On the detection of imprinted quantitative trait loci in experimental crosses of outbred species

In this article, the quantitative genetic aspects of imprinted genes and statistical properties of methods to detect imprinted QTL are studied. Different models to detect imprinted QTL and to distinguish between imprinted and Mendelian QTL were compared in a simulation study. Mendelian and imprinted QTL were simulated in an F2 design and analyzed under Mendelian and imprinting models. Mode of expression was evaluated against the H(0) of a Mendelian QTL as well as the H(0) of an imprinted QTL. It was shown that imprinted QTL might remain undetected when analyzing the genome with Mendelian models only. Compared to testing against a Mendelian QTL, using the H(0) of an imprinted QTL gave a higher proportion of correctly identified imprinted QTL, but also gave a higher proportion of false inference of imprinting for Mendelian QTL. When QTL were segregating in the founder lines, spurious detection of imprinting became more prominent under both tests, especially for designs with a small number of F1 sires.     

Bayesian inference for genomic imprinting underlying developmental characteristics

The identification of imprinted genes is becoming a standard procedure in searching for quantitative trait loci (QTL) underlying complex traits. When a developmental characteristic such as growth or drug response is observed at multiple time points, understanding the dynamics of gene function governing the underlying feature should provide more biological information regarding the genetic control of an organism. Recognizing that differential imprinting can be development-specific, mapping imprinted genes considering the dynamic imprinting effect can provide additional biological insights into the epigenetic control of a complex trait. In this study, we proposed a Bayesian imprinted QTL (iQTL) mapping framework considering the dynamics of imprinting effects and model multiple iQTLs with an efficient Bayesian model selection procedure. The method overcomes the limitation of likelihood-based mapping procedure, and can simultaneously identify multiple iQTLs with different gene action modes across the whole genome with high computational efficiency. An inference procedure using Bayes factors to distinguish different imprinting patterns of iQTL was proposed. Monte Carlo simulations were conducted to evaluate the performance of the method. The utility of the approach was illustrated through an analysis of a body weight growth data set in an F(2) family derived from LG/J and SM/J mouse stains. The proposed Bayesian mapping method provides an efficient and computationally feasible framework for genome-wide multiple iQTL inference with complex developmental traits.     

Parent-of-origin specific QTL--a possibility towards understanding reciprocal effects in chicken and the origin of imprinting

Reciprocal effects for sexual maturity, egg production, egg quality traits and viability are well known in poultry crosses. They have been used in an optimal way to form profitable production hybrids. These effects have been hypothesized to originate from sex-linked genes, maternal effects or a combination of both. However, these may not be the only explanations for reciprocal effects. Recent mapping of quantitative trait loci (QTL) has revealed autosomal areas with parent-of-origin specific effects in the chicken. In mammals, parental imprinting, i.e. the specifically regulated expression of either maternal or paternal allele in the offspring, is the main cause of such effects. The most commonly accepted hypothesis for the origin of imprinting, the conflict hypothesis, assumes a genetic conflict of interest between the maternal and paternal genomes regarding the allocation of resources to the offspring. It also intrinsically implies that imprinting should not occur in oviparous taxa. However, new molecular genetic information has raised a need to review the possible involvement of imprinting or some related phenomena as a putative cause of reciprocal effects in poultry. Comparative mapping provides strong evidence for the conservation of orthologous imprinted gene clusters on chicken macrochromosomes. Furthermore, these gene clusters exhibit asynchronous DNA replication, an epigenetic mark specific for all imprinted regions. It has been proposed that these intrinsic chromosomal properties have been important for the evolution of imprinted gene expression in the mammalian lineage. Many of the mapped parent-of-origin specific QTL effects in chicken locate in or close to these conserved regions that show some of the basic features involved in monoallelic expression. If monoallelic expression in these regions would be observed in birds, the actual mechanism and cause may be different from the imprinting that evolved later in the mammalian lineage. In this review we discuss recent molecular genetic results that may provide tools for understanding of reciprocal differences in poultry breeding and the evolution of imprinting.     

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.     

A random model for mapping imprinted quantitative trait loci in a structured pedigree: an implication for mapping canine hip dysplasia

Genetic imprinting may have played a more notable role in shaping embryonic development of plants, animals, and humans than previously appreciated. Quantitative trait loci that are imprinted (iQTL) exert monoallelic effects, depending on the parent of origin, which is an exception to the laws of Mendelian genetics. In this article, we present a modified random effect-based mapping model to use in a genome-wide scan for the distribution of iQTL that contribute to genetic variance for a complex trait in a structured pedigree. This model, implemented with the maximum likelihood method, capitalizes on a network of relatedness for maternally and paternally derived alleles through identical-by-descent sharing, thus allowing for the discrimination of the genetic variances due to alleles derived from maternal and paternal parents. The model was employed to map iQTL responsible for canine hip dysplasia in a multihierarchical canine pedigree, founded with seven greyhounds and six Labrador retrievers. Of eight significant QTL detected, three, located on CFA1, CFA8, and CF28, were found to trigger significant parent-of-origin effects on the age of femoral capital ossification measured at the left and right hips of a canine. The detected iQTL provide important candidate regions for fine-mapping of imprinted genes and for studying their structure and function in the control of complex traits.     

Characterization of genomic imprinting effects and patterns with parametric accelerated failure time model

Genomic imprinting, a genetic phenomenon of non-equivalent allele expression that depends on parental origins, has been ubiquitously observed in nature. It does not only control the traits of growth and development but also may be responsible for survival traits. Based on the accelerated failure time model, we construct a general parametric model for mapping the imprinted QTL (iQTL). Within the framework of interval mapping, maximum likelihood estimation of iQTL parameters is implemented via EM algorithm. The imprinting patterns of the detected iQTL are statistically tested according to a series of null hypotheses. BIC model selection criterion is employed to choose an optimal baseline hazard function with maximum likelihood and parsimonious parameters. Simulations are used to validate the proposed mapping procedure. A published dataset from a mouse model system was used to illustrate the proposed framework. Results show that among the five commonly used survival distributions, Log-logistic distribution is the optimal baseline hazard function for mapping QTL of hyperoxic acute lung injury (HALI) survival; under the log-logistic distribution, four QTLs were identified, in which only one QTL was inherited in Mendelian fashion, whereas others were imprinted in different imprinting patterns.     

Bayesian mapping of quantitative trait loci for complex binary traits

A complex binary trait is a character that has a dichotomous expression but with a polygenic genetic background. Mapping quantitative trait loci (QTL) for such traits is difficult because of the discrete nature and the reduced variation in the phenotypic distribution. Bayesian statistics are proved to be a powerful tool for solving complicated genetic problems, such as multiple QTL with nonadditive effects, and have been successfully applied to QTL mapping for continuous traits. In this study, we show that Bayesian statistics are particularly useful for mapping QTL for complex binary traits. We model the binary trait under the classical threshold model of quantitative genetics. The Bayesian mapping statistics are developed on the basis of the idea of data augmentation. This treatment allows an easy way to generate the value of a hypothetical underlying variable (called the liability) and a threshold, which in turn allow the use of existing Bayesian statistics. The reversible jump Markov chain Monte Carlo algorithm is used to simulate the posterior samples of all unknowns, including the number of QTL, the locations and effects of identified QTL, genotypes of each individual at both the QTL and markers, and eventually the liability of each individual. The Bayesian mapping ends with an estimation of the joint posterior distribution of the number of QTL and the locations and effects of the identified QTL. Utilities of the method are demonstrated using a simulated outbred full-sib family. A computer program written in FORTRAN language is freely available on request.     

Analysis of quantitative trait loci that influence animal behavior

Behavioral differences between inbred strains of mice and rats have a genetic basis that can now be dissected using quantitative trait locus (QTL) analysis. Over the last 10 years, a large number of genetic loci that influence behavior have been mapped. In this article I review what that information has revealed about the genetic architecture of behavior. I show that most behaviors are influenced by QTL of small effect, each contributing to less than 10% of the variance of a behavioral trait. The small effect of each QTL on behavioral variation suggests that the mutational spectrum is different from that which results in Mendelian disorders. Regions of DNA should be appropriately prioritized to find the molecular variants, for instance by looking at sequences that control the level of gene expression rather than variants in coding regions. While the number of allelic loci that can contribute to a trait is large, this is not necessarily the case: the analysis of selected strains shows that a remarkably small number of QTL can explain the bulk of the genetic variation in behavior. I conclude by arguing that genetic mapping has more to offer than a starting point for positional cloning projects. With advances in multivariate analyses, mapping can also test hypotheses about the psychological processes that give rise to behavioral variation.     

Functional mapping imprinted quantitative trait loci underlying developmental characteristics

Background

Genomic imprinting, a phenomenon referring to nonequivalent expression of alleles depending on their parental origins, has been widely observed in nature. It has been shown recently that the epigenetic modification of an imprinted gene can be detected through a genetic mapping approach. Such an approach is developed based on traditional quantitative trait loci (QTL) mapping focusing on single trait analysis. Recent studies have shown that most imprinted genes in mammals play an important role in controlling embryonic growth and post-natal development. For a developmental character such as growth, current approach is less efficient in dissecting the dynamic genetic effect of imprinted genes during individual ontology.

Results

Functional mapping has been emerging as a powerful framework for mapping quantitative trait loci underlying complex traits showing developmental characteristics. To understand the genetic architecture of dynamic imprinted traits, we propose a mapping strategy by integrating the functional mapping approach with genomic imprinting. We demonstrate the approach through mapping imprinted QTL controlling growth trajectories in an inbred F₂ population. The statistical behavior of the approach is shown through simulation studies, in which the parameters can be estimated with reasonable precision under different simulation scenarios. The utility of the approach is illustrated through real data analysis in an F₂ family derived from LG/J and SM/J mouse stains. Three maternally imprinted QTLs are identified as regulating the growth trajectory of mouse body weight.

Conclusion

The functional iQTL mapping approach developed here provides a quantitative and testable framework for assessing the interplay between imprinted genes and a developmental process, and will have important implications for elucidating the genetic architecture of imprinted traits.     

Intronic Parent-of-Origin Dependent Differential Methylation at the Actn1 Gene Is Conserved in Rodents but Is Not Associated with Imprinted Expression

Parent-of-origin differential DNA methylation has been associated with regulation of the preferential expression of paternal or maternal alleles of imprinted genes. Based on this association, recent studies have searched for parent-of-origin dependent differentially methylated regions in order to identify new imprinted genes in their vicinity. In a previous genome-wide analysis of mouse brain DNA methylation, we found a novel differentially methylated region in a CpG island located in the last intron of the alpha 1 Actinin (Actn1) gene. In this region, preferential methylation of the maternal allele was observed; however, there were no reports of imprinted expression of Actn1. Therefore, we have tested if differential methylation of this region is common to other tissues and species and affects the expression of Actn1. We have found that Actn1 differential methylation occurs in diverse mouse tissues. Moreover, it is also present in other murine rodents (rat), but not in the orthologous human region. In contrast, we have found no indication of an imprinted effect on gene expression of Actn1 in mice: expression is always biallelic regardless of sex, tissue type, developmental stage or isoform. Therefore, we have identified a novel parent-of-origin dependent differentially methylated region that has no apparent association with imprinted expression of the closest genes. Our findings sound a cautionary note to genome-wide searches on the use of differentially methylated regions for the identification of imprinted genes and suggest that parent-of-origin dependent differential methylation might be conserved for functions other that the control of imprinted expression.     

QTL mapping and the genetic basis of adaptation: recent developments

Quantitative trait loci (QTL) mapping has been used in a number of evolutionary studies to study the genetic basis of adaptation by mapping individual QTL that explain the differences between differentiated populations and also estimating their effects and interaction in the mapping population. This analysis can provide clues about the evolutionary history of populations and causes of the population differentiation. QTL mapping analysis methods and associated computer programs provide us tools for such an inference on the genetic basis and architecture of quantitative trait variation in a mapping population. Current methods have the capability to separate and localize multiple QTL and estimate their effects and interaction on a quantitative trait. More recent methods have been targeted to provide a comprehensive inference on the overall genetic architecture of multiple traits in a number of environments. This development is important for evolutionary studies on the genetic basis of multiple trait variation, genotype by environment interaction, host–parasite interaction, and also microarray gene expression QTL analysis.     

A survey for novel imprinted genes in the mouse placenta by mRNA-seq

Many questions about the regulation, functional specialization, computational prediction, and evolution of genomic imprinting would be better addressed by having an exhaustive genome-wide catalog of genes that display parent-of-origin differential expression. As a first-pass scan for novel imprinted genes, we performed mRNA-seq experiments on embryonic day 17.5 (E17.5) mouse placenta cDNA samples from reciprocal cross F1 progeny of AKR and PWD mouse strains and quantified the allele-specific expression and the degree of parent-of-origin allelic imbalance. We confirmed the imprinting status of 23 known imprinted genes in the placenta and found that 12 genes reported previously to be imprinted in other tissues are also imprinted in mouse placenta. Through a well-replicated design using an orthogonal allelic-expression technology, we verified 5 novel imprinted genes that were not previously known to be imprinted in mouse (Pde10, Phf17, Phactr2, Zfp64, and Htra3). Our data suggest that most of the strongly imprinted genes have already been identified, at least in the placenta, and that evidence supports perhaps 100 additional weakly imprinted genes. Despite previous appearance that the placenta tends to display an excess of maternally expressed imprinted genes, with the addition of our validated set of placenta-imprinted genes, this maternal bias has disappeared.     

Joint-multiple family linkage analysis predicts within-family variation better than single-family analysis of the maize nested association mapping population

Quantitative trait locus (QTL) mapping has been used to dissect the genetic architecture of complex traits and predict phenotypes for marker-assisted selection. Many QTL mapping studies in plants have been limited to one biparental family population. Joint analysis of multiple biparental families offers an alternative approach to QTL mapping with a wider scope of inference. Joint-multiple population analysis should have higher power to detect QTL shared among multiple families, but may have lower power to detect rare QTL. We compared prediction ability of single-family and joint-family QTL analysis methods with fivefold cross-validation for 6 diverse traits using the maize nested association mapping population, which comprises 25 biparental recombinant inbred families. Joint-family QTL analysis had higher mean prediction abilities than single-family QTL analysis for all traits at most significance thresholds, and was always better at more stringent significance thresholds. Most robust QTL (detected in >50% of data samples) were restricted to one family and were often not detected at high frequency by joint-family analysis, implying substantial genetic heterogeneity among families for complex traits in maize. The superior predictive ability of joint-family QTL models despite important genetic differences among families suggests that joint-family models capture sufficient smaller effect QTL that are shared across families to compensate for missing some rare large-effect QTL.     

Bayesian functional mapping of dynamic quantitative traits

Without consideration of other linked QTLs responsible for dynamic trait, original functional mapping based on a single QTL model is not optimal for analyzing multiple dynamic trait loci. Despite that composite functional mapping incorporates the effects of genetic background outside the tested QTL in mapping model, the arbitrary choice of background markers also impact on the power of QTL detection. In this study, we proposed Bayesian functional mapping strategy that can simultaneously identify multiple QTL controlling developmental patterns of dynamic traits over the genome. Our proposed method fits the change of each QTL effect with the time by Legendre polynomial and takes the residual covariance structure into account using the first autoregressive equation. Also, Bayesian shrinkage estimation was employed to estimate the model parameters. Especially, we specify the gamma distribution as the prior for the first-order auto-regressive coefficient, which will guarantee the convergence of Bayesian sampling. Simulations showed that the proposed method could accurately estimate the QTL parameters and had a greater statistical power of QTL detection than the composite functional mapping. A real data analysis of leaf age growth in rice is used for the demonstration of our method. It shows that our Bayesian functional mapping can detect more QTLs as compared to composite functional mapping.     

Developmental control of imprinted expression by macro non-coding RNAs

Genomic imprinting is a developmentally regulated epigenetic phenomenon. The majority of imprinted genes only show parent-of-origin specific expression in a subset of tissues or at defined developmental stages. In some cases, imprinted expression is controlled by an imprinted macro non-coding RNA (ncRNA) whose expression pattern and repressive activity does not necessarily correlate with that of the genes whose imprinted expression it controls. This suggests that developmentally regulated factors other than the macro ncRNA are involved in establishing or maintaining imprinted expression. Here, we review how macro ncRNAs control imprinted expression during development and differentiation and consider how this impacts on target choice in epigenetic therapy.     

Bayesian mapping of quantitative trait loci under the identity-by-descent-based variance component model

Variance component analysis of quantitative trait loci (QTL) is an important strategy of genetic mapping for complex traits in humans. The method is robust because it can handle an arbitrary number of alleles with arbitrary modes of gene actions. The variance component method is usually implemented using the proportion of alleles with identity-by-descent (IBD) shared by relatives. As a result, information about marker linkage phases in the parents is not required. The method has been studied extensively under either the maximum-likelihood framework or the sib-pair regression paradigm. However, virtually all investigations are limited to normally distributed traits under a single QTL model. In this study, we develop a Bayes method to map multiple QTL. We also extend the Bayesian mapping procedure to identify QTL responsible for the variation of complex binary diseases in humans under a threshold model. The method can also treat the number of QTL as a parameter and infer its posterior distribution. We use the reversible jump Markov chain Monte Carlo method to infer the posterior distributions of parameters of interest. The Bayesian mapping procedure ends with an estimation of the joint posterior distribution of the number of QTL and the locations and variances of the identified QTL. Utilities of the method are demonstrated using a simulated population consisting of multiple full-sib families.     

Bayesian mapping of genome-wide epistatic imprinted loci for quantitative traits

Genomic imprinting, an epigenetic phenomenon of parent-of-origin-specific gene expression, has been widely observed in plants, animals, and humans. To detect imprinting genes influencing quantitative traits, the least squares and maximum likelihood approaches for fitting a single quantitative trait locus (QTL) and Bayesian methods for simultaneously modeling multiple QTL have been adopted, respectively, in various studies. However, most of these studies have only estimated imprinting main effects and thus ignored imprinting epistatic effects. In the presence of extremely complex genomic imprinting architectures, we introduce a Bayesian model selection method to analyze the multiple interacting imprinted QTL (iQTL) model. This approach will greatly enhance the computational efficiency through setting the upper bound of the number of QTLs and performing selective sampling for QTL parameters. The imprinting types of detected main-effect QTLs can be estimated from the Bayes factor statistic formulated by the posterior probabilities for the genetic effects being compared. The performance of the proposed method is demonstrated by several simulation experiments. Moreover, this method is applied to dissect the imprinting genetic architecture for body weight in mouse and fruit weight in tomato. Matlab code for implementing this approach will be available from the authors upon request.     

Efficiency of population structures for mapping of Mendelian and imprinted quantitative trait loci in outbred pigs using variance component methods

In a simulation study different designs for a pure line pig population were compared for efficiency of mapping QTL using the variance component method. Phenotypes affected by a Mendelian QTL, a paternally expressed QTL, a maternally expressed QTL or by a QTL without an effect were simulated. In all alternative designs 960 progeny were phenotyped. Given the limited number of animals there is an optimum between the number of families and the family size. Estimation of Mendelian and parentally expressed QTL is more efficient in a design with large family sizes. Too small a number of sires should be avoided to minimize chances of sires to be non-segregating. When a large number of families is used, the number of haplotypes increases which reduces the accuracy of estimating the QTL effect and thereby reduces the power to show a significant QTL and to correctly position the QTL. Dense maps allow for smaller family size due to exploitation of LD-information. Given the different possible modes of inheritance of the QTL using 8 to16 boars, two litters per dam was optimal with respect to determining significance and correct location of the QTL for a data set consisting of 960 progeny. The variance component method combining linkage disequilibrium and linkage analysis seems to be an appropriate choice to analyze data sets which vary in marker density and which contain complex family structures.     

Bayesian analysis of genetic architecture of quantitative trait using data of crosses of multiple inbred lines

Using the data of crosses of multiple of inbred lines for mapping QTL can increase QTL detecting power compared with only cross of two inbred lines. Although many fixed-effect model methods have been proposed to analyze such data, they are largely based on one-QTL model or main effect model, and the interaction effects between QTL are always neglected. However, effectively separating the interaction effects from the residual error can increase the statistical power. In this article, we both extended the novel Bayesian model selection method and Bayesian shrinkage estimation approaches to multiple inbred line crosses. With two extensions, interacting QTL are effectively detected with high solution; in addition, the posterior variances for both main effects and interaction effects are also subjected to full Bayesian estimate, which is more optimal than two step approach involved in maximum-likelihood. A series of simulation experiments have been conducted to demonstrate the performance of the methods. The computer program written in FORTRAN language is freely available on request.