matched unrelated donor or cord blood units, with the respective odds differing significantly between various populations. In this study, we analysed data of 2205 unsuccessful real-life donor searches sent to the DKMS Registry to identify populations in which further donor recruitment would be associated with particularly large patient benefits. For that purpose, we estimated haplotype frequencies of 67 donor populations at various sample sizes and entered them into two different mathematical models. These models assessed patient benefits from population-specific donor recruitment, operationalised by the number of originally unsuccessful searches that may become successful due to new donors. Consistently, across the different mathematical models and sample sizes, we obtained several countries from East and Southeast Asia (Thailand, Vietnam, China, and the Philippines) and the population of Asians in the USA as countries/populations where donor recruitment activities would be particularly beneficial for patients. We also identified various countries in Southeast and Central Europe as possible target regions for donor recruitment with above-average patient benefits. The results presented are registry-specific in the sense that they were obtained by optimising unsuccessful searches that had been sent to the DKMS Registry. Therefore, it would be desirable to apply the presented methods to a global data set that includes all unsuccessful stem cell donor searches worldwide and uses population-specific haplotype frequencies based on all donors available in the WMDA Search & Match Service.

PyPop: a mature open-source software pipeline for population genomics.

Python for Population Genomics (PyPop) is a software package that processes genotype and allele data and performs large-scale population genetic analyses on highly polymorphic multi-locus genotype data. In particular, PyPop tests data conformity to Hardy-Weinberg equilibrium expectations, performs Ewens-Watterson tests for selection, estimates haplotype frequencies, measures linkage disequilibrium, and tests significance. Standardized means of performing these tests is key for contemporary studies of evolutionary biology and population genetics, and these tests are central to genetic studies of disease association as well. Here, we present PyPop 1.0.0, a new major release of the package, which implements new features using the more robust infrastructure of GitHub, and is distributed via the industry-standard Python Package Index. New features include implementation of the asymmetric linkage disequilibrium measures and, of particular interest to the immunogenetics research communities, support for modern nomenclature, including colon-delimited allele names, and improvements to meta-analysis features for aggregating outputs for multiple populations. Code available at: https://zenodo.org/records/10080668 and https://github.com/alexlancaster/pypop.

Graph-Based Imputation Methods and Their Applications to Single Donors and Families.

The outcome of Hematopoietic Stem Cell (HSCT) and organ transplant is strongly affected by the matching of the HLA alleles of the donor and the recipient. However, donors and sometimes recipients are often typed at low resolution, with some alleles either missing or ambiguous. Thus, imputation methods are required to detect the most probably high-resolution HLA haplotypes consistent with a typing. Such imputation algorithms require predefined haplotype frequencies. As such, the phasing of the typing is required for both imputation and frequency generation.We have developed a new approach to HLA haplotype and genotype imputation, where first all candidate phases of a typing are explicated, and then the ambiguity within each phase is solved. This ambiguity is solved through a graph structure of all partial haplotypes and the haplotypes consistent with them.This phasing approach was used to produce an imputation algorithm (GRIMM-Graph Imputation and Matching). GRIMM was then combined with the possibility of combining information from multiple races to produce MR-GRIMM (Multi-Race GRIMM). When family information is available, the phasing of each family member can be restricted by the others. We propose GRAMM (GRaph-bAsed faMily iMputation) to phase alleles in family pedigree HLA typing data and in mother-cord blood unit pairs. Finally, we combined MR-GRIMM with an expectation-maximization (EM) algorithm to estimate haplotype frequencies sharing information between races to produce MR-GRIMME (MR-GRIMM EM).We have shown that these algorithms naturally combine information between races and family members. The accuracy of each of these algorithms is significantly better than its current parallel methods. MR-GRIMM leads to high accuracy in matching predictions. GRAMM better imputes family members than either MR-GRIMM or any existing algorithm and has practically no phasing errors. MR-GRIMME obtains a higher likelihood than existing algorithms.MR-GRIMM, MR-GRIMME, and GRAMM are available as servers or through stand-alone versions in GITHUB and PyPi, as detailed in the appropriate sections.

Evaluation of CAT Variants A-89T, C389T, and C419T in Patients with Vitiligo in the Saudi Population.

Background and Objectives: Vitiligo is a chronic autoimmune and depigmentation disorder in humans that manifests as whitening lesions. Reactive oxygen species (ROS) are involved in cell damage. Catalase (CAT) is a well-known oxidative stress regulator and is primarily responsible for the catalytic decomposition of hydrogen peroxide into water and oxygen. Based on previous case-control and meta-analysis studies, we assessed the prevalence of three single-nucleotide polymorphisms (SNPs) of the CAT genes A-89T (rs7943316), C389T (rs769217) and C419T (rs11032709) in participants with vitiligo and healthy controls in the Saudi population. Materials and Methods: We recruited 152 participants with vitiligo and 159 healthy controls for A-89T, C389T, and C419T SNP genotyping studies using PCR and RFLP analysis. Additionally, we performed linkage disequilibrium and haplotype analyses between vitiligo cases and controls. Results: The rs7943316 and rs11032709 SNPs of the CAT genes showed a positive association with vitiligo for both heterozygous genotypes and dominant genetic models (TT + AT vs. AA in A-89T and TT + CT vs. CC in C389T), in the CAT gene. Linkage disequilibrium analysis revealed a moderate linkage between rs7943316 and rs11032709 SNPs in vitiligo cases and controls. Haplotype frequency estimation revealed a significant association (p = 0.003) among the three SNP alleles. Conclusions: The rs7943316 and rs11032709 SNPs of the CAT genes were strongly associated with susceptibility to vitiligo.

Unrelated Stem Cell Donor HLA Match Likelihood in the US Registry Incorporating HLA-DPB1 Permissive Mismatching

Donor-recipient HLA matching at the DPB1 locus improves the outcomes of hematopoietic stem cell transplantation (HCT). Retrospective outcome studies found that in HCTs matched for all 8 alleles of the A, B, C, and DRB1 loci at high resolution (8/8 match), few transplantations were also allele-matched at the DPB1 locus. DPB1 allele matching was once thought to be logistically impractical; however, a DPB1-permissive mismatch model based on T cell epitope (TCE) reactivity expands the proportion of suitable donors. To understand the likelihood of finding a DPB1-permissive donor, we sought to expand population genetic match likelihood models for the US unrelated donor registry, the National Marrow Donor Program (NMDP). After extending HLA haplotype frequency estimates to include the DPB1 locus, our models found that the likelihood of having a DPB1-permissive donor was not much lower than likelihood of 8/8 matching. A maximum of 5 additional donors would need to be typed to find a more optimal DPB1-permissive donor at least 90% of the time. Linkage disequilibrium patterns between the DPB1 locus and other classical HLA loci varied markedly by haplotype and population, indicating that the known recombination hotspot between DQ and DP gene complexes has not had a uniform impact; thus, DPB1-permissive donors are easier to identify within minority populations. DPB1 TCE categories were highly predictable from HLA typing at other loci when imputed with extended haplotype frequency data. Our overall results indicate that registry search strategies that seek a more optimally matched HCT donor encompassing HLA-DPB1 permissibility are likely to be highly productive.

Allele and eight-locus haplotype frequencies in population of Belgorod region, Russia

This paper reports the HLA-A, -B, -C, -DRB1, -DQA1, -DQB1, -DPA1 and –DPB1 alleles and estimated haplotype frequencies in a population of 153 healthy potential blood marrow donors from Belgorod region, Russia. HLA genotyping was performed by next generation sequencing method (NGS). Statistical analysis were performed using Arlequin software packages. There was no deviation from Hardy-Weinberg Equilibrium detected at HLA-A, -B, -DRB1, -DQA1, -DQB1, and -DPA1 loci. Deviation was detected at the HLA-C and DPB1 locus probably due to an excess of C*12:03:01 and DPB1*04:01:01 homozygotes. These genotype data are available in the Allele Frequencies Net Database under the population name, “Russia, Belgorod Region” and the identifier: 3780.

An experimental extension to the discrete Laplace method for Y-STR haplotype frequency estimation

Frequency estimation for Y-STR haplotypes is a challenging problem because limited data are available and complex dependencies exist within the data. As a result, various statistical methods have been proposed for frequency estimation. The discrete Laplace method has been recommended in some contexts by the DNA commission of the ISFG. This method is limited to haplotypes with single integer repeat alleles only at all loci. We propose a generalisation of the method that handles duplicated loci such as DYS385 and less common alleles that are not integer repeats. The extension is implemented in an experimental R package called disclapmix2.

A maximum-likelihood method to estimate haplotype frequencies and prevalence alongside multiplicity of infection from SNP data.

The introduction of genomic methods facilitated standardized molecular disease surveillance. For instance, SNP barcodes in Plasmodium vivax and Plasmodium falciparum malaria allows the characterization of haplotypes, their frequencies and prevalence to reveal temporal and spatial transmission patterns. A confounding factor is the presence of multiple genetically distinct pathogen variants within the same infection, known as multiplicity of infection (MOI). Disregarding ambiguous information, as usually done in ad-hoc approaches, leads to less confident and biased estimates. We introduce a statistical framework to obtain maximum-likelihood estimates (MLE) of haplotype frequencies and prevalence alongside MOI from malaria SNP data, i.e., multiple biallelic marker loci. The number of model parameters increases geometrically with the number of genetic markers considered and no closed-form solution exists for the MLE. Therefore, the MLE needs to be derived numerically. We use the Expectation-Maximization (EM) algorithm to derive the maximum-likelihood estimates, an efficient and easy-to-implement algorithm that yields a numerically stable solution. We also derive expressions for haplotype prevalence based on either all or just the unambiguous genetic information and compare both approaches. The latter corresponds to a biased ad-hoc estimate of prevalence. We assess the performance of our estimator by systematic numerical simulations assuming realistic sample sizes and various scenarios of transmission intensity. For reasonable sample sizes, and number of loci, the method has little bias. As an example, we apply the method to a dataset from Cameroon on sulfadoxine-pyrimethamine resistance in P. falciparum malaria. The method is not confined to malaria and can be applied to any infectious disease with similar transmission behavior. An easy-to-use implementation of the method as an R-script is provided.

Extended population genetic analysis of 12 X-STRs – Exemplified using a Norwegian population sample

The use of X-chromosomal markers to resolve questions of relatedness has experienced a significant increase during the last years in forensic genetics. Perhaps primarily due to the emergence of commercial kits, but equally important due to an increased awareness of the utility of those markers. The X-chromosomal inheritance pattern entails that some cases, for instance paternal half-sisters, can potentially be resolved using a few X-chromosomal markers alone. For the statistical assessment in kinship cases it is of importance to have relevant population frequency data. In the present study 631 unrelated males from a Norwegian population sample are analyzed. The resulting haplotypes are compared to previously studied population samples and a deeper analysis of the linkage disequilibrium (LD) structure is conducted. We demonstrate that the power to detect LD will be low when few males, say below 300, are analyzed. We use entropy to describe the degree of LD between multiallelic loci and describe how this measure varies between different studied populations. Large population frequency databases have been recommended when using X-chromosomal markers, and we show that by combining reference databases from genetically similar populations, more precise haplotype frequency estimates can be obtained for rare haplotypes which improves the statistical assessment of the weight of evidence. In addition, we promote the use of simulations to assess the utility of STR markers in contrast to standard forensic parameters. Specifically we perform extensive simulations on cases where X-chromosomal markers are important and illustrate how the results can be used to infer the information gained from these markers.

Estimation of allele and haplotype frequencies for 23 YSTR markers of Iraqi populations in Baghdad

Specialized class of short tandem repeats located on human Y (male) chromosomes called Y-chromosome short tandem repeats (Y-STRs) are transferred from one generation to the next with unchanged (barring a mutation). Also, these loci have high discriminatory capacities among individuals of the same population or ethnicity due to the non-recombining nature of it. Peripheral blood sample from 160 unrelated Iraqi males in Baghdad are collected and DNA was extracted from it. Amplification of 23 Y-STR markers (DYS576, DYS3891, DYS448, DYS389II ,DYS19, DYS481, DYS549, DYS533, DYS438, DYS437, DYS570, DYS635, DYS390, DYS439, DYS392, DYS643, DYS393, DYS458a/b, DYS456 and YGATAH4) was performed using PowerPlex Y 23 System (Promega Corporation), PCR amplicons were analyzed on 4-capillary ABI Prism® 3100 Genetic Analyzer. Collected data were analyzed and haplotypes were obtained using Gene Mapper ID-X software version 1.4 (Applied Biosystems). Results indicated that the most polymorphic loci were DYS385a/b with 43 alleles and The GD value was 0.929, while 4 alleles at the DYS576 and DYS391, with the genetic diversity of 0.459 and 0.480 respectively. At the loci DYS570 and DYS458 the allele frequency were 10 and 12 alleles with a genetic diversity 0.780 and 0.844 respectively. Gene diversity values for the South of Iraq males ranged from 0.447 to 0.844. The highest GD was detected at DYS458loci with a value of 0.856 and the lowest GD at DYS448 locus with a value of 0.447, 143 Haplotype was identified, 130 (81, 25%) as a unique Haplotype and 13 (18, 75%) as replicated haplotype among individuals. The highest haplotype were found in sample H19, H43, H72 and H122 at frequency 0.01875, While 130 haplotype with 0.00625 frequency and haplotype diversity was 0.99835 with a discrimination capacity 0.91. The study revealed that the loci under study and the used kit are suitable for use in identification, discrimination and forensic applications in the Iraqi population.

P1352: THE INTRA-POPULATION HLA DIVERSITY IN CRETE AND THE IMPORTANCE OF THE REGIONAL PUBLIC UMBILICAL CORD BLOOD BANK IN HLA-BASED DONOR SELECTION FOR ALLOGENEIC HEMATOPOIETIC STEM CELL TRANSPLANTATION

Background: Allogeneic hematopoietic stem cell transplantation is the elective treatment for several life-threatening hematologic diseases. The high genetic diversity of HLA across populations, combined with the complexity of its molecular variation and the limitations of traditional HLA typing, confines the effectiveness of matched unrelated donor registries and public umbilical cord blood banks (UCBB), particularly in populations with ethnic minorities. Aims: Prompted by our recent study describing a considerable HLA diversity between a representative Cretan cohort and the donors of DKMS, we set out to unravel the effect of potential intra-population diversity on HLA distribution. We used samples stratified by a specific Prefecture of origin aiming to signify the possible existence of a severe shortage of genetically HLA compatible samples and to justify the importance of the regional UCBB for an HLA-based donor selection in Crete. Methods: A combined cohort of 1,744 representative samples from the four Prefectures of Crete (Heraklion, Lasithi, Rethymno, Chania) were typed for HLA Class I (-A, -C, -B) and Class II (-DRB1, -DQB1) loci using 2nd field NGS. Fisher’s exact test was used for the comparison of g-grouped alleles with frequencies corrected by Bonferroni and of haplotypes estimated by Hapl-o-Mat with frequencies f≥1/2n. The average probability of finding a >6/10 compatible donor within and across the four Prefectures was also estimated using custom scripts in R. Results: In the combined cohort, HLA-B exhibited the highest allelic variability (n=74) and number of unique alleles (n=21/39). While the diversity of all loci, except for HLA-C, was attributed to the largest Prefecture, Heraklion, the high number of unique HLA-C alleles in Chania (n=4/8) contributed to both intra- and inter-population diversity. While the distribution of the most frequent common alleles across the 5 loci were similar between all Prefectures, significant differences (n=27 alleles) were revealed when each Prefecture was compared to the remaining pooled Cretan cohort. Such analyses substantiated the diversity of Chania (37.04%) mostly versus the geographically and genetically isolated Prefectures of Lasithi and Rethymno. Significant diversity was also observed among the 1,406 inferred haplotypes, with 80.2% being unique. The distribution of the top 10 out of the 21 common haplotypes in the combined cohort was 0.63%-1.38%. However, the most common haplotypes A*24:02~B*35:02~C*04:01~DRB1*11:04~DQB1*03:01 (1.38%) and A*33:01g~B*14:02g ~C*08:02g~DRB1*01:02g~DQB1*05:01g (1.38%) were mainly attributed to Rethymno with frequencies of 3.35% and 1.96%, respectively. The low frequency of A*24:02~B*35:02~C*04:01 ~DRB1*11:04~DQB1*03:01 in Heraklion (0.97%) and Chania (0.73%) resulted in a significant difference (p=5.8e-05) when both were compared to Rethymno. The diversity of Chania may underlie the higher probability of not finding a compatible donor in Lasithi and Rethymno (i.e. >30%) or Heraklion (i.e. >20%). Besides the lower distribution of the most common haplotypes, Heraklion seems a good pool for finding potential donors since 46.8-49.1% of common HLA haplotype needs are met between the former and each Prefecture. Summary/Conclusion: The in-depth immunogenetic profile of the Cretan population justifies the reported HLA diversity compared to the European populations of DKMS. The significant differences in the estimated haplotype frequencies between the Cretan Prefectures substantiates the importance of geographically or genetically isolated population clusters in the regional UCB banking and donor selection.

Human leukocyte antigen allele and haplotype frequencies in Singapore bone marrow donors and cord blood units.

We describe the allele and haplotype frequencies seen in a volunteer unrelated bone marrow donor registry, a public cord blood bank, and donor/recipient samples processed by the Health Sciences Authority (HSA) in Singapore. Historical human leukocyte antigen (HLA) typing reports were anonymized and combined. They were checked for HLA typing nomenclature discrepancies or ambiguities using the HLA-net UNIFORMATE tool, and for analysis, the validated data were subsequently separated into Chinese, Malay, Indian, and "Others," according to the race classification system used in Singapore. Individual ethnic allele and haplotype frequencies were calculated with the HLA-net GENE[RATE] pipeline using basic statistics. The Basic Statistics Tool of HLA-net was used to estimate haplotype frequency using an expectation maximization algorithm, given a set of multi-allelic data pairs for a given HLA locus. The outputs downloaded from the site comprised plain text files with haplotype frequency estimates, results of a global linkage disequilibrium test, and standardized residuals (stdres) corresponding to deviations from expected frequencies. HLA typing results from 59,186 individuals met the inclusion criteria, yielding 118,372 analyzable alleles. In our study population, the haplotype A*33:03-B*58:01-C*03:02-DRB1*03:01～DQB1*02:01:01G with a frequency of 4.91% was the most common. This haplotype was also the most common among Singaporean Chinese donors. Consistent with the predominant Chinese population, haplotypes with a frequency greater than 1% were also the most frequently observed haplotypes in the Singaporean population. In the Malay donor population, the most common haplotype was A*33:03～B*44:03～C*07:01:01G～ DRB1*07:01-DQB1*02:01:01G, with a frequency of 3.41%, whereas within the Indian donor population, the most common haplotype was A*01:01-B*57:01-C*06:02～DRB1*07:01-DQB1*03:03, with a frequency of 3.42%. Haplotype diversity and composition statistics within donor pools provide HLA background data required for the targeted recruitment of donors to support the hematopoietic stem cell donor requirements of the country. These data may be used in the future to devise donor recruitment strategies for optimizing the donor pool through targeted publicity and accruals.

Graphical user interface for the haplotype frequency estimation software Hapl-o-Mat

Population-specific human leukocyte antigen (HLA) haplotype frequencies are an essential basis of advanced algorithms for donor selection in unrelated hematopoietic stem cell transplantation. In 2016, we introduced Hapl-o-Mat, a versatile tool for haplotype frequency estimation based on an expectation-maximization algorithm (https://github.com/DKMS/hapl-o-Mat). Hapl-o-Mat is specifically tailored to the analysis of HLA genes and able to cope with the heterogeneous genotyping data usually found in donor registries. To make Hapl-o-Mat accessible to a wider range of users, we designed a graphical user interface module that considerably facilitates the interaction with the application (https://github.com/DKMS/hapl-o-Mat_GUI). We further provide a precompiled version of Hapl-o-Mat that can be used on Windows personal computers without dependency on additional software libraries (https://github.com/DKMS/hapl-o-Mat_WinBin). We are confident that these new, user-oriented features will encourage more researchers to apply Hapl-o-Mat to their data, thereby increasing knowledge and public availability of population-specific HLA haplotype frequencies.

Osteopontin Gene Polymorphisms rs1126616 C>T and rs1126772 A>G are Associated with Atopic Dermatitis in Polish Population.

PurposeAtopic dermatitis (AD) is a chronic, relapsing inflammatory disease, caused by environmental and genetic factors, which lead to immunological abnormalities. Osteopontin (OPN), also named secreted phosphoprotein 1 (SPP1), is a protein involved in the pathogenesis of numerous autoimmune and inflammatory conditions. However, its role in AD has not been fully elucidated. Therefore, we aim to gain an insight into the role of OPN in AD pathogenesis through investigating its gene single nucleotide polymorphisms (SNPs) and their possible associations with disease clinical features.Patients and MethodsA total of 182 Caucasian participants (45 AD patients and 137 gender- and age-matched controls) were studied. Genomic DNA was isolated from peripheral blood samples. Genotyping for the rs1126616 C>T, rs1126772 A>G, rs9138 A>C, and rs3841116 T>G SNPs was performed by real time polymerase chain reaction (RT-PCR).ResultsThe frequency of the minor TT genotype and the T allele of rs1126616 C>T was higher in AD patients compared to controls (P = 0.019, OD = 4.86, 95% CI = 1.46–16.20, and P = 0.047, OR = 1.77, 95% CI = 1.04–3.00, respectively) and was associated with the higher prevalence of asthma (P = 0.017, OR = 3.73, 95% CI = 0.71–19.67, and P = 0.004, OR = 3.96, 95% CI = 1.53–10.25, respectively). Likewise, the minor GG genotype and the G allele of rs1126772 A>G were more frequent in AD patients (P = 0.026, OR = 3.27, 95% CI = 1.29–8.33, and P = 0.013, OR = 1.94, 95% CI = 1.18–3.21, respectively) and were associated with the increased incidence of asthma (P = 0.016, OR = 5.06, 95% CI = 1.14–22.49, and P = 0.002, OR = 4.40, 95% CI = 1.71–11.35, respectively). Furthermore, haplotype frequency estimation determined the four-loci haplotype TGCT, as a significant risk factor for AD compared to controls (P = 0.031, OR = 9.48, 95% CI = 1.23–71.91).ConclusionOur results suggest that the variation in the OPN gene might be associated with AD and increased incidence of asthma in Caucasians. Further studies should be conducted to look into the possible role of OPN as a biomarker for AD.

HLA haplotype frequency estimation for heterogeneous populations using a graph-based imputation algorithm

HLA haplotype frequencies are estimated from ambiguous unphased HLA genotyping data using Expectation-Maximization (EM) algorithms. Current population genetics methods require independent EM frequency estimates for each population, and assume that each population is in Hardy-Weinberg Equilibrium (HWE). The HWE assumption of EM has thus far resulted in the exclusion of individuals from mixed or unknown ethnic backgrounds from reference datasets. Multi-region populations are currently poorly served by stem cell donor registry HLA imputation and matching implementations due to the inability of such algorithms to incorporate admixture into their population genetics models. To address this unmet need, we have expanded the imputation component of our GRaph IMputation and Matching (GRIMM) framework, where imputation becomes the expectation step in an iterative EM algorithm. Our novel multi-region EM implementation considers region as a Bayesian prior, enabling integration of HLA information from multiple single-region population groups, and for the first time including individuals with ambiguous or mixed ethnic backgrounds. We show that our multi-region EM produces much higher likelihood values and better haplotype recovery as measured by Kullback-Leibler divergence than all evaluated EM implementations when tested on real datasets of US donor registry HLA typings as well as simulated multi-region datasets of ambiguous HLA typings.

Markov chain Monte Carlo Gibbs sampler approach for estimating haplotype frequencies among multiple malaria infected human blood samples

BackgroundMalaria patients can have two or more haplotypes in their blood sample making it challenging to identify which haplotypes they carry. In addition, there are challenges in measuring the type and frequency of resistant haplotypes in populations. This study presents a novel statistical method Gibbs sampler algorithm to investigate this issue.ResultsThe performance of the algorithm is evaluated on simulated datasets consisting of patient blood samples characterized by their multiplicity of infection (MOI) and malaria genotype. The simulation used different resistance allele frequencies (RAF) at each Single Nucleotide Polymorphisms (SNPs) and different limit of detection (LoD) of the SNPs and the MOI. The Gibbs sampler algorithm presents higher accuracy among high LoD of the SNPs or the MOI, validated, and deals with missing MOI compared to previous related statistical approaches.ConclusionsThe Gibbs sampler algorithm provided robust results when faced with genotyping errors caused by LoDs and functioned well even in the absence of MOI data on individual patients.

HLA diversity in the Russian population assessed by next generation sequencing

Next generation sequencing is used to determine full-length sequences of HLA genes at the 4-field (allelic) resolution. The study was aimed at determining frequency and diversity of HLA alleles in a cohort of blood donors from the Registry of the National Research Center for Hematology who design ated themselves as Russians (including some not routinely typed variations in HLA gene regions). The studied population consisted of 1510 donors. HLA typing was performed by next generation sequencing. Libraries were performed with AllType NGS Amplification Kits (One Lambda, USA) and sequenced using MiSeq (Illumina, USA). Data analysis used the TypeStream Visual Software V2.0.0.68 (One Lambda, USA) and IPD-IMGT/HLA database 3.40.0.1. Arlequin 3.5 software was used for estimation of allele and haplotype frequencies, deviation from Hardy-Weinberg equilibrium. 82 HLA-A, 156 HLA-В and 85 HLA-С alleles were identified with four-field resolution. 45 HLA-DRB1 and 18 HLA-DQB1 alleles were identified with 2-3-field resolution. Considerable HLA diversity was found among the donors self-designated as Russians: the population had large numbers of distinct alleles at each HLA gene, high percentage of alleles (25-32% of HLA class I) were revealed only once. Sufficient numbers of new alleles were registered which are absent in the IPD-IMGT/HLA database. Considerable allelic diversity in Russian population is due to low-incidence alleles. Despite this diversity, the majority of HLA alleles detected at each locus were common. Significant HLA diversity of the donors was connected with a large number of alleles with rare occurrence. The novel alleles identified in our study differed from the known alleles by single nucleotide substitutions. The most common alleles at the four-field level were as follows: A*02:01:01:01 (27.1%), C*07:02:01:03 (13.1%), A*03:01:01:01 (13.0%), B*07:02:01:01 (13.0%), A*01:01:01:01 (11.6%) and C*07:01:01:01/16 (10.4%). The HLA alleles, which are common for Russian populations, are not always common or well-documented alleles in present catalogues. The data obtained in this study may be used as a reference sample for estimation of HLA allele frequencies in Russian population, for proper frequency evaluation of specific alleles when searching donors for allogeneic hematopoietic stem cell transplantation, as well as for association studies between HLA alleles and different diseases, and for research in population genetics.

Characterization of a Sex-Determining Region and Its Genomic Context via Statistical Estimates of Haplotype Frequencies in Daughters and Sons Sequenced in Pools.

Sex chromosomes are generally derived from a pair of autosomes that have acquired a locus controlling sex. Sex chromosomes may evolve reduced recombination around this locus and undergo a long process of molecular divergence. At that point, the original loci controlling sex may be difficult to pinpoint. This difficulty has affected many model species from mammals to birds to flies, which present highly diverged sex chromosomes. Identifying sex-controlling loci is easier in species with molecularly similar sex chromosomes. Here we aimed at pinpointing the sex-determining region (SDR) of Armadillidium vulgare, a terrestrial isopod with female heterogamety (ZW females and ZZ males) and whose sex chromosomes appear to show low genetic divergence. To locate the SDR, we assessed single-nucleotide polymorphism (SNP) allele frequencies in F1 daughters and sons sequenced in pools (pool-seq) in several families. We developed a Bayesian method that uses the SNP genotypes of individually sequenced parents and pool-seq data from F1 siblings to estimate the genetic distance between a given genomic region (contig) and the SDR. This allowed us to assign more than 43 Mb of contigs to sex chromosomes, and to demonstrate extensive recombination and very low divergence between these chromosomes. By taking advantage of multiple F1 families, we delineated a very short genomic region (∼65 kb) that presented no evidence of recombination with the SDR. In this short genomic region, the comparison of sequencing depths between sexes highlighted female-specific genes that have undergone recent duplication, and which may be involved in sex determination in A. vulgare.