Software for genetic linkage analysis

Recent developments in human genetic linkage analysis have included the appearance of new software and collections of data and program resources, accessible by means of the Internet. Many of these new programs and collections are described, including their availability, literature background, and specific technical information.     

Automating data manipulation for genetic analysis using a data base management system

Inefficient coding and manipulation of pedigree data have often hindered the progress of genetic studies. In this paper we present the methodology for interfacing a data base management system (DBMS) called MEGADATS with a linkage analysis program called LIPED. Two families that segregate a dominant trait and one test marker were used in a simulated exercise to demonstrate how a DBMS can be used to automate tedious clerical steps and improve the efficiency of a genetic analysis. The merits of this approach to data management are discussed. We conclude that a standardized format for genetic analysis programs would greatly facilitate data analysis.     

Microsatellites for linkage analysis of genetic traits.

Microsatellites are tandem repeats of simple sequence that occur abundantly and at random throughout most eukaryotic genomes. Since they are usually less than 100 bp long and are embedded in DNA with unique sequence, they can be amplified in vitro using the polymerase chain reaction. Microsatellites are easy to clone and characterize and display considerable polymorphism due to variation in the number of repeat units. This polymorphism is sufficiently stable to use in genetic analyses. Microsatellites are therefore ideal markers for constructing high-resolution genetic maps in order to identify susceptibility loci involved in common genetic diseases.     

Methods for genetic linkage analysis using trisomies.

Certain genetic disorders are rare in the general population, but more common in individuals with specific trisomies. Examples of this include leukemia and duodenal atresia in trisomy 21. This paper presents a linkage analysis method for using trisomic individuals to map genes for such traits. It is based on a very general gene-specific dosage model that posits that the trait is caused by specific effects of different alleles at one or a few loci and that duplicate copies of "susceptibility" alleles inherited from the nondisjoining parent give increased likelihood of having the trait. Our mapping method is similar to identity-by-descent-based mapping methods using affected relative pairs and also to methods for mapping recessive traits using inbred individuals by looking for markers with greater than expected homozygosity by descent. In the trisomy case, one would take trisomic individuals and look for markers with greater than expected homozygosity in the chromosomes inherited from the nondisjoining parent. We present statistical methods for performing such a linkage analysis, including a test for linkage to a marker, a method for estimating the distance from the marker to the trait gene, a confidence interval for that distance, and methods for computing power and sample sizes. We also resolve some practical issues involved in implementing the methods, including how to use partially informative markers and how to test candidate genes.     

Systematic detection of errors in genetic linkage data.

Construction of dense genetic linkage maps is hampered, in practice, by the occurrence of laboratory typing errors. Even relatively low error rates cause substantial map expansion and interfere with the determination of correct genetic order. Here, we describe a systematic method for overcoming these difficulties, based on incorporating the possibility of error into the usual likelihood model for linkage analysis. Using this approach, it is possible to construct genetic maps allowing for error and to identify the typings most likely to be in error. The method has been implemented for F2 intercrosses between two inbred strains, a situation relevant to the construction of genetic maps in experimental organisms. Tests involving both simulated and real data are presented, showing that the method detects the vast majority of errors.     

Genotype transposer: automated genotype manipulation for linkage disequilibrium analysis

SUMMARY: The purpose of this work is to provide the modern molecular geneticist with tools to perform more efficient and more accurate analysis of the genotype data they produce. By using Microsoft Excel macros written in Visual Basic, we can translate genotype data into a form readable by the versatile software 'Arlequin', read the Arlequin output, calculate statistics of linkage disequilibrium, and put the results in a format for viewing with the software 'GOLD'. AVAILABILITY: The software is available by FTP at: ftp://xcsg.iarc.fr/cox/Genotype_Transposer/. SUPPLEMENTARY INFORMATION: Detailed instruction and examples are available at: ftp://xcsg.iarc.fr/cox/Genotype&_Transposer/. Arlequin is available at: http://lgb.unige.ch/arlequin/. GOLD is available at: http://www.well.ox.ac.uk/asthma/GOLD/.     

The Lutheran and secretor loci: genetic linkage analysis.

Linkage analysis of Lu and Se and 31 other loci indicate that Lu:Se are not closely linked to ABO, ACP1, Co, Do, Est.D,Fy, GC, Gm, GLO:HLA, GPT, Inv, Jk,K,MN,P,PGD,PGM1, Rh,Sc, UMPK OR Yt. Lod scores for 18 families informative for Lu:Se gave no evidence for sex differentiation in recombination fraction: theta for males was 0.07, and for females, .08.     

Contraselectable streptomycin susceptibility determinant for genetic manipulation and analysis of Helicobacter pylori

Many Helicobacter pylori genetic studies would benefit from an ability to move DNA sequences easily between strains by transformation and homologous recombination, without needing to leave a conventional drug resistance determinant at the targeted locus. Presented here is a two-gene cassette that can be selected both (i) against, due to a Campylobacter jejuni rpsL gene (dominant streptomycin susceptibility in cells also carrying an rpsL-str(r) allele), and (ii) for, due to an erm gene (erythromycin resistance). This rpsL,erm cassette's utility was assessed by using it to replace four gene loci (mdaB, frxA, fur, and nikR) in four streptomycin-resistant [Str(r)] strain backgrounds (derivatives of 26695, SS1, X47, and G27MA). The resultant 16 strains (phenotypically erythromycin resistant [Erm(r)] and Str(s)) were each transformed with wild-type genomic DNAs, and Str(r) derivatives were selected. The desired Erm(s) Str(r) isolates were obtained at frequencies that ranged from 17 to 96% among Str(r) transformants, with the Erm(s) yield apparently depending on the strain background and genome location of the targeted locus. The ease of isolating unmarked transformants described here should be valuable for many H. pylori molecular genetic and evolutionary analyses.     

Two-trait-locus linkage analysis: a powerful strategy for mapping complex genetic traits.

Recent advances in molecular biology have provided geneticists with ever-increasing numbers of highly polymorphic genetic markers that have made possible linkage mapping of loci responsible for many human diseases. However, nearly all diseases mapped to date follow clear Mendelian, single-locus segregation patterns. In contrast, many common familial diseases such as diabetes, psoriasis, several forms of cancer, and schizophrenia are familial and appear to have a genetic component but do not exhibit simple Mendelian transmission. More complex models are required to explain the genetics of these important diseases. In this paper, we explore two-trait-locus, two-marker-locus linkage analysis in which two trait loci are mapped simultaneously to separate genetic markers. We compare the utility of this approach to standard one-trait-locus, one-marker-locus linkage analysis with and without allowance for heterogeneity. We also compare the utility of the two-trait-locus, two-marker-locus analysis to two-trait-locus, one-marker-locus linkage analysis. For common diseases, pedigrees are often bilineal, with disease genes entering via two or more unrelated pedigree members. Since such pedigrees often are avoided in linkage studies, we also investigate the relative information content of unilineal and bilineal pedigrees. For the dominant-or-recessive and threshold models that we consider, we find that two-trait-locus, two-marker-locus linkage analysis can provide substantially more linkage information, as measured by expected maximum lod score, than standard one-trait-locus, one-marker-locus methods, even allowing for heterogeneity, while, for a dominant-or-dominant generating model, one-locus models that allow for heterogeneity extract essentially as much information as the two-trait-locus methods. For these three models, we also find that bilineal pedigrees provide sufficient linkage information to warrant their inclusion in such studies. We also discuss strategies for assessing the significance of the two linkages assumed in two-trait-locus, two-marker-locus models.     

Retrotransposon-based molecular markers for linkage and genetic diversity analysis in wheat

Retrotransposon-based molecular markers have been developed to study bread wheat ( Triticum aestivum) and its wild relatives. SSAP (Sequence-Specific Amplification Polymorphism) markers based on the BARE-1/ Wis-2-1A retrotransposons were assigned to T. aestivum chromosomes by scoring nullisomic-tetrasomic chromosome substitution lines. The markers are distributed among all wheat chromosomes, with the lowest proportion being assigned the D wheat genome. SSAP markers for BARE-1/ Wis-2-1A and three other wheat retrotransposons, Thv19 , Tagermina and Tar1, are broadly distributed on a wheat linkage map. Polymorphism levels associated with these four retrotransposons vary, with BARE-1/ Wis-2-1A and Thv19 both showing approximately 13% of bands polymorphic in a mapping population, Tagermina showing approximately 17% SSAP band polymorphism and Tar1 roughly 18%. This suggests that Tagermina and Tar1 have been more transpositionally active in the recent evolutionary past, and are potentially the more useful source of molecular markers in wheat. Lastly, BARE-1 / Wis-2-1A markers have also been used to characterise the genetic diversity among a set of 35 diploid and tetraploid wheat species including 26 Aegilops and 9 Triticum accessions. The SSAP-based diversity tree for Aegilops species agrees well with current classifications, though the Triticum tree shows several significant differences, which may be associated with polyploidy in this genus.Communicated by M.-A. Grandbastien     

Strategies for the genetic manipulation of Saccharomyces cerevisiae.

The budding yeast Saccharomyces cerevisiae is now widely used as a model organism in the study of gene structure, function, and regulation in addition to its more traditional use as a workhorse of the brewing and baking industries. In this article the plethora of methods available for manipulating the genome of S. cerevisiae are reviewed. This will include a discussion of methods for manipulating individual genes and whole chromosomes, and will address both classic genetic and recombinant DNA-based methods. Furthermore, a critical evaluation of the various genetic strategies for genetically manipulating this simple eukaryote will be included, highlighting the requirements of both the new and the more traditional biotechnology industries.     

Optimizing parental selection for genetic linkage maps.

Genetic linkage maps based on restriction fragment length polymorphisms are useful for many purposes; however, different populations are required to fulfill different objectives. Clones from the linkage map(s) are subsequently probed onto populations developed for special purposes such as gene tagging. Therefore, clones contained on the initial map(s) must be polymorphic on a wide range of genotypes to have maximum utility. The objectives of this research were to (i) calculate polymorphism information content values of 51 low-copy DNA clones and (ii) use the resulting values to choose potential mapping parents. Polymorphism information content was calculated using gene diversity by classifying restriction fragment patterns on a diverse set of 18 wheat genotypes. Combinations of potential parents were then compared by examining both the proportion of polymorphic clones and the likelihood that those mapped clones would give a polymorphism when used on other populations. Genotype pairs were identified that would map more highly informative DNA clones compared with a population derived from the most polymorphic potential parents. The methodologies used to characterize clones and rank potential parents should be applicable to other species and types of markers as well.     

Detecting linkage for genetically heterogeneous diseases and detecting heterogeneity with linkage data.

Interest in searching for genetic linkage between diseases and marker loci has been greatly increased by the recent introduction of DNA polymorphisms. However, even for the most well-behaved Mendelian disorders, those with clear-cut mode of inheritance, complete penetrance, and no phenocopies, genetic heterogeneity may exist; that is, in the population there may be more than one locus that can determine the disease, and these loci may not be linked. In such cases, two questions arise: (1) What sample size is necessary to detect linkage for a genetically heterogeneous disease? (2) What sample size is necessary to detect heterogeneity given linkage between a disease and a marker locus? We have answered these questions for the most important types of matings under specified conditions: linkage phase known or unknown, number of alleles involved in the cross at the marker locus, and different numbers of affected and unaffected children. In general, the presence of heterogeneity increases the recombination value at which lod scores peak, by an amount that increases with the degree of heterogeneity. There is a corresponding increase in the number of families necessary to establish linkage. For the specific case of backcrosses between disease and marker loci with two alleles, linkage can be detected at recombination fractions up to 20% with reasonable numbers of families, even if only half the families carry the disease locus linked to the marker. The task is easier if more than two informative children are available or if phase is known. For recessive diseases, highly polymorphic markers with four different alleles in the parents greatly reduce the number of families required.     

Testing for linkage under robust genetic models.

Robust genetic models are used to assess linkage between a quantitative trait and genetic variation at a specific locus using allele-sharing data. Little is known about the relative performance of different possible significance tests under these models. Under the robust variance components model approach there are several alternatives: standard Wald and likelihood ratio tests, a quasilikelihood Wald test, and a Monte Carlo test. This paper reports on the relative performance (significance level and power) of the robust sibling pair test and the different alternatives under the robust variance components model. Simulations show that (1) for a fixed sample size of nuclear families, the variance components model approach is more powerful than the robust sibling pair approach; (2) when the number of nuclear families is at least approximately 100 and heritability at the trait locus is moderate to high (>0.20) all tests based on the variance components model are equally effective; (3) when the number of nuclear families is less than approximately 100 or heritability at the trait locus is low (<0. 20), on balance, the Monte Carlo test provides the best power and is the most valid. The different testing procedures are applied to determine which are able to detect the known association between low density lipoprotein cholesterol and the common genotypes at the locus encoding apolipoprotein E. Results from this application show that the robust sibling pair method may be more effective in practice than that indicated by simulations.