Regional heritability mapping method helps explain missing heritability of blood lipid traits in isolated populations.

Single single-nucleotide polymorphism (SNP) genome-wide association studies (SSGWAS) may fail to identify loci with modest effects on a trait. The recently developed regional heritability mapping (RHM) method can potentially identify such loci. In this study, RHM was compared with the SSGWAS for blood lipid traits (high-density lipoprotein (HDL), low-density lipoprotein (LDL), plasma concentrations of total cholesterol (TC) and triglycerides (TG)). Data comprised 2246 adults from isolated populations genotyped using ∼300 000 SNP arrays. The results were compared with large meta-analyses of these traits for validation. Using RHM, two significant regions affecting HDL on chromosomes 15 and 16 and one affecting LDL on chromosome 19 were identified. These regions covered the most significant SNPs associated with HDL and LDL from the meta-analysis. The chromosome 19 region was identified in our data despite the fact that the most significant SNP in the meta-analysis (or any SNP tagging it) was not genotyped in our SNP array. The SSGWAS identified one SNP associated with HDL on chromosome 16 (the top meta-analysis SNP) and one on chromosome 10 (not reported by RHM or in the meta-analysis and hence possibly a false positive association). The results further confirm that RHM can have better power than SSGWAS in detecting causal regions including regions containing crucial ungenotyped variants. This study suggests that RHM can be a useful tool to explain some of the 'missing heritability' of complex trait variation.

Variation and covariation in strongyle infection in East African shorthorn zebu calves.

Parasite burden varies widely between individuals within a population, and can covary with multiple aspects of individual phenotype. Here we investigate the sources of variation in faecal strongyle eggs counts, and its association with body weight and a suite of haematological measures, in a cohort of indigenous zebu calves in Western Kenya, using relatedness matrices reconstructed from single nucleotide polymorphism (SNP) genotypes. Strongyle egg count was heritable (h(2) = 23.9%, s.e. = 11.8%) and we also found heritability of white blood cell counts (WBC) (h(2) = 27.6%, s.e. = 10.6%). All the traits investigated showed negative phenotypic covariances with strongyle egg count throughout the first year: high worm counts were associated with low values of WBC, red blood cell count, total serum protein and absolute eosinophil count. Furthermore, calf body weight at 1 week old was a significant predictor of strongyle EPG at 16-51 weeks, with smaller calves having a higher strongyle egg count later in life. Our results indicate a genetic basis to strongyle EPG in this population, and also reveal consistently strong negative associations between strongyle infection and other important aspects of the multivariate phenotype.

Effect of the Texel muscling QTL (TM-QTL) on spine characteristics in purebred Texel lambs.

Previous work showed that the Texel muscling QTL (TM-QTL) results in pronounced hypertrophy in the loin muscle, with the largest phenotypic effects observed in lambs inheriting a single copy of the allele from the sire. As the loin runs parallel to the spinal vertebrae, and the development of muscle and bone are closely linked, the primary aim of this study was to investigate if there were any subsequent associations between TM-QTL inheritance and underlying spine characteristics (vertebrae number, VN; spine region length, SPL; average length of individual vertebrae, VL) of the thoracic, lumbar, and thoracolumbar spine regions. Spine characteristics were measured from X-ray computed tomography (CT) scans for 142 purebred Texel lambs which had been previously genotyped. Least-squares means were significantly different between genotype groups for lumbar and thoracic VN and lumbar SPL. Similarly for these traits, contrasts were shown to be significant for particular modes of gene action but overall were inconclusive. In general, the results showed little evidence that spine trait phenotypes were associated with differences in loin muscling associated with the different TM-QTL genotypes.

Genetic linkage analysis identifies Pas1 as the common locus modulating lung tumorigenesis and acute inflammatory response in mice.

Selective breeding for the acute inflammatory response (AIR) generated two mouse lines characterized by maximum (AIRmax) and minimum (AIRmin) responses, explained by the additive effect of alleles differentially fixed in quantitative trait loci (QTLs). These mice also differ in their susceptibility to lung tumorigenesis, raising the possibility that the same loci are involved in the control of both phenotypes. To map the QTLs responsible for the different phenotypes, we carried out a genome-wide linkage analysis using single-nucleotide polymorphism arrays in a pedigree consisting of 802 mice, including 693 (AIRmax × AIRmin)F2 intercross mice treated with urethane and phenotyped for AIR and lung tumor multiplicity. We mapped five loci on chromosomes 4, 6, 7, 11 and 13 linked to AIR (logarithm of odds (LOD)=3.56, 3.52, 15.74, 7.74 and 3.34, respectively) and two loci linked to lung tumor multiplicity, on chromosomes 6 and 18 (LOD=12.18 and 4.69, respectively). The known pulmonary adenoma susceptibility 1 (Pas1) locus on chromosome 6 was the only locus linked to both phenotypes, suggesting that alleles of this locus were differentially fixed during breeding and selection of AIR mice. These results represent a step toward understanding the link between inflammation and cancer.

Optimal use of regression models in genome-wide association studies.

The performance of linear regression models in genome-wide association studies is influenced by how marker information is parameterized in the model. Considering the impact of parameterization is especially important when using information from multiple markers to test for association. Properties of the population, such as linkage disequilibrium (LD) and allele frequencies, will also affect the ability of a model to provide statistical support for an underlying quantitative trait locus (QTL). Thus, for a given location in the genome, the relationship between population properties and model parameterization is expected to influence the performance of the model in providing evidence for the position of a QTL. As LD and allele frequencies vary throughout the genome and between populations, understanding the relationship between these properties and model parameterization is of considerable importance in order to make optimal use of available genomic data. Here, we evaluate the performance of regression-based association models using genotype and haplotype information across the full spectrum of allele frequency and LD scenarios. Genetic marker data from 200 broiler chickens were used to simulate genomic conditions by selecting individual markers to act as surrogate QTL (sQTL) and then investigating the ability of surrounding markers to estimate sQTL genotypes and provide statistical support for their location. The LD and allele frequencies of markers and sQTL are shown to have a strong effect on the performance of models relative to one another. Our results provide an indication of the best choice of model parameterization given certain scenarios of marker and QTL LD and allele frequencies. We demonstrate a clear advantage of haplotype-based models, which account for phase uncertainty over other models tested, particularly for QTL with low minor allele frequencies. We show that the greatest advantage of haplotype models over single-marker models occurs when LD between markers and the causal locus is low. Under these situations, haplotype models have a greater accuracy of predicting the location of the QTL than other models tested.

Complex traits analysis of chicken growth using targeted genetical genomics.

Dissecting the genetic control of complex trait variation remains very challenging, despite many advances in technology. The aim of this study was to use a major growth quantitative trait locus (QTL) in chickens mapped to chromosome 4 as a model for a targeted approach to dissect the QTL. We applied a variant of the genetical genomics approach to investigate genome-wide gene expression differences between two contrasting genotypes of a marked QTL. This targeted approach allows the direct quantification of the link between the genotypes and the genetic responses, thus narrowing the QTL-phenotype gap using fewer samples (i.e. microarrays) compared with the genome-wide genetical genomics studies. Four differentially expressed genes were localized under the region of the QTL. One of these genes is a potential positional candidate gene (AADAT) that affects lysine and tryptophan metabolism and has alternative splicing variants between the two genotypes. In addition, the lysine and glycolysis metabolism pathways were significantly enriched for differentially expressed genes across the genome. The targeted approach provided a complementary route to fine mapping of QTL by characterizing the local and the global downstream effects of the QTL and thus generating further hypotheses about the action of that QTL.

Bone mineral density QTL at sexual maturity and end of lay.

1. An F2 cross of a broiler male line and a White Leghorn layer line was used to identify quantitative trait loci (QTL) for bone density at the onset of lay and at the end of the laying period. A total of 686 measures of humeral bone density were available for analysis. 2. There was no evidence for epistasis. 3. Genome-wide significant QTL for bone density at the onset of lay were identified on chromosomes 1 (311 cM) and 8 (2 cM) and on chromosomes 1 (311 cM), 3 (57 cM) and 8 (2 cM) with a covariate for the number of yellow follicles (a proxy for the concentration of circulating oestrogen). 4. Evidence for only 4 chromosome-wide suggestive QTL were detected at the end of lay (72 weeks). 5. Analysis of the combined data confirmed two genome-wide suggestive QTL on chromosome 1 (137 and 266 cM) and on chromosomes 8 (2 cM) and 9 (10 cM) in analyses with or without the covariate. 6. Positive QTL alleles came from the broiler line with the exception of 2 suggestive QTL at the onset of lay on chromosomes 3 and 5 in an analysis with the covariate. 7. In general, QTL acted additively, except that dominant effects were identified for three suggestive QTL at the onset of lay on chromosomes 3 (57 and 187 cM) and 5 (9 cM). 8. The significant QTL in this study were at similar locations to QTL identified in a range of crosses in other publications, suggesting that they are prime candidates for the search for genes and mutations that could be used as selection criteria to improve bone strength and decrease fractures in commercial laying hens.

Overlap of quantitative trait loci for early growth rate, and for body weight and age at onset of sexual maturity in chickens.

Critical age, weight and body composition have been suggested as necessary correlates of sexual maturity. A genome scan to identify quantitative trait loci (QTL) for age and body weight at first egg (AFE and WFE) was conducted on 912 birds from an F(2) broiler-layer cross using 106 microsatellite markers. Without a covariate, QTL for body WFE were detected on chromosomes 2, 4, 8, 27 and Z and a single QTL for AFE was detected on chromosome 2. With AFE as a covariate, additional QTL for body WFE were found on chromosomes 1 and 13, with abdominal fat pad as covariate a QTL for body WFE was found on chromosome 1. With body WFE as covariate, additional QTL for AFE were found on chromosomes 1, 3, 4, 13 and 27. The QTL generally acted additively and there was no evidence for epistasis. Consistent with the original line differences, broiler alleles had positive effects on body WFE and negative effects on AFE, whereas the phenotypic correlation between the two traits was positive. The mapped QTL for body WFE cumulatively accounted for almost half the body weight difference between the chicken lines at puberty. Overlapping QTL for body WFE and body weight to 9 weeks of age indicate that most QTL affecting growth rate also affect body WFE. The co-localisation of QTL for body weight, growth and sexual maturity suggests that body weight and growth rate are closely related to the attainment of sexual maturity and that the genetic determination of growth rate has correlated effects on puberty.

The quantitative genetic basis of sex ratio variation in Nasonia vitripennis: a QTL study.

Our understanding of how natural selection should shape sex allocation is perhaps more developed than for any other trait. However, this understanding is not matched by our knowledge of the genetic basis of sex allocation. Here, we examine the genetic basis of sex ratio variation in the parasitoid wasp Nasonia vitripennis, a species well known for its response to local mate competition (LMC). We identified a quantitative trait locus (QTL) for sex ratio on chromosome 2 and three weaker QTL on chromosomes 3 and 5. We tested predictions that genes associated with sex ratio should be pleiotropic for other traits by seeing if sex ratio QTL co-occurred with clutch size QTL. We found one clutch size QTL on chromosome 1, and six weaker QTL across chromosomes 2, 3 and 5, with some overlap to regions associated with sex ratio. The results suggest rather limited scope for pleiotropy between these traits.

Controlling false positives in the mapping of epistatic QTL.

This study addresses the poorly explored issue of the control of false positive rate (FPR) in the mapping of pair-wise epistatic quantitative trait loci (QTL). A nested test framework was developed to (1) allow pre-identified QTL to be used directly to detect epistasis in one-dimensional genome scans, (2) to detect novel epistatic QTL pairs in two-dimensional genome scans and (3) to derive genome-wide thresholds through permutation and handle multiple testing. We used large-scale simulations to evaluate the performance of both the one- and two-dimensional approaches in mapping different forms and levels of epistasis and to generate profiles of FPR, power and accuracy to inform epistasis mapping studies. We showed that the nested test framework and genome-wide thresholds were essential to control FPR at the 5% level. The one-dimensional approach was generally more powerful than the two-dimensional approach in detecting QTL-associated epistasis and identified nearly all epistatic pairs detected from the two-dimensional approach. However, only the two-dimensional approach could detect epistatic QTL with weak main effects. Combining the two approaches allowed effective mapping of different forms of epistasis, whereas using the nested test framework kept the FPR under control. This approach provides a good search engine for high-throughput epistasis analyses.

Genetic mapping of quantitative trait loci for growth and fatness in pigs.

The European wild boar was crossed with the domesticated Large White pig to genetically dissect phenotypic differences between these populations for growth and fat deposition. The most important effects were clustered on chromosome 4, with a single region accounting for a large part of the breed difference in growth rate, fatness, and length of the small intestine. The study is an advance in genome analyses and documents the usefulness of crosses between divergent outbred populations for the detection and characterization of quantitative trait loci. The genetic mapping of a major locus for fat deposition in the pig could have implications for understanding human obesity.

Thermodynamic investigations of ternary liquid alloys.

A review of different methods for determining thermodynamic quantities is given. The electromotive force (EMF) method with a liquid and solid electrolyte, the calorimetric and differential scanning calorimetry (DSC) methods, and vapour pressure experiments like the isopiestic and Knudsen effusion methods are discussed.

Rams with poor feed efficiency are highly responsive to an exogenous adrenocorticotropin hormone (ACTH) challenge.

An animal's response to a stressor is to increase metabolic rate, and thus energy consumption through the activation of the hypothalamic-pituitary-adrenal axis. Changes to energy use by an animal are likely to influence the efficiency with which it is utilised. In this study, we tested the hypothesis that less efficient sheep are more responsive to exogenous administration of adrenocorticotropin hormone. This was done by firstly determining the appropriate dose (0.4, 1.6 or 6.4microg/kg LW) and peak serum cortisol response time (45min) to exogenous administration of adrenocorticotropin hormone in a pilot study (n=3 sheep). Following this, adrenocorticotropin hormone (2.0microg/kg LW) stimulated cortisol levels were measured in a larger group of sheep (n=50) of known feed efficiency (feed conversion ratio and residual feed intake values). Less efficient sheep (more positive residual feed intake values) were found to have a greater (P<0.001) increase in cortisol concentration in comparison to more efficient animals. Those sheep which had higher levels of cortisol also had a greater proportion (P<0.001) of fat tissue. These data clearly demonstrated that efficiency of energy use, when measured as residual feed intake, is significantly related to an animal's stress response. These findings have important implications for understanding the physiological mechanisms underpinning efficiency of energy use, and may be useful in successfully identifying animals which are superior in terms of feed efficiency.

Prediction of intramuscular fat content and shear force in Texel lamb loins using combinations of different X-ray computed tomography (CT) scanning techniques.

Computed tomography (CT) parameters, including spiral computed tomography scanning (SCTS) parameters, intramuscular fat (IMF) and mechanically measured shear force were derived from two previously published studies. Purebred Texel (n = 377) of both sexes, females (n = 206) and intact males (n = 171) were used to investigate the prediction of IMF and shear force in the loin. Two and three dimensional CT density information was available. Accuracies in the prediction of shear force and IMF ranged from R2 0.02 to R2 0.13 and R2 0.51 to R2 0.71 respectively, using combinations of SCTS and CT scan information. The prediction of mechanical shear force could not be achieved at an acceptable level of accuracy employing SCTS information. However, the prediction of IMF in the loin employing information from SCTS and additional information from standard CT scans was successful, providing evidence that the prediction of IMF and related meat eating quality (MEQ) traits for Texel lambs in vivo can be achieved.

The influence of folic acid depletion on the Nucleotide Excision Repair capacity of human dermal fibroblasts measured by a modified Host Cell Reactivation Assay.

Animal and human studies have shown that low levels of folic acid are associated with an impaired DNA Repair Capacity (DRC) and an increased cancer risk. However, the molecular evidence that folic acid enhances the DRC of cultured human cells is still limited because of a paucity of in vitro studies. We investigated the effect of folic acid depletion in vitro on the DRC of human dermal fibroblasts derived from 17 donors of different ages. To assess the cellular Nucleotide Excision DRC, we used a modified Host Cell-Reactivation Assay (HCRA), adapted to the Fluorescence Activated Cell Sorting (FACS)-technology, which is highly sensitive in comparison to luminometer-technology and allows single cell based analysis. We used DsRed as a reporter (irradiated with UVC light) and pEGFP to control the performance of the transformations. Folic acid had a statistically significant effect on the DRC in all of the 17 donors, however, the levels varied considerably between individuals (2.0-19.6%). When the effect of folic acid substituted on the DRC was compared to donor age, we observed that there was less DNA repair in old donors compared to the younger donors, although this was only significant at lower levels.

Maximum likelihood mapping of quantitative trait loci using full-sib families.

A maximum likelihood method is presented for the detection of quantitative trait loci (QTL) using flanking markers in full-sib families. This method incorporates a random component for common family effects due to additional QTL or the environment. Simulated data have been used to investigate this method. With a fixed total number of full sibs power of detection decreased substantially with decreasing family size. Increasing the number of alleles at the marker loci (i.e., polymorphism information content) and decreasing the interval size about the QTL increased power. Flanking markers were more powerful than single markers. In testing for a linked QTL the test must be made against a model which allows for between family variation (i.e., including an unlinked QTL or a between family variance component) or the test statistic may be grossly inflated. Mean parameter estimates were close to the simulated values in all situations when fitting the full model (including a linked QTL and common family effect). If the common family component was omitted the QTL effect was overestimated in data in which additional genetic variance was simulated and when compared with an unlinked QTL model there was reduced power. The test statistic curves, reflecting the likelihood of the QTL at each position along the chromosome, have discontinuities at the markers caused by adjacent pairs of markers providing different amounts of information. This must be accounted for when using flanking markers to search for a QTL in an outbred population.

Multitrait least squares for quantitative trait loci detection.

A multiple-trait QTL mapping method using least squares is described. It is presented as an extension of a single-trait method for use with three-generation, outbred pedigrees. The multiple-trait framework allows formal testing of whether the same QTL affects more than one trait (i.e., a pleiotropic QTL) or whether more than one linked QTL are segregating. Several approaches to the testing procedure are presented and their suitability discussed. The performance of the method is investigated by simulation. As previously found, multitrait analyses increase the power to detect a pleiotropic QTL and the precision of its location estimate. With enough information, discrimination between alternative genetic models is possible.

Mapping quantitative trait loci in crosses between outbred lines using least squares.

The use of genetic maps based upon molecular markers has allowed the dissection of some of the factors underlying quantitative variation in crosses between inbred lines. For many species crossing inbred lines is not a practical proposition, although crosses between genetically very different outbred lines are possible. Here we develop a least squares method for the analysis of crosses between outbred lines which simultaneously uses information from multiple linked markers. The method is suitable for crosses where the lines may be segregating at marker loci but can be assumed to be fixed for alternative alleles at the major quantitative trait loci (QTLs) affecting the traits under analysis (e.g., crosses between divergent selection lines or breeds with different selection histories). The simultaneous use of multiple markers from a linkage group increases the sensitivity of the test statistic, and thus the power for the detection of QTLs, compared to the use of single markers or markers flanking an interval. The gain is greater for more closely spaced markers and for markers of lower information content. Use of multiple markers can also remove the bias in the estimated position and effect of a QTL which may result when different markers in a linkage group vary in their heterozygosity in the F1 (and thus in their information content) and are considered only singly or a pair at a time. The method is relatively simple to apply so that more complex models can be fitted than is currently possible by maximum likelihood. Thus fixed effects of background genotype can be fitted simultaneously with the exploration of a single linkage group which will increase the power to detect QTLs by reducing the residual variance. More complex models with several QTLs in the same linkage group and two-locus interactions between QTLs can similarly be examined. Thus least squares provides a powerful tool to extend the range of crosses from which QTLs can be dissected whilst at the same time allowing flexible and realistic models to be explored.

Quantitative trait loci affecting body weight and fatness from a mouse line selected for extreme high growth.

Quantitative trait loci (QTL) influencing body weight were mapped by linkage analysis in crosses between a high body weight selected line (DU6) and a control line (DUKs). The two mouse lines differ in body weight by 106% and in abdominal fat weight by 100% at 42 days. They were generated from the same base population and maintained as outbred colonies. Determination of line-specific allele frequencies at microsatellite markers spanning the genome indicated significant changes between the lines on 15 autosomes and the X chromosome. To confirm these effects, a QTL analysis was performed using structured F2 pedigrees derived from crosses of a single male from DU6 with a female from DUKs. QTL significant at the genome-wide level were mapped for body weight on chromosome 11; for abdominal fat weight on chromosomes 4, 11, and 13; for abdominal fat percentage on chromosomes 3 and 4; and for the weights of liver on chromosomes 4 and 11, of kidney on chromosomes 2 and 9, and of spleen on chromosome 11. The strong effect on body weight of the QTL on chromosome 11 was confirmed in three independent pedigrees. The effect was additive and independent of sex, accounting for 21-35% of the phenotypic variance of body weight within the corresponding F2 populations. The test for multiple QTL on chromosome 11 with combined data from all pedigrees indicated the segregation of two loci separated by 36 cM influencing body weight.

Multiple marker mapping of quantitative trait loci in a cross between outbred wild boar and large white pigs.

A quantitative trait locus (QTL) analysis of growth and fatness data from a three generation pig experiment is presented. The population of 199 F2 animals was derived from a cross between wild boar and Large White pigs. Animals were typed for 240 markers spanning 23 Morgans of 18 autosomes and the X chromosome. A series of analyses are presented within a least squares framework. First, these identify chromosomes containing loci controlling trait variation and subsequently attempt to map QTLs to locations within chromosomes. This population gives evidence for a large QTL affecting back fat and another for abdominal fat segregating on chromosome 4. The best locations for these QTLs are within 4 cM of each other and, hence, this is likely to be a single QTL affecting both traits. The allele inherited from the wild boar causes an increase in fat deposition. A QTL for intestinal length was also located in the same region on chromosome 4 and could be the same QTL with pleiotropic effects. Significant effects, owing to multiple QTLs, for intestinal length were identified on chromosomes 3 and 5. A single QTL affecting growth rate to 30 kg was located on chromosome 13 such that the Large White allele increased early growth rate, another QTL on chromosome 10 affected growth rate from 30 to 70 kg and another on chromosome 4 affected growth rate to 70 kg.