Chromlook: an interactive program for error detection and mapping in reference linkage data.

Preliminary genetic linkage maps of every human chromosome have been generated over the past few years, and efforts to extend and refine these maps are under way. However, fine-resolution mapping is tedious and difficult because the inevitable errors in the data confound estimates of both the placement of loci and the distances between them. Fortunately, in most cases these errors result in observed recombinants where no true recombinant has occurred. The simple strategy presented here identifies these recombinants by relying on the assumption that recombinants between two adjacent markers are relatively rare events. This strategy has been implemented in the computer program CHROMLOOK, and examples of its use are given. Identification of recombinants allows for the directed regenotyping of suspicious data, the quick mapping of new polymorphisms using recombination minimization, and the development of a meiotic breakpoint map.     

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.     

Error detection for genetic data, using likelihood methods.

As genetic maps become denser, the effect of laboratory typing errors becomes more serious. We review a general method for detecting errors in pedigree genotyping data that is a variant of the likelihood-ratio test statistic. It pinpoints individuals and loci with relatively unlikely genotypes. Power and significance studies using Monte Carlo methods are shown by using simulated data with pedigree structures similar to the CEPH pedigrees and a larger experimental pedigree used in the study of idiopathic dilated cardiomyopathy (DCM). The studies show the index detects errors for small values of theta with high power and an acceptable false positive rate. The method was also used to check for errors in DCM laboratory pedigree data and to estimate the error rate in CEPH-chromosome 6 data. The errors flagged by our method in the DCM pedigree were confirmed by the laboratory. The results are consistent with estimated false-positive and false-negative rates obtained using simulation.     

Genetic linkage analysis and homology relationships of genes located on human chromosome 11q.

We have used DNA polymorphisms detected by probes for 11q to order 16 genes and to determine the genetic distances between them. Our map includes the genes for CD20, tyrosinase, progesterone receptor, stromelysin, collagenase, N-CAM, dopamine-D2 receptor, apolipoproteins AI-CIII-AIV, CD3-epsilon, -delta, and -gamma, porphobilinogen deaminase, thy-1, and ets-1. These genes have previously been sequenced as well as placed on the 11q cytogenetic map, which now makes them anchor points between the cytogenetic, genetic, and physical maps of this region. The ordering and distances between these genes are of immediate use in testing hypotheses of candidate genes for human genetic diseases associated with chromosome 11q. A comparison between our genetic map and similar maps from other species defines regions of homologous synteny that may be useful in mapping human genetic disease genes localized to the 11q region. Analysis of such homology provides additional bases for speculation of the evolutionary histories of gene families in this region.     

Idealized atomic coordinates of yeast phenylalanine transfer RNA.

The atomic coordinates are given for yeast phenylalanine transfer RNA in the orthorhombic crystal form. The structure has been refined by fitting to successively improved electron density maps at 2.7 Å resolution. The model fitting has been accomplished by using an interactive computer graphics system to minimize the errors inherent in manual model building and coordinate measurements, using an optical comparator. The atomic coordinates have then been “idealized” to make bond distances, bond angles, steric conformation and non-bonded contacts close to standard values, while constraining the model to fit the electron density maps.     

Patterns of recombination and MLH1 foci density along mouse chromosomes: modeling effects of interference and obligate chiasma

Crossover interference in meiosis is often modeled via stationary renewal processes. Here we consider a new model to incorporate the known biological feature of "obligate chiasma" whereby in most organisms each bivalent almost always has at least one crossover. The initial crossover is modeled as uniformly distributed along the chromosome, and starting from its position, subsequent crossovers are placed with forward and backward stationary renewal processes using a chi-square distribution of intercrossover distances. We used our model as well as the standard chi-square model to simulate the patterns of crossover densities along bivalents or chromatids for those having zero, one, two, or three or more crossovers; indeed, such patterns depend on the number of crossovers. With both models, simulated patterns compare very well to those found experimentally in mice, both for MLH1 foci on bivalents and for crossovers on genetic maps. However, our model provides a better fit to experimental data as compared to the standard chi-square model, particularly regarding the distribution of numbers of crossovers per chromosome. Finally, our model predicts an enhancement of the recombination rate near the extremities, which, however, explains only a part of the pattern observed in mouse.     

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.     

A multipoint method for detecting genotyping errors and mutations in sibling-pair linkage data

The identification of genes contributing to complex diseases and quantitative traits requires genetic data of high fidelity, because undetected errors and mutations can profoundly affect linkage information. The recent emphasis on the use of the sibling-pair design eliminates or decreases the likelihood of detection of genotyping errors and marker mutations through apparent Mendelian incompatibilities or close double recombinants. In this article, we describe a hidden Markov method for detecting genotyping errors and mutations in multilocus linkage data. Specifically, we calculate the posterior probability of genotyping error or mutation for each sibling-pair-marker combination, conditional on all marker data and an assumed genotype-error rate. The method is designed for use with sibling-pair data when parental genotypes are unavailable. Through Monte Carlo simulation, we explore the effects of map density, marker-allele frequencies, marker position, and genotype-error rate on the accuracy of our error-detection method. In addition, we examine the impact of genotyping errors and error detection and correction on multipoint linkage information. We illustrate that even moderate error rates can result in substantial loss of linkage information, given efforts to fine-map a putative disease locus. Although simulations suggest that our method detects 相似文献   

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.     

Languages, geography and HLA haplotypes in native American and Asian populations

A number of studies based on linguistic, dental and genetic data have proposed that the colonization of the New World took place in three separate waves of migration from North-East Asia. Recently, other studies have suggested that only one major migration occurred. It is the aim of this study to assess these opposing migration hypotheses using molecular-typed HLA class II alleles to compare the relationships between linguistic and genetic data in contemporary Native American populations. Our results suggest that gene flow and genetic drift have been important factors in shaping the genetic landscape of Native American populations. We report significant correlations between genetic and geographical distances in Native American and East Asian populations. In contrast, a less clear-cut relationship seems to exist between genetic distances and linguistic affiliation. In particular, the close genetic relationship of the neighbouring Na-Dene Athabaskans and Amerindian Salishans suggests that geography is the more important factor. Overall, our results are most congruent with the single migration model.     

Mapping functions

Accurate estimation of map distance between markers is important for the construction of large-scale linkage maps because it provides reliable and useful linkage information of markers on chromosomes. How to improve accuracy of estimating map distances depends on an appropriate mapping function. We used the coefficient of coincidence to integrate the Haldane function, in which crossovers are assumed to be independent and the Morgan function, in which crossovers are assumed to be interfered, and produce a new mapping function. The mapping function based on positive interference is referred to as the positive function and that on negative interference as the negative function. In these two mapping functions, map distances between loci are determined by both recombination frequencies and the coefficient of coincidence. We applied our mapping functions to four examples and show that our map estimates have much higher goodness-of-fit to the observed mapping data than the Haldane and Kosambi functions. Therefore, they can provide much more precise estimates of map distances than the two conventional mapping functions. Furthermore, our mapping functions produced almost linear (additive) map distances.     

Linkage analysis using sex-specific recombination fractions with GENEHUNTER-MODSCORE

MOTIVATION: Sex-specific marker maps have become increasingly available. We have implemented the usage of sex-specific recombination frequencies in the GENEHUNTER-MODSCORE program that performs multipoint linkage analysis. Furthermore, we have devised a consistent method to choose the combinations of male and female genetic positions at which linkage scores should be calculated. Marker coordinates can be read automatically from publicly available genetic maps. RESULTS: In a MOD-score analysis of the COGA dataset provided for Genetic Analysis Workshop 14, the highest linkage peak on chromosome 1 further increases when using sex-specific maps, while some smaller peaks are decreased. Simulations confirm that the MOD score can be biased when a sex-averaged instead of the correct sex-specific map is employed. This shows that an adequate modeling of the female:male ratio of genetic distances is important, especially for complex traits. AVAILABILITY: The new version of GENEHUNTER-MODSCORE can be downloaded from the following website: http://www.staff.uni-marburg.de/~strauchk/software.html     

A genetic map of chromosome 1: comparison of different data sets and linkage programs

We have used 22 chromosome 1 loci to construct a genetic linkage map of this autosome using the Venezuelan Reference Pedigree. These markers formed two linkage groups separated by an interval of more than 30 cM. Linkage maps were constructed separately using the computer programs LINKAGE and MAPMAKER to determine their relative speed, efficiency, and accuracy. We found that both programs generated maps with the same order and distances, although the LINKAGE program derived more information from the data, allowing placement of one additional marker. Many of the probes have previously been mapped using the CEPH pedigrees. However, the current map is generated from a different data set and so can be used to increase the certainty of locus order and map position. Ultimately, the generation and confirmation of a 1-cM map of this chromosome will require such multiple data sets.     

ODS2: a multiplatform software application for creating integrated physical and genetic maps

A contig map is a physical map that shows the native order of a library of overlapping genomic clones. One common method for creating such maps involves using hybridization to detect clone overlaps. False- positive and false-negative hybridization errors, the presence of chimeric clones, and gaps in library coverage lead to ambiguity and error in the clone order. Genomes with good genetic maps, such as Neurospora crassa, provide a means for reducing ambiguities and errors when constructing contig maps if clones can be anchored with genetic markers to the genetic map. A software application called ODS2 for creating contig maps based on clone-clone hybridization data is presented. This application is also designed to exploit partial ordering information provided by anchorage of clones to a genetic map. This information, along with clone-clone hybridization data, is used by a clone ordering algorithm and is represented graphically, allowing users to interactively align physical and genetic maps. ODS2 has a graphical user interface and is implemented entirely in Java, so it runs on multiple platforms. Other features include the flexibility of storing data in a local file or relational database and the ability to create full or minimum tiling contig maps.     

Gene flow and natal dispersal in the Siberian flying squirrel based on direct and indirect data

Dispersal is a key determinant of the evolution and ecology of species. For a comprehensive picture of dispersal, a combination of both field observations and indirect genetic measures are required, as both of these have strengths that may mitigate the other’s limitations. Here, we used microsatellite markers and radio-telemetry data to study dispersal and gene flow in Siberian flying squirrels. Genetic data confirmed our empirical results that dispersal is female biased in the flying squirrel. Female bias in dispersal is exceptional among mammals and in flying squirrels is probably explained by competition for food resources and nesting cavities among mothers and daughters. The individual-level genetic pattern was influenced by isolation by distance. Using this information fairly comparable dispersal distances were derived using indirect data as observed directly with radio telemetry. Thus, our results support the recent conclusion that individual-level genetic data can be useful in inferring dispersal distances for species for which direct data are lacking.     

phylin: an r package for phylogeographic interpolation

phylin is a package for the r programming environment which offers different methods to spatially interpolate genetic information from phylogeographic data. These interpolations can be used to predict the spatial occurrence of different lineages within a phylogeny using a modified method of kriging, which allows the usage of a genetic distance matrix to derive a model of spatial dependence. phylin improves the available methods to generate interpolated surfaces from a phylogenetic trees by assessing the autocorrelation structure of the genetic information, interpolating the genetic data based on a statistical model, estimating the uncertainty of the predictions and identifying lineage occurrence and contact zones probability without projection of pairwise genetic distances into mid‐points between sample locations. The package also includes methods to plot interpolation surfaces and provide summary tables from the generated data and models. We provide an example of the usefulness of this tool by inferring the spatial occurrence of distinct historical evolutionary lineages of the Lataste's viper (Vipera latastei Boscá, 1878) in the Iberian Peninsula and identifying potential contact areas. The maps of phylogenetic patterns obtained with these methods provide a spatial context to test hypotheses related to processes underlying the geographic distribution of genetic diversity and to inform conservation planning.     

IRILmap: linkage map distance correction for intermated recombinant inbred lines/advanced recombinant inbred strains

Intermated Recombinant Inbred Lines (IRILs) in plants, or Advanced Recombinant Inbred Strains in animals, are constructed by carrying out generations of intermating between F2 individuals before starting recurrent inbreeding generations by selfing or sib-mating. IRILs are powerful for high-resolution genetic mapping because they have undergone more recombination than usual Recombinant Inbred Lines (RILs). However, there is no mapping software able to generate actual centiMorgan distances from the segregation data obtained with IRILs. IRILmap software converts genetic distances computed with any linkage mapping program designed for RILs, so that IRIL-derived data can be used to get actual centiMorgan distances, directly comparable to F2, backcross or RIL-derived maps.     

Mapping in the realm of polyploidy: The wheat model

Wheat is an allopolyploid containing three distinct but genetically related (homoeologous) genomes, A, B and D. Because of polyploid inheritance and large genome size (16×10¹² bp), the wheat genome is thought to be intractable to map-based cloning of agronomic and other genes of interest. We propose a targeted geneti mapping strategy that combines linkage and physical mapping and may facilitate map-based cloning. High-density linkage maps are either generated in wheat or in diploid Triticum tauschii, the donor of the D genome to wheat. Molecular marker-based chromosome maps are constructed, using an array of deletion lines in wheat. The conventional genetic linkage maps are aligned with chromosome maps to construct cytogenetic ladder maps (CLMs). The CLMs allow region-specific mapping and convert genetic distances into physical distances. The information from CLMs suggests that many genes in wheat are present in clusters that are highly recombiogenic, small, and may be amenable to cloning by chromosome walking. Therefore, the effective genome size of wheat is relatively small in comparison to the whole genome. The utility of using the smaller genome of rice for mapping and homologous gene cloning is discussed.     

Linkage analysis using single nucleotide polymorphisms

We performed multipoint linkage analysis using 83 markers from the SNP Consortium (TSC) SNP linkage map in 3 regions covering 190 cM previously scanned with microsatellite markers and found to be linked to type 2 diabetes. Since the average linkage disequilibrium present in the TSC SNP marker clusters is relatively low, we assumed the intracluster genetic distances were a reasonable small nonzero distance (0.03 cM) and performed linkage analysis using GENEHUNTER PLUS and ASM linkage analysis software. We found that for the pedigree structures and missing data patterns in our samples the average information content in all three regions and the LOD score curves in two regions obtained from the TSC SNP markers were similar to results obtained from microsatellite marker maps with 10 cM average spacing. We also give an algorithm which extends the Lander-Green algorithm to permit multipoint linkage analysis of clusters of tightly linked markers with arbitrarily high levels of intracluster linkage disequilibrium.     

A Field Evaluation of Distance Measurement Error in Auditory Avian Point Count Surveys

ABSTRACT Detection distance is an important and common auxiliary variable measured during avian point count surveys. Distance data are used to determine the area sampled and to model the detection process using distance sampling theory. In densely forested habitats, visual detections of birds are rare, and most estimates of detection distance are based on auditory cues. Distance sampling theory assumes detection distances are measured accurately, but empirical validation of this assumption for auditory detections is lacking. We used a song playback system to simulate avian point counts with known distances in a forested habitat to determine the error structure of distance estimates based on auditory detections. We conducted field evaluations with 6 experienced observers both before and after distance estimation training. We conducted additional studies to determine the effect of height and speaker orientation (toward or away from observers) on distance estimation error. Distance estimation errors for all evaluations were substantial, although training reduced errors and bias in distance estimates by approximately 15%. Measurement errors showed a nonlinear relationship to distance. Our results suggest observers were not able to differentiate distances beyond 65 m. The height from which we played songs had no effect on distance estimation errors in this habitat. The orientation of the song source did have a large effect on distance estimation errors; observers generally doubled their distance estimates for songs played away from them compared with distance estimates for songs played directly toward them. These findings, which we based on realistic field conditions, suggest measures of uncertainty in distance estimates to auditory detections are substantially higher than assumed by most researchers. This means aural point count estimates of avian abundance based on distance methods deserve careful scrutiny because they are likely biased.