Map Manager QTX, cross-platform software for genetic mapping

Map Manager QTX (QTX) is software for analysis of genetic mapping experiments in experimental plants and animals. It includes functions for mapping both Mendelian and quantitative trait loci. QTX is an enhanced version of Map Manager QT, rewritten with the aid of cross-platform libraries (XVT, Boulder Software Foundry, Inc.), which allow it to be compiled for multiple computer platforms. It currently is distributed for Microsoft Windows and Mac OS and is available at http://mapmgr.roswellpark.org/mmQTX.html. Received: 2 July 2001 / Accepted: 20 August 2001     

A simple linear regression method for quantitative trait loci linkage analysis with censored observations

Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using simulation we compare this method to both the Cox and Weibull proportional hazards models and a standard linear regression method that ignores censoring. The grouped linear regression method is of equivalent power to both the Cox and Weibull proportional hazards methods and is significantly better than the standard linear regression method when censored observations are present. The method is also robust to the proportion of censored individuals and the underlying distribution of the trait. On the basis of linear regression methodology, the grouped linear regression model is computationally simple and fast and can be implemented readily in freely available statistical software.     

Chromosomal loci influencing chronic alcohol withdrawal severity

Ethanol (alcohol) withdrawal-induced convulsions are a key index of physical dependence on ethanol and a clinically important consequence of alcohol abuse in humans. In rodent models, severity of withdrawal is strongly influenced by genotype. For example, many studies have reported marked differences in withdrawal severity between the WSR (Withdrawal Seizure Resistant) and WSP (Withdrawal Seizure Prone) mouse strains selectively bred for over 25 generations to differ in chronic withdrawal severity. Therefore, we used an F₂ intercross between the inbred WSP and WSR strains for a genome-wide search for quantitative trait loci (QTLs), which are chromosomal sites containing genes influencing the magnitude of withdrawal. We also used the recently developed HW, RHW (high withdrawal) and LW, RLW (low withdrawal) lines selectively bred for the same trait and in the same manner as the WSP, WSR lines. QTL analysis was then used to dissect the continuous trait distribution of withdrawal severity into component loci, and to map them to broad chromosomal regions by using the Pseudomarker 0.9 and Map Manager QT29b programs. This genome-wide search identified five significant QTLs influencing chronic withdrawal severity on Chromosomes (Chrs) 1 (proximal), 4 (mid), 8 (mid), 11 (proximal), and 14 (mid), plus significant interactions (epistasis) between loci on Chr 11 with 13, 4 with 8, and 8 with 14.     

Genetic mapping of quantitative trait loci affecting susceptibility to Marek's disease virus induced tumors in F2 intercross chickens.

Marek''s disease (MD) is a lymphoproliferative disease caused by the MD virus (MDV), which costs the poultry industry nearly $1 billion annually. To identify quantitative trait loci (QTL) affecting MD susceptibility, the inbred lines 6(3) (MD resistant) and 7(2) (MD susceptible) were mated to create more than 300 F2 chickens. The F2 chickens were challenged with MDV JM strain, moderately virulent) at 1 wk of age and assessed for MD susceptibility. The QTL analysis was divided into three stages. In stage 1, 65 DNA markers selected from the chicken genetic maps were typed on the 40 most MD-susceptible and the 40 most MD-resistant F2 chickens, and 21 markers residing near suggestive QTL were revealed by analysis of variance (ANOVA). In stage 2, the suggestive markers plus available flanking markers were typed on 272 F2 chickens, and three suggestive QTL were identified by ANOVA. In stage 3, using the interval mapping program Map Manager and permutation tests, two significant and two suggestive MD QTL were identified on four chromosomal subregions. Three to five loci collected explained between 11 and 23% of the phenotypic MD variation, or 32-68% of the genetic variance. This study constitutes the first report in the domestic chicken on the mapping of non-major histocompatibility complex QTL affecting MD susceptibility.     

小鼠15号染色体上脊髓重数量性状基因座的精细定位

目的以前的研究结果表明,控制小鼠脊髓重的一个数量性状基因座(QTL)位于15号染色体D15Mit158附近,跨度约30cM。为分离和确认脊髓重相关基因,本文对该QTL区域进行了精细定位。方法以高级互交系小鼠A/J×C57BL/6J(F4)为研究对象,选择脊髓重偏向两极的个体,在D15Mit158位点附近作高密度局部基因组扫描,用Map Manager QTX19软件对脊髓重与基因型进行连锁不平衡分析。结果在15号染色体D15Mit107附近出现了一个很强的连锁峰,LRS值为17.3(P=1.8×10-4),变异解释率为27%,LOD值达到3.75,可以认定为一主效QTL。该QTL跨度范围为3.2cM。另一个提示可能具有连锁关系的QTL位点在D15Mit28附近,LRS值为7.6(P=0.02),变异解释率为13%,跨度范围为5.0cM。结论控制小鼠脊髓重的D15Mit158区域实际上含有两个QTL,其中一个主效QTL位于15号染色体上宽约3.2cM的D15Mit107位点附近;另一个可能的QTL位于宽约5.0cM的D15Mit28附近。     

Mapping quantitative trait loci in inbred backcross lines of Lycopersicon pimpinellifolium (LA1589).

Although tomato has been the subject of extensive quantitative trait loci (QTLs) mapping experiments, most of this work has been conducted on transient populations (e.g., F2 or backcross) and few homozygous, permanent mapping populations are available. To help remedy this situation, we have developed a set of inbred backcross lines (IBLs) from the interspecific cross between Lycopersicon esculentum cv. E6203 and L. pimpinellifolium (LA1589). A total of 170 BC2F1 plants were selfed for five generations to create a set of homozygous BC2F6 lines by single-seed descent. These lines were then genotyped for 127 marker loci covering the entire tomato genome. These IBLs were evaluated for 22 quantitative traits. In all, 71 significant QTLs were identified, 15% (11/71) of which mapped to the same chromosomal positions as QTLs identified in earlier studies using the same cross. For 48% (34/71) of the detected QTLs, the wild allele was associated with improved agronomic performance. A number of new QTLs were identified including several of significant agronomic importance for tomato production: fruit shape, firmness, fruit color, scar size, seed and flower number, leaf curliness, plant growth, fertility, and flowering time. To improve the utility of the IBL population, a subset of 100 lines giving the most uniform genome coverage and map resolution was selected using a randomized greedy algorithm as implemented in the software package MapPop (http://www.bio.unc.edu/faculty/vision/lab/ mappop/). The map, phenotypic data, and seeds for the IBL population are publicly available (http://soldb.cit.cornell.edu) and will provide tomato geneticists and breeders with a genetic resource for mapping, gene discovery, and breeding.     

A high density consensus map of rye (Secale cereale L.) based on DArT markers

Background

Rye (Secale cereale L.) is an economically important crop, exhibiting unique features such as outstanding resistance to biotic and abiotic stresses and high nutrient use efficiency. This species presents a challenge to geneticists and breeders due to its large genome containing a high proportion of repetitive sequences, self incompatibility, severe inbreeding depression and tissue culture recalcitrance. The genomic resources currently available for rye are underdeveloped in comparison with other crops of similar economic importance. The aim of this study was to create a highly saturated, multilocus linkage map of rye via consensus mapping, based on Diversity Arrays Technology (DArT) markers.

Methodology/Principal Findings

Recombinant inbred lines (RILs) from 5 populations (564 in total) were genotyped using DArT markers and subjected to linkage analysis using Join Map 4.0 and Multipoint Consensus 2.2 software. A consensus map was constructed using a total of 9703 segregating markers. The average chromosome map length ranged from 199.9 cM (2R) to 251.4 cM (4R) and the average map density was 1.1 cM. The integrated map comprised 4048 loci with the number of markers per chromosome ranging from 454 for 7R to 805 for 4R. In comparison with previously published studies on rye, this represents an eight-fold increase in the number of loci placed on a consensus map and a more than two-fold increase in the number of genetically mapped DArT markers.

Conclusions/Significance

Through the careful choice of marker type, mapping populations and the use of software packages implementing powerful algorithms for map order optimization, we produced a valuable resource for rye and triticale genomics and breeding, which provides an excellent starting point for more in-depth studies on rye genome organization.     

Mapping and manipulating quantitative traits in maize

Maize has been used effectively as a model organism in the development and evaluation of molecular markers for the identification, mapping and manipulation of major genes affecting the expression of quantitative traits in plants. Although quantitative geneticists have recognized the possibility of major loci, the general dogma bad emerged that quantitative traits were controlled by many loci, each with a small effect. This interpretation sent a signal to the molecular biologist not to bother with quantitative traits because it would be essentially impossible to isolate a gene responsible for the trait. Recent results from numerous mapping studies have shown that quantitative traits are controlled by, at least some, factors with major effects, and have given credibility to the conclusion that major loci exist and that one might be able to study them. Positive results from marker-facilitated selection and introgression studies have further strengthened this conclusion.     

Quantitative trait locus mapping for atherosclerosis susceptibility

PURPOSE OF REVIEW: Atherosclerosis is a complex trait with both environmental and genetic aspects. Although some progress has been made in defining genes associated with atherosclerosis in humans, animal models have been useful in learning about pathways and genes involved in atherogenesis. This review describes an unbiased genetic mapping method called quantitative trait locus mapping and progress in using this method to identify genes that alter atherosclerosis susceptibility in mice. RECENT FINDINGS: Approximately 10 well defined genetic loci have been described that are associated with lesion severity in diet-induced or gene knockout mouse models of atherosclerosis. Recently, two of these genetic loci were narrowed considerably by analysis of genetic recombinants within these loci. In addition, a computational method to discover quantitative trait loci has been applied to atherosclerosis. However, none of the genes responsible for these atherosclerosis quantitative trait loci has been definitively identified. The recent completion of the mouse draft genome should facilitate the task of identifying these genes. SUMMARY: Quantitative trait locus mapping studies in mouse models of atherosclerosis have defined genetic regions that alter lesion severity. The identification of the responsible genes may lead to insights into the pathogenesis of atherosclerosis as well as to candidates for human genetic association studies.     

RAPD-based genetic linkage maps of yellow passion fruit (Passiflora edulis Sims. f. flavicarpa Deg.).

A single cross between two clones of passion fruit (Passiflora edulis Sims. f. flavicarpa Deg., 2n = 18) was selected for genetic mapping. The mapping population was composed of 90 F1 plants derived from a cross between 'IAPAR 123' (female parent) and 'IAPAR 06' (male parent). A total of 380 RAPD primers were analyzed according to two-way pseudo-testcross mapping design. The linkage analysis was performed using Mapmaker version 3.0 with LOD 4.0 and a maximum recombination fraction (theta) of 0.30. Map distances were estimated using the Kosambi mapping function. Linkage maps were constructed with 269 loci (2.38 markers/primer), of which 255 segregated 1:1, corresponding to a heterozygous state in one parent and null in the other. The linkage map for 'IAPAR123' consisted of 135 markers. A total of nine linkage groups were assembled covering 727.7 cM, with an average distance of 11.20 cM between framework loci. The sizes of the linkage groups ranged from 56 to 144.6 cM. The linkage map for 'IAPAR 06' consisted of 96 markers, covering 783.5 cM. The average distance between framework loci was 12.2 cM. The length of the nine linkage groups ranged from 20.6 to 144.2 cM. On average, both maps provided 61% genome coverage. Twenty-four loci (8.9%) remained unlinked. Among their many applications, these maps are a starting point for the identification of quantitative trait loci for resistance to the main bacterial disease affecting passion fruit orchards in Brazil, caused by Xanthomonas campestris pv. passiflorae, because parental genotypes exhibit diverse responses to bacterial inoculation.     

Linkage disequilibrium mapping of quantitative trait loci under truncation selection

As a dense map of single nucleotide polymorphism (SNP) markers are available, population-based linkage disequilibrium (LD) mapping or association study is becoming one of the major tools for identifying quantitative trait loci (QTL) and for fine gene mapping. However, in many cases, LD between the marker and trait locus is not very strong. Approaches that maximize the potential of detecting LD will be essential for the success of LD mapping of QTL. In this paper, we propose two strategies for increasing the probability of detecting LD: (1) phenotypic selection and (2) haplotype LD mapping. To provide the foundations for LD mapping of QTL under selection, we develop analytic tools for assessing the impact of phenotypic selection on allele and haplotype frequencies, and LD under three trait models: single trait locus, two unlinked trait loci, and two linked trait loci with or without epistasis. In addition to a traditional chi(2) test, which compares the difference in allele or haplotype frequencies in the selected sample and population sample, we present multiple regression methods for LD mapping of QTL, and investigate which methods are effective in employing phenotypic selection for QTL mapping. We also develop a statistical framework for investigating and comparing the power of the single marker and multilocus haplotype test for LD mapping of QTL. Finally, the proposed methods are applied to mapping QTL influencing variation in systolic blood pressure in an isolated Chinese population.     

Construction of dense linkage maps “on the fly” using early generation wheat breeding populations

In plant species, construction of framework linkage maps to facilitate quantitative trait loci mapping and molecular breeding has been confined to experimental mapping populations. However, development and evaluation of these populations is detached from breeding efforts for cultivar development. In this study, we demonstrate that dense and reliable linkage maps can be constructed using extant breeding populations derived from a large number of crosses, thus eliminating the need for extraneous population development. Using 565 segregating F₁ progeny from 28 four-way cross breeding populations, a linkage map of the hexaploid wheat genome consisting of 3,785 single nucleotide polymorphism (SNP) loci and 22 simple sequence repeat loci was developed. Map estimation was facilitated by application of mapping algorithms for general pedigrees implemented in the software package CRI-MAP. The developed linkage maps showed high rank-order concordance with a SNP consensus map developed from seven mapping studies. Therefore, the linkage mapping methodology presented here represents a resource efficient approach for plant breeding programs that enables development of dense linkage maps “on the fly” to support molecular breeding efforts.     

Quantitative Resistance to Phytophthora Infestans in Potato: A Case Study for Qtl Mapping in an Allogamous Plant Species

Phytophthora infestans is the most important fungal pathogen in the cultivated potato (Solanum tuberosum). Dominant, race-specific resistance alleles and quantitative resistance-the latter being more important for potato breeding- are found in the germplasm of cultivated and wild potato species. Quantitative trait loci (QTLs) for resistance to two races of P. infestans have been mapped in an F(1) progeny of a cross between non-inbred diploid potato parents with multiple alleles. Interval mapping methods based on highly informative restriction fragment length polymorphism markers revealed 11 chromosome segments on 9 potato chromosomes showing significant contrasts between marker genotypic classes. Whereas phenotypically no difference in quantitative resistance response was observed between the two fungal races, QTL mapping identified at least one race specific QT locus. Two QT regions coincided with two small segments on chromosomes V and XII to which the dominant alleles R1, conferring race specific resistance to P. infestans, Rx1 and Rx2, both inducing extreme resistance to potato virus X, have been allocated in independent mapping experiments. Some minor QTLs were correlated with genetic loci for specific proteins related to pathogenesis, the expression of which is induced after infection with P. infestans.     

Qxpak: a versatile mixed model application for genetical genomics and QTL analyses

MOTIVATION: Current methodology and software for quantitative trait loci (QTL) analyses do not use all available information and are inadequate to deal with the huge amount of QTL analyses to be needed in forecoming genetical genomics' studies. RESULTS: We show that a mixed model statistical framework provides a very flexible tool for QTL modeling in a variety of populations, be it a cross between inbred lines, a within population study, or experiments involving a mixture of populations or crosses. The software allows multitrait and multiQTL analyses, inclusion of infinitesimal genetic value and a batch multitrait option suitable for genetical genomics studies. It also allows massive association studies between single nucleotide polymorphisms and the trait(s) of interest. AVAILABILITY: A software (Qxpak), together with a manual and example files, is freely available for research purposes. So far, the compiled program is available for linux systems, the windows version will follow soon. See http://www.icrea.es/pag.asp?id=Miguel.Perez     

Analysis of allele fidelity, polymorphic information content, and density of microsatellites in a genome-wide screening for hip dysplasia in a crossbreed pedigree

Recent advances in genomics resources and tools are facilitating quantitative trait locus mapping. We developed a crossbreed pedigree for mapping quantitative trait loci for hip dysplasia in dogs by crossing dysplastic Labrador Retrievers and normal Greyhounds. We show that one advantage to using a crossbreed pedigree is the increased marker informativeness in the backcross/F2 population relative to the founder populations. We also discuss three factors that affect the detection power in the context of this crossbreed pedigree: being able to detect and correct genotyping errors, increasing marker density for chromosomes with a sparse coverage, and adding individuals to the mapping population as soon as they become available.     

R/qtl: QTL mapping in experimental crosses

SUMMARY: R/qtl is an extensible, interactive environment for mapping quantitative trait loci (QTLs) in experimental populations derived from inbred lines. It is implemented as an add-on package for the freely-available statistical software, R, and includes functions for estimating genetic maps, identifying genotyping errors, and performing single-QTL and two-dimensional, two-QTL genome scans by multiple methods, with the possible inclusion of covariates. AVAILABILITY: The package is freely available at http://www.biostat.jhsph.edu/~kbroman/qtl.     

Mapping Mendelian Factors Underlying Quantitative Traits Using RFLP Linkage Maps

The advent of complete genetic linkage maps consisting of codominant DNA markers [typically restriction fragment length polymorphisms (RFLPs)] has stimulated interest in the systematic genetic dissection of discrete Mendelian factors underlying quantitative traits in experimental organisms. We describe here a set of analytical methods that modify and extend the classical theory for mapping such quantitative trait loci (QTLs). These include: (i) a method of identifying promising crosses for QTL mapping by exploiting a classical formula of SEWALL WRIGHT; (ii) a method (interval mapping) for exploiting the full power of RFLP linkage maps by adapting the approach of LOD score analysis used in human genetics, to obtain accurate estimates of the genetic location and phenotypic effect of QTLs; and (iii) a method (selective genotyping) that allows a substantial reduction in the number of progeny that need to be scored with the DNA markers. In addition to the exposition of the methods, explicit graphs are provided that allow experimental geneticists to estimate, in any particular case, the number of progeny required to map QTLs underlying a quantitative trait.     

Bayesian mapping of multiple quantitative trait loci from incomplete inbred line cross data.

A novel fine structure mapping method for quantitative traits is presented. It is based on Bayesian modeling and inference, treating the number of quantitative trait loci (QTLs) as an unobserved random variable and using ideas similar to composite interval mapping to account for the effects of QTLs in other chromosomes. The method is introduced for inbred lines and it can be applied also in situations involving frequent missing genotypes. We propose that two new probabilistic measures be used to summarize the results from the statistical analysis: (1) the (posterior) QTL intensity, for estimating the number of QTLs in a chromosome and for localizing them into some particular chromosomal regions, and (2) the locationwise (posterior) distributions of the phenotypic effects of the QTLs. Both these measures will be viewed as functions of the putative QTL locus, over the marker range in the linkage group. The method is tested and compared with standard interval and composite interval mapping techniques by using simulated backcross progeny data. It is implemented as a software package. Its initial version is freely available for research purposes under the name Multimapper at URL http://www.rni.helsinki.fi/mjs.