Locus ordering based on crossover information in family haplotypes: application of a "minimum break" algorithm.

A "minimum break" method, previously applied to radiation hybrid data, is applied to the Genetic Analysis Workshop 12 simulated family data to assess the method's feasibility for ordering dense markers that have been typed in a set of pedigrees of three or more generations. Ordering is based on minimizing the total number of crossovers ("breaks") in a set of haplotypes where allele origin can be assigned to each specific haplotype, but locus order is unknown. It is shown that, for average locus spacing of about 2 cM and a set of 300 to 600 haplotypes, locus ordering can be reliably determined for sets of at least 50 loci. However, in the absence of crossovers between some pairs (sets) of loci, no unique order can be identified and sets of orders that are equally likely will be recovered. The method presented can be used to obtain reasonable sets of ordered loci that can then be used by other methods to refine the statistical confidence of the locus order.

Identification of a locus for autosomal dominant polycystic liver disease, on chromosome 19p13.2-13.1.

Polycystic liver disease (PCLD) is characterized by the growth of fluid-filled cysts of biliary epithelial origin in the liver. Although the disease is often asymptomatic, it can, when severe, lead to complications requiring surgical therapy. PCLD is most often associated with autosomal dominant polycystic kidney disease (ADPKD); however, families with an isolated polycystic liver phenotype without kidney involvement have been described. The clinical presentation and histological features of polycystic liver disease in the presence or absence of ADPKD are indistinguishable, raising the possibility that the pathogenetic mechanisms in the diseases are interrelated. We ascertained two large families with polycystic liver disease without kidney cysts and performed a genomewide scan for genetic linkage. A causative gene, PCLD, was mapped to chromosome 19p13.2-13.1, with a maximum LOD score of 10.3. Haplotype analysis refined the PCLD interval to 12.5 cM flanked by D19S586/D19S583 and D19S593/D19S579. The discovery of genetic linkage will facilitate diagnosis and study of this underdiagnosed disease entity. Identification of PCLD will be instrumental to an understanding of the pathogenesis of cyst formation in the liver in isolated PCLD and in ADPKD.

Design of artificial neural network and its applications to the analysis of alcoholism data.

Artificial neural networks were applied to the alcoholism data to reveal nonlinear relationships between intermediate phenotypes, marker identity-by-descent sharing, and the affection status. A variable number of hidden units were considered to achieve a balance between the minimal mean-squared error and over-fitting of the data. The predictability of the affection status based on intermediate phenotype information (event-related potential 300, monoamine oxidase, and gender) was 65% to 75%, and sensitivity/specificity ranged around 50% to 80%. The IBD approach succeeded in identifying the same marker as previous studies, but also found additional peaks.

Simulated data for a complex genetic trait (problem 2 for GAW11): how the model was developed, and why.

This paper describes a simulated data set created as Problem 2 for GAW11. The generating model for Problem 2 involved two different genetic diseases, or "types," in three separate populations. The two-locus (2L) type results from the epistatic interaction of two genetic loci, and the three-allele type, from a single locus with two disease-causing alleles and one normal allele. Each type has two phenotypic forms: Mild and Severe. Both forms are subject to both genetic and environmental influences. The disease occurs in three different hypothetical populations, each with different disease allele frequencies and penetrances. In two populations there is also a fourth locus with an allele that is associated with the 2L type. Misdiagnosis can occur, but only after a family has already been ascertained through > or = 2 "genetically" affected offspring. Finally, the three different populations are studied by four different hypothetical research groups. These groups each have their own ideas about how the disease is inherited and have therefore devised different ascertainment schemes based on those beliefs. Each research group collected 100-family data sets, including data on 300 markers on six chromosomes and measurements on disease status and on the proposed two environmental factors. GAW participants were supplied with 25 random replicates of each data set.

Systematic search for disease loci for complex genetic traits: a study based on simulated population data.

Simulated family data were analyzed using one- and two-locus disease models to detect linkage. Regions of interest, found on chromosomes 3 and 5, were then further analyzed to look for evidence of locus interaction and/or genetic heterogeneity. Methods described by Falk [1993] were used to separate families into subsets likely to be genetically homogeneous. Based on the results, it was concluded that there were at least two distinct disease loci, one on chromosome 3 and one on chromosome 5, and that these loci were probably not interacting but were expressing two distinct forms of the disease. The identification of these loci was in agreement with the generating model. However, the analysis did not show any indication of a two-locus form of the disease or detect a disease locus on chromosome 1. This could be due to lack of power and/or too small a sample size for the method of analysis.

Using neural networks as an aid in the determination of disease status: comparison of clinical diagnosis to neural-network predictions in a pedigree with autosomal dominant limb-girdle muscular dystrophy.

Studies of the genetics of certain inherited diseases require expertise in the determination of disease status even for single-locus traits. For example, in the diagnosis of autosomal dominant limb-girdle muscular dystrophy (LGMD1A), it is not always possible to make a clear-cut determination of disease, because of variability in the diagnostic criteria, age at onset, and differential presentation of disease. Mapping such diseases is greatly simplified if the data present a homogeneous genetic trait and if disease status can be reliably determined. Here, we present an approach to determination of disease status, using methods of artificial neural-network analysis. The method entails "training" an artificial neural network, with input facts (based on diagnostic criteria) and related results (based on disease diagnosis). The network contains weight factors connecting input "neurons" to output "neurons," and these connections are adjusted until the network can reliably produce the appropriate outputs for the given input facts. The trained network can be "tested" with a second set of facts, in which the outcomes are known but not provided to the network, to see how well the training has worked. The method was applied to members of a pedigree with LGMD1A, now mapped to chromosome 5q. We used diagnostic criteria and disease status to train a neural network to classify individuals as "affected" or "not affected." The trained network reproduced the disease diagnosis of all individuals of known phenotype, with 98% reliability. This approach defined an appropriate choice of clinical factors for determination of disease status. Additionally, it provided insight into disease classification of those considered to have an "unknown" phenotype on the basis of standard clinical diagnostic methods.

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.

Physical mapping of a commonly deleted region, the site of a candidate tumor suppressor gene, at 12q22 in human male germ cell tumors.

A candidate tumor suppressor gene (TSG) site at 12q22 characterized by a high frequency of loss of heterozygosity (LOH) and a homozygous deletion has previously been reported in human male germ cell tumors (GCTs). In a detailed deletion mapping analysis of 67 normal-tumor DNAs utilizing 20 polymorphic markers mapped to 12q22-q24, we identified the limits of the minimal region of deletion at 12q22 between D12S377 (proximal) and D12S296 (distal). We have constructed a YAC contig map of a 3-cM region of this band between the proximal marker D12S101 and the distal marker D12S346, which contained the minimal region of deletion in GCTs. The map is composed of 53 overlapping YACs and 3 cosmids onto which 25 polymorphic and nonpolymorphic sequence-tagged sites (STSs) were placed in a unique order. The size of the minimal region of deletion was approximately 2 Mb from overlapping, nonchimeric YACs that spanned the region. We also developed a radiation hybrid (RH) map of the region between D12S101 and D12S346 containing 17 loci. The consensus order developed by RH mapping is in good agreement with the YAC STS-content map order. The RH map estimated the distance between D12S101 and D12S346 to be 246 cR8000 and the minimal region of deletion to be 141 cR8000. In addition, four genes that were previously mapped to 12q22 have been excluded as candidate genes. The leads gained from the deletion mapping and physical maps should expedite the isolation and characterization of the TSG at 12q22.

Identification of susceptibility loci contributing to a complex disease using conventional segregation, linkage, and association methods.

We set out to apply conventional analytic methods to a GAW data set of nuclear families with an oligogenic disease that has a population prevalence of 0.023. We chose methods generally applied to disorders with at least one major gene. Our approaches included: 1) complex segregation analysis under two models of ascertainment, 2) linkage analysis assuming either a single-locus trait with possible genetic heterogeneity or a two-locus trait, and 3) allelic association studies using both a case/control approach and the haplotype relative risk (HRR) test. The association study was the only analysis of the three that provided evidence for genes playing a role in the etiology of this disorder.

Preliminary ordering of multiple linked loci using pairwise linkage data.

A method is presented for the preliminary ordering of loci on a chromosome using pairwise linkage data. The method is based on the biologically reasonable assumption that the "true" order of a set of linked loci will be the one that minimizes the total length of the chromosome segment. Here the "length" is defined as the sum of adjacent recombination fractions. The method searches for the optimal order, represented by a minimum distance map (MDMAP), even when it is not possible to examine the n!/2 possible distinct orders for n loci. A computerized approach, using the simulated annealing algorithm of Kirkpatrick et al. [1983], forms the basis of the method. It can be applied to data from radiation hybrid experiments as well as that from conventional family linkage studies. The technique is applied to several sets of published data to illustrate how it performs in practice. The advantages and the disadvantages of the method are discussed so that it will be clear under what conditions it is likely to work well. When data sets are "complete," in the sense that all possible pairwise recombination fractions have estimates, and when no large clusters of extremely tightly linked loci are present, the method produces ordered sets of loci that agree well with those generated by other, more complex methods. Any discrepancies that occur are likely to be with respect to the orientation of nearest-neighbor loci, where relative order cannot be reliably established by any method. The method thus provides a simple, rapid means of obtaining a preliminary order for a set of loci known to be in the same linkage group.

A simple method for ordering loci using data from radiation hybrids.

A method is presented for ordering loci on a chromosome based on data generated from radiation hybrids. All loci are tabulated as being present, absent, or not scored in a series of clones. Correlation coefficients are calculated for all pairs of loci indicating how often they are retained or lost together in the clones. On the assumption that a high positive correlation implies closely linked loci, a distance score, d, equal to one minus the correlation coefficient, is obtained for each locus pair and an order is generated that minimizes the sum of the adjacent distances [the MDMAP method of Falk ("Multipoint Mapping and Linkage Analysis Based upon Affected Pedigree Members: Genetic Analysis Workshop 6," pp. 17-22, A. R. Liss, New York, 1989)]. Two sets of data, with information on 13 and 16 loci mapped to chromosome 21q, have been ordered using this method. The results are in very good agreement with other ordering methods used on the same data and with physical mapping data.

Genetic loci ordering instability: an example.

In attempting to establish the order of genetic loci by constructing a map from pairwise linkage data, one assumes that the loci satisfy a linear-order relation. If the data utilized in the construction are not consistent with the linear-order assumption, then a very small change in the data may lead to a large qualitative change in the map. An example of such an instability is presented in this paper.

Human gene for torsion dystonia located on chromosome 9q32-q34.

Torsion dystonia is a movement disorder of unknown etiology characterized by loss of control of voluntary movements appearing as sustained muscle contractions and/or abnormal postures. Dystonic movements can be caused by lesions in the basal ganglia, drugs, or gene defects. Several hereditary forms have been described, most of which have autosomal dominant transmission with variable expressivity. In the Ashkenazi Jewish population the defective gene frequency is about 1/10,000. Here, linkage analysis using polymorphic DNA and protein markers has been used to locate a gene responsible for susceptibility to dystonia in a large, non-Jewish kinship. Affected members of this family have a clinical syndrome similar to that found in the Jewish population. This dystonia gene (ITD1) shows tight linkage with the gene encoding gelsolin, an actin binding protein, and appears by multipoint linkage analysis to lie in the q32-q34 region of chromosome 9 between ABO and D9S26, a region that also contains the locus for dopamine-beta-hydroxylase.

Characteristics of a multiplex IDDM sample: unexplained differences with other samples.

Characteristics of a multiplex sample of families with insulin-dependent diabetes mellitus (IDDM) are studied and contrasted with similar characteristics in other, more conventionally sampled data sets. Some characteristics remain consistent with earlier observations including the high frequency of human leukocyte antigen (HLA) DR3,4 in affected individuals and the greater than expected percentage of HLA haplotype sharing among affected sib pairs. In other respects, however, differences are seen between this sample and others. "Control" haplotypes, i.e., those not transmitted to the first affected offspring, had a higher frequency of DR3 and DR4 than expected, and a rather high frequency of affected parents was observed. Differences between the first affected and later affected offspring reported in other samples were absent from these families. No effect of the sampling scheme and the resulting distribution of parental phenotypes could be shown to explain this difference.