Multiple-trait quantitative trait locus mapping with incomplete phenotypic data

Background

The goal of linkage analysis is to determine the chromosomal location of the gene(s) for a trait of interest such as a common disease. Three-locus linkage analysis is an important case of multi-locus problems. Solutions can be found analytically for the case of triple backcross mating. However, in the present study of linkage analysis and gene mapping some natural inequality restrictions on parameters have not been considered sufficiently, when the maximum likelihood estimates (MLEs) of the two-locus recombination fractions are calculated.

Results

In this paper, we present a study of estimating the two-locus recombination fractions for the phase-unknown triple backcross with two offspring in each family in the framework of some natural and necessary parameter restrictions. A restricted expectation-maximization (EM) algorithm, called REM is developed. We also consider some extensions in which the proposed REM can be taken as a unified method.

Conclusion

Our simulation work suggests that the REM performs well in the estimation of recombination fractions and outperforms current method. We apply the proposed method to a published data set of mouse backcross families.     

Conclusion of LOD-score analysis for family data generated under two-locus models.

The power to detect linkage by the LOD-score method is investigated here for diseases that depend on the effects of two genes. The classical strategy is, first, to detect a major-gene (MG) effect by segregation analysis and, second, to seek for linkage with genetic markers by the LOD-score method using the MG parameters. We already showed that segregation analysis can lead to evidence for a MG effect for many two-locus models, with the estimates of the MG parameters being very different from those of the two genes involved in the disease. We show here that use of these MG parameter estimates in the LOD-score analysis may lead to a failure to detect linkage for some two-locus models. For these models, use of the sib-pair method gives a non-negligible increase of power to detect linkage. The linkage-homogeneity test among subsamples differing for the familial disease distribution provides evidence of parameter misspecification, when the MG parameters are used. Moreover, for most of the models, use of the MG parameters in LOD-score analysis leads to a large bias in estimation of the recombination fraction and sometimes also to a rejection of linkage for the true recombination fraction. A final important point is that a strong evidence of an MG effect, obtained by segregation analysis, does not necessarily imply that linkage will be detected for at least one of the two genes, even with the true parameters and with a close informative marker.     

Evidence for two unlinked loci regulating total serum IgE levels.

Studies investigating the genetic control of total serum IgE levels are of major importance in understanding basic pathophysiologic mechanisms in atopy and asthma, since IgE levels predict onset and correlate with the clinical expression of these disorders. Previous analysis of data from 92 families, ascertained through a parent with asthma, showed evidence for recessive inheritance of high IgE levels with linkage to chromosome 5q. Since there was significant residual familial correlation in the one-locus segregation analysis, two-locus segregation and linkage analyses were performed. Segregation analyses provided evidence for a second major locus unlinked to the locus on 5q. Utilization of this two-locus model corroborates the previous evidence for linkage between this trait and markers on 5q31-q33. The LODs for the most informative marker D5S436 increased from 3.00 at 10% recombination to 4.67 at 9% recombination, when the two-locus model was used. Additional linkage studies are needed to map this second locus. These results demonstrate the importance of performing multilocus segregation and linkage analyses for quantitative traits that are related to the phenotype of a complex disorder. This approach has given further insight into the genetics of allergy and asthma by providing evidence for a two-locus model.     

Joint linkage and linkage disequilibrium mapping in natural populations

A new strategy for studying the genome structure and organization of natural populations is proposed on the basis of a combined analysis of linkage and linkage disequilibrium using known polymorphic markers. This strategy exploits a random sample drawn from a panmictic natural population and the open-pollinated progeny of the sample. It is established on the principle of gene transmission from the parental to progeny generation during which the linkage between different markers is broken down due to meiotic recombination. The strategy has power to simultaneously capture the information about the linkage of the markers (as measured by recombination fraction) and the degree of their linkage disequilibrium created at a historic time. Simulation studies indicate that the statistical method implemented by the Fisher-scoring algorithm can provide accurate and precise estimates for the allele frequencies, recombination fractions, and linkage disequilibria between different markers. The strategy has great implications for constructing a dense linkage disequilibrium map that can facilitate the identification and positional cloning of the genes underlying both simple and complex traits.     

基于贝叶斯统计的遗传连锁分析方法

贝叶斯学派是不同于经典数理统计的一个重要学派, 其发展的贝叶斯统计方法在现代科学的许多领域已有着广泛的应用。探讨了贝叶斯统计在遗传连锁分析中的应用, 包括遗传重组率的贝叶斯估计、遗传连锁的贝叶斯因子检验和基于马尔可夫链蒙特卡罗理论的遗传连锁图谱构建。用编制的SAS/IML程序进行了模拟研究和实例分析, 验证了贝叶斯方法在遗传连锁分析中的有效性和实用性。     

Effect of genetic heterogeneity and assortative mating on linkage analysis: a simulation study.

Linkage studies of complex genetic traits raise questions about the effects of genetic heterogeneity and assortative mating on linkage analysis. To further understand these problems, I have simulated and analyzed family data for a complex genetic disease in which disease phenotype is determined by two unlinked disease loci. Two models were studied, a two-locus threshold model and a two-locus heterogeneity model. Information was generated for a marker locus linked to one of the disease-defining loci. Random-mating and assortative-mating samples were generated. Linkage analysis was then carried out by use of standard methods, under the assumptions of a single-locus disease trait and a random-mating population. Results were compared with those from analysis of a single-locus homogeneous trait in samples with the same levels of assortative mating as those considered for the two-locus traits. The results show that (1) introduction of assortative mating does not, in itself, markedly affect the estimate of the recombination fraction; (2) the power of the analysis, reflected in the LOD scores, is somewhat lower with assortative rather than random mating. Loss of power is greater with increasing levels of assortative mating; and (3) for a heterogeneous genetic disease, regardless of mating type, heterogeneity analysis permits more accurate estimate of the recombination fraction but may be of limited use in distinguishing which families belong to each homogeneous subset. These simulations also confirmed earlier observations that linkage to a disease "locus" can be detected even if the disease is incorrectly defined as a single-locus (homogeneous) trait, although the estimated recombination fraction will be significantly greater than the true recombination fraction between the linked disease-defining locus and the marker locus.     

Linkage homogeneity near the fragile X locus in normal and fragile X families

The fragile X syndrome locus, FRAXA, is located at Xq27. Until recently, few polymorphic loci had been genetically mapped close to FRAXA. This has been attributed to an increased frequency of recombination at Xq27, possibly associated with the fragile X mutation. In addition, the frequency of recombination around FRAXA has been reported to vary among fragile X families. These observations suggested that the genetic map at Xq27 in normal populations was different from that in fragile X populations and that the genetic map also varied within the fragile X population. Such variability would reduce the reliability of carrier risk estimates based on DNA studies in fragile X families. Five polymorphic loci have now been mapped to within 4 cM of FRAXA--DXS369, DXS297, DXS296, IDS, and DXS304. The frequency of recombination at Xq26-q28 was evaluated using data at these loci and at more distant loci from 112 families with the fragile X syndrome. Two-point and multipoint linkage analyses failed to detect any difference in the recombination fractions in fragile X versus normal families. Two-point and multipoint tests of linkage homogeneity failed to detect any evidence of linkage heterogeneity in the fragile X families. On the basis of this analysis, genetic maps derived from large samples of normal families and those derived from fragile X families are equally valid as the basis for calculating carrier risk estimates in a particular family.     

Limiting relationships between selection and recombination

It is difficult to directly observe processes like natural selection at the genetic level, but relatively easy to estimate genetic frequencies in populations. As a result, genetic frequency data are widely used to make inferences about the underlying evolutionary processes. However, multiple processes can generate the same patterns of frequency data, making such inferences weak. By studying the limits to the underlying processes, one can make inferences from frequency data by asking how strong selection (or some other process of interest) would have to be to generate the observed pattern. Here we present results of a study of the limits to the relationship between selection and recombination in two-locus, two-allele systems in which we found the limiting relationships for over 30 000 sets of parameters, effectively covering the range of two-locus, two-allele problems. Our analysis relates T _min—the minimum time for a population to evolve from the initial to the final conditions—to the strengths of selection and recombination, the amount of linkage disequilibrium, and the Nei distance between the initial and final conditions. T _min can be large with either large disequilibrium and small Nei distance, or the reverse. The behavior of T _min provides information about the limiting relationships between selection and recombination. Our methods allow evolutionary inferences from frequency data when deterministic processes like selection and recombination are operating; in this sense they complement methods based entirely on drift.     

A nearest-neighboring-end algorithm for genetic mapping

MOTIVATION: High-throughput methods are beginning to make possible the genotyping of thousands of loci in thousands of individuals, which could be useful for tightly associating phenotypes to candidate loci. Current mapping algorithms cannot handle so many data without building hierarchies of framework maps. RESULTS: A version of Kruskal's minimum spanning tree algorithm can solve any genetic mapping problem that can be stated as marker deletion from a set of linkage groups. These include backcross, recombinant inbred, haploid and double-cross recombinational populations, in addition to conventional deletion and radiation hybrid populations. The algorithm progressively joins linkage groups at increasing recombination fractions between terminal markers, and attempts to recognize and correct erroneous joins at peaks in recombination fraction. The algorithm is O (mn3) for m individuals and n markers, but the mean run time scales close to mn2. It is amenable to parallel processing and has recovered true map order in simulations of large backcross, recombinant inbred and deletion populations with up to 37,005 markers. Simulations were used to investigate map accuracy in response to population size, allelic dominance, segregation distortion, missing data and random typing errors. It produced accurate maps when marker distribution was sufficiently uniform, although segregation distortion could induce translocated marker orders. The algorithm was also used to map 1003 loci in the F7 ITMI population of bread wheat, Triticum aestivum L. emend Thell., where it shortened an existing standard map by 16%, but it failed to associate blocks of markers properly across gaps within linkage groups. This was because it depends upon the rankings of recombination fractions at individual markers, and is susceptible to sampling error, typing error and joint selection involving the terminal markers of nearly finished linkage groups. Therefore, the current form of the algorithm is useful mainly to improve local marker ordering in linkage groups obtained in other ways. AVAILABILITY: The source code and supplemental data are http://www.iubio.bio.indiana.edu/soft/molbio/qtl/flipper/ CONTACT: ccrane@purdue.edu.     

Inter- and intrafamilial heterogeneity: effective sampling strategies and comparison of analysis methods.

Heterogeneity, both inter- and intrafamilial, represents a serious problem in linkage studies of common complex diseases. In this study we simulated different scenarios with families who phenotypically have identical diseases but who genotypically have two different forms of the disease (both forms genetic). We examined the proportion of families displaying intrafamilial heterogeneity, as a function of mode of inheritance, gene frequency, penetrance, and sampling strategies. Furthermore, we compared two different ways of analyzing linkage in these data sets: a two-locus (2L) analysis versus a one-locus (SL) analysis combined with an admixture test. Data were simulated with tight linkage between one disease locus and a marker locus; the other disease locus was not linked to a marker. Our findings are as follows: (1) In contrast to what has been proposed elsewhere to minimize heterogeneity, sampling only "high-density" pedigrees will increase the proportion of families with intrafamilial heterogeneity, especially when the two forms are relatively close in frequency. (2) When one form is dominant and one is recessive, this sampling strategy will greatly decrease the proportions of families with a recessive form and may therefore make it more difficult to detect linkage to the recessive form. (3) An SL analysis combined with an admixture test achieves about the same lod scores and estimate of the recombination fraction as does a 2L analysis. Also, a 2L analysis of a sample of families with intrafamilial heterogeneity does not perform significantly better than an SL analysis. (4) Bilineal pedigrees have little effect on the mean maximum lod score and mean maximum recombination fraction, and therefore there is little danger that including these families will lead to a false exclusion of linkage.     

Joint estimation of recombination fractions and interference coefficients in multilocus linkage analysis.

Estimation of recombination fractions and interference coefficients is of importance in multilocus linkage analysis. With the development of molecular genetic technologies such as RFLP, multilocus data are readily available to researchers. Several methods have been developed to analyze such data, and each performs well under restrictive conditions. The present paper proposes a method based on a multiplicative model and maximum-likelihood estimation of recombination fractions and interference coefficients. The estimators are consistent regardless of the model assumptions and are efficient if the model is a good approximation. The estimators are tractable even when there are incomplete observations. Furthermore, the interference between nonadjacent chromosomal regions or those among three chromosomal regions can be modeled and tested by a simple Z-test. The proposed method was applied to linkage analysis of four-locus data obtained from Drosophila and that of seven-locus data obtained again from Drosophila. Reanalysis of the first example revealed that there is interference between chromosomal regions 2 and 3. Analysis of the second example suggested that there is triple interference as well as pairwise interference between nonadjacent chromosomal regions; the genetic interpretation of these findings remains to be developed.     

Linkage mapping of sex-specific differences

Most current linkage analyses assume identical fractions of meiotic recombination between homologous marker loci of the two sexes. This assumption is not realistic, because considerable sex-related differences have been observed in recombination fraction. In this paper, a general EM-based algorithm is presented to estimate sex-specific recombination fractions for a mixed set of molecular markers segregating differently in a full-sib family derived from two heterozygous parents. The asymptotic variances of the estimates of linkage specifically for each of the parents are evaluated using a numerical analysis based on information functions. This approach will have important implications for precise gene mapping based on sex-specific linkage maps.     

A new strategy for estimating recombination fractions between dominant markers from an F2 population

Although most high-density linkage maps have been constructed from codominant markers such as single-nucleotide polymorphisms (SNPs) and microsatellites due to their high linkage information, dominant markers can be expected to be even more significant as proteomic technique becomes widely applicable to generate protein polymorphism data from large samples. However, for dominant markers, two possible linkage phases between a pair of markers complicate the estimation of recombination fractions between markers and consequently the construction of linkage maps. The low linkage information of the repulsion phase and high linkage information of coupling phase have led geneticists to construct two separate but related linkage maps. To circumvent this problem, we proposed a new method for estimating the recombination fraction between markers, which greatly improves the accuracy of estimation through distinction between the coupling phase and the repulsion phase of the linked loci. The results obtained from both real and simulated F2 dominant marker data indicate that the recombination fractions estimated by the new method contain a large amount of linkage information for constructing a complete linkage map. In addition, the new method is also applicable to data with mixed types of markers (dominant and codominant) with unknown linkage phase.     

The use of map functions in multipoint mapping.

The analysis of multipoint data in humans involves detection of linkage, inferences about order, and estimation of map lengths. In order to calculate likelihoods, it is necessary to have predictive formulas for multiple recombination frequencies. In the present study the Markovian assumption of Morton and MacLean is generalized to give predictive formulas for multiple-region recombination using realistic map functions. The best-fitting map functions have been determined by fitting the nine-locus data of Morgan et al. and the seven-locus data of Weinstein on the Drosophila X chromosome. Two map functions fit the data better than other published functions: that of Rao et al. with a map parameter of P = .33 and a new function suggested in the present paper. The close agreement of the estimate of the mapping parameter with a previous estimate inferred from human male meiosis suggests that the map function is robust. A further improvement in the fit to the data can be obtained by the addition of a second parameter to reduce the expected number of multiple recombinants. By comparison with the map functions recommended in the present paper, the assumption of no interference gives a poor fit to the data.     

A genetic linkage map of 41 restriction fragment length polymorphism markers for human chromosome 3.

A genetic linkage map for human chromosome 3 has been constructed using 41 polymorphic DNA markers genotyped in 40 CEPH reference families. The map spans a genetic distance of 261 cM in males and 413 cM in females; the ratio of these distances (approximately 1.6 in favor of female meioses) was fairly constant across the map. Frequency of recombination was relatively uniform throughout much of the chromosome, except that in both telomeric regions recombination was more frequent than the physical distances would predict. The genetic map was basically in agreement with physical localization of 24 loci that were mapped by fluorescent in situ hybridization. This map can be used for linkage studies for genetic diseases, and it will serve as a step toward a high-resolution map for human chromosome 3.     

Two-locus identity probabilities and identity disequilibrium in a partially selfing subdivided population

Measures of association of genes at different loci (linkage disequilibrium) are widely used to determine whether the structure of natural populations is clonal or not, to map genes from population data, or to test for the homogeneity of response of molecular markers to background selection, for example. However, the usual definitions of parameters for gametic associations may not be suitable for all these purposes. In this paper, we derive the recursion equations for one- and two-locus identity probabilities in an infinite island model. We study the role of drift, gene flow, partial selfing and mutation model on the expected association of genes across loci. We define the 'within-subpopulation identity disequilibrium' as the difference between the joint two-locus probability of identity in state and the expected product of one-locus identity probabilities. We evaluate this parameter as a function of recombination rate, effective size, gene flow and selfing rate. Within-subpopulation identity disequilibrium attains maximum values for intermediate immigration rates, whatever the selfing rate. Moreover, identity disequilibrium may be very small, even for high selfing rates. We discuss the implications of these findings for the analysis of data from natural populations.     

Model-free linkage analysis using likelihoods.

Misspecification of transmission model parameters can produce artifactually negative lod scores at small recombination fractions and in multipoint analysis. To avoid this problem, we have tried to devise a test that aims to detect a genetic effect at a particular locus, rather than attempting to estimate the map position of a locus with specified effect. Maximizing likelihoods over transmission model parameters, as well as linkage parameters, can produce seriously biased parameter estimates and so yield tests that lack power for the detection of linkage. However, constraining the transmission model parameters to produce the correct population prevalence largely avoids this problem. For computational convenience, we recommend that the likelihoods under linkage and non-linkage are independently maximized over a limited set of transmission models, ranging from Mendelian dominant to null effect and from null effect to Mendelian recessive. In order to test for a genetic effect at a given map position, the likelihood under linkage is maximized over admixture, the proportion of families linked. Application to simulated data for a wide range of transmission models in both affected sib pairs and pedigrees demonstrates that the new method is well behaved under the null hypothesis and provides a powerful test for linkage when it is present. This test requires no specification of transmission model parameters, apart from an approximate estimate of the population prevalence. It can be applied equally to sib pairs and pedigrees, and, since it does not diminish the lod score at test positions very close to a marker, it is suitable for application to multipoint data.     

A second-generation genetic linkage map of the baboon (Papio hamadryas) genome

Construction of genetic linkage maps for nonhuman primate species provides information and tools that are useful for comparative analysis of chromosome structure and evolution and facilitates comparative analysis of meiotic recombination mechanisms. Most importantly, nonhuman primate genome linkage maps provide the means to conduct whole genome linkage screens for localization and identification of quantitative trait loci that influence phenotypic variation in primate models of common complex human diseases such as atherosclerosis, hypertension, and diabetes. In this study we improved a previously published baboon whole genome linkage map by adding more loci. New loci were added in chromosomal regions that did not have sufficient marker density in the initial map. Relatively low heterozygosity loci from the original map were replaced with higher heterozygosity loci. We report in detail on baboon chromosomes 5, 12, and 18 for which the linkage maps are now substantially improved due to addition of new informative markers.     

Constructing the parental linkage phase and the genetic map over distances <1 cM using pooled haploid DNA

A new statistical approach for construction of the genetic linkage map and estimation of the parental linkage phase based on allele frequency data from pooled gametic (sperm or egg) samples is introduced. This method can be applied for estimation of recombination fractions (over distances <1 cM) and ordering of large numbers (even hundreds) of closely linked markers. This method should be extremely useful in species with a long generation interval and a large genome size such as in dairy cattle or in forest trees; the conifer species have haploid tissues available in megagametophytes. According to Mendelian expectation, two parental alleles should occur in gametes in 1:1 proportions, if segregation distortion does not occur. However, due to mere sampling variation, the observed proportions may deviate from their expected value in practice. These deviations and their dependence along the chromosome can provide information on the parental linkage phase and on the genetic linkage map. Usefulness of the method is illustrated with simulations. The role of segregation distortion as a source of these deviations is also discussed. The software implementing this method is freely available for research purposes from the authors.     

Spline methods for the comparison of physical and genetic maps.

The first genetic maps were constructed by linkage analysis. Physical mapping techniques, such as radiation hybrids and complete sequencing, produce a different picture. For the purposes of population genetics, clinical genetics, and genetic epidemiology, it is important to harmonize and amalgamate existing genetic and physical maps. Among other things, comparisons of the two kinds of maps promotes better understanding of the wide variation in local recombination rates per unit physical length of DNA. The current paper presents methods for estimating recombination intensity as a function of physical distance along a chromosome. Genetic map distance is the integral of intensity. We derive fast reliable estimation algorithms based on a Poisson process model, penalized likelihoods, and cubic spline interpolation. Our methods provide a rigorous and statistically sound foundation for comparing physical and genetic maps. To illustrate the possibilities, we apply the methods to published recombination data on CEPH families and the complete sequences of chromosomes 21 and 22. Our results are in good agreement with previous studies and the biological data.