Orientador: Lucia Galvão de Albuquerque / Resumo: Registros de características quantitativas e informações genotípicas cole- tadas para cada animal são utilizados para identificar regiões do genoma associadas à variação fenotípica. No entanto, essas investigações são, geralmente, realizadas com base em testes estatísticos de correlação ou associação, que não implicam em causalidade. A fim de explorar amplamente essas informações, métodos poderosos de inferência causal foram desenvolvidos para estimar os efeitos causais entre as variáveis estudadas. Apesar do progresso significativo neste campo, inferir os efeitos causais entre variáveis aleatórias contínuas ainda é um desafio e poucos estudos têm explorado as relações causais em genética quantitativa e no melhoramento animal. Neste contexto, dois estudos foram realizados com os seguintes objetivos: 1) Buscar as relações causais entre as características de carcaça e qualidade de carne usando um modelo de equação estrutural (MEE), sob modelo linear misto em bovinos da raça Nelore, e 2) Reconstruir redes de genes-fenótipos e realizar análise de rede causal por meio da integração de dados fenotípicos, genotípicos e transcriptômicos em bovinos da raça Nelore. Para o primeiro estudo, um total de 4.479 animais com informação fenotípica para o peso da carcaça quente (PCQ), área de olho lombo (AOL), espessura de gordura subcutânea (EGS), força de cisalhamento (FC) e marmoreio (MAR) foram usados. Os animais foram genotipados usando os painéis BovineHD Bead- Chip e GeneSeek Genomic Pro... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Quantitative traits and genotypes information have been collected for each animal and used to identify genome regions related to phenotypes variation. However, these investigations are, usually, performed based on correlation or association statistical tests, which do not imply in causation. In order to fully explore these information, powerful causal inference methods have been developed to estimate causal effects among the variables under study. Despite significant progress in this field infer causal effect among random variables remains a challenge and some few studies have explored causal relationships in quantitative genetics and animal breeding. In this context, two studies were performed with the following objectives: 1) Search for the causal relationship among carcass yield and meat quality traits using a structural equation model (SEM), under linear mixed model context in Nelore cattle, and 2) Reconstruct gene-phenotype networks and perform causal network analysis through the integrating of phenotypic, genotypic, and transcriptomic data in Nelore cattle. For the first study, a total of 4,479 animals with phenotypic information for hot carcass weight (HCW), longissimus muscle area (LMA), backfat thickness (BF), Warner-Bratzler shear force (WBSF), and marbling score (MB) traits were used. Animals were genotyped using BovineHD BeadChip and GeneSeek Genomic Profiler Indicus HD - GGP75Ki. For causal inference using SEM a multistep procedure methodology was used as follow:... (Complete abstract click electronic access below) / Doutor

Von Willebrand Disease (VWD) is the most common bleeding disorder. In addition to known major genes, genetic modifiers, such as ABO blood group, affect quantitative outcome measures for VWD. The data consist of an 854-member Amish pedigree with established linkage of VWD to a locus within the Von Willebrand Factor (VWF) gene on chromosome 12. The DNA sequence of the causative mutation is known. Phenotypic information and genotypic data consisting of VWF mutation status and a genome screen of markers are available for 385 pedigree members. Genetic modifiers of the VWF mutation are investigated using known and new conditional linkage methods that search for modifier genes of a major gene with known mutation. The MCMC-based program LOKI was used to conduct multipoint linkage analysis of VWD outcome measures while controlling for the VWF mutation. Adjustment for the mutation did not eliminate the linkage signal on chromosome 12 in the same location as the VWF mutation. Evidence for QTLs was also found on six other chromosomes. Smod, a score statistic that detects evidence of a genetic modifier conditional on linkage to a major gene, was developed for sib pair data. To limit the modifier gene main effect, Smod was developed so that variance due to the modifier locus is bounded above by the variance of the interaction between major gene and modifier gene. The performance of Smod was compared to other published score statistics. Power to detect linkage to the modifier locus depended on major gene and modifier gene risk allele frequencies, relative contribution of the major gene main effect to the interaction effect, and the upper bound on the modifier gene main effect. The Amish pedigree was broken up into sib pair data and analyzed using Smod and other score statistics. Using these statistics, the strongest evidence for QTLs for VWD was also found on chromosome 12 in the region of the VWF mutation. Combined with the LOKI results, further analysis will help determine if intragenic modification is occurring or if linkage disequilibrium between the mutation and analyzed markers is driving results.

Needle-to-stem unit rate (NESTUR) is a stem growth index of conifer seedling trees that measures the efficiency of stemwood production per unit of needle growth. Five experiments were carried out in this thesis using progenies of two unrelated full-sib radiata pine crosses. The initial experiment (experiment 1) applied the bulked segregant analysis technique to determine whether RAPD analysis could be successfully extended to the development of molecular markers for NESTUR in radiata pine. The NESTUR values of 174 progenies of the full-sib family 12038 x 10946 were determined. Based on the genotypic analysis of the individuals, two quantitative trait loci (QTL) controlling NESTUR were identified at ANOVA P-levels of 0.01-0.001. An absence of RAPD fragment markers generated by primers OPE-06 and OPA-10 was associated with low NESTUR values, while primer UBC-333 generated a 550 bp band that was associated with high NESTUR values. Linkage to components of NESTUR (increments in stem diameter and stem volume) was demonstrated for one of the QTL, while the other was unique to NESTUR, and not shared with the components. There was a significant interaction between the two QTLs. Presence of OPA-101200 locus appeared to inhibit expression of the QTL linked to UBC-333 [subscript 550]. ¶ To further analyse the quantitative trait loci (QTLs) controlling NESTUR, a linkage map was constructed from RAPD markers segregating in 93 haploid progeny of another full sib cross (30040 x 80121) (experiment 2). Two hundred and sixty-two (262) markers were mapped to 14 linkage groups of at least 7 markers, ranging in size from 39 to 183 cM. The 14 linkage groups covered approximately 1511 cM of genetic map distance. ¶ In experiment 3, the linkage map was used to map QTLs controlling NESTUR, as well as increments in seedling stem diameter, volume, and height and needle volume. Altogether, five putative QTLs were detected for NESTUR, with explained variation ranging from 9 to 22%. Of the five QTLs detected, 3 were coincidental with those for stem growth in height, diameter and volume. The two QTL positions that were unique to NESTUR were flanked by QTLs for the component traits. Together, effects of the five QTLs explained 48% of the total phenotypic variation for NESTUR. ¶ Ability of identified markers to predict the phenotype and seedlings with growth potential was assessed in the cross 30040 x 80121, using six RAPD markers associated with NESTUR at ANOVA P-levels of 0.01-0.001 (experiment 4). The correlation between observed NESTUR and predicted values was 0.70. Differences in observed vs. predicted values were not large and did not indicate serious misclassifications, such as classification of an upper ranking individual into the lower group, or vice versa. ¶ Over a two-year growth period, the ability of NESTUR to predict stem growth was strongly affected by seedling age. In contrast, markers linked to NESTUR showed a consistent ability to predict stem growth, irrespective of seedling age. Compared with the top 1% of the original population, seedlings selected for their genotypic values showed a higher stem volume growth of 103% in the first year, and 76% in the second year. ¶ The expression of QTLs for stem volume, stem diameter, height, number of branches, number of whorls, and branches/whorl were compared at 5, 12, and 24 months of age. Two QTLs detected for height showed contrasting expression over two years, one was gradually reduced from LOD of 2.70 to 0.43 and the other increased from 1.12 to 2.45. Compared with the pattern observed for height, LOD scan profiles for diameter and volume showed less temporal change of peaks, suggesting that the genetic control for height growth is probably more unstable than that of diameter. QTLs controlling the phenotype at the time of measurement (ie the final phenotype) showed similar magnitude of effects on that trait's respective increments (or growth rate).

The seed size and shape of lentil are important traits because they determine the market class, cooking time, and can influence quality and yield of milled lentils. Understanding the genetic control of seed size and shape can help breeders develop varieties with improved seed size and shape characteristics such as seed diameter, seed thickness and seed plumpness. The objectives were to determine the heritability of seed size and shape and identify the genomic regions controlling these traits. This involved i) developing a linkage map for the LR-18 population (CDC Robin x 964a-46) using a recently developed single nucleotide polymorphism (SNP) assay; ii) analyzing the LR-18 population for seed size and shape QTLs; iii) analyzing an association mapping panel for seed size and shape QTLs. Phenotyping trials were grown at two different locations in Saskatchewan, Canada. The mapping population was grown in two different years while the association panel was only grown in one. Seed diameter and thickness were measured using sieves and this data were used to calculate seed plumpness. Days to flowering was also recorded to determine if it had any effect on seed size or shape. A linkage map consisting of 537 SNPs, 10 SSRs and 4 morphological markers on seven linkage groups was constructed and used for the QTL analysis. The heritability estimates were high for seed diameter and seed plumpness (0.92 and 0.94, respectively) while for seed thickness and days to flowering they were more moderate (0.60 and 0.45, respectively). QTL analysis revealed QTLs on five of the seven linkage groups. The association mapping study revealed similar heritability estimates of 0.97, 0.62, 0.94, and 0.62 for seed diameter, seed thickness, seed plumpness and flowering time, respectively. There were 31 different significant marker trait associations, however only 5 of those were significant for both locations. Four of those five markers did not map in the LR-18 linkage map so their genomic locations are still to be determined. Results showed that there are key regions in the genome that control seed size and shape and flowering time in lentil. These markers could be used for marker-assisted selection or for further candidate gene analysis.

Domestication is the process by which animals become adapted to the environment provided by humans. The process of domestication has let to a number of correlated behavioural, morphological and physiological changes among many domesticated animal species. An example is the changes of plumage colour in the chicken. Plumage colour is one of the most readily observable traits that make distinction between breeds as well as between strains within a breed. Understanding the genetic architecture of pigmentation traits or indeed any trait is always a great challenge in evolutionary biology. The main aim of this study was to map quantitative trait loci (QTLs) affecting the red and metallic green coloration in the chicken plumage. In this study, a total of 572 F8 intercross chickens between Red Junglefowl and White Leghorn were used. Phenotypic measurements were done using a combination of digital photography and photography manipulating software. Moreover, all birds were genotyped with 657 molecular markers, covering 30 autosomes. The total map distance covered was 11228 cM and the average interval distance was 17 cM. In this analysis, a total of six QTLs (4 for red and 2 for metallic green colour) were detected on four different chromosomes: 2, 3 11 and 14. For red colour, the most significant QTL was detected on chromosome 2 at 165 cM. An additional QTL was also detected on the same chromosome at 540 cM. Two more QTLs were detected on chromosomes 11 and 14 at 24 and 203 cM respectively. Additionally, two epistatic pairs of QTLs were also detected. The identified four QTLs together can explain approximately 36% of the phenotypic variance in this trait. In addition, for metallic green colour, one significant and one suggestive QTLs were detected on chromosomes 2 and 3 at 399 and 247 cM respectively. Moreover, significant epistatic interactions between these two QTLs were detected. Furthermore, these two QTLs together can explain approximately 24% of the phenotypic variance in this trait. These findings suggest that the expression of pigmentation in the chicken plumage is highly influenced by both the epistatic actions and pleiotropic effects of different QTLs located on different chromosomes.

The protein quality of maize can be improved by replacing normal Opaque2 alleles with non-functional recessive alleles opaque2 (o2). The allele o2 produces a severe phenotype with soft endosperm enhancing its protein quality but decreasing its agronomical value. Plant breeders have restored a desirable ratio of hard to soft endosperm in o2 germplasm known as Quality Protein Maize (QPM). Neither the mechanism nor the genetic components by which the modification of the endosperm in QPM lines occurs are well understood. To increase the understanding of the genetics of endosperm modification, a population of 146 recombinant inbred lines derived from a cross between the o2 inbred line B73o2 and the QPM inbred line CML161 was evaluated in two Texas locations from 2004 to 2006. Four traits related to endosperm texture were measured and showed significant effect of the inbred lines, high heritability estimates and high genetic correlations. Relative content of the essential amino acids lysine, tryptophan and methionine were measured and showed significant effects of the lines and considerable high genetic correlations and heritabilities. Negative correlation was observed between endosperm texture traits and amino acid content. Quantitative trait loci (QTL) were mapped for traits related to the modification of endosperm texture and the content of lysine, tryptophan and methionine. QTLs clusters for endosperm texture traits were detected on chromosomes 3, 5, 6 and 8 explaining 62-68% of the variation. QTLs clusters for amino acid contents were located on chromosomes 7 and 8 that explained up to 39% of the observed variation. The product of the O2 gene is a transcription factor that affects the expression of a number of endosperm genes. A group of 29 endosperm genes associated with the O2 activity were evaluated in developing endosperm of the recombinant inbred lines. Genomic regions controlling gene transcript abundance in developing endosperm were identified by expression QTL mapping. Evidence is presented of QTL hot spots that segregate in association with endosperm texture modification or amino acid contents and are associated with the regulation of the expression of a group of endosperm genes.

Heat stress adversely affects wheat production in many regions of the world and is particularly detrimental during reproductive development. The objective of this study was to identify quantitative trait loci (QTL) associated with improved heat tolerance in hexaploid bread wheat (Triticum aestivum). To accomplish this objective, an analysis of both the phenotypic and genetic responses of two recombinant inbred line (RIL) populations was conducted. RIL populations Halberd x Cutter and Halberd x Karl 92 (H/K) both derive heat tolerance from Halberd and segregate in their response to heat stress. A heat susceptibility index (HSI) was calculated from the reduction of three yield components; kernel number, kernel weight, and single kernel weight, following a three-day 38 degrees C heat stress treatment during early grain-filling. The HSI, as well as temperature depression of the main spike and flag leaf were used as measurements of heat tolerance. Genetic linkage maps were constructed for both populations and were used in combination with phenotypic data and statistical software to detect QTL for heat tolerance. In a comparison across the two across populations, seven common QTL regions were identified for HSI, located on chromosomes 1B, 3B, 4A, 5A, 5B, and 6D. Subsequent analysis of temperature depression in the H/K population identified seven QTL that co-localized for both cooler organ temperature and improved HSI. Four of the beneficial alleles at these loci were contributed Halberd. The genetic effect of combining QTL, including QHkw.tam-1B, QHkwm.tam-5A.1, and QHskm.tam-6D showed the potential benefit of selection for multiple heat tolerant alleles simultaneously. Analysis of the H/K population in the field under abiotic stress detected QTL on chromosome 3B and 5A, which were in agreement with results from the greenhouse study. The locus QYld.tam-3B was pleiotropic for both temperature depression and HSI in both experiments and was associated with higher biomass and yield under field conditions. The results presented here represent a comprehensive analysis of both the phenotypic response of wheat to high temperature stress and the genetic loci associated with improved heat tolerance and will be valuable for future understanding and improvement of heat stress tolerance in wheat.

Variable selection methods play important roles in modeling high-dimensional data and are key to data-driven scientific discoveries. In this thesis, we consider the problem of variable selection with interaction detection. Instead of building a predictive model of the response given combinations of predictors, we start by modeling the conditional distribution of predictors given partitions based on responses. We use this inverse modeling perspective as motivation to propose a stepwise procedure for effectively detecting interaction with few assumptions on parametric form. The proposed procedure is able to detect pairwise interactions among p predictors with a computational time of \(O(p)\) instead of \(O(p^2)\) under moderate conditions. We establish consistency of the proposed procedure in variable selection under a diverging number of predictors and sample size. We demonstrate its excellent empirical performance in comparison with some existing methods through simulation studies as well as real data examples. Next, we combine the forward and inverse modeling perspectives under the Bayesian framework to detect pleiotropic and epistatic effects in effects in expression quantitative loci (eQTLs) studies. We augment the Bayesian partition model proposed by Zhang et al. (2010) to capture complex dependence structure among gene expression and genetic markers. In particular, we propose a sequential partition prior to model the asymmetric roles played by the response and the predictors, and we develop an efficient dynamic programming algorithm for sampling latent individual partitions. The augmented partition model significantly improves the power in detecting eQTLs compared to previous methods in both simulations and real data examples pertaining to yeast. Finally, we study the application of Bayesian partition models in the unsupervised learning of transcription factor (TF) families based on protein binding microarray (PBM). The problem of TF subclass identification can be viewed as the clustering of TFs with variable selection on their binding DNA sequences. Our model provides simultaneous identification of TF families and their shared sequence preferences, as well as DNA sequences bound preferentially by individual members of TF families. Our analysis may aid in deciphering cis regulatory codes and determinants of protein-DNA binding specificity. / Statistics

The fungus Fusarium graminearum (Schwabe) causes Gibberella ear rot in maize, resulting in accumulation of harmful mycotoxins in the grain. Disease severity and pericarp/aleurone dehydrodiferulic acid content are negatively correlated. Furthermore, quantitative trait locus mapping (QTL) identified colocalization between QTL for both traits. A candidate gene approach was employed to identify the genes responsible for the observed colocalization. Candidate genes selected on the basis of their putative involvement in various aspects of cell wall DFA accumulation were mapped in silico using the maize genome sequence. Polymorphisms were discovered in putative genes and converted to molecular markers. The in silico mapping effort was successful in predicting map locations of the analyzed sequences, and the segregation of certain marker alleles could explain variation for Gibberella ear rot severity and pericarp-aleurone DFA content.

I examined phenotypic and genetic variation in growth traits in 30 families of commercial Fraser strain Arctic charr (Salvelinus alpinus) reared in freshwater (FRW) and brackish water (BRW) in Eastern Canada. I detected family by treatment interactions for all traits [body weight (BW), condition factor (K) and specific growth rate (SGR)] across all measurement dates and growth intervals, however, mean family BW in FRW was correlated phenotypically with BRW BW. In addition, FRW fish showed significantly greater survival than those transferred to BRW and fish which survived until the conclusion of the experiment were significantly heavier in BW at the baseline assessment than their full-sibs that died. These observations suggest that BW in FRW and BW in BRW should be analyzed as separate but correlated traits in Arctic charr breeding programs. I then tested the potential for genetic improvement in this species by calculating genetic parameters for BW and K, and tested if previously identified quantitative trait loci (QTL) for these traits were detectable across the broodstock. QTL with experiment-wide and chromosome-wide significance for body size and condition factor were detected on multiple linkage groups. Heritability for BW and K was moderate in FRW (0.29-0.38) but lower in BRW (0.14-0.17). Genetic correlations for BW across environments were positive and moderate (0.33-0.67), however equivalent K correlations were weaker (0.24-0.37). This information was then used to predict the rate of genetic change following one generation of selection for BW using phenotypic selection and genomic methodologies including marker-only selection and marker assisted selection. The greatest response in the rate of genetic change was achieved by selecting only from families in which significant BW QTL had been identified. As such, marker assisted selection showed the greatest gain in genetic response with 5.4% in FRW and 4.3% in BRW. These results have applications to commercial aquaculture as the Canadian aquaculture industry is attempting to diversify with alternative species. Such genetic improvement strategies will aid in developing a strain of Arctic charr characterised by increased BW. / Funding provided through the NSERC Strategic grants program. The project was sponsored by CanAqua Seafoods Ltd. in collaboration with the Coastal Zones Research Institute.