Assumption-Free Estimation of Heritability from Genome-Wide Identity-by-Descent Sharing between Full Siblings

The study of continuously varying, quantitative traits is important in evolutionary biology, agriculture, and medicine. Variation in such traits is attributable to many, possibly interacting, genes whose expression may be sensitive to the environment, which makes their dissection into underlying causative factors difficult. An important population parameter for quantitative traits is heritability, the proportion of total variance that is due to genetic factors. Response to artificial and natural selection and the degree of resemblance between relatives are all a function of this parameter. Following the classic paper by R. A. Fisher in 1918, the estimation of additive and dominance genetic variance and heritability in populations is based upon the expected proportion of genes shared between different types of relatives, and explicit, often controversial and untestable models of genetic and non-genetic causes of family resemblance. With genome-wide coverage of genetic markers it is now possible to estimate such parameters solely within families using the actual degree of identity-by-descent sharing between relatives. Using genome scans on 4,401 quasi-independent sib pairs of which 3,375 pairs had phenotypes, we estimated the heritability of height from empirical genome-wide identity-by-descent sharing, which varied from 0.374 to 0.617 (mean 0.498, standard deviation 0.036). The variance in identity-by-descent sharing per chromosome and per genome was consistent with theory. The maximum likelihood estimate of the heritability for height was 0.80 with no evidence for non-genetic causes of sib resemblance, consistent with results from independent twin and family studies but using an entirely separate source of information. Our application shows that it is feasible to estimate genetic variance solely from within-family segregation and provides an independent validation of previously untestable assumptions. Given sufficient data, our new paradigm will allow the estimation of genetic variation for disease susceptibility and quantitative traits that is free from confounding with non-genetic factors and will allow partitioning of genetic variation into additive and non-additive components

Haplotype Analysis Reveals a Possible Founder Effect of RET Mutation R114H for Hirschsprung's Disease in the Chinese Population

Background Hirschsprung's disease (HSCR) is a congenital disorder associated with the lack of intramural ganglion cells in the myenteric and sub-mucosal plexuses along varying segments of the gastrointestinal tract. The RET gene is the major gene implicated in this gastrointestinal disease. A highly recurrent mutation in RET (RETR114H) has recently been identified in ~6-7% of the Chinese HSCR patients which, to date, has not been found in Caucasian patients or controls nor in Chinese controls. Due to the high frequency of RETR114H in this population, we sought to investigate whether this mutation may be a founder HSCR mutation in the Chinese population. Methodology and Principal Findings To test whether all RETR114H were originated from a single mutational event, we predicted the approximate age of RETR114H by applying a Bayesian method to RET SNPs genotyped in 430 Chinese HSCR patients (of whom 25 individuals had the mutation) to be between 4-23 generations old depending on growth rate. We reasoned that if RETR114H was a founder mutation then those with the mutation would share a haplotype on which the mutation resides. Including SNPs spanning 509.31 kb across RET from a recently obtained 500 K genome-wide dataset for a subset of 181 patients (14 RETR114H patients), we applied haplotype estimation methods to determine whether there were any segments shared between patients with RETR114H that are not present in those without the mutation or controls. Analysis yielded a 250.2 kb (51 SNP) shared segment over the RET gene (and downstream) in only those patients with the mutation with no similar segments found among other patients. Conclusions This suggests that RETR114H is a founder mutation for HSCR in the Chinese population. © 2010 Cornes et al.published_or_final_versio

Genetic influences on exercise participation in 37.051 twin pairs from seven countries

Background. A sedentary lifestyle remains a major threat to health in contemporary societies. To get more insight in the relative contribution of genetic and environmental influences on individual differences in exercise participation, twin samples from seven countries participating in the GenomEUtwin project were used. Methodology. Self-reported data on leisure time exercise behavior from Australia, Denmark, Finland, Norway, the Netherlands, Sweden and United Kingdom were used to create a comparable index of exercise participation in each country (60 minutes weekly at a minimum intensity of four metabolic equivalents). Principal Findings. Modest geographical variation in exercise participation was revealed in 85,198 subjects, aged 19-40 years. Modeling of monozygotic and dizygotic twin resemblance showed that genetic effects play an important role in explaining individual differences in exercise participation in each country. Shared environmental effects played no role except for Norwegian males. Heritability of exercise participation in males and females was similar and ranged from 48% to 71% (excluding Norwegian males). Conclusions. Genetic variation is important in individual exercise behavior and may involve genes influencing the acute mood effects of exercise, high exercise ability, high weight loss ability, and personality. This collaborative study suggests that attempts to find genes influencing exercise participation can pool exercise data across multiple countries and different instruments.Background. A sedentary lifestyle remains a major threat to health in contemporary societies. To get more insight in the relative contribution of genetic and environmental influences on individual differences in exercise participation, twin samples from seven countries participating in the GenomEUtwin project were used. Methodology. Self-reported data on leisure time exercise behavior from Australia, Denmark, Finland, Norway, the Netherlands, Sweden and United Kingdom were used to create a comparable index of exercise participation in each country (60 minutes weekly at a minimum intensity of four metabolic equivalents). Principal Findings. Modest geographical variation in exercise participation was revealed in 85,198 subjects, aged 19-40 years. Modeling of monozygotic and dizygotic twin resemblance showed that genetic effects play an important role in explaining individual differences in exercise participation in each country. Shared environmental effects played no role except for Norwegian males. Heritability of exercise participation in males and females was similar and ranged from 48% to 71% (excluding Norwegian males). Conclusions. Genetic variation is important in individual exercise behavior and may involve genes influencing the acute mood effects of exercise, high exercise ability, high weight loss ability, and personality. This collaborative study suggests that attempts to find genes influencing exercise participation can pool exercise data across multiple countries and different instruments.Background. A sedentary lifestyle remains a major threat to health in contemporary societies. To get more insight in the relative contribution of genetic and environmental influences on individual differences in exercise participation, twin samples from seven countries participating in the GenomEUtwin project were used. Methodology. Self-reported data on leisure time exercise behavior from Australia, Denmark, Finland, Norway, the Netherlands, Sweden and United Kingdom were used to create a comparable index of exercise participation in each country (60 minutes weekly at a minimum intensity of four metabolic equivalents). Principal Findings. Modest geographical variation in exercise participation was revealed in 85,198 subjects, aged 19-40 years. Modeling of monozygotic and dizygotic twin resemblance showed that genetic effects play an important role in explaining individual differences in exercise participation in each country. Shared environmental effects played no role except for Norwegian males. Heritability of exercise participation in males and females was similar and ranged from 48% to 71% (excluding Norwegian males). Conclusions. Genetic variation is important in individual exercise behavior and may involve genes influencing the acute mood effects of exercise, high exercise ability, high weight loss ability, and personality. This collaborative study suggests that attempts to find genes influencing exercise participation can pool exercise data across multiple countries and different instruments.Peer reviewe

RET Mutational Spectrum in Hirschsprung Disease: Evaluation of 601 Chinese Patients

Rare (RVs) and common variants of the RET gene contribute to Hirschsprung disease (HSCR; congenital aganglionosis). While RET common variants are strongly associated with the commonest manifestation of the disease (males; short-segment aganglionosis; sporadic), rare coding sequence (CDS) variants are more frequently found in the lesser common and more severe forms of the disease (females; long/total colonic aganglionosis; familial)

Genome-Wide Meta-Analysis of Five Asian Cohorts Identifies PDGFRA as a Susceptibility Locus for Corneal Astigmatism

Corneal astigmatism refers to refractive abnormalities and irregularities in the curvature of the cornea, and this interferes with light being accurately focused at a single point in the eye. This ametropic condition is highly prevalent, influences visual acuity, and is a highly heritable trait. There is currently a paucity of research in the genetic etiology of corneal astigmatism. Here we report the results from five genome-wide association studies of corneal astigmatism across three Asian populations, with an initial discovery set of 4,254 Chinese and Malay individuals consisting of 2,249 cases and 2,005 controls. Replication was obtained from three surveys comprising of 2,139 Indians, an additional 929 Chinese children, and an independent 397 Chinese family trios. Variants in PDGFRA on chromosome 4q12 (lead SNP: rs7677751, allelic odds ratio = 1.26 (95% CI: 1.16–1.36), Pmeta = 7.87×10−9) were identified to be significantly associated with corneal astigmatism, exhibiting consistent effect sizes across all five cohorts. This highlights the potential role of variants in PDGFRA in the genetic etiology of corneal astigmatism across diverse Asian populations

Insights into the Genetic Architecture of Early Stage Age-Related Macular Degeneration: A Genome-Wide Association Study Meta-Analysis

10.1371/journal.pone.0053830PLoS ONE81

A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data

Background: Rare variants have gathered increasing attention as a possible alternative source of missing heritability. Since next generation sequencing technology is not yet cost-effective for large-scale genomic studies, a widely used alternative approach is imputation. However, the imputation approach may be limited by the low accuracy of the imputed rare variants. To improve imputation accuracy of rare variants, various approaches have been suggested, including increasing the sample size of the reference panel, using sequencing data from study-specific samples (i.e., specific populations), and using local reference panels by genotyping or sequencing a subset of study samples. While these approaches mainly utilize reference panels, imputation accuracy of rare variants can also be increased by using exome chips containing rare variants. The exome chip contains 250 K rare variants selected from the discovered variants of about 12,000 sequenced samples. If exome chip data are available for previously genotyped samples, the combined approach using a genotype panel of merged data, including exome chips and SNP chips, should increase the imputation accuracy of rare variants. Results: In this study, we describe a combined imputation which uses both exome chip and SNP chip data simultaneously as a genotype panel. The effectiveness and performance of the combined approach was demonstrated using a reference panel of 848 samples constructed using exome sequencing data from the T2D-GENES consortium and 5,349 sample genotype panels consisting of an exome chip and SNP chip. As a result, the combined approach increased imputation quality up to 11 %, and genomic coverage for rare variants up to 117.7 % (MAF < 1 %), compared to imputation using the SNP chip alone. Also, we investigated the systematic effect of reference panels on imputation quality using five reference panels and three genotype panels. The best performing approach was the combination of the study specific reference panel and the genotype panel of combined data. Conclusions: Our study demonstrates that combined datasets, including SNP chips and exome chips, enhances both the imputation quality and genomic coverage of rare variants