Sorgo sacarino e cana-de-açúcar são duas importantes gramíneas com fins potencialmente bioenergéticos. No entanto, apesar do conhecido relacionamento evolutivo, os genomas dessas espécies diferem em complexidade e tamanho. O sorgo, Sorghum bicolor, é diploide, com número básico de cromossomos igual a dez, os quais totalizam ~ 726 Mb já sequenciadas. Já a cana cultivada, Saccharum × officinarum, é um autopoliploide com frequente aneuploidia, e apresenta genoma monoploide estimado em ~ 1 Gb. Provavelmente, decorre deste fato, e dos cruzamentos interespecíficos que originaram as variedades atuais, a relativa dificuldade em se realizar estudos genéticos em cana, e, como consequência, em se incrementar os trabalhos de melhoramento na espécie. Nesse contexto, a possibilidade de integrar estudos de mapeamento entre sorgo e cana torna-se viável dado o emprego de metodologias apropriadas. O presente trabalho objetivou mapear e comparar QTLs para caracteres agro-industriais nos genomas de ambas as espécies, baseando-se no relacionamento evolutivo existente entre elas. Para tanto, foram utilizadas duas populações de mapeamento. A população de sorgo sacarino foi constituída por 223 RILs genotipadas por mais de cem mil marcadores baseados em GBS fisicamente mapeados contra o genoma da espécie. A população de cana-de-açúcar constituiu-se de uma progênie F1 segregante com 153 indivíduos genotipados por 500 marcadores baseados em géis (SSR e TRAP) e 7.049 marcadores baseados em GBS, segregando em dose única. Esses marcadores possibilitaram a construção de um mapa genético informativo e saturado, com 993 marcadores distribuídos ao longo de 223 grupos de ligação, totalizando 3.682,05 cM. Ambas as populações foram avaliadas para quatro caracteres de interesse bioenergético: altura de colmos, toneladas de colmos ou de massa verde por hectare, e porcentagens de pol de caldo e de fibra. Modelos mistos foram utilizados para a análise dos dados fenotípicos, evidenciando a existência de interação genótipo-ambiente a partir da estruturação de matrizes de variâncias-covariâncias genéticas. As médias ajustadas conjunta e marginalmente foram utilizadas na descoberta de QTLs. Para este fim, modelos de mapeamento de múltiplos intervalos uni- e multivariados foram utilizados e determinaram a descoberta de 53 e 36 regiões contendo QTLs para as populações de sorgo e cana, respectivamente, para o conjunto dos quatro caracteres. Os genomas foram comparados utilizando os marcadores baseados em GBS de cana com informação posicional em relação ao genoma do sorgo. Um total de 16 regiões sintênicas identificadas entre as espécies possibilitaram inferências a respeito do controle evolutivamente conservado dos caracteres relacionados. Mais oito regiões foram adicionadas a estas após análise de marcadores individualmente para a população de cana. A descoberta dessas regiões subjacente à variação de caracteres bioenergéticos sugere aplicações na clonagem de genes e na seleção assistida por marcadores, beneficiando os programas de melhoramento de ambas as espécies. / Sweet sorghum and sugarcane are two important grasses for bioenergy purposes. However, despite their known evolutionary relationship, the genomes of these species differ in complexity and size. Sorghum bicolor is a diploid species, with basic chromosome number of ten and ~ 726 Mb completely sequenced, whereas Saccharum × officinarum has a autopolyploid genome with frequent aneuploidy and monoploid size estimated at ~ 1 Gb. Therefore, genetic studies and breeding in sugarcane is challenging. In this context, the possibility of integrating mapping studies between sorghum and sugarcane becomes feasible given the recent development of appropriate methodologies. In this work, we aimed to map and compare QTLs for bioenergy traits in both species. To do this, two mapping populations were used. The population of sorghum consisted of 223 RILs genotyped by more than one hundred thousand GBS-based markers, which were physically mapped against the species genome. The population of sugarcane is an F1 segregating progeny with 153 individuals genotyped by 500 gel-based (SSR and TRAP) and 7,049 GBS-based single-dose markers. These markers allowed the construction of an informative and dense genetic map with 993 markers belonging to 223 linkage groups and spanning 3,682.05 cM. Both populations were evaluated for four bioenergy traits: stalk height, prodution in tons per hectare, and percentages of pol and fiber. Mixed models were used to analyze phenotypic data and showed genotype-by-environment interaction on their genetic variance-covariance structures. Joint and marginal adjusted means were used for QTL discovery. Toward this end, univariate and multivariate multiple interval mapping models were used, and a total of 53 and 36 QTLs were found for sorghum and sugarcane, respectively. Comparison of the genomes were based on GBS markers in sugarcane with relative sorghum chromosome information. A total of 16 syntenic regions were identified between the species, allowing inferences in relation to evolutionary conserved control of the related traits. In addition, eight regions were also identified by considering single marker analyses. The discovery of QTLs underlying such bioenergy traits may suggest further applications in gene cloning and marker assisted selection for both sweet sorghum and sugarcane species.

The efficacy of a novel carbohydrate extraction procedure was investigated with methylation analysis and alditol acetate method by Gas Chromatography-Mass Spectrometry. A published extraction procedure for β-glucans was compared to one developed in house. Both procedures gave a dominant glucose peak in the Gas chromatogram indicative of successful β-glucan isolation. Further linkage studies showed four linkage positions for β-glucans isolated with the published method; terminal, 1,3-linkage, 1,6-linkage and 1,3,6-linkage, while β-glucans isolated using the new method showed six linkage positions; terminal, 1,3-linkage, 1,6-linkage, 1,4-linkage, 1,2,3-linkage and 1,3,6-linkage. Diminishing β-glucan linkage peaks in the chromatogram for the published method indicated structure degradation. The results for mannan isolated with 50 mM base gave mannose as a dominant component compared to mannan isolated with 50 mM acid. Base extracted mannan also indicated a good yield of mannan in hyphal form of Candida albicans. This has not been reported with other published isolation methods.

<p>This thesis focuses on the identification of genetic factors underlying two inherited human phenotypes: hearing loss and monoamine oxidase activity. </p><p>Non-syndromic hearing loss segregating in a Swedish family was tested for linkage to 13 previously reported candidate loci for hearing disabilities. Linkage was found to two loci: DFNA12 (llq22-q24) and DFNA2 (lp32). A detailed analysis of the phenotypes and haplotypes shared by the affected individuals supported the hypothesis of digenic inheritance of hearing disability in the Swedish family. Mutation screening of α-tectorin, a gene residing within the DFNA12 region revealed a mutation of a conserved amino acid (Cys to Ser), that segregated with the disease. The identification of the mutation added support to the involvement of α-tectorin in hearing disabilities. In contrast, no mutations were identified in two candidate genes at the DFNA2 locus, that were reported to cause hearing loss in other families. It is possible that the DFNA2 locus contains a third, not yet identified, hearing loss gene. </p><p>Monoamine oxidase A (MAOA) and B (MAOB) catalyze the degradation of certain neurotransmitters in the central nervous system and are associated with specific behavioral and neuropsychiatric human traits. Activity levels of both monoamine oxidases (MAO) are highly variable among humans and are determined by unknown genetic factors. This study investigated the relationship of different MAO alleles with MAO mRNA levels and enzyme activity in human brain. Several novel DNA polymorphisms were identified in a group of Swedish individuals. Haplotypes containing several closely located MAOA polymorphisms were assessed in Asian, African, and Caucasian populations. The haplotype distribution and diversity pattern found among the three populations supported the occurrence of a bottleneck during the dispersion of modem humans from Africa. </p><p>Allelic association studies conducted on postmortem human brain samples, revealed the association between a SNP in the MAOB intron 13, and different levels of both MAO enzyme activities. This suggested that this SNP is in linkage disequilibrium with at least one novel functional DNA polymorphism that controls MAO enzyme activities in human brain. The identification of functional polymorphisms regulating the activity of these enzymes will help to elucidate the involvement of MAO in human behavior and neuropsychiatric conditions. </p>

This thesis focuses on the identification of genetic factors underlying two inherited human phenotypes: hearing loss and monoamine oxidase activity. Non-syndromic hearing loss segregating in a Swedish family was tested for linkage to 13 previously reported candidate loci for hearing disabilities. Linkage was found to two loci: DFNA12 (llq22-q24) and DFNA2 (lp32). A detailed analysis of the phenotypes and haplotypes shared by the affected individuals supported the hypothesis of digenic inheritance of hearing disability in the Swedish family. Mutation screening of α-tectorin, a gene residing within the DFNA12 region revealed a mutation of a conserved amino acid (Cys to Ser), that segregated with the disease. The identification of the mutation added support to the involvement of α-tectorin in hearing disabilities. In contrast, no mutations were identified in two candidate genes at the DFNA2 locus, that were reported to cause hearing loss in other families. It is possible that the DFNA2 locus contains a third, not yet identified, hearing loss gene. Monoamine oxidase A (MAOA) and B (MAOB) catalyze the degradation of certain neurotransmitters in the central nervous system and are associated with specific behavioral and neuropsychiatric human traits. Activity levels of both monoamine oxidases (MAO) are highly variable among humans and are determined by unknown genetic factors. This study investigated the relationship of different MAO alleles with MAO mRNA levels and enzyme activity in human brain. Several novel DNA polymorphisms were identified in a group of Swedish individuals. Haplotypes containing several closely located MAOA polymorphisms were assessed in Asian, African, and Caucasian populations. The haplotype distribution and diversity pattern found among the three populations supported the occurrence of a bottleneck during the dispersion of modem humans from Africa. Allelic association studies conducted on postmortem human brain samples, revealed the association between a SNP in the MAOB intron 13, and different levels of both MAO enzyme activities. This suggested that this SNP is in linkage disequilibrium with at least one novel functional DNA polymorphism that controls MAO enzyme activities in human brain. The identification of functional polymorphisms regulating the activity of these enzymes will help to elucidate the involvement of MAO in human behavior and neuropsychiatric conditions.

Our ability to map and sequence whole genomes is one of the most important developments in biological science. It will provide us with an unprecedented insight into the genetic background of phenotypic traits, such as disease resistance, reproduction and growth and also makes it feasible to study the processes of genome evolution. The main focus of this thesis has been to develop a linkage map of the horse (Equus caballus) genome. A secondary aim was to expand the number of physically mapped genes in the horse, allowing comparative analyses with data from the human genome map. Finally, attempts were made to identify single nucleotide polymorphisms (SNPs) on the horse Y chromosome. The development of a genome map relies on the information generated by both linkage and cytogenetical studies. To integrate genetical and physical assignments in the very early phase of equine genome map construction, 19 polymorphic microsatellite markers were isolated from lambda phage clones which, in parallel, were physically assigned to chromosomes by fluorescent in situ hybridization (FISH). The microsatellites were simultaneously mapped by linkage analysis in a Swedish reference pedigree. A first primary male autosomal linkage map of the domestic horse was constructed by segregation analysis of 140 genetic markers within eight half-sib families with, in total, 263 offspring. One hundred markers were arranged into 25 linkage groups, 22 of which could be assigned physically to 18 different chromosomes. The total map distance contained within linkage groups was 679 cM. The presented map provides an important framework for future genome mapping in the horse. Our contribution to the comparative horse genome map, was the presentation of map data for 12 novel genes using FISH and somatic cell hybrid mapping. AD chromosomal assignments except one were in agreement with human-horse Zoo-FISH data. The exception concerned the CLU gene which was mapped by synteny to ECA2 while human-horse Zoo-FISH data predicted that it would be located on ECA9. The level of SNPs on the horse Y chromosome was also investigated by DNA sequencing and denaturing high performance liquid chromatography (DHPLC) of Y chromosome-specific fragments derived mainly from BAC clone subcloning. The amount of genetic variability was found to be very low, consistent with low male effective population size.

Spinocerebellar ataxia type 7 (SCA7) is a hereditary neurodegenerative disorder affecting the cerebellum, pons and retina. SCA7 patients present with gait ataxia and visual impairment as the main symptoms. Anticipation, commonly observed in SCA7 families, is a phenomenon where an earlier age at onset and a more severe progression of disease is seen in successive generations. In order to identify the gene responsible for SCA7, we performed linkage analysis on a Swedish SCA7 kindred. Evidence for linkage of the SCA7 disease locus to a 32 cM region on chromosome 3p12-21.1, between markers D3S1547 and D3S1274, was established. A number of neurodegenerative disorders associated with anticipation are caused by expanded (CAG)n repeats in their respective disease genes. In order to isolate the SCA7 disease gene we, therefore, screened a human infant brain stem cDNA library for CAG repeat containing clones, mapping to chromosome 3. Four candidate clones were isolated and analysed, but could all be excluded as the SCA7 disease gene. In 1997, the SCA7 disease gene was identified and, as expected, shown to harbour a CAG repeat, expanded in SCA7 patients. Analysis of the SCA7 CAG repeat region in Swedish SCA7 patients demonstrated that CAG repeat size was negatively correlated to age at onset of disease. Furthermore, patients with larger repeats presented with visual impairment, whereas patients with smaller repeats presented with ataxia as the initial symptom. SCA7 is the most common autosomal dominant cerebellar ataxia in Sweden and Finland, but rare in other populations. In order to investigate if the relatively high frequency of SCA7 in these countries is the result of a founder effect in the region, a haplotype analysis was performed on all SCA7 families available. All 7 families shared a common haplotype of at least 1.9 cM surrounding the SCA7 locus. In addition, strong linkage disequilibrium was demonstrated for marker D3S1287 closely linked to the SCA7 gene, suggesting a founder effect for the SCA7 mutation in Sweden and Finland. The function of the SCA7 protein, ataxin-7, is not known and it does not show significant homologies to any previously known proteins. In order to gain insight into the function of ataxin-7 we analysed the expression of ataxin-7 in brain and peripheral tissue from SCA7 patients and controls. In brain, expression was found to be mainly neuronal with a nuclear subcellular localisation. Ataxin-7 expression was found throughout the CNS, not restricted to sites of pathology. We also confirmed previously reported findings of neuronal intranuclear inclusions (NIls) in the brains of SCA7 patients. Based on our findings, we conclude that the cell type specific neurodegeneration in SCA7 is not due to differences in expression pattern in affected and non-affected tissue or the distribution pattern of aggregated protein.

<p>Traditionally in human genetic linkage analysis, extended families were only used in the analysis of dichotomous traits, such as Disease/No Disease. For quantitative traits, analyses initially focused on data from family trios (for example, mother, father, and child) or sib-pairs. Recently however, there have been two very important developments in genetics: It became clear that if the disease status of several generations of a family is known and their genetic information is obtained, researchers can pinpoint which pieces of genetic material are linked to the disease or trait. It also became evident that if a trait is quantitative (numerical), as blood pressure or viral loads are, rather than dichotomous, one has much more power for the same sample size. This led to the&nbsp / development of statistical mixed models which could incorporate all the features of the data, including the degree of relationship between each pair of family members. This is necessary because a parent-child pair definitely shares half their genetic material, whereas a pair of cousins share, on average, only an eighth. The statistical methods involved here have however been developed by geneticists, for their specific studies, so there does not seem to be a unified and general description of the theory underlying the methods. The aim of this dissertation is to explain in a unified and statistically comprehensive manner, the theory involved in the analysis of quantitative trait genetic data from extended families. The focus is on linkage analysis: what it is and what it aims to do.&nbsp / There is a step-by-step build up to it, starting with an introduction to genetic epidemiology. This includes an explanation of the relevant genetic terminology. There is also an application section where an appropriate human genetic family dataset is analysed, illustrating the methods explained in the theory sections.</p>

Atherosklerotisch bedingte Herz-Kreislauferkrankungen zählen weltweit zu den häufigsten Todesursachen. Die vorliegende Arbeit befasst sich in einem Mausmodell mit der Identifikation neuer Genorte, welche die Ausprägung der Atherosklerose und deren Kofaktoren beeinflussen. Zu diesem Zweck wurde eine Kopplungsuntersuchung in einer Kreuzung Atherosklerose-empfindlicher C57BL/6 und BALB/c Mäuse auf dem LDL-Rezeptor defizienten Hintergrund durchgeführt. Außer der Größe der atherosklerotischen Läsionen wurden 61 weitere Phänotypen bestimmt. Als Hauptergebnis konnte ein neuer Genlocus auf dem proximalen Chromosom 2 identifiziert werden, welcher einen Einfluss auf die Größe der atherosklerotischen Läsionen an der Aortenwurzel hat. Des Weiteren zeigte sich eine Co-Segregation von Lipoproteinen (Very-Low-Density Lipoprotein (VLDL) Cholesterin und High-Density Lipoprotein (HDL) Cholesterin mit diesem Locus sowie eine Korrelation dieser Lipide mit der Läsionsgrösse. Diese Ergebnisse deuten darauf hin, dass der Effekt des Chromosom 2 Lokus auf die Atherosklerose durch genetische Faktoren des Fettstoffwechsels bedingt ist. Weitere Experimente sind notwendig um den QTL weiter einzuengen und die verantwortlichen Gene zu identifizieren.

<p>Osteoarthritis (OA) is the most common joint disorder causing chronic disability in the world population. By the year 2030, an estimated one fifth of this population will be affected by OA. Although OA is regarded as a multi-factorial disorder with both environmental and genetic components, the exact pathogenesis remains unknown. </p><p> In this study, we hypothesize that biomarkers associated with OA can be used as quantitative traits of OA, and provide enough power to identify new genes or replicate known gene associations for OA. We established an extensive family called the CARRIAGE (CARolinas Region Interaction of Aging, Genes and Environment) family. Then, we measured and analyzed seven OA-related biomarkers (HA, COMP, PIIANP, CPII, C2C, hs-CRP and GSP) in this extensive family to evaluate their association with OA clinical phenotypes. These findings suggest that OA biomarkers can reflect hand OA in this large multigenerational family. Therefore, we performed nonparametric variance components analysis to evaluate heritability for quantitative traits for those biomarkers. Finally, based upon OA biomarkers with high heritability, we performed a genome-wide linkage scan. Our results provide the first evidence of genetic susceptibility loci identified by OA-related biomarkers, indicating several genetic loci potentially contributing to the genetic diversity of OA. </p><p> Meanwhile, we identified joint hypermobility as a factor which reduces OA risk and has an inverse association with serum COMP levels in this family. The relationship between lower serum COMP and OA have been further validated in another Caucasian GOGO (Genetics of Generalized Osteoarthritis) population. Therefore, we further hypothesize that joint hypermobility, having the characteristic of a decreased OA risk, can serve as a quantitative trait for identifying protective loci for OA. Then, we performed nonparametric variance components analysis to evaluate the heritability of joint hypermobility. The result also shows joint hypermobility has substantial heritable components in this family. Lastly, based on the same genome-wide linkage scan, we identify genetic susceptibility loci for joint hypermobility. </p><p> In conclusion, our work provides the first linkage study to identify genetic loci associated with OA using biological markers. Furthermore, we have also shown genetic susceptibility loci for joint hypermobility, possibly implying protective loci for OA.</p> / Dissertation

<p>Traditionally in human genetic linkage analysis, extended families were only used in the analysis of dichotomous traits, such as Disease/No Disease. For quantitative traits, analyses initially focused on data from family trios (for example, mother, father, and child) or sib-pairs. Recently however, there have been two very important developments in genetics: It became clear that if the disease status of several generations of a family is known and their genetic information is obtained, researchers can pinpoint which pieces of genetic material are linked to the disease or trait. It also became evident that if a trait is quantitative (numerical), as blood pressure or viral loads are, rather than dichotomous, one has much more power for the same sample size. This led to the&nbsp / development of statistical mixed models which could incorporate all the features of the data, including the degree of relationship between each pair of family members. This is necessary because a parent-child pair definitely shares half their genetic material, whereas a pair of cousins share, on average, only an eighth. The statistical methods involved here have however been developed by geneticists, for their specific studies, so there does not seem to be a unified and general description of the theory underlying the methods. The aim of this dissertation is to explain in a unified and statistically comprehensive manner, the theory involved in the analysis of quantitative trait genetic data from extended families. The focus is on linkage analysis: what it is and what it aims to do.&nbsp / There is a step-by-step build up to it, starting with an introduction to genetic epidemiology. This includes an explanation of the relevant genetic terminology. There is also an application section where an appropriate human genetic family dataset is analysed, illustrating the methods explained in the theory sections.</p>