Multipoint genetic mapping with uniparental disomy data

Uniparental disomy (UPD) refers to the presence of two copies of a chromosome from one parent and none from the other parent. In genetic studies of UPDs, many genetic markers are usually used to identify the stage of nondisjunction that leads to UPD and to uncover the associated unusual patterns of recombinations. However, genetic information in such data has not been fully utilized because of the limitations of the existing statistical methods for UPD data. In the present article, we develop a multilocus statistical approach that has the advantages of being able to simultaneously consider all genetic markers for all individuals in the same analysis and to allow general models for the crossover process to incorporate crossover interference. In particular, for a general crossover-process model that assumes only that there exists in each interval at most one crossover, we describe how to use the expectation-maximization algorithm to examine the probability distribution of the recombination events underlying meioses leading to UPD. We can also use this flexible approach to create genetic maps based on UPD data and to inspect recombination differences between meioses exhibiting UPD and normal meioses. The proposed method has been implemented in a computer program, and we illustrate the proposed approach through its application to a set of UPD15 data.     

Bayesian and maximum likelihood estimation of genetic maps

There has recently been increased interest in the use of Markov Chain Monte Carlo (MCMC)-based Bayesian methods for estimating genetic maps. The advantage of these methods is that they can deal accurately with missing data and genotyping errors. Here we present an extension of the previous methods that makes the Bayesian method applicable to large data sets. We present an extensive simulation study examining the statistical properties of the method and comparing it with the likelihood method implemented in Mapmaker. We show that the Maximum A Posteriori (MAP) estimator of the genetic distances, corresponding to the maximum likelihood estimator, performs better than estimators based on the posterior expectation. We also show that while the performance is similar between Mapmaker and the MCMC-based method in the absence of genotyping errors, the MCMC-based method has a distinct advantage in the presence of genotyping errors. A similar advantage of the Bayesian method was not observed for missing data. We also re-analyse a recently published set of data from the eggplant and show that the use of the MCMC-based method leads to smaller estimates of genetic distances.     

Haplotype reconstruction and estimation of haplotype frequencies from nuclear families with only one parent available

Recent literature has suggested that haplotype inference through close relatives, especially from nuclear families can be an alternative strategy in determining the linkage phase. In this paper, haplotype reconstruction and estimation of haplotype frequencies via expectation maximization (EM) algorithm including nuclear families with only one parent available is proposed. Parent and his (her) child are treated as parent-child pair with one shared haplotype. This reduces the number of potential haplotype pairs for both parent and child separately, resulting in a higher accuracy of the estimation. In a series of simulations, the comparisons of PHASE, GENEHUNTER, EM-based approach for complete nuclear families and our approach are carried out. In all situations, EM-based approach for trio data is comparable but slightly worse error rate than PHASE, our approach is slightly better and much faster than PHASE for incomplete trios, the performance of GENEHUNTER is very bad in simple nuclear family settings and dramatically decreased with the number of markers being increased. On the other hand, the comparison result of different sampling designs demonstrates that sampling trios is the most efficient design to estimate haplotype frequencies in populations under same genotyping cost.     

Maximum-likelihood estimation of admixture proportions from genetic data

For an admixed population, an important question is how much genetic contribution comes from each parental population. Several methods have been developed to estimate such admixture proportions, using data on genetic markers sampled from parental and admixed populations. In this study, I propose a likelihood method to estimate jointly the admixture proportions, the genetic drift that occurred to the admixed population and each parental population during the period between the hybridization and sampling events, and the genetic drift in each ancestral population within the interval between their split and hybridization. The results from extensive simulations using various combinations of relevant parameter values show that in general much more accurate and precise estimates of admixture proportions are obtained from the likelihood method than from previous methods. The likelihood method also yields reasonable estimates of genetic drift that occurred to each population, which translate into relative effective sizes (N(e)) or absolute average N(e)'s if the times when the relevant events (such as population split, admixture, and sampling) occurred are known. The proposed likelihood method also has features such as relatively low computational requirement compared with previous ones, flexibility for admixture models, and marker types. In particular, it allows for missing data from a contributing parental population. The method is applied to a human data set and a wolflike canids data set, and the results obtained are discussed in comparison with those from other estimators and from previous studies.     

HumanMSD and MouseMSD: generating genetic maps for human and murine microsatellite markers

We present two Web interfaces that generate genetic maps for given sets of human or mouse microsatellite markers. The genetic maps are generated from available databases using linear interpolation of physical map distances to infer genetic map positions for missing markers in these databases.     

Multipoint oligogenic analysis of age-at-onset data with applications to Alzheimer disease pedigrees

It is usually difficult to localize genes that cause diseases with late ages at onset. These diseases frequently exhibit complex modes of inheritance, and only recent generations are available to be genotyped and phenotyped. In this situation, multipoint analysis using traditional exact linkage analysis methods, with many markers and full pedigree information, is a computationally intractable problem. Fortunately, Monte Carlo Markov chain sampling provides a tool to address this issue. By treating age at onset as a right-censored quantitative trait, we expand the methods used by Heath (1997) and illustrate them using an Alzheimer disease (AD) data set. This approach estimates the number, sizes, allele frequencies, and positions of quantitative trait loci (QTLs). In this simultaneous multipoint linkage and segregation analysis method, the QTLs are assumed to be diallelic and to interact additively. In the AD data set, we were able to localize correctly, quickly, and accurately two known genes, despite the existence of substantial genetic heterogeneity, thus demonstrating the great promise of these methods for the dissection of late-onset oligogenic diseases.     

Multipoint genetic mapping of quantitative trait loci with dominant markers in outbred populations

We present a multipoint algorithm for mapping quantitative trait loci (QTLs) using dominant markers. The algorithm is designed for outbred populations and is particularly suited for large families. The algorithm works with either codominant or dominant markers, either of which may be interspersed within the same linkage map. Concurrently, the algorithm also partitions dominance variance at the QTL. Computer simulations show that with large families, QTL mapping with dominant markers can be almost as powerful as with bi-allelic, codominant markers. Yet despite this, other situations show a large standard deviation in the estimate of the QTL position, thus making QTL mapping with dominant markers in outbred populations a useful detection tool, albeit limited in its resolution. This revised version was published online in July 2006 with corrections to the Cover Date.     

Viability thresholds for partial trisomies and monosomies. A study of 1,159 viable unbalanced reciprocal translocations

From a data base of 1,590 independent families with autosomal reciprocal translocations, 1,159 viable unbalances were studied and the lengths of their trisomy/ monosomy segments measured according to the method proposed by Daniel. About 5% of cases were found not to comply with Daniel viability criteria. The thresholds of viability vary with the mode of unbalance and with the sex of the carrier. Thus, new viability criteria are proposed as a guide for genetic counseling and prenatal diagnosis.     

Comparative visualization of genetic and physical maps with Strudel

Data visualization can play a key role in comparative genomics, for example, underpinning the investigation of conserved synteny patterns. Strudel is a desktop application that allows users to easily compare both genetic and physical maps interactively and efficiently. It can handle large datasets from several genomes simultaneously, and allows all-by-all comparisons between these. Availability and implementation: Installers for Strudel are available for Windows, Linux, Solaris and Mac OS X at http://bioinf.scri.ac.uk/strudel/.     

Applying a new generation of genetic maps to understand human inflammatory disease

The sequencing of the human genome and the intense study of its variation in different human populations have improved our understanding of the genome's architecture. It is now becoming clear that segments of the genome that are unbroken by reshuffling or recombination during meiosis create a mosaic of DNA 'haplotype blocks'. Here, we discuss the advantages and limitations of this block structure. Haplotype blocks hold the promise of reducing the complexity of analysing the human genome for association with disease. But can they deliver on this promise? First generation maps of these block patterns, such as the admixture and haplotype maps, are now emerging and, it is to be hoped, will accelerate the discovery of alleles that contribute to susceptibility to human inflammatory diseases.     

A bayesian framework for parentage analysis: the value of genetic and other biological data

We develop fractional allocation models and confidence statistics for parentage analysis in mating systems. The models can be used, for example, to estimate the paternities of candidate males when the genetic mother is known or to calculate the parentage of candidate parent pairs when neither is known. The models do not require two implicit assumptions made by previous models, assumptions that are potentially erroneous. First, we provide formulas to calculate the expected parentage, as opposed to using a maximum likelihood algorithm to calculate the most likely parentage. The expected parentage is superior as it does not assume a symmetrical probability distribution of parentage and therefore, unlike the most likely parentage, will be unbiased. Second, we provide a mathematical framework for incorporating additional biological data to estimate the prior probability distribution of parentage. This additional biological data might include behavioral observations during mating or morphological measurements known to correlate with parentage. The value of multiple sources of information is increased accuracy of the estimates. We show that when the prior probability of parentage is known, and the expected parentage is calculated, fractional allocation provides unbiased estimates of the variance in reproductive success, thereby correcting a problem that has previously plagued parentage analyses. We also develop formulas to calculate the confidence interval in the parentage estimates, thus enabling the assessment of precision. These confidence statistics have not previously been available for fractional models. We demonstrate our models with several biological examples based on data from two fish species that we study, coho salmon (Oncorhychus kisutch) and bluegill sunfish (Lepomis macrochirus). In coho, multiple males compete to fertilize a single female's eggs. We show how behavioral observations taken during spawning can be combined with genetic data to provide an accurate calculation of each male's paternity. In bluegill, multiple males and multiple females may mate in a single nest. For a nest, we calculate the fertilization success and the 95% confidence interval of each candidate parent pair.     

Cytogenetic analysis of human chromosomes and its valu for the estimation of genetic risk

A short review of present-day contradictory opinions on the usefulness of human chromosomal analysis in the system of chemical mutagen testing is illustrated by examples of the results achieved by both conventional and banding techniques. The results include exposures of human chromosomes to ECHH and TEPA in vitro, and to ECHH, vinyl chloride and Imuran in vivo. Exposures of human lymphocytes in vitro to the chemical to be tested for mutagenicity are recommended as one of the tests to be included in the system of mutagenicity testing, parallel with all other tests on mammalian and submammalian levels. The testing of human chromosomes of people exposed to chemicals in vivo is considered essential.     

Cloning of a polymorphic canine genetic marker which maps to human chromosome 9

We describe the cloning of a novel canine polymorphic genetic marker which maps to human chromosome 9. The sequence is 2092 bp, 59% GC rich, and contains three GC boxes. Chemilumin-escent probing of zooblots showed evolutionary conservation. Dogs have three Bam HI alleles: 2.3 kb, 2.1 kb and 1.7 kb. Allele frequencies in 17 unrelated dogs representing 13 breeds are presented. Polymorphism for the 1.7-kb allele in beagles is common. The 2.1-kb allele is probably the ancestral allele since it is the most common and is also noted in the Cape hunting dog. Interestingly, in more than 50 dogs tested to date, the 2.3-kb allele has been found only in miniature and giant schnauzers. This points to a common origin for these two breeds.     

Timely monthly surveillance of birth prevalence rates of congenital malformations and genetic disorders ascertained by registries or other systematic data bases

In many jurisdictions large data sets on malformations are now collected routinely in order to define prevalence rates of malformations in infants and children, to detect long-term secular trends, and to ascertain cases for ad hoc case-control studies. With slight modifications, these data sets may be used for prompt surveillance of changes in the birth prevalence of malformations, changes that conceivably could be possibly due to the introduction of a teratogen into the environment. A specific logistic approach is suggested, modeled on the New York State Malformation Registry, for prompt detection of changes in rates.     

A strategy for constructing high-resolution genetic maps of the human genome: a genetic map of chromosome 17p, ordered with meiotic breakpoint-mapping panels.

Genetic linkage analyses with genotypic data obtained from four CEPH reference families initially assigned 24 new PCR-based markers to chromosome 17 and located the markers at specific intervals of an existing genetic map of chromosome 17p. Each marker was additionally genotyped with an ordered set of obligate, phase-known recombinant chromosomes. The breakpoint-mapping panels for each family consisted of two parents, one sib with a nonrecombinant chromosome, and one or more sibs with obligate recombinant chromosomes. The relative order of markers was determined by sorting segregation patterns of new markers and ordered anchor markers and by minimizing double-recombination events. Consistency of segregation patterns with multiple flanking loci constituted support for order. A genetic map of chromosome 17p was completed with 39 markers in 23 clusters, with an average space of 3 cM between clusters. The collection of informative genotypes was highly efficient, requiring fivefold fewer genotypes than would be collected with all the CEPH families. Given the availability of large numbers of highly informative PCR-based markers, meiotic breakpoint mapping should facilitate construction of a human genomic map with 1-cM resolution.