HaplotypeCN: Copy Number Haplotype Inference with Hidden Markov Model and Localized Haplotype Clustering

Copy number variation (CNV) has been reported to be associated with disease and various cancers. Hence, identifying the accurate position and the type of CNV is currently a critical issue. There are many tools targeting on detecting CNV regions, constructing haplotype phases on CNV regions, or estimating the numerical copy numbers. However, none of them can do all of the three tasks at the same time. This paper presents a method based on Hidden Markov Model to detect parent specific copy number change on both chromosomes with signals from SNP arrays. A haplotype tree is constructed with dynamic branch merging to model the transition of the copy number status of the two alleles assessed at each SNP locus. The emission models are constructed for the genotypes formed with the two haplotypes. The proposed method can provide the segmentation points of the CNV regions as well as the haplotype phasing for the allelic status on each chromosome. The estimated copy numbers are provided as fractional numbers, which can accommodate the somatic mutation in cancer specimens that usually consist of heterogeneous cell populations. The algorithm is evaluated on simulated data and the previously published regions of CNV of the 270 HapMap individuals. The results were compared with five popular methods: PennCNV, genoCN, COKGEN, QuantiSNP and cnvHap. The application on oral cancer samples demonstrates how the proposed method can facilitate clinical association studies. The proposed algorithm exhibits comparable sensitivity of the CNV regions to the best algorithm in our genome-wide study and demonstrates the highest detection rate in SNP dense regions. In addition, we provide better haplotype phasing accuracy than similar approaches. The clinical association carried out with our fractional estimate of copy numbers in the cancer samples provides better detection power than that with integer copy number states.     

Haplotype block structure is conserved across mammals

Genetic variation in genomes is organized in haplotype blocks, and species-specific block structure is defined by differential contribution of population history effects in combination with mutation and recombination events. Haplotype maps characterize the common patterns of linkage disequilibrium in populations and have important applications in the design and interpretation of genetic experiments. Although evolutionary processes are known to drive the selection of individual polymorphisms, their effect on haplotype block structure dynamics has not been shown. Here, we present a high-resolution haplotype map for a 5-megabase genomic region in the rat and compare it with the orthologous human and mouse segments. Although the size and fine structure of haplotype blocks are species dependent, there is a significant interspecies overlap in structure and a tendency for blocks to encompass complete genes. Extending these findings to the complete human genome using haplotype map phase I data reveals that linkage disequilibrium values are significantly higher for equally spaced positions in genic regions, including promoters, as compared to intergenic regions, indicating that a selective mechanism exists to maintain combinations of alleles within potentially interacting coding and regulatory regions. Although this characteristic may complicate the identification of causal polymorphisms underlying phenotypic traits, conservation of haplotype structure may be employed for the identification and characterization of functionally important genomic regions.     

Haplotype Phasing and Inheritance of Copy Number Variants in Nuclear Families

DNA copy number variants (CNVs) that alter the copy number of a particular DNA segment in the genome play an important role in human phenotypic variability and disease susceptibility. A number of CNVs overlapping with genes have been shown to confer risk to a variety of human diseases thus highlighting the relevance of addressing the variability of CNVs at a higher resolution. So far, it has not been possible to deterministically infer the allelic composition of different haplotypes present within the CNV regions. We have developed a novel computational method, called PiCNV, which enables to resolve the haplotype sequence composition within CNV regions in nuclear families based on SNP genotyping microarray data. The algorithm allows to i) phase normal and CNV-carrying haplotypes in the copy number variable regions, ii) resolve the allelic copies of rearranged DNA sequence within the haplotypes and iii) infer the heritability of identified haplotypes in trios or larger nuclear families. To our knowledge this is the first program available that can deterministically phase null, mono-, di-, tri- and tetraploid genotypes in CNV loci. We applied our method to study the composition and inheritance of haplotypes in CNV regions of 30 HapMap Yoruban trios and 34 Estonian families. For 93.6% of the CNV loci, PiCNV enabled to unambiguously phase normal and CNV-carrying haplotypes and follow their transmission in the corresponding families. Furthermore, allelic composition analysis identified the co-occurrence of alternative allelic copies within 66.7% of haplotypes carrying copy number gains. We also observed less frequent transmission of CNV-carrying haplotypes from parents to children compared to normal haplotypes and identified an emergence of several de novo deletions and duplications in the offspring.     

Haplotype kinship for three populations of the Goettingen minipig

To overcome limitations of diversity measures applied to livestock breeds marker based estimations of kinship within and between populations were proposed. This concept was extended from the single locus consideration to chromosomal segments of a given length in Morgan. Algorithms for the derivation of haplotype kinship were suggested and the behaviour of marker based haplotype kinship was investigated theoretically. In the present study the results of the first practical application of this concept are presented. Full sib pairs of three sub-populations of the Goettingen minipig were genotyped for six chromosome segments. After haplotype reconstruction the haplotypes were compared and mean haplotype kinships were estimated within and between populations. Based on haplotype kinships a distance measure is proposed which is approximatively linear with the number of generations since fission. The haplotype kinship distances, the respective standard errors and the pedigree-based expected values are presented and are shown to reflect the true population history better than distances based on single-locus kinships. However the marker estimated haplotype kinship reveals variable among segments. This leads to high standard errors of the respective distances. Possible reasons for this phenomenon are discussed and a pedigree-based approach to correct for identical haplotypes which are not identical by descent is proposed.     

Bayesian Haplotype Inference for Multiple Linked Single-Nucleotide Polymorphisms

Haplotypes have gained increasing attention in the mapping of complex-disease genes, because of the abundance of single-nucleotide polymorphisms (SNPs) and the limited power of conventional single-locus analyses. It has been shown that haplotype-inference methods such as Clark's algorithm, the expectation-maximization algorithm, and a coalescence-based iterative-sampling algorithm are fairly effective and economical alternatives to molecular-haplotyping methods. To contend with some weaknesses of the existing algorithms, we propose a new Monte Carlo approach. In particular, we first partition the whole haplotype into smaller segments. Then, we use the Gibbs sampler both to construct the partial haplotypes of each segment and to assemble all the segments together. Our algorithm can accurately and rapidly infer haplotypes for a large number of linked SNPs. By using a wide variety of real and simulated data sets, we demonstrate the advantages of our Bayesian algorithm, and we show that it is robust to the violation of Hardy-Weinberg equilibrium, to the presence of missing data, and to occurrences of recombination hotspots.     

Haplotype inference by maximum parsimony

MOTIVATION: Haplotypes have been attracting increasing attention because of their importance in analysis of many fine-scale molecular-genetics data. Since direct sequencing of haplotype via experimental methods is both time-consuming and expensive, haplotype inference methods that infer haplotypes based on genotype samples become attractive alternatives. RESULTS: (1) We design and implement an algorithm for an important computational model of haplotype inference that has been suggested before in several places. The model finds a set of minimum number of haplotypes that explains the genotype samples. (2) Strong supports of this computational model are given based on the computational results on both real data and simulation data. (3) We also did some comparative study to show the strength and weakness of this computational model using our program. AVAILABILITY: The software HAPAR is free for non-commercial uses. Available upon request (lwang@cs.cityu.edu.hk).     

Haplotype Parsing

While the shared consensus genetic sequence of our species contains a great deal of information about our common biology, there is also much to be learned from the subtle genetic variations across our species. These variations are believed to be generally of little or no direct functional significance and predominantly reflect the chance accumulation of small genetic changes since our emergence as a species. Therefore, they carry little useful information when observed in a single individual. When tallied across a whole population though, these chance mutations can teach us a great deal about our evolutionary history and the patterns of inheritance in particular individuals. In particular, frequently observed patterns of single nucleotide polymorphisms (SNPs) in a population can identify segments of chromosome that have been passed down largely intact through long stretches of our evolution. Finding these frequently conserved chromosomal segments, or haplotypes, and developing methods to identify haplotype patterns in particular individuals, will in turn help us to identify those particular segments that carry genetic factors influencing risk for many common human diseases. To make the best use of this data, we will need to develop new models for the encoding of information in genome variations--the "language of genetic variation"--and new algorithms for fitting datasets to those models. This article surveys past work by the author and colleagues on this problem, utilising computational methods for locating frequent patterns in haploid sequence data, and "parsing" sequences so as to optimally explain them given the knowledge of the general population structure. The author's recent work in this area has been compiled into a set of computational tools available at http://www-2.cs.cmu.edu/~russells/software/hapmotif.html.     

Detecting Local Haplotype Sharing and Haplotype Association

A novel haplotype association method is presented, and its power is demonstrated. Relying on a statistical model for linkage disequilibrium (LD), the method first infers ancestral haplotypes and their loadings at each marker for each individual. The loadings are then used to quantify local haplotype sharing between individuals at each marker. A statistical model was developed to link the local haplotype sharing and phenotypes to test for association. We devised a novel method to fit the LD model, reducing the complexity from putatively quadratic to linear (in the number of ancestral haplotypes). Therefore, the LD model can be fitted to all study samples simultaneously, and, consequently, our method is applicable to big data sets. Compared to existing haplotype association methods, our method integrated out phase uncertainty, avoided arbitrariness in specifying haplotypes, and had the same number of tests as the single-SNP analysis. We applied our method to data from the Wellcome Trust Case Control Consortium and discovered eight novel associations between seven gene regions and five disease phenotypes. Among these, GRIK4, which encodes a protein that belongs to the glutamate-gated ionic channel family, is strongly associated with both coronary artery disease and rheumatoid arthritis. A software package implementing methods described in this article is freely available at http://www.haplotype.org.     

Haplotype reconstruction from SNP alignment.

In this paper, we describe a method for statistical reconstruction of haplotypes from a set of aligned SNP fragments. We consider the case of a pair of homologous human chromosomes, one from the mother and the other from the father. After fragment assembly, we wish to reconstruct the two haplotypes of the parents. Given a set of potential SNP sites inferred from the assembly alignment, we wish to divide the fragment set into two subsets, each of which represents one chromosome. Our method is based on a statistical model of sequencing errors, compositional information, and haplotype memberships. We calculate probabilities of different haplotypes conditional on the alignment. Due to computational complexity, we first determine phases for neighboring SNPs. Then we connect them and construct haplotype segments. Also, we compute the accuracy or confidence of the reconstructed haplotypes. We discuss other issues, such as alternative methods, parameter estimation, computational efficiency, and relaxation of assumptions.     

Haplotype diversity in 11 candidate genes across four populations

Analysis of haplotypes based on multiple single-nucleotide polymorphisms (SNP) is becoming common for both candidate gene and fine-mapping studies. Before embarking on studies of haplotypes from genetically distinct populations, however, it is important to consider variation both in linkage disequilibrium (LD) and in haplotype frequencies within and across populations, as both vary. Such diversity will influence the choice of "tagging" SNPs for candidate gene or whole-genome association studies because some markers will not be polymorphic in all samples and some haplotypes will be poorly represented or completely absent. Here we analyze 11 genes, originally chosen as candidate genes for oral clefts, where multiple markers were genotyped on individuals from four populations. Estimated haplotype frequencies, measures of pairwise LD, and genetic diversity were computed for 135 European-Americans, 57 Chinese-Singaporeans, 45 Malay-Singaporeans, and 46 Indian-Singaporeans. Patterns of pairwise LD were compared across these four populations and haplotype frequencies were used to assess genetic variation. Although these populations are fairly similar in allele frequencies and overall patterns of LD, both haplotype frequencies and genetic diversity varied significantly across populations. Such haplotype diversity has implications for designing studies of association involving samples from genetically distinct populations.     

Copy number polymorphism in plant genomes

Copy number variants (CNVs) are genomic rearrangements resulting from gains or losses of DNA segments. Typically, the term refers to rearrangements of sequences larger than 1 kb. This type of polymorphism has recently been shown to be a key contributor to intra-species genetic variation, along with single-nucleotide polymorphisms and short insertion-deletion polymorphisms. Over the last decade, a growing number of studies have highlighted the importance of copy number variation (CNV) as a factor affecting human phenotype and individual CNVs have been linked to risks for severe diseases. In plants, the exploration of the extent and role of CNV is still just beginning. Initial genomic analyses indicate that CNVs are prevalent in plants and have greatly affected plant genome evolution. Many CNV events have been observed in outcrossing and autogamous species. CNVs are usually found on all chromosomes, with CNV hotspots interspersed with regions of very low genetic variation. Although CNV is mainly associated with intergenic regions, many CNVs encompass protein-coding genes. The collected data suggest that CNV mainly affects the members of large families of functionally redundant genes. Thus, the effects of individual CNV events on phenotype are usually modest. Nevertheless, there are many cases in which CNVs for specific genes have been linked to important traits such as flowering time, plant height and resistance to biotic and abiotic stress. Recent reports suggest that CNVs may form rapidly in response to stress.     

Haplotype analysis of common transthyretin mutations

The most frequent transthyretin (TTR) variant associated with hereditary amyloidosis is TTR Met 30, which has its major focus in Portugal, although it also occurs in many other countries. The distribution of the mutation and its occurrence in a CpG dinucleotide lead us to question the origin of the mutation and the possibility of its having originated in Portugal. In order to investigate these questions, we studied the distribution of haplotypes associated with the Met 30 mutation in families from different European countries. All the analysed Portuguese families presented the same haplotype associated with the Met 30 mutation (haplotype I). The same was found for the Swedish and Spanish families studied. However, a distinct haplotype (haplotype III) was found in three families, one Italian, one English and one Turkish. These results suggest that, although the Portuguese Met 30 carriers might have one founder, the mutation probably recurred in populations in Europe in a similar manner to that reported in Japan. In this study, we have also analysed the haplotypes associated with other TTR variants frequent in the Portuguese population.     

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.     

Bayesian Modeling of Haplotype Effects in Multiparent Populations

A general Bayesian model, Diploffect, is described for estimating the effects of founder haplotypes at quantitative trait loci (QTL) detected in multiparental genetic populations; such populations include the Collaborative Cross (CC), Heterogeneous Socks (HS), and many others for which local genetic variation is well described by an underlying, usually probabilistically inferred, haplotype mosaic. Our aim is to provide a framework for coherent estimation of haplotype and diplotype (haplotype pair) effects that takes into account the following: uncertainty in haplotype composition for each individual; uncertainty arising from small sample sizes and infrequently observed haplotype combinations; possible effects of dominance (for noninbred subjects); genetic background; and that provides a means to incorporate data that may be incomplete or has a hierarchical structure. Using the results of a probabilistic haplotype reconstruction as prior information, we obtain posterior distributions at the QTL for both haplotype effects and haplotype composition. Two alternative computational approaches are supplied: a Markov chain Monte Carlo sampler and a procedure based on importance sampling of integrated nested Laplace approximations. Using simulations of QTL in the incipient CC (pre-CC) and Northport HS populations, we compare the accuracy of Diploffect, approximations to it, and more commonly used approaches based on Haley–Knott regression, describing trade-offs between these methods. We also estimate effects for three QTL previously identified in those populations, obtaining posterior intervals that describe how the phenotype might be affected by diplotype substitutions at the modeled locus.     

Bisretinoid-mediated Complement Activation on Retinal Pigment Epithelial Cells Is Dependent on Complement Factor H Haplotype

Age-related macular degeneration (AMD) is a common central blinding disease of the elderly. Homozygosity for a sequence variant causing Y402H and I62V substitutions in the gene for complement factor H (CFH) is strongly associated with risk of AMD. CFH, secreted by many cell types, including those of the retinal pigment epithelium (RPE), is a regulatory protein that inhibits complement activation. Recessive Stargardt maculopathy is another central blinding disease caused by mutations in the gene for ABCA4, a transporter in photoreceptor outer segments (OS) that clears retinaldehyde and prevents formation of toxic bisretinoids. Photoreceptors daily shed their distal OS, which are phagocytosed by the RPE cells. Here, we investigated the relationship between the CFH haplotype of human RPE (hRPE) cells, exposure to OS containing bisretinoids, and complement activation. We show that hRPE cells of the AMD-predisposing CFH haplotype (HH402/VV62) are attacked by complement following exposure to bisretinoid-containing Abca4^−/− OS. This activation was dependent on factor B, indicating involvement of the alternative pathway. In contrast, hRPE cells of the AMD-protective CFH haplotype (YY402/II62) showed no complement activation following exposure to either Abca4^−/− or wild-type OS. The AMD-protective YY402/II62 hRPE cells were more resistant to the membrane attack complex, whereas HH402/VV62 hRPE cells showed significant membrane attack complex deposition following ingestion of Abca4^−/− OS. These results suggest that bisretinoid accumulation in hRPE cells stimulates activation and dysregulation of complement. Cells with an intact complement negative regulatory system are protected from complement attack, whereas cells with reduced CFH synthesis because of the Y402H and I62V substitutions are vulnerable to disease.     

Haplotype structure in Ashkenazi Jewish BRCA1 and BRCA2 mutation carriers

Three founder mutations in BRCA1 and BRCA2 contribute to the risk of hereditary breast and ovarian cancer in Ashkenazi Jews (AJ). They are observed at increased frequency in the AJ compared to other BRCA mutations in Caucasian non-Jews (CNJ). Several authors have proposed that elevated allele frequencies in the surrounding genomic regions reflect adaptive or balancing selection. Such proposals predict long-range linkage disequilibrium (LD) resulting from a selective sweep, although genetic drift in a founder population may also act to create long-distance LD. To date, few studies have used the tools of statistical genomics to examine the likelihood of long-range LD at a deleterious locus in a population that faced a genetic bottleneck. We studied the genotypes of hundreds of women from a large international consortium of BRCA1 and BRCA2 mutation carriers and found that AJ women exhibited long-range haplotypes compared to CNJ women. More than 50% of the AJ chromosomes with the BRCA1 185delAG mutation share an identical 2.1?Mb haplotype and nearly 16% of AJ chromosomes carrying the BRCA2 6174delT mutation share a 1.4?Mb haplotype. Simulations based on the best inference of Ashkenazi population demography indicate that long-range haplotypes are expected in the context of a genome-wide survey. Our results are consistent with the hypothesis that a local bottleneck effect from population size constriction events could by chance have resulted in the large haplotype blocks observed at high frequency in the BRCA1 and BRCA2 regions of Ashkenazi Jews.     

Haplotype probabilities for multiple-strain recombinant inbred lines

Recombinant inbred lines (RIL) derived from multiple inbred strains can serve as a powerful resource for the genetic dissection of complex traits. The use of such multiple-strain RIL requires a detailed knowledge of the haplotype structure in such lines. Broman (2005) derived the two- and three-point haplotype probabilities for 2(n)-way RIL; the former required hefty computation to infer the symbolic results, and the latter were strictly numerical. We describe a simpler approach for the calculation of these probabilities, which allowed us to derive the symbolic form of the three-point haplotype probabilities. We also extend the two-point results for the case of additional generations of intermating, including the case of 2(n)-way intermated recombinant inbred populations (IRIP).     

Direct Haplotype‐Specific DNA Sequencing

Abstract

Determining haplotype‐specific DNA sequence information is very important in a wide range of research fields. However, no simple and robust approaches are currently available for determining haplotype‐specific sequence information. We have addressed this problem by developing a very simple and robust haplotype‐specific sequencing approach. We utilise the fact that DNA sequencing polymerases are sensitive to 3′end mismatches in the sequencing primer. By using two sequencing primers with 3′end corresponding to the two alleles in a given SNP locus, we are able to obtain allele‐specific DNA sequences from both alleles.

We evaluated this direct haplotype‐specific approach by determining haplotypes within the intron 2 sequence of the fructan‐6‐fructosyltransferase (6‐ft) gene in Lolium perenne L. We obtained reliable haplotype‐specific sequences for all primers and genotypes evaluated. We conclude that the haplotype‐specific sequencing is robust, and that the approach has a potentially very wide application range for any diploid organism.     

Estimating Haplotype Effects for Survival Data

Summary Genetic association studies often investigate the effect of haplotypes on an outcome of interest. Haplotypes are not observed directly, and this complicates the inclusion of such effects in survival models. We describe a new estimating equations approach for Cox's regression model to assess haplotype effects for survival data. These estimating equations are simple to implement and avoid the use of the EM algorithm, which may be slow in the context of the semiparametric Cox model with incomplete covariate information. These estimating equations also lead to easily computable, direct estimators of standard errors, and thus overcome some of the difficulty in obtaining variance estimators based on the EM algorithm in this setting. We also develop an easily implemented goodness‐of‐fit procedure for Cox's regression model including haplotype effects. Finally, we apply the procedures presented in this article to investigate possible haplotype effects of the PAF‐receptor on cardiovascular events in patients with coronary artery disease, and compare our results to those based on the EM algorithm.