A unified statistical model for functional mapping of environment-dependent genetic expression and genotype x environment interactions for ontogenetic development

The effects of quantitative trait loci (QTL) on phenotypic development may depend on the environment (QTL x environment interaction), other QTL (genetic epistasis), or both. In this article, we present a new statistical model for characterizing specific QTL that display environment-dependent genetic expressions and genotype x environment interactions for developmental trajectories. Our model was derived within the maximum-likelihood-based mixture model framework, incorporated by biologically meaningful growth equations and environment-dependent genetic effects of QTL, and implemented with the EM algorithm. With this model, we can characterize the dynamic patterns of genetic effects of QTL governing growth curves and estimate the global effect of the underlying QTL during the course of growth and development. In a real example with rice, our model has successfully detected several QTL that produce differences in their genetic expression between two contrasting environments. These detected QTL cause significant genotype x environment interactions for some fundamental aspects of growth trajectories. The model provides the basis for deciphering the genetic architecture of trait expression adjusted to different biotic and abiotic environments and genetic relationships for growth rates and the timing of life-history events for any organism.     

Combined analyses of data from quantitative trait loci mapping studies. Chromosome 4 effects on porcine growth and fatness

For many species several similar QTL mapping populations have been produced and analyzed independently. Joint analysis of such data could be used to increase power to detect QTL and evaluate population differences. In this study, data were collated on almost 3000 pigs from seven different F(2) crosses between Western commercial breeds and either the European wild boar or the Chinese Meishan breed. Genotypes were available for 31 markers on chromosome 4 (on average 8.3 markers per population). Data from three traits common to all populations (birth weight, mean backfat depth at slaughter or end of test, and growth rate from birth to slaughter or end of test) were analyzed for individual populations and jointly. A QTL influencing birth weight was detected in one individual population and in the combined data, with no significant interaction of the QTL effect with population. A QTL affecting backfat that had a significantly greater effect in wild boar than in Meishan crosses was detected. Some evidence for a QTL affecting growth rate was detected in all populations, with no significant differences between populations. This study is the largest F(2) QTL analysis achieved in a livestock species and demonstrates the potential of joint analysis.     

Characterization of a major X-linked quantitative trait locus influencing body weight of mice

Growth rate in mice is an archetypal quantitative trait that has long been studied genetically, physiologically, and metabolically, but its genetic basis is still poorly understood due to its complex inheritance and the influence of environment. We measured differences in 17 growth-related traits between a pair of partially congenic lines that differ for a segment of the X chromosome containing a quantitative trait locus (QTL) that we identified in a genomewide QTL scan. The QTL has a large effect on mean body weight of approximately 20% at all ages, and affects early growth rate to a greater extent than late growth rate. Feed is converted to body mass more efficiently in the high chromosome segment-bearing line than the low line. The weights of various internal organs are affected to a somewhat greater extent by the QTL than body weight. The proportional change in body length is smaller than body weight, but this may be an effect of scale. Body weight at late ages appears to allow the most efficient detection of allelic differences at the QTL, although assignment of genotypic state based on phenotype is never unambiguous.     

A QTL study of growth and body shape in the inter-species hybrid of Père David's deer (Elaphurus davidianus) and red deer (Cervus elaphus)

An interspecies deer hybrid resource population developed from a cross of Père David's and red deer was used to detect QTL that account for species differences. A genome scan, coupled with composite interval mapping, was conducted to search for QTL controlling body measurements at pre-pubescent age (6 months of age) and puberty (15 months of age) in this interspecies hybrid. Five linkage groups that harbour QTL affecting morphology were identified. A joint-traits analysis was used to search for putative pleiotropic QTL on four of these linkage groups, and three were significantly associated with pleiotropic QTL for nose width and foot length (metacarpal and phalanges), which collectively accounted for 29-58% of the phenotypic difference between the two deer species. This study suggests that a few loci with large pleiotropic effects may be responsible for species-specific differences in growth and structure-related traits.     

Mapping phenotypic plasticity and genotype-environment interactions affecting life-history traits in Caenorhabditis elegans

Phenotypic plasticity and genotype-environment interactions (GEI) play an important role in the evolution of life histories. Knowledge of the molecular genetic basis of plasticity and GEI provides insight into the underlying mechanisms of life-history changes in different environments. We used a genomewide single-nucleotide polymorphism map in a recombinant N2 x CB4856 inbred panel of the nematode Caenorhabditis elegans to study the genetic control of phenotypic plasticity to temperature in four fitness-related traits, that is, age at maturity, fertility, egg size and growth rate. We mapped quantitative trait loci (QTL) for the respective traits at 12 and 24 degrees C, as well as their plasticities. We found genetic variation and GEI for age at maturity, fertility, egg size and growth rate. GEI in fertility and egg size was attributed to changes in rank order of reaction norms. In case of age at maturity and growth rate, GEI was caused mainly by differences in the among-line variance. In total, 11 QTLs were detected, five QTL at 12 degrees C and six QTL at 24 degrees C, which were associated with life-history traits. Five QTL associated with age at maturity, fertility and growth rate showed QTL x environment interaction. These colocalized with plasticity QTL for the respective traits suggesting allelic sensitivity to temperature. Further fine mapping, complementation analyses and gene silencing are planned to identify candidate genes underlying phenotypic plasticity for age at maturity, fertility and growth.     

Combined line-cross and half-sib QTL analysis of crosses between outbred lines

Data from an F 2 cross between breeds of livestock are typically analysed by least squares line-cross or half-sib models to detect quantitative trait loci (QTL) that differ between or segregate within breeds. These models can also be combined to increase power to detect QTL, while maintaining the computational efficiency of least squares. Tests between models allow QTL to be characterized into those that are fixed (LC QTL), or segregating at similar (HS QTL) or different (CB QTL) frequencies in parental breeds. To evaluate power of the combined model, data wih various differences in QTL allele frequencies (FD) between parental breeds were simulated. Use of all models increased power to detect QTL. The line-cross model was the most powerful model to detect QTL for FD>0.6. The combined and half-sib models had similar power for FD<0.4. The proportion of detected QTL declared as LC QTL decreased with FD. The opposite was observed for HS QTL. The proportion of CB QTL decreased as FD deviated from 0.5. Accuracy of map position tended to be greatest for CB QTL. Models were applied to a cross of Berkshire and Yorkshire pig breeds and revealed 160 (40) QTL at the 5% chromosome (genome)-wise level for the 39 growth, carcass composition and quality traits, of which 72, 54, and 34 were declared as LC, HS and CB QTL. Fourteen CB QTL were detected only by the combined model. Thus, the combined model can increase power to detect QTL and mapping accuracy and enable characterization of QTL that segregate within breeds.     

Genetics of species differences in the wild annual sunflowers, Helianthus annuus and H. petiolaris

Much of our knowledge of speciation genetics stems from quantitative trait locus (QTL) studies. However, interpretations of the size and distribution of QTL underlying species differences are complicated by differences in the way QTL magnitudes are estimated. Also, many studies fail to exploit information about QTL directions or to compare inter- and intraspecific QTL variation. Here, we comprehensively analyze an extensive QTL data set for an interspecific backcross between two wild annual sunflowers, Helianthus annuus and H. petiolaris, interpret different estimates of QTL magnitudes, identify trait groups that have diverged through selection, and compare inter- and intraspecific QTL magnitudes. Our results indicate that even minor QTL (in terms of backcross variance) may be surprisingly large compared to levels of standing variation in the parental species or phenotypic differences between them. Morphological traits, particularly flower morphology, were more strongly or consistently selected than life history or physiological traits. Also, intraspecific QTL were generally smaller than interspecific ones, consistent with the prediction that larger QTL are more likely to spread to fixation across a subdivided population. Our results inform the genetics of species differences in Helianthus and suggest an approach for the simultaneous mapping of inter- and intraspecific QTL.     

Quantitative trait loci for early plant vigour of maize grown in chilly environments

Maize (Zea mays L.) is particularly sensitive to chilling in the early growth stages. The objective of this study was to determine quantitative trait loci (QTL) for early plant vigour of maize grown under cool and moderately warm conditions in Central Europe. A population of 720 doubled haploid (DH) lines was derived from a cross between two dent inbred lines contrasting in early vigour and were genotyped with 188 SSR markers. The DH lines per se and their testcrosses with a flint line were evaluated in field experiments across 11 environments in 2001 and 2002. Plants were harvested after six to eight leaves had been fully developed to assess fresh matter yield as a criterion of early vigour. Seven QTL were detected for line performance and ten QTL for testcross performance, explaining 64 and 49% of the genetic variance. Six out of seven QTL detected in the lines per se were also significant in their testcrosses. Significant QTL × environment interaction was observed, but no relationship existed between the size of the QTL effects and the mean temperature in the individual environment. The correlation between fresh matter yield and days to silking was non-significant, indicating that differences in early plant vigour were not simply caused by maturity differences. For three additional chilling-related traits, leaf chlorosis, leaf purpling, and frost damage seven, six, and five QTL were detected, respectively. Three QTL for leaf chlorosis, two for leaf purpling, and two for frost damage co-localized with QTL for fresh matter yield. Results are considered as a reliable basis for further genetic, molecular, and physiological investigations.     

Age-dependent quantitative trait loci affecting growth traits in Scottish Blackface sheep

To dissect age-dependent quantitative trait loci (QTL) associated with growth and to examine changes in QTL effects over time, the Gompertz growth model was fitted to longitudinal live weight data on 788 Scottish Blackface lambs from nine half-sib families. QTL were mapped for model parameters and weekly live weights and growth rates using microsatellite markers on chromosomes 1, 2, 3, 5, 14, 18, 20 and 21. QTL significance (using α = 0.05 chromosome-wide significance thresholds, unless otherwise stated) varied with age, and those for growth rate occurred earlier than equivalent QTL for live weight. A chromosome 20 QTL for growth rate was significant from 4 to 9 weeks (maximum significance at 6 weeks) and for maximum growth rate. For live weight, this QTL was significant from 8 to 16 weeks (maximum significance at 12 weeks). A nominally significant chromosome 14 QTL was detected for growth rates from birth to week 2 in the same families and location as an 8-week weight QTL. In addition, at the same position on chromosome 14, a QTL was significant for growth rate for 17–28 weeks (maximum significance at 24 weeks). A chromosome 3 QTL was significant for weights at early ages (birth to week 4) and a growth rate QTL on chromosome 18 was significant from 8 to 12 weeks. Fitting growth curves allowed the combination of information from multiple measurements into a few biologically meaningful variables, and the detection of growth QTL that were not observed from analyses of raw weight data. These QTL describe distinct parts of an animal's growth curve trajectory, possibly enabling manipulation of this trajectory.     

Habitat-specific natural selection at a flowering-time QTL is a main driver of local adaptation in two wild barley populations

Understanding the genetic basis of local adaptation requires insight in the fitness effects of individual loci under natural field conditions. While rapid progress is made in the search for genes that control differences between plant populations, it is typically unknown whether the genes under study are in fact key targets of habitat-specific natural selection. Using a quantitative trait loci (QTL) approach, we show that a QTL associated with flowering-time variation between two locally adapted wild barley populations is an important determinant of fitness in one, but not in the other population's native habitat. The QTL mapped to the same position as a habitat-specific QTL for field fitness that affected plant reproductive output in only one of the parental habitats, indicating that the genomic region is under differential selection between the native habitats. Consistent with the QTL results, phenotypic selection of flowering time differed between the two environments, whereas other traits (growth rate and seed weight) were under selection but experienced no habitat-specific differential selection. This implies the flowering-time QTL as a driver of adaptive population divergence. Our results from phenotypic selection and QTL analysis are consistent with local adaptation without genetic trade-offs in performance across environments, i.e. without alleles or traits having opposing fitness effects in contrasting environments.     

Detection and stability of quantitative trait loci (QTL) in Eucalyptus globulus

Eucalyptus globulus Labill. ssp. globulus is an important tree species for the pulp and paper industry, and several breeding programmes throughout the world are striving to improve key traits such as growth and wood density. This study aimed to detect quantitative trait loci (QTL) for growth, wood density, relative bark thickness and early flowering in a single full-sib E. globulus family grown across seven sites. Growth was measured a number of times over a 6-year period, enabling temporal stability of growth QTL to be studied. Ten putative QTL (LOD > 2.0) were detected in the single family, which was of moderate size. Based on permutations of the trait data, six of these QTL were significant at the experimentwise significance level of 0.1 for at least one of the four models implemented in analysis to remove site effects. For wood density, two putative QTL explained 20% of the variance for the trait, indicating that a small number of QTL might explain a reasonable proportion of the trait variance. One of these QTL was found to be independent of QTL for growth whereas the second QTL co-segregated with a QTL for relative incremental growth. The marker nearest to this QTL was associated with fast growth but low wood density. A putative growth QTL at year 6 was found to be relatively stable across ages. In addition, it was found that residuals from models based on measurements from across all families across all sites in the trial detected QTL with greater experimentwise significance.     

Quantitative trait loci with additive effects on growth and carcass traits in a Wagyu-Limousin F2 population

A whole-genome scan for carcass traits [average daily gain during the pre-weaning, growth and finishing periods; birth weight; hot carcass weight and longissimus muscle area (LMA)] was performed on 328 F(2) progeny produced from Wagyu x Limousin-cross parents derived from eight founder Wagyu bulls. Nine significant (P 相似文献   

Complex Genetic Effects on Early Vegetative Development Shape Resource Allocation Differences Between Arabidopsis lyrata Populations

Costs of reproduction due to resource allocation trade-offs have long been recognized as key forces in life history evolution, but little is known about their functional or genetic basis. Arabidopsis lyrata, a perennial relative of the annual model plant A. thaliana with a wide climatic distribution, has populations that are strongly diverged in resource allocation. In this study, we evaluated the genetic and functional basis for variation in resource allocation in a reciprocal transplant experiment, using four A. lyrata populations and F₂ progeny from a cross between North Carolina (NC) and Norway parents, which had the most divergent resource allocation patterns. Local alleles at quantitative trait loci (QTL) at a North Carolina field site increased reproductive output while reducing vegetative growth. These QTL had little overlap with flowering date QTL. Structural equation models incorporating QTL genotypes and traits indicated that resource allocation differences result primarily from QTL effects on early vegetative growth patterns, with cascading effects on later vegetative and reproductive development. At a Norway field site, North Carolina alleles at some of the same QTL regions reduced survival and reproductive output components, but these effects were not associated with resource allocation trade-offs in the Norway environment. Our results indicate that resource allocation in perennial plants may involve important adaptive mechanisms largely independent of flowering time. Moreover, the contributions of resource allocation QTL to local adaptation appear to result from their effects on developmental timing and its interaction with environmental constraints, and not from simple models of reproductive costs.     

Detection of quantitative trait loci for growth- and fatness-related traits in a large-scale White Duroc × Erhualian intercross pig population

Growth and fatness are economically important traits in pigs. In this study, a genome scan was performed to detect quantitative trait loci (QTL) for 14 growth and fatness traits related to body weight, backfat thickness and fat weight in a large-scale White Duroc × Erhualian F(2) intercross. A total of 76 genome-wide significant QTL were mapped to 16 chromosomes. The most significant QTL was found on pig chromosome (SSC) 7 for fatness with unexpectedly small confidence intervals of ～2 cM, providing an excellent starting point to identify causal variants. Common QTL for both fatness and growth traits were found on SSC4, 5, 7 and 8, and shared QTL for fat deposition were detected on SSC1, 2 and X. Time-series analysis of QTL for body weight at six growth stages revealed the continuously significant effects of the QTL on SSC4 at the fattening period and the temporal-specific expression of the QTL on SSC7 at the foetus and fattening stages. For fatness traits, Chinese Erhualian alleles were associated with increased fat deposition except that at the major QTL on SSC7. For growth traits, most of White Duroc alleles enhanced growth rates except for those at three significant QTL on SSC6, 7 and 9. The results confirmed many previously reported QTL and also detected novel QTL, revealing the complexity of the genetic basis of growth and fatness in pigs.     

On the differences between maximum likelihood and regression interval mapping in the analysis of quantitative trait loci

The differences between maximum-likelihood (ML) and regression (REG) interval mapping in the analysis of quantitative trait loci (QTL) are investigated analytically and numerically by simulation. The analytical investigation is based on the comparison of the solution sets of the ML and REG methods in the estimation of QTL parameters. Their differences are found to relate to the similarity between the conditional posterior and conditional probabilities of QTL genotypes and depend on several factors, such as the proportion of variance explained by QTL, relative QTL position in an interval, interval size, difference between the sizes of QTL, epistasis, and linkage between QTL. The differences in mean squared error (MSE) of the estimates, likelihood-ratio test (LRT) statistics in testing parameters, and power of QTL detection between the two methods become larger as (1) the proportion of variance explained by QTL becomes higher, (2) the QTL locations are positioned toward the middle of intervals, (3) the QTL are located in wider marker intervals, (4) epistasis between QTL is stronger, (5) the difference between QTL effects becomes larger, and (6) the positions of QTL get closer in QTL mapping. The REG method is biased in the estimation of the proportion of variance explained by QTL, and it may have a serious problem in detecting closely linked QTL when compared to the ML method. In general, the differences between the two methods may be minor, but can be significant when QTL interact or are closely linked. The ML method tends to be more powerful and to give estimates with smaller MSEs and larger LRT statistics. This implies that ML interval mapping can be more accurate, precise, and powerful than REG interval mapping. The REG method is faster in computation, especially when the number of QTL considered in the model is large. Recognizing the factors affecting the differences between REG and ML interval mapping can help an efficient strategy, using both methods in QTL mapping to be outlined.     

Complex traits analysis of chicken growth using targeted genetical genomics

Dissecting the genetic control of complex trait variation remains very challenging, despite many advances in technology. The aim of this study was to use a major growth quantitative trait locus (QTL) in chickens mapped to chromosome 4 as a model for a targeted approach to dissect the QTL. We applied a variant of the genetical genomics approach to investigate genome-wide gene expression differences between two contrasting genotypes of a marked QTL. This targeted approach allows the direct quantification of the link between the genotypes and the genetic responses, thus narrowing the QTL-phenotype gap using fewer samples (i.e. microarrays) compared with the genome-wide genetical genomics studies. Four differentially expressed genes were localized under the region of the QTL. One of these genes is a potential positional candidate gene (AADAT) that affects lysine and tryptophan metabolism and has alternative splicing variants between the two genotypes. In addition, the lysine and glycolysis metabolism pathways were significantly enriched for differentially expressed genes across the genome. The targeted approach provided a complementary route to fine mapping of QTL by characterizing the local and the global downstream effects of the QTL and thus generating further hypotheses about the action of that QTL.     

Paths to selection on life history loci in different natural environments across the native range of Arabidopsis thaliana

Selection on quantitative trait loci (QTL) may vary among natural environments due to differences in the genetic architecture of traits, environment‐specific allelic effects or changes in the direction and magnitude of selection on specific traits. To dissect the environmental differences in selection on life history QTL across climatic regions, we grew a panel of interconnected recombinant inbred lines (RILs) of Arabidopsis thaliana in four field sites across its native European range. For each environment, we mapped QTL for growth, reproductive timing and development. Several QTL were pleiotropic across environments, three colocalizing with known functional polymorphisms in flowering time genes (CRY2, FRI and MAF2‐5), but major QTL differed across field sites, showing conditional neutrality. We used structural equation models to trace selection paths from QTL to lifetime fitness in each environment. Only three QTL directly affected fruit number, measuring fitness. Most QTL had an indirect effect on fitness through their effect on bolting time or leaf length. Influence of life history traits on fitness differed dramatically across sites, resulting in different patterns of selection on reproductive timing and underlying QTL. In two oceanic field sites with high prereproductive mortality, QTL alleles contributing to early reproduction resulted in greater fruit production, conferring selective advantage, whereas alleles contributing to later reproduction resulted in larger size and higher fitness in a continental site. This demonstrates how environmental variation leads to change in both QTL effect sizes and direction of selection on traits, justifying the persistence of allelic polymorphism at life history QTL across the species range.     

A non-stationary model for functional mapping of complex traits

SUMMARY: Understanding the genetic control of growth is fundamental to agricultural, evolutionary and biomedical genetic research. In this article, we present a statistical model for mapping quantitative trait loci (QTL) that are responsible for genetic differences in growth trajectories during ontogenetic development. This model is derived within the maximum likelihood context, implemented with the expectation-maximization algorithm. We incorporate mathematical aspects of growth processes to model the mean vector and structured antedependence models to approximate time-dependent covariance matrices for longitudinal traits. Our model has been employed to map QTL that affect body mass growth trajectories in both male and female mice of an F2 population derived from the Large and Small mouse strains. The results from this model are compared with those from the autoregressive-based functional mapping approach. Based on results from computer simulation studies, we suggest that these two models are alternative to one another and should be used simultaneously for the same dataset.