The influence of environmentally induced heterogeneity on age-specific genetic variance for mortality rates

Using parametric models that describe the increase in mortality rates with age, we demonstrate that environmentally induced heterogeneity among genetically identical individuals is sufficient to generate biased estimates of age-specific genetic variance. Although the magnitude of the bias may change with age, one general trend emerges: the true genetic variance at the oldest ages is likely to be dramatically underestimated. Our results are robust to different manifestations of heterogeneity and suggest that such a bias is a general feature of these models. We note that age-dependent estimates of genetic variance for characters that are correlated with mortality (either genetically or environmentally) can be expected to be similarly affected. The results are independent of sample size and suggest that the bias may be more widespread in the literature than is currently appreciated. Our results are discussed with reference to existing data on mortality variance in Drosophila melanogaster.     

The use of a genetic algorithm for simultaneous mapping of multiple interacting quantitative trait loci

Here we describe a general method for improving computational efficiency in simultaneous mapping of multiple interacting quantitative trait loci (QTL). The method uses a genetic algorithm to search for QTL in the genome instead of an exhaustive enumerative ("step-by-step") search. It can be used together with any method of QTL mapping based on a genomic search, since it only provides a more efficient way to search the genome for QTL. The computational demand decreases by a factor of approximately 130 when using genetic algorithm-based mapping instead of an exhaustive enumerative search for two QTL in a genome size of 2000 cM using a resolution of 1 cM. The advantage of using a genetic algorithm increases further for larger genomes, higher resolutions, and searches for more QTL. We show that a genetic algorithm-based search has efficiency higher than or equal to a search method conditioned on previously identified QTL for all epistatic models tested and that this efficiency is comparable to that of an exhaustive search for multiple QTL. The genetic algorithm is thus a powerful and computationally tractable alternative to the exhaustive enumerative search for simultaneous mapping of multiple interacting QTL. The use of genetic algorithms for simultaneous mapping of more than two QTL and for determining empirical significance thresholds using permutation tests is also discussed.     

The genetic variance for multiple linked quantitative trait loci conditional on marker information in a crossed population

In the prediction of genetic values and quantitative trait loci (QTLs) mapping via the mixed model method incorporating marker information in animal populations, it is important to model the genetic variance for individuals with an arbitrary pedigree structure. In this study, for a crossed population originated from different genetic groups such as breeds or outbred strains, the variance of additive genetic values for multiple linked QTLs that are contained in a chromosome segment, especially the segregation variance, is investigated assuming the use of marker data. The variance for a finite number of QTLs in one chromosomal segment is first examined for the crossed population with the general pedigree. Then, applying the concept of the expectation of identity-by-descent proportion, an approximation to the mean of the conditional probabilities for the linked QTLs over all loci is obtained, and using it an expression for the variance in the case of an infinite number of linked QTLs marked by flanking markers is derived. It appears that the approach presented can be useful in the segment mapping using, and in the genetic evaluation of, crosses with general pedigrees in the population of concern. The calculation of the segregation variance through the current approach is illustrated numerically, using a small data-set.     

Prediction of breeding values and selection responses with genetic heterogeneity of environmental variance

There is empirical evidence that genotypes differ not only in mean, but also in environmental variance of the traits they affect. Genetic heterogeneity of environmental variance may indicate genetic differences in environmental sensitivity. The aim of this study was to develop a general framework for prediction of breeding values and selection responses in mean and environmental variance with genetic heterogeneity of environmental variance. Both means and environmental variances were treated as heritable traits. Breeding values and selection responses were predicted with little bias using linear, quadratic, and cubic regression on individual phenotype or using linear regression on the mean and within-family variance of a group of relatives. A measure of heritability was proposed for environmental variance to standardize results in the literature and to facilitate comparisons to "conventional" traits. Genetic heterogeneity of environmental variance can be considered as a trait with a low heritability. Although a large amount of information is necessary to accurately estimate breeding values for environmental variance, response in environmental variance can be substantial, even with mass selection. The methods developed allow use of the well-known selection index framework to evaluate breeding strategies and effects of natural selection that simultaneously change the mean and the variance.     

Inference on the strength of balancing selection for epistatically interacting loci

Existing inference methods for estimating the strength of balancing selection in multi-locus genotypes rely on the assumption that there are no epistatic interactions between loci. Complex systems in which balancing selection is prevalent, such as sets of human immune system genes, are known to contain components that interact epistatically. Therefore, current methods may not produce reliable inference on the strength of selection at these loci. In this paper, we address this problem by presenting statistical methods that can account for epistatic interactions in making inference about balancing selection. A theoretical result due to Fearnhead (2006) is used to build a multi-locus Wright-Fisher model of balancing selection, allowing for epistatic interactions among loci. Antagonistic and synergistic types of interactions are examined. The joint posterior distribution of the selection and mutation parameters is sampled by Markov chain Monte Carlo methods, and the plausibility of models is assessed via Bayes factors. As a component of the inference process, an algorithm to generate multi-locus allele frequencies under balancing selection models with epistasis is also presented. Recent evidence on interactions among a set of human immune system genes is introduced as a motivating biological system for the epistatic model, and data on these genes are used to demonstrate the methods.     

New quantitative trait loci for the genetic variance in circadian period of locomotor activity between inbred strains of mice

Provisional quantitative trait loci (QTL) for circadian locomotor period and wheel-running period have been identified in recombinant inbred (RI) mouse strains. To confirm those QTL and identify new ones, the genetic component of variance of the circadian period was partitioned among an F2 intercross of RI mouse strains (BXD19 and CXB07). First, a genomic survey using 108 SSLP markers with an average spacing of 15 cM was carried out in a population of 259 (BXD19 x CXB07)F2 animals. The genome-wide survey identified two significant QTL for period of locomotor activity measured by infrared photobeam crossings on mouse chromosomes 1 (lod score 5.66) and 14 (lod score 4.33). The QTL on distal chromosome 1 confirmed a previous report based on congenic B6.D2-Mtv7a/Ty mice. Lod scores greater than 2.0 were found on chromosomes 1, 2, 6, 12, 13, and 14. In a targeted extension study, additional genotyping was performed on these chromosomes in the full sample of 341 F2 progeny. The 6 chromosome-wide surveys identified 3 additional QTL on mouse chromosomes 6, 12, and 13. The QTL on chromosome 12 overlaps with circadian period QTL identified in several prior studies. For wheel-running period, the chromosome-wide surveys identified QTL on chromosomes 2 and 13 and one highly suggestive QTL on proximal chromosome 1. The results are compared to other published studies of QTL of circadian period.     

Bayesian mapping of genomewide interacting quantitative trait loci for ordinal traits

Development of statistical methods and software for mapping interacting QTL has been the focus of much recent research. We previously developed a Bayesian model selection framework, based on the composite model space approach, for mapping multiple epistatic QTL affecting continuous traits. In this study we extend the composite model space approach to complex ordinal traits in experimental crosses. We jointly model main and epistatic effects of QTL and environmental factors on the basis of the ordinal probit model (also called threshold model) that assumes a latent continuous trait underlies the generation of the ordinal phenotypes through a set of unknown thresholds. A data augmentation approach is developed to jointly generate the latent data and the thresholds. The proposed ordinal probit model, combined with the composite model space framework for continuous traits, offers a convenient way for genomewide interacting QTL analysis of ordinal traits. We illustrate the proposed method by detecting new QTL and epistatic effects for an ordinal trait, dead fetuses, in a F(2) intercross of mice. Utility and flexibility of the method are also demonstrated using a simulated data set. Our method has been implemented in the freely available package R/qtlbim, which greatly facilitates the general usage of the Bayesian methodology for genomewide interacting QTL analysis for continuous, binary, and ordinal traits in experimental crosses.     

我国特有树种长叶榧树的生物学特性与保护问题研究

在持续１０余年对我国特有珍贵树种长叶榧树的分布区、生长环境、生物学特性调查研究基础上,全面系统地提出了该树种保护措施与开发利用意见。     

Evidence for genetic heterogeneity in Carvajal syndrome

Carvajal syndrome is a rare syndrome with woolly hair, palmoplantar keratosis and dilated cardiomyopathy. The inheritance of the mutation is autosomal recessive. As a causal gene, the desmoplakin gene (DSP) has so far been identified; it encodes an essential component of desmosomes, a cell-cell structure aimed at keeping cells attached to each other in tissues in which cells are often exposed to strong shear forces. Recently, familial cases of an autosomal dominant Carvajal syndrome were documented with a new feature: hypo/oligodontia. A mutation in the DSP gene was also evidenced in these latter cases. A patient was seen for cardiogenetic consultation at the University Hospital of Lyon with cardiac failure involving first degree atrioventricular block, complete left bundle branch block, non-compaction of the apex of the left ventricle and a dilated cardiomyopathy. A coronarography disclosed a complete thrombosis of the right coronary artery. At examination, he had also woolly hair, mild palmoplantar keratosis and missing teeth (essentially molars and premolars). His family history was uninformative. His DNA was screened for mutations in the DSP and plakoglobin genes but no mutation could be found. This case suggests that Carvajal syndrome with hypo/oligodontia is a heterogeneous condition in which genes other than DSP might be involved, although we cannot rule out a mutation in this gene consisting in a deletion of a single exon or a gene rearrangement.     

A heterogeneity test for fine-scale genetic structure

For organisms with limited vagility and/or occupying patchy habitats, we often encounter nonrandom patterns of genetic affinity over relatively small spatial scales, labelled fine-scale genetic structure. Both the extent and decay rate of that pattern can be expected to depend on numerous interesting demographic, ecological, historical, and mating system factors, and it would be useful to be able to compare different situations. There is, however, no heterogeneity test currently available for fine-scale genetic structure that would provide us with any guidance on whether the differences we encounter are statistically credible. Here, we develop a general nonparametric heterogeneity test, elaborating on standard autocorrelation methods for pairs of individuals. We first develop a 'pooled within-population' correlogram, where the distance classes (lags) can be defined as functions of distance. Using that pooled correlogram as our null-hypothesis reference frame, we then develop a heterogeneity test of the autocorrelations among different populations, lag-by-lag. From these single-lag tests, we construct an analogous test of heterogeneity for multilag correlograms. We illustrate with a pair of biological examples, one involving the Australian bush rat, the other involving toadshade trillium. The Australian bush rat has limited vagility, and sometimes occupies patchy habitat. We show that the autocorrelation pattern diverges somewhat between continuous and patchy habitat types. For toadshade trillium, clonal replication in Piedmont populations substantially increases autocorrelation for short lags, but clonal replication is less pronounced in mountain populations. Removal of clonal replicates reduces the autocorrelation for short lags and reverses the sign of the difference between mountain and Piedmont correlograms.     

The detection of linkage and heterogeneity in nuclear families for complex disorders: one versus two marker loci.

Using exact expected likelihoods, we have computed the average number of phase-unknown nuclear families needed to detect linkage and heterogeneity. We have examined the case of both dominant and recessive inheritance with reduced penetrance and phenocopies. Most of our calculations have been carried out under the assumption that 50% of families are linked to a marker locus. We have varied both the number of offspring per family and the sampling scheme. We have also investigated the increased power when the disease locus is midway between two marker loci 10 cM apart. For recessive inheritance, both linkage and heterogeneity can be detected in clinically feasible sample sizes. For dominant inheritance, linkage can be detected but heterogeneity cannot be detected unless larger sibships (four offspring) are sampled or two linked markers are available. As expected, if penetrance is reduced, sampling families with all sibs affected is most efficient. Our results provide a basis for estimating the amount of resources needed to find genes for complex disorders under conditions of heterogeneity.     

Evidence for genetic heterogeneity of malignant hyperthermia susceptibility

A locus for malignant hyperthermia susceptibility (MHS) has been localized on chromosome 19q12-13.2, while at the same time the gene encoding the skeletal muscle ryanodine receptor (RYR1) also has been mapped to this region and has been found to be tightly linked to MHS. RYR1 was consequently postulated as the candidate for the molecular defect causing MHS, and a point mutation in the gene has now been identified and is thought to be the cause of MH in at least some MHS patients. Here we report the results of a linkage study done with 19q12-13.2 markers, including the RYR1 cDNA, in two Bavarian families with MHS. In one of the families, three unambiguous recombination events between MHS and the RYR1 locus were found. In the second family only one informative meiosis was seen with RYR1. However, segregation analysis with markers for D19S75, D19S28, D19S47, CYP2A, BCL3, and APOC2 shows that the crossovers in the first family involve the entire haplotype defined by these markers flanking RYR1 and, furthermore, reveals multiple crossovers between these haplotypes and MHS in the second family. In these families, pairwise and multipoint lod scores below -2 exclude MHS from an interval spanning more than 26 cM and comprising the RYR1 and the previously described MHS locus. Our findings thus strongly suggest genetic heterogeneity of the MHS trait and prompt the search for another MHS locus.