Populations genetics study of the Ammi Genus in the Azores

Dissertação de Mestrado, Biodiversidade e Biotecnologia Vegetal, 6 de Julho de 2016, Universidade dos Açores.

Survey of Amphiprion clarki & Amphiprion sebae populations in Persian Gulf by molecular genetics

Anemone fishes are a group of 28 species of coral reef fishes belonging to the family Pomacentridae, subfamily Amphiprioninae and all have an obligate symbiotic relationship with sea anemones. Two species of these small ornamental fishes have been identified in the Persian Gulf including Amphiprion clarkii and A. sebae. The phylogenetic relationship between Amphiprion species of the Persian Gulf was studied by collecting 15 samples from three Iranian islands, Larak, Farur and Kish. DNA was extracted from each sample and a part of mtDNA was amplified. Two pairs of primers were designed to amplify a final target of 400 by nested-PCR. Each amplicon was sequenced, aligned and genetic diversity among samples was investigated by phylogenetic analysis. Results show that there is no significant genetic variation among A. clarkii individuals; however, A. sebae individuals from Larak were different from other fishes of the same species. Most probably this is due to the ability of A. clarkii to be symbiotant with all 10 species of host sea anemones which enables it to spread its own population in the 3 islands. However, A. sebae is observed to be symbiotant only with one host in the sea, therefore, has one option that reduces its distribution.

National evaluation of NHS genetics service investments: emerging issues from the cancer genetics pilots

In seeking to fulfil the ambition of the 2003 genetics white paper, Our Inheritance, Our Future, to ‘mainstream’ genetic knowledge and practices, the Department of Health provided start-up funding for pilot services in various clinical areas, including seven cancer genetics projects. To help to understand the challenges encountered by such an attempt at reconfiguring the organization and delivery of services in this field, a programme-level evaluation of the genetics projects was commissioned to consider the organizational issues faced. Using a qualitative approach, this research has involved comparative case-study work in 11 of the pilot sites, including four of the seven cancer genetics pilots. In this paper, the researchers present early findings from their work, focusing in particular on the cancer genetics pilots. They consider some of the factors that have influenced how the pilots have sought to address pre-existing sector, organizational and professional boundaries to these new ways of working. The article examines the relationship between these factors and the extent to which pilots have succeeded in setting up boundary-spanning services, dealing with human-resource issues and creating sustainable, ‘mainstreamed’ provision which attracts ongoing funding in a volatile NHS commissioning environment where funding priorities do not always favour preventive, risk-assessment services.

Estimation of leaf area in grapevine cv. Syrah using empirical models

Aiming to obtain empirical models for the estimation of Syrah leaf area a set of 210 fruiting shoots was randomly collected during the 2013 growing season in an adult experimental vineyard, located in Lisbon, Portugal. Samples of 30 fruiting shoots were taken periodically from the stage of inflorescences visible to veraison (7 sampling dates). At the lab, from each shoot, primary and lateral leaves were separated and numbered according to node insertion. For each leaf, the length of the central and lateral veins was recorded and then the leaf area was measured by a leaf area meter. For single leaf area estimation the best statistical models uses as explanatory variable the sum of the lengths of the two lateral leaf veins. For the estimation of leaf area per shoot it was followed the approach of Lopes & Pinto (2005), based on 3 explanatory variables: number of primary leaves and area of the largest and smallest leaves. The best statistical model for estimation of primary leaf area per shoot uses a calculated variable obtained from the average of the largest and smallest primary leaf area multiplied by the number of primary leaves. For lateral leaf area estimation another model using the same type of calculated variable is also presented. All models explain a very high proportion of variability in leaf area. Our results confirm the already reported strong importance of the three measured variables (number of leaves and area of the largest and smallest leaf) as predictors of the shoot leaf area. The proposed models can be used to accurately predict Syrah primary and secondary leaf area per shoot in any phase of the growing cycle. They are inexpensive, practical, non-destructive methods which do not require specialized staff or expensive equipment.

Behavioral and molecular genetics of reading-related AM and FM detection thresholds

Auditory detection thresholds for certain frequencies of both amplitude modulated (AM) and frequency modulated (FM) dynamic auditory stimuli are associated with reading in typically developing and dyslexic readers. We present the first behavioral and molecular genetic characterization of these two auditory traits. Two extant extended family datasets were given reading tasks and psychoacoustic tasks to determine FM 2 Hz and AM 20 Hz sensitivity thresholds. Univariate heritabilities were significant for both AM (h2 = 0.20) and FM (h2 = 0.29). Bayesian posterior probability of linkage (PPL) analysis found loci for AM (12q, PPL = 81 %) and FM (10p, PPL = 32 %; 20q, PPL = 65 %). Bivariate heritability analyses revealed that FM is genetically correlated with reading, while AM was not. Bivariate PPL analysis indicates that FM loci (10p, 20q) are not also associated with reading.

he genome and genetics of a high oxidative stress tolerant Serratia sp. LCN16 isolated from the plant parasitic nematode Bursaphelenchus xylophilus

Background: Pine wilt disease (PWD) is a worldwide threat to pine forests, and is caused by the pine wood nematode (PWN) Bursaphelenchus xylophilus. Bacteria are known to be associated with PWN and may have an important role in PWD. Serratia sp. LCN16 is a PWN-associated bacterium, highly resistant to oxidative stress in vitro, and which beneficially contributes to the PWN survival under these conditions. Oxidative stress is generated as a part of the basal defense mechanism used by plants to combat pathogenic invasion. Here, we studied the biology of Serratia sp. LCN16 through genome analyses, and further investigated, using reverse genetics, the role of two genes directly involved in the neutralization of H2O2, namely the H2O2 transcriptional factor oxyR; and the H2O2-targeting enzyme, catalase katA. Results: Serratia sp. LCN16 is phylogenetically most closely related to the phytosphere group of Serratia, which includes S. proteamaculans, S. grimessi and S. liquefaciens. Likewise, Serratia sp. LCN16 shares many features with endophytes (plant-associated bacteria), such as genes coding for plant polymer degrading enzymes, iron uptake/ transport, siderophore and phytohormone synthesis, aromatic compound degradation and detoxification enzymes. OxyR and KatA are directly involved in the high tolerance to H2O2 of Serratia sp. LCN16. Under oxidative stress, Serratia sp. LCN16 expresses katA independently of OxyR in contrast with katG which is under positive regulation of OxyR. Serratia sp. LCN16 mutants for oxyR (oxyR::int(614)) and katA (katA::int(808)) were sensitive to H2O2 in relation with wild-type, and both failed to protect the PWN from H2O2-stress exposure. Moreover, both mutants showed different phenotypes in terms of biofilm production and swimming/swarming behaviors. Conclusions: This study provides new insights into the biology of PWN-associated bacteria Serratia sp. LCN16 and its extreme resistance to oxidative stress conditions, encouraging further research on the potential role of this bacterium in interaction with PWN in planta environment.

Advanced statistical models for the segregation, identification and measurement of coexisting sound sources

Long-term monitoring of acoustical environments is gaining popularity thanks to the relevant amount of scientific and engineering insights that it provides. The increasing interest is due to the constant growth of storage capacity and computational power to process large amounts of data. In this perspective, machine learning (ML) provides a broad family of data-driven statistical techniques to deal with large databases. Nowadays, the conventional praxis of sound level meter measurements limits the global description of a sound scene to an energetic point of view. The equivalent continuous level Leq represents the main metric to define an acoustic environment, indeed. Finer analyses involve the use of statistical levels. However, acoustic percentiles are based on temporal assumptions, which are not always reliable. A statistical approach, based on the study of the occurrences of sound pressure levels, would bring a different perspective to the analysis of long-term monitoring. Depicting a sound scene through the most probable sound pressure level, rather than portions of energy, brought more specific information about the activity carried out during the measurements. The statistical mode of the occurrences can capture typical behaviors of specific kinds of sound sources. The present work aims to propose an ML-based method to identify, separate and measure coexisting sound sources in real-world scenarios. It is based on long-term monitoring and is addressed to acousticians focused on the analysis of environmental noise in manifold contexts. The presented method is based on clustering analysis. Two algorithms, Gaussian Mixture Model and K-means clustering, represent the main core of a process to investigate different active spaces monitored through sound level meters. The procedure has been applied in two different contexts: university lecture halls and offices. The proposed method shows robust and reliable results in describing the acoustic scenario and it could represent an important analytical tool for acousticians.

Exploring Iris Colour Prediction And Ancestry Inference In Admixed Populations Of South America.

New DNA-based predictive tests for physical characteristics and inference of ancestry are highly informative tools that are being increasingly used in forensic genetic analysis. Two eye colour prediction models: a Bayesian classifier - Snipper and a multinomial logistic regression (MLR) system for the Irisplex assay, have been described for the analysis of unadmixed European populations. Since multiple SNPs in combination contribute in varying degrees to eye colour predictability in Europeans, it is likely that these predictive tests will perform in different ways amongst admixed populations that have European co-ancestry, compared to unadmixed Europeans. In this study we examined 99 individuals from two admixed South American populations comparing eye colour versus ancestry in order to reveal a direct correlation of light eye colour phenotypes with European co-ancestry in admixed individuals. Additionally, eye colour prediction following six prediction models, using varying numbers of SNPs and based on Snipper and MLR, were applied to the study populations. Furthermore, patterns of eye colour prediction have been inferred for a set of publicly available admixed and globally distributed populations from the HGDP-CEPH panel and 1000 Genomes databases with a special emphasis on admixed American populations similar to those of the study samples.

Cognitive And Behavioral Heterogeneity In Genetic Syndromes.

this study aimed to investigate the cognitive and behavioral profiles, as well as the psychiatric symptoms and disorders in children with three different genetic syndromes with similar sociocultural and socioeconomic backgrounds. thirty-four children aged 6 to 16 years, with Williams-Beuren syndrome (n=10), Prader-Willi syndrome (n=11), and Fragile X syndrome (n=13) from the outpatient clinics of Child Psychiatry and Medical Genetics Department were cognitively assessed through the Wechsler Intelligence Scale for Children (WISC-III). Afterwards, a full-scale intelligence quotient (IQ), verbal IQ, performance IQ, standard subtest scores, as well as frequency of psychiatric symptoms and disorders were compared among the three syndromes. significant differences were found among the syndromes concerning verbal IQ and verbal and performance subtests. Post-hoc analysis demonstrated that vocabulary and comprehension subtest scores were significantly higher in Williams-Beuren syndrome in comparison with Prader-Willi and Fragile X syndromes, and block design and object assembly scores were significantly higher in Prader-Willi syndrome compared with Williams-Beuren and Fragile X syndromes. Additionally, there were significant differences between the syndromes concerning behavioral features and psychiatric symptoms. The Prader-Willi syndrome group presented a higher frequency of hyperphagia and self-injurious behaviors. The Fragile X syndrome group showed a higher frequency of social interaction deficits; such difference nearly reached statistical significance. the three genetic syndromes exhibited distinctive cognitive, behavioral, and psychiatric patterns.

Censored Linear Regression Models For Irregularly Observed Longitudinal Data Using The Multivariate-t Distribution.

In acquired immunodeficiency syndrome (AIDS) studies it is quite common to observe viral load measurements collected irregularly over time. Moreover, these measurements can be subjected to some upper and/or lower detection limits depending on the quantification assays. A complication arises when these continuous repeated measures have a heavy-tailed behavior. For such data structures, we propose a robust structure for a censored linear model based on the multivariate Student's t-distribution. To compensate for the autocorrelation existing among irregularly observed measures, a damped exponential correlation structure is employed. An efficient expectation maximization type algorithm is developed for computing the maximum likelihood estimates, obtaining as a by-product the standard errors of the fixed effects and the log-likelihood function. The proposed algorithm uses closed-form expressions at the E-step that rely on formulas for the mean and variance of a truncated multivariate Student's t-distribution. The methodology is illustrated through an application to an Human Immunodeficiency Virus-AIDS (HIV-AIDS) study and several simulation studies.

Preserved Fertility In A Patient With Gynecomastia Associated With The P.pro695ser Mutation In The Androgen Receptor.

The androgen insensitivity syndrome (AIS) is described as a dysfunction of the androgen receptor (AR) in 46,XY individuals, which can be associated with mutations in the AR gene or can be due to unknown mechanisms. Different mutations in AIS generally cause variable phenotypes that range from a complete hormone resistance to a mild form usually associated with male infertility. The purpose of this study was to search for mutations in the AR gene in a fertile man with gynecomastia and to evaluate the influence of the mutation on the AR transactivation ability. Sequencing of the AR gene revealed the p.Pro695Ser mutation. It is located within the AR ligand-binding domain. Bioinformatics analysis indicated a deleterious role, which was verified after testing transactivation activity and N-/C-terminal (N/C) interaction by in vitro expression of a reporter gene and 2-hybrid assays. p.Pro695Ser showed low levels of both transactivation activity and N/C interaction at low dihydrotestosterone (DHT) conditions. As the ligand concentration increased, both transactivation activity and N/C interaction also increased and reached normal levels. Therefore, this study provides functional insights for the p.Pro695Ser mutation described here for the first time in a patient with mild AIS. The expression profile of p.Pro695Ser not only correlates to the patient's phenotype, but also suggests that a high-dose DHT therapy may overcome the functional deficit of the mutant AR.

Augmented Mixed Models For Clustered Proportion Data.

Often in biomedical research, we deal with continuous (clustered) proportion responses ranging between zero and one quantifying the disease status of the cluster units. Interestingly, the study population might also consist of relatively disease-free as well as highly diseased subjects, contributing to proportion values in the interval [0, 1]. Regression on a variety of parametric densities with support lying in (0, 1), such as beta regression, can assess important covariate effects. However, they are deemed inappropriate due to the presence of zeros and/or ones. To evade this, we introduce a class of general proportion density, and further augment the probabilities of zero and one to this general proportion density, controlling for the clustering. Our approach is Bayesian and presents a computationally convenient framework amenable to available freeware. Bayesian case-deletion influence diagnostics based on q-divergence measures are automatic from the Markov chain Monte Carlo output. The methodology is illustrated using both simulation studies and application to a real dataset from a clinical periodontology study.

Epilepsias parciais familiares

OBJECTIVE: To investigate the clinical and genetic characteristics of familial partial epilepsies. METHOD: Family history of seizures was questioned in all patients followed in our epilepsy clinics, from October 1997 to December 1998. Those with positive family history were further investigated and detailed pedigrees were obtained. All possibly affected individuals available underwent clinical evaluation. Seizures and epilepsy syndromes were classified according to the ILAE recommendations. Whenever possible, EEG and MRI were performed. RESULTS: Positive family history was identified in 32 unrelated patients. A total of 213 possibly affected individuals were identified, 161 of whom have been evaluated. The number of affected subjects per family ranged from two to 23. Temporal lobe epilepsy (TLE) was identified in 22 families (68%), frontal lobe epilepsy in one family (3%), partial epilepsy with centrotemporal spikes in five families (15%), and other benign partial epilepsies of childhood in four families (12%). Most of the affected individuals in the TLE families (69%) had clinical and/or EEG characteristics of typical TLE. However, the severity of epilepsy was variable, with 76% of patients with spontaneous seizure remission or good control with medication and 24% with refractory seizures, including 7 patients that underwent surgical treatment. In the other 10 families, we identified 39 possibly affected subjects, 23 of whom were evaluated. All had good seizure control (with or without medication) except for one patient with frontal lobe epilepsy. Pedigree analysis suggested autosomal dominant inheritance with incomplete penetrance in all families. CONCLUSION: Family history of seizures is frequent among patients with partial epilepsies. The majority of our families had TLE and its expression was not different from that observed in sporadic cases. The identification of genes involved in partial epilepsies may be usefull in classification of syndromes, to stablish prognosis and optimal treatment.

Composição corporal e somatotipo em pessoas com síndrome de Down

Universidade Estadual de Campinas . Faculdade de Educação Física

Possibilidades e limites da avaliação da qualidade de vida : análise dos instrumentos WHOQOL e modelos clássicos de qualidade de vida no trabalho = Possibilities and limits of quality of life assessment : analysis of WHOQOL instruments and quality of work life classical models

Universidade Estadual de Campinas . Faculdade de Educação Física