Genomic imprinting and genetic effects on muscle traits in mice

ABSTRACT: BACKGROUND: Genomic imprinting refers to parent-of-origin dependent gene expression caused by differential DNA methylation of the paternally and maternally derived alleles. Imprinting is increasingly recognized as an important source of variation in complex traits, however, its role in explaining variation in muscle and physiological traits, especially those of commercial value, is largely unknown compared with genetic effects. RESULTS: We investigated both genetic and genomic imprinting effects on key muscle traits in mice from the Berlin Muscle Mouse population, a key model system to study muscle traits. Using a genome scan, we first identified loci with either imprinting or genetic effects on phenotypic variation. Next, we established the proportion of phenotypic variation explained by additive, dominance and imprinted QTL and characterized the patterns of effects. In total, we identified nine QTL, two of which show large imprinting effects on glycogen content and potential, and body weight. Surprisingly, all imprinting patterns were of the bipolar type, in which the two heterozygotes are different from each other but the homozygotes are not. Most QTL had pleiotropic effects and explained up to 40% of phenotypic variance, with individual imprinted loci accounting for 4-5% of variation alone. CONCLUSION: Surprisingly, variation in glycogen content and potential was only modulated by imprinting effects. Further, in contrast to general assumptions, our results show that genomic imprinting can impact physiological traits measured at adult stages and that the expression does not have to follow the patterns of paternal or maternal expression commonly ascribed to imprinting effects.     

Genome-wide analysis reveals a complex pattern of genomic imprinting in mice

Parent-of-origin–dependent gene expression resulting from genomic imprinting plays an important role in modulating complex traits ranging from developmental processes to cognitive abilities and associated disorders. However, while gene-targeting techniques have allowed for the identification of imprinted loci, very little is known about the contribution of imprinting to quantitative variation in complex traits. Most studies, furthermore, assume a simple pattern of imprinting, resulting in either paternal or maternal gene expression; yet, more complex patterns of effects also exist. As a result, the distribution and number of different imprinting patterns across the genome remain largely unexplored. We address these unresolved issues using a genome-wide scan for imprinted quantitative trait loci (iQTL) affecting body weight and growth in mice using a novel three-generation design. We identified ten iQTL that display much more complex and diverse effect patterns than previously assumed, including four loci with effects similar to the callipyge mutation found in sheep. Three loci display a new phenotypic pattern that we refer to as bipolar dominance, where the two heterozygotes are different from each other while the two homozygotes are identical to each other. Our study furthermore detected a paternally expressed iQTL on Chromosome 7 in a region containing a known imprinting cluster with many paternally expressed genes. Surprisingly, the effects of the iQTL were mostly restricted to traits expressed after weaning. Our results imply that the quantitative effects of an imprinted allele at a locus depend both on its parent of origin and the allele it is paired with. Our findings also show that the imprinting pattern of a locus can be variable over ontogenetic time and, in contrast to current views, may often be stronger at later stages in life.     

Quantitative trait loci with parent-of-origin effects in chicken

We investigated potential effects of parent-of-origin specific quantitative trait loci (QTL) in chicken. Two divergent egg-layer lines differing in egg quality were reciprocally crossed to produce 305 F2 hens. Searching the genome using models with uni-parental expression, we identified four genome-wide significant QTL with parent-of-origin effects and three highly suggestive QTL affecting age at first egg, egg weight, number of eggs, body weight, feed intake, and egg white quality. None of these QTL had been detected previously using Mendelian models. Two genome-wide significant and one highly suggestive QTL show exclusive paternal expression while the others show exclusive maternal expression. Each of the parent-of-origin specific QTL explained 3-5 % of the total phenotypic variance, with the effects ranging from 0.18 to 0.4 phenotypic SD in the F2. Using simulations and further detailed analyses, it was shown that departure from fixation in the founder lines, grand-maternal effects (i.e. mitochondrial or W-linked) and Z-linked QTL were unlikely to give rise to any spurious parent-of-origin effects. The present results suggest that QTL with parent-of-origin specific expression are a plausible explanation for some reciprocal effects in poultry and deserve more attention. An intriguing hypothesis is whether these effects could be the result of genomic imprinting, which is often assumed to be unique to eutherian mammals.     

DIFFERENTIAL DOMINANCE OF PLEIOTROPIC LOCI FOR MOUSE SKELETAL TRAITS

The term "differential dominance" describes the situation in which the dominance effects at a pleiotropic locus vary between traits. Directional selection on the phenotype can lead to balancing selection on differentially dominant pleiotropic loci. Even without any individual overdominant traits, some linear combination of traits will display overdominance at a locus displaying differential dominance. Multivariate overdominance may be responsible, in part, for high levels of heterozygosity found in natural populations. We examine differential dominance of 70 mouse skeletal traits at 92 quantitative trait loci (QTL). Our results indicate moderate to strong additive and dominance effects at pleiotropic loci, low levels of individual-trait overdominance, and universal multivariate overdominance. Multivariate overdominance affects a range of 6% to 81% of morphospace, with a mean of 32%. Multivariate overdominance tends to affect a larger percentage of morphospace at pleiotropic loci with antagonistic effects on multiple traits (42%). We conclude that multivariate overdominance is common and should be considered in models and in empirical studies of the role of genetic variation in evolvability.     

Conservation of gene function in the solanaceae as revealed by comparative mapping of domestication traits in eggplant

Quantitative trait loci (QTL) for domestication-related traits were identified in an interspecific F(2) population of eggplant (Solanum linnaeanum x S. melongena). Although 62 quantitative trait loci (QTL) were identified in two locations, most of the dramatic phenotypic differences in fruit weight, shape, color, and plant prickliness that distinguish cultivated eggplant from its wild relative could be attributed to six loci with major effects. Comparison of the genomic locations of the eggplant fruit weight, fruit shape, and color QTL with the positions of similar loci in tomato, potato, and pepper revealed that 40% of the different loci have putative orthologous counterparts in at least one of these other crop species. Overall, the results suggest that domestication of the Solanaceae has been driven by mutations in a very limited number of target loci with major phenotypic effects, that selection pressures were exerted on the same loci despite the crops' independent domestications on different continents, and that the morphological diversity of these four crops can be explained by divergent mutations at these loci.     

MHC polymorphism and disease resistance to vibrio anguillarum in 8 families of half-smooth tongue sole (Cynoglossus semilaevis)

Background

Most quantitative traits are controlled by multiple quantitative trait loci (QTL). The contribution of each locus may be negligible but the collective contribution of all loci is usually significant. Genome selection that uses markers of the entire genome to predict the genomic values of individual plants or animals can be more efficient than selection on phenotypic values and pedigree information alone for genetic improvement. When a quantitative trait is contributed by epistatic effects, using all markers (main effects) and marker pairs (epistatic effects) to predict the genomic values of plants can achieve the maximum efficiency for genetic improvement.

Results

In this study, we created 126 recombinant inbred lines of soybean and genotyped 80 makers across the genome. We applied the genome selection technique to predict the genomic value of somatic embryo number (a quantitative trait) for each line. Cross validation analysis showed that the squared correlation coefficient between the observed and predicted embryo numbers was 0.33 when only main (additive) effects were used for prediction. When the interaction (epistatic) effects were also included in the model, the squared correlation coefficient reached 0.78.

Conclusions

This study provided an excellent example for the application of genome selection to plant breeding.     

Many QTLs with minor additive effects are associated with a large difference in growth between two selection lines in chickens

Two growth-selected lines in chickens have been developed from a single founder population by divergent selection for body weight at 56 days of age. After more than 40 generations of selection they show a nine-fold difference in body weight at selection age and large differences in growth rate, appetite, fat deposition and metabolic characteristics. We have generated a large intercross between these lines comprising more than 800 F2 birds. QTL mapping revealed 13 loci affecting growth. The most striking observation was that the allele in the high weight line in all cases was associated with enhanced growth, but each locus explained only a small proportion of the phenotypic variance using a standard QTL model (1.3-3.1%). This result is in sharp contrast to our previous study where we reported that the two-fold difference in adult body size between the red junglefowl and White Leghorn domestic chickens is explained by a small number of QTLs with large additive effects. Furthermore, no QTLs for anorexia or antibody response were detected despite large differences for these traits between the founder lines. The result is an excellent example where a large phenotypic difference between populations occurs in the apparent absence of any single locus with large phenotypic effects. The study underscores the need for powerful experimental designs in genetic studies of multifactorial traits. No QTL at all would have reached genome-wide significance using a less powerful design (e.g. approx. 200 F2 individuals) regardless of the nine-fold phenotypic difference between the founder lines for the selected trait.     

QTL mapping for test weight by using F<Subscript><Emphasis Type="Bold">2:3</Emphasis></Subscript> population in maize

Test weight is an important trait in maize breeding. Understanding the genetic mechanism of test weight is important for effective selection of maize test weight improvement. In this study, quantitative trait loci (QTL) for maize test weight were identified. In the years 2007 and 2008, a F_2:3 population along with the parents Chang7-2 and Zheng58 were planted in Zhengzhou, People’s Republic of China. Significant genotypic variation for maize test weight was observed in both years. Based on the genetic map containing 180 polymorphic SSR markers with an average linkage distance of 11.0 cM, QTL for maize test weight were analysed by mixed-model composite interval mapping. Five QTL, including four QTL with only additive effects, were identified on chromosomes 1, 2, 3, 4 and 5, and together explained 25.2% of the phenotypic variation. Seven pairs of epistatic interactions were also detected, involving 11 loci distributed on chromosomes 1, 2, 3, 4, 5 and 7, respectively, which totally contributed 18.2% of the phenotypic variation. However, no significant QTL × environment (Q×E) interaction and epistasis × environment interaction effects were detected. The results showed that besides the additive QTL, epistatic interactions also formed an important genetic basis for test weight in maize.     

Different models of genetic variation and their effect on genomic evaluation

Background

The theory of genomic selection is based on the prediction of the effects of quantitative trait loci (QTL) in linkage disequilibrium (LD) with markers. However, there is increasing evidence that genomic selection also relies on "relationships" between individuals to accurately predict genetic values. Therefore, a better understanding of what genomic selection actually predicts is relevant so that appropriate methods of analysis are used in genomic evaluations.

Methods

Simulation was used to compare the performance of estimates of breeding values based on pedigree relationships (Best Linear Unbiased Prediction, BLUP), genomic relationships (gBLUP), and based on a Bayesian variable selection model (Bayes B) to estimate breeding values under a range of different underlying models of genetic variation. The effects of different marker densities and varying animal relationships were also examined.

Results

This study shows that genomic selection methods can predict a proportion of the additive genetic value when genetic variation is controlled by common quantitative trait loci (QTL model), rare loci (rare variant model), all loci (infinitesimal model) and a random association (a polygenic model). The Bayes B method was able to estimate breeding values more accurately than gBLUP under the QTL and rare variant models, for the alternative marker densities and reference populations. The Bayes B and gBLUP methods had similar accuracies under the infinitesimal model.

Conclusions

Our results suggest that Bayes B is superior to gBLUP to estimate breeding values from genomic data. The underlying model of genetic variation greatly affects the predictive ability of genomic selection methods, and the superiority of Bayes B over gBLUP is highly dependent on the presence of large QTL effects. The use of SNP sequence data will outperform the less dense marker panels. However, the size and distribution of QTL effects and the size of reference populations still greatly influence the effectiveness of using sequence data for genomic prediction.     

Divergent selection as revealed by P(ST) and QTL-based F(ST) in three-spined stickleback (Gasterosteus aculeatus) populations along a coastal-inland gradient

Three measures of divergence, estimated at nine putatively neutral microsatellite markers, 14 quantitative traits, and seven quantitative trait loci (QTL) were compared in eight populations of the three-spined stickleback (Gasterosteus aculeatus L.) living in the Scheldt river basin (Belgium). Lowland estuarine and polder populations were polymorphic for the number of lateral plates, whereas upland freshwater populations were low-plated. The number of short gill rakers and the length of dorsal and pelvic spines gradually declined along a coastal-inland gradient. Plate number, short gill rakers and spine length showed moderate to strong signals of divergent selection between lowland and upland populations in comparison between P(ST) (a phenotypic alternative for Q(ST)) and neutral F(ST). However, such comparisons rely on the unrealistic assumption that phenotypic variance equals additive genetic variance, and that nonadditive genetic effects and environmental effects can be minimized. In order to verify this assumption and to confirm the phenotypic signals of divergence, we tested for divergent selection at the underlying QTL. For plate number, strong genetic evidence for divergent selection between lowland and upland populations was obtained based on an intron marker of the Eda gene, of which the genotype was highly congruent with plate morph. Genetic evidence for divergent selection on short gill rakers was limited to some population pairs where F(ST) at only one of two QTL was detected as an outlier, although F(ST) at both loci correlated significantly with P(ST). No genetic confirmation was obtained for divergent selection on dorsal spine length, as no outlier F(ST)s were detected at dorsal spine QTL, and no significant correlations with P(ST) were observed.     

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.     

Quantitative trait loci affecting knockdown resistance to high temperature in Drosophila melanogaster

Knockdown resistance to high temperature is an ecologically important trait in small insects. A composite interval mapping was performed on the two major autosomes of Drosophila melanogaster to search for quantitative trait loci (QTL) affecting knockdown resistance to high temperature (KRHT). Two dramatically divergent lines from geographically different thermal environments were artificially selected on KRHT. These lines were crossed to produce two backcross (BC) populations. Each BC was analysed for 200 males with 18 marker loci on chromosomes 2 and 3. Three X-linked markers were used to test for X-linked QTL in an exploratory way. The largest estimate of autosome additive effects was found in the pericentromeric region of chromosome 2, accounting for 19.26% (BC to the low line) and 29.15% (BC to the high line) of the phenotypic variance in BC populations, but it could represent multiple closely linked QTL. Complete dominance was apparent for three QTL on chromosome 3, where heat-shock genes are concentrated. Exploratory analysis of chromosome X indicated a substantial contribution of this chromosome to KRHT. The results show that a large-effect QTL with dominant gene action maps on the right arm of chromosome 3. Further, the results confirm that QTL for heat resistance are not limited to chromosome 3.     

Maternal effects as the cause of parent-of-origin effects that mimic genomic imprinting

Epigenetic effects are increasingly recognized as an important source of variation in complex traits and have emerged as the focus of a rapidly expanding area of research. Principle among these effects is genomic imprinting, which has generally been examined in analyses of complex traits by testing for parent-of-origin-dependent effects of alleles. However, in most of these analyses maternal effects are confounded with genomic imprinting because they can produce the same patterns of phenotypic variation expected for various forms of imprinting. Distinguishing between the two is critical for genetic and evolutionary studies because they have entirely different patterns of gene expression and evolutionary dynamics. Using a simple single-locus model, we show that maternal genetic effects can result in patterns that mimic those expected under genomic imprinting. We further demonstrate how maternal effects and imprinting effects can be distinguished using genomic data from parents and offspring. The model results are applied to a genome scan for quantitative trait loci (QTL) affecting growth- and weight-related traits in mice to illustrate how maternal effects can mimic imprinting. This genome scan revealed five separate maternal-effect loci that caused a diversity of patterns mimicking those expected under various modes of genomic imprinting. These results demonstrate that the appearance of parent-of-origin-dependent effects (POEs) of alleles at a locus cannot be taken as direct evidence that the locus is imprinted. Moreover, they show that, in gene mapping studies, genetic data from both parents and offspring are required to successfully differentiate between imprinting and maternal effects as the cause of apparent parent-of-origin effects of alleles.     

Quantitative trait loci for growth and body size in the nine‐spined stickleback Pungitius pungitius L.

Body size is an ecologically important trait shown to be genetically variable both within and among different animal populations as revealed by quantitative genetic studies. However, few studies have looked into underlying genetic architecture of body size variability in the wild using genetic mapping methods. With the aid of quantitative trait loci (QTL) analyses based on 226 microsatellite markers, we mapped body size and growth rate traits in the nine‐spined stickleback (Pungitius pungitius) using an F₂‐intercross (n = 283 offspring) between size‐divergent populations. In total, 17 QTL locations were detected. The proportion of phenotypic variation explained by individual body size‐related QTL ranged from 3% to 12% and those related to growth parameters and increments from 3% to 10%. Several of the detected QTL affected either early or late growth. These results provide a solid starting point for more in depth investigations of structure and function of genomic regions involved in determination of body size in this popular model of ecological and evolutionary research.     

Developmental Quantitative Genetics, Conditional Epigenetic Variability and Growth in Mice

Ontogenetic variation in the causal components of phenotypic variability and covariability is described for body weight and tail length in mice derived from a full 7 X 7 diallel cross. Age-related changes in additive, dominance, sex-linked and maternal variance and covariance between 14 and 70 days of age are described. Age-specific variance components at time t are conditioned on the causal genetic effects at time (t - 1). This procedure demonstrates the generation of significant episodes of new genetic variation arising at specific intervals during ontogeny. These episodes of new genetic variation are placed in the context of epigenetic models in developmental quantitative genetics. These results are also concordant on recent findings on age-specific gene expression in mouse growth as shown by QTL analyses.     

Detection of favorable alleles for plant height and crown rust tolerance in three connected populations of perennial ryegrass (<Emphasis Type="Italic">Lolium perenne</Emphasis> L.)

Plant height, which is an estimator of vegetative yield, and crown rust tolerance are major criteria for perennial ryegrass breeding. Genetic improvement has been achieved through phenotypic selection but it should be speeded up using marker-assisted selection, especially in this heterozygous species suffering from inbreeding depression. Using connected multiparental populations should increase the diversity studied and could substantially increase the power of quantitative trait loci (QTL) detection. The objective of this study was to detect the best alleles for plant height and rust tolerance among three connected populations derived from elite material by comparing an analysis per parent and a multipopulation connected analysis. For the studied traits, 17 QTL were detected with the analysis per parent while the additive and dominance models of the multipopulation connected analysis made it possible to detect 33 and 21 QTL, respectively. Favorable alleles have been detected in all parents. Only a few dominance effects were detected and they generally had lower values than the additive effects. The additive model of the multipopulation connected analysis was the most powerful as it made it possible to detect most of the QTL identified in the other analyses and 11 additional QTL. Using this model, plant growth QTL and rust tolerance QTL explained up to 19 and 38.6% of phenotypic variance, respectively. This example involving three connected populations is promising for an application on polycross progenies, traditionally used in breeding programs. Indeed, polycross progenies actually are a set of several connected populations.     

Optimal selection on two quantitative trait loci with linkage

A mathematical approach to optimize selection on multiple quantitative trait loci (QTL) and an estimate of residual polygenic effects was applied to selection on two linked or unlinked additive QTL. Strategies to maximize total or cumulative discounted response over ten generations were compared to standard QTL selection on the sum of breeding values for the QTL and an estimated breeding value for polygenes, and to phenotypic selection. Optimal selection resulted in greater response to selection than standard QTL or phenotypic selection. Tight linkage between the QTL (recombination rate 0.05) resulted in a slightly lower response for standard QTL and phenotypic selection but in a greater response for optimal selection. Optimal selection capitalized on linkage by emphasizing selection on favorable haplotypes. When the objective was to maximize total response after ten generations and QTL were unlinked, optimal selection increased QTL frequencies to fixation in a near linear manner. When starting frequencies were equal for the two QTL, equal emphasis was given to each QTL, regardless of the difference in effects of the QTL and regardless of the linkage, but the emphasis given to each of the two QTL was not additive. These results demonstrate the ability of optimal selection to capitalize on information on the complex genetic basis of quantitative traits that is forthcoming.     

Quantitative trait loci for body growth and sex determination in the hermaphrodite teleost fish Sparus aurata L.

Gilthead sea bream (Sparus aurata L.) is an important marine fish in Mediterranean aquaculture. Sex determination by age and/or body weight is a critical life‐history trait, the genetic basis for which is largely unknown in this sequential hermaphrodite species. Herein, we performed a partial genome scan to map quantitative trait loci (QTL) affecting body weight and sex using 74 informative microsatellite markers from 10 paternal half‐sib families to construct nine linkage groups (LG). In total, four growth‐related QTL (two chromosome‐wide and two genome‐wide) and six QTL related to sex determination (three pairs in three different LGs) were detected (two chromosome‐wide and one genome‐wide). The proportion of phenotypic variation explained by the body‐weight QTL ranged from 9.3% to 17.2%, showing their potential for use in marker‐assisted selection. The results obtained offer solid ground to investigate the structure and function of the genomic regions involved in the mechanisms of sex reversal.     

Mapping of quantitative trait loci for kernel row number in maize across seven environments

Genetic factors controlling quantitative inheritance of grain yield and its components have been intensively investigated during recent decades using diverse populations in maize (Zea mays L.). Notwithstanding this, quantitative trait loci (QTL) for kernel row number (KRN) with large and consistent effect have not been identified. In this study, a linkage map of 150 simple sequence repeat (SSR) loci was constructed by using a population of 500 F2 individuals derived from a cross between elite inbreds Ye478 and Dan340. The linkage map spanned a total of 1478 cM with an average interval of 10.0 cM. A total of 397 F2:3 lines were evaluated across seven diverse environments for mapping QTL for KRN. Some QTL for grain yield and its components had previously been confirmed with this population across environments. A total of 13 QTL for KRN were identified, with each QTL explaining from 3.0 to 17.9% of phenotypic variance. The gene action for KRN was mainly additive to partial dominance. A large-effect QTL (qkrn7) with partial dominance effect accounting for 17.9% of the phenotypic variation for KRN was identified on chromosome 7 near marker umc1865 with consistent gene effect across seven diverse environments. This study has laid a foundation for map-based cloning of this major QTL and for developing molecular markers for marker-assisted selection of high KRN.