xi, 52 p. ; ill. (some col.) A print copy of this title is available through the UO Libraries under the call number: SCIENCE QH445.2 .B35 2008 / Activation of Heat shock proteins (Hsps) is critical to adaptation to low oxygen levels (hypoxia) and enduring the oxidative stress of reoxygenation. Hsps are known to be regulated by Heat shock factor (Hsf), but my results demonstrate an unexpected regulatory link between the oxygen sensing and heat shock pathways. Hsf transcription is upregulated during hypoxia due to direct binding by Hypoxia-inducible Factor-1 (HIF-1) to HIF-1 response elements in an Hsf intron. This increase in Hsf transcripts is necessary for full Hsp induction during hypoxia and reoxygenation. The HIF-1-dependent increase in Hsps has a functional impact, as reduced production of Hsps decreases viability of adult flies exposed to hypoxia and reoxygenation. Thus, HIF-1 control of Hsf transcriptional levels is a regulatory mechanism for sensitizing heat shock pathway activity in order to maximize production of protective Hsps. This cross-regulation represents a mechanism by which the low oxygen response pathway has assimilated complex new functions by regulating the heat shock pathway's key transcriptional activator. Beyond studying the regulation of specific genes. I have also developed a method to identify small, yet important, changes within entire genomes. Genetic variation is the foundation of phenotypic traits, as well as many disease states. Variation can be caused by inversions, insertions, deletions, duplications, or single nucleotide polymorphisms (SNPs) within a genome. However, identifying a genetic change that is the cause of a specific phenotype or disease has been a difficult and laborious task for researchers. I developed a technique to quickly and accurately map genetic changes due to natural phenotypic variation or produced by genetic screens. I utilized massively parallel, high-throughput sequencing and restriction site associated DNA (RAD) markers, which are short tags of DNA adjacent to the restriction sites. These RAD markers generate a genome-wide signature of fragments for any restriction enzyme. Taken together with the fact that the vast majority of organisms have SNPs that disrupt restriction site sequences, the differences in the restriction fragment profiles between individuals can be compared. In addition, by using bulk segregant analysis, RAD tags can be used as high-density genetic markers to identify a genetic region that corresponds to a trait of interest. This dissertation includes both previously published and unpublished co-authored materials. / Adviser: Eric Johnson

Purpose: The scientific knowledge of how genes affect disease expression and evolution can facilitate more effective environmental and drug therapy interventions delivered by health care professionals. The purpose of this paper is to a) describe the role of genetic science in healthcare; b) explore genotype determinants for environmental and pharmacological interventions; c) and analyze ethical dilemmas, barriers to access, and allocation of resources based on genotype. Methods: A review of literature was conducted from the disciplines of nursing, medicine, psychology, and sociology using the CINAHL, Ebsco Host, Medline, and PsychINFO databases. The search was limited to peer reviewed, full text article in English that dated from 1987 to 2011. Inclusion criteria were articles describing environmental, pharmacologic, and nutritional influence on genetic expression. Forty-five articles on genetic intervention were chosen for further review, in addition to five book publications which met inclusion criteria. Many of the sources retrieved were obtained from the biomedical sciences and published in the last decade, owing to more recent innovations in genetic discovery. Results: Disease and treatment must be approached according to genetic profiles for effectiveness and to increase health outcomes. Several variations were found regarding response to pharmaceuticals, as well as environmental exposures, based on genotype. Conclusions: Health care has been practiced using a "universal protocol" approach; however, as the literature reveals, each individual genotype must be taken into account to provide optimal care.

No description available.

Cultivated strawberry (Fragaria × ananassa) is an octoploid (2n=8x=56) species that belongs to the Rosaceae family and the high ploidy level makes genetic and molecular studies difficult. However, its commercial success because of its unique flavor and nutritious qualities has increased interest in the development of genomic resources. Fragaria vesca L. is a diploid (2n=2x=14) species with a small genome size (206 Mbp), short reproductive cycle, and facile vegetative and seed propagation that make it an attractive model for genomic studies. The availability of an efficient transformation methodology for Fragaria vesca has facilitated the use of a T-DNA mutagenesis system to develop a collection of several hundred insertional T-DNA mutants at Virginia Tech, using either of two commercially available vectors, pCAMBIA 1302 and 1304. In this study, we have used expression of the green fluorescent protein (GFP) as a tool to identify homozygous mutant lines. Three different approaches were conducted, first we identified 11 homozygous lines by PCR, then another 55 homozygous lines by absence of segregation of GFP expression in T2 seedlings, and finally we attempted to distinguish homozygous from hemizygous lines by relative GFP expression measured using a commercially available GFP meter. The latter methodology was unsuccessful due to uncontrolled variability in the readings. Continuing the characterization of our mutant population, we used thermal asymmetric interlaced PCR (TAIL-PCR) to obtain the nucleotide sequence of the genomic DNA regions that flank the T-DNA insertion sites in independent transgenic strawberry lines. Primers were designed that would amplify the derived strawberry flanking sequences in the two parents of an interspecific mapping population between the two diploid species, F. vesca x F. bucharica. The amplified products were sequenced and examined for the occurrence of SNPs (single nucleotide polymorphisms). The same primers were then used on the F2 mapping population. Segregation of SNP markers with previously mapped genetic markers allowed us to position 74 SNP markers, and hence their corresponding insertional mutants, on a well-populated genetic linkage map for the diploid strawberry. Finally, we analyzed the insertion site from more than 190 mutants looking at both the right and left borders of the T-DNA where microsimilarities of a few base pairs between ends of T-DNA and genomic DNA were observed, indicating that T-DNA integration had not occurred randomly in strawberry. We have also characterized the insertion sites through gene annotation found in the strawberry genome database. / Ph. D.

Zusammenfassung Brassica-Arten sind von großer Bedeutung für die menschliche Ernährung und für die Tierernährung. Brassica napus ist hinter der Sojabohne die zweit wichtigste Ölsaat. Brassica oleracea umfasst mehrere wichtige Gemüseformen. Die Produktivität dieser Arten wird weltweit durch Versalzung als ein biotischer Stressfaktor beeinträchtigt. Die Salztoleranz ist abhängig von der Pflanzenentwicklung, also stadienspezifisch, artspezifisch und organspezifisch. Im Vergleich zu unseren Kenntnissen über Samenglucosinolate ist wenig über die genetische Kontrolle von Blattglucosinolaten bekannt. Die Arbeit hat folgende Zielsetzungen: (1) den Einfluss von Salzstress auf zwei Entwicklungsstadien zu untersuchen, und zwar auf die Keimung und die Jungpflanzenentwicklung, und in doppel-haploiden (DH) Populationen von B. napus und B. oleracea QTL (Quantitative Trait Loci) für Salztoleranz in beiden Entwicklungsstadien zu kartieren, und (2) die Variation im Blatt-GSL Gehalt zu untersuchen und QTL zu kartieren für den GSL Gehalt in einer Kontrolle und unter Salzstress. Der Einfluss von Salzstress auf die Keimfähigkeit wurde an drei DH Populationen untersucht, zwei B. napus und eine B. oleracea Population. Die beiden erstgenannten Populationen wurde aus Alesi × H30 bzw. Mansholts × Samourai entwickelt. Die B. oleracea Population entstand aus der Kreuzung zwischen der „rapid cycling“ Linie TO1000DH3 (TO) und einer DH Linie aus dem Broccoli Early Big (EB). Die Anzahl DH Linien 138 Für die QTL Analysen wurde eine framework map verwendet mit 188, 208 bzw. 128 Markern für die Populationen Alesi × H30, Mansholts × Samourai bzw. TO × EB. Die Versuche wurden mit den Salzkonzentrationen 200 mM NaCl für B. napus und 100 mM NaCl für B. oleracea durchgeführt. Von jeder DH Linie wurden 10 Samen in 9 cm Petrischalen auf Filterpapier ausgelegt, das mit 5 ml Leitungswasser als Kontrolle bzw. 5 ml Salzlösung befeuchtet war. Die Petrischalen wurden bei 20 °C im Dunkeln inkubiert. Die Anzahl gekeimter Samen wurde täglich gezählt. Unter Salzstress war die Keimfähigkeit signifikant reduziert und die Keimgeschwindigkeit verlangsamt. Einige DH Linien übertrafen dabei ihre Eltern mit einer höheren Keimfähigkeit und Keimgeschwindigkeit. Es konnten für alle untersuchten Merkmale mehrere QTL identifiziert werden. Einige dieser QTL beeinflussen die Merkmalsausprägung sowohl in der Kontrolle als auch unter Salzstress, während andere QTL nur entweder in der Kontrolle oder in der Stressvariante auftreten. Der Einfluss von Salz auf die Jungpflanzenentwicklung wurde in der B. napus DH Population Mansholts × Samourai und in der B. oleracea Population TO × EB untersucht. Von jeder Population wurden die DH Linien und die Eltern in Topfversuchen im Gewächshaus bei halbkotrollierten Bedingungen angezogen. Die Salzkonzentrationen waren 200 mM NaCl für B. napus und 100 mM NaCl für B. oleracea. Die erfassten Merkmale waren Frischgewicht (FW), Trockengewicht (DW), Chlorophyllgehalt (SPAD), relativer Wassergehalt (RWC), Natriumgehalt (Na+ mg/g DM), Kaliumgehalt (K+ mg/g DM) sowie das Natrium/Kalium-Verhältns (Na+/K+). Der Salzstress begann 21 Tage nach Aussaat und der Versuch wurde 35 Tage nach Aussaat beendet. In beiden Populationen trat für alle Merkmale eine signifikante Variation auf. In beiden Populationen war das Wachstum unter Salzstress gehemmt, wobei FW und DW sehr stark reduziert waren während der RWC nur eine leichte Reduktion zeigte. Die anderen Merkmale zeigten unter Salzstress einen Anstieg mit Ausnahme von K+ in der B. oleracea Population. Die SPAD Werte zeigten einen Anstieg. Auch Na+ mg/g DM und Na+/K+ zeigten einen starken Anstieg. Der K+ Gehalt stieg in der B. napus Population unerwartet an, während er in der B. oleracea Population abnahm. Das Aufrechterhalten von hohen K+ Konzentrationen unter Salzstress ist ein Merkmal für Salztoleranz. Diese Ergebnisse unterstützen frühere Ergebnisse dass B. napus eine höhere Salztoleranz hat als B. oleracea. In beiden Populationen wurde sowohl in der Kontrolle als auch unter Salzstress eine Reihe von QTL identifiziert. In der B. napus Population wurden auf verschiedenen Kopplungsgruppen (LG) QTL „hotspots“ entdeckt. Der größte „hotspot“ lag auf LG C3. Auch in der B. oleracea Population wurde auf LG C3 ein „hotspot“ entdeckt mit QTL für mehrere Merkmale. Hier liegen also in derselben Region des Genoms Gene für mehr als nur ein Merkmal sowohl in der Kontrolle als auch unter Salzstress. Die Variation dieser Merkmale wird entweder von einem Gen mit pleiotropem Effekt gesteuert oder von mehreren unabhängigen Genen. Regionen mit QTL für mehrere Merkmale sind von großem Interesse weil dadurch mehr als nur ein Merkmal gleichzeitig verbessert werden kann. Unter den gleichen Bedingungen wurde in den beiden B. napus bzw. B. oleracea Populationen auch die Variation in den Blatt-GSL untersucht. Die Elternlinien beider Populationen unterschieden sich stark in GLS Gehalt und Zusammensetzung. In der B. napus Population hatte Mansholts einen im Vergleich zu Samourai hohen GSL Gehalt sowohl in der Kontrolle als auch unter Salzstress. Unter Salzstress verhielten sich die beiden Eltern unterschiedlich, Mansholts zeigte einen Anstieg und Samourai eine Abnahme des GSL Gesamtgehalts. In der B. oleracea Population zeigte die Elternlinie TO eine höheren GSL-Gehalt als der Elter EB. Die einzelnen GSL Komponenten zeigten in beiden DH Populationen eine Abnahme bei Salzstress mit Ausnahme von RAA und GBC bei B. napus und GBC bei B. oleracea. Aufgrund ihrer antioxidativen Eigenschaften könnte der Anstieg von RAA und GBC dazu dienen die ROS zu detoxifizieren, die als Reaktion auf Salzstress produziert wurden. Mehrere QTL wurden sowohl in der Kontrolle als auch unter Salzstress kartiert. In der B. napus Population wurden QTL „hotspots“ in Regionen identifiziert in denen bereits früher QTL für Samen-GSL lokalisiert wurden. Dies war vor allem auf LG A9 und LG C2 der Fall. In der B. oleracea Population wurden QTL „hotspots“ auf LG C9 und LG C7 lokalisiert. Das gleichzeitige Auftreten von QTL an derselben Position lässt sich teilweise dadurch erklären dass es sich um Komponenten derselben GSL Gruppen handelt. Es gab keine Übereinstimmung zwischen den QTL für die Keimfähigkeit unter Salzstress und den QTL für Variation bei Jungpflanzen. Dies weist darauf hin dass für die Salztoleranz während der Pflanzenentwicklung unterschiedliche Mechanismen verantwortlich sind. Durch die Kombination von QTL für Salztoleranz in den unterschiedlichen Entwicklungsstadien lässt sich eine verbesserte Anpassung an Salzstress erreichen.

Flax (Linum usitatissimum L.) is a commercial oilseed crop in Canada. Globally flax is known for industrial oil and fiber. Flaxseed contains Omega 3 fatty acid, lignans like secoisolariciresinol diglucoside (SDG), flavonoids and polysaccharides which offer potential health benefits. Conventional flax cultivars are brown seeded and few mutant lines are yellow seeded. The darkness of seed colour depends on the presence of polymerized proanthocyanidins (PA; condensed tannins) in the seed coat. PAs are the product of the phenylpropanoid pathway. Previous genetic studies by Mittapalli and Rowland (2003) on G1186/94 showed the seed colour trait was governed by the homozygous recessive alleles at D locus and the same locus is closely linked to white or pink flower petals. To start with, single seeds of already developed stable recombinant inbred lines (RILs) (of F8:9 generation) from a cross of yellow seeded European recessive line (G1186/94) and brown seeded CDC Bethune (popular variety) were grown. In this study, seed colour phenotyping was done by measuring seed colour of each RIL in Red-Green-Blue (RGB) values. To understand the genetic basis of flax seed and flower colour, mapping with single sequence repeats (SSRs) and CAPS (Cleaved Amplified Polymorphic Sequences) markers were used. For the first time, a framework genetic linkage map was constructed from populations of CDC Bethune/ G1186/94 containing 19 linkage groups (LGs). LG 1 with four SSR markers was found to be linked with the seed colour locus D. During the fine-mapping, two SSR markers (LuM566 and Lu2351) were found to be linked with the seed colour trait. The D locus has been confined in a 2.8 cM region and the closest marker was LuM566 at a distance of 0.6 cM. This was observed to be a stable locus in two growth trials and in different environments with logarithm of odds (LOD) above 39 and more than 84 % of the trait expressed by the major locus in both trials. As there were no recombinants (off types) for flower colour in F8:9 plants i.e brown-seeded lines produced blue flowers and yellow-seeded lines produced white flowers, the same locus holds well for the flower colour trait. The marker associated with seed and flower colour in G1186/94 (European recessive yellow line) was identified and can be used in flax breeding. Additionally, an interesting putative candidate gene of potential significance was identified through genomics assisted gene search from the flax whole genome sequence database. The gene expression analyses showed lower expression of putative flavonoid 3’ hydroxylase (F3’H) (a gene involved in flavonoid biosynthesis pathway) in both seed coat and flower petal tissues of G1186/94 as compared to CDC Bethune. Therefore, this study represents the first report on genetic mapping based putative candidate gene finding for recessive yellow seed colour mutation in the D locus in flax.

The link between the genotype and the phenotype of an organism is immensely complex. Despite this it can, to a great extent, be captured using models that assume that gene variants combine their effects in an additive manner. This thesis explores aspects of genetics that cannot be fully captured using such additive models. Using experimental data from three different model organisms, I study two phenomena that fall outside of the additive paradigm: genetic interactions and genetic variance heterogeneity. Using the model plant Arabidopsis thaliana, we show how important biological insights can be reached by exploring loci that display genetic variance heterogeneity. In the first study, this approach identified alleles in the gene CMT2 associated with the climate at sampling locations, suggesting a role in climate adaption. These alleles affected the genome wide methylation pattern, and a complete knock down of this gene increased the plants heat tolerance. In the second study, we demonstrate how the observed genetic variance heterogeneity was the result of the partial linkage of many functional alleles near the gene MOT1, all contributing to Molybdenum levels in the leaves. Further, we explore genetic interactions using data from dogs and budding yeast (Saccharomyces cerevisiae). In the dog population, two interacting loci were associated with fructosamine levels, a biomarker used to monitor blood glucose. One of the loci displayed the pattern of a selective sweep in some of the studied breeds, suggesting that the interaction is important for the phenotypic breed-differences. In a cross between two strains of yeast, with the advantage of large population size and nearly equal allele frequencies, we identified large epistatic networks. The networks were largely centered on a number of hub-loci and altogether involved hundreds of genetic interactions. Most network hubs had the ability to either suppress or uncover the phenotypic effects of other loci. Many multi-locus allele combinations resulted in phenotypes that deviated significantly from the expectations, had the loci acted in an additive manner. Critically, this thesis demonstrates that non-additive genetic mechanisms often need to be considered in order to fully understand the genetics of complex traits.

A surdez pode ser causada por fatores ambientais, genéticos ou ambos. Do ponto de vista genético, a surdez é extremamente heterogênea, pois é condicionada por mutações em diversos genes localizados em diferentes cromossomos, podendo exibir mecanismos de herança diversos. O objetivo desse estudo foi identificar novos genes e mutações relacionados à perda auditiva de herança autossômica dominante. Foram estudadas molecularmente cinco famílias. A família 1 foi averiguada na cidade de Maringá-PR. Apresenta 20 indivíduos afetados pela síndrome Oto-branquial (BOS). Estudos de mapeamento gênico com arrays de SNPs mostraram um Lod Score sugestivo de ligação para uma região do cromossomo 8, onde está localizado o gene EYA1, já relacionado à síndrome. O sequenciamento dos exons do gene não revelou mutação. No entanto, estudos de array-CGH e de PCR em tempo real permitiram detectar uma duplicação de aproximadamente 86 kb no gene EYA1 em 11 dos 12 indivíduos afetados testados da família, ausente nos indivíduos fenotipicamente normais. Portanto, concluímos que a síndrome nessa família é decorrente dessa duplicação, nunca antes descrita em casos de BOS. A família 2 foi averiguada na cidade de São Miguel-RN, com 16 indivíduos afetados por perda auditiva de herança autossômica dominante não sindrômica. Estudos de mapeamento gênico com marcadores moleculares do tipo microssatélites e cálculos de Lod Score indicaram uma região no cromossomo 3 como candidata a conter o gene responsável pelo fenótipo na família. Estudos de sequenciamento massivo em paralelo da amostra de um indivíduo afetado apontaram três variantes missense em heterozigose como sendo as mais prováveis causas do fenótipo, mas duas delas foram excluídas com base em estudos de segregação. A terceira variante foi triada em uma coleção de 47 amostras de probandos de famílias com surdez autossômica dominante, mas não foi encontrada. Há estudos em andamento buscando confirmar seu papel na surdez hereditária. A família 3 foi averiguada na cidade de São Paulo-SP e apresenta 15 indivíduos afetados por perda auditiva de herança autossômica dominante não sindrômica. Estudos de mapeamento gênico com o uso de arrays de SNPs e cálculos de Lod Score mapearam uma região no cromossomo 20 como candidata a conter o gene responsável pelo fenótipo. Estudos de sequenciamento massivo em paralelo de amostras de dois indivíduos afetados apontaram três variantes missense em heterozigose como as mais prováveis causas do quadro. Estudos de segregação excluíram duas das variantes e a terceira variante foi triada na coleção de 47 amostras de probandos de famílias com surdez de herança dominante, mas não foi encontrada. Outros estudos estão em andamento para verificar seu papel na surdez. A família 4 foi averiguada na cidade de Porto Alegre-RS e apresenta 11 indivíduos afetados por perda auditiva de herança autossômica dominante não sindrômica. Estudos de mapeamento genético com o uso de arrays de SNPs e de cálculo de Lod Score mapearam duas regiões, nos cromossomos 14 e 22, como candidatas a conter o gene responsável. Estudos de sequenciamento massivo em paralelo em amostras de três indivíduos afetados apontaram 3 variantes missense em heterozigose nas regiões mapeadas (duas no cromossomo 14 e uma no cromossomo 22). Observamos que somente a variante rs80338828 no gene MYH9, no cromossomo 22, segrega com o fenótipo. Essa variante já foi previamente relacionada à perda auditiva de herança autossômica dominante e provavelmente explica a perda auditiva na família. A família 5 foi averiguada na cidade de São Paulo-SP e apresenta 30 indivíduos afetados por perda auditiva de herança autossômica dominante e não sindrômica. Estudos de ligação com arrays de SNPs e cálculos de Lod Score não apontaram a região candidata devido a limitações computacionais e à estrutura da genealogia. Estudos de sequenciamento massivo em paralelo de amostras de quatro indivíduos afetados apontaram 13 variantes presentes nos quatro, em heterozigose. Foram selecionadas para estudo duas das variantes, uma no gene MYO3A, por se tratar de um gene já relacionado à perda auditiva e uma no gene LONP2, por se tratar de uma mutação de códon de parada prematuro. Estudos de segregação mostraram que a variante no gene LONP2 não segrega com o fenótipo na família e que a variante no gene MYO3A parece segregar com o fenótipo, exceto por sua ausência em um indivíduo afetado e sua presença em sete indivíduos aparentemente normais, que poderiam ser não-penetrantes. Mutações no gene MYO3A já foram relacionadas previamente à perda auditiva de herança autossômica recessiva, mas chama a atenção o fato do padrão de herança nessa família ser o dominante. Mais estudos são necessários para confirmar o papel dessa e de outras variantes no fenótipo da família. Portanto, o estudo molecular das cinco famílias revelou dois possíveis novos genes de surdez, um novo mecanismo mutacional na síndrome BOS, mutação em gene já conhecido e hipótese de novo mecanismo de herança para mutação no gene MYO3A / Deafness can be caused by environmental factors, genetic factors or both. Genetic deafness is highly heterogeneous, because it is caused by mutations in many genes located in different chromosomes and can be explained by different inheritance patterns. The aim of this study was to identify new genes and search for new mutations related to autosomal dominant hearing loss. Five families were selected for molecular studies. Family 1 was ascertained in Maringá-PR. It includes 20 individuals affected by Branchio-oto syndrome (BOS). Genomic scanning with SNP arrays showed suggestive Lod scores on a region at chromosome 8, where the EYA1 gene is located, already known to be related to this syndrome. Sequencing of all exons of the gene did not reveal the mutation. However, array-CGH and real time PCR studies detected a duplication of 86 kb on EYA1 gene, in 11 of the 12 affected individuals tested, and it was absent in the unaffected individuals. Our findings implicate this EYA1 duplication in the BOS1 phenotype observed in the pedigree. Large duplications in EYA1 gene were not reported before. Family 2 was ascertained at São Miguel-RN, with 16 individuals affected by non syndromic autosomal dominant hearing loss. Genomic scanning with microsatellites and Lod score calculations mapped a region at chromosome 3 as candidate to contain the gene responsible for the phenotype in the family. Massive Parallel Sequencing of a sample from one affected individual indicated 3 missense variants in heterozygosis that could explain the phenotype. Two variants were excluded after segregation studies. The third variant was screened in a cohort of 47 probands from families with individuals affected by autosomal dominant hearing loss and it was not detected. Further studies are needed to confirm its role in hearing loss. Family 3 was ascertained in São Paulo-SP and presents 15 individuals affected by non syndromic autosomal dominant hearing loss. Genomic scanning with SNP arrays and Lod score calculations suggested a region at chromosome 20 as the candidate to contain the gene that causes the phenotype. Massive Parallel Sequencing with samples from two affected individuals suggested 3 missense variants in heterozygosis that could explain the phenotype. Two variants were excluded after segregation studies and one variation was selected as the best candidate to explain the phenotype. We searched for this variant in a cohort of 47 probands from families with individuals affected by autosomal dominant hearing loss and it was not detected. Other studies are being conducted to confirm the role of this variation in deafness. Family 4 was ascertained at Porto Alegre-RS and presents 11 individuals affected by non syndromic autosomal dominant hearing loss. Genomic scanning with SNP arrays and Lod score calculations indicated two regions, at chromosomes 14 and 22, as the best candidates to contain the hearing loss gene. Massive Parallel Sequencing studies with samples from 3 affected individuals indicated 3 missense variants in heterozygosis (two variants at chromosome 14 and one at chromosome 22). We observed that only the variant rs80338828, in MYH9 gene, in chromosome 22, segregates with the phenotype. This variant was previously related to autosomal dominant hearing loss and probably explains the phenotype observed in this family. Family 5 was ascertained at São Paulo-SP and presents 30 individuals affected by non syndromic autosomal dominant hearing loss. Genomic scanning with SNP arrays and Lod score calculations did not indicate candidate regions due to computer limitations. Massive Parallel Sequence studies with samples from four affected individuals suggested 13 candidate variants, in heterozygosis. Two variants were selected for further studies: one in MYO3A, previously related to hearing loss, and one in LONP2 gene, a nonsense mutation. Segregation studies showed the LONP2 variant did not segregate with the phenotype and MYO3A variant seems to segregate with the phenotype, except for its absence in one affected individual and its presence in seven unaffected ones, who could be nonpenetrants. Mutations in MYO3A were previously related to autosomal recessive hearing loss, but the family described here presents autosomal dominant pattern of inheritance. More studies are needed to explain the role of this variant in the phenotype. Thus, the molecular study of five pedigrees revealed two novel candidate genes for deafness, one novel mutation mechanism in BOS, a mutation in one previously known gene and the possibility of a novel inheritance mechanism for a MYO3A mutation.

O mapeamento genético e a genética funcional de doenças são de grande importância na pesquisa médica e genômica. Para estas finalidades o estudo de associação entre fatores de risco genéticos e doença tem ganhado destaque na literatura. Neste trabalho disserta-se sobre a análise de associação aplicada ao mapeamento genético de doenças, caracterizando diferentes possibilidades de planejamentos experimentais e de utilização de modelos estatísticos de análise de dados. As formalizações estatísticas, como o tipo de delineamento experimental, a inclusão ou não de dados familiares, bem como a escolha do método estatístico de análise, que são decisivos na avaliação do poder dos testes obtidos e na sua aplicabilidade ao mapeamento genético, também são discutidas. Além disso, considera-se a análise de associação por meio de modelos de regressão logística em que, as análises de dados genéticos são abordadas via dados no nível genotípico e cromossômico. Finalmente, os conceitos supracitados são aplicados a conjuntos de dados reais, fornecidos pelo Laboratório de Cardiologia e Genética Molecular do InCor/USP, com o objetivo de ilustrar o problema teórico tratado e motivar a aplicação das metodologias estatísticas envolvidas. / The genetic mapping and functional genetics have great importance in the genomics research. In order to conduct these researches the study of the association between genetic risk factors and disease has been becoming an important role in the literature. In this work we consider the association analyses applied to the genetic diseases mapping, charactering different possibilities of experimental designs and the use of statistical models to analyze data sets. The statistical concepts, as the kind of experimental design, the inclusion of familiar records or not, as well as the choice of the statistical analyze method, which are very important to the evaluation of the power of the tests obtained and to their applicability in the genetic mapping, are also discussed. Furthermore, we consider the association analysis at person level and chromosome data set. Finally, the latter concepts are applied to a real data set, provided by the Molecular Genetic and Cardiology Laboratory of InCor/USP, in order to illustrate the theoretical problem treated in this work and to motive the use of the involved statistical methodologies.

Um dos principais desafios do melhoramento de milho doce é aumentar a eficiência da seleção para produtividade e qualidade dos grãos. Uma das formas de aumentar essa eficiência é a utilização de marcadores moleculares para auxiliar a seleção nos programas de melhoramento. Para isso, o estudo da herança por meio do mapeamento de QTL é uma ferramenta importante para o conhecimento da base genética dos caracteres e para gerar informações que possam ser utilizadas na seleção assistida por marcadores moleculares. O presente estudo teve como objetivo mapear QTL em testecrosses de milho doce para produção de grãos, seus componentes e caracteres de qualidade, e avaliar o efeito de diferentes testadores e ambientes no mapeamento de QTL. Para tanto, foi utilizada uma população obtida do cruzamento entre as linhagens B532 e B605 do mesmo grupo heterótico e contrastantes para diversos caracteres. Duzentas e cinqüenta e seis progênies F4:5 foram genotipadas com marcadores moleculares SNP para a construção do mapa genético. Posteriormente, essas progênies foram cruzadas com os testadores A36 e A17 de um grupo heterótico distinto do grupo da população. Os testecrosses obtidos foram avaliados em dois ambientes, Uberlândia, MG, e Itatiba, SP, em látices simples 16 x 16. Os caracteres avaliados foram produção de grãos (PG), número de fileiras de grãos (NF), comprimento de espiga (CE), diâmetro de espiga (DE), comprimento de grãos (CG), coloração de grãos (CL), maciez de grãos (MC) e doçura de grãos (DÇ). O método de mapeamento por intervalo composto expandido para múltiplos ambientes (mCIM) foi utilizado para mapear QTL e detectar a interação QTL x ambiente. Foram mapeados 116 QTL, sendo 21 para PG, 17 para NF, 22 para CE, 14 para DE, 12 para CG, 11 para CL, 11 para MC e 8 para DÇ. Com exceção de 2 QTL para NF que explicaram 12,19% e 10,03% e de 1 QTL para CE que explicou 10,48%, todos os outros explicaram menos de 10% da variância fenotípica. Considerando todos os caracteres, 91% dos QTL mapeados foram específicos para cada testador, evidenciando uma elevada interação QTL x testador. Dos 116 QTL mapeados apenas 22 apresentaram interação QTL x ambiente, indicando que houve baixa interação QTL x ambiente. Dessa forma, a maioria dos caracteres de importância econômica em milho doce foi controlada por muitos QTL de baixos efeitos na variação fenotípica, os quais apresentaram uma elevada interação QTL x testador e uma reduzida interação QTL x ambiente. O elevado número de QTL controlando os caracteres e a elevada interação QTL x testador mostram a complexidade da aplicação da seleção assistida no melhoramento de milho doce. / One of the main challenges in sweet corn breeding is to improve the efficiency of selection for grain yield and quality traits. The use of molecular markers would be a way to increase the selection efficiency in breeding programs. QTL mapping is an important tool for understanding the genetic basis of the traits and to generate information that can be used in marker assisted selection. This study aimed to map QTL in sweet corn testecrosses for grain yield, its components and quality traits, and evaluate the effect of different testers and environments in QTL mapping. For this study a population was obtained by crossing lines B532 and B605, from the same heterotic group and contrasting for different traits. Two hundred and fifty-six F4:5 progenies were genotyped with SNP markers for the construction of the genetic map. Subsequently, these progenies were crossed with the testers A36 and A17 from a different heterotic group than the population. The obtained testecrosses were evaluated in two environments, Uberlândia, MG, e Itatiba, SP, in a simple lattice design 16 x 16. The traits evaluated were: grain yield (PG); number of rows (NF); ear length (CE); ear diameter (DE); kernel depth (CG), kernel color (CL); kernel tenderness (MC) and kernel sweetness (DÇ). The composite interval mapping extended to multiple environments (mCIM) was used to map QTL and to detect the QTL x environment interaction. One hundred and sixteen QTL were mapped; with 21 for PG, 17 for NF, 22 for CE, 14 for DE, 12 for CG, 11 for CL, 11 for MC and 8 for DÇ. With the exception of 2 QTL for NF which explained 12%,19% and 10,03% and by 1 QTL for CE which explained 10,48%, all the others explained less than 10% of the phenotypic variance. Considering all of the traits, 91% of the mapped QTL were specific to each tester, indicating a high QTL x tester interaction. Out of the 116 QTL mapped, only 22 showed significant QTL x environment interaction, indicating that there was a small QTL x environment interaction. Thus, most traits of economic importance in sweet corn seem to be controlled by many QTL with small effects, which showed a large QTL x tester interaction and a small QTL x environment interaction. The large number of QTL controlling the traits and the large QTL x tester interactions demonstrate the complexity of the implementation of marker assisted selection in sweet corn breeding.