Optimal Step Length EM Algorithm (OSLEM) for the estimation of haplotype frequency and its application in lipoprotein lipase genotyping

Background  

Haplotype based linkage disequilibrium (LD) mapping has become a powerful and cost-effective method for performing genetic association studies, particularly in the search for genetic markers in linkage disequilibrium with complex disease loci. Various methods (e.g. Monte-Carlo (Gibbs sampling); EM (expectation maximization); and Clark's method) have been used to estimate haplotype frequencies from routine genotyping data.     

Rainfall-driven sex-ratio genes in African buffalo suggested by correlations between Y-chromosomal haplotype frequencies and foetal sex ratio

Background  

The Y-chromosomal diversity in the African buffalo (Syncerus caffer) population of Kruger National Park (KNP) is characterized by rainfall-driven haplotype frequency shifts between year cohorts. Stable Y-chromosomal polymorphism is difficult to reconcile with haplotype frequency variations without assuming frequency-dependent selection or specific interactions in the population dynamics of X- and Y-chromosomal genes, since otherwise the fittest haplotype would inevitably sweep to fixation. Stable Y-chromosomal polymorphism due one of these factors only seems possible when there are Y-chromosomal distorters of an equal sex ratio, which act by negatively affecting X-gametes, or Y-chromosomal suppressors of a female-biased sex ratio. These sex-ratio (SR) genes modify (suppress) gamete transmission in their own favour at a fitness cost, allowing for stable polymorphism.     

Nuclear gene phylogeography using PHASE: dealing with unresolved genotypes,lost alleles,and systematic bias in parameter estimation

Background  

A widely-used approach for screening nuclear DNA markers is to obtain sequence data and use bioinformatic algorithms to estimate which two alleles are present in heterozygous individuals. It is common practice to omit unresolved genotypes from downstream analyses, but the implications of this have not been investigated. We evaluated the haplotype reconstruction method implemented by PHASE in the context of phylogeographic applications. Empirical sequence datasets from five non-coding nuclear loci with gametic phase ascribed by molecular approaches were coupled with simulated datasets to investigate three key issues: (1) haplotype reconstruction error rates and the nature of inference errors, (2) dataset features and genotypic configurations that drive haplotype reconstruction uncertainty, and (3) impacts of omitting unresolved genotypes on levels of observed phylogenetic diversity and the accuracy of downstream phylogeographic analyses.     

A novel tool for individual haplotype inference using mixed data

Background

In many studies, researchers may recruit samples consisting of independent trios and unrelated individuals. However, most of the currently available haplotype inference methods do not cope well with these kinds of mixed data sets.

Methods

We propose a general and simple methodology using a mixture of weighted multinomial (MIXMUL) approach that combines separate haplotype information from unrelated individuals and independent trios for haplotype inference to the individual level.

Results

The new MIXMUL procedure improves over existing methods in that it can accurately estimate haplotype frequencies from mixed data sets and output probable haplotype pairs in optimized reconstruction outcomes for all subjects that have contributed to estimation. Simulation results showed that this new MIXMUL procedure competes well with the EM-based method, i.e. FAMHAP, under a few assumed scenarios.

Conclusion

The results showed that MIXMUL can provide accurate estimates similar to those haplotype frequencies obtained from FAMHAP and output the probable haplotype pairs in the most optimal reconstruction outcome for all subjects that have contributed to estimation. If available data consist of combinations of unrelated individuals and independent trios, the MIXMUL procedure can be used to estimate the haplotype frequencies accurately and output the most likely reconstructed haplotype pairs of each subject in the estimation.     

Haplotype allelic classes for detecting ongoing positive selection

Background  

Natural selection eliminates detrimental and favors advantageous phenotypes. This process leaves characteristic signatures in underlying genomic segments that can be recognized through deviations in allelic or haplotypic frequency spectra. To provide an identifiable signature of recent positive selection that can be detected by comparison with the background distribution, we introduced a new way of looking at genomic polymorphisms: haplotype allelic classes.     

htSNPer1.0: software for haplotype block partition and htSNPs selection

Background  

There is recently great interest in haplotype block structure and haplotype tagging SNPs (htSNPs) in the human genome for its implication on htSNPs-based association mapping strategy for complex disease. Different definitions have been used to characterize the haplotype block structure in the human genome, and several different performance criteria and algorithms have been suggested on htSNPs selection.     

ParaHaplo 2.0: a program package for haplotype-estimation and haplotype-based whole-genome association study using parallel computing

Background  

The use of haplotype-based association tests can improve the power of genome-wide association studies. Since the observed genotypes are unordered pairs of alleles, haplotype phase must be inferred. However, estimating haplotype phase is time consuming. When millions of single-nucleotide polymorphisms (SNPs) are analyzed in genome-wide association study, faster methods for haplotype estimation are required.     

Evidence for Positive Selection on the Osteogenin (BMP3) Gene in Human Populations

Background

Human skeletal system has evolved rapidly since the dispersal of modern humans from Africa, potentially driven by selection and adaptation. Osteogenin (BMP3) plays an important role in skeletal development and bone osteogenesis as an antagonist of the osteogenic bone morphogenetic proteins, and negatively regulates bone mineral density.

Methodology/Principal Findings

Here, we resequenced the BMP3 gene from individuals in four geographically separated modern human populations. Features supportive of positive selection in the BMP3 gene were found including the presence of an excess of nonsynonymous mutations in modern humans, and a significantly lower genetic diversity that deviates from neutrality. The prevalent haplotypes of the first exon region in Europeans demonstrated features of long-range haplotype homogeneity. In contrast with findings in European, the derived allele SNP Arg192Gln shows higher extended haplotype homozygosity in East Asian. The worldwide allele frequency distribution of SNP shows not only a high-derived allele frequency in Asians, but also in Americans, which is suggestive of functional adaptation.

Conclusions/Significance

In conclusion, we provide evidence for recent positive selection operating upon a crucial gene in skeletal development, which may provide new insight into the evolution of the skeletal system and bone development.     

Haplotypes versus genotypes on pedigrees

Background  

Genome sequencing will soon produce haplotype data for individuals. For pedigrees of related individuals, sequencing appears to be an attractive alternative to genotyping. However, methods for pedigree analysis with haplotype data have not yet been developed, and the computational complexity of such problems has been an open question. Furthermore, it is not clear in which scenarios haplotype data would provide better estimates than genotype data for quantities such as recombination rates.     

Analysis of concordance of different haplotype block partitioning algorithms

Background  

Different classes of haplotype block algorithms exist and the ideal dataset to assess their performance would be to comprehensively re-sequence a large genomic region in a large population. Such data sets are expensive to collect. Alternatively, we performed coalescent simulations to generate haplotypes with a high marker density and compared block partitioning results from diversity based, LD based, and information theoretic algorithms under different values of SNP density and allele frequency.     

Allele and Haplotype Diversity of 26 X-STR Loci in Four Nationality Populations from China

Background

Haplotype analysis of closely associated markers has proven to be a powerful tool in kinship analysis, especially when short tandem repeats (STR) fail to resolve uncertainty in relationship analysis. STR located on the X chromosome show stronger linkage disequilibrium compared with autosomal STR. So, it is necessary to estimate the haplotype frequencies directly from population studies as linkage disequilibrium is population-specific.

Methodology and Findings

Twenty-six X-STR loci including six clusters of linked markers DXS6807-DXS8378-DXS9902(Xp22), DXS7132-DXS10079-DXS10074-DXS10075-DXS981 (Xq12), DXS6801-DXS6809-DXS6789-DXS6799(Xq21), DXS7424-DXS101-DXS7133(Xq22), DXS6804-GATA172D05(Xq23), DXS8377-DXS7423 (Xq28) and the loci DXS6800, DXS6803, DXS9898, GATA165B12, DXS6854, HPRTB and GATA31E08 were typed in four nationality (Han, Uigur, Kazakh and Mongol) samples from China (n = 1522, 876 males and 646 females). Allele and haplotype frequency as well as linkage disequilibrium data for kinship calculation were observed. The allele frequency distribution among different populations was compared. A total of 5–20 alleles for each locus were observed and altogether 289 alleles for all the selected loci were found. Allele frequency distribution for most X-STR loci is different in different populations. A total of 876 male samples were investigated by haplotype analysis and for linkage disequilibrium. A total of 89, 703, 335, 147, 39 and 63 haplotypes were observed. Haplotype diversity was 0.9584, 0.9994, 0.9935, 0.9736, 0.9427 and 0.9571 for cluster I, II, III, IV, V and VI, respectively. Eighty-two percent of the haplotype of cluster IIwas found only once. And 94% of the haplotype of cluster III show a frequency of <1%.

Conclusions

These results indicate that allele frequency distribution for most X-STR loci is population-specific and haplotypes of six clusters provide a powerful tool for kinship testing and relationship investigation. So it is necessary to obtain allele frequency and haplotypes data of the linked loci for forensic application.     

Haplotype inference in crossbred populations without pedigree information

Background

Current methods for haplotype inference without pedigree information assume random mating populations. In animal and plant breeding, however, mating is often not random. A particular form of nonrandom mating occurs when parental individuals of opposite sex originate from distinct populations. In animal breeding this is called crossbreeding and hybridization in plant breeding. In these situations, association between marker and putative gene alleles might differ between the founding populations and origin of alleles should be accounted for in studies which estimate breeding values with marker data. The sequence of alleles from one parent constitutes one haplotype of an individual. Haplotypes thus reveal allele origin in data of crossbred individuals.

Results

We introduce a new method for haplotype inference without pedigree that allows nonrandom mating and that can use genotype data of the parental populations and of a crossbred population. The aim of the method is to estimate line origin of alleles. The method has a Bayesian set up with a Dirichlet Process as prior for the haplotypes in the two parental populations. The basic idea is that only a subset of the complete set of possible haplotypes is present in the population.

Conclusion

Line origin of approximately 95% of the alleles at heterozygous sites was assessed correctly in both simulated and real data. Comparing accuracy of haplotype frequencies inferred with the new algorithm to the accuracy of haplotype frequencies inferred with PHASE, an existing algorithm for haplotype inference, showed that the DP algorithm outperformed PHASE in situations of crossbreeding and that PHASE performed better in situations of random mating.     

Relative role of life-history traits and historical factors in shaping genetic population structure of sardines (<Emphasis Type="Italic">Sardina pilchardus</Emphasis>)

Background  

Marine pelagic fishes exhibit rather complex patterns of genetic differentiation, which are the result of both historical processes and present day gene flow. Comparative multi-locus analyses based on both nuclear and mitochondrial genetic markers are probably the most efficient and informative approach to discerning the relative role of historical events and life-history traits in shaping genetic heterogeneity. The European sardine (Sardina pilchardus) is a small pelagic fish with a relatively high migratory capability that is expected to show low levels of genetic differentiation among populations. Previous genetic studies based on meristic and mitochondrial control region haplotype frequency data supported the existence of two sardine subspecies (S. p. pilchardus and S. p. sardina).     

Efficient algorithms for polyploid haplotype phasing

Background

Inference of haplotypes, or the sequence of alleles along the same chromosomes, is a fundamental problem in genetics and is a key component for many analyses including admixture mapping, identifying regions of identity by descent and imputation. Haplotype phasing based on sequencing reads has attracted lots of attentions. Diploid haplotype phasing where the two haplotypes are complimentary have been studied extensively. In this work, we focused on Polyploid haplotype phasing where we aim to phase more than two haplotypes at the same time from sequencing data. The problem is much more complicated as the search space becomes much larger and the haplotypes do not need to be complimentary any more.

Results

We proposed two algorithms, (1) Poly-Harsh, a Gibbs Sampling based algorithm which alternatively samples haplotypes and the read assignments to minimize the mismatches between the reads and the phased haplotypes, (2) An efficient algorithm to concatenate haplotype blocks into contiguous haplotypes.

Conclusions

Our experiments showed that our method is able to improve the quality of the phased haplotypes over the state-of-the-art methods. To our knowledge, our algorithm for haplotype blocks concatenation is the first algorithm that leverages the shared information across multiple individuals to construct contiguous haplotypes. Our experiments showed that it is both efficient and effective.

     

Selecting additional tag SNPs for tolerating missing data in genotyping

Background  

Recent studies have shown that the patterns of linkage disequilibrium observed in human populations have a block-like structure, and a small subset of SNPs (called tag SNPs) is sufficient to distinguish each pair of haplotype patterns in the block. In reality, some tag SNPs may be missing, and we may fail to distinguish two distinct haplotypes due to the ambiguity caused by missing data.     

A classification approach for genotyping viral sequences based on multidimensional scaling and linear discriminant analysis

Background  

Accurate classification into genotypes is critical in understanding evolution of divergent viruses. Here we report a new approach, MuLDAS, which classifies a query sequence based on the statistical genotype models learned from the known sequences. Thus, MuLDAS utilizes full spectra of well characterized sequences as references, typically of an order of hundreds, in order to estimate the significance of each genotype assignment.     

A constrained polynomial regression procedure for estimating the local False Discovery Rate

Background  

In the context of genomic association studies, for which a large number of statistical tests are performed simultaneously, the local False Discovery Rate (lFDR), which quantifies the evidence of a specific gene association with a clinical or biological variable of interest, is a relevant criterion for taking into account the multiple testing problem. The lFDR not only allows an inference to be made for each gene through its specific value, but also an estimate of Benjamini-Hochberg's False Discovery Rate (FDR) for subsets of genes.     

Viral quasispecies profiles as the result of the interplay of competition and cooperation

Background  

Viral quasispecies can be regarded as a swarm of genetically related mutants. A common approach employed to describe viral quasispecies is by means of the quasispecies equation (QE). However, a main criticism of QE is its lack of frequency-dependent selection. This can be overcome by an alternative formulation for the evolutionary dynamics: the replicator-mutator equation (RME). In turn, a problem with the RME is how to quantify the interaction coefficients between viral variants. Here, this is addressed by adopting an ecological perspective and resorting to the niche theory of competing communities, which assumes that the utilization of resources primarily determines ecological segregation between competing individuals (the different viral variants that constitute the quasispecies). This provides a theoretical framework to estimate quantitatively the fitness landscape.     

FCRL3 Gene Polymorphisms Confer Autoimmunity Risk for Allergic Rhinitis in a Chinese Han Population

Background

Heredity and environmental exposures may contribute to a predisposition to allergic rhinitis (AR). Autoimmunity may also involve into this pathologic process. FCRL3 (Fc receptor-like 3 gene), a novel immunoregulatory gene, has recently been reported to play a role in autoimmune diseases.

Objective

This study was performed to evaluate the potential association of FCRL3 polymorphisms with AR in a Chinese Han population.

Methods

Five single-nucleotide polymorphisms of FCRL3, rs945635, rs3761959, rs7522061, rs10489678 and rs7528684 were genotyped in 540 AR patients and 600 healthy controls using a PCR-restriction fragment length polymorphism assay. Allele, genotype and haplotype frequencies were compared between patients and controls using the χ2 test. The online software platform SHEsis was used to analyze their haplotypes.

Results

This study identified three strong risk SNPs rs7528684, rs10489678, rs7522061 and one weak risk SNP rs945635 of FCRL3 in Chinese Han AR patients. For rs7528684, a significantly increased prevalence of the AA genotype and A allele in AR patients was recorded. The frequency of the GG genotype and G allele of rs10489678 was markedly higher in AR patients than those in controls. For rs7522061, a higher frequency of the TT genotype, and a lower frequency of the CT genotype were found in AR patients. Concerning rs945635, a lower frequency of the CC genotype, and a higher frequency of G allele were observed in AR patients. According to the analysis of the three strong positive SNPs, the haplotype of AGT increased significantly in AR cases (AR = 38.8%, Controls = 24.3%, P = 8.29×10-14, OR [95% CI] 1.978 [1.652~2.368]).

Conclusions

This study found a significant association between the SNPs in FCRL3 gene and AR in Chinese Han patients. The results suggest these gene polymorphisms might be the autoimmunity risk for AR.     

Haplotype reconstruction error as a classical misclassification problem: introducing sensitivity and specificity as error measures

Background

Statistically reconstructing haplotypes from single nucleotide polymorphism (SNP) genotypes, can lead to falsely classified haplotypes. This can be an issue when interpreting haplotype association results or when selecting subjects with certain haplotypes for subsequent functional studies. It was our aim to quantify haplotype reconstruction error and to provide tools for it.

Methods and Results

By numerous simulation scenarios, we systematically investigated several error measures, including discrepancy, error rate, and R², and introduced the sensitivity and specificity to this context. We exemplified several measures in the KORA study, a large population-based study from Southern Germany. We find that the specificity is slightly reduced only for common haplotypes, while the sensitivity was decreased for some, but not all rare haplotypes. The overall error rate was generally increasing with increasing number of loci, increasing minor allele frequency of SNPs, decreasing correlation between the alleles and increasing ambiguity.

Conclusions

We conclude that, with the analytical approach presented here, haplotype-specific error measures can be computed to gain insight into the haplotype uncertainty. This method provides the information, if a specific risk haplotype can be expected to be reconstructed with rather no or high misclassification and thus on the magnitude of expected bias in association estimates. We also illustrate that sensitivity and specificity separate two dimensions of the haplotype reconstruction error, which completely describe the misclassification matrix and thus provide the prerequisite for methods accounting for misclassification.