BioMercator: integrating genetic maps and QTL towards discovery of candidate genes

SUMMARY: Breeding programs face the challenge of integrating information from genomics and from quantitative trait loci (QTL) analysis in order to identify genomic sequences controlling the variation of important traits. Despite the development of integrative databases, building a consensus map of genes, QTL and other loci gathered from multiple maps remains a manual and tedious task. Nevertheless, this is a critical step to reveal co-locations between genes and QTL. Another important matter is to determine whether QTL linked to same traits or related ones is detected in independent experiments and located in the same region, and represents a single locus or not. Statistical tools such as meta-analysis can be used to answer this question. BioMercator has been developed to automate map compilation and QTL meta-analysis, and to visualize co-locations between genes and QTL through a graphical interface. AVAILABILITY: Available upon request (http://moulon/~bioinfo/BioMercator/). Free of charge for academic use.     

Bayesian shrinkage analysis of quantitative trait Loci for dynamic traits

Many quantitative traits are measured repeatedly during the life of an organism. Such traits are called dynamic traits. The pattern of the changes of a dynamic trait is called the growth trajectory. Studying the growth trajectory may enhance our understanding of the genetic architecture of the growth trajectory. Recently, we developed an interval-mapping procedure to map QTL for dynamic traits under the maximum-likelihood framework. We fit the growth trajectory by Legendre polynomials. The method intended to map one QTL at a time and the entire QTL analysis involved scanning the entire genome by fitting multiple single-QTL models. In this study, we propose a Bayesian shrinkage analysis for estimating and mapping multiple QTL in a single model. The method is a combination between the shrinkage mapping for individual quantitative traits and the Legendre polynomial analysis for dynamic traits. The multiple-QTL model is implemented in two ways: (1) a fixed-interval approach where a QTL is placed in each marker interval and (2) a moving-interval approach where the position of a QTL can be searched in a range that covers many marker intervals. Simulation study shows that the Bayesian shrinkage method generates much better signals for QTL than the interval-mapping approach. We propose several alternative methods to present the results of the Bayesian shrinkage analysis. In particular, we found that the Wald test-statistic profile can serve as a mechanism to test the significance of a putative QTL.     

Mapping genome-wide QTL of ratio traits with Bayesian shrinkage analysis for its component traits

The ratio trait is defined as a ratio of two regular quantitative traits with normal distribution, which is distinguished from regular quantitative traits in the genetic analysis because it does not follow the normal distribution. On the basis of maximum likelihood method that uses a special linear combination of the two component traits, we develop a Bayesian mapping strategy for ratio traits, which firstly analyzes the two component traits by Bayesian shrinkage method, and then generates a new posterior sample of genetic effects for a ratio trait from ones of population means and genetic effects for the two component traits, finally, infers QTL for the ratio trait via post MCMC analysis for the new posterior sample. A simulation study demonstrates that the new method has higher detecting power of the QTL than maximum likelihood method. An application is illustrated to map genome-wide QTL for relative growth rate of height on soybean.     

Genetic mapping and quantitative trait locus analysis of fiber quality traits using a three-parent composite population in upland cotton (Gossypium hirsutum L.)

Composite cross populations (CP) developed from three or more cultivars/lines are frequently used to improve agronomic and economic traits in crop cultivar development programs. Employing CP in linkage map construction and quantitative trait locus (QTL) mapping may increase the marker density of upland cotton (Gossypium hirsutum L.) genetic maps, exploit more adequate gene resources and facilitate marker-assisted selection (MAS). To construct a relatively high-density map and identify QTL associated with fiber quality traits in upland cotton, three elite upland cultivars/lines, Yumian 1, CRI 35 and 7,235, were used to obtain the segregating population, Yumian 1/CRI 35//Yumian 1/7,235. A genetic map containing 978 simple sequence repeat (SSR) loci and 69 linkage groups was constructed; the map spanned 4,184.4 cM, covering approximately 94.1% of the entire tetraploid cotton genome. A total of 63 QTL were detected, explaining 8.1–55.8% of the total phenotypic variance: 11 QTL for fiber elongation, 16 QTL for fiber length, 9 QTL for fiber micronaire reading, 10 QTL for fiber strength and 17 QTL for fiber length uniformity. The genetic map and QTL detected for fiber quality traits are promising for further breeding programs of upland cotton with improved fiber quality.     

远交群体动态性状基因定位的似然分析Ⅰ.理论方法

受动物遗传育种中用来估计动态性状育种值的随机回归测定日模型思想的启发 ,将关于时间 (测定日期 )的Legendre多项式镶嵌在遗传模型的每个遗传效应中 ,以刻画QTL对动态性状变化过程的作用 ,从而建立起动态性状基因定位的数学模型。利用远交设计群体 ,阐述了动态性状基因定位的似然分析原理 ,推导了定位参数似然估计的EM法两步求解过程。结合动态性状遗传分析的特点和普通数量性状基因定位研究进展 ,还提出了有关动态性状基因定位进一步研究的设想     

Fine mapping reveals sex bias in quantitative trait loci affecting growth, skeletal size and obesity-related traits on mouse chromosomes 2 and 11

Previous speed congenic analysis has suggested that the expression of growth and obesity quantitative trait loci (QTL) on distal mouse chromosomes (MMU) 2 and 11, segregating between the CAST/EiJ (CAST) and C57BL/6J-hg/hg (HG) strains, is dependent on sex. To confirm, fine map, and further evaluate QTL x sex interactions, we constructed congenic by recipient F2 crosses for the HG.CAST-(D2Mit329-D2Mit457)N(6) (HG2D) and HG.CAST-(D11Mit260-D11Mit255)N(6) (HG11) congenic strains. Over 700 F2 mice were densely genotyped and phenotyped for a panel of 40 body and organ weight, skeletal length, and obesity-related traits at 9 weeks of age. Linkage analysis revealed 20 QTL affecting a representative subset of phenotypes in HG2DF2 and HG11F2 mice. The effect of sex was quantified by comparing two linear models: the first model included sex as an additive covariate and the second incorporated sex as an additive and an interactive covariate. Of the 20 QTL, 8 were sex biased, sex specific, or sex antagonistic. Most traits were regulated by single QTL; however, two closely linked loci were identified for five traits in HG2DF2 mice. Additionally, the confidence intervals for most QTL were significantly reduced relative to the original mapping results, setting the stage for quantitative trait gene (QTG) discovery. These results highlight the importance of assessing the contribution of sex in complex trait analyses.     

Both additivity and epistasis control the genetic variation for fruit quality traits in tomato

The effect of a gene involved in the variation of a quantitative trait may change due to epistatic interactions with the overall genetic background or with other genes through digenic interactions. The classical populations used to map quantitative trait loci (QTL) are poorly efficient to detect epistasis. To assess the importance of epistasis in the genetic control of fruit quality traits, we compared 13 tomato lines having the same genetic background except for one to five chromosome fragments introgressed from a distant line. Six traits were assessed: fruit soluble solid content, sugar content and titratable acidity, fruit weight, locule number and fruit firmness. Except for firmness, a large part of the variation of the six traits was under additive control, but interactions between QTL leading to epistasis effects were common. In the lines cumulating several QTL regions, all the significant epistatic interactions had a sign opposite to the additive effects, suggesting less than additive epistasis. Finally the re-examination of the segregating population initially used to map the QTL confirmed the extent of epistasis, which frequently involved a region where main effect QTL have been detected in this progeny or in other studies.     

3FunMap: full-sib family functional mapping of dynamic traits

MOTIVATION: Functional mapping that embeds the developmental mechanisms of complex traits shows great power to study the dynamic pattern of genetic effects triggered by individual quantitative trait loci (QTLs). A full-sib family, produced by crossing two heterozygous parents, is characteristic of uncertainties about cross-type at a locus and linkage phase between different loci. Integrating functional mapping into a full-sib family requires a model selection procedure capable of addressing these uncertainties. 3FunMap, written in VC++ 6.0, provides a flexible and extensible platform to perform full-sib functional mapping of dynamic traits. Functions in the package encompass linkage phase determination, marker map construction and the pattern identification of QTL segregation, dynamic tests of QTL effects, permutation tests and numerical simulation. We demonstrate the features of 3FunMap through real data analysis and computer simulation. AVAILABILITY: http://statgen.psu.edu/software.     

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.     

Genetic basis of phenotypic correlations among growth traits in hybrid willow (Salix dasycladosxS. viminalis) grown under two water regimes

Phenotypic correlations and quantitative trait loci (QTL) for important growth traits and a surrogate of intrinsic water-use efficiency (leaf delta(13)C) were analysed in a willow pedigree of 92 full-sibling clones grown under two water regimes. The major objective was to examine the genetic basis of the phenotypic correlations. Cuttings of Salix were glasshouse-grown during one growing season. The relative growth rate (RGR) and underlying traits were assessed. QTL analysis was conducted based on an available linkage map for Salix. Leaf area productivity and leaf nitrogen productivity were more important in determining RGR than leaf area ratio and specific leaf area. However, phenotypic correlations among growth traits partly varied between the two environments. QTL were detected for most growth traits, among them many common QTL for different traits. The QTL pattern reflected the phenotypic correlation pattern. None of the QTL for the complex traits was consistent across the different environments. The results demonstrate a genetic basis for phenotypic correlations among growth traits in Salix, and provide evidence for the existence of 'master switches' regulating some of the traits.     

A QTL resource and comparison tool for pigs: PigQTLDB

During the past decade, efforts to map quantitative trait loci (QTL) in pigs have resulted in hundreds of QTL being reported for growth, meat quality, reproduction, disease resistance, and other traits. It is a challenge to locate, interpret, and compare QTL results from different studies. We have developed a pig QTL database (PigQTLdb) that integrates available pig QTL data in the public domain, thus, facilitating the use of this QTL data in future studies. We also developed a pig trait classification system to standardize names of traits and to simplify organization and searching of the trait data. These steps made it possible to compare primary data from diverse sources and methods. We used existing pig map databases and other publicly available data resources (such as PubMed) to avoid redundant developmental work. The PigQTLdb was also designed to include data representing major genes and markers associated with a large effect on economically important traits. To date, over 790 QTL from 73 publications have been curated into the database. Those QTL cover more than 300 different traits. The data have been submitted to the Entrez Gene and the Map Viewer resources at NCBI, where the information about markers was matched to marker records in NCBI’s UniSTS database. Having these data in a public resource like NCBI allows regularly updated automatic matching of markers to public sequence data by e-PCR. The submitted data, and the results of these calculations, are retrievable from NCBI via Entrez Gene, Map Viewer, and UniSTS. Efforts were undertaken to improve the integrated functional genomics resources for pigs.     

A consensus linkage map of common carp (Cyprinus carpio L.) to compare the distribution and variation of QTLs associated with growth traits

The ability to detect and identify quantitative trait loci (QTLs) in a single population is often limited. Analyzing multiple populations in QTL analysis improves the power of detecting QTLs and provides a better understanding of their functional allelic variation and distribution. In this study, a consensus map of the common carp was constructed, based on four populations, to compare the distribution and variation of QTLs. The consensus map spans 2371.6 cM across the 42 linkage groups and comprises 257 microsatellites and 421 SNPs, with a mean marker interval of 3.7 cM/marker. Sixty-seven QTLs affecting four growth traits from the four populations were mapped to the consensus map. Only one QTL was common to three populations, and nine QTLs were detected in two populations. However, no QTL was common to all four populations. The results of the QTL comparison suggest that the QTLs are responsible for the phenotypic variability observed for these traits in a broad array of common carp germplasms. The study also reveals the different genetic performances between major and minor genes in different populations.     

Multiple trait multiple interval mapping of quantitative trait loci from inbred line crosses

ABSTRACT: BACKGROUND: Although many experiments have measurements on multiple traits, most studies performed the analysis of mapping of quantitative trait loci (QTL) for each trait separately using single trait analysis. Single trait analysis does not take advantage of possible genetic and environmental correlations between traits. In this paper, we propose a novel statistical method for multiple trait multiple interval mapping (MTMIM) of QTL for inbred line crosses. We also develop a novel score-based method for estimating genome-wide significance level of putative QTL effects suitable for the MTMIM model. The MTMIM method is implemented in the freely available and widely used Windows QTL Cartographer software. RESULTS: Throughout the paper, we provide compelling empirical evidences that: (1) the score-based threshold maintains proper type I error rate and tends to keep false discovery rate within an acceptable level; (2) the MTMIM method can deliver better parameter estimates and power than single trait multiple interval mapping method; (3) an analysis of Drosophila dataset illustrates how the MTMIM method can better extract information from datasets with measurements in multiple traits. CONCLUSIONS: The MTMIM method represents a convenient statistical framework to test hypotheses of pleiotropic QTL versus closely linked nonpleiotropic QTL, QTL by environment interaction, and to estimate the total genotypic variance-covariance matrix between traits and to decompose it in terms of QTL-specific variance-covariance matrices, therefore, providing more details on the genetic architecture of complex traits.     

Meta-analysis of QTL involved in silage quality of maize and comparison with the position of candidate genes

A meta-analysis of quantitative trait loci (QTL) associated with plant digestibility and cell wall composition in maize was carried out using results from 11 different mapping experiments. Statistical methods implemented in “MetaQTL” software were used to build a consensus map, project QTL positions and perform meta-analysis. Fifty-nine QTL for traits associated with digestibility and 150 QTL for traits associated with cell wall composition were included in the analysis. We identified 26 and 42 metaQTL for digestibility and cell wall composition traits, respectively. Fifteen metaQTL with confidence interval (CI) smaller than 10 cM were identified. As expected from trait correlations, 42% of metaQTL for digestibility displayed overlapping CIs with metaQTL for cell wall composition traits. Coincidences were particularly strong on chromosomes 1 and 3. In a second step, 356 genes selected from the MAIZEWALL database as candidates for the cell wall biosynthesis pathway were positioned on our consensus map. Colocalizations between candidate genes and metaQTL positions appeared globally significant based on χ² tests. This study contributed in identifying key chromosomal regions involved in silage quality and potentially associated genes for most of these regions. These genes deserve further investigation, in particular through association mapping.     

Does fructan have a functional role in physiological traits? Investigation by quantitative trait locus mapping

* The role of fructan in growth and drought-stress responses of perennial ryegrass (Lolium perenne) was investigated in an F(2) mapping family that segregates for carbohydrate metabolism. * A quantitative trait locus approach was used to compare the genetic control of traits. * Growth and drought-stress traits were extremely variable within the family. Most traits had high broad-sense heritability. Quantitative trait loci (QTL) were identified for most traits; the maximum number of QTL per trait was four. Between 11% and 75% of total phenotypic variation was explained. Few growth-trait QTL coincided with previously identified fructan QTL. A cluster of drought-trait QTL was close to two previously identified regions of the genome with tiller base fructan QTL in repulsion. * The high sugar parent contributed few alleles that increased 'reserve-driven' growth or performance during drought-stress. Correlation of growth and drought-stress traits with fructan content was low and increasing fructan content per se would not appear to improve drought resistance. Complex patterns of carbohydrate partitioning and metabolism within the cell may explain contradictory relationships between carbohydrate content and growth/stress-resistance traits.     

Advances in QTL mapping in pigs

Over the past 15 years advances in the porcine genetic linkage map and discovery of useful candidate genes have led to valuable gene and trait information being discovered. Early use of exotic breed crosses and now commercial breed crosses for quantitative trait loci (QTL) scans and candidate gene analyses have led to 110 publications which have identified 1,675 QTL. Additionally, these studies continue to identify genes associated with economically important traits such as growth rate, leanness, feed intake, meat quality, litter size, and disease resistance. A well developed QTL database called PigQTLdb is now as a valuable tool for summarizing and pinpointing in silico regions of interest to researchers. The commercial pig industry is actively incorporating these markers in marker-assisted selection along with traditional performance information to improve traits of economic performance. The long awaited sequencing efforts are also now beginning to provide sequence available for both comparative genomics and large scale single nucleotide polymorphism (SNP) association studies. While these advances are all positive, development of useful new trait families and measurement of new or underlying traits still limits future discoveries. A review of these developments is presented.     

Molecular-marker analysis of quantitative traits for growth and development in juvenile apple trees

Random amplified polymorphic DNAs (RAPDs) were used in combination with a double pseudo-testcross mapping strategy to estimate the position and effects of quantitative trait loci (QTLs) for traits influencing juvenile tree growth and development in two apple cultivars. The mapping population consisted of 172 F₁ trees from a cross between the columnar mutant ‘Wijcik McIntosh’ and a standard form disease-resistant selection NY 75441-58. Significant associations were found between markers and height increment, internode number, internode length, base diameter increment, base diameter after 9 years of growth, branch number, and leaf break. The number of genomic regions associated with each trait varied from one to eight. The amount of variation explained by linear regression on individual marker loci (R²) ranged from 3.9 to 24.3%, with an average of 7%. Multiple regression using markers for each putative QTL explained from 6.6 to 41.6% of the phenotypic variation, with an average value of 24.3%. A large number of traits had significant variation associated with the map position of the dominant columnar gene, Co. QTL stability over years was estimated by comparing the locations of putative QTLs for traits measured in multiple years. The majority of genomic regions were associated with a trait in only a single year, although regions associated with a trait in more than 1 year were also detected. The limitations of dominant markers and an outbred mapping pedigree for QTL analysis are discussed. Received: 27 August 1997 / Accepted: 10 February 1998     

A potato molecular-function map for carbohydrate metabolism and transport

Molecular-linkage maps based on functional gene markers (molecular-function maps) are the prerequisite for a candidate-gene approach to identify genes responsible for quantitative traits at the molecular level. Genetic linkage between a quantitative trait locus (QTL) and a candidate-gene locus is observed when there is a causal relationship between alleles of the candidate gene and the QTL effect. Functional gene markers can also be used for marker-assisted selection and as anchors for structural and functional comparisons between distantly related plant species sharing the same metabolic pathways. A first molecular-function map with 85 loci was constructed in potato based on 69 genes. Priority was given to genes operating in carbohydrate metabolism and transport. Public databases were searched for genes of interest from potato, tomato, or other plant species. DNA sequence information was used to develop PCR-based marker assays that allowed the localization of corresponding potato genes on existing RFLP linkage maps. Comparing the molecular-function map for genes operating in carbohydrate metabolism and transport with a QTL map for tuber starch content indicates a number of putative candidate genes for this important agronomic trait. Received: 19 March 2000 / Accepted: 16 May 2000     

玉米和水稻重要性状QTL的比较研究

在构建玉米分子标记连锁图和对重要性状进行QTL定位的基础上,以玉米和水稻的分子标记比较图谱为桥梁,分析了控制玉米和水稻F2：3群体重要农艺和产量性状QTL的共线性关系。研究结果表明：在玉米和水稻共线性的染色体区段,控制玉米株高、行数和行粒数的QTL与控制水稻株高、单株有效穗和每穗实粒数的QTL存在广泛的对应关系;在已定位的影响玉米株高等5个性状的45个QTL中,有16个与水稻“汕优63”群体中5个相同或相似性状所定位的38个QTL中的12个具有共线性关系。这一结果为利用水稻的基因组数据来定位、分离和克隆玉米重要性状的QTL提供了有益信息。同时发现,控制水稻某一个性状的QTL常常与控制玉米同一性状的两个QTL相对应,这一结果为玉米染色体是由水稻染色体加倍而来的理论假设提供了支持。研究还发现,不管是玉米还是水稻在染色体上都存在QTL的富集区域,而这些富集区域常常存在于相同的共线性区域,暗示着玉米和水稻控制相同或相似性状的QTL可能有着相同的起源。基于性状的比较基因组研究不但有助于新基因或QTL的发现、克隆和利用,同时还有助于研究不同物种间染色体的演变和进化规律。     

Pleiotropic patterns of quantitative trait loci for 70 murine skeletal traits

Quantitative trait locus (QTL) studies of a skeletal trait or a few related skeletal components are becoming commonplace, but as yet there has been no investigation of pleiotropic patterns throughout the skeleton. We present a comprehensive survey of pleiotropic patterns affecting mouse skeletal morphology in an intercross of LG/J and SM/J inbred strains (N = 1040), using QTL analysis on 70 skeletal traits. We identify 798 single-trait QTL, coalescing to 105 loci that affect on average 7-8 traits each. The number of traits affected per locus ranges from only 1 trait to 30 traits. Individual traits average 11 QTL each, ranging from 4 to 20. Skeletal traits are affected by many, small-effect loci. Significant additive genotypic values average 0.23 standard deviation (SD) units. Fifty percent of loci show codominance with heterozygotes having intermediate phenotypic values. When dominance does occur, the LG/J allele tends to be dominant to the SM/J allele (30% vs. 8%). Over- and underdominance are relatively rare (12%). Approximately one-fifth of QTL are sex specific, including many for pelvic traits. Evaluating the pleiotropic relationships of skeletal traits is important in understanding the role of genetic variation in the growth and development of the skeleton.