Contrasting quantitative traits and neutral genetic markers for genetic resource assessment of Mesoamerican Cedrela odorata

We compared within-population variability and degree of population differentiation for neutral genetic markers (RAPDS) and eight quantitative traits in Central American populations of the endangered tree, Cedrela odorata. Whilst population genetic diversity for neutral markers (Shannon index) and quantitative traits (heritability, coefficient of additive genetic variation) were uncorrelated, both marker types revealed strong differentiation between populations from the Atlantic coast of Costa Rica and the rest of the species' distribution. The degree of interpopulation differentiation was higher for RAPD markers (F-ST 0.67 for the sampled Mesoamerican range) than for quantitative traits (Q(ST) = 0.30). Hence, the divergence in quantitative traits was lower than could have been achieved by genetic drift alone, suggesting that balancing selection for similar phenotypes in different populations of this species. Nevertheless, a comparison of pair-wise estimates of population differentiation in neutral genetic markers and quantitative traits revealed a strong positive correlation (r = 0.66) suggesting that, for C. odorata, neutral marker divergence could be used as a surrogate for adaptive gene divergence for conservation planning. The utility of this finding and suggested further work are discussed.

Unlocking pathology archives for molecular genetic studies: a reliable method to generate probes for chromogenic and fluorescent in situ hybridization

Chromogenic (CISH) and fluorescent ( FISH) in situ hybridization have emerged as reliable techniques to identify amplifications and chromosomal translocations. CISH provides a spatial distribution of gene copy number changes in tumour tissue and allows a direct correlation between copy number changes and the morphological features of neoplastic cells. However, the limited number of commercially available gene probes has hindered the use of this technique. We have devised a protocol to generate probes for CISH that can be applied to formalin-fixed, paraffin-embedded tissue sections (FFPETS). Bacterial artificial chromosomes ( BACs) containing fragments of human DNA which map to specific genomic regions of interest are amplified with phi 29 polymerase and random primer labelled with biotin. The genomic location of these can be readily confirmed by BAC end pair sequencing and FISH mapping on normal lymphocyte metaphase spreads. To demonstrate the reliability of the probes generated with this protocol, four strategies were employed: (i) probes mapping to cyclin D1 (CCND1) were generated and their performance was compared with that of a commercially available probe for the same gene in a series of 10 FFPETS of breast cancer samples of which five harboured CCND1 amplification; (ii) probes targeting cyclin-dependent kinase 4 were used to validate an amplification identified by microarray-based comparative genomic hybridization (aCGH) in a pleomorphic adenoma; (iii) probes targeting fibroblast growth factor receptor 1 and CCND1 were used to validate amplifications mapping to these regions, as defined by aCGH, in an invasive lobular breast carcinoma with FISH and CISH; and (iv) gene-specific probes for ETV6 and NTRK3 were used to demonstrate the presence of t(12; 15)(p12; q25) translocation in a case of breast secretory carcinoma with dual colour FISH. In summary, this protocol enables the generation of probes mapping to any gene of interest that can be applied to FFPETS, allowing correlation of morphological features with gene copy number.

Multilevel modelling for inference of genetic regulatory networks

Time-course experiments with microarrays are often used to study dynamic biological systems and genetic regulatory networks (GRNs) that model how genes influence each other in cell-level development of organisms. The inference for GRNs provides important insights into the fundamental biological processes such as growth and is useful in disease diagnosis and genomic drug design. Due to the experimental design, multilevel data hierarchies are often present in time-course gene expression data. Most existing methods, however, ignore the dependency of the expression measurements over time and the correlation among gene expression profiles. Such independence assumptions violate regulatory interactions and can result in overlooking certain important subject effects and lead to spurious inference for regulatory networks or mechanisms. In this paper, a multilevel mixed-effects model is adopted to incorporate data hierarchies in the analysis of time-course data, where temporal and subject effects are both assumed to be random. The method starts with the clustering of genes by fitting the mixture model within the multilevel random-effects model framework using the expectation-maximization (EM) algorithm. The network of regulatory interactions is then determined by searching for regulatory control elements (activators and inhibitors) shared by the clusters of co-expressed genes, based on a time-lagged correlation coefficients measurement. The method is applied to two real time-course datasets from the budding yeast (Saccharomyces cerevisiae) genome. It is shown that the proposed method provides clusters of cell-cycle regulated genes that are supported by existing gene function annotations, and hence enables inference on regulatory interactions for the genetic network.

The dynamics of a genetic algorithm under stabilizing selection

A formalism recently introduced by Prugel-Bennett and Shapiro uses the methods of statistical mechanics to model the dynamics of genetic algorithms. To be of more general interest than the test cases they consider. In this paper, the technique is applied to the subset sum problem, which is a combinatorial optimization problem with a strongly non-linear energy (fitness) function and many local minima under single spin flip dynamics. It is a problem which exhibits an interesting dynamics, reminiscent of stabilizing selection in population biology. The dynamics are solved under certain simplifying assumptions and are reduced to a set of difference equations for a small number of relevant quantities. The quantities used are the population's cumulants, which describe its shape, and the mean correlation within the population, which measures the microscopic similarity of population members. Including the mean correlation allows a better description of the population than the cumulants alone would provide and represents a new and important extension of the technique. The formalism includes finite population effects and describes problems of realistic size. The theory is shown to agree closely to simulations of a real genetic algorithm and the mean best energy is accurately predicted.

Modelling the dynamics of genetic algorithms using statistical mechanics

A formalism for modelling the dynamics of Genetic Algorithms (GAs) using methods from statistical mechanics, originally due to Prugel-Bennett and Shapiro, is reviewed, generalized and improved upon. This formalism can be used to predict the averaged trajectory of macroscopic statistics describing the GA's population. These macroscopics are chosen to average well between runs, so that fluctuations from mean behaviour can often be neglected. Where necessary, non-trivial terms are determined by assuming maximum entropy with constraints on known macroscopics. Problems of realistic size are described in compact form and finite population effects are included, often proving to be of fundamental importance. The macroscopics used here are cumulants of an appropriate quantity within the population and the mean correlation (Hamming distance) within the population. Including the correlation as an explicit macroscopic provides a significant improvement over the original formulation. The formalism is applied to a number of simple optimization problems in order to determine its predictive power and to gain insight into GA dynamics. Problems which are most amenable to analysis come from the class where alleles within the genotype contribute additively to the phenotype. This class can be treated with some generality, including problems with inhomogeneous contributions from each site, non-linear or noisy fitness measures, simple diploid representations and temporally varying fitness. The results can also be applied to a simple learning problem, generalization in a binary perceptron, and a limit is identified for which the optimal training batch size can be determined for this problem. The theory is compared to averaged results from a real GA in each case, showing excellent agreement if the maximum entropy principle holds. Some situations where this approximation brakes down are identified. In order to fully test the formalism, an attempt is made on the strong sc np-hard problem of storing random patterns in a binary perceptron. Here, the relationship between the genotype and phenotype (training error) is strongly non-linear. Mutation is modelled under the assumption that perceptron configurations are typical of perceptrons with a given training error. Unfortunately, this assumption does not provide a good approximation in general. It is conjectured that perceptron configurations would have to be constrained by other statistics in order to accurately model mutation for this problem. Issues arising from this study are discussed in conclusion and some possible areas of further research are outlined.

Offline Handwriting Recognition Using Genetic Algorithm

In this paper, a new method for offline handwriting recognition is presented. A robust algorithm for handwriting segmentation has been described here with the help of which individual characters can be segmented from a word selected from a paragraph of handwritten text image which is given as input to the module. Then each of the segmented characters are converted into column vectors of 625 values that are later fed into the advanced neural network setup that has been designed in the form of text files. The networks has been designed with quadruple layered neural network with 625 input and 26 output neurons each corresponding to a character from a-z, the outputs of all the four networks is fed into the genetic algorithm which has been developed using the concepts of correlation, with the help of this the overall network is optimized with the help of genetic algorithm thus providing us with recognized outputs with great efficiency of 71%.

Genetic markers, birth characteristics, and childhood leukemia risk

The cause for childhood acute lymphoblastic leukemia (ALL) remains unknown, but male gender is a risk factor, and among ethnicities, Hispanics have the highest risk. In this dissertation, we explored correlations among genetic polymorphisms, birth characteristics, and the risk of childhood ALL in a multi-ethnic sample in 161 cases and 231 controls recruited contemporaneously (2007-2012) in Houston, TX. We first examined three lymphoma risk markers, since lymphoma and ALL both stem from lymphoid cells. Of these, rs2395185 showed a risk association in non-Hispanic White males (OR=2.8, P=0.02; P interaction=0.03 for gender), but not in Hispanics. We verified previously known risk associations to validate the case-control sample. Mutations of HFE (C282Y, H63D) were genotyped to test whether iron-regulatory gene (IRG) variants known to elevate iron levels increase childhood ALL risk. Being positive for either polymorphism yielded only a modestly elevated OR in males, which increased to 2.96 (P=0.01) in the presence of a particular transferrin receptor (TFRC) genotype for rs3817672 (Pinteraction=0.04). SNP rs3817672 itself showed an ethnicity-specific association (P interaction=0.02 for ethnicity). We then examined additional IRG SNPs (rs422982, rs855791, rs733655), which showed risk associations in males (ORs=1.52 to 2.60). A polygenic model based on the number of polymorphic alleles in five IRG SNPs revealed a linear increase in risk (OR=2.00 per incremental change; P=0.002). Having three or more alleles compared with none was associated with increased risk in males (OR=4.12; P=0.004). Significant risk associations with childhood ALL was found with birth length (OR=1.18 per inch, P=0.04), high birth weight (>4,000g) (OR=1.93, P=0.01), and with gestational age (OR=1.10 per week, P=0.04). We observed a negative correlation between HFE SNP rs9366637 and gestational age (P=0.005), again, stronger in males ( P=0.001) and interacting with TFRC (P interaction=0.05). Our results showed that (i) ALL risk markers do not show universal associations across ethnicities or between genders, (ii) IRG SNPs modify ALL risk presumably by their effects on iron levels, (iii) a negative correlation between an HFE SNP and gestational age exists, which implicates an iron-related mechanism. The results suggest that currently unregulated supplemental iron intake may have implications on childhood ALL development.

Improved damage detectability in a wind turbine blade by optimal selection of vibration signal correlation coefficients

Piotr Omenzetter and Simon Hoell’s work within the Lloyd’s Register Foundation Centre for Safety and Reliability Engineering at the University of Aberdeen is supported by Lloyd’s Register Foundation. The Foundation helps to protect life and property by supporting engineering-related education, public engagement and the application of research.

Correlation between pre-treatment quasispecies complexity and treatment outcome in chronic HCV genotype 3a

Pre-treatment HCV quasispecies complexity and diversity may predict response to interferon based anti-viral therapy. The objective of this study was to retrospectively (1) examine temporal changes in quasispecies prior to the start of therapy and (2) investigate extensively quasispecies evolution in a group of 10 chronically infected patients with genotype 3a, treated with pegylated alpha 2a-Interferon and ribavirin. The degree of sequence heterogeneity within the hypervariable region 1 was assessed by analyzing 20-30 individual clones in serial serum samples. Genetic parameters, including amino acid Shannon entropy, Hamming distance and genetic distance were calculated for each sample. Treatment outcome was divided into (1) sustained virological responders (SVR) and (2) treatment failure (TF).Our results indicate, (1) quasispecies complexity and diversity are lower in the SVR group, (2) quasispecies vary temporally and (3) genetic heterogeneity at baseline can be used to predict treatment outcome. We discuss the results from the perspective of replicative homeostasis. We discuss the results from the perspective of replicative homeostasis.

Peroxisome Proliferator-Activated Receptor-γ Coactivator 1-α (PPARGC1A) Genetic Associations with Type 2 Diabetes in Three Ethnicities

Genetic heterogeneity, lifestyle factors, gene-gene or gene-environment interactions are the determinants of T2D which puts Hispanics and populations with African ancestry at higher risk of developing T2D. In this dissertation, the genetic associations of PPARGC1A polymorphisms with T2D and its related phenotypes (metabolic markers) in Haitian Americans (cases=110, controls=116), African Americans (cases=120, controls=124) and Cuban Americans (cases=160, controls=181) of South Florida were explored. Five single nucleotide polymorphisms of gene PPARGC1A were evaluated in each ethnicity for their disease association. In Haitian Americans, rs7656250 (OR= 0.22, pp=0.03) had significant protective association with T2D but had risk association in African Americans for rs7656250 (OR=1.02, p=0.96) and rs4235308 (OR=2.53, p=0.03). We found that in Haitian American females, both rs7656250 (OR=0.23, pp=0.03) had protective association with T2D. In African American females, rs7656250 (OR=1.14, p=0.78) had risk association whereas in males, it had significant protective effect (OR=0.37, p=0.04). However, the risk association exhibited by rs4235308 was stronger in African American females (OR=2.69, p=0.03) than males (OR=1.16, p=0.72). In Cuban Americans, only rs7656250 showed significant risk association with T2D (OR=6.87, p=0.02) which was stronger in females alone (OR=7.67, p=0.01). We also observed significant differences among correlations of PPARGC1A SNPs and T2D phenotypes. Positive correlation was observed for log Hs-CRP with rs3774907 (pp=0.03) in Cuban Americans respectively. Correlation of log A1C with rs7656250 (p=0.02) was positive in Cuban Americans while it was negative for rs3774907 in Haitian Americans (ppPPARGC1A correlations with T2D and its phenotypes among the three ethnicities studied (ii) the associations of PPARGC1A SNPs showed significant effect modification by sex. The findings suggest that variations in effects of PPARGC1A gene polymorphisms among three ethnicities and between sexes may have biomedical implications for the development of T2D as well as the phenotypes related to T2D.

Variation, correlation and heritability of interest characters for selection of African eggplant

The eggplant ( Solanum aethiopicum ) is the species of the Solanum genus, whose geographical distribution is broadest. It is grown throughout tropical Africa, and includes three groups of cultivars commonly called African or indigenous eggplant. Kumba group or “bitter eggplant” is an important Solanaceous vegetable crop in Burkina Faso. The objective of this study was to determine genetic variability, strength of association and level of heritability among agronomic interest traits. Phenotypic and genotypic variations and heritability of 14 traits were estimated in 61 accessions at Institut de Développement Rural (IDR), Gampela in Burkina Faso. High phenotypic and genotypic coefficients of variation were observed for fruit diameter, number of seeds per fruit, fruit weight, leaf blade length and width, and height at flowering. In addition, genetic and phenotypic variances were high for the number of seed, fruit weight, plant height at flowering and days to 50% flowering. High heritability estimates were recorded for all traits. Fruit weight showed a positive association with fruit diameter and thickness. The fifty percent flowering cycle registered positive correlations with plant height and fruit diameter. Fruit number showed a negative association with fruit weight and diameter, and 50% flowering cyle.

Estimates of genetic parameters using RELM/BLUP for intrapopulational genetic breeding of Platonia insignis Mart.

The aim of this study was to estimate genetic parameters to support the selection of bacuri progenies for a first cycle of recurrent selection, using the REML/BLUP (restricted maximum likelihood/best linear unbiased prediction) procedure to estimate the variance components and genotypic values. Were evaluated twelve variables in a total of 210 fruits from 39 different seed trees, from a field trial with an experimental design of incomplete blocks with clonal replies among subplots. The three variables related with the fruit development (weight, diameter, length) showed strong correlation, and where fruit length showed higher heritability and potential to be used for indirect selection. Among the 39 progenies evaluated in this study, five present potential to compose the next cycle of recurrent selection, due they hold good selection differential either to agrotechnological variables as to development of bacuri fruit.

Genotype-phenotype correlation in trisomy 21

Down syndrome (DS) or trisomy 21 (T21) is the most common genetic cause of intellectual disability (ID). Subjects with DS are characterized by complex and variable clinical features including intellectual disability (ID) and craniofacial dysmorphisms. The aim of the thesis is to uncover genotype-phenotype relationships in DS possibly useful to devise therapies based on molecular and cellular mechanisms. In this work, we have investigated different aspects of DS: - we have collected clinical data of children with DS and we have evaluated the cognitive impairment through specific cognitive tests - we have analysed genomics of DS through the study of partial trisomy (PT21) cases. We have described new PT21 cases confirming the hypothesis of the highly restricted DS critical region (HR-DSCR) recently identified as the minimal region whose duplication is shared by all PT21 subjects diagnosed with DS, while it is absent in all PT21 non-DS subjects. Moreover, we have characterized new transcripts included in the HR-DSCR; - we have studied gene expression through RNAseq in blood cells of children with DS; -metabolic alterations in plasma of children with DS were identified through different methods: Nuclear Magnetic resonance, routine blood exams performed during the follow up of the subjects and enzyme-linked immunosorbent assay (ELISA); - to test possible correlations between specific Hsa21 regions and alterations in transcriptomics and metabolomics, we have used trisomic iPSCs and differentiated them into neuronal derivatives. Significant alterations in gene expression and metabolic profiles have been identified, as well as significant correlations with clinical and cognitive aspects. Specific genes and the HR-DSCR may play a role in these alterations: cell models need to be developed to investigate this role. Neural derivatives from trisomic iPSCs are a promising model to better understand genotype-phenotype correlations in DS.

Evaluation of clinical implications correlate to genetic polymorphisms and pharmacokinetic of transdermal fentanyl

ABSTRACT Background:Strong opioids are the treatment of choice for moderate to severe cancer-related pain. Fentanyl is a synthetic opioid with high affinity for the μ-opioid receptor and is 75–100 times more potent than morphine. Fentanyl is metabolised rapidly, particularly in the liver and only 10% is excreted as intact substance. The use of CYP3A4 inhibitors and inducers, impaired liver function, and heating of the patch potentially influence fentanyl pharmacokinetics in a clinically relevant way. The influence of BMI and gender on fentanyl pharmacokinetics is questionable. Pharmacogenetic, may influence fentanyl pharmacokinetic and other factors have been studied but did not show significant and clinically relevant effects on fentanyl pharmacokinetic. Method: This is a biological interventional prospective, single-center study in 49 patients with solid or haematological neoplasm treated with transdermal fentanyl undergoing 5-step pharmacokinetic and pharmacogenetic withdrawals from administration of the fentanyl patch. Objective:to evaluate the pharmacokinetic and pharmacogenetic of transdermal fentanyl in relation to the patient's clinical response on pain Results: Sex was the only parameter with evidence of different distribution between responders and non-responders , showing a major chance for male to be responders than females. We found some correlation with pharmacokinetic parameters and sex, regarding adverse events and NRS correlation with BPI. NAT2 and UGT2B7 polymorphisms are associated with AUC and Cmax kinetics parameters, NAT2 and CYP4F2 showed some evidence of association with the fentanyl dosage and CYP2B6 polymorphism seemed to be correlate with side effects. Conclusion: Small sample size of study population make difficult do find some significant correlation between pharmacogenetic, pharmacokinetic and clinical response. Larger studies are needed to increase knowledge about response to opioid treatment in cancer patients to better individualized pain treatment.