MapDraw，在Excel中绘制遗传连锁图的宏

MAPMAKER是现今广泛使用的遗传连锁数据分析软件,然而其广泛使用的DOS版本却不具有连锁图绘制功能,给连锁作图工作带来了相当大的麻烦。为了解决这一问题,我们以大家广泛使用的数据处理软件Microsoft Excel为平台,编写了一个Excel宏——MapDraw来在轻松的操作中实现遗传连锁图的绘制。 Abstract:MAPMAKER is one of the most widely used computer software package for constructing genetic linkage maps.However,the PC version,MAPMAKER 3.0 for PC,could not draw the genetic linkage maps that its Macintosh version,MAPMAKER 3.0 for Macintosh,was able to do.Especially in recent years,Macintosh computer is much less popular than PC.Most of the geneticists use PC to analyze their genetic linkage data.So a new computer software to draw the same genetic linkage maps on PC as the MAPMAKER for Macintosh to do on Macintosh has been crying for.Microsoft Excel,one component of Microsoft Office package,is one of the most popular software in laboratory data processing.Microsoft Visual Basic for Applications (VBA) is one of the most powerful functions of Microsoft Excel.Using this program language,we can take creative control of Excel,including genetic linkage map construction,automatic data processing and more.In this paper,a Microsoft Excel macro called MapDraw is constructed to draw genetic linkage maps on PC computer based on given genetic linkage data.Use this software,you can freely construct beautiful genetic linkage map in Excel and freely edit and copy it to Word or other application.This software is just an Excel format file.You can freely copy it from ftp://211.69.140.177 or ftp://brassica.hzau.edu.cn and the source code can be found in Excel′s Visual Basic Editor.     

Construction of an AFLP genetic map with nearly complete genome coverage in Pinus taeda

  De novo construction of complete genetic linkage maps requires large mapping populations, large numbers of genetic markers, and efficient algorithms for ordering markers and evaluating order confidence. We constructed a complete genetic map of an individual loblolly pine (Pinus taeda L.) using amplified fragment length polymorphism (AFLP) markers segregating in haploid megagametophytes and PGRI mapping software. We generated 521 polymorphic fragments from 21 AFLP primer pairs. A total of 508 fragments mapped to 12 linkage groups, which is equal to the Pinus haploid chromosome number. Bootstrap locus order matrices and recombination matrices generated by PGRI were used to select 184 framework markers that could be ordered confidently. Order support was also evaluated using log likelihood criteria in MAPMAKER. Optimal marker orders from PGRI and MAPMAKER were identical, but the implied reliability of orders differed greatly. The framework map provides nearly complete coverage of the genome, estimated at approximately 1700 cM in length using a modified estimator. This map should provide a useful framework for merging existing loblolly pine maps and adding multiallelic markers as they become available. Map coverage with dominant markers in both linkage phases will make the map useful for subsequent quantitative trait locus mapping in families derived by self-pollination. Received: 7 August 1998 / Accepted: 27 October 1998     

Influence of aberrant observations on high-resolution linkage analysis outcomes

Because of the availability of efficient, user-friendly computer analysis programs, the construction of multilocus human genetic maps has become commonplace. At the level of resolution at which most of these maps have been developed, the methods have proved to be robust. This may not be true in the construction of high-resolution linkage maps (3-cM interlocus resolution or less). High-resolution meiotic maps, by definition, have a low probability of recombination occurring in an interval. As such, even low frequencies of errors in typing (1.5% or less) may influence mapping outcomes. To investigate the influence of aberrant observations on high-resolution maps, a Monte Carlo simulation analysis of multipoint linkage data was performed. Introduction of error was observed to reduce power to discriminate orders, dramatically inflate map length, and provide significant support for incorrect over correct orders. These results appear to be due to the misclassification of nonrecombinant gametes as multiple recombinants. Chi 2-Like goodness-of-fit analysis appears to be quite sensitive to the appearance of misclassified gametes, providing a simple test for aberrant data sets. Multiple pairwise likelihood analysis appears to be less sensitive than does multipoint analysis and may serve as a check for map validity.     

Rapid multipoint linkage analysis of recessive traits in nuclear families, including homozygosity mapping.

Homozygosity mapping is a powerful strategy for mapping rare recessive traits in children of consanguineous marriages. Practical applications of this strategy are currently limited by the inability of conventional linkage analysis software to compute, in reasonable time, multipoint LOD scores for pedigrees with inbreeding loops. We have developed a new algorithm for rapid multipoint likelihood calculations in small pedigrees, including those with inbreeding loops. The running time of the algorithm grows, at most, linearly with the number of loci considered simultaneously. The running time is not sensitive to the presence of inbreeding loops, missing genotype information, and highly polymorphic loci. We have incorporated this algorithm into a software package, MAPMAKER/HOMOZ, that allows very rapid multipoint mapping of disease genes in nuclear families, including homozygosity mapping. Multipoint analysis with dozens of markers can be carried out in minutes on a personal workstation.     

Complete multipoint sib-pair analysis of qualitative and quantitative traits.

Sib-pair analysis is an increasingly important tool for genetic dissection of complex traits. Current methods for sib-pair analysis are primarily based on studying individual genetic markers one at a time and thus fail to use the full inheritance information provided by multipoint linkage analysis. In this paper, we describe how to extract the complete multipoint inheritance information for each sib pair. We then describe methods that use this information to map loci affecting traits, thereby providing a unified approach to both qualitative and quantitative traits. Specifically, complete multipoint approaches are presented for (1) exclusion mapping of qualitative traits; (2) maximum-likelihood mapping of qualitative traits; (3) information-content mapping, showing the extent to which all inheritance information has been extracted at each location in the genome; and (4) quantitative-trait mapping, by two parametric methods and one nonparametric method. In addition, we explore the effects of marker density, marker polymorphism, and availability of parents on the information content of a study. We have implemented the analysis methods in a new computer package, MAPMAKER/SIBS. With this computer package, complete multipoint analysis with dozens of markers in hundreds of sib pairs can be carried out in minutes.     

Integration of the PiGMaP and USD A maps for porcine chromosome 14

In order to align two previously published genetic linkage maps, a set of four of the United States Department of Agriculture (USDA) microsatellite linkage markers was mapped in the International Pig Gene Mapping Project (PiGMaP) reference families. Two-point linkage analysis was used between these USDA markers and the set of genes and markers previously mapped on the PiGMaP chromosome 14 map-Markers with threshold lod scores of three or greater were used for multipoint map construction. The USDA and PigGMaP linkage maps of chromosome 14 were aligned using the four USDA microsatellite markers along with three markers that are common to both maps. The PiGMaP genetic linkage map order for chromosome 14 was confirmed and the map was expanded to 193 cM with addition of the new markers.     

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.     

Towards second-generation STS (sequence-tagged sites) linkage maps in conifers: a genetic map of Norway spruce (Picea abies K.)

Genetic linkage maps have been produced for a wide range of organisms during the last decade, thanks to the increasing availability of molecular markers. The use of microsatellites (or Simple Sequence Repeats, SSRs) as genetic markers has led to the construction of “second-generation” genetic maps for humans, mouse and other organisms of major importance. We constructed a second-generation single-tree genetic linkage map of Norway spruce (Picea abies K.) using a panel of 72 haploid megagametophytes with a total of 447 segregating bands [366 Amplified Fragment Length Polymorphisms (AFLPs), 20 Selective Amplification of Microsatellite Polymorphic Loci (SAMPLs) and 61 SSRs, each single band being treated initially as a dominant marker]. Four hundred and thirteen markers were mapped in 29 linkage groups (including triplets and doublets) covering a genetic length of 2198.3?cM, which represents 77.4% of the estimated genome length of Picea abies (approximately 2839?cM). The map is still far from coalescing into the expected 12 chromosomal linkage groups of Norway spruce (2n?=?2x?=?24). A?possible explanation for this comes from the observed non-random distribution of markers in the framework map. Thirty-eight SSR marker loci could be mapped onto 19 linkage groups. This set of highly informative Sequence Tagged Sites (STSs) can be used in many aspects of genetic analysis of forest trees, such as marker-assisted selection, QTL mapping, positional cloning, gene flow analysis, mating system analysis and genetic diversity studies.     

Towards second-generation STS (sequence-tagged sites) linkage maps in conifers: a genetic map of Norway spruce ( Picea abies K.)

Genetic linkage maps have been produced for a wide range of organisms during the last decade, thanks to the increasing availability of molecular markers. The use of microsatellites (or Simple Sequence Repeats, SSRs) as genetic markers has led to the construction of “second-generation” genetic maps for humans, mouse and other organisms of major importance. We constructed a second-generation single-tree genetic linkage map of Norway spruce (Picea abies K.) using a panel of 72 haploid megagametophytes with a total of 447 segregating bands [366 Amplified Fragment Length Polymorphisms (AFLPs), 20 Selective Amplification of Microsatellite Polymorphic Loci (SAMPLs) and 61 SSRs, each single band being treated initially as a dominant marker]. Four hundred and thirteen markers were mapped in 29 linkage groups (including triplets and doublets) covering a genetic length of 2198.3 cM, which represents 77.4% of the estimated genome length of Picea abies (approximately 2839 cM). The map is still far from coalescing into the expected 12 chromosomal linkage groups of Norway spruce (2n = 2x = 24). A possible explanation for this comes from the observed non-random distribution of markers in the framework map. Thirty-eight SSR marker loci could be mapped onto 19 linkage groups. This set of highly informative Sequence Tagged Sites (STSs) can be used in many aspects of genetic analysis of forest trees, such as marker-assisted selection, QTL mapping, positional cloning, gene flow analysis, mating system analysis and genetic diversity studies. Received: 5 November 1997 / Accepted: 16 March 1998     

林木全同胞群体的多位点连锁分析

多位点连锁分析是构建人类以及动植物的遗传连锁图谱的关键步骤之一。但是由于林木遗传背景的复杂性,多位点连锁分析在林木的全同胞群体中还没有得到应用．本文将多位点连锁分析应用到林木的F1代全同胞群体中．对于全同胞群体的任意分离比的两个位点,给出了在不同的连锁相下从一个位点到另一个位点的转移概率矩阵．对于给定的一列标记位点,考虑了不同分离比位点以及两位点间的连锁相信息,采用隐马尔可夫链模型计算极大似然函数和相邻位点间的重组率．本文的方法有助于构建完整的高密度的林木遗传连锁图谱．     

A primary linkage map of the human chromosome 11q22-23 region

We have constructed a genetic map of the human chromosomal region 11q22-23 by multipoint linkage analysis of 13 DNA polymorphisms that we have condensed into eight loci. An analysis for linkage disequilibrium between tightly linked probe/enzyme systems allows us to make specific recommendations for future DNA typing at these loci. The resulting sex-averaged multipoint map spans approximately 80 cM and differs considerably from previously reported genetic maps of this region. Our mathematically derived "most likely order" of the markers is compatible with physical mapping data using somatic cell hybrids. The known localizations of at least 14 functional genes and several disease loci to 11q22-23, including ataxia telangiectasia, make the mapping of this region especially relevant to studies of disease pathogenesis.     

Preliminary linkage map of the turkey (Meleagris gallopavo) based on microsatellite markers

The turkey is an agriculturally important species for which, until now, there is no published genetic linkage map based on microsatellite markers--still the markers most used in the chicken and other farm animals. In order to increase the number of markers on a turkey genetic linkage map we decided to map new microsatellite sequences obtained from a GT-enriched turkey genomic library. In different chicken populations more than 35-55% of microsatellites are polymorphic. In the turkey populations tested here, 43% of all turkey primers tested were found to be polymorphic, in both commercial and wild type turkeys. Twenty linkage groups (including the Z chromosome) containing 74 markers have been established, along with 37 other unassigned markers. This map will lay the foundations for further genetic mapping and the identification of genes and quantitative trait loci in this economically important species. Genome comparisons, based on genetic maps, with related species such as the chicken would then also be possible. All primer information, polymerase chain reaction (PCR) conditions, allele sizes and genetic linkage maps can be viewed at http://roslin.thearkdb.org/. The DNA is also available on request through the Roslin Institute.     

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.     

构建分子标记连锁图谱的一种新方法：三点自交法

作者从数学上导出了基因作图的三点自交方法。这一方法同用三点测交法一样能提供各种作图信息,但不需要选育三隐性纯合基因亲本或品系,因而能大大提高作图功效。,从理论上证明,该方法也适合于小群体作图分子标记连锁图谱,同时用Ｆisher单一观察信息（即Ｆ信息）量证明,三点自交法是一种有效的作图方法,应用ＭＡＰＭＡＫＥＲ程序中所提供的才鼠Ｆ２群体中３３３个个体的１２个ＲＦＬＰ标记位点中前６个位点的数据对三点自交图图距计算具有与ＭＡＰＭＡＫＥＲ程序一样的功能,而且还提供了位点间的交叉干涉和位点的相引或相斥构型等信息以及紧密位点间发生负干涉作用的证据。     

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.     

Genetic heterogeneity in tuberous sclerosis

Tuberous sclerosis (TSC) is an autosomal dominant disorder characterized by widespread hamartosis. Preliminary evidence of linkage between the TSC locus and markers on chromosome 9q34 was established, but subsequently disputed. More recently, a putative TSC locus on chromosome 11 has been suggested and genetic heterogeneity seems likely. Here we describe an approach combining multipoint linkage analysis and heterogeneity tests that has enabled us to obtain significant evidence for locus heterogeneity after studying a relatively small number of families. Our results support a model with two different loci independently causing the disease. One locus (TSC1) maps in the vicinity of the Abelson oncogene at 9q34 and a second locus (TSC2) maps in the region of the anonymous DNA marker Lam L7 and the dopamine D2 receptor gene at 11q23.     

Combination of multipoint maximum likelihood (MML) and regression mapping algorithms to construct a high-density genetic linkage map for loblolly pine (Pinus taeda L.)

Genetic maps have been successfully applied to assist in the dissection of complex traits, provide insight on genome structure, and estimate recombination in conjunction with physical maps. Despite an extensive list of genetic maps developed for loblolly pine (Pinus taeda L.) over the past two decades, a high-density consensus map has not yet been constructed. In this study, we used two reference three-generation outbred pedigrees, base and qtl, obtained from the North Carolina State University Cooperative Tree Improvement Program, to obtain a high-density genetic consensus map. Both populations were genotyped with ≈ 7,000 different markers (restriction fragment length polymorphisms, expressed sequence tag polymorphisms, simple sequence repeats, SNPs). The grouping, ordering, and spacing of the markers on each linkage group were performed with JoinMap® 4.1, which implements the multipoint maximum likelihood algorithm for outbred populations. The final consensus map contains 2,466 markers, with a total length of 1,476 centimorgans (cM). The average marker density across the 12 linkage groups was 0.62 cM/marker. This high-density map provides an important resource for breeders and geneticists and will enable comparative studies across species, as well as improve the loblolly pine genome sequence assembly.     

Incorporating interference into linkage analysis for experimental crosses

The phenomenon of interference in genetic recombination is well-known and studied in a wide variety of organisms. Multilocus linkage analysis, which makes use of recombination patterns among all genetic markers simultaneously, is routinely used with data on humans and experimental organisms to build genetic maps. It is also used to try to determine the genes involved in traits of interest, such as common diseases. Most linkage analyses performed today ignore the occurrence of genetical interference. We present an extension to the Lander-Green algorithm for experimental crosses (backcross and intercross) to incorporate crossover interference according to the chi2 model. Simulation results show the impact of using this model on the accuracy of estimated genetic maps.     

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.     

Robustness of linkage maps in natural populations: a simulation study

In a number of long-term individual-based studies of vertebrate populations, the genealogical relationships between individuals have been established with molecular markers. As a result, it is possible to construct genetic linkage maps of these study populations by examining the co-segregation of markers through the pedigree. There are now four free-living vertebrate study populations for whom linkage maps have been built. In this study, simulation was used to investigate whether these linkage maps are likely to be accurate. In all four populations, the probability of assigning markers to the correct chromosome is high and framework maps are generally inferred correctly. However, genotyping error can result in incorrect maps being built with very strong statistical support over the correct order. Future applications of linkage maps of natural populations are discussed.