Dataset Information

Estimation of German KIR Allele Group Haplotype Frequencies.

ABSTRACT: The impact of the highly polymorphic Killer-cell immunoglobulin-like receptor (KIR) gene cluster on the outcome of hematopoietic stem cell transplantation (HCST) is subject of current research. To further understand the involvement of this gene family into Natural Killer (NK) cell-mediated graft-versus-leukemia reactions, knowledge of haplotype structures, and allelic linkage is of importance. In this analysis, we estimate population-specific KIR haplotype frequencies at allele group resolution in a cohort of n = 458 German families. We addressed the polymorphism of the KIR gene complex and phasing ambiguities by a combined approach. Haplotype inference within first-degree family relations allowed us to limit the number of possible diplotypes. Structural restriction to a pattern set of 92 previously described KIR copy number haplotypes further reduced ambiguities. KIR haplotype frequency estimation was finally accomplished by means of an expectation-maximization algorithm. Applying a resolution threshold of ½ n, we were able to identify a set of 551 KIR allele group haplotypes, representing 21 KIR copy number haplotypes. The haplotype frequencies allow studying linkage disequilibrium in two-locus as well as in multi-locus analyses. Our study reveals associations between KIR haplotype structures and allele group frequencies, thereby broadening our understanding of the KIR gene complex.

SUBMITTER: Solloch UV

PROVIDER: S-EPMC7080815 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Estimation of German KIR Allele Group Haplotype Frequencies.

Solloch Ute V UV Schefzyk Daniel D Schäfer Gesine G Massalski Carolin C Kohler Maja M Pruschke Jens J Heidl Annett A Schetelig Johannes J Schmidt Alexander H AH Lange Vinzenz V Sauter Jürgen J

Frontiers in immunology 20200312

The impact of the highly polymorphic Killer-cell immunoglobulin-like receptor (<i>KIR</i>) gene cluster on the outcome of hematopoietic stem cell transplantation (HCST) is subject of current research. To further understand the involvement of this gene family into Natural Killer (NK) cell-mediated graft-versus-leukemia reactions, knowledge of haplotype structures, and allelic linkage is of importance. In this analysis, we estimate population-specific <i>KIR</i> haplotype frequencies at allele gro ...[more]

PMID: 32226430

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Project description:BackgroundIn addition to heterogeneity and artificial selection, natural selection is one of the forces used to combat climate change and improve agrobiodiversity in evolutionary plant breeding. Accurate identification of the specific genomic effects of natural selection will likely accelerate transfer between populations. Thus, insights into changes in allele frequency, adequate population size, gene flow and drift are essential. However, observing such effects often involves a trade-off between costs and resolution when a large sample of genotypes for many loci is analysed. Pool genotyping approaches achieve high resolution and precision in estimating allele frequency when sequence coverage is high. Nevertheless, high-coverage pool sequencing of large genomes is expensive.ResultsThree pool samples (n = 300, 300, 288) from a barley backcross population were generated to assess the population's allele frequency. The tested population (BC2F21) has undergone 18 generations of natural adaption to conventional farming practice. The accuracies of estimated pool-based allele frequencies and genome coverage yields were compared using three next-generation sequencing genotyping methods. To achieve accurate allele frequency estimates with low sequence coverage, we employed a haplotyping approach. Low coverage allele frequencies of closely located single polymorphisms were aggregated into a single haplotype allele frequency, yielding 2-to-271-times higher depth and increased precision. When we combined different haplotyping tactics, we found that gene and chip marker-based haplotype analyses performed equivalently or better compared with simple contig haplotype windows. Comparing multiple pool samples and referencing against an individual sequencing approach revealed that whole-genome pool re-sequencing (WGS) achieved the highest correlation with individual genotyping (≥ 0.97). In contrast, transcriptome-based genotyping (MACE) and genotyping by sequencing (GBS) pool replicates were significantly associated with higher error rates and lower correlations, but are still valuable to detect large allele frequency variations.ConclusionsThe proposed strategy identified the allele frequency of populations with high accuracy at low cost. This is particularly relevant to evolutionary plant breeding of crops with very large genomes, such as barley. Whole-genome low coverage re-sequencing at 0.03 × coverage per genotype accurately estimated the allele frequency when a loci-based haplotyping approach was applied. The implementation of annotated haplotypes capitalises on the biological background and statistical robustness.

Project description: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.

Project description:The killer cell immunoglobulin-like receptors (KIR) mediate human natural killer (NK) cell cytotoxicity via activating or inhibiting signals. Although informative and functional haplotype patterns have been reported, most genotyping has been performed at resolutions that are structurally ambiguous. In order to leverage structural information given low-resolution genotypes, we performed experiments to quantify the effects of population variations, reference haplotypes, and genotyping resolutions on population-level haplotype frequency estimations as well as predictions of individual haplotypes. We genotyped 10,157 unrelated individuals in 5 populations (518 African American[AFA], 258 Asian or Pacific Islander[API], 8,245 European[EUR], 1,073 Hispanic[HIS], and 63 Native American[NAM]) for KIR gene presence/absence (PA), and additionally half of the AFA samples for KIR gene copy number variation (CNV). A custom EM algorithm was used to estimate haplotype frequencies for each population by interpretation in the context of three sets of reference haplotypes. The algorithm also assigns each individual the haplotype pairs of maximum likelihood. Generally, our haplotype frequency estimates agree with similar previous publications to within <5% difference for all haplotypes. The exception is that estimates for NAM from the U.S. showed higher frequency association of cB02 with tA01 (+14%) instead of tB01 (-8.5%) compared to a previous study of NAM from south of the U.S. The higher-resolution CNV genotyping on the AFA samples allowed unambiguous haplotype-pair assignments for the majority of individuals, resulting in a 22% higher median typing resolution score (TRS), which measures likelihood of self-match in the context of population-specific haplo- and geno-types. The use of TRS to quantify reduced ambiguity with CNV data clearly revealed the few individuals with ambiguous genotypes as outliers. It is observed that typing resolution and reference haplotype set influence haplotype frequency estimates. For example, PA resolution may be used with reference haplotype sets up to the point where certain haplotypes are gene-content subsets of others. At that point, CNV must be used for all genes.

Dataset Information

Estimation of German KIR Allele Group Haplotype Frequencies.

Publications

Estimation of German KIR Allele Group Haplotype Frequencies.

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