POOR PERFORMANCE OF BOOTSTRAP CONFIDENCE INTERVALS FOR THE LOCATION OF A QUANTITATIVE TRAIT LOUCS

The aim of many genetic studies is to locate the genomic regions (called quantitative trait loci, QTLs) that contribute to variation in a quantitative trait (such as body weight). Confidence intervals for the locations of QTLs are particularly important for the design of further experiments to identify the gene or genes responsible for the effect. Likelihood support intervals are the most widely used method to obtain confidence intervals for QTL location, but the non-parametric bootstrap has also been recommended. Through extensive computer simulation, we show that bootstrap confidence intervals are poorly behaved and so should not be used in this context. The profile likelihood (or LOD curve) for QTL location has a tendency to peak at genetic markers, and so the distribution of the maximum likelihood estimate (MLE) of QTL location has the unusual feature of point masses at genetic markers; this contributes to the poor behavior of the bootstrap. Likelihood support intervals and approximate Bayes credible intervals, on the other hand, are shown to behave appropriately.

Sequential Quantitative Trait Locus Mapping in Experimental Crosses

The etiology of complex diseases is heterogeneous. The presence of risk alleles in one or more genetic loci affects the function of a variety of intermediate biological pathways, resulting in the overt expression of disease. Hence, there is an increasing focus on identifying the genetic basis of disease by sytematically studying phenotypic traits pertaining to the underlying biological functions. In this paper we focus on identifying genetic loci linked to quantitative phenotypic traits in experimental crosses. Such genetic mapping methods often use a one stage design by genotyping all the markers of interest on the available subjects. A genome scan based on single locus or multi-locus models is used to identify the putative loci. Since the number of quantitative trait loci (QTLs) is very likely to be small relative to the number of markers genotyped, a one-stage selective genotyping approach is commonly used to reduce the genotyping burden, whereby markers are genotyped solely on individuals with extreme trait values. This approach is powerful in the presence of a single quantitative trait locus (QTL) but may result in substantial loss of information in the presence of multiple QTLs. Here we investigate the efficiency of sequential two stage designs to identify QTLs in experimental populations. Our investigations for backcross and F2 crosses suggest that genotyping all the markers on 60% of the subjects in Stage 1 and genotyping the chromosomes significant at 20% level using additional subjects in Stage 2 and testing using all the subjects provides an efficient approach to identify the QTLs and utilizes only 70% of the genotyping burden relative to a one stage design, regardless of the heritability and genotyping density. Complex traits are a consequence of multiple QTLs conferring main effects as well as epistatic interactions. We propose a two-stage analytic approach where a single-locus genome scan is conducted in Stage 1 to identify promising chromosomes, and interactions are examined using the loci on these chromosomes in Stage 2. We examine settings under which the two-stage analytic approach provides sufficient power to detect the putative QTLs.

Mapping quantitative trait loci for osteochondrosis in fetlock and hock joints and palmar/plantar osseus fragments in fetlock joints of South German Coldblood horses

The aim of this study was to identify quantitative trait loci (QTL) for osteochondrosis (OC) and palmar/plantar osseous fragments (POF) in fetlock joints in a whole-genome scan of 219 South German Coldblood horses. Symptoms of OC and POF were checked by radiography in 117 South German Coldblood horses at a mean age of 17 months. The radiographic examination comprised the fetlock and hock joints of all limbs. The genome scan included 157 polymorphic microsatellite markers. All microsatellite markers were equally spaced over the 31 autosomes and the X chromosome, with an average distance of 17.7 cM and a mean polymorphism information content (PIC) of 63%. Sixteen chromosomes harbouring putative QTL regions were further investigated by genotyping the animals with 93 additional markers. QTL that had chromosome-wide significance by non-parametric Z-means and LOD scores were found on 10 chromosomes. This included seven QTL for fetlock OC and one QTL on ECA18 associated with hock OC and fetlock OC. Significant QTL for POF in fetlock joints were located on equine chromosomes 1, 4, 8, 12 and 18. This genome scan is an important step towards the identification of genes responsible for OC in horses.

Heterosis for biomass-related traits in Arabidopsis investigated by quantitative trait loci analysis of the triple testcross design with recombinant inbred lines

Arabidopsis thaliana has emerged as a leading model species in plant genetics and functional genomics including research on the genetic causes of heterosis. We applied a triple testcross (TTC) design and a novel biometrical approach to identify and characterize quantitative trait loci (QTL) for heterosis of five biomass-related traits by (i) estimating the number, genomic positions, and genetic effects of heterotic QTL, (ii) characterizing their mode of gene action, and (iii) testing for presence of epistatic effects by a genomewide scan and marker x marker interactions. In total, 234 recombinant inbred lines (RILs) of Arabidopsis hybrid C24 x Col-0 were crossed to both parental lines and their F1 and analyzed with 110 single-nucleotide polymorphism (SNP) markers. QTL analyses were conducted using linear transformations Z1, Z2, and Z3 calculated from the adjusted entry means of TTC progenies. With Z1, we detected 12 QTL displaying augmented additive effects. With Z2, we mapped six QTL for augmented dominance effects. A one-dimensional genome scan with Z3 revealed two genomic regions with significantly negative dominance x additive epistatic effects. Two-way analyses of variance between marker pairs revealed nine digenic epistatic interactions: six reflecting dominance x dominance effects with variable sign and three reflecting additive x additive effects with positive sign. We conclude that heterosis for biomass-related traits in Arabidopsis has a polygenic basis with overdominance and/or epistasis being presumably the main types of gene action.

Mouse models and quantitative trait loci of susceptibility to bleomycin- and radiation-induced pulmonary fibrosis

Radiotherapy involving the thoracic cavity and chemotherapy with the drug bleomycin are both dose limited by the development of pulmonary fibrosis. From evidence that there is variation in the population in susceptibility to pulmonary fibrosis, and animal data, it was hypothesized that individual variation in susceptibility to bleomycin-induced, or radiation-induced, pulmonary fibrosis is, in part, genetically controlled. In this thesis a three generation mouse genetic model of C57BL/6J (fibrosis prone) and C3Hf/Kam (fibrosis resistant) mouse strains and F1 and F2 (F1 intercross) progeny derived from the parental strains was developed to investigate the genetic basis of susceptibility to fibrosis. In the bleomycin studies the mice received 100 mg/kg (125 for females) of bleomycin, via mini osmotic pump. The animals were sacrificed at eight weeks following treatment or when their breathing rate indicated respiratory distress. In the radiation studies the mice were given a single dose of 14 or 16 Gy (Co$\sp{60})$ to the whole thorax and were sacrificed when moribund. The phenotype was defined as the percent of fibrosis area in the left lung as quantified with image analysis of histological sections. Quantitative trait loci (QTL) mapping was used to identify the chromosomal location of genes which contribute to susceptibility to bleomycin-induced pulmonary fibrosis in C57BL/6J mice compared to C3Hf/Kam mice and to determine if the QTL's which influence susceptibility to bleomycin-induced lung fibrosis in these progenitor strains could be implicated in susceptibility to radiation-induced lung fibrosis. For bleomycin, a genome wide scan revealed QTL's on chromosome 17, at the MHC, (LOD = 11.7 for males and 7.2 for females) accounting for approximately 21% of the phenotypic variance, and on chromosome 11 (LOD = 4.9), in male mice only, adding 8% of phenotypic variance. The bleomycin QTL on chromosome 17 was also implicated for susceptibility to radiation-induced fibrosis (LOD = 5.0) and contributes 7% of the phenotypic variance in the radiation study. In conclusion, susceptibility to both bleomycin-induced and radiation-induced pulmonary fibrosis are heritable traits, and are influenced by a genetic factor which maps to a genomic region containing the MHC. ^

Identification of multiple quantitative trait loci linked to prion disease incubation period in mice

Polymorphisms in the prion protein gene are known to affect prion disease incubation times and susceptibility in humans and mice. However, studies with inbred lines of mice show that large differences in incubation times occur even with the same amino acid sequence of the prion protein, suggesting that other genes may contribute to the observed variation. To identify these loci we analyzed 1,009 animals from an F2 intercross between two strains of mice, CAST/Ei and NZW/OlaHSd, with significantly different incubation periods when challenged with RML scrapie prions. Interval mapping identified three highly significantly linked regions on chromosomes 2, 11, and 12; composite interval mapping suggests that each of these regions includes multiple linked quantitative trait loci. Suggestive evidence for linkage was obtained on chromosomes 6 and 7. The sequence conservation between the mouse and human genome suggests that identification of mouse prion susceptibility alleles may have direct relevance to understanding human susceptibility to bovine spongiform encephalopathy (BSE) infection, as well as identifying key factors in the molecular pathways of prion pathogenesis. However, the demonstration of other major genetic effects on incubation period suggests the need for extreme caution in interpreting estimates of variant Creutzfeldt–Jakob disease epidemic size utilizing existing epidemiological models.

Quantitative trait loci and metabolic pathways: genetic control of the concentration of maysin, a corn earworm resistance factor, in maize silks.

Interpretation of quantitative trait locus (QTL) studies of agronomic traits is limited by lack of knowledge of biochemical pathways leading to trait expression. To more fully elucidate the biological significance of detected QTL, we chose a trait that is the product of a well-characterized pathway, namely the concentration of maysin, a C-glycosyl flavone, in silks of maize, Zea mays L. Maysin is a host-plant resistance factor against the corn earworm, Helicoverpa zea (Boddie). We determined silk maysin concentrations and restriction fragment length polymorphism genotypes at flavonoid pathway loci or linked markers for 285 F2 plants derived from the cross of lines GT114 and GT119. Single-factor analysis of variance indicated that the p1 region on chromosome 1 accounted for 58.0% of the phenotypic variance and showed additive gene action. The p1 locus is a transcription activator for portions of the flavonoid pathway. A second QTL, represented by marker umc 105a near the brown pericarp1 locus on chromosome 9, accounted for 10.8% of the variance. Gene action of this region was dominant for low maysin, but was only expressed in the presence of a functional p1 allele. The model explaining the greatest proportion of phenotypic variance (75.9%) included p1, umc105a, umc166b (chromosome 1), r1 (chromosome 10), and two epistatic interaction terms, p1 x umc105a and p1 x r1. Our results provide evidence that regulatory loci have a central role and that there is a complex interplay among different branches of the flavonoid pathway in the expression of this trait.

Interactions between quantitative trait loci in soybean in which trait variation at one locus is conditional upon a specific allele at another.

A large recombinant inbred population of soybean has been characterized for 220 restriction fragment-length polymorphism (RFLP) markers. Values for agronomic traits also have been measured. Quantitative trait loci (QTL) for height, yield, and maturity were located by their linkage to RFLP markers. QTL controlling large amounts of trait variation were analyzed for the dependence of trait variation on particular alleles at a second locus by comparing cumulative distributions of the trait for each genotype (four genotypes per pair of loci). Interesting pairs of loci were analyzed statistically with maximum likelihood and Monte Carlo comparison of additive and epistatic models. For each locus affecting height, variation was conditional upon the presence of a particular allele at a second unlinked locus that itself explained little or no trait variation. The results show that interactions between QTL are frequent and control large effects. Interactions distinguished between different QTL in a single linkage group and between QTL that affect different traits closely linked to one RFLP marker--i.e., distinguished between pleiotropy and closely linked genes. The implications for the evolution of inbreeding plants and for the construction of agronomic breeding strategies are discussed.

Resistance gene analogues in sugarcane and sorghum and their association with quantitative trait loci for rust resistance

Fifty-four different sugarcane resistance gene analogue (RGA) sequences were isolated, characterized, and used to identify molecular markers linked to major disease-resistance loci in sugarcane. Ten RGAs were identified from a sugarcane stem expressed sequence tag (EST) library; the remaining 44 were isolated from sugarcane stem, leaf, and root tissue using primers designed to conserved RGA motifs. The map location of 31 of the RGAs was determined in sugarcane and compared with the location of quantitative trait loci (QTL) for brown rust resistance. After 2 years of phenotyping, 3 RGAs were shown to generate markers that were significantly associated with resistance to this disease. To assist in the understanding of the complex genetic structure of sugarcane, 17 of the 31 RGAs were also mapped in sorghum. Comparative mapping between sugarcane and sorghum revealed syntenic localization of several RGA clusters. The 3 brown rust associated RGAs were shown to map to the same linkage group (LG) in sorghum with 2 mapping to one region and the third to a region previously shown to contain a major rust-resistance QTL in sorghum. These results illustrate the value of using RGAs for the identification of markers linked to disease resistance loci and the value of simultaneous mapping in sugarcane and sorghum.

Analysis of expression quantitative trait loci in D. melanogaster

Expression Quantitative Trait Loci (eQTL) analysis allows for the identification of genetic variation associated with variation in gene expression. It is often unclear however, which of the associated variants are causal, and by what mechanism. Integrating functional genomic data with eQTL data can provide insight into the impact of natural variation in the population, and the nature of the transcriptional machinery itself. In this thesis, I integrate functional genomic data with eQTL data derived from both 5’ CAGE and 3’ TagXseq expression assays, in developing embryos. I first use both datasets to analyse the transcription landscape in embryonic D., melanogaster, and then carry out an analysis of sequence motifs associated with transcription factor binding sites, promoters, and 3’ polyadenylation sites. Finally, I integrate functional genomic data, including these novel sequence motifs, to shed light on the mechanisms of gene expression variation in D.,melanogaster. I am able to demonstrate that some variants effecting gene regulation in Drosophila are found within haplotypes which buffer their effects.

Modularisation épistatique des loci à trait quantitatif associés à la pression artérielle et identification de gènes candidats pour l’hypertension

Problématique: L’hypertension artérielle essentielle, facteur de risque majeur dans le développement des maladies cardiovasculaires, est un trait multigénique complexe dont les connaissances sur le déterminisme génétique nécessitent d’être approfondies. De nombreux loci à trait quantitatif (QTLs); soit des gènes responsables de faire varier la pression artérielle (PA), ont été identifiés chez l’humain et le modèle animal. Cependant, le mystère plane encore sur la façon dont ces gènes fonctionnent ensemble pour réguler la PA. Hypothèse et objectif: Plutôt qu’une addition de QTLs ayant chacun une action infinitésimale sur la PA, une interaction épistatique entre les gènes serait responsable du phénotype hypertendu. Ainsi, l’étude de cette épistasie entre les gènes impliqués, directement ou indirectement, dans l’homéostasie de la PA nous permettrait d’explorer de nouvelles voies de régulation moléculaire en cause dans cette maladie. Méthodes: Via la réalisation de souches congéniques de rats, où un segment chromosomique provenant d’une souche receveuse hypertendue (Dahl Salt Sensitive, SS/Jr) est remplacé par son homologue provenant d’une souche donneuse normotendue (Lewis, LEW), des QTLs peuvent être mis en évidence. Dans ce contexte, la combinaison de QTLs via la création de doubles ou multiples congéniques constitue la première démonstration fonctionnelle des interactions intergéniques. Résultats: Vingt-sept combinaisons au total nous ont menés à l’appréciation d’une modularisation des QTLs. Ces derniers ont été catégorisés selon deux principaux modules épistatiques (EMs) où les QTLs appartenant à un même EM sont épistatiques entre eux et participent à une même voie régulatrice. Les EMs/cascades agissent alors en parallèle pour réguler la PA. Grâce à l’existence de QTLs ayant des effets opposés sur la PA, nous avons pu établir l’ordre hiérarchique entre trois paires de QTLs. Cependant, lorsque cette suite régulatrice ne peut être déterminée, d’autres approches sont nécessaires. Nos travaux nous ont mené à l’identification d’un QTL situé sur le chromosome 16 du rat (C16QTL), appartenant au EM1 et qui révélerait une nouvelle voie de l’homéostasie de la PA. Le gène retinoblastoma-associated protein 140 (Rap140)/family with sequence similarity 208 member A (Fam208a), présentant une mutation non synonyme entre SS/Jr et LEW est le gène candidat le plus plausible pour représenter C16QTL. Celui-ci code pour un facteur de transcription et semblerait influencer l’expression de Solute carrier family 7 (cationic amino acid transporter, y+ system) member 12 (Slc7a12), spécifiquement et significativement sous exprimé dans les reins de la souche congénique portant C16QTL par rapport à la souche SS/Jr. Rap140/Fam208a agirait comme un inhibiteur de la transcription de Slc7a12 menant à une diminution de la pression chez Lewis. Conclusions: L’architecture complexe de la régulation de la PA se dévoile mettant en scène de nouveaux acteurs, pour la plupart inconnus pour leur implication dans la PA. L’étude de la nouvelle voie de signalisation Rap140/Fam208a - Slc7a12 nous permettra d’approfondir nos connaissances quant à l’homéostasie de la pression artérielle et de l’hypertension chez SS/Jr. À long terme, de nouveaux traitements anti-hypertenseurs, ciblant plus d’une voie de régulation à la fois, pourraient voir le jour.

Modularisation épistatique des loci à trait quantitatif associés à la pression artérielle et identification de gènes candidats pour l’hypertension

Problématique: L’hypertension artérielle essentielle, facteur de risque majeur dans le développement des maladies cardiovasculaires, est un trait multigénique complexe dont les connaissances sur le déterminisme génétique nécessitent d’être approfondies. De nombreux loci à trait quantitatif (QTLs); soit des gènes responsables de faire varier la pression artérielle (PA), ont été identifiés chez l’humain et le modèle animal. Cependant, le mystère plane encore sur la façon dont ces gènes fonctionnent ensemble pour réguler la PA. Hypothèse et objectif: Plutôt qu’une addition de QTLs ayant chacun une action infinitésimale sur la PA, une interaction épistatique entre les gènes serait responsable du phénotype hypertendu. Ainsi, l’étude de cette épistasie entre les gènes impliqués, directement ou indirectement, dans l’homéostasie de la PA nous permettrait d’explorer de nouvelles voies de régulation moléculaire en cause dans cette maladie. Méthodes: Via la réalisation de souches congéniques de rats, où un segment chromosomique provenant d’une souche receveuse hypertendue (Dahl Salt Sensitive, SS/Jr) est remplacé par son homologue provenant d’une souche donneuse normotendue (Lewis, LEW), des QTLs peuvent être mis en évidence. Dans ce contexte, la combinaison de QTLs via la création de doubles ou multiples congéniques constitue la première démonstration fonctionnelle des interactions intergéniques. Résultats: Vingt-sept combinaisons au total nous ont menés à l’appréciation d’une modularisation des QTLs. Ces derniers ont été catégorisés selon deux principaux modules épistatiques (EMs) où les QTLs appartenant à un même EM sont épistatiques entre eux et participent à une même voie régulatrice. Les EMs/cascades agissent alors en parallèle pour réguler la PA. Grâce à l’existence de QTLs ayant des effets opposés sur la PA, nous avons pu établir l’ordre hiérarchique entre trois paires de QTLs. Cependant, lorsque cette suite régulatrice ne peut être déterminée, d’autres approches sont nécessaires. Nos travaux nous ont mené à l’identification d’un QTL situé sur le chromosome 16 du rat (C16QTL), appartenant au EM1 et qui révélerait une nouvelle voie de l’homéostasie de la PA. Le gène retinoblastoma-associated protein 140 (Rap140)/family with sequence similarity 208 member A (Fam208a), présentant une mutation non synonyme entre SS/Jr et LEW est le gène candidat le plus plausible pour représenter C16QTL. Celui-ci code pour un facteur de transcription et semblerait influencer l’expression de Solute carrier family 7 (cationic amino acid transporter, y+ system) member 12 (Slc7a12), spécifiquement et significativement sous exprimé dans les reins de la souche congénique portant C16QTL par rapport à la souche SS/Jr. Rap140/Fam208a agirait comme un inhibiteur de la transcription de Slc7a12 menant à une diminution de la pression chez Lewis. Conclusions: L’architecture complexe de la régulation de la PA se dévoile mettant en scène de nouveaux acteurs, pour la plupart inconnus pour leur implication dans la PA. L’étude de la nouvelle voie de signalisation Rap140/Fam208a - Slc7a12 nous permettra d’approfondir nos connaissances quant à l’homéostasie de la pression artérielle et de l’hypertension chez SS/Jr. À long terme, de nouveaux traitements anti-hypertenseurs, ciblant plus d’une voie de régulation à la fois, pourraient voir le jour.

Major quantitative trait locus for eosinophil count is located on chromosome 2q

Background: Eosinophils are granulocytic white blood cells implicated in asthma and atopic disease. The degree of eosinophilia in the blood of patients with asthma correlates with the severity of asthmatic symptoms. Quantitative trait loci (QTL) linkage analysis of eosinophil count may be a more powerful strategy of mapping genes involved in asthma than linkage analysis using affected relative pairs. 1 Objective: To identify QTLs responsible for variation in eosinophil count in adolescent twins. Methods: We measured eosinophil count longitudinally in 738 pairs of twins at 12, 14, and 16 years of age. We typed 757 highly polymorphic microsatellite markers at an average spacing of similar to5 centimorgans across the genome. We then used multipoint variance components linkage analysis to test for linkage between marker loci and eosinophil concentrations at each age across the genome. Results: We found highly significant linkage on chromosome 2q33 in 12-year-old twins (logarithm of the odds = 4.6; P = .000002) and suggestive evidence of linkage in the same region in 14-year-olds (logarithm of the odds = 1.0; P = .016). We also found suggestive evidence of linkage at other areas of the genome, including regions on chromosomes 2, 3, 4, 8, 9, 11, 12, 17, 20, and 22. Conclusion: A QTL for eosinophil count is present on chromosome 2q33. This QTL might represent a gene involved in asthma pathophysiology.