RAPD analysis of genetic variability in a multiprovenance base population of Eucalyptus grandis hill ex maiden

This study aimed to evaluate the genetic variability among individuals of a base population of Eucalyptus grandis and to build a molecular marker database for the analyzed populations. The Eucalyptus grandis base population comprised 327 individuals from Coff's Harbour, Atherton and Rio Claro. A few plants came from other sites (Belthorpe MT. Pandanus, Kenilworth, Yabbra, etc.). Since this base population had a heterogeneous composition, the groups were divided according to geographic localization (latitude and longitude), and genetic breeding level. Thus, the influence of those two factors (geographic localization and genetic breeding level) on the genetic variability detected was discussed. The RAPD technique allowed the evaluation of 70 loci. The binary matrix was used to estimate the genetic similarity among individuals using Jaccard's Coefficient. Parametric statistical tests were used to compare within-group similarity of the means. The obtained results showed that the base population had wide genetic variability and a mean genetic similarity of 0.328. Sub-group 3 (wild materials from the Atherton region) showed mean genetic similarity of 0.318. S.P.A. (from Coff's Harbour region) had a mean genetic similarity of 0.322 and was found to be very important for maintenance of variation in the base population. This can be explained since the individuals from those groups accounted for most of the base population (48.3% for it). The base population plants with genetic similarity higher than 0.60 should be phenotypically analyzed again in order to clarify the tendency of genetic variability during breeding programs.

Genetic analysis and cAMP measurement: comparison between lean and obese anovulating mice

PURPOSE: To evaluate genes differentially expressed in ovaries from lean (wild type) and obese (ob/ob) female mice and cyclic AMP production in both groups.METHODS: The expression on messenger RNA levels of 84 genes concerning obesity was analyzed through the PCR array, and cyclic AMP was quantified by the enzyme immunoassay method.RESULTS: The most downregulated genes in the Obesity Group included adenylate cyclase-activating polypeptide type 1, somatostatin, apolipoprotein A4, pancreatic colipase, and interleukin-1 beta. The mean decrease in expression levels of these genes was around 96, 40, 9, 4.2 and 3.6-fold, respectively. On the other hand, the most upregulated genes in the Obesity Group were receptor (calcitonin) activity-modifying protein 3, peroxisome proliferator activated receptor alpha, calcitonin receptor, and corticotropin-releasing hormone receptor 1. The increase means in the expression levels of such genes were 2.3, 2.7, 4.8 and 6.3-fold, respectively. The ovarian cyclic AMP production was significantly higher in ob/ob female mice (2,229±52 fMol) compared to the Control Group (1,814±45 fMol).CONCLUSIONS: Obese and anovulatory female mice have reduced reproductive hormone levels and altered ovogenesis. Several genes have their expression levels altered when leptin is absent, especially adenylate cyclase-activating polypeptide type 1.

Genetic and antigenic analysis of Babesia bigemina isolates from five geographical regions of Brazil

A molecular epidemiological study was performed with Babesia bigemina isolates from five geographical regions of Brazil. The genetic analysis was done with random amplification of polymorphic DNA (RAPD), repetitive extragenic palindromic elements-polymerase chain reaction (REP-PCR) and enterobacterial repetitive intergenic consensus sequences-polymerase chain reaction (ERIC-PCR) that showed genetic polymorphism between these isolates and generated fingerprinting. In RAPD, ILO872 and ILO876 primers were able to detect at least one fingerprinting for each B. bigemina isolate. The amplification of B. bigemina DNA fragments by REP-PCR and ERIC-PCR gave evidence for the presence in this haemoprotozoan of the sequences described previously in microorganisms of the bacterial kingdom. For the first time it was demonstrated that both techniques can be used for genetic analysis of a protozoan parasite, although the ERIC-PCR was more discriminatory than REP-PCR. The dendogram with similarity coefficient among isolates showed two clusters and one subcluster. The Northeastern and Mid-Western isolates showed the greatest genetic diversity, while the Southeastern and Southern isolates were the closest. The antigenic analysis was done through indirect fluorescent antibody technique and Western blotting using a panel of monoclonal antibodies directed against epitopes on the merozoite membrane surface, rhoptries and membrane of infected erythrocytes. As expected, the merozoite variable surface antigens, major surface antigen (MSA)-1 and MSA-2 showed antigenic diversity. However, B cell epitopes on rhoptries and infected erythrocytes were conserved among all isolates studied. In this study it was possible to identify variable and conserved antigens, which had already been described as potential immunogens. Considering that an attenuated Babesia clone used as immunogen selected populations capable of evading the immunity induced by this vaccine, it is necessary to evaluate more deeply the cross-protection conferred by genetically more distant Brazilian B. bigemina isolates and make an evaluation of the polymorphism degree of variable antigens such as MSA-1 and MSA-2.

Genetic grouping of avian infectious bronchitis virus isolated in Brazil based on RT-PCR/RFLP analysis of the S1 gene

Twelve Brazilian isolates and one reference vaccine strain of avian infectious bronchitis virus (IBV) were propagated in embryonating chicken eggs. The entire S1 glycoprotein gene of these viruses was analysed by reverse-transcriptase-polymerase chain reaction and restriction fragment length polymorphism (RT-PCR-RFLP), using the restriction enzymes HaeIII, XcmI and BstyI. The RFLP patterns led to the classification of these isolates into five distinct genotypes: A, B, C, D and Massachusetts. Five of twelve isolates were grouped in Massachusetts genotype and the remaining seven viruses were classified into four distinct genotypes: A (2), B (2), C (2) or D (1). Such genotyping classification agreed with previous immunological analysis for most of these viruses, highlighting the occurrence of a relevant variability among the IBV strains that are circulating in Brazilian commercial poultry flocks.

Effect of race, genetic population structure, and genetic models in two-locus association studies: clustering of functional renin-angiotensin system gene variants in hypertension association studies

Previous genetic association studies have overlooked the potential for biased results when analyzing different population structures in ethnically diverse populations. The purpose of the present study was to quantify this bias in two-locus association studies conducted on an admixtured urban population. We studied the genetic structure distribution of angiotensin-converting enzyme insertion/deletion (ACE I/D) and angiotensinogen methionine/threonine (M/T) polymorphisms in 382 subjects from three subgroups in a highly admixtured urban population. Group I included 150 white subjects; group II, 142 mulatto subjects, and group III, 90 black subjects. We conducted sample size simulation studies using these data in different genetic models of gene action and interaction and used genetic distance calculation algorithms to help determine the population structure for the studied loci. Our results showed a statistically different population structure distribution of both ACE I/D (P = 0.02, OR = 1.56, 95% CI = 1.05-2.33 for the D allele, white versus black subgroup) and angiotensinogen M/T polymorphism (P = 0.007, OR = 1.71, 95% CI = 1.14-2.58 for the T allele, white versus black subgroup). Different sample sizes are predicted to be determinant of the power to detect a given genotypic association with a particular phenotype when conducting two-locus association studies in admixtured populations. In addition, the postulated genetic model is also a major determinant of the power to detect any association in a given sample size. The present simulation study helped to demonstrate the complex interrelation among ethnicity, power of the association, and the postulated genetic model of action of a particular allele in the context of clustering studies. This information is essential for the correct planning and interpretation of future association studies conducted on this population.

Genetic analysis of the porcine group B rotavirus NSP2 gene from wild-type Brazilian strains

Group B rotaviruses (RV-B) were first identified in piglet feces, being later associated with diarrhea in humans, cattle, lambs, and rats. In human beings, the virus was only described in China, India, and Bangladesh, especially infecting adults. Only a few studies concerning molecular analysis of the RV-B NSP2 gene have been conducted, and porcine RV-B has not been characterized. In the present study, three porcine wild-type RV-B strains from piglet stool samples collected from Brazilian pig herds were used for analysis. PAGE results were inconclusive for those samples, but specific amplicons of the RV-B NSP2 gene (segment 8) were obtained in a semi-nested PCR assay. The three porcine RV-B strains showed the highest nucleotide identity with the human WH1 strain and the alignments with other published sequences resulted in three groups of strains divided according to host species. The group of human strains showed 92.4 to 99.7% nucleotide identity while the porcine strains of the Brazilian RV-B group showed 90.4 to 91.8% identity to each other. The identity of the Brazilian porcine RV-B strains with outer sequences consisting of group A and C rotaviruses was only 35.3 to 38.8%. A dendrogram was also constructed to group the strains into clusters according to host species: human, rat, and a distinct third cluster consisting exclusively of the Brazilian porcine RV-B strains. This is the first study of the porcine RV-B NSP2 gene that contributes to the partial characterization of this virus and demonstrates the relationship among RV-B strains from different host species.

Candidate gene linkage analysis indicates genetic heterogeneity in Marfan syndrome

Marfan syndrome (MFS) is an autosomal dominant disease of the connective tissue that affects the ocular, skeletal and cardiovascular systems, with a wide clinical variability. Although mutations in the FBN1 gene have been recognized as the cause of the disease, more recently other loci have been associated with MFS, indicating the genetic heterogeneity of this disease. We addressed the issue of genetic heterogeneity in MFS by performing linkage analysis of the FBN1 and TGFBR2 genes in 34 families (345 subjects) who met the clinical diagnostic criteria for the disease according to Ghent. Using a total of six microsatellite markers, we found that linkage with the FBN1 gene was observed or not excluded in 70.6% (24/34) of the families, and in 1 family the MFS phenotype segregated with the TGFBR2 gene. Moreover, in 4 families linkage with the FBN1 and TGFBR2 genes was excluded, and no mutations were identified in the coding region of TGFBR1, indicating the existence of other genes involved in MFS. Our results suggest that the genetic heterogeneity of MFS may be greater that previously reported.

Genetic analysis of the ELOVL6 gene polymorphism associated with type 2 diabetes mellitus

Recent animal studies have indicated that overexpression of the elongation of long-chain fatty acids family member 6 (Elovl6) gene can cause insulin resistance and β-cell dysfunction. These are the major factors involved in the development of type 2 diabetes mellitus (T2DM). To identify the relationship between single nucleotide polymorphisms (SNP) ofELOVL6 and T2DM pathogenesis, we conducted a case-control study of 610 Han Chinese individuals (328 newly diagnosed T2DM and 282 healthy subjects). Insulin resistance and islet first-phase secretion function were evaluated by assessment of insulin resistance in a homeostasis model (HOMA-IR) and an arginine stimulation test. Three SNPs of the ELOVL6 gene were genotyped with polymerase chain reaction-restriction fragment length polymorphism, with DNA sequencing used to confirm the results. Only genotypes TT and CT of the ELOVL6 SNP rs12504538 were detected in the samples. Genotype CC was not observed. The T2DM group had a higher frequency of the C allele and the CT genotype than the control group. Subjects with the CT genotype had higher HOMA-IR values than those with the TT genotype. In addition, no statistical significance was observed between the genotype and allele frequencies of the control and T2DM groups for SNPs rs17041272 and rs6824447. The study indicated that the ELOVL6 gene polymorphism rs12504538 is associated with an increased risk of T2DM, because it causes an increase in insulin resistance.

Genetic Analysis of Taste in Homo Sapiens

There are many known taste receptors specific to each taste attribute. This thesis examines the relationship between single nucleotide polymorphisms (SNPs) and copy number variations (CNVs) in known taste and taste pathway receptors TAS2R38, Gustin, and TRPM5 and for PROP (6-n-propylthiouracil) taster status (PTS), thermal taster status (TTS), and orosensory sensation intensity ratings. PTS is a proxy for general taste responsiveness, and the ability to taste PROP classifies individuals into three phenotypes: super (PST), medium (PMT), and non-tasters (PNT). Another taste phenotype, also serving as a proxy for general taste responsiveness, is TTS, classifying individuals as thermal tasters (TTs) or thermal non-tasters (TnTs). DNA extractions from buccal cells obtained from 60 individuals were performed and analysis of TAS2R38, Gustin, and TRPM5 variations were conducted through Polymerase Chain Reaction (PCR), sequencing for SNPs, and upQMPSF for CNV analysis of TRPM5. Among the SNPs and CNVs studied, only TAS2R38 was found to be significantly associated with PTS and intensity ratings for sweet, bitter, and sour taste as well as astringency. However, not all PROP phenotypic differences can be explained by the variations at these three SNP sites in TAS2R38, suggesting the involvement of additional genes. No association was found between TTS and TAS2R38 or Gustin, confirming that PTS and TTS are not genetically associated. The examined TRPM5 SNPs and CNVs did not correlate with TTS. Therefore, further research is necessary into other factors contributing to PTS and TTS.

The patentability of human genetic material in China : a comparative analysis

"Mémoire Présenté à la Faculté des Études Supérieures en vue de l'obtention du Grade de Maîtrise En Droit Option Recherche"

Analysis of the Ethical, Social and Legal Issues Related to the Delivery of the Prenatal Genetic Testing in Argentina

L'introduction de nouvelles biotechnologies dans tout système de soins de santé est un processus complexe qui est étroitement lié aux facteurs économiques, politiques et culturels, et, par conséquent, demande de remettre en cause plusieurs questions sociales et éthiques. Dans la situation particulière de l’Argentine - c’est-à-dire: de grandes inégalités sociales entre les citoyens, la rareté des ressources sanitaires, l’accès limité aux services de base, l’absence de politiques spécifiques - l'introduction de technologies génétiques pose de sérieux défis qui doivent impérativement être abordés par les décideurs politiques. Ce projet examine le cas des tests génétiques prénataux dans le contexte du système de santé argentin pour illustrer comment leur introduction peut être complexe dans une nation où l’accès égale aux services de santé doit encore être amélioré. Il faut également examiner les restrictions légales et les préceptes religieux qui influencent l'utilisation des technologies génétiques, ce qui souligne la nécessite de développer un cadre de référence intégral pour le processus d'évaluation des technologies afin d’appuyer l’élaboration de recommandations pour des politiques cohérentes et novatrices applicables au contexte particulier de l’Argentine.

Clustering algorithms and shape factor methods to discriminate among small GTPase phenotypes using DIC image analysis.

Naïvement perçu, le processus d’évolution est une succession d’événements de duplication et de mutations graduelles dans le génome qui mènent à des changements dans les fonctions et les interactions du protéome. La famille des hydrolases de guanosine triphosphate (GTPases) similaire à Ras constitue un bon modèle de travail afin de comprendre ce phénomène fondamental, car cette famille de protéines contient un nombre limité d’éléments qui diffèrent en fonctionnalité et en interactions. Globalement, nous désirons comprendre comment les mutations singulières au niveau des GTPases affectent la morphologie des cellules ainsi que leur degré d’impact sur les populations asynchrones. Mon travail de maîtrise vise à classifier de manière significative différents phénotypes de la levure Saccaromyces cerevisiae via l’analyse de plusieurs critères morphologiques de souches exprimant des GTPases mutées et natives. Notre approche à base de microscopie et d’analyses bioinformatique des images DIC (microscopie d’interférence différentielle de contraste) permet de distinguer les phénotypes propres aux cellules natives et aux mutants. L’emploi de cette méthode a permis une détection automatisée et une caractérisation des phénotypes mutants associés à la sur-expression de GTPases constitutivement actives. Les mutants de GTPases constitutivement actifs Cdc42 Q61L, Rho5 Q91H, Ras1 Q68L et Rsr1 G12V ont été analysés avec succès. En effet, l’implémentation de différents algorithmes de partitionnement, permet d’analyser des données qui combinent les mesures morphologiques de population native et mutantes. Nos résultats démontrent que l’algorithme Fuzzy C-Means performe un partitionnement efficace des cellules natives ou mutantes, où les différents types de cellules sont classifiés en fonction de plusieurs facteurs de formes cellulaires obtenus à partir des images DIC. Cette analyse démontre que les mutations Cdc42 Q61L, Rho5 Q91H, Ras1 Q68L et Rsr1 G12V induisent respectivement des phénotypes amorphe, allongé, rond et large qui sont représentés par des vecteurs de facteurs de forme distincts. Ces distinctions sont observées avec différentes proportions (morphologie mutante / morphologie native) dans les populations de mutants. Le développement de nouvelles méthodes automatisées d’analyse morphologique des cellules natives et mutantes s’avère extrêmement utile pour l’étude de la famille des GTPases ainsi que des résidus spécifiques qui dictent leurs fonctions et réseau d’interaction. Nous pouvons maintenant envisager de produire des mutants de GTPases qui inversent leur fonction en ciblant des résidus divergents. La substitution fonctionnelle est ensuite détectée au niveau morphologique grâce à notre nouvelle stratégie quantitative. Ce type d’analyse peut également être transposé à d’autres familles de protéines et contribuer de manière significative au domaine de la biologie évolutive.

Mean Squared Residue Based Biclustering Algorithms for the Analysis of Gene Expression Data

Computational Biology is the research are that contributes to the analysis of biological data through the development of algorithms which will address significant research problems.The data from molecular biology includes DNA,RNA ,Protein and Gene expression data.Gene Expression Data provides the expression level of genes under different conditions.Gene expression is the process of transcribing the DNA sequence of a gene into mRNA sequences which in turn are later translated into proteins.The number of copies of mRNA produced is called the expression level of a gene.Gene expression data is organized in the form of a matrix. Rows in the matrix represent genes and columns in the matrix represent experimental conditions.Experimental conditions can be different tissue types or time points.Entries in the gene expression matrix are real values.Through the analysis of gene expression data it is possible to determine the behavioral patterns of genes such as similarity of their behavior,nature of their interaction,their respective contribution to the same pathways and so on. Similar expression patterns are exhibited by the genes participating in the same biological process.These patterns have immense relevance and application in bioinformatics and clinical research.Theses patterns are used in the medical domain for aid in more accurate diagnosis,prognosis,treatment planning.drug discovery and protein network analysis.To identify various patterns from gene expression data,data mining techniques are essential.Clustering is an important data mining technique for the analysis of gene expression data.To overcome the problems associated with clustering,biclustering is introduced.Biclustering refers to simultaneous clustering of both rows and columns of a data matrix. Clustering is a global whereas biclustering is a local model.Discovering local expression patterns is essential for identfying many genetic pathways that are not apparent otherwise.It is therefore necessary to move beyond the clustering paradigm towards developing approaches which are capable of discovering local patterns in gene expression data.A biclusters is a submatrix of the gene expression data matrix.The rows and columns in the submatrix need not be contiguous as in the gene expression data matrix.Biclusters are not disjoint.Computation of biclusters is costly because one will have to consider all the combinations of columans and rows in order to find out all the biclusters.The search space for the biclustering problem is 2 m+n where m and n are the number of genes and conditions respectively.Usually m+n is more than 3000.The biclustering problem is NP-hard.Biclustering is a powerful analytical tool for the biologist.The research reported in this thesis addresses the problem of biclustering.Ten algorithms are developed for the identification of coherent biclusters from gene expression data.All these algorithms are making use of a measure called mean squared residue to search for biclusters.The objective here is to identify the biclusters of maximum size with the mean squared residue lower than a given threshold. All these algorithms begin the search from tightly coregulated submatrices called the seeds.These seeds are generated by K-Means clustering algorithm.The algorithms developed can be classified as constraint based,greedy and metaheuristic.Constarint based algorithms uses one or more of the various constaints namely the MSR threshold and the MSR difference threshold.The greedy approach makes a locally optimal choice at each stage with the objective of finding the global optimum.In metaheuristic approaches particle Swarm Optimization(PSO) and variants of Greedy Randomized Adaptive Search Procedure(GRASP) are used for the identification of biclusters.These algorithms are implemented on the Yeast and Lymphoma datasets.Biologically relevant and statistically significant biclusters are identified by all these algorithms which are validated by Gene Ontology database.All these algorithms are compared with some other biclustering algorithms.Algorithms developed in this work overcome some of the problems associated with the already existing algorithms.With the help of some of the algorithms which are developed in this work biclusters with very high row variance,which is higher than the row variance of any other algorithm using mean squared residue, are identified from both Yeast and Lymphoma data sets.Such biclusters which make significant change in the expression level are highly relevant biologically.