MicroRNAs are short RNA molecules that are central to the regulation of many cellular and developmental pathways. They are processed in several stages from structured precursors in the nucleus, into mature microRNAs in the cytoplasm where they direct protein complexes to regulate gene expression through, often imperfect base-pairing with target messenger RNAs. The broad aim of this project is to better understand how polymorphisms and new mutations can disrupt microRNA processing and targeting, and ultimately define their contributions to human disease. I have taken two approaches towards this. The first approach is to comprehensively identify the microRNA targets by developing and applying a novel computational pipeline to identify microRNA binding events genome-wide in RNA-RNA interaction datasets. I use this to examine the transcriptomic diversity of microRNA binding, finding microRNA binding events along the full length of protein coding transcripts and with a variety of non-coding RNAs. This reveals enrichment for non-canonical microRNA binding at promoters and intronic regions around splice sites, and identifies highly spatially clustered binding sites within transcripts that may be acting as competitive endogenous RNAs to compete for microRNAs, effectively sequestering them. Using statistical models and new cell fractionated RNA-seq data, I rank the features of microRNAs and their binding sites which contribute to the strength and specificity of their interaction to provide a better understanding of the major determinants of microRNA targeting. The second approach is to directly identify DNA sequence changes in microRNA precursors that alter processing efficiency affecting mature microRNA abundance which are routinely overlooked in the search for disease or trait associated causal variants. I have systematically screened public datasets for both rare and common polymorphisms that overlap microRNA precursors and are correlated with mature microRNA levels as measured in short RNA sequencing. I use these eQTL SNPs to examine the most important microRNA precursor regions and sequence motifs. Several of these SNPs have been observed as risk factors in cancer or other clinically relevant traits, and correlated with microRNA processing efficiency. I demonstrate that a specific DNA change which is known to be important in the development of some cancers, is located in a microRNA precursor and affects the balance of its two products, miR-146a-3p and miR-146a-5p, that can be produced from that single precursor providing new insights into the mechanisms of microRNA production and the aspects of genetic mis-regulation that result in cancer. I find further examples of common human polymorphisms that appear to affect microRNA production from their precursors, several of these variants are independently implicated in human immune disease, cancer susceptibility and associated with other complex traits. As they exhibit a molecular phenotype and immediately lead to mechanistic hypotheses of trait causality that can be tested, these variants could provide a route into the frequently intractable problem of mechanistically linking non-coding genetic variation to human phenotypes. Applying similar studies to patient DNA has revealed rare and unique DNA changes that are now candidates for causing human disease that are being subject to follow-up experimental studies. Collectively this work has started to define which sequences changes in microRNAs are likely to disrupt their function and provides a paradigm for the analysis of microRNA sequence variants in human genetic disease.

Aflatoxins are potent carcinogens produced by the fungus Aspergillus flavus Link:Fr and are a significant preharvest problem in maize production in Texas, the southern US, and subtropical climates. Several sources of maize germplasm are available which reduce preharvest aflatoxin accumulation, but many of these sources lack agronomic performance for direct use as a parent in commercial hybrids. Tropical germplasm is a source of both resistance to aflatoxin accumulation resistance and agronomic performance traits. The goal of this study was to investigate germplasm for traits to reduce preharvest aflatoxin accumulation. The specific objectives of this research were: 1) to validate QTL estimates previously identified in lines per se and estimate new QTL associated with reduced aflatoxin accumulations and agronomic traits; 2) to evaluate agronomic characteristics of selections from a RIL population in testcrosses at multiple locations across Texas; and (3) to release agronomically desirable germplasm sources with reduced risk to preharvest aflatoxin accumulation. A total of 96 QTLs were detected across fourteen measured traits using an RIL population of 130 individuals in testcross hybrids evaluated in five environments. Three QTL detected in per se analyses were also detected in hybrid testcrosses. Previously unreported QTL were detected on chromosomes 3, 4, 8 and 9. Within each of the two years, neither subset of the RIL testcross hybrids produced grain yields equal to commercial hybrid checks in these trials, but one testcross in 2008 produced grain yield within 10 percent of commercial check hybrids and in 2009, five RIL testcrosses produced grain yield within 17 percent of the commercial check hybrids. Although RIL testcrosses did not yield more than the commercial checks, they will be a source of germplasm for reduced aflatoxin. Improved sources of maize germplasm lines Tx736, Tx739, and Tx740 have been selected for adaptation to southern US and Texas growing environments with traits that reduce aflatoxin accumulation. Each of the lines in testcross accumulated significantly fewer aflatoxins than commercial hybrids in the trial.

Wheat (Triticum aestivum L.) is one of the most important food crops, comprising the largest source of daily calorie and protein intake of human beings worldwide. Among the several diseases of wheat, Yellow Rust (YR; caused by Puccinia striiformis Westend. f. sp. tritici) and Leaf Rust (LR; caused by Puccinia triticina Erikss. & Henn.) have always been major production constraints since the domestication of wheat. For the last few decades, scientists have invested large efforts to identify, characterize and utilize Adult Plant Resistance (APR), a.k.a. slow rusting resistance, in wheat germplasm to promote durability of resistance against rust. The objectives of this study were to 1) understand the genetics of APR to YR and/or LR present in two potential wheat lines 'Quaiu 3' and 'TAM 111', and 2) map the putative Quantitative Trait Loci (QTL) associated with YR and LR resistance using DNA-based molecular markers. Two Recombinant Inbred Line (RIL) populations were subjected to YR and LR disease evaluation experiments in multiple years and locations. Visual evaluation of Disease severity (DS) and Infection Type (IT) score in both RIL populations showed that APR to YR and LR were highly heritable quantitative traits with significant correlation among experiments. In spring wheat population, composite interval mapping consistently detected four and three large effect QTL for YR and LR resistance, respectively. Among those QTLs, 1B, 3B and 1D QTL were found to be associated with previously characterized genes Lr46/Yr29, Sr2/Yr30 and Lr42, respectively. However, QTLs QYr.tam-3D and QYr.tam-2D were potentially novel. The largest YR QTL QYr.tam-2D was located on long arm of chromosome 2D explaining about 48 to 61% of the total phenotypic variation. Similarly, in winter wheat population, apart from three environment-specific QTL on chromosomes 1A, 2A and 7D, the QTL on chromosome 2B (QYr.tam-2B) was found to express consistently in multiple environments explaining about 23 to 63% of total phenotypic variation. This study has further elucidated the inheritance mechanism of APR to YR and LR present in two different wheat lines, Quaiu 3 and TAM 111, and resulted in the successful mapping and characterization of the genetic loci associated with corresponding disease resistance traits. These findings should be very useful to isolate the novel APR genes and/or directly use in wheat breeding programs to enhance durable rust resistance in diverse wheat germplasm and cultivars in the future.

In cattle, base color is attributed to activity at the melanocortin-1 receptor (MC1R), historically termed the extension locus, with alleles coding for black (ED), red (e), and wild-type (E+). These alleles, in most mammals, are presumed to follow the dominance model ED > E+ > e, although exceptions are often seen. In Bos indicus x Bos taurus F2 cattle, EDE+ heterozygotes observed were discordant with the dominance series for the MC1R alleles and displayed various degrees of reddening on an otherwise predicted black background. The objective of this study was to identify loci modifying black coat color in these individuals. The hypothesis was that degree of reddening was a quantitative trait controlled by multiple genes of small effect. Reddening was classified utilizing photographs for 5 subjective scoring systems and analyzed by general linear model procedures of SAS with fixed effects of sex, sire, family nested within sire, season of photo, and spotted status. Residuals from these models were utilized for interval analyses to identify quantitative trait loci (QTL). Analyses of 19 bovine autosomal chromosomes, identified chromosome-wise suggestive (P < 0.05) and significant (P < 0.01) QTL on bovine chromosomes (BTA) 4, 5, 15, 18, 21, 27, and 29. Unexpectedly, there was evidence of a major gene (F = 67.88) affecting reddening at 71 Mb of BTA 6 (based on build Btau4.0 of the bovine genome sequence) that accounted for 61.1% of the variation in reddening. This QTL coincided closely with a cluster of tyrosine kinase receptor genes (PDGFRA, KIT and KDR). Fitting SNP haplotypes for a 1 Mb region containing all 3 genes and centered on KIT accounted for all the variation attributed to this QTL. These data suggested that one of these 3 genes, or a gene in high linkage disequilibrium with them, was responsible for the majority of variation in degree of reddening. Two recombinants within this region identified PDGFRA as the strongest candidate gene. Functional analyses will be required to verify the role of PDGFRA and its interaction with MC1R to modify black coat color of Bos indicus influenced cattle.

Endurance exercise capacity is a powerful predictor of health status. Having low levels of endurance exercise capacity has been linked with cardiovascular disease. Variation in endurance exercise capacity, measured during a graded exercise test, has been reported across cross-section, twin, and family studies. This variation is evidence of a genetic component to the phenotype of endurance exercise capacity: however, the genetic factors responsible for explaining this variation are undefined, in part because previous research has been performed on a limited scale. Therefore, three sets of experiments were designed to identify: 1) Novel quantitative trait loci (QTL) for endurance exercise capacity in 34 strains of inbred mice using genome-wide association mapping. 2) The effect of chromosome substitution on endurance exercise capacity using linkage analysis in F2 mice. 3) The effect of chromosome substitution on endurance exercise capacity using wild-derived mice. The main findings of this dissertation are: 1) There are strain-specific differences in endurance exercise capacity across 34 strains of male inbred mice. Genome-wide association mapping identified novel putative QTL on chromosomes 2, 7, 11, and 13. 2) Linkage analysis identified a novel QTL on chromosome 14 at the 56 cM position for run time and work. Linkage analysis also identified a potential sex-specific QTL, with the identified QTL significant for male mice only. 3) Novel putative QTL were identified on chromosomes 3 and 14 in chromosome substitution mice from wild-derived mice. These data suggest that chromosome 14 is an important contributor to the genetic regulation of intrinsic endurance exercise capacity. These studies support a genetic component to endurance exercise capacity by identifying strain-specific differences and novel, putative QTL.

Soybean [Glycine max (L.) Merrill] is an important source of protein and oil for both nutritional and industrial applications. Increasing seed yield and protein concentration is the main goal of many soybean breeders to meet market demands. Soybean breeders have occasionally succeeded in producing high yielding cultivars with increased protein content using conventional means despite the negative correlation that exists between these two traits. The efficiency of breeding for seed yield and protein concentration improvement in soybean could be increased using marker assisted selection (MAS) breeding strategies to select genotypes containing favorable alleles for faster cultivar development. The objective of this study was to identify quantitative trait loci (QTL) associated with seed yield, and separately, seed protein concentration and then compare phenotypic selection (PHE) and MAS approaches for seed yield and protein concentration improvement. Two hundred and eighty two F5 derived recombinant inbred lines (RILs) were developed from a cross of Essex × Williams 82 and genotyped with 1586 single nucleotide polymorphism (SNP) markers. The population was divided by days to maturity (10 days) into three tests (early, mid and late) each with 94 genotypes, with one genotype overlapping in maturity in the mid and late tests. In 2009, the three tests, parents and checks were grown in a randomized complete block design (RCBD) in: Fayetteville, AR; Harrisburg, IL and, Knoxville, TN replicated three times, and evaluated for seed yield and protein concentration. Data were combined within each test across three locations and analyzed using the MIXED procedure of SAS to determine that there were significant genotypic differences among RILs. Composite interval mapping (CIM) detected nine seed yield and ten protein concentration QTL which may be good candidates for MAS as they were environmentally stable. Selections to compare PHE, and MAS for seed yield and protein concentration provided 8 replicated field tests in four relative maturity groups grown in a RCBD replicated three times in three locations in Tennessee, in 2010. We demonstrated that both MAS and PHE may be used to select quantitative traits; however, more studies are required to optimize MAS for quantitative trait improvement. 

München, Techn. University, Diss., 2007.

Hohenheim, Univ., Diss., 2005.

No description available.

A nivel mundial, el objetivo principal de los programas de mejoramiento de trigo candeal es desarrollar variedades con mayores rendimientos. El rendimiento potencial se define como el rendimiento de un genotipo adaptado y crecido en condi-ciones óptimas de manejo y en ausencia de factores bióticos y abióticos. El rendimiento (Kg/ha) de trigo también puede ser disectado en sus componentes, incluyendo los componentes de espigas (número de granos/espiga y peso de granos-/espiga, número de espiguillas totales/espiga, fertilidad de es-piga, número de granos/espiguillas fértiles y número de granos-/espiguillas totales), los caracteres agronómicos (altura de planta, peso de mil granos, peso hectolítrico y Índice de cose-cha) y caracteres morfológicos (largo de pedúnculo). El obje-tivo de esta tesis fue caracterizar genética y biométricamente el carácter rendimiento y sus componentes en varios ambien-tes y mapear regiones genómicas asociadas a estos caracte-res en una población de RILs de trigo candeal derivada de la cruza Kofa x UC1113. En función de este objetivo general, se plantearon los siguientes objetivos particulares: 1. Cuantificar y evaluar la respuesta de la población de RILs en varios ambientes de Argentina (localidad y año), 2. Estimar pará-metros genéticos que permitan la caracterización genética-biométrica de los caracteres, 3. Mapear QTL asociados a ren-dimiento y sus componentes, 4. Identificar marcadores mole-culares ligados a esos caracteres, 5. Realizar correlaciones entre el rendimiento y sus componentes y entre componentes entre sí y 6. Determinar regiones del genoma pleiotrópicas para estos caracteres.Para ello se evaluó el rendimiento y sus componentes en una población de 93 RILs derivadas de la cruza UC1113 x Kofa, los progenitores y 8 cultivares comer-ciales de la Argentina. Estos materiales fueron sembrados en cuatro ambientes (CEI-Barrow 2006/07, INTA-Balcarce 2007/08, CEI-Barrow 2007/08 y ACA-Cabildo 2007/08). El rendimiento y sus componentes evaluados en esta tesis fueron expresados de la siguiente forma: rendimiento (Kg/ha), peso de granos (g), peso hectolítrico (kg/hl), altura de planta (cm), largo del pedúnculo (cm), peso de granos/espiga (g), índice de cosecha (%), fertilidad de espiga (%) y en número, por espiguillas totales/espiga, granos/espiga, granos/espi-guillas fértiles y granos/ espiguillas totales. El material de estudio, la población de RILs, presentó durante el desarrollo del cultivo en los ensayos a campo, una particularidad: se observó la presencia de espigas blancas entre las espi-gas verdes o normales. Las espigas blancas se presentaron en algunos genotipos de la población, no en todos, y en di-ferente magnitud. El rendimiento fue ajustado para mapear utilizando la manera mencionada por otros autores (Khan et al. (2000) y por CIMMYT) para minimizar o eliminar el efecto espiga blanca. La distribución de los valores fenotipicos en las RILs evidenció un tipo de herencia transgresiva bi-direccional para todos los caracteres en todos los ambientes. De acuerdo al test de Shapiro-Wilk (α = 0,05) la distribución de frecuen-cias de los valores fenotípicos obtenidos (rendimiento y sus componentes para cada ambiente) fue normal en los ambien-tes para la mayoría de los caracteres. Los datos fueron completamente normales en todos las ambientes para altura de planta, espiguilla totales/espiga y peso de granos/espiga), parcialmente normales (entre uno y tres ambientes) para peso de mil granos, peso hectolítrico, largo del pedúnculo, número de granos/espiga, número de granos/espiguillas totales, índice de cosecha, fertilidad de espiga y número de granos/espi-guillas fértiles. Sin embargo, para el carácter rendimiento la distribución no fue normal en ninguno de los ambientes considerados. Los caracteres número de granos/espiga, peso de granos/espiga, peso de mil granos, peso hectolítrico, altura de planta, largo del pedúnculo, número de espiguillas totales/ espiga y número de granos/espiguillas totales mostraron en la variación fenotípica un componente genotípico mayor que el componente ambiental en la mayoría de los ambientes. Esto resultó en una alta heredabilidad de los mismos. Los caracte-res fertilidad de espiga y número de granos/espiguillas fértiles mostraron en la variación fenotípica un componente genotí-pico mayor que el componente ambiental en dos de los cuatro ambientes. Sin embargo, para el carácter rendimiento, la varia-ción fenotípica incluyó un componente ambiental elevado, mayor que el componente genotípico en la mayoría de los ambientes. La interacción genotipo x ambiente resultó ser altamente significativa por todos los caracteres, indicando que las diferencias en los caracteres entre los distintos genotipos no son las mismas en los diferentes ambientes. Los valores de LOD significativos para todos los caracteres evaluados por ambiente o en combinaciones de ambientes utilizando el test de 1000 permutaciones fueron de alrededor de 3,0. El rango de los valores de LOD para los diferentes caracteres estuvo entre 2,0 (fertilidad de espiga) y 3,4 (rendimiento). En total se encontraron 74 QTL significativos y 36 QTL probables para rendimiento y sus componentes. Los QTL significativos encontrados en esta tesis fueron: 5 para rendimiento; 7 para número de granos/ espiga; 4 para peso de granos/espiga; 8 para peso de mil granos; 5 para peso hectolí-trico; 7 para altura de planta; 8 para largo del pedúnculo; 5 para índice de cosecha; 6 para número de espiguillas totales-/espiga; 6 para fertilidad de espiga; 5 para número de granos/espiguillas fértiles y 8 para número de granos/ espi-guillas totales. Los QTL probables encontrados en esta tesis fueron: 4 para rendimiento; 3 para número de granos/ espiga; 5 para peso de granos/espiga; 3 para peso de mil granos; 4 para peso hectolítrico; 2 para largo del pedúnculo; 5 para índice de cosecha; 1 para número de espiguillas totales-/espiga; 2 para fertilidad de espiga; 6 para número de granos/espiguillas fértiles y uno para número de granos/ espiguillas totales.En total se encontraron 80 NUEVOS QTL (60 significativas y 20 probables) para rendimiento y sus componentes. Los nuevos QTL encontrados fueron: 2 para rendimiento; 7 para número de granos/ espiga; 5 para peso de granos/espiga; 5 para peso de mil granos; 7 para peso hecto-lítrico; 3 para altura de planta; 10 para largo del pedúnculo; 8 para índice de cosecha; 5 para número de espiguillas totales-/espiga; 8 para fertilidad de espiga; 11 para número de granos/espiguillas fértiles y 9 para número de granos/ espigui-llas totales.Pocos de los QTL mapeados fueron estables para el carácter en cuestión. El número de QTL estables encon-trados para cada carácter fue: uno para número de granos-/espiga; uno para peso hectolítrico; 5 para altura de planta; 4 para largo del pedúnculo; 3 para número de espiguillas totales-/espiga y uno para número de granos/espiguillas fértiles. El número de QTL probablemente estables encontrados para cada carácter fue: uno para rendimiento; uno para peso de granos/ espiga; 3 para peso de mil granos; 2 para índice de cosecha; 2 para fertilidad de espiga y uno para número de granos/espiguillas totales. La variación fenotípica para cada carácter estuvo en los siguientes rangos: rendimiento (9,67% a 27,51%), peso de mil granos (9% a 42,01%), peso hectolí-trico (7,95% a 34,53%), altura de planta(8,41% a 45%), largo del pedúnculo (6,12% a 40,6%), índice de cosecha (7,9% a 28%), número de espiguillas totales/espiga (8% a 32,5%), número de granos/espiga (8,35% a 24,6%), peso de granos-/espiga (8,54% a 22,4%), fertilidad de espiga (7,33% a 15,4%), número de granos/espiguillas fértiles (8,2% a 27,75) y número de granos/ espiguillas totales (7,15% a 23%). El efecto aditivo para cada carácter estuvo en los siguientes rangos: rendimiento (109,9Kg/ha a 335,4Kg/ha), peso de mil granos (0,60g a 1,46g), peso hectolítrico (0,24Kg/hl a 0,56Kg/hl), altura de planta(1,55cm a 3,73cm), largo del pedúnculo (0,62cm a 1,63cm), índice de cosecha (0,005% a 0,014%), número de espiguillas totales/espiga (0,20 a 0,41), número de granos/espiga (0,63 a 1,43), peso de granos/es-piga (0,03g a 0,07g), fertilidad de espiga (0,009% a 0,025%), número de granos/espiguillas fértiles (0,03 a 0,07) y número de granos/ espiguillas totales (0,03 a 0,08).Por otro lado se encontraron 7 QTL significativos y 4 QTL probables para el carácter espigas blancas. Este carácter afecta el rendimiento y sus componentes. Se encontraron 4 QTL estables para el carácter. Este carácter mostró una alta heredabilidad, en un rango de 90% - 98%, con un promedio de 94%. La variación fenotípica estuvo en un rango de 3,03% a 24,45%. El efecto aditivo estuvo en un rango de 1,13% a 3,63%. Este carácter fue especificado por una combinación de alelos aportados por ambos progenitores de la población de RILs. La variedad Kofa afecta el carácter debido a alelos ubicados sobre los cromo-somas 1B, 2B, 3A y 5A. La línea UC1113 aporta alelos ubica-dos sobre los cromosomas 3B, 5B y 7A. Para la mayoría de los caracteres, el progenitor UC1113 portó el alelo favorable, como por ejemplo para rendimiento, número de granos/espiga, peso de granos/espiga, peso de mil granos, peso hectolítrico, índice de cosecha y número de granos/espiguillas totales. Los casos donde el alelo favorable fue aportado por ambos proge-nitores (UC1113 y Kofa) fueron altura de planta, largo del pedúnculo, número de espiguillas totales/espiga, fertilidad de espiga y número de granos/espiguillas fértiles. Como se men-cionara más arriba, para la mayoría de los QTL hallados, el alelo favorable fue aportado por UC1113, siendo este el proge-nitor de mayor rendimiento. Regiones pleiotrópicas para varios caracteres fueron encontradas en los ambientes y en sus promedios. Los cromosomas que mostraron regiones pleiotró-picas incluyendo más caracteres fueron: 2B asociada al marcador wmc361, 3A asociada al marcador ksm28, 3B asociada a los marcadores gwm493, barc147 y cfd79, 4A asociada a los marcadores gwm265 y wmc258, 4B asociada al marcador ksm62 y 5A asociada al marcador gwm126. De todos los caracteres, la altura de planta y el largo del pedúnculo fueron los que mostraron una asociación más estable. Los estudios realizados en esta tesis mostraron correlaciones altamente significativas entre varios compo-nentes del rendimiento. Los componentes más correlacionados entre si fueron el carácter rendimiento con los componentes principales NG/E y PG/E y ellos mismos se encontraron correla-cionados positivamente con todos los demás componentes evaluados. Por otro lado, los caracteres que encontraron correlaciones con algunos de los componentes en todos los ambientes fueron: RTO con NG/E, PG/E y NG/EgT; PMG con PG/E; ALT con LP, PG/E y FE; LP con ALT y PG/E; IC con NG/E, PG/E, FE, NG/EgF y NG/EgT; EgT/E con NG/E y PG/E; NG/E con RTO, IC, EgT/E, PG/E, FE, NG/EgF y NG/EgT; PG/E con RTO, PMG, ALT, LP, IC, EgT/E, NG/E, FE, NG/EgF y NG/EgT; FE con ALT, IC, NG/E, PG/E y NG/EgT; NG/EgF con IC, NG/E y PG/E y NG/EgT con RTO, NG/E, PG/E, FE y NG/EgF. La selección directa o indirecta para estos componentes podría aumentar el rendimiento potencial de trigo candeal. El carácter espigas blancas mostró correlaciones negativas con todos componentes del rendimiento, por lo cual deberían no incluirse las líneas afectadas en los programas de mejora. En esta tesis, se encontraron varios QTL a lo largo de los cromosomas de trigo candeal para el carácter rendimiento y sus componentes. Los mismos y sus marcadores asociados podrán ser utilizados en el programa del mejoramiento de trigo candeal para lograr mayores rendimientos. Se trabaja en colaboración con la Asociación de Cooperativas Argentinas y otros criaderos nacionales de trigo y el Programa de mejoramiento del INTA a través del PAE 37108 (ANPCyT). Estos QTL pueden ser de utilidad para: Introducir aquellos favorables o interesantes en materiales de interés. Realizar selección asistida por marcadores en programas de mejoramiento. Analizar germoplasma para los caracteres evaluados. También podemos concluir, de lo expuesto, que todas las hipótesis planteadas se han cumplido: Se determinaron las regiones genómicas que determinan el rendimiento y sus componentes. Se estudió la respuesta de los distintos genotipos al ambiente en varios ambientes (definidos por localidad y año), que varía en distinta medida para los diferen-tes caracteres y los diferentes ambientes.El mapa genético basado en marcadores moleculares posibilitó la obtención de marcadores ligados a QTL para los caracteres investigados. / Developing crop cultivars with high grain yield has been the principal aim of durum wheat breeding programs worldwide. The potential yield is defined as the performance of an adap-ted genotype grown under optimal management and in the absence of biotic and abiotic factors. The grain yield of wheat can also be dissected into, spike characters (grain number-/spike and grain weight/spike, number of spikelets/spike, spike fertility, number of grains/fertile spikelets and number of grains/total spikelets) and also it can be correlated with the agronomic traits (plant height, thousand-grain weight, test weight and harvest index) and morphological characters (peduncle length). The objective of this thesis was to charac-terize the genetic nature of yield and its components in various environments and mapping genomic regions associated to these traits in a population of RILs of durum wheat derived from the cross Kofa x UC1113. Based on this overall objective, the following three specific objectives were planned: 1. To quantify and evaluate the response of RILs in different envi-ronments of Argentina (location and year), 2. To estimate genetic parameters that permits the genetic-biometric charac-terization of the mentioned traits, 3. To map QTL associated with yield and its components, 4. To identify molecular mar-kers linked to these traits, 5. To find correlations between yield and its components and in among components also, and 6. To determine pleiotropic regions for these traits. To fullfil these objectives, the yield and its components were evalua-ted in a population of 93 RILs derived from the cross UC1113 x Kofa, parents and 8 commertial cultivars of Argentina. These materials were planted in four environments (CEI-Barrow 2006/07, INTA-Balcarce 2007/08, CEI-Barrow 2007/08 y ACA-Cabildo 2007/08). Grain yield and its components evaluated in this thesis were expressed in the following units: grain yield (Kg/ha), thousand-grain weight (g), test weight (Kg/hl), plant height (cm), peduncle length (cm), grain weight/spike (g), harvest index (%), spike fertility (%) and in number for total spikelets/spike, grains/spike, grains/fertile spikelets and grains/total spikelets. When growing in the field the RILs showed a particularity: the presence of white spikes in between the normal green ones. These white spikes were observed only in some of the spikes and with different magni-tudes. The grain yield used for mapping was adjusted in the way mentioned by other authors (Khan et al. (2000) and uses in CIMMYT), to minimize or eliminate the effect of white spikes. The phenotypic data of RILs showed a bi-directional transgressive inheritance for all the characters in all envi-ronments. According to Shapiro-Wilk test (α = 0.05) the distribution of frequencies of phenotypic values obtained (yield and its components for each environment) were normal in all the environments for most of the characters. The distri-bution was completely normal in all environments for the cha-racters, plant height, total spikelts/spike and grain weight-/spike, partially normal (from one to three environments) for the characters thousand-grain weight, test weight, peduncle length, number of grains/spike, number of grains/total spi-kelets, harvest index, spike fertility and number of grains-/fertile spikelets. However, the character grain yield was not distributed normally in none of the environments considered. The phenotypic variance for the characters number of grains-/spike, grain weight/spike, thousand-grain weight, test weight, plant height, peduncle length, number of total spi-kelets/spike and number of grains/total spikelets, had a higher genetic component than the environmental one. This resulted in a high heritability for these characters. Spike fertility and number of grains/fertile spikelets showed the phenotypic variance more affected by the environment than from the genotype in two of the four environments. However, for grain yield, the phenotypic variance was highly influenced by the environment, higher than genotype one in majority of envi-ronments. The Genotype x Environment interaction resulted highly significant for all the characters, indicating that the differences in the characters among different genotypes are not the same in different environments. The significant LOD threshold values for all the characters were calculated for each environment and on average of all by using the 1000 permutations test and was considered around 3 for all the characters. The threshold values for different characters ran-ged between 2.0 (spike fertility) and 3.4 (grain yield). A total of 74 significant QTL and 36 probable QTLs were found for grain yield and its components. The significant QTL found in this thesis were: 5 for grain yield; 7 for number of grains-/spike; 4 for grain weight/ spike; 8 for thousand-grain weight; 5 for test weight; 7 for plant height; 8 for peduncle length; 5 for harvest index; 6 for number of total spikelets/spike; 6 for spike fertility, 5 for number of grains/fertile spikelets and 8 for number of grains/total spikelets. The probable QTL were: 4 for grain yield; 3 for number of grains/spike; 5 for grain weight/ spike; 3 for thousand-grain weight; 4 for test weight; 2 for peduncle length; 5 for harvest index; one for number of total spikelets/spike; 2 for spike fertility, 6 for number of grains/fertile spikelets and one for number of grains/total spikelets. In total, 80 new QTL (60 significant & 20 probable) were found for grain yield and its components. The new QTL were: 2 for grain yield; 7 for number of grains/spike; 5 for grain weight/ spike; 5 for thousand-grain weight; 7 for test weight; 3 for plant height; 10 for peduncle length; 8 for harvest index; 5 for number of total spikelets/spike; 8 for spike fertility; 11 for number of grains/fertile spikelets and 9 for number of grains/total spikelets. A less number of stable QTL were found for each character. The number of stable QTL for each character was: one for number of grains/spike; one for test weight; 5 for plant height; 4 for peduncle length; 3 for number of total spikelets/spike and one for number of grains/fertile spikelets. The number of probably stable QTL for each character was: one for grain yield; one for grain weight/ spike; 3 for thousand-grain weight; 2 for harvest index; 2 for spike fertility and one for number of grains/total spikelets. The phenotypic variation for each character was in the follo-wing ranges: grain yield (9.67% to 27.51%). thousand-grain weight (9% to 42.01%). test weight (7.95% to 34.53%), plant height (8.41% to 45%), peduncle length (6.12% to 40.6%), harvest index (7.9% to 28%), number of total spikelets/spike (8% to 32.5%), number of grains/spike (8.35% to 24.6%), grain weight/ spike (8.54% to 22.4%), spike fertility (7.33% to 15.4%), number of grains/fertile spikelets (8.2% to 27.75) y number of grains/total spikelets (7.15% to 23%).The additive effect for each character was in the following ranges: grain yield (109.9Kg/ha a 335.4Kg/ha), thousand-grain weight (0.60g to 1.46g), test weight (0.24Kg/hl to 0.56Kg/hl), plant height (1.55cm to 3.73cm), peduncle length (0.62cm to 1.63cm), harvest index (0.005% to 0.014%), number of total spikelets/spike (0.20 to 0.41), number of grains/spike (0.63 to 1.43), grain weight/ spike (0.03g to 0.07g), spike fertility (0.009% to 0.025%), number of grains/fertile spikelets (0.03 to 0.07) y number of grains/total spikelets (0.03 to 0.08).For the character white spikes 7 significant and 4 probable QTLs were found. This character severely affected the grain yield and its components. There were 4 stable QTL for this character. This character showed a high heritability, ranging from 90-98% with an average of 94%. The phenotypic variance was found in a range of 3.03% to 24.45%. The additive effect ranged from 1.13% to 3.63%. Both the parents contributed favorable alleles for this character. The variety Kofa affected on the chromosomes 1B, 2B, 3A and 5A. The line UC1113 provided alleles over the chromosomes 3B, 5B and 7A. UC1113 carried positive alleles for most of the characters like grain yield, number of grains/spike, grain weight/spike, thousand-grain weight, test weight, harvest index and number of grains/total spikelets. Those characters where both parents contributed with favorable alleles were, plant height, peduncle length, number of total spikelets/spike, spike fertility y number of grains/fertile spikelets. As mentioned earlier, for the majority of QTL found, the favorable allele was inherited from UC1113 being the favorable parent for grain yield. Pleiotropic regions or co-localization of various characters were found in different environments and in average of the environments. The chromosomes showing pleiotropic regions for most of the characters were: 2B associated with the marker wmc361, 3A associated with the marker ksm28, 3B associated with the markers gwm493, barc147 y cfd79, 4A associated with the markers gwm265 y wmc258, 4B associated with the marker ksm62 y 5A associated with the marker gwm126. The plant height and peduncle length showed a stable association between them. The correlation analyses showed highly significant correlations between different components of grain yield. Number of grains/spike and grain weight/spike showed a high positive correlation with grain yield, and also, they were correlated with all the other yield components. In addition, the characters correlated with some of the yield components in all environments, were: grain yield with grain number/spike, grain weight/spike y number of grains/total spikelets; 1000-grain weight with grain weight/spike; plant height with pe-duncle length, grain weight/spike y spike fertility; peduncle length with plant height y grain weight/spike; harvest index with grain number/spike, grain weight/spike, spike fertility, number of grains/fertile spikelets y number of grains/total spikelets; number of total spikelets/spike with grain num-ber/spike y grain weight/spike; grain number/spike with grain yield, harvest index, number of total spikelets/spike, grain weight/spike, spike fertility, number of grains/fertile spikelets y number of grains/total spikelets; grain weight/spike with grain yield, 1000-grain weight, plant height, peduncle length, harvest index, number of total spikelets/spike, grain number-/spike, spike fertility, number of grains/fertile spikelets y number of grains/total spikelets; spike fertility with plant height, harvest index, grain number/spike, grain weight/spike y number of grains/total spikelets; number of grains/fertile spikelets with IC, grain number/spike y grain weight/spike y number of grains/total spikelets with grain yield, grain number/spike, grain weight/spike, spike fertility y number of grains/fertile spikelets. The direct or indirect selection for these components can increase the potential yield in durum wheat. The character white spikes showed negative corre-lations with all the yield components, and therefore the affected RILs should not be included in breeding programs. In this thesis, various QTL were found throughout the chromo-somes of durum wheat for the grain yield and its components. Those QTL and their associated markers can be used in durum wheat breeding programmes to obtain higher yields. This work was conducted in close collaboration with the Asociación de Cooperativas Argentinas and other national breeding compa-nies of wheat and the breeding program of INTA through PAE 37108 (ANPCyT). The QTL found can be used for: intro-gression of favorable genes and QTLs into interesting plant materials, marker-assisted selection of plants in breeding programs and germplasm screening for the evaluated traits. We can also conclude that all hypotheses were fulfilled: Genomic regions were identified which are associated with yield and its components. The response of different genotypes to environment was studied and differed in different levels for the different characters and the different environments. The genetic map based on molecular markers allowed us to map QTLs and identify markers linked to QTL for the evaluated characters.