Reliable Haplotype Research Articles

ARHap: Association Rule Haplotype Phasing.

This article proposes a novel approach for Individual Human phasing through discovery of interesting hidden relations among single variant sites. The proposed framework, called ARHap, learns strong association rules among variant loci on the genome and develops a combinatorial approach for fast and accurate haplotype phasing based on the discovered associations. ARHap is composed of two main modules or processing phases. In the first phase, called association rule learning, ARHap identifies quantitative association rules from a collection of DNA reads of the organism under study, resulting in a set of strong rules that reveal the inter-dependency of alleles. In the next phase, called haplotype reconstruction, we develop algorithms to utilize the learned rules to construct highly reliable haplotypes at individual single nucleotide polymorphism (SNP) sites. ARHap has several features that lead to both fast and accurate haplotyping. It uses an incremental haplotype reconstruction approach that enables us to generate association rules according to the unreconstructed SNP sites during each round of the algorithm. During each round, the association rule learning module generates rules while constraining the length of the rules and limiting the rules to those that contribute to reconstruction of unreconstructed sites only. The framework begins by generating rules of small size and highly strong. The rule length can increase and/or criteria about strongness of the rule are adjusted gradually, during subsequent rounds, if some SNP sites have remained unreconstructed. This adaptive approach, which uses feedback from haplotype reconstruction module, eliminates generation of rules that do not contribute to haplotype reconstruction as well as weak rules that may introduce error in the final haplotypes. Extensive experimental analyses on datasets representing diploid organisms demonstrate superiority of ARHap in diploid haplotyping compared to the state-of-the-art algorithms. In particular, we show that this novel approach to haplotype phasing not only is fast but also achieves significantly better accuracy performance compared to other read-based computational approaches.

Metabarcoding for biodiversity inventory blind spots: A test case using the beetle fauna of an insular cloud forest.

Soils harbour a rich arthropod fauna, but many species are still not formally described (Linnaean shortfall) and the distribution of those already described is poorly understood (Wallacean shortfall). Metabarcoding holds much promise to fill this gap, however, nuclear copies of mitochondrial genes, and other artefacts lead to taxonomic inflation, which compromise the reliability of biodiversity inventories. Here, we explore the potential of a bioinformatic approach to jointly "denoise" and filter nonauthentic mitochondrial sequences from metabarcode reads to obtain reliable soil beetle inventories and address open questions in soil biodiversity research, such as the scale of dispersal constraints in different soil layers. We sampled cloud forest arthropod communities from 49 sites in the Anaga peninsula of Tenerife (Canary Islands). We performed whole organism community DNA (wocDNA) metabarcoding, and built a local reference database with COI barcode sequences of 310 species of Coleoptera for filtering reads and the identification of metabarcoded species. This resulted in reliable haplotype data after considerably reducing nuclear mitochondrial copies and other artefacts. Comparing our results with previous beetle inventories, we found: (i) new species records, potentially representing undescribed species; (ii) new distribution records, and (iii) validated phylogeographic structure when compared with traditional sequencing approaches. Analyses also revealed evidence for higher dispersal constraint within deeper soil beetle communities, compared to those closer to the surface. The combined power of barcoding and metabarcoding contribute to mitigate the important shortfalls associated with soil arthropod diversity data, and thus address unresolved questions for this vast biodiversity fraction.

Application of Dual Metabarcoding Platforms for the Meso- and Macrozooplankton Taxa in the Ross Sea.

Meso- and macrozooplankton play crucial roles in the trophic web and the biological carbon pump in the ocean by transferring energy from lower to higher trophic levels and vertically exporting carbon from the surface to the deep ocean and seabed. In this study, zooplankton community structures in the Ross Sea, Antarctica, were analyzed using metabarcoding methods. Both regular barcode (RB) (using a PacBio Sequel system) and mini barcode (MB) (using the Illumina MiSeq platform) methods were utilized. As the result of a combination of the two bioinformatic pipelines used in the RB, 55 reliable haplotypes were obtained from the pooled zooplankton net samples, whereas 183 amplicon sequence variants (ASVs) were isolated from the MB metabarcoding analyses of 14 individual stations. Among these, 39 (70.9%) and 125 (90.6%) showed higher than 99% sequence identity to the database, indicating that there were sufficient reference sequences to employ metabarcoding analysis—except for several taxa, including small-sized copepods, cnidarians, and pneumodermatids. A high degree of shared taxa showed that both metabarcoding analyses were feasible for use in the analysis of zooplankton assemblages in the Ross Sea. However, RB would be more useful for the construction of a reference database due to its relatively high cost, whereas MB would be more economic for ecological surveys due to its relatively low cost (albeit, only if reference sequences were well documented using RB). Zooplankton assemblages were highly diverse in each sample site, presumably due to the narrow covered volumes of the vertical net-towed samples from polynyas in the Ross Sea. As metabarcoding data accumulate, we will gain better insights into zooplankton communities and their ecological implications in the Ross Sea.

Genome-wide association study for starch content and constitution in sorghum (Sorghum bicolor (L.) Moench)

Starch is the most important component in endosperm of sorghum grain. Usually, two types of starch are present: amylose (AM) and amylopectin (AP). The levels of AM and AP contents play a significant role in the appearance, structure, and quality of sorghum grains and in marketing applications. In the present study, a panel of 634 sorghum (Sorghum bicolor (L.) Moench) accessions were evaluated for starch, AM, and AP contents of grain, which included a mini core collection of 242 accessions from the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) in India, and 252 landraces and 140 cultivars from China. The average starch content was 67.64% and the average AM and AP contents were 20.19 and 79.81%, respectively. We developed a total of 260 000 high-confidence single nucleotide polymorphism (SNP) markers in the panel of 634 accessions of S. bicolor using specific locus amplified fragment sequencing (SLAF-seq). We performed genome-wide association studies (GWAS) of starch, AM, and AM/AP of grain and SNP markers based on a mixed linear model (MLM). In total, 70 significant association signals were detected for starch, AM, and AM/AP ratio of grain with P<4.452×10–7, of which 10 SNPs were identified with significant starch, 51 SNPs were associated with AM, and nine SNPs were associated with the AM/AP ratio. The Gene Ontology (GO) analysis identified 12 candidate genes at five QTLs associated with starch metabolism within the 200-kb intervals, located on chromosomes 1, 5, 6, and 9. Of these genes, Sobic.006G036500.1 encodes peptidyl-prolyl cis-trans-isomerase CYP38 responsible for hexose monophosphate shunt (HMS) and Sobic.009G071800 encodes 6-phospho-fructokinase (PFK), which is involved in the embden-meyerhof pathway (EMP). Kompetitive allele specific PCR (KASP) markers were developed to validate the GWAS results. The C allele is correlated with a high starch content, while the T allele is linked with a low level of starch content, and provides reliable haplotypes for MAS in sorghum quality improvement.

A Genome-Wide Association Study of Wheat Spike Related Traits in China.

Rapid detection of allelic variation and identification of advantage haplotypes responsible for spike related traits play a crucial role in wheat yield improvement. The released genome sequence of hexaploid wheat (Chinese Spring) provides an extraordinary opportunity for rapid detection of natural variation and promotes breeding application. Here, selection signals detection and genome-wide association study (GWAS) were conducted for spike related traits. Based on the genotyping results by 90K SNP chip, 192 common wheat samples from southwest China were analyzed. One hundred and forty-six selective windows and one hundred and eighty-four significant SNPs (51 for spike length, 28 for kernels per spike, 39 for spikelet number, 30 for thousand kernel weight, and 36 for spike number per plant) were detected. Furthermore, tightly linkage and environmental stability window clusters and SNP clusters were also obtained. As a result, four SNP clusters associated with spike length were detected on chromosome 2A, 2B, 2D, and 6A. Two SNP clusters correlated to kernels per spike were detected on 2A and 2B. One pleiotropy SNP cluster correlated to spikelet number and kernels per spike was detected on 7B. According to the genome sequence, these SNP clusters and their overlapped/flanking QTLs which have been reported previously were integrated to a physical map. The candidate genes responsible for spike length, kernels per spike and spikelet number were predicted. Based on the genotypes of cultivars in south China, two advantage haplotypes associated with spike length and one advantage haplotype associated with kernels per spike/spikelet number were detected which have not been effectively transited into cultivars. According to these haplotypes, KASP markers were developed and diagnosed across landraces and cultivars which were selected from south and north China. Consequently, KASP assay, consistent with the GWAS results, provides reliable haplotypes for MAS in wheat yield improvement.

Development of a new S locus haplotyping system based on three tightly linked genes in the S locus controlling self-incompatibility in radish (Raphanus sativus L.)

To develop an efficient and reliable haplotype identification system of the S locus controlling self-incompatibility (SI) in radish (Raphanus sativus L.), polymorphic sequences of the SLL2 and SP6 genes, which were located at each border of the S core regions, were used together with those of the SRK gene, the female determinant of SI. Partial sequences of the SP6 and SRK genes were isolated from 35 diverse breeding lines that showed differential self-incompatibility responses. A total of 25 SP6 and 29 SRK alleles were isolated in this study, and 29 SLL2 alleles isolated from the previous study were included for the S haplotyping. Whereas the phylogenetic tree of the SP6 alleles showed species-specific clustering patterns, the phylogenetic tree of the SRK alleles revealed intergeneric pairing of some SRK alleles, although the others showed species-specific clustering. Among 35 breeding lines, 13 had combinations of the unique SLL2, SRK, and SP6 alleles, but the others shared a common allele of either SLL2 or SP6 genes. Except for two breeding lines that contained the same SLL2, SRK, and SP6 alleles, all breeding lines were shown to harbor unique haplotypes that consisted of different combinations of SLL2, SRK, and SP6 alleles. When 73 additional diverse breeding lines were analyzed by this new S locus haplotyping system, the haplotypes of all breeding lines were clearly identified. In addition, eight new combinations that contained different combinations of the SLL2, SRK, and SP6 alleles were identified.

PEATH: single-individual haplotyping by a probabilistic evolutionary algorithm with toggling.

Single-individual haplotyping (SIH) is critical in genomic association studies and genetic diseases analysis. However, most genomic analysis studies do not perform haplotype-phasing analysis due to its complexity. Several computational methods have been developed to solve the SIH problem, but these approaches have not generated sufficiently reliable haplotypes. Here, we propose a novel SIH algorithm, called PEATH (Probabilistic Evolutionary Algorithm with Toggling for Haplotyping), to achieve more accurate and reliable haplotyping. The proposed PEATH method was compared to the most recent algorithms in terms of the phased length, N50 length, switch error rate and minimum error correction. The PEATH algorithm consistently provides the best phase and N50 lengths, as long as possible, given datasets. In addition, verification of the simulation data demonstrated that the PEATH method outperforms other methods on high noisy data. Additionally, the experimental results of a real dataset confirmed that the PEATH method achieved comparable or better accuracy. Source code of PEATH is available at https://github.com/jcna99/PEATH. jkrhee@catholic.ac.kr or sooyong.shin@gmail.com. Supplementary data are available at Bioinformatics online.

P191 A first evaluation of the HLA-A gene 3′ untranslated region diversity in Brazil and its relationship with coding haplotypes

Aim Here we propose a NGS strategy to evaluate the HLA-A coding and 3′UTR variability and get reliable haplotypes. Then, we present the data obtained in very admixed population (Brazil). Methods The HLA-Agene segment was amplified in a unique amplicon considering 408 Brazilian individuals. Amplicons were sequenced by NGS and data processed using hla-mapper and a local pipeline to get genotypes and haplotypes. Allele and haplotype frequencies, together with Linkage Disequilibrium (LD) plots, were also calculated. Results According to the human genome draft version hg38, and known HLA-A transcripts available, the HLA-A 3′UTR comprises a segment of 433 nucleotides. However, only 70 percent of this segment is considered at the IPD-IMGT/HLA database. A total of 21 variable sites were found in the 3′UTR and, together, they were organized in 11 different haplotypes. Seven of those variants were detected outside the segment tracked by the IMGT/HLA database. We observed a high LD throughout the HLA-A locus and associations between each of these 3′UTR haplotypes and specific coding alleles. Thus, in many cases, it is possible to detect the HLA-A allele group by targeting one or two variations at the 3′UTR. Although few haplotypes were detected, they were quite frequent. It is possible that the variability detected at this segment would influence allelic expression, mainly by posttranscriptional mechanisms through microRNA binding. Conclusions The HLA-A locus is one of the most variable genes on the human genome. Most of its variability was described within exons 2 and 3, which encode the peptide-binding groove. Thus, these segment are usually the only ones targeted by many HLA-A studies. Little is known regarding the HLA-Aregulatory segments variability, including its 3′ untranslated region (3′UTR). Thus, HLA-A 3′UTR present few but frequent haplotypes, and each of these haplotype is associated with a specific group of coding alleles, which in turn may present a similar post transcriptional profile.

Information-Theoretic Analysis of Haplotype Assembly

This paper studies the haplotype assembly problem from an information-theoretic perspective. In the human genome, a haplotype is a sequence of nucleotide bases on a chromosome that differ from the bases in the corresponding positions on the other chromosome in a homologous pair. Haplotype sequences can conveniently be represented by binary strings, which enable us to transform the bioinformatics problem of haplotype assembly into an equivalent information-theoretic problem. Information about the order of bases in a genome is readily inferred using short reads provided by high-throughput DNA sequencing technologies. Performing haplotype assembly is challenging due to limited lengths of the reads and the presence of sequencing errors. In this paper, the recovery of the target pair of haplotype sequences using short reads is transformed into an equivalent joint source-channel coding problem. Two binary messages, representing haplotypes and chromosome memberships of reads, are encoded and transmitted over a channel with erasures and errors, where the channel model reflects salient features of high-throughput sequencing. The focus of this paper is on determining the required number of reads for reliable haplotype reconstruction. For the error-free reading case, erasure decoding is shown to be one of the optimal algorithms enabling reliable haplotype assembly. For the erroneous reading case, spectral partitioning is proved to be an efficient algorithm with orderwise optimal bounds.

RNA-Seq bulked segregant analysis enables the identification of high-resolution genetic markers for breeding in hexaploid wheat.

The identification of genetic markers linked to genes of agronomic importance is a major aim of crop research and breeding programmes. Here, we identify markers for Yr15, a major disease resistance gene for wheat yellow rust, using a segregating F2 population. After phenotyping, we implemented RNA sequencing (RNA-Seq) of bulked pools to identify single-nucleotide polymorphisms (SNP) associated with Yr15. Over 27000 genes with SNPs were identified between the parents, and then classified based on the results from the sequenced bulks. We calculated the bulk frequency ratio (BFR) of SNPs between resistant and susceptible bulks, selecting those showing sixfold enrichment/depletion in the corresponding bulks (BFR>6). Using additional filtering criteria, we reduced the number of genes with a putative SNP to 175. The 35 SNPs with the highest BFR values were converted into genome-specific KASP assays using an automated bioinformatics pipeline (PolyMarker) which circumvents the limitations associated with the polyploid wheat genome. Twenty-eight assays were polymorphic of which 22 (63%) mapped in the same linkage group as Yr15. Using these markers, we mapped Yr15 to a 0.77-cM interval. The three most closely linked SNPs were tested across varieties and breeding lines representing UK elite germplasm. Two flanking markers were diagnostic in over 99% of lines tested, thus providing a reliable haplotype for marker-assisted selection in these breeding programmes. Our results demonstrate that the proposed methodology can be applied in polyploid F2 populations to generate high-resolution genetic maps across target intervals.

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.

IXora: exact haplotype inferencing and trait association

BackgroundWe address the task of extracting accurate haplotypes from genotype data of individuals of large F1 populations for mapping studies. While methods for inferring parental haplotype assignments on large F1 populations exist in theory, these approaches do not work in practice at high levels of accuracy.ResultsWe have designed iXora (Identifying crossovers and recombining alleles), a robust method for extracting reliable haplotypes of a mapping population, as well as parental haplotypes, that runs in linear time. Each allele in the progeny is assigned not just to a parent, but more precisely to a haplotype inherited from the parent. iXora shows an improvement of at least 15% in accuracy over similar systems in literature. Furthermore, iXora provides an easy-to-use, comprehensive environment for association studies and hypothesis checking in populations of related individuals.ConclusionsiXora provides detailed resolution in parental inheritance, along with the capability of handling very large populations, which allows for accurate haplotype extraction and trait association. iXora is available for non-commercial use from http://researcher.ibm.com/project/3430.

MixSIH: a mixture model for single individual haplotyping

BackgroundHaplotype information is useful for various genetic analyses, including genome-wide association studies. Determining haplotypes experimentally is difficult and there are several computational approaches that infer haplotypes from genomic data. Among such approaches, single individual haplotyping or haplotype assembly, which infers two haplotypes of an individual from aligned sequence fragments, has been attracting considerable attention. To avoid incorrect results in downstream analyses, it is important not only to assemble haplotypes as long as possible but also to provide means to extract highly reliable haplotype regions. Although there are several efficient algorithms for solving haplotype assembly, there are no efficient method that allow for extracting the regions assembled with high confidence.ResultsWe develop a probabilistic model, called MixSIH, for solving the haplotype assembly problem. The model has two mixture components representing two haplotypes. Based on the optimized model, a quality score is defined, which we call the 'minimum connectivity' (MC) score, for each segment in the haplotype assembly. Because existing accuracy measures for haplotype assembly are designed to compare the efficiency between the algorithms and are not suitable for evaluating the quality of the set of partially assembled haplotype segments, we develop an accuracy measure based on the pairwise consistency and evaluate the accuracy on the simulation and real data. By using the MC scores, our algorithm can extract highly accurate haplotype segments. We also show evidence that an existing experimental dataset contains chimeric read fragments derived from different haplotypes, which significantly degrade the quality of assembled haplotypes.ConclusionsWe develop a novel method for solving the haplotype assembly problem. We also define the quality score which is based on our model and indicates the accuracy of the haplotypes segments. In our evaluation, MixSIH has successfully extracted reliable haplotype segments. The C++ source code of MixSIH is available at https://sites.google.com/site/hmatsu1226/software/mixsih.

Fosmid-based whole genome haplotyping of a HapMap trio child: evaluation of Single Individual Haplotyping techniques

Determining the underlying haplotypes of individual human genomes is an essential, but currently difficult, step toward a complete understanding of genome function. Fosmid pool-based next-generation sequencing allows genome-wide generation of 40-kb haploid DNA segments, which can be phased into contiguous molecular haplotypes computationally by Single Individual Haplotyping (SIH). Many SIH algorithms have been proposed, but the accuracy of such methods has been difficult to assess due to the lack of real benchmark data. To address this problem, we generated whole genome fosmid sequence data from a HapMap trio child, NA12878, for which reliable haplotypes have already been produced. We assembled haplotypes using eight algorithms for SIH and carried out direct comparisons of their accuracy, completeness and efficiency. Our comparisons indicate that fosmid-based haplotyping can deliver highly accurate results even at low coverage and that our SIH algorithm, ReFHap, is able to efficiently produce high-quality haplotypes. We expanded the haplotypes for NA12878 by combining the current haplotypes with our fosmid-based haplotypes, producing near-to-complete new gold-standard haplotypes containing almost 98% of heterozygous SNPs. This improvement includes notable fractions of disease-related and GWA SNPs. Integrated with other molecular biological data sets, this phase information will advance the emerging field of diploid genomics.

The Effect of Aquaporin 2 Gene Variations on Plasma Levels of von Willebrand Factor and Factor VIII and on the Risk of Venous Thrombosis.

High levels of von Willebrand factor (VWF) and factor VIII (FVIII) are a risk factor for thrombosis. Determinants of high VWF and FVIII levels are poorly understood. Secretion of VWF from endothelial storage pools is regulated by vasopressin type-2 receptor (V2R). Previously, we have shown that a V2R variant, which has increased binding affinity for its ligand vasopressin (AVP), is associated with increased levels of VWF and FVIII1. Nephrogenic Diabetes Insipidus (NDI) is a disorder characterized by renal insensitivity to AVP, caused by mutations in the genes encoding V2R or the aquaporin 2 water channel (AQP2). AQP2 expression is enhanced by stimulation of V2R. Patients with NDI are unable to concentrate their pre-urine. We hypothesized that carriers of AQP2 mutations compensate excess fluid loss by up-regulating AVP release and V2R expression, resulting in increased VWF and FVIII secretion. To test this hypothesis, we set up the Factor Eight in Nephrogenic Diabetus Insipidus study (FENDI), which includes 13 NDI families: 14 NDI patients (12 V2R- and 2 AQP2-linked), 14 carriers (9 V2R- and 5 AQP2-linked) and 25 unaffected family members, as well as 48 unrelated healthy individuals. In addition, we looked at effects of common AQP2 gene variations in a case-control study on venous thrombosis, the Leiden Thrombophilia Study (LETS), which consists of 474 patients with a first deep vein thrombosis and 474 healthy controls, sex and age matched to the patients. In the FENDI, no differences were observed between NDI patients, carriers and unaffected individuals in markers for fluid homeostasis such as hematocrite, serum osmolality and blood pressure. AVP reached detectable levels in all carriers of AQP2 mutations, compared to 27% and 56% in unrelated and related unaffected individuals, respectively. AVP levels, were, when detectable, elevated in all patients and carriers. VWF propeptide, a measure of the VWF secretion rate, VWF antigen and FVIII activity were also highest in carriers of AQP2 mutations. In the LETS, we sequenced a 6.6 kb long genomic region around the AQP2 gene in 25 selected individuals. We identified 18 single nucleotide polymorphisms (SNPs), of which 16 were genotyped in the entire LETS. Although reliable haplotypes could not be formed, due to recombination, the SNPs were linked within 5 clusters. In three of these clusters, up to 2.5-fold increases in thrombosis risk were observed. In these same clusters we observed associations of the AQP2 SNPs with arterial blood pressure. However, none of the AQP2 SNPs were associated with VWF or FVIII levels in healthy controls of the LETS. In conclusion, increased AVP levels in carriers of NDI-causing AQP2 mutations appear associated with increased VWF secretion. Furthermore, in the LETS, common AQP2 gene variations are associated with the risk of venous thrombosis.

Evaluation of sample size effect on the identification of haplotype blocks.

BackgroundGenome-wide maps of linkage disequilibrium (LD) and haplotypes have been created for different populations. Substantial sharing of the boundaries and haplotypes among populations was observed, but haplotype variations have also been reported across populations. Conflicting observations on the extent and distribution of haplotypes require careful examination. The mechanisms that shape haplotypes have not been fully explored, although the effect of sample size has been implicated. We present a close examination of the effect of sample size on haplotype blocks using an original computational simulation.ResultsA region spanning 19.31 Mb on chromosome 20q was genotyped for 1,147 SNPs in 725 Japanese subjects. One region of 445 kb exhibiting a single strong LD value (average |D'|; 0.94) was selected for the analysis of sample size effect on haplotype structure. Three different block definitions (recombination-based, LD-based, and diversity-based) were exploited to create simulations for block identification with θ value from real genotyping data. As a result, it was quite difficult to estimate a haplotype block for data with less than 200 samples. Attainment of a reliable haplotype structure with 50 samples was not possible, although the simulation was repeated 10,000 times.ConclusionThese analyses underscored the difficulties of estimating haplotype blocks. To acquire a reliable result, it would be necessary to increase sample size more than 725 and to repeat the simulation 3,000 times. Even in one genomic region showing a high LD value, the haplotype block might be fragile. We emphasize the importance of applying careful confidence measures when using the estimated haplotype structure in biomedical research.

Molecular haplotype determination using allele-specific PCR and pyrosequencing technology

Haplotyping of single-nucleotide polymorphisms (SNPs) is usually performed statistically by computational analysis or by time-consuming cloning techniques. Here we present a simple molecular approach for reliable haplotype determination on individual samples. The procedure is based on allele-specific PCR (AS-PCR) in combination with Pyrosequencing analysis. AS-PCR primers for each allelic variant of the investigated SNPs were used. A mismatch introduced at the second base from the 3′ end dramatically improved allele specificity. Analysis of multiple SNPs on amplified fragments using Pyrosequencing technology allowed determination of haplotypes. Genotyping of heterozygote samples after AS-PCR gave a typical monoallelic pattern at each SNP, in which the identity of the present allele depended on the allele-specific initial amplification. Haplotype determination by the described procedure proved to be highly reliable. The results obtained by Pyrosequencing technology have the benefit of being truly quantitative, enabling detection of any nonspecific allele amplification.

Facilitating haplotype analysis by fully automated analysis of all chromosomes in human-mouse hybrid cell lines

Recent evidence suggests that haplotype analysis is essential in recognizing genetic factors involved in the tendency toward a particular disease or pharmacogenetic phenotype, as well as to identify genes involved in multigenic disorders. Because of the increasing need for efficient haplotype tests, a new hybrid system, called conversion technology, was developed. Conversion technology aims at converting the diploid chromosome content into a haploid state so that hybrids contain a single copy of any desired chromosome. A number of mutations can now be identified easily, as they are no longer obscured by the normal sequence present on the other copy of the chromosome. However, the efficient use of this hybrid system depends on a complete analysis of both human and mouse chromosome complements in order to assess the stability of the hybrid cells and to accurately determine their human chromosome content. We describe a new multicolor FISH-based method capable of analyzing both genomes simultaneously in a single hybridization. This new technique should become an instrumental part of inexpensive, reliable haplotype tests.

Validation of haplotype frequency estimation methods

In order to investigate the performance of haplotype frequency estimation methods using unrelated individuals, we compared the results of three estimation methods with those from the haplotypes deduced from family pedigrees. To that end we used the HLA phenotypes of the parents of 1040 families as data for the estimation methods and the full pedigree information as data for the deductive method. We evaluated the results of the following estimation methods: the method using two by two tables described by Mattiuz et al., the maximum likelihood method described by Yasuda and Tsuji and a crude method that uses the information on homozygosity in the phenotypes. All estimation methods generate reliable haplotype frequencies for the more frequent haplotypes, but are unreliable for the less frequent haplotypes. The maximum likelihood estimation method shows the best overall correlation with the results of the deductive method.

Validation of large data sets, an essential prerequisite for data analysis: an analytical survey of the Bone Marrow Donors Worldwide.

Large data sets like the Bone Marrow Donors Worldwide (BMDW) data set can be used for population genetic analyses. The qualities of such data sets are unique. To be able to use the BMDW data for analyses, several problems, like limited size and selective DR typing, of the data have to be solved and the quality of the registry data subsets has to be examined. We describe these problems and methods to overcome them. Also, we give an overview of the qualities of the different registry subsets. Sixteen of the twenty-nine examined subsets contain data that can be used for population genetic analysis. We will deal with these analyses in the future. Additionally, we present a method to calculate the minimum number of individuals required for reliable haplotype frequency estimation.