Estimating the additive genetic effect of the X chromosome

Polygenic response of sex chromosomes to sexual antagonism

Sexual antagonism occurs when males and females differ in their phenotypic fitness optima but are constrained in their evolution to these optima because of their shared genome. The sex chromosomes, which have distinct evolutionary "interests" relative to the autosomes, are theorized to play an important role in sexually antagonistic conflict. However, the evolutionary responses of sex chromosomes and autosomes have usually been considered independently, that is, via contrasting the response of a gene located on either an X chromosome or an autosome. Here, we study the coevolutionary response of the X chromosome and autosomes to sexually antagonistic selection acting on a polygenic phenotype. We model a phenotype initially under stabilizing selection around a single optimum, followed by a sudden divergence of the male and female optima. We find that, in the absence of dosage compensation, the X chromosome promotes evolution toward the female optimum, inducing coevolutionary male-biased responses on the autosomes. Dosage compensation obscures the female-biased interests of the X, causing it to contribute equally to male and female phenotypic change. We further demonstrate that fluctuations in an adaptive landscape can generate prolonged intragenomic conflict and accentuate the differential responses of the X and autosomes to this conflict.

The effect of X-linked dosage compensation on complex trait variation

Quantitative genetics theory predicts that X-chromosome dosage compensation (DC) will have a detectable effect on the amount of genetic and therefore phenotypic trait variances at associated loci in males and females. Here, we systematically examine the role of DC in humans in 20 complex traits in a sample of more than 450,000 individuals from the UK Biobank and 1600 gene expression traits from a sample of 2000 individuals as well as across-tissue gene expression from the GTEx resource. We find approximately twice as much X-linked genetic variation across the UK Biobank traits in males (mean h²_SNP = 0.63%) compared to females (mean h²_SNP = 0.30%), confirming the predicted DC effect. Our DC estimates for complex traits and gene expression are consistent with a small proportion of genes escaping X-inactivation in a trait- and tissue-dependent manner. Finally, we highlight examples of biologically relevant X-linked heterogeneity between the sexes that bias DC estimates if unaccounted for.

Dosage compensation (DC) on the X chromosome has predictable effects on genetic and phenotypic trait variance. Here, the authors use information for 20 quantitative traits in the UK Biobank and across-tissue gene expression to compare X-linked heritability and the effects of trait-associated SNPs between the sexes.

The kinship2 R package for pedigree data

BACKGROUND

The kinship2 package is restructured from the previous kinship package. Existing features are now enhanced and new features added for handling pedigree objects.

METHODS

Pedigree plotting features have been updated to display features on complex pedigrees while adhering to pedigree plotting standards. Kinship matrices can now be calculated for the X chromosome. Other methods have been added to subset and trim pedigrees while maintaining the pedigree structure.

CONCLUSION

We make the kinship2 package available for R on the Contributed R Archives Network (CRAN), where data management is built-in and other packages can use the pedigree object.

Genome partitioning of genetic variation for complex traits using common SNPs

We estimate and partition genetic variation for height, body mass index (BMI), von Willebrand factor and QT interval (QTi) using 586,898 SNPs genotyped on 11,586 unrelated individuals. We estimate that ∼45%, ∼17%, ∼25% and ∼21% of the variance in height, BMI, von Willebrand factor and QTi, respectively, can be explained by all autosomal SNPs and a further ∼0.5-1% can be explained by X chromosome SNPs. We show that the variance explained by each chromosome is proportional to its length, and that SNPs in or near genes explain more variation than SNPs between genes. We propose a new approach to estimate variation due to cryptic relatedness and population stratification. Our results provide further evidence that a substantial proportion of heritability is captured by common SNPs, that height, BMI and QTi are highly polygenic traits, and that the additive variation explained by a part of the genome is approximately proportional to the total length of DNA contained within genes therein.

GCTA: a tool for genome-wide complex trait analysis

For most human complex diseases and traits, SNPs identified by genome-wide association studies (GWAS) explain only a small fraction of the heritability. Here we report a user-friendly software tool called genome-wide complex trait analysis (GCTA), which was developed based on a method we recently developed to address the "missing heritability" problem. GCTA estimates the variance explained by all the SNPs on a chromosome or on the whole genome for a complex trait rather than testing the association of any particular SNP to the trait. We introduce GCTA's five main functions: data management, estimation of the genetic relationships from SNPs, mixed linear model analysis of variance explained by the SNPs, estimation of the linkage disequilibrium structure, and GWAS simulation. We focus on the function of estimating the variance explained by all the SNPs on the X chromosome and testing the hypotheses of dosage compensation. The GCTA software is a versatile tool to estimate and partition complex trait variation with large GWAS data sets.

Association test for X-linked QTL in family-based designs

Family-based association methods for detecting quantitative trait loci (QTL) have been developed primarily for autosomes, and comparable methods for X-linked QTL have received less attention. We have developed a family-based association test for quantitative traits, named XQTL, which uses X-linked markers in a nuclear family design. XQTL adopts the framework of the orthogonal model implemented in the QTDT program, modifying the sex-specific score for X-linked genotypes. XQTL also takes into account the dosage effect due to female X chromosome inactivation. Restricted maximum likelihood (REML) and Fisher's scoring method are used to estimate variance components of random effects. Fixed effects, derived from the phenotypic differences among and within families, are estimated by the least-squares method. Our proposed XQTL can perform allelic and two-locus haplotypic association tests and can provide estimates of additive genetic effects and variance components. Simulation studies show correct type I error rates under the null hypothesis and robust statistical power under alternative scenarios. The loss of power observed when parental genotypes are missing can be compensated by an increase of offspring number. By treating age at onset of Parkinson disease as a quantitative trait, we illustrate our method, using MAO polymorphisms in 780 families.

Genetic variation in baboon craniofacial sexual dimorphism

Sexual dimorphism is a widespread phenomenon and contributes greatly to intraspecies variation. Despite a long history of active research, the genetic basis of dimorphism for complex traits remains unknown. Understanding the sex-specific differences in genetic architecture for cranial traits in a highly dimorphic species could identify possible mechanisms through which selection acts to produce dimorphism. Using distances calculated from three-dimensional landmark data from CT scans of 402 baboon skulls from a known genealogy, we estimated genetic variance parameters in both sexes to determine the presence of gene-by-sex (G x S) interactions and X-linked heritability. We hypothesize that traits exhibiting the greatest degree of sexual dimorphism (facial traits in baboons) will demonstrate either stronger G x S interactions or X-linked effects. We found G x S interactions and X-linked effects for a few measures that span the areas connecting the face to the neurocranium but for no traits restricted to the face. This finding suggests that facial traits will have a limited response to selection for further evolution of dimorphism in this population. We discuss the implications of our results with respect to the origins of cranial sexual dimorphism in this baboon sample, and how the genetic architecture of these traits affects their potential for future evolution.

Whole genome approaches to quantitative genetics

Apart from parent-offspring pairs and clones, relative pairs vary in the proportion of the genome that they share identical by descent. In the past, quantitative geneticists have used the expected value of sharing genes by descent to estimate genetic parameters and predict breeding values. With the possibility to genotype individuals for many markers across the genome it is now possible to empirically estimate the actual relationship between relatives. We review some of the theory underlying the variation in genetic identity, show applications to estimating genetic variance for height in humans and discuss other applications.

A model incorporating potential skewed X-inactivation in MZ girls suggests that X-linked QTLs exist for several social behaviours including autism spectrum disorder

Sex differences in the frequency and patterns of behaviours are frequently observed and largely unexplained. We have investigated the possible role of X-linked genes in the aetiology of social behaviour problems, including those involved in autistic spectrum disorders. A novel approach has been implemented. This is based on predictions following from stochastic patterns of X-inactivation of lower concordance of monozygous female (MZF) twins than MZM twins for behaviours underpinned by X-linked QTLs and the converse that DZF twins are expected to correlate more strongly for X-linked traits than DZM twins because unlike males, females always have at least one X chromosome in common. These expectations were tested in an ongoing longitudinal cohort study in which all twins born in England and Wales between 1994 and 1996 were invited to take part. 1000 each of MZF, MZM, DZF and DZM pairs from TEDS were tested at 7 and 8 years of age. The results suggest the persistent influence of X-linked genes on cognition and social behaviour problems, including those involved in autistic spectrum disorders, from early to middle childhood. This emphasises the potential importance of X-linked genes in the developmental trajectories of behaviour and mental health and the need to stratify genetic analysis of behaviours by gender.

Linkage analysis of a model quantitative trait in humans: finger ridge count shows significant multivariate linkage to 5q14.1

The finger ridge count (a measure of pattern size) is one of the most heritable complex traits studied in humans and has been considered a model human polygenic trait in quantitative genetic analysis. Here, we report the results of the first genome-wide linkage scan for finger ridge count in a sample of 2,114 offspring from 922 nuclear families. Both univariate linkage to the absolute ridge count (a sum of all the ridge counts on all ten fingers), and multivariate linkage analyses of the counts on individual fingers, were conducted. The multivariate analyses yielded significant linkage to 5q14.1 (Logarithm of odds [LOD] = 3.34, pointwise-empirical p-value = 0.00025) that was predominantly driven by linkage to the ring, index, and middle fingers. The strongest univariate linkage was to 1q42.2 (LOD = 2.04, point-wise p-value = 0.002, genome-wide p-value = 0.29). In summary, the combination of univariate and multivariate results was more informative than simple univariate analyses alone. Patterns of quantitative trait loci factor loadings consistent with developmental fields were observed, and the simple pleiotropic model underlying the absolute ridge count was not sufficient to characterize the interrelationships between the ridge counts of individual fingers.

Finger ridge count (an index of the size of the fingerprint pattern) has been used as a model trait for the study of human quantitative genetics for over 80 years. Here, we present the first genome-wide linkage scan for finger ridge count in a large sample of 2,114 offspring from 922 nuclear families. Our results illustrate the increase in power and information that can be gained from a multivariate linkage analysis of ridge counts of individual fingers as compared to a univariate analysis of a summary measure (absolute ridge count). The strongest evidence for linkage was seen at 5q14.1, and the pattern of loadings was consistent with a developmental field factor whose influence is greatest on the ring finger, falling off to either side, which is consistent with previous findings that heritability for ridge count is higher for the middle three fingers. We feel that the paper will be of specific methodological interest to those conducting linkage and association analyses with summary measures. In addition, given the frequency with which this phenotype is used as a didactic example in genetics courses we feel that this paper will be of interest to the general scientific community.

Genome partitioning of genetic variation for height from 11,214 sibling pairs

Height has been used for more than a century as a model by which to understand quantitative genetic variation in humans. We report that the entire genome appears to contribute to its additive genetic variance. We used genotypes and phenotypes of 11,214 sibling pairs from three countries to partition additive genetic variance across the genome. Using genome scans to estimate the proportion of the genomes of each chromosome from siblings that were identical by descent, we estimated the heritability of height contributed by each of the 22 autosomes and the X chromosome. We show that additive genetic variance is spread across multiple chromosomes and that at least six chromosomes (i.e., 3, 4, 8, 15, 17, and 18) are responsible for the observed variation. Indeed, the data are not inconsistent with a uniform spread of trait loci throughout the genome. Our estimate of the variance explained by a chromosome is correlated with the number of times suggestive or significant linkage with height has been reported for that chromosome. Variance due to dominance was not significant but was difficult to assess because of the high sampling correlation between additive and dominance components. Results were consistent with the absence of any large between-chromosome epistatic effects. Notwithstanding the proposed architecture of complex traits that involves widespread gene-gene and gene-environment interactions, our results suggest that variation in height in humans can be explained by many loci distributed over all autosomes, with an additive mode of gene action.

Heritability estimation of sex-specific effects on human quantitative traits

Recent studies have suggested that sex-specific genetic architecture could be because of the effects of autosomal genes that are differentially expressed in males and females. Yet, few studies have explored the effects of X-linked genes on sex-specific genetic architecture. In this study, we extended the variance component, maximum likelihood method to evaluate the relative contributions of sex-specific effects on both autosomes and the X chromosome to estimates of heritability of 20 quantitative human phenotypes in the Hutterites. Seventeen of these traits were previously analyzed in this population under a model that did not include X chromosomal effects; three traits are analyzed for the first time (age at menarche, percent fat and fat-free mass [FFM]). Seven traits (systolic blood pressure (SBP), adult height, fasting insulin, triglycerides, lipoprotein (a) [Lp(a)], serotonin, and age at menarche) showed significant X-linked effects; three of these (SBP, adult height, and triglycerides) showed X-linked effects only in males. Four traits (Lp(a), low-density lipoprotein cholesterol, ratio of percent predicted forced expiratory volume at 1 s/forced vital capacity, and FFM) showed significant sex-environment interactions, and two traits (high-density lipoprotein cholesterol and FFM) showed significant sex-specific autosomal effects. Our analyses demonstrate that sex-specific genetic effects may not only be common in human quantitative traits, but also that the X chromosome both plays a large role in these effects and has a variable influence between the sexes.

Genome-wide scan for adiposity-related phenotypes in adults from American Samoa

OBJECTIVE

To detect quantitative trait loci influencing adiposity-related phenotypes assessed by body mass index (BMI), abdominal circumference (ABDCIR), percent body fat (%BFAT) and fasting serum leptin and adiponectin using a whole genome linkage scan of families from American Samoa.

DESIGN

Family-based linkage analysis, the probands and family members were unselected for obesity.

SUBJECTS

A total of 583 phenotyped American Samoan adults, of which 578 were genotyped in 34 pedigrees.

MEASUREMENTS

A total of 377 autosomal and 18 X chromosome microsatellite markers were typed at an approximate average spacing of 10 cM spanning the genome. Multipoint LOD (logarithm of the odds) scores were calculated using variance-components approaches and SOLAR/LOKI software. The covariates simultaneously evaluated were age, sex, education, farm work and cigarette smoking, with a significance level of 0.1. Due to the stochastic nature of LOKI, we report the average of maximum LOD scores from 10 runs.

RESULTS

Significant linkage to leptin was found at 6q32.2 with LOD of 3.83. Suggestive linkage to leptin was found at 16q21:LOD=2.98, 1q42.2:LOD=1.97, 5q11.2:LOD=2.08, 12q24.23:LOD=2.00, 19p13.3:LOD=2.05; adiponectin was linked to 13q33.1-q22.1:LOD=2.41; %BFAT was linked to 16q12.2-q21, LOD=2.24; ABDCIR was linked to 16q23.1:LOD=1.95; %BFAT-adjusted leptin to 14q12, LOD=2.01; %BFAT-adjusted ABDCIR to 1q31.1, LOD=2.36, to 3q27.3-q28, LOD=2.10 and to 12p12.3, LOD=2.04.

CONCLUSION

We found strong evidence for a major locus on 6q23.2 influencing serum leptin levels in American Samoans. The 16q21 region appears to harbor a susceptibility locus that has significant pleiotrophic effects on phenotypes BMI, %BFAT, leptin and ABDCIR as shown by bivariate linkage analyses. Several other loci of varying significance were detected across the genome.

Variance component models for X-linked QTLs

This paper discusses the theory and implementation of a model for mapping X-linked quantitative trait loci (QTL). As a result of X inactivation, a female's body is subdivided into a number of patches. In each patch one of her two X chromosomes is randomly switched off. This smooths the allelic contributions in a heterozygote and implies that females should show less trait variation than males for an X-linked trait. The latest version of the genetic analysis program Mendel incorporates a simple variance component version of this model. An application to head circumference in autistic children illustrates Mendel in action.

X chromosome effects and their interactions with mitochondrial effects

We report a simple and rapid method for detecting additive genetic variance due to X-linked loci in the absence of marker data for this chromosome. We examined the interaction of this method with an established method for detecting mitochondrial linkage (another source of sex-asymmetric genetic covariance). When applied to data from the Collaborative Study on the Genetics of Alcoholism, this method found evidence of X-chromosomal linkage for one continuous trait (ntth1) and one discrete trait (SPENT). Evidence of mitochondrial contribution was found for one discrete trait (CRAVING) and three continuous traits (ln(CIGPKYR), ecb21, and tth1). Results for ntth1 suggest that methods that do not also allow for male-female heterogeneity in environmental variance may be overly conservative in detection of X-chromosomal effects.