Master of Science / Department of Statistics / Gary L. Gadbury / QTL (quantitative-trait locus) analysis aims to locate and estimate the effects of genes that are responsible for quantitative traits, such as grain protein content and yield, by means of statistical methods that evaluate the association of genetic variation with trait (phenotypic) variation. Quantitative traits are typically polygenic, i.e., controlled by multiple genes, with varying degrees of in uence on the phenotype. Several methods have been developed to increase the accuracy of QTL location and effect estimates. One of them, multiple interval mapping (MIM) (Kao et al. 1999), has been shown to be more accurate than conventional methods such as composite interval mapping (CIM) (Zeng 1994). Other QTL analysis methods have been developed to perform additional analyses that might be useful for breeders, such as of pleiotropy and QTL-by-environment (QxE) interaction. It has been shown (Jiang and Zeng 1995) that these analyses can be carried out with a multivariate extension of CIM (MT-CIM) that exploits the correlation structure in a set of traits. In doing so, this method also improves the accuracy of QTL location detection. This thesis describes the multivariate extension of MIM (MT-MIM) using ideas from MT-CIM. The development of additional multivariate tests, such as of pleiotropy and QxE interaction, and several methods pertinent to the development of MT-MIM are also described. A small simulation study shows that MT-MIM is more accurate than MT-CIM and univariate MIM. Results for real data show that MT-MIM is able to provide a more accurate and precise estimate of QTL location.

This study combines formal analysis of Shakespeare’s texts with an investigation of early modern English culture in order to explore the social energy circulating between. It argues that the conceptual categories of fluidity and loci are two features prevalent not only in Shakespeare’s plays specifically, but also in early modern English culture generally. Chapter One maps out the scholarship on death and memory in early modern English culture; Chapter Two investigates fluidity and loci in numerous forms, including humoral bodies, identities, money, commodity and texts, as regards physiology, economics, cosmology and politics. Chapter Three on Hamlet investigates corruption and fragmentation regarding both death and memory, and it also argues that Hamlet is troubled by memory’s excessiveness and fickleness. Chapter Four explores time, memory, emotion and death in Macbeth, followed by a study of Henry V, The Tempest and The Winter’s Tale in Chapter Five. There are two points underlying the argument of the whole thesis. The first point is that, whereas the brain-centred understanding of memory was predominant in early modern England as in other European countries, there was also a heart-centred tradition. Although the brain and reason still occupied pivotal positions in early modern England, the heart and emotion were given substantial attention by Shakespeare among others. As regards the relationship between the heart and the emotions, there were also two divergent attitudes to emotion: praise of emotion and denigration of emotion. As the connotations and history of the term “emotion” are complex, this study distinguishes between it and its synonyms such as passion, affection, feeling and the Chinese concept of qing. Other Chinese philosophies such as Daoism and theories including Yin-Yang theory and “Three Immortality” are also explored to shed light on the foci of this study. Secondly, this thesis argues that there are two categories of memory, namely, locative memory and fluid memory, and Shakespeare was influenced by both. It also contends that the eradication and displacement of memory provoked anxiety about memory, just as the displacement and annihilation of corpses, mainly caused by plagues and the Reformation as well as other factors, lead to heightened anxiety about death in early modern English culture.

This thesis explores the genetic characterization of the mechanisms underlying complex traits in chicken through the use and development of bioinformatics tools. The characterization of quantitative trait loci controlling complex traits has proven to be very challenging. This thesis comprises the study of experimental designs, annotation procedures and functional analyses. These represent some of the main ‘bottlenecks’ involved in the integration of QTLs with the biological interpretation of high-throughput technologies. The thesis begins with an investigation of the bioinformatics tools and procedures available for genome research, briefly reviewing microarray technology and commonly applied experimental designs. A targeted experimental design based on the concept of genetical genomics is then presented and applied in order to study a known functional QTL responsible for chicken body weight. This approach contrasts the gene expression levels of two alternative QTL genotypes, hence narrowing the QTL-phenotype gap, and, giving a direct quantification of the link between the genotypes and the genetic responses. Potential candidate genes responsible for the chicken body weight QTL are identified by using the location of the genes, their expression and biological significance. In order to deal with the multiple sources of information and exploit the data effectively, a systematic approach and a relational database were developed to improve the annotation of the probes of the ARK-Genomics G. gallus 13K v4.0 cDNA array utilized on the experiment. To follow up the investigation of the targeted genetical genomics study, a detailed functional analysis is performed on the dataset. The aim is to identify the downstream effects through the identification of functional variation found in pathways, and secondly to achieve a further characterization of potential candidate genes by using comparative genomics and sequence analyses. Finally the investigation of the body weight QTL syntenic regions and their reported QTLs are presented.

A quantitative trait locus (QTL) is the location of a gene that affects a trait that is measured on a quantitative (linear) scale. Many important agricultural traits such as weight gain, milk fat content and intramuscular fat in cattle are quantitative traits. There is a need to integrate genomic sequence data with QTL data and to develop an analytical tool to visualize the data. Without integration, application of this data to agricultural enterprise productivity will be slow and inefficient. My thesis presents a web-accessible tool called the Bovine QTL Viewer developed to solve this problem. It consists of an integrated database of bovine QTL and the QTL viewer to view the QTL and their relative chromosomal position. This tool generates dynamic and interactive images and supports research in the field of genomics. For this tool, the data is modeled and the QTL viewer is developed based on the requirements and feedback of experts in the field of bovine genomics.

Detecting both the majors genes that control the phenotypic mean and those controlling phenotypic variance has been raised in quantitative trait loci analysis. In order to mapping both kinds of genes, we applied the idea of the classic Haley-Knott regression to double generalized linear models. We performed both kinds of quantitative trait loci detection for a Red Jungle Fowl x White Leghorn F2 intercross using double generalized linear models. It is shown that double generalized linear model is a proper and efficient approach for localizing variance-controlling genes. We compared two models with or without fixed sex effect and prefer including the sex effect in order to reduce the residual variances. We found that different genes might take effect on the body weight at different time as the chicken grows.

A quantitative trait locus (QTL) is the location of a gene that affects a trait that is measured on a quantitative (linear) scale. Many important agricultural traits such as weight gain, milk fat content and intramuscular fat in cattle are quantitative traits. There is a need to integrate genomic sequence data with QTL data and to develop an analytical tool to visualize the data. Without integration, application of this data to agricultural enterprise productivity will be slow and inefficient. My thesis presents a web-accessible tool called the Bovine QTL Viewer developed to solve this problem. It consists of an integrated database of bovine QTL and the QTL viewer to view the QTL and their relative chromosomal position. This tool generates dynamic and interactive images and supports research in the field of genomics. For this tool, the data is modeled and the QTL viewer is developed based on the requirements and feedback of experts in the field of bovine genomics.

Co-variation in the genetic architecture, and co-localization of quantitative trait loci (QTL), for embryonic developmental rate and age at maturation in male rainbow trout (Oncorhynchus mykiss) was examined. Two lots (September and December spawning) of 2 x 5 (male x female) diallel crosses were performed and the resulting progeny were raised to maturity. Higher incidences of precocious maturation were observed in the September lot fish compared to December lot fish, which was uncoupled to developmental rate. However, precocious maturation and body size was higher in early hatching December lot fish. A genome scan was also completed across 4 linkage groups previously reported to possess embryonic developmental rate QTL and/or age at maturation QTL. No evidence of co-localization of QTL for the two traits was detected. However, the presence of QTL for embryonic developmental rate on RT-8 and RT-24 and one for age at maturation on RT-17 supports previous results.

The main goal of soybean breeding is to increase yield with improved seed quality characters. The objectives of this thesis were: i) to identify yield quantitative trait loci (QTL) across different mega-environments (ME); ii) to evaluate the relationship between yield and yield components and the co-localization of QTL; iii) to analyze environmental factors that affect QTL expression and identify different ME. Two Canadian x Chinese soybean populations were tested across Canada, northern United States and China. Yield QTL were identified at one, two and three hypothetical ME. Most of them were co-localized with agronomic trait QTL. These results give strong evidence that Canada, northern United States and China are different ME. Novel alleles from plant introductions can favorably contribute directly or indirectly to seed yield and the use of QTL would facilitate their introgression into breeding populations in both North America and China. / National Science and Engineering Research Council of Canada (NSERC) and the Ontario Ministry of Agriculture, Food and Rural Affairs (OMAFRA)

I examined the influence of cyclic feeding regime on fillet yield and quality and their genetic architecture in rainbow trout (Oncorhynchus mykiss). Two lots of half-sib families produced in September and December were exposed to periods of reduced ration followed by increased ration. Fish fed cyclically reduced rations weighed less and had smaller fillets and body proportions relative to controls. They also had less estimated muscle and visceral lipid but also more proportional visceral mass. Lots and families within lots differed significantly for the majority of traits. Genotypic analysis with 23 microsatellite markers spanning 19 linkage groups detected QTL for all traits over multiple linkage groups that were not necessarily consistent between feeding regime and parental lot. Linkage groups RT-9 and 29 had the largest QTL effects for fillet composition traits and overall body size across the greatest number of parents sampled.

Soybean [Glycine max (L.) Merr.] seed is a major source of edible oil in the world and the main renewable raw material for biodiesel production in North America. Oil, which on average accounts for 20% of the soybean seed weight, is a complex quantitative trait controlled by many genes with mostly minor effects and influenced by environmental conditions. Because of its quantitative nature, the seed oil concentration may have an indirect effect on other economically important and agronomic traits such as seed yield and protein concentration. Increasing the oil concentration in soybean has been given more attention in recent years due to increasing demand for both edible oil and feedstock. To achieve this objective, it is important to understand the genetic control of the oil accumulation and its relationship with other traits. The main objectives of this thesis were to identify quantitative trait loci (QTL) and genes involved in oil biosynthesis in soybean. Two recombinant inbred line (RIL) populations were developed from crosses between moderately high oil soybean cultivars with high seed yield and protein concentration. In a population of 203 F3:6 RILs from a cross of ‘OAC Wallace’ and ‘OAC Glencoe’, a total of 11 genomic regions located on nine different chromosomes were identified as associated with oil concentration using multiple QTL mapping (MQM) and single-factor ANOVA. Among the 11 oil-associated QTL, four QTL were also validated in a population of 211 F3:5 RILs from a cross of ‘RCAT Angora’ and ‘OAC Wallace’. There were six oil QTL identified in this study that were co-localized with seed protein QTL and four for seed yield QTL. The oil-beneficial allele of the QTL tagged by marker Sat_020, on Chromosome 9, was positively associated with seed protein concentration. The oil-enhancing alleles at markers Satt001 and GmDGAT2B were positively correlated with seed yield. In this study, three sequence mutations were also discovered in either the coding or non-coding regions of three DGAT soybean genes (GmDGAT2B, GmDGAT2C, and GmDGAT1B) between ‘OAC Wallace’ and ‘OAC Glencoe’ that showed significant effects on some of the traits evaluated. GmDGAT2B showed significant association with seed oil and yield across different environments. The oil-favorable allele of the gene GmDGAT2B from ‘OAC Glencoe’ was also positively correlated with seed yield. GmDGAT2C was associated with seed yield, whereas GmDGAT1B showed significant effects on seed yield and protein concentration. However, neither of these two genes showed any association with seed oil. The yield-enhancing allele of GmDGAT1B showed negative association with protein concentration. The identification of oil QTL that were either positively associated with seed yield and protein or neutral to both traits and the development of new gene-based markers will facilitate marker-assisted breeding to develop high oil soybean cultivars with high yield and minimal effect on protein concentration. / Generous funding to conduct this research was provided by the Alternative Renewable Fuels II Program of the Ontario Ministry of Agriculture, Food and Rural Affairs (OMAFRA) and by the Grain Farmers of Ontario.