Fructans are polysaccharides that are made up mainly of fructose. They are non-digestible carbohydrates and act as prebiotics to selectively promote the growth of colonic bifidobacteria, thereby improving human gut health. Fructans are present in the grain of wheat (Triticum aestivum L.), a staple food crop. Until now, there has been no research on genetic improvement of the concentration of fructans in wheat grain, partly because it has been difficult to accurately measure. One aim of this research project was to develop a simple and effective method to measure the fructan concentration in wheat grain. This was achieved by modifying a method that involves extraction of fructans from wheat grain followed by enzymatic hydrolysis to break down fructans into monosaccharides and quantification by anion-exchange liquid chromatography coupled with pulsed amperometric detection. The modified procedure is reliable and allows the handling of large numbers of flour samples at a relatively low cost, and can therefore be useful for assessing large numbers of wheat breeding lines. Using this method, grain samples taken from a diverse set of 117 wheat cultivars and breeding lines, including parents of mapping populations, were analysed for grain fructan concentration. There was significant genotypic variation among these materials, with grain fructan concentration ranging from 0.3 to 2.3% of grain dry weight. There was no evidence of strong genotype-byenvironment interaction; the fructan concentrations of the same genotypes were positively correlated over different environments in Australia. Genetic mapping was carried out to detect and map loci affecting grain fructan concentration in wheat using a doubled haploid population derived from a cross between Berkut (high fructan) and Krichauff (low fructan). Grain samples were obtained from two field sites in South Australia and one in Kazakhstan. Fructan concentration varied widely within the population (0.6-2.6% of grain dry weight), with heritability estimated as h² = 0.71. A linkage map of 528 molecular markers covering 21 wheat chromosomes was used for locating quantitative trait loci (QTL). Genetic mapping identified two major QTLs on chromosomes 6D and 7A, with the (high fructan concentration) alleles contributed from Berkut, contributing to a 30-40% increase in wheat grain fructan compared to the Krichauff alleles. Effects of these chromosome regions were validated in additional environments and in another mapping population, Sokoll/Krichauff, with the favourable alleles contributed from Sokoll. The major QTL on chromosome 7A was in the same region with a reported fructosyltransferase orthologue (AB029888), while the major QTL on chromosome 6D seemed to be co-located with a reported gene encoding for a fructan-degrading enzyme 1-exohydrolase (1-FEHw2). It is concluded that grain fructan concentration of wheat can be improved by breeding and that molecular markers could be used to select effectively for favourable alleles in two regions of the wheat genome. / Thesis (Ph.D.) - University of Adelaide, School of Agriculture, Food and Wine, 2009

Fructans are polysaccharides that are made up mainly of fructose. They are non-digestible carbohydrates and act as prebiotics to selectively promote the growth of colonic bifidobacteria, thereby improving human gut health. Fructans are present in the grain of wheat (Triticum aestivum L.), a staple food crop. Until now, there has been no research on genetic improvement of the concentration of fructans in wheat grain, partly because it has been difficult to accurately measure. One aim of this research project was to develop a simple and effective method to measure the fructan concentration in wheat grain. This was achieved by modifying a method that involves extraction of fructans from wheat grain followed by enzymatic hydrolysis to break down fructans into monosaccharides and quantification by anion-exchange liquid chromatography coupled with pulsed amperometric detection. The modified procedure is reliable and allows the handling of large numbers of flour samples at a relatively low cost, and can therefore be useful for assessing large numbers of wheat breeding lines. Using this method, grain samples taken from a diverse set of 117 wheat cultivars and breeding lines, including parents of mapping populations, were analysed for grain fructan concentration. There was significant genotypic variation among these materials, with grain fructan concentration ranging from 0.3 to 2.3% of grain dry weight. There was no evidence of strong genotype-byenvironment interaction; the fructan concentrations of the same genotypes were positively correlated over different environments in Australia. Genetic mapping was carried out to detect and map loci affecting grain fructan concentration in wheat using a doubled haploid population derived from a cross between Berkut (high fructan) and Krichauff (low fructan). Grain samples were obtained from two field sites in South Australia and one in Kazakhstan. Fructan concentration varied widely within the population (0.6-2.6% of grain dry weight), with heritability estimated as h² = 0.71. A linkage map of 528 molecular markers covering 21 wheat chromosomes was used for locating quantitative trait loci (QTL). Genetic mapping identified two major QTLs on chromosomes 6D and 7A, with the (high fructan concentration) alleles contributed from Berkut, contributing to a 30-40% increase in wheat grain fructan compared to the Krichauff alleles. Effects of these chromosome regions were validated in additional environments and in another mapping population, Sokoll/Krichauff, with the favourable alleles contributed from Sokoll. The major QTL on chromosome 7A was in the same region with a reported fructosyltransferase orthologue (AB029888), while the major QTL on chromosome 6D seemed to be co-located with a reported gene encoding for a fructan-degrading enzyme 1-exohydrolase (1-FEHw2). It is concluded that grain fructan concentration of wheat can be improved by breeding and that molecular markers could be used to select effectively for favourable alleles in two regions of the wheat genome. / Thesis (Ph.D.) - University of Adelaide, School of Agriculture, Food and Wine, 2009

Variations in gene expression have long been hypothesised to be the major cause of individual differences. An initial focus of this research thesis is to elucidate the genetic regulatory architecture of gene expression. Expression quantitative trait locus (eQTL) mapping analyses have been performed on expression levels of over 22,000 mRNAs from three tissues of a panel of recombinant inbred mice. These analyses are "single-locus" where "linkage" (i.e. significant correlation) between an expression trait and a putative eQTL is considered independently of other loci. Major conclusions from these analyses are: 1. Gene expression is mainly influenced by genetic (sequence) variations that act in trans rather than in cis; 2. Subsets of genes are controlled by master regulators that influence multiple genes; 3. Gene expression is a polygenic trait with multiple regulators. Single-locus mapping analyses are not designed for detecting multiple regulators of gene expression, and so observation of multiple-linkages (i.e. one expression trait mapped to multiple eQTLs) formed the basis of the second objective of this research project: to investigate the relationship between multiple-linkages and genotype pattern-association. A locus-pair is said to have associated genotype patterns if they have similar inheritance pattern across a panel of individuals, and these are attributed to one of fours sources: 1. linkage disequilibrium between loci located on the same chromosome; 2. non-syntenic association; 3. random association; 4. un-associated. To understand the validity of multiple-linkages observed in single-locus mapping studies, a newly developed method, bqtl.twolocus, is applied to confirm two-locus effects for a total of 898 out of 1,233 multiple-linkages identified from the three studies mentioned above as well as from seven publicly available eQTL-mapping studies. Combining these results with information of genotype pattern-association, a subset of 478 multiple-linkages has been deduced for which there is high confidence to be real.

This study comprised three major parts: a comparative physiological study of drought responses under controlled conditions; a genetic study to construct the skeleton map of a doubled haploid (DH) population; and a quantitative trait loci (QTL) analysis to identify QTLs associated with drought tolerance traits in the field. In the first part (Chapter 3), three cultivars of wheat (Triticum aestivum L.) adapted to South Australian conditions were tested for drought tolerance under cyclic drought in growth rooms and glasshouse. Extensive physiological traits, including stomatal conductance, chlorophyll content and fluorescence, ABA content, water status traits (e.g. osmotic adjustment, RWC and leaf water potential), water soluble carbohydrates (WSC) and carbon isotope discrimination (Δ¹ ³C) were measured during experiments. Through these experiments, the drought responses of the three cultivars were physiologically dissected and the likely processes contributing most to drought tolerance were identified. In the South Australian wheatbelt, cyclic drought is a frequent event, represented by intermittent periods of rainfall which can occur around anthesis and post-anthesis in wheat. Three South Australian bread wheat cultivars, Excalibur, Kukri and RAC875, were evaluated in two growth room experiments under cyclic water-limiting conditions. In the first experiment, where plants were subjected to severe water stress, RAC875 and Excalibur (drought tolerant) showed significantly (P < 0.05) higher grain yield under cyclic water availability compared to Kukri (drought susceptible), producing 44% and 18% more grain yield compared to Kukri, respectively. In the second growth room experiment, where plants were subjected to a milder drought stress, the differences between cultivars were less pronounced, with only RAC875 showing significantly higher grain yield under the cyclic water treatment. Grain number per spike and the percentage of aborted tillers were the major yield components that affected yield under cyclic water stress. Excalibur and RAC875 adopted different morpho-physiological traits and mechanisms to reduce water stress. Excalibur was most responsive to cyclic water availability and showed the highest level of osmotic adjustment (OA), highest stomatal conductance, lowest ABA content and most rapid recovery from stress under cyclic water stress. RAC875 was more ‘conservative’ in its responses, with moderate OA, high leaf waxiness, high chlorophyll content and slower recovery from stress. Within this germplasm, the capacity for osmotic adjustment was the main physiological attribute associated with tolerance under cyclic water stress, which enabled plants to recover from water deficit. In the second part (Chapter 4), the genetic linkage map of a DH population including 368 lines, which was developed from a cross between ‘RAC875’ and ‘Kukri’, was constructed. The genetic linkage map consisted of about 500 molecular markers including ~300 DArT (Diversity array technology) and ~200 SSR (Microsattelite markers). In the third part (Chapter 5), Quantitative Trait Loci (QTLs) linked to plant phenology and production traits under irrigated and drought stress conditions were mapped by means of a DH population. To phenotype the population, 368 DH lines were cultivated in two replicates in five environments (three sites across South Australian wheatbelt in collaboration with Australian Grain Technology (AGT) in 2006, and two trials in Mexico in collaboration with CYMMIT, 2007). Data of grain yield, yield components, maturity related traits and some morpho-physiological traits such as leaf chlorophyll content, leaf waxiness, plant height, peduncle length, flag leaf and spike length were measured. Raw data were then analysed for spatial variation for each single trial using the REML procedure in GenStat (version 6). The DH lines showed significant variation for plant phenology, grain yield and yield components under irrigated and drought stress conditions. QTL analyses were performed using QTLCartographer and QTLNetwork for each trait in each site. Two major QTL for maturity traits were identified on chromosomes 2BS and 2DS corresponding to Ppd-B1 and Ppd-D1, respectively. A region was identified on chromosome 7A that harbored major QTL for grain yield, number of grains per square meter, number of grain per spike and spike fertility under drought stress. For yield data in the irrigated trial, two major QTL were identified on chromosome 3B which were not detected in drought stress environments. By using different datasets in the QTL analysis (splitting the population into two subpopulation based on heading time and also adjusting the phenotypic data for heading time to eliminate heading time effect), a QTL for grain yield was consistently detected on chromosome 7A in drought-affected environments. The coincidence of a drought response index QTL on this chromosome indicated that it might be a QTL for yield response under drought. This study demonstrated that the region on the long arm of chromosome 7A identified for grain yield and yield components is a drought response QTL which is closely linked to, but separate from, a heading time QTL. This QTL cluster on chromosome 7A could be used as a good target for positional cloning and gene isolation. However further work would be required to confirm and validate the identified QTLs in this preliminary QTL analysis. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1340056 / Thesis (Ph.D.) -- University of Adelaide, School of Agriculture, Food and Wine, 2008

This study comprised three major parts: a comparative physiological study of drought responses under controlled conditions; a genetic study to construct the skeleton map of a doubled haploid (DH) population; and a quantitative trait loci (QTL) analysis to identify QTLs associated with drought tolerance traits in the field. In the first part (Chapter 3), three cultivars of wheat (Triticum aestivum L.) adapted to South Australian conditions were tested for drought tolerance under cyclic drought in growth rooms and glasshouse. Extensive physiological traits, including stomatal conductance, chlorophyll content and fluorescence, ABA content, water status traits (e.g. osmotic adjustment, RWC and leaf water potential), water soluble carbohydrates (WSC) and carbon isotope discrimination (Δ¹ ³C) were measured during experiments. Through these experiments, the drought responses of the three cultivars were physiologically dissected and the likely processes contributing most to drought tolerance were identified. In the South Australian wheatbelt, cyclic drought is a frequent event, represented by intermittent periods of rainfall which can occur around anthesis and post-anthesis in wheat. Three South Australian bread wheat cultivars, Excalibur, Kukri and RAC875, were evaluated in two growth room experiments under cyclic water-limiting conditions. In the first experiment, where plants were subjected to severe water stress, RAC875 and Excalibur (drought tolerant) showed significantly (P < 0.05) higher grain yield under cyclic water availability compared to Kukri (drought susceptible), producing 44% and 18% more grain yield compared to Kukri, respectively. In the second growth room experiment, where plants were subjected to a milder drought stress, the differences between cultivars were less pronounced, with only RAC875 showing significantly higher grain yield under the cyclic water treatment. Grain number per spike and the percentage of aborted tillers were the major yield components that affected yield under cyclic water stress. Excalibur and RAC875 adopted different morpho-physiological traits and mechanisms to reduce water stress. Excalibur was most responsive to cyclic water availability and showed the highest level of osmotic adjustment (OA), highest stomatal conductance, lowest ABA content and most rapid recovery from stress under cyclic water stress. RAC875 was more ‘conservative’ in its responses, with moderate OA, high leaf waxiness, high chlorophyll content and slower recovery from stress. Within this germplasm, the capacity for osmotic adjustment was the main physiological attribute associated with tolerance under cyclic water stress, which enabled plants to recover from water deficit. In the second part (Chapter 4), the genetic linkage map of a DH population including 368 lines, which was developed from a cross between ‘RAC875’ and ‘Kukri’, was constructed. The genetic linkage map consisted of about 500 molecular markers including ~300 DArT (Diversity array technology) and ~200 SSR (Microsattelite markers). In the third part (Chapter 5), Quantitative Trait Loci (QTLs) linked to plant phenology and production traits under irrigated and drought stress conditions were mapped by means of a DH population. To phenotype the population, 368 DH lines were cultivated in two replicates in five environments (three sites across South Australian wheatbelt in collaboration with Australian Grain Technology (AGT) in 2006, and two trials in Mexico in collaboration with CYMMIT, 2007). Data of grain yield, yield components, maturity related traits and some morpho-physiological traits such as leaf chlorophyll content, leaf waxiness, plant height, peduncle length, flag leaf and spike length were measured. Raw data were then analysed for spatial variation for each single trial using the REML procedure in GenStat (version 6). The DH lines showed significant variation for plant phenology, grain yield and yield components under irrigated and drought stress conditions. QTL analyses were performed using QTLCartographer and QTLNetwork for each trait in each site. Two major QTL for maturity traits were identified on chromosomes 2BS and 2DS corresponding to Ppd-B1 and Ppd-D1, respectively. A region was identified on chromosome 7A that harbored major QTL for grain yield, number of grains per square meter, number of grain per spike and spike fertility under drought stress. For yield data in the irrigated trial, two major QTL were identified on chromosome 3B which were not detected in drought stress environments. By using different datasets in the QTL analysis (splitting the population into two subpopulation based on heading time and also adjusting the phenotypic data for heading time to eliminate heading time effect), a QTL for grain yield was consistently detected on chromosome 7A in drought-affected environments. The coincidence of a drought response index QTL on this chromosome indicated that it might be a QTL for yield response under drought. This study demonstrated that the region on the long arm of chromosome 7A identified for grain yield and yield components is a drought response QTL which is closely linked to, but separate from, a heading time QTL. This QTL cluster on chromosome 7A could be used as a good target for positional cloning and gene isolation. However further work would be required to confirm and validate the identified QTLs in this preliminary QTL analysis. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1340056 / Thesis (Ph.D.) -- University of Adelaide, School of Agriculture, Food and Wine, 2008

This study comprised three major parts: a comparative physiological study of drought responses under controlled conditions; a genetic study to construct the skeleton map of a doubled haploid (DH) population; and a quantitative trait loci (QTL) analysis to identify QTLs associated with drought tolerance traits in the field. In the first part (Chapter 3), three cultivars of wheat (Triticum aestivum L.) adapted to South Australian conditions were tested for drought tolerance under cyclic drought in growth rooms and glasshouse. Extensive physiological traits, including stomatal conductance, chlorophyll content and fluorescence, ABA content, water status traits (e.g. osmotic adjustment, RWC and leaf water potential), water soluble carbohydrates (WSC) and carbon isotope discrimination (Δ¹ ³C) were measured during experiments. Through these experiments, the drought responses of the three cultivars were physiologically dissected and the likely processes contributing most to drought tolerance were identified. In the South Australian wheatbelt, cyclic drought is a frequent event, represented by intermittent periods of rainfall which can occur around anthesis and post-anthesis in wheat. Three South Australian bread wheat cultivars, Excalibur, Kukri and RAC875, were evaluated in two growth room experiments under cyclic water-limiting conditions. In the first experiment, where plants were subjected to severe water stress, RAC875 and Excalibur (drought tolerant) showed significantly (P < 0.05) higher grain yield under cyclic water availability compared to Kukri (drought susceptible), producing 44% and 18% more grain yield compared to Kukri, respectively. In the second growth room experiment, where plants were subjected to a milder drought stress, the differences between cultivars were less pronounced, with only RAC875 showing significantly higher grain yield under the cyclic water treatment. Grain number per spike and the percentage of aborted tillers were the major yield components that affected yield under cyclic water stress. Excalibur and RAC875 adopted different morpho-physiological traits and mechanisms to reduce water stress. Excalibur was most responsive to cyclic water availability and showed the highest level of osmotic adjustment (OA), highest stomatal conductance, lowest ABA content and most rapid recovery from stress under cyclic water stress. RAC875 was more ‘conservative’ in its responses, with moderate OA, high leaf waxiness, high chlorophyll content and slower recovery from stress. Within this germplasm, the capacity for osmotic adjustment was the main physiological attribute associated with tolerance under cyclic water stress, which enabled plants to recover from water deficit. In the second part (Chapter 4), the genetic linkage map of a DH population including 368 lines, which was developed from a cross between ‘RAC875’ and ‘Kukri’, was constructed. The genetic linkage map consisted of about 500 molecular markers including ~300 DArT (Diversity array technology) and ~200 SSR (Microsattelite markers). In the third part (Chapter 5), Quantitative Trait Loci (QTLs) linked to plant phenology and production traits under irrigated and drought stress conditions were mapped by means of a DH population. To phenotype the population, 368 DH lines were cultivated in two replicates in five environments (three sites across South Australian wheatbelt in collaboration with Australian Grain Technology (AGT) in 2006, and two trials in Mexico in collaboration with CYMMIT, 2007). Data of grain yield, yield components, maturity related traits and some morpho-physiological traits such as leaf chlorophyll content, leaf waxiness, plant height, peduncle length, flag leaf and spike length were measured. Raw data were then analysed for spatial variation for each single trial using the REML procedure in GenStat (version 6). The DH lines showed significant variation for plant phenology, grain yield and yield components under irrigated and drought stress conditions. QTL analyses were performed using QTLCartographer and QTLNetwork for each trait in each site. Two major QTL for maturity traits were identified on chromosomes 2BS and 2DS corresponding to Ppd-B1 and Ppd-D1, respectively. A region was identified on chromosome 7A that harbored major QTL for grain yield, number of grains per square meter, number of grain per spike and spike fertility under drought stress. For yield data in the irrigated trial, two major QTL were identified on chromosome 3B which were not detected in drought stress environments. By using different datasets in the QTL analysis (splitting the population into two subpopulation based on heading time and also adjusting the phenotypic data for heading time to eliminate heading time effect), a QTL for grain yield was consistently detected on chromosome 7A in drought-affected environments. The coincidence of a drought response index QTL on this chromosome indicated that it might be a QTL for yield response under drought. This study demonstrated that the region on the long arm of chromosome 7A identified for grain yield and yield components is a drought response QTL which is closely linked to, but separate from, a heading time QTL. This QTL cluster on chromosome 7A could be used as a good target for positional cloning and gene isolation. However further work would be required to confirm and validate the identified QTLs in this preliminary QTL analysis. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1340056 / Thesis (Ph.D.) -- University of Adelaide, School of Agriculture, Food and Wine, 2008

Hohenheim, Univ., Diss., 2004.

Berlin, Humboldt-University, Diss, 2003.

Submitted by Rodrigo Martins Cruz (rodrigo.cruz@ufvjm.edu.br) on 2015-12-17T16:32:54Z No. of bitstreams: 2 michel_marques_farah.pdf: 437133 bytes, checksum: efc5c1b8937d6edbcc7aaf0f1481a293 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Rodrigo Martins Cruz (rodrigo.cruz@ufvjm.edu.br) on 2015-12-17T16:33:17Z (GMT) No. of bitstreams: 2 michel_marques_farah.pdf: 437133 bytes, checksum: efc5c1b8937d6edbcc7aaf0f1481a293 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2015-12-17T16:33:19Z (GMT). No. of bitstreams: 2 michel_marques_farah.pdf: 437133 bytes, checksum: efc5c1b8937d6edbcc7aaf0f1481a293 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2010 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior (CAPES) / A simula??o de dados apresenta diversas vantagens, como proporcionar a obten??o de respostas ? sele??o e diminuir o tempo necess?rio para a avalia??o das metodologias estudadas no melhoramento gen?tico animal. Por?m, os trabalhos que utilizam simula??o empregam v?rios termos como simula??o estoc?stica, simula??o determin?stica, simula??o de Monte Carlo, simula??o em n?vel de gene e simula??o em n?vel de indiv?duo e, muitas vezes, estes termos s?o utilizados de maneiras diferentes ou em outras condi??es, causando uma diverg?ncia nos termos utilizados. Assim, os objetivos deste trabalho foram agrupar, definir e diferenciar os termos t?cnicos utilizados nos trabalhos de simula??o em melhoramento gen?tico animal e comparar e definir as propriedades dos procedimentos de simula??o em n?vel de indiv?duo e em n?vel de gene. Foram desenvolvidos tr?s cen?rios de simula??o, em n?vel de indiv?duo, em n?vel de gene com e sem marcador utilizando o software LZ5. Foram simuladas tr?s popula??es de su?nos para cada cen?rio e com diferentes herdabilidades (0,12, 0,27 e 0,47). A popula??o-base foi constitu?da de 1500 animais, sendo 750 machos e 750 f?meas e para as duas simula??es em n?vel de gene foi considerado um genoma de 2800 cM e 18 cromossomos de tamanhos aleat?rios, as caracter?sticas foram governadas por 500 locos polig?nicos dial?licos, com freq??ncias al?licas iguais e taxa de recombina??o de 0,01. Para a simula??o em n?vel de gene com marcadores, ainda foram distribu?dos marcadores distanciados igualmente a 50 cM e distribu?dos aleatoriamente 5 QTLs por todo o genoma. Os valores amostrados apresentaram bem semelhantes para os tr?s tipos de simula??o, apresentando um aumento das vari?ncias aditiva e fenot?pica e da herdabilidade nas primeiras gera??es e depois decrescendo ao longo das gera??es. J? para a m?dia fenot?pica, houve um ganho gen?tico por gera??o, indicando que todos os m?todos utilizados s?o eficientes para a obten??o de dados simulados. Assim, a vantagem da simula??o em n?vel de gene ? que ? poss?vel simular marcadores moleculares e QTLs, enquanto a simula??o em n?vel de indiv?duo ? muito eficiente para obten??o de dados como o valor gen?tico do indiv?duo e da m?dia fenot?pica da popula??o em um per?odo de tempo muito menor, pois demanda menos recursos computacionais e de algoritmos estruturados para desenvolver quando comparado com a simula??o em n?vel de gene. Portanto, define-se simula??o em n?vel de indiv?duo como uma metodologia de simula??o que consiste em gerar valores gen?ticos (G) a partir de uma distribui??o normal com m?dia e vari?ncia previamente definidas; enquanto para a simula??o em n?vel de gene a metodologia consiste em gerar os valores dos efeitos de cada loco polig?nico e seus QTLs, a partir de uma distribui??o normal com m?dia e vari?ncia previamente definidas para cada componente, e pela soma destes, obt?m-se o G de cada indiv?duo da popula??o. Para a gera??o do efeito residual (E) as duas metodologias de simula??o s?o feitas da mesma forma, gerando-se um efeito aleat?rio amostrado, tamb?m, de uma distribui??o normal e assim obt?m-se os valores fenot?picos (P) de cada indiv?duo pela soma destes dois componentes (G+E). / Disserta??o (Mestrado) ? Programa de P?s-Gradua??o em Zootecnia, Universidade Federal dos Vales do Jequitinhonha e Mucuri, 2010. / ABSTRACT The simulation data has several advantages, such as providing the obtaining responses to selection and reduce the time required for evaluation methodologies studied in animal breeding. However, simulation studies employ various terms such as simulation stochastic, deterministic simulation, Monte Carlo simulation, simulation level of gene and simulation at the individual level and often these terms are used in different ways or in other conditions, causing a divergence in the terms used. Thus, the objectives were cluster, define and differentiate the technical terms used in the work of simulation in animal breeding and compare and define the properties procedures for simulation-level and individual-level gene. There had been developed three scenarios for simulation at the individual-level and level gene, with and without marker, using the software LZ5. There had been simulated three pig populations for each scenario, with different heritabilities (0.12, 0.27 and 0.47). The base population consisted of 1500 animals, 750 males and 750 females and for both simulations at the level of the gene was considered a genome of 2800 cM, and 18 chromosomes in random sizes, the characteristics were governed by 500 loci diallelic polygenic, with equal allele frequencies and recombination rate of 0.01. For the simulation Level with gene markers, were also distributed bookmarks equally spaced at 50 cM and five QTL distributed randomly across the genome. The sampled values were very similar for the three types of simulation, an increase of additive variance and phenotype and heritability in the first generations and then decreasing to over the generations. As for the average phenotype was a genetic per generation, indicating that all methods used are efficient for obtain simulated data. Thus, the advantage of gene-level simulation is that it can simulate molecular markers and QTLs, while the simulation at individual level is very efficient for obtaining data as the individual's genetic value and phenotypic average of the population over a period of much less time, since it requires less computational resources and algorithms structured to develop, when compared with the simulation-level gene. Therefore, it is defined as the individual level simulation a methodology simulation that generates breeding values (G) from a normal distribution with mean and variance as previously defined; and the gene level simulation is defined as a methodology that generates the values of effects of each locus and their polygenic QTLs from a normal distribution with mean and variance previously defined for each component, and the sum of these gives the G of each individual in the population. For the generation of residual effect (E) the two simulation methodologies are made in the same way, generating a random effects sampled also a normal distribution and so it was obtained the phenotypic values (P) of each individual by summing these two components (G+E).

Submitted by Marco Antônio de Ramos Chagas (mchagas@ufv.br) on 2017-06-02T13:27:13Z No. of bitstreams: 1 texto completo.pdf: 890455 bytes, checksum: bf21dc226caf677a51f14dc3f09b9bb5 (MD5) / Made available in DSpace on 2017-06-02T13:27:13Z (GMT). No. of bitstreams: 1 texto completo.pdf: 890455 bytes, checksum: bf21dc226caf677a51f14dc3f09b9bb5 (MD5) Previous issue date: 2003-03-24 / Conselho Nacional de Desenvolvimento Científico e Tecnológico / O objetivo deste estudo foi realizar o mapeamento de QTL no cromossomo 6 de suínos (SSC6), associados a diversas características de desempenho, carcaça e qualidade de carne. Uma população de 617 animais F2 foi obtida do intercruzamento da geração F1, produzida pelo cruzamento divergente de dois machos da raça nativa brasileira Piau e 18 fêmeas comerciais (Landrace x Large White x Pietrain) e genotipada para 13 marcadores microssatélites. As características avaliadas na F2 foram: 1 - desempenho: número de tetas (NT), peso ao nascimento (PN), peso aos 21, 42, 63, 77 e 105 dias de idade (P21, P42, P63, P77 e P105), peso ao abate (PA), consumo de ração (CR), conversão alimentar (CA) e ganho de peso médio diário (GPD) dos 77 aos 105 dias de idade, e idade ao abate (IDA); 2 - carcaça: comprimento de carcaça pelos métodos brasileiro e americano, peso e rendimento de carcaça, espessura de toucinho na região da copa, espessura de toucinho imediatamente após a última costela, espessura de toucinho entre a última e a penúltima vértebra lombar, menor espessura de toucinho na região acima da última vértebra lombar e espessura de toucinho imediatamente após a última costela, a 6,5 cm da linha dorso-lombar, espessura de bacon, profundidade de lombo, área de olho de lombo, pesos de órgãos internos (coração, pulmões, fígado, baço e rim) e comprimento de intestino; e 3 - qualidade de carne: pH medido 45 minutos e 24 horas post-morten (pH45, pH24, respectivamente), perda de peso por gotejamento (GOTEJ), perda de peso por cozimento (COZ), perda de peso total (PTOT), gordura intramuscular (GORINT), maciez objetiva (MACIEZ) e coloração da carne [luminosidade (L), índice de vermelho (A), índice de amarelo (B), tonalidade de cor (H) e índice de saturação (C)]. Foi utilizado o método de regressão por intervalo de mapeamento, por meio do programa QTL Express. Foi encontrado um QTL significativo associado a CR, a 99 cM no cromossomo 6 de suínos. Para a característica P42, foi encontrado um QTL sugestivo localizado a 55 cM. Um mesmo gene ou grupo gênico, localizado em torno de 100 cM, pode estar atuando sobre as características CR, GPD e IDA. Embora com resultados não significativos, os genes ou grupos de genes que atuam sobre a característica peso corporal podem ser diferentes, dependendo da idade em que for medida tal característica. Foram encontrados QTLs sugestivos para as características de carcaça comprimento de carcaça e espessura de bacon, além de QTL significativo para peso do rim. QTLs sugestivos foram encontrados também para peso de pernil limpo, peso de paleta, peso de lombo e peso de filezinho. Foram encontrados QTLs significativos para as características pH45 e GOTEJ e QTLs sugestivos para GOTEJ. Não foram encontrados QTLs para as demais características. Mesmos grupos gênicos, localizados em torno de 76, 88 e 97 cM, podem estar atuando sobre as características pH45 e GOTEJ. Nas regiões dos picos da estatística F onde foram encontrados QTLs sugestivos, devem ser incluídos mais marcadores, para se confirmar a presença de QTLs de associações falso-positivas. / The objective of this study was to perform QTL mapping on swine chromosome 6 (SSC6) associated to performance, carcass and meat quality traits. The F2 population was produced by outbred cross using two sires of the Piau native brasilian breed and 18 commercial dams (Landrace x Large White). A total of 617 F2 animals were genotyped for 13 microsatellite markers. The traits evaluated on F2 population were: 1 - performance: teat number (NT); birth weight (PN); weight at 21, 42, 63, 77 and 105 days of age (P21, P42, P63, P77 and P105); slaughter weight (PA); feed intake (CR); feed-gain ratio (CA), average daily gain (GPD) to 77 at 105 days of age; and slaughter age (IDA); 2 - carcass: several carcass, cuts and internal organs weight were evaluated: heart wt, lungs wt, liver wt, kidney wt and spleen wt, and intestine length; and 3 - meat quality: pH evaluated at 45 minutes and at 24 hours "post-morten" (pH45, pH24, respectively), drip loss (GOTEJ), cooking loss (COZ), total weight loss (PTOT), intramuscular fat content (GORINT), objective tenderness (MACIEZ) and muscle color Minolta measurements: lightness (L), redness (A), yellowness (B), hue angle (H) and chroma (C). Data were analyzed by multiple regression developed for analysis of crosses between outbred lines, using the QTL Express software. It was detected a significant QTL for CR, in 99 cM on SSC6. Suggestive QTL was obtained for P42, located in 55 cM. The traits CR, GPD and IDA may be under the influence of a gene or gene group, located about 100 cM. Despite of the non significant results, the genes or genes groups related to body weight traits may be different, depending of age in what the traits are measured. Suggestive QTL were found for carcass length and bacon depth. A significant QTL for kidney wt was also found. Further suggestive QTL were found for the cut traits: skinless and fatless ham weight, picnic shoulder weight, loin weight and sirloin weight. Significant QTL were detected for pH45 and GOTEJ traits, and suggestive QTL for GOTEJ. It was not found QTL for another traits. The traits pH45 and GOTEJ may be under the influence of a gene or gene group, located about 76, 88 and 97. In the F-values peak where were detected suggestive QTL, more markers should be included, in order to verify if they are QTL in fact, or just false-positive associations. / Tese importada do Alexandria