Chris Haley

Epistasis: too often neglected in complex trait studies?

Interactions among loci or between genes and environmental factors make a substantial contribution to variation in complex traits such as disease susceptibility. Nonetheless, many studies that attempt to identify the genetic basis of complex traits ignore the possibility that loci interact. We argue that epistasis should be accounted for in complex trait studies; we critically assess current study designs for detecting epistasis and discuss how these might be adapted for use in additional populations, including humans.

A regulatory mutation in IGF2 causes a major QTL effect on muscle growth in the pig

Most traits and disorders have a multifactorial background indicating that they are controlled by environmental factors as well as an unknown number of quantitative trait loci (QTLs). The identification of mutations underlying QTLs is a challenge because each locus explains only a fraction of the phenotypic variation. A paternally expressed QTL affecting muscle growth, fat deposition and size of the heart in pigs maps to the IGF2 (insulin-like growth factor 2) region. Here we show that this QTL is caused by a nucleotide substitution in intron 3 of IGF2. The mutation occurs in an evolutionarily conserved CpG island that is hypomethylated in skeletal muscle. The mutation abrogates in vitro interaction with a nuclear factor, probably a repressor, and pigs inheriting the mutation from their sire have a threefold increase in IGF2 messenger RNA expression in postnatal muscle. Our study establishes a causal relationship between a single-base-pair substitution in a non-coding region and a QTL effect. The result supports the long-held view that regulatory mutations are important for controlling phenotypic variation.

QTL Express mapping quantitative trait loci in simple and complex pedigrees

QTL Express is the first application for Quantitative Trait Locus (QTL) mapping in outbred populations with a web-based user interface. User input of three files containing a marker map, trait data and marker genotypes allows mapping of single or multiple QTL by the regression approach, with the option to perform permutation or bootstrap tests.

THE PIGMAP CONSORTIUM LINKAGE MAP OF THE PIG (SUS SCROFA).

A linkage map of the porcine genome has been developed by segregation analysis of 239 genetic markers. Eighty-one of these markers correspond to known genes. Linkage groups have been assigned to all 18 autosomes plus the X Chromosome (Chr). As 69 of the markers on the linkage map have also been mapped physically (by others), there is significant integration of linkage and physical map data. Six informative markers failed to show linkage to these maps. As in other species, the genetic map of the heterogametic sex (male) was significantly shorter (∼16.5 Morgans) than the genetic map of the homogametic sex (female) (∼21.5 Morgans). The sex-averaged genetic map of the pig was estimated to be ∼18 Morgans in length. Mapping information for 61 Type I loci (genes) enhances the contribution of the pig gene map to comparative gene mapping. Because the linkage map incorporates both highly polymorphic Type II loci, predominantly microsatellites, and Type I loci, it will be useful both for large experiments to map quantitative trait loci and for the subsequent isolation of trait genes following a comparative and candidate gene approach.

Major quantitative trait loci affect resistance to infectious pancreatic necrosis in Atlantic salmon (Salmo salar).

Infectious pancreatic necrosis (IPN) is a viral disease currently presenting a major problem in the production of Atlantic salmon (Salmon salar). IPN can cause significant mortality to salmon fry within freshwater hatcheries and to smolts following transfer to seawater, although challenged populations show clear genetic variation in resistance. To determine whether this genetic variation includes loci of major effect, a genomewide quantitative trait loci (QTL) scan was performed within 10 full-sib families that had received a natural seawater IPN challenge. To utilize the large difference between Atlantic salmon male and female recombination rates, a two-stage mapping strategy was employed. Initially, a sire-based QTL analysis was used to detect linkage groups with significant effects on IPN resistance, using two to three microsatellite markers per linkage group. A dam-based analysis with additional markers was then used to confirm and position any detected QTL. Two genomewide significant QTL and one suggestive QTL were detected in the genome scan. The most significant QTL was mapped to linkage group 21 and was significant at the genomewide level in both the sire and the dam-based analyses. The identified QTL can be applied in marker-assisted selection programs to improve the resistance of salmon to IPN and reduce disease-related mortality.

Detecting epistasis in human complex traits

Genome-wide association studies (GWASs) have become the focus of the statistical analysis of complex traits in humans, successfully shedding light on several aspects of genetic architecture and biological aetiology. Single-nucleotide polymorphisms (SNPs) are usually modelled as having additive, cumulative and independent effects on the phenotype. Although evidently a useful approach, it is often argued that this is not a realistic biological model and that epistasis (that is, the statistical interaction between SNPs) should be included. The purpose of this Review is to summarize recent directions in methodology for detecting epistasis and to discuss evidence of the role of epistasis in human complex trait variation. We also discuss the relevance of epistasis in the context of GWASs and potential hazards in the interpretation of statistical interaction terms.

Fine mapping of trypanosomiasis resistance loci in murine advanced intercross lines

Abstract. We have previously reported the results of genome-wide searches in two murine F2 populations for QTLs that influence survival following Trypanosoma congolense infection. Three loci, Tir1, Tir2, and Tir3, were identified and mapped to mouse Chromosomes (Chrs) 17, 5, and 1 respectively, with confidence intervals (CIs) in the range 10–40 cM. The size of these CIs is to a large degree the consequence of limited numbers of recombination events in small chromosomal regions in F2 populations. A number of population designs have been proposed to increase recombination levels in crosses, one of which is the advanced intercross line (AIL). Here we report fine mapping of Tir1, Tir2, and Tir3 in G6 populations of two independent murine AILs created by crossing the C57BL/6J strain with the A/J and BALB/cJ strains, respectively. Data were analyzed by two methods that gave equally informative and similar results. The three QTLs were confirmed in the A/J × C57BL/6J AIL and in the combined data set, but Tir2 was apparently lost from the BALB/cJ × C57BL/6J AIL. The reduction in CIs for the Tir loci ranged from 2.5 to more than ten-fold in G6 populations by comparison with CIs obtained previously in the equivalent F2 generations. Mapping in the AILs also resolved the Tir3 locus into three trypanosomiasis resistance QTLs, revealing a degree of complexity not evident in extensive studies at the F2 level.

A simple and rapid method for calculating identity-by-descent matrices using multiple markers

A fast, partly recursive deterministic method for calculating Identity-by-Descent (IBD) probabilities was developed with the objective of using IBD in Quantitative Trait Locus (QTL) mapping. The method combined a recursive method for a single marker locus with a method to estimate IBD between sibs using multiple markers. Simulated data was used to compare the deterministic method developed in the present paper with a stochastic method (LOKI) for precision in estimating IBD probabilities and performance in the task of QTL detection with the variance component approach. This comparison was made in a variety of situations by varying family size and degree of polymorphism among marker loci. The following were observed for the deterministic method relative to MCMC: (i) it was an order of magnitude faster; (ii) its estimates of IBD probabilities were found to agree closely, even though it does not extract information when haplotypes are not known with certainty; (iii) the shape of the profile for the QTL test statistic as a function of location was similar, although the magnitude of the test statistic was slightly smaller; and (iv) the estimates of QTL variance was similar. It was concluded that the method proposed provided a rapid means of calculating the IBD matrix with only a small loss in precision, making it an attractive alternative to the use of stochastic MCMC methods. Furthermore, developments in marker technology providing denser maps would enhance the relative advantage of this method.

Multiple marker mapping of quantitative trait loci in an outbred pedigree of loblolly pine

Abstract A multiple marker least squares approach is presented for the analysis of a single three-generation pedigree for quantitative trait locus (QTL) characterisation. It is an extension of the approach by Haley et al. (1994) to the situation where grandparents cannot be assumed to be homozygous at QTLs for the trait of interest. The method is applied to the analysis of wood specific gravity in loblolly pine (Pinus taeda L.). Within a similar framework, a series of preliminary analyses are carried out, followed by a more detailed search of the genome for one or more QTLs. The preliminary analyses provide information about whether the contribution from each linkage group appears to be polygenic, localised to a small region (e.g. a single QTL) or oligogenic (i.e. several QTLs). Significance levels are obtained using a permutation test that uses the observed phenotypes and marker genotypes. The conclusion of these analyses is that in this pedigree single QTLs with very large effect on wood specific gravity do not appear to be segregating, although there is evidence for QTLs with small effect. Finally, in order to assess the potential power of this pedigree, we simulated QTLs within the framework of the actual marker data. As expected, QTL effects would need to be large to be reliably detected in this study, and the power to detect QTLs varies at different positions in the genome depending on the level of information in the local markers.

MAPPING QTLS FOR BINARY TRAITS IN BACKCROSS AND F2 POPULATIONS

Mapping quantitative trait loci (QTLs) for binary traits in backcross and F-2 populations was investigated using stochastic stimulation. Data were analysed using either linear regression or a generalized linear model. Parameters which were varied in the simulations were the population size (200 and 500), heritability in the backcross or F-2 population (0.01, 0.05, 0.10), marker spacing (10 and 20 cM) and the incidence of the trait (0.50, 0.25, 0.10). The methods gave very similar results in terms of estimates of the QTL location and QTL effects and power of QTL detection, and it was concluded that in practice treating the zero-one data as continuous and using standard linear regression was efficient.