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Results for “QTL mapping”

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PubMed2000

Analysing complex genetic traits with chromosome substitution strains.

Many valuable animal models of human disease are known and new models are continually being generated in existing inbred strains,. Some disease models are simple mendelian traits, but most have a polygenic basis. The current approach to identifying quantitative trait loci (QTLs) that underlie such traits is to localize them in crosses, construct congenic strains carrying individual QTLs, and finally map and clone the genes. This process is time-consuming and expensive, requiring the genotyping of large crosses and many generations of breeding. Here we describe a different approach in which a panel of chromosome substitution strains (CSSs) is used for QTL mapping. Each of these strains has a single chromosome from the donor strain substituting for the corresponding chromosome in the host strain. We discuss the construction, applications and advantages of CSSs compared with conventional crosses for detecting and analysing QTLs, including those that have weak phenotypic effects.

Animals↗

PubMed2006

Interval mapping of quantitative trait loci for time-to-event data with the proportional hazards mixture cure model.

Interval mapping using normal mixture models has been an important tool for analyzing quantitative traits in experimental organisms. When the primary phenotype is time-to-event, it is natural to use survival models such as Cox's proportional hazards model instead of normal mixtures to model the phenotype distribution. An extra challenge for modeling time-to-event data is that the underlying population may consist of susceptible and nonsusceptible subjects. In this article, we propose a semiparametric proportional hazards mixture cure model which allows missing covariates. We discuss applications to quantitative trait loci (QTL) mapping when the primary trait is time-to-event from a population of mixed susceptibility. This model can be used to characterize QTL effects on both susceptibility and time-to-event distribution, and to estimate QTL location. The model can naturally incorporate covariate effects of other risk factors. Maximum likelihood estimates for the parameters in the model as well as their corresponding variance estimates can be obtained numerically using an EM-type algorithm. The proposed methods are assessed by simulations under practical settings and illustrated using a real data set containing survival times of mice after infection with Listeria monocytogenes. An extension to multiple intervals is also discussed.

Algorithms↗

PubMed1995

A nonparametric approach for mapping quantitative trait loci.

Genetic mapping of quantitative trait loci (QTLs) is performed typically by using a parametric approach, based on the assumption that the phenotype follows a normal distribution. Many traits of interest, however, are not normally distributed. In this paper, we present a nonparametric approach to QTL mapping applicable to any phenotypic distribution. The method is based on a statistic ZW, which generalizes the nonparametric Wilcoxon rank-sum test to the situation of whole-genome search by interval mapping. We determine the appropriate significance level for the statistic ZW, by showing that its asymptotic null distribution follows an Ornstein-Uhlenbeck process. These results provide a robust, distribution-free method for mapping QTLs.

Animals↗

PubMed2006

Genetic analysis of resistance to yellow rust in hexaploid wheat using a mixture model for multiple crosses.

DNA-based molecular markers have been used in numerous studies for tagging specific genes in wheat for subsequent use in marker-assisted selection. Usually in plant breeding, procedures for mapping genes are based on analysis of a single segregating population. However, breeding programmes routinely evaluate large numbers of progeny derived from multiple-related crosses with some parental lines shared. In most such related crosses, the number of progeny is quite small. Thus, statistical techniques for detecting quantitative trait loci (QTLs) using data from conventional multi-cross breeding programmes are interesting. The objective of this study is to present a mixture model for QTL mapping in crosses of multiple inbred varieties with non-normal phenotype distributions and to use this model to map QTLs for yellow rust resistance in elite wheat breeding material. Three doubled haploid populations consisting of 41, 42 and 55 lines, respectively, originating from four parental varieties were studied. Multi-cross QTL analysis with three specific pathogen isolates of Puccinia striiformis f. sp. tritici and a mixture of the isolates revealed QTLs for resistance at four different genomic locations. These QTLs were found on chromosome 2AL, 2AS, 2BL and 6BL and explained between 21 and 41% of the phenotypic variation. Two of these QTLs, one on the long arm of chromosome 2A and one on the short arm of chromosome 2A were identical to the known yellow rust resistance genes Yr32 and Yr17, respectively, whereas the QTLs located on the long arms of chromosomes 2B and 6B may reflect types of resistance to yellow rust, which have not previously been mapped.

Basidiomycota↗

PubMed2005

Gene actions of QTLs affecting several agronomic traits resolved in a recombinant inbred rice population and two backcross populations.

To understand the types of gene action controlling seven quantitative traits in rice, we carried out quantitative trait locus (QTL) mapping in order to distinguish between the main-effect QTLs (M-QTLs) and digenic epistatic QTLs (E-QTLs) responsible for the trait performance of 254 recombinant inbred lines (RILs) from rice varieties Lemont/Teqing and two backcross hybrid (BCF1) populations derived from these RILs. We identified 44 M-QTL and 95 E-QTL pairs in the RI and BCF1 populations as having significant effects on the mean values and mid-parental heterosis of heading date, plant height, flag leaf length, flag leaf width, panicle length, spikelet number and spikelet fertility. The E-QTLs detected collectively explained a larger portion of the total phenotypic variation than the M-QTLs in both the RI and BCF1 populations. In both BCF1 populations, over-dominant (or under-dominant) loci were more important than additive and complete or partially dominant loci for M-QTLs and E-QTL pairs, thereby supporting prior findings that overdominance resulting from epistatic loci are the primary genetic basis of inbreeding depression and heterosis in rice.

Chromosome Mapping↗

PubMed2004

Limitations of a two-step moment method for mapping linked multiple QTL.

As an alternative to multiple-interval mapping a two-step moment method was recently proposed to map linked multiple quantitative trait loci (QTLs). The advantage of this moment method was supposed to be its simplicity and computational efficiency, especially in detecting closely linked QTLs within a marker bracket, but also in mapping QTLs in different marker intervals. Using simulations it is shown that the two-step moment method may give poor results compared with multiple-interval mapping, irrespective of whether the QTLs are in the same or in different marker intervals, especially if linked QTLs are in repulsion. The criteria of comparison are number of identified QTLs, likelihood ratio test statistics, means and empirical standard errors of the QTL position and QTL effects estimates, and the accuracy of the residual variance estimates. Further, the joint conditional probabilities of QTL genotypes for two putative QTLs within a marker interval were derived and compared with the unmodified approach ignoring the non-independence of the conditional probabilities.

Analysis of Variance↗

PubMed2005

A paternally imprinted QTL for mature body mass on mouse chromosome 8.

Body mass (BM) is a classic polygenic trait that has been extensively investigated to determine the underlying genetic architecture. Many previous studies looking at the genetic basis of variation in BM in murine animal models by quantitative trait loci (QTL) mapping have used crosses between two inbred lines. As a consequence it has not been possible to explore imprinting effects which have been shown to play an important role in the genetic basis of early growth with persistent effects throughout the growth curve. Here we use partially inbred mouse lines to identify QTL for mature BM by applying both Mendelian and Imprinting models. The analysis of an F2 population (n approximately 500) identified a number of QTL at 14, 16, and 18 weeks explaining in total 31.5%, 34.4%, and 30.5% of total phenotypic variation, respectively. On Chromosome 8 a QTL of large effect (14% of the total phenotypic variance at 14 weeks) was found to be explained by paternal imprinting. Although Chromosome 8 has not been previously associated with imprinting effects, features of candidate genes within the QTL confidence interval (CpG islands and direct clustered repeats) support the hypothesis that Insulin receptor substrate 2 may be associated with imprinting, but as yet is unidentified as being so.

Animals↗

PubMed1991

Mendelian factors underlying quantitative traits in tomato: comparison across species, generations, and environments.

As part of ongoing studies regarding the genetic basis of quantitative variation in phenotype, we have determined the chromosomal locations of quantitative trait loci (QTLs) affecting fruit size, soluble solids concentration, and pH, in a cross between the domestic tomato (Lycopersicon esculentum Mill.) and a closely-related wild species, L. cheesmanii. Using a RFLP map of the tomato genome, we compared the inheritance patterns of polymorphisms in 350 F2 individuals with phenotypes scored in three different ways: (1) from the F2 progeny themselves, grown near Davis, California; (2) from F3 families obtained by selfing each F2 individual, grown near Gilroy, California (F3-CA); and (3) from equivalent F3 families grown near Rehovot, Israel (F3-IS). Maximum likelihood methods were used to estimate the approximate chromosomal locations, phenotypic effects (both additive effects and dominance deviations), and gene action of QTLs underlying phenotypic variation in each of these three environments. A total of 29 putative QTLs were detected in the three environments. These QTLs were distributed over 11 of the 12 chromosomes, accounted for 4.7-42.0% of the phenotypic variance in a trait, and showed different types of gene action. Among these 29 QTLs, 4 were detected in all three environments, 10 in two environments, and 15 in only a single environment. The two California environments were most similar, sharing 11/25 (44%) QTLs, while the Israel environment was quite different, sharing 7/20 (35%) and 5/26 (19%) QTLs with the respective California environments. One major goal of QTL mapping is to predict, with maximum accuracy, which individuals will produce progeny showing particular phenotypes. Traditionally, the phenotype of an individual alone has been used to predict the phenotype of its progeny. Our results suggested that, for a trait with low heritability (soluble solids), the phenotype of F3 progeny could be predicted more accurately from the genotype of the F2 parent at QTLs than from the phenotype of the F2 individual. For a trait with intermediate heritability (fruit pH), QTL genotype and observed phenotype were about equally effective at predicting progeny phenotype. For a trait with high heritability (mass per fruit), knowing the QTL genotype of an individual added little if any predictive value, to simply knowing the phenotype. The QTLs mapped in the L. esculentum X L. cheesmanii F2 appear to be at similar locations to many of those mapped in a previous cross with a different wild tomato (L. chmielewskii).(ABSTRACT TRUNCATED AT 400 WORDS)

Biological Evolution↗

PubMed2005

Integrative genetic analysis of transcription modules: towards filling the gap between genetic loci and inherited traits.

Genetic loci that regulate inherited traits are routinely identified using quantitative trait locus (QTL) mapping methods. However, the genotype-phenotype associations do not provide information on the gene expression program through which the genetic loci regulate the traits. Transcription modules are 'self-consistent regulatory units' and are closely related to the modular components of gene regulatory network [Ihmels, J., Friedlander, G., Bergmann, S., Sarig, O., Ziv, Y. and Barkai, N. (2002) Revealing modular organization in the yeast transcriptional network. Nat. Genet., 31, 370-377; Segal, E., Shapira, M., Regev, A., Pe'er, D., Botstein, D., Koller, D. and Friedman, N. (2003) Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data. Nat. Genet., 34, 166-176]. We used genome-wide genotype and gene expression data of a genetic reference population that consists of mice of 32 recombinant inbred strains to identify the transcription modules and the genetic loci regulating them. Twenty-nine transcription modules defined by genetic variations were identified. Statistically significant associations between the transcription modules and 18 classical physiological and behavioral traits were found. Genome-wide interval mapping showed that major QTLs regulating the transcription modules are often co-localized with the QTLs regulating the associated classical traits. The association and the possible co-regulation of the classical trait and transcription module indicate that the transcription module may be involved in the gene pathways connecting the QTL and the classical trait. Our results show that a transcription module may associate with multiple seemingly unrelated classical traits and a classical trait may associate with different modules. Literature mining results provided strong independent evidences for the relations among genes of the transcription modules, genes in the regions of the QTLs regulating the transcription modules and the keywords representing the classical traits.

Animals↗

PubMed2000

Bias and Sampling Error of the Estimated Proportion of Genotypic Variance Explained by Quantitative Trait Loci Determined From Experimental Data in Maize Using Cross Validation and Validation With Independent Samples.

Cross validation (CV) was used to analyze the effects of different environments and different genotypic samples on estimates of the proportion of genotypic variance explained by QTL (p). Testcrosses of 344 F(3) maize lines grown in four environments were evaluated for a number of agronomic traits. In each of 200 replicated CV runs, this data set was subdivided into an estimation set (ES) and various test sets (TS). ES were used to map QTL and estimate p for each run (p(ES)) and its median (p(ES)) across all runs. The bias of these estimates was assessed by comparison with the median (p(TS.ES)) obtained from TS. We also used two independent validation samples derived from the same cross for further comparison. The median p(ES) showed a large upward bias compared to p(TS.ES). Environmental sampling generally had a smaller effect on the bias of p(ES) than genotypic sampling or both factors simultaneously. In independent validation, p(TS.ES) was on average only 50% of p(ES). A wide range among p(ES) reflected a large sampling error of these estimates. QTL frequency distributions and comparison of estimated QTL effects indicated a low precision of QTL localization and an upward bias in the absolute values of estimated QTL effects from ES. CV with data from three QTL studies reported in the literature yielded similar results as those obtained with maize testcrosses. We therefore recommend CV for obtaining asymptotically unbiased estimates of p and consequently a realistic assessment of the prospects of MAS.

Journal Article↗

PubMed2003

Mapping quantitative trait loci associated with resistance to coccidiosis and growth.

To map QTL associated with disease resistance to avian coccidiosis and growth, two commercial broiler lines with different degrees of resistance to the disease were crossed to generate an F1 generation that was intercrossed to produce 314 F2 generation offspring. The F2 offspring were inoculated with sporulated oocysts of Eimeria maxima. Five disease-associated phenotypes were measured after the infection. Intertrait comparisons revealed that oocyst shedding was a good parameter for evaluating disease resistance or susceptibility. One hundred nineteen microsatellite markers, covering 80% of the chicken genome with an average marker interval of 25 cM, were used for genotyping of F1 parents and F2 offspring. Statistical analysis based on the data of four families revealed a locus on chromosome 1 associated with oocyst shedding (logarithm of odds = 3.46). The genetic mechanism of this locus appeared additive. The genomic scan also identified three potential growth QTL on chromosomes 1, 6, and 8. These results provide the foundation for further investigation to validate the QTL.

Animals↗

PubMed2005

Genomic mapping of direct and correlated responses to long-term selection for rapid growth rate in mice.

Understanding the genetic architecture of traits such as growth, body composition, and energy balance has become a primary focus for biomedical and agricultural research. The objective of this study was to map QTL in a large F(2) (n = 1181) population resulting from an intercross between the M16 and ICR lines of mice. The M16 line, developed by long-term selection for 3- to 6-week weight gain, is larger, heavier, fatter, hyperphagic, and diabetic relative to its randomly selected control line of ICR origin. The F(2) population was phenotyped for growth and energy intake at weekly intervals from 4 to 8 weeks of age and for body composition and plasma levels of insulin, leptin, TNFalpha, IL6, and glucose at 8 weeks and was genotyped for 80 microsatellite markers. Since the F(2) was a cross between a selection line and its unselected control, the QTL identified likely represent genes that contributed to direct and correlated responses to long-term selection for rapid growth rate. Across all traits measured, 95 QTL were identified, likely representing 19 unique regions on 13 chromosomes. Four chromosomes (2, 6, 11, and 17) harbored loci contributing disproportionately to selection response. Several QTL demonstrating differential regulation of regional adipose deposition and age-dependent regulation of growth and energy consumption were identified.

Animals↗

PubMed2006

Genetic analyses and mapping of a new thermo-sensitive genic male sterile gene in maize.

The present study describes a novel thermo-sensitive genic male sterile (TGMS) line, Qiong68ms. To analyse the mode of fertility inheritance and tag the TGMS gene, a set of F2, BC1 and F(2:3) populations derived from a cross between Qiong68ms and K12 were evaluated for a period of 2 years. Classical genetic analyses and QTL mapping using the mean restoration percentage of the F(2:3) populations revealed that the fertility of Qiong68ms was likely to be governed by a single recessive gene, which was named tms3; the tms3 gene was mapped to a location between SSR markers umc2129 and umc1041, at a distance of 3.7 cM form umc2129 and 1.5 cM form umc1041. The molecular markers tightly linked with tms3 gene will aid in the transfer of the TGMS gene to various background inbred lines using the MAS method.

Chromosome Mapping↗

PubMed2006

A genetic and cytogenetic map for the duck (Anas platyrhynchos).

A genetic linkage map for the duck (Anas platyrhynchos) was developed within a cross between two extreme Peking duck lines by linkage analysis of 155 polymorphic microsatellite markers, including 84 novel markers reported in this study. A total of 115 microsatellite markers were placed into 19 linkage groups. The sex-averaged map spans 1353.3 cM, with an average interval distance of 15.04 cM. The male map covers 1415 cM, whereas the female map covers only 1387.6 cM. All of the flanking sequences of the 155 polymorphic loci--44 monomorphic loci and a further 41 reported microsatellite loci for duck--were blasted against the chicken genomic sequence, and corresponding orthologs were found for 49. To integrate the genetic and cytogenetic map of the duck genome, 28 BAC clones were screened from a chicken BAC library using the specific PCR primers and localized to duck chromosomes by FISH, respectively. Of 28 BAC clones, 24 were detected definitely on duck chromosomes. Thus, 11 of 19 linkage groups were localized to 10 duck chromosomes. This genetic and cytogenetic map will be helpful for the mapping QTL in duck for breeding applications and for conducting genomic comparisons between chicken and duck.

Animals↗

PubMed2005

Bayesian analysis of quantitative trait loci for boar taint in a Landrace outbred population.

The genetic basis of the main components of boar taint was investigated in intact male pigs in a commercial population. We analyzed fat androsten-one and skatole concentrations from 217 males of an outbred Landrace population. Records were normalized using a logarithm transformation and tested for normality using a Wilk-Shapiro test. Bayesian analysis was then used to map QTL in 10 candidate regions previously selected on chromosomes 1, 2, 3, 4, 6, 7, 8, 9, 10, and 13. The criterion for QTL detection was the Bayes factor (BF) between polygenic models with and without QTL effects. Both traits had considerable genetic determination, with posterior means of total heritabilities ranging from 0.59 to 0.73 for androstenone and from 0.74 to 0.89 for skatole. Positive evidence for a fat skatole QTL was detected on SSC6 (BF = 5.16); however, no QTL for androstenone were found in any of the 10 chromosomal regions analyzed. With the detection of a QTL for the fat skatole concentration segregating in this population, marker-assisted selection or even gene-assisted selection could be used once the causal mutation of the QTL was identified.

Adipose Tissue↗

PubMed2001

[QTL analysis for epistatic effects and QTL x environment interaction effects on final height of rice (Oryza sativa L.)].

QTLs with epistatic effects and environmental interaction effects for final height of rice were studied by mixed-model based QTL mapping with a doubled haploid population from IR64/Azucena in four environments. The results demonstrated the importance of epistasis as a genetic basis of the quantitative traits and also revealed several important features of this phenomenon. In the results, 100 per cent of QTLs were involved in epistasis, of which 64 per cent were found with significant additive effects. This might mean that the usual estimates of the QTL additive effects could be confounded by epistatic interactions and result in biased estimation unless epistatic effect is separated. The other 36 per cent did not have any significant additive effects of their own but were involved in 48 per cent of the identified epistatic interactions. Such loci might play the role of modifying agents that tend to activate other loci or modify the action of other loci. The other features of epistasis include as follows: it was fairly common for the same locus to get involved in interactions with more than one locus; the QTLs with relatively high magnitude of effects might also be involved in epistasis; and epistasis was sensitive to environmental interactions for their expression. QTL x environment (QE) interaction effects were detected more often than QTL main effects for plant height behavior, as might indicate that gene expression could be greatly affected by environments.

Chromosome Mapping↗

PubMed2006

Molecular genetic analysis of five spike-related traits in wheat using RIL and immortalized F2 populations.

Kernel number per spike is one of the most important yield components of wheat. To map QTLs related to kernel number including spike length (SPL), spikelet number per spike (SPN), fertile spikelet number (FSPN), sterile spikelet number (SSPN) and compactness, and to characterize the inheritance modes of the QTLs and two-locus interactions, 136 recombinant inbred lines (RILs) derived from 'Nanda2419' x 'Wangshuibai' and an immortalized F(2 )population (IF(2)) generated by randomly permutated intermating of these RILs were investigated. QTL mapping made use of the previously constructed over 3300 cM linkage map of the RIL population. Three, five, two, two and six chromosome regions were identified, respectively, for their association with SPL, SPN, FSPN, SSPN, and compactness in at least two of the three environments examined. All compactness QTLs but one shared the respective intervals of QSpn.nau-5A and the SPL QTLs. Xcfd46-Xwmc702 interval on chromosome 7D was related to all traits but SSPN and had consistently the largest effects. The fact that not all the compactness QTL intervals were related to both SPL and SPN indicates that compactness is regulated by different mechanisms. Interval coincidence between QTLs of SPL and SPN and between QTLs of FSPN and SSPN was minimal. For all the traits, favorable alleles exist in both parents. Inheritance modes from additiveness to overdominance of the QTLs were revealed and two-locus interactions were detected, implying that the traits studied are under complex genetic control. The results could contribute to wheat yield improvement and better use of Wangshuibai and Nanda2419 the two special germplasms in wheat breeding program.

Chromosome Mapping↗

PubMed2005

Genetic basis of drought resistance at reproductive stage in rice: separation of drought tolerance from drought avoidance.

Drought tolerance (DT) and drought avoidance (DA) are two major mechanisms in drought resistance of higher plants. In this study, the genetic bases of DT and DA at reproductive stage in rice were analyzed using a recombinant inbred line population from a cross between an indica lowland and a tropical japonica upland cultivar. The plants were grown individually in PVC pipes and two cycles of drought stress were applied to individual plants with unstressed plants as the control. A total of 21 traits measuring fitness, yield, and the root system were investigated. Little correlation of relative yield traits with potential yield, plant size, and root traits was detected, suggesting that DT and DA were well separated in the experiment. A genetic linkage map consisting of 245 SSR markers was constructed for mapping QTL for these traits. A total of 27 QTL were resolved for 7 traits of relative performance of fitness and yield, 36 QTL for 5 root traits under control, and 38 for 7 root traits under drought stress conditions, suggesting the complexity of the genetic bases of both DT and DA. Only a small portion of QTL for fitness- and yield-related traits overlapped with QTL for root traits, indicating that DT and DA had distinct genetic bases.

Analysis of Variance↗