On the number of independent cultural traits carried by individuals and populations.

In species subject to individual and social learning, each individual is likely to express a certain number of different cultural traits acquired during its lifetime. If the process of trait innovation and transmission reaches a steady state in the population, the number of different cultural traits carried by an individual converges to some stationary distribution. We call this the trait-number distribution. In this paper, we derive the trait-number distributions for both individuals and populations when cultural traits are independent of each other. Our results suggest that as the number of cultural traits becomes large, the trait-number distributions approach Poisson distributions so that their means characterize cultural diversity in the population. We then analyse how the mean trait number varies at both the individual and population levels as a function of various demographic features, such as population size and subdivision, and social learning rules, such as conformism and anti-conformism. Diversity at the individual and population levels, as well as at the level of cultural homogeneity within groups, depends critically on the details of population demography and the individual and social learning rules.

Segmental copy number variation shapes tissue transcriptomes.

Copy number variation (CNV) is a key source of genetic diversity, but a comprehensive understanding of its phenotypic effect is only beginning to emerge. We have generated a CNV map in wild mice and classical inbred strains. Genome-wide expression data from six major organs show not only that expression of genes within CNVs tend to correlate with copy number changes, but also that CNVs influence the expression of genes in their vicinity, an effect that extends up to half a megabase. Genes within CNVs show lower expression and more specific spatial expression patterns than genes mapping elsewhere. Our analyses reveal differential constraint on copy number changes of genes expressed in different tissues. Dosage alterations of brain-expressed genes are less frequent than those of other genes and are buffered by tighter transcriptional regulation. Our study provides initial evidence that CNVs shape tissue transcriptomes on a global scale.

Use of flow cytometric methods for single-cell analysis in environmental microbiology

Flow cytometry (FCM) is emerging as an important tool in environmental microbiology. Although flow cytometry applications have to date largely been restricted to certain specialized fields of microbiology, such as the bacterial cell cycle and marine phytoplankton communities, technical advances in instrumentation and methodology are leading to its increased popularity and extending its range of applications. Here we will focus on a number of recent flow cytometry developments important for addressing questions in environmental microbiology. These include (i) the study of microbial physiology under environmentally relevant conditions, (ii) new methods to identify active microbial populations and to isolate previously uncultured microorganisms, and (iii) the development of high-throughput autofluorescence bioreporter assays

Copy number variation characteristics in subpopulations of patients with autism spectrum disorders.

Autism spectrum disorders (ASDs) are a heterogeneous group of disorders with a complex genetic etiology. We used high-resolution whole genome array-based comparative genomic hybridization (array-CGH) to screen 223 ASD patients for gene dose alterations associated with susceptibility for autism. Clinically significant copy number variations (CNVs) were identified in 18 individuals (8%), of which 9 cases (4%) had de novo aberrations. In addition, 20 individuals (9%) were shown to have CNVs of unclear clinical relevance. Among these, 13 cases carried rare but inherited CNVs that may increase the risk for developing ASDs, while parental samples were unavailable in the remaining seven cases. Classification of all patients into different phenotypic and inheritance pattern groups indicated the presence of different CNV patterns in different patient groups. Clinically relevant CNVs were more common in syndromic cases compared to non-syndromic cases. Rare inherited CNVs were present in a higher proportion of ASD cases having first- or second-degree relatives with an ASD-related neuropsychiatric phenotype in comparison with cases without reported heredity (P = 0.0096). We conclude that rare CNVs, encompassing potential candidate regions for ASDs, increase the susceptibility for the development of ASDs and related neuropsychiatric disorders giving us further insight into the complex genetics underlying ASDs.

Genome-wide association analysis of copy number variation in recurrent depressive disorder.

Large, rare copy number variants (CNVs) have been implicated in a variety of psychiatric disorders, but the role of CNVs in recurrent depression is unclear. We performed a genome-wide analysis of large, rare CNVs in 3106 cases of recurrent depression, 459 controls screened for lifetime-absence of psychiatric disorder and 5619 unscreened controls from phase 2 of the Wellcome Trust Case Control Consortium (WTCCC2). We compared the frequency of cases with CNVs against the frequency observed in each control group, analysing CNVs over the whole genome, genic, intergenic, intronic and exonic regions. We found that deletion CNVs were associated with recurrent depression, whereas duplications were not. The effect was significant when comparing cases with WTCCC2 controls (P=7.7 × 10(-6), odds ratio (OR) =1.25 (95% confidence interval (CI) 1.13-1.37)) and to screened controls (P=5.6 × 10(-4), OR=1.52 (95% CI 1.20-1.93). Further analysis showed that CNVs deleting protein coding regions were largely responsible for the association. Within an analysis of regions previously implicated in schizophrenia, we found an overall enrichment of CNVs in our cases when compared with screened controls (P=0.019). We observe an ordered increase of samples with deletion CNVs, with the lowest proportion seen in screened controls, the next highest in unscreened controls and the highest in cases. This may suggest that the absence of deletion CNVs, especially in genes, is associated with resilience to recurrent depression.

Integrated Analysis of High-Resolution Gene Expression and Copy Number Profiling Identified Biallelic Deletion of CDKN2A/2B Tumor Suppressor Locus As the Most Frequent and Unique Genomic Abnormality in Diffuse Large B-Cell Lymphoma (DLBCL) with Strong Prognostic Value in Both GCB and ABC Subtypes and Not Overcome by a Dose-Intensive Immunochemotherapy Regimen Plus Rituximab. Results of a Prospective GELA Clinical Trial Program

Background and aim of the study: Genomic gains and losses play a crucial role in the development and progression of DLBCL and are closely related to gene expression profiles (GEP), including the germinal center B-cell like (GCB) and activated B-cell like (ABC) cell of origin (COO) molecular signatures. To identify new oncogenes or tumor suppressor genes (TSG) involved in DLBCL pathogenesis and to determine their prognostic values, an integrated analysis of high-resolution gene expression and copy number profiling was performed. Patients and methods: Two hundred and eight adult patients with de novo CD20+ DLBCL enrolled in the prospective multicentric randomized LNH-03 GELA trials (LNH03-1B, -2B, -3B, 39B, -5B, -6B, -7B) with available frozen tumour samples, centralized reviewing and adequate DNA/RNA quality were selected. 116 patients were treated by Rituximab(R)-CHOP/R-miniCHOP and 92 patients were treated by the high dose (R)-ACVBP regimen dedicated to patients younger than 60 years (y) in frontline. Tumour samples were simultaneously analysed by high resolution comparative genomic hybridization (CGH, Agilent, 144K) and gene expression arrays (Affymetrix, U133+2). Minimal common regions (MCR), as defined by segments that affect the same chromosomal region in different cases, were delineated. Gene expression and MCR data sets were merged using Gene expression and dosage integrator algorithm (GEDI, Lenz et al. PNAS 2008) to identify new potential driver genes. Results: A total of 1363 recurrent (defined by a penetrance > 5%) MCRs within the DLBCL data set, ranging in size from 386 bp, affecting a single gene, to more than 24 Mb were identified by CGH. Of these MCRs, 756 (55%) showed a significant association with gene expression: 396 (59%) gains, 354 (52%) single-copy deletions, and 6 (67%) homozygous deletions. By this integrated approach, in addition to previously reported genes (CDKN2A/2B, PTEN, DLEU2, TNFAIP3, B2M, CD58, TNFRSF14, FOXP1, REL...), several genes targeted by gene copy abnormalities with a dosage effect and potential physiopathological impact were identified, including genes with TSG activity involved in cell cycle (HACE1, CDKN2C) immune response (CD68, CD177, CD70, TNFSF9, IRAK2), DNA integrity (XRCC2, BRCA1, NCOR1, NF1, FHIT) or oncogenic functions (CD79b, PTPRT, MALT1, AUTS2, MCL1, PTTG1...) with distinct distribution according to COO signature. The CDKN2A/2B tumor suppressor locus (9p21) was deleted homozygously in 27% of cases and hemizygously in 9% of cases. Biallelic loss was observed in 49% of ABC DLBCL and in 10% of GCB DLBCL. This deletion was strongly correlated to age and associated to a limited number of additional genetic abnormalities including trisomy 3, 18 and short gains/losses of Chr. 1, 2, 19 regions (FDR < 0.01), allowing to identify genes that may have synergistic effects with CDKN2A/2B inactivation. With a median follow-up of 42.9 months, only CDKN2A/2B biallelic deletion strongly correlates (FDR p.value < 0.01) to a poor outcome in the entire cohort (4y PFS = 44% [32-61] respectively vs. 74% [66-82] for patients in germline configuration; 4y OS = 53% [39-72] vs 83% [76-90]). In a Cox proportional hazard prediction of the PFS, CDKN2A/2B deletion remains predictive (HR = 1.9 [1.1-3.2], p = 0.02) when combined with IPI (HR = 2.4 [1.4-4.1], p = 0.001) and GCB status (HR = 1.3 [0.8-2.3], p = 0.31). This difference remains predictive in the subgroup of patients treated by R-CHOP (4y PFS = 43% [29-63] vs. 66% [55-78], p=0.02), in patients treated by R-ACVBP (4y PFS = 49% [28-84] vs. 83% [74-92], p=0.003), and in GCB (4y PFS = 50% [27-93] vs. 81% [73-90], p=0.02), or ABC/unclassified (5y PFS = 42% [28-61] vs. 67% [55-82] p = 0.009) molecular subtypes (Figure 1). Conclusion: We report for the first time an integrated genetic analysis of a large cohort of DLBCL patients included in a prospective multicentric clinical trial program allowing identifying new potential driver genes with pathogenic impact. However CDKN2A/2B deletion constitutes the strongest and unique prognostic factor of chemoresistance to R-CHOP, regardless the COO signature, which is not overcome by a more intensified immunochemotherapy. Patients displaying this frequent genomic abnormality warrant new and dedicated therapeutic approaches.

Time-lapse and probabilistic inversion strategies for plane-wave electromagnetic data.

L'utilisation efficace des systèmes géothermaux, la séquestration du CO2 pour limiter le changement climatique et la prévention de l'intrusion d'eau salée dans les aquifères costaux ne sont que quelques exemples qui démontrent notre besoin en technologies nouvelles pour suivre l'évolution des processus souterrains à partir de la surface. Un défi majeur est d'assurer la caractérisation et l'optimisation des performances de ces technologies à différentes échelles spatiales et temporelles. Les méthodes électromagnétiques (EM) d'ondes planes sont sensibles à la conductivité électrique du sous-sol et, par conséquent, à la conductivité électrique des fluides saturant la roche, à la présence de fractures connectées, à la température et aux matériaux géologiques. Ces méthodes sont régies par des équations valides sur de larges gammes de fréquences, permettant détudier de manières analogues des processus allant de quelques mètres sous la surface jusqu'à plusieurs kilomètres de profondeur. Néanmoins, ces méthodes sont soumises à une perte de résolution avec la profondeur à cause des propriétés diffusives du champ électromagnétique. Pour cette raison, l'estimation des modèles du sous-sol par ces méthodes doit prendre en compte des informations a priori afin de contraindre les modèles autant que possible et de permettre la quantification des incertitudes de ces modèles de façon appropriée. Dans la présente thèse, je développe des approches permettant la caractérisation statique et dynamique du sous-sol à l'aide d'ondes EM planes. Dans une première partie, je présente une approche déterministe permettant de réaliser des inversions répétées dans le temps (time-lapse) de données d'ondes EM planes en deux dimensions. Cette stratégie est basée sur l'incorporation dans l'algorithme d'informations a priori en fonction des changements du modèle de conductivité électrique attendus. Ceci est réalisé en intégrant une régularisation stochastique et des contraintes flexibles par rapport à la gamme des changements attendus en utilisant les multiplicateurs de Lagrange. J'utilise des normes différentes de la norme l2 pour contraindre la structure du modèle et obtenir des transitions abruptes entre les régions du model qui subissent des changements dans le temps et celles qui n'en subissent pas. Aussi, j'incorpore une stratégie afin d'éliminer les erreurs systématiques de données time-lapse. Ce travail a mis en évidence l'amélioration de la caractérisation des changements temporels par rapport aux approches classiques qui réalisent des inversions indépendantes à chaque pas de temps et comparent les modèles. Dans la seconde partie de cette thèse, j'adopte un formalisme bayésien et je teste la possibilité de quantifier les incertitudes sur les paramètres du modèle dans l'inversion d'ondes EM planes. Pour ce faire, je présente une stratégie d'inversion probabiliste basée sur des pixels à deux dimensions pour des inversions de données d'ondes EM planes et de tomographies de résistivité électrique (ERT) séparées et jointes. Je compare les incertitudes des paramètres du modèle en considérant différents types d'information a priori sur la structure du modèle et différentes fonctions de vraisemblance pour décrire les erreurs sur les données. Les résultats indiquent que la régularisation du modèle est nécessaire lorsqu'on a à faire à un large nombre de paramètres car cela permet d'accélérer la convergence des chaînes et d'obtenir des modèles plus réalistes. Cependent, ces contraintes mènent à des incertitudes d'estimations plus faibles, ce qui implique des distributions a posteriori qui ne contiennent pas le vrai modèledans les régions ou` la méthode présente une sensibilité limitée. Cette situation peut être améliorée en combinant des méthodes d'ondes EM planes avec d'autres méthodes complémentaires telles que l'ERT. De plus, je montre que le poids de régularisation des paramètres et l'écart-type des erreurs sur les données peuvent être retrouvés par une inversion probabiliste. Finalement, j'évalue la possibilité de caractériser une distribution tridimensionnelle d'un panache de traceur salin injecté dans le sous-sol en réalisant une inversion probabiliste time-lapse tridimensionnelle d'ondes EM planes. Etant donné que les inversions probabilistes sont très coûteuses en temps de calcul lorsque l'espace des paramètres présente une grande dimension, je propose une stratégie de réduction du modèle ou` les coefficients de décomposition des moments de Legendre du panache de traceur injecté ainsi que sa position sont estimés. Pour ce faire, un modèle de résistivité de base est nécessaire. Il peut être obtenu avant l'expérience time-lapse. Un test synthétique montre que la méthodologie marche bien quand le modèle de résistivité de base est caractérisé correctement. Cette méthodologie est aussi appliquée à un test de trac¸age par injection d'une solution saline et d'acides réalisé dans un système géothermal en Australie, puis comparée à une inversion time-lapse tridimensionnelle réalisée selon une approche déterministe. L'inversion probabiliste permet de mieux contraindre le panache du traceur salin gr^ace à la grande quantité d'informations a priori incluse dans l'algorithme. Néanmoins, les changements de conductivités nécessaires pour expliquer les changements observés dans les données sont plus grands que ce qu'expliquent notre connaissance actuelle des phénomenès physiques. Ce problème peut être lié à la qualité limitée du modèle de résistivité de base utilisé, indiquant ainsi que des efforts plus grands devront être fournis dans le futur pour obtenir des modèles de base de bonne qualité avant de réaliser des expériences dynamiques. Les études décrites dans cette thèse montrent que les méthodes d'ondes EM planes sont très utiles pour caractériser et suivre les variations temporelles du sous-sol sur de larges échelles. Les présentes approches améliorent l'évaluation des modèles obtenus, autant en termes d'incorporation d'informations a priori, qu'en termes de quantification d'incertitudes a posteriori. De plus, les stratégies développées peuvent être appliquées à d'autres méthodes géophysiques, et offrent une grande flexibilité pour l'incorporation d'informations additionnelles lorsqu'elles sont disponibles. -- The efficient use of geothermal systems, the sequestration of CO2 to mitigate climate change, and the prevention of seawater intrusion in coastal aquifers are only some examples that demonstrate the need for novel technologies to monitor subsurface processes from the surface. A main challenge is to assure optimal performance of such technologies at different temporal and spatial scales. Plane-wave electromagnetic (EM) methods are sensitive to subsurface electrical conductivity and consequently to fluid conductivity, fracture connectivity, temperature, and rock mineralogy. These methods have governing equations that are the same over a large range of frequencies, thus allowing to study in an analogous manner processes on scales ranging from few meters close to the surface down to several hundreds of kilometers depth. Unfortunately, they suffer from a significant resolution loss with depth due to the diffusive nature of the electromagnetic fields. Therefore, estimations of subsurface models that use these methods should incorporate a priori information to better constrain the models, and provide appropriate measures of model uncertainty. During my thesis, I have developed approaches to improve the static and dynamic characterization of the subsurface with plane-wave EM methods. In the first part of this thesis, I present a two-dimensional deterministic approach to perform time-lapse inversion of plane-wave EM data. The strategy is based on the incorporation of prior information into the inversion algorithm regarding the expected temporal changes in electrical conductivity. This is done by incorporating a flexible stochastic regularization and constraints regarding the expected ranges of the changes by using Lagrange multipliers. I use non-l2 norms to penalize the model update in order to obtain sharp transitions between regions that experience temporal changes and regions that do not. I also incorporate a time-lapse differencing strategy to remove systematic errors in the time-lapse inversion. This work presents improvements in the characterization of temporal changes with respect to the classical approach of performing separate inversions and computing differences between the models. In the second part of this thesis, I adopt a Bayesian framework and use Markov chain Monte Carlo (MCMC) simulations to quantify model parameter uncertainty in plane-wave EM inversion. For this purpose, I present a two-dimensional pixel-based probabilistic inversion strategy for separate and joint inversions of plane-wave EM and electrical resistivity tomography (ERT) data. I compare the uncertainties of the model parameters when considering different types of prior information on the model structure and different likelihood functions to describe the data errors. The results indicate that model regularization is necessary when dealing with a large number of model parameters because it helps to accelerate the convergence of the chains and leads to more realistic models. These constraints also lead to smaller uncertainty estimates, which imply posterior distributions that do not include the true underlying model in regions where the method has limited sensitivity. This situation can be improved by combining planewave EM methods with complimentary geophysical methods such as ERT. In addition, I show that an appropriate regularization weight and the standard deviation of the data errors can be retrieved by the MCMC inversion. Finally, I evaluate the possibility of characterizing the three-dimensional distribution of an injected water plume by performing three-dimensional time-lapse MCMC inversion of planewave EM data. Since MCMC inversion involves a significant computational burden in high parameter dimensions, I propose a model reduction strategy where the coefficients of a Legendre moment decomposition of the injected water plume and its location are estimated. For this purpose, a base resistivity model is needed which is obtained prior to the time-lapse experiment. A synthetic test shows that the methodology works well when the base resistivity model is correctly characterized. The methodology is also applied to an injection experiment performed in a geothermal system in Australia, and compared to a three-dimensional time-lapse inversion performed within a deterministic framework. The MCMC inversion better constrains the water plumes due to the larger amount of prior information that is included in the algorithm. The conductivity changes needed to explain the time-lapse data are much larger than what is physically possible based on present day understandings. This issue may be related to the base resistivity model used, therefore indicating that more efforts should be given to obtain high-quality base models prior to dynamic experiments. The studies described herein give clear evidence that plane-wave EM methods are useful to characterize and monitor the subsurface at a wide range of scales. The presented approaches contribute to an improved appraisal of the obtained models, both in terms of the incorporation of prior information in the algorithms and the posterior uncertainty quantification. In addition, the developed strategies can be applied to other geophysical methods, and offer great flexibility to incorporate additional information when available.

On the use of IRMS in forensic science: proposals for a methodological approach

The flourishing number of publications on the use of isotope ratio mass spectrometry (IRMS) in forensic science denotes the enthusiasm and the attraction generated by this technology. IRMS has demonstrated its potential to distinguish chemically identical compounds coming from different sources. Despite the numerous applications of IRMS to a wide range of forensic materials, its implementation in a forensic framework is less straightforward than it appears. In addition, each laboratory has developed its own strategy of analysis on calibration, sequence design, standards utilisation and data treatment without a clear consensus.Through the experience acquired from research undertaken in different forensic fields, we propose a methodological framework of the whole process using IRMS methods. We emphasize the importance of considering isotopic results as part of a whole approach, when applying this technology to a particular forensic issue. The process is divided into six different steps, which should be considered for a thoughtful and relevant application. The dissection of this process into fundamental steps, further detailed, enables a better understanding of the essential, though not exhaustive, factors that have to be considered in order to obtain results of quality and sufficiently robust to proceed to retrospective analyses or interlaboratory comparisons.

External irradiation with or without long-term androgen suppression for prostate cancer with high metastatic risk: 10-year results of an EORTC randomised study.

BACKGROUND: We did a randomised phase 3 trial assessing the benefit of addition of long-term androgen suppression with a luteinising-hormone-releasing hormone (LHRH) agonist to external irradiation in patients with prostate cancer with high metastatic risk. In this report, we present the 10-year results. METHODS: For this open-label randomised trial, eligible patients were younger than 80 years and had newly diagnosed histologically proven T1-2 prostatic adenocarcinoma with WHO histological grade 3 or T3-4 prostatic adenocarcinoma of any histological grade, and a WHO performance status of 0-2. Patients were randomly assigned (1:1) to receive radiotherapy alone or radiotherapy plus immediate androgen suppression. Treatment allocation was open label and used a minimisation algorithm with institution, clinical stage of the disease, results of pelvic-lymph-node dissection, and irradiation fields extension as minimisation factors. Patients were irradiated externally, once a day, 5 days a week, for 7 weeks to a total dose of 50 Gy to the whole pelvis, with an additional 20 Gy to the prostate and seminal vesicles. The LHRH agonist, goserelin acetate (3·6 mg subcutaneously every 4 weeks), was started on the first day of irradiation and continued for 3 years; cyproterone acetate (50 mg orally three times a day) was given for 1 month starting a week before the first goserelin injection. The primary endpoint was clinical disease-free survival. Analysis was by intention to treat. The trial is registered at ClinicalTrials.gov, number NCT00849082. FINDINGS: Between May 22, 1987, and Oct 31, 1995, 415 patients were randomly assigned to treatment groups and were included in the analysis (208 radiotherapy alone, 207 combined treatment). Median follow-up was 9·1 years (IQR 5·1-12·6). 10-year clinical disease-free survival was 22·7% (95% CI 16·3-29·7) in the radiotherapy-alone group and 47·7% (39·0-56·0) in the combined treatment group (hazard ratio [HR] 0·42, 95% CI 0·33-0·55, p<0·0001). 10-year overall survival was 39·8% (95% CI 31·9-47·5) in patients receiving radiotherapy alone and 58·1% (49·2-66·0) in those allocated combined treatment (HR 0·60, 95% CI 0·45-0·80, p=0·0004), and 10-year prostate-cancer mortality was 30·4% (95% CI 23·2-37·5) and 10·3% (5·1-15·4), respectively (HR 0·38, 95% CI 0·24-0·60, p<0·0001). No significant difference in cardiovascular mortality was noted between treatment groups both in patients who had cardiovascular problems at study entry (eight of 53 patients in the combined treatment group had a cardiovascular-related cause of death vs 11 of 63 in the radiotherapy group; p=0·60) and in those who did not (14 of 154 vs six of 145; p=0·25). Two fractures were reported in patients allocated combined treatment. INTERPRETATION: In patients with prostate cancer with high metastatic risk, immediate androgen suppression with an LHRH agonist given during and for 3 years after external irradiation improves 10-year disease-free and overall survival without increasing late cardiovascular toxicity.

A step beyond--the relevance of depressed mood and mastery in the interplay between the number of social roles and alcohol use.

OBJECTIVES: The present study examines whether depressed mood and external control mediate or moderate the relationship between the number of social roles and alcohol use. PARTICIPANTS: The analysis was based on a national representative sample of 25- to 45-year-old male and female drinkers in Switzerland. METHOD: The influence of depressed mood and external control on the relationship between the number of social roles (parenthood, partnership, employment) and alcohol use was examined in linear structural equation models (mediation) and in multiple regressions (moderation) stratified by gender. All analyses were adjusted for age and education level. RESULTS: Holding more roles was associated with lower alcohol use, lower external control and lower depressed mood. The study did not find evidence of depressed mood or external control mediating the social roles-alcohol relationship. A moderation effect was identified among women only, whereby a protective effect of having more roles could not be found among those who scored high on external control. In general, a stronger link was observed between roles and alcohol use, while depressed mood and external control acted independently on drinking. With the exception of women with high external control, the study found no link between a higher number of social roles and greater alcohol use. CONCLUSION: Our results indicate that drinking behaviours are more strongly linked to external control and depressed mood than they are to the number of social roles. The study also demonstrates that in any effective alcohol prevention policy, societal actions that enable individuals to combine more social roles play a central role.

Prominent use of distal 5' transcription start sites and discovery of a large number of additional exons in ENCODE regions.

This report presents systematic empirical annotation of transcript products from 399 annotated protein-coding loci across the 1% of the human genome targeted by the Encyclopedia of DNA elements (ENCODE) pilot project using a combination of 5' rapid amplification of cDNA ends (RACE) and high-density resolution tiling arrays. We identified previously unannotated and often tissue- or cell-line-specific transcribed fragments (RACEfrags), both 5' distal to the annotated 5' terminus and internal to the annotated gene bounds for the vast majority (81.5%) of the tested genes. Half of the distal RACEfrags span large segments of genomic sequences away from the main portion of the coding transcript and often overlap with the upstream-annotated gene(s). Notably, at least 20% of the resultant novel transcripts have changes in their open reading frames (ORFs), most of them fusing ORFs of adjacent transcripts. A significant fraction of distal RACEfrags show expression levels comparable to those of known exons of the same locus, suggesting that they are not part of very minority splice forms. These results have significant implications concerning (1) our current understanding of the architecture of protein-coding genes; (2) our views on locations of regulatory regions in the genome; and (3) the interpretation of sequence polymorphisms mapping to regions hitherto considered to be "noncoding," ultimately relating to the identification of disease-related sequence alterations.

Numerical simulation of gel electrophoresis of DNA knots in weak and strong electric fields.

Gel electrophoresis allows one to separate knotted DNA (nicked circular) of equal length according to the knot type. At low electric fields, complex knots, being more compact, drift faster than simpler knots. Recent experiments have shown that the drift velocity dependence on the knot type is inverted when changing from low to high electric fields. We present a computer simulation on a lattice of a closed, knotted, charged DNA chain drifting in an external electric field in a topologically restricted medium. Using a Monte Carlo algorithm, the dependence of the electrophoretic migration of the DNA molecules on the knot type and on the electric field intensity is investigated. The results are in qualitative and quantitative agreement with electrophoretic experiments done under conditions of low and high electric fields.

Kernel-based mapping of orographic rainfall enhancement in the Swiss Alps as detected by weatherradar

In this paper, we develop a data-driven methodology to characterize the likelihood of orographic precipitation enhancement using sequences of weather radar images and a digital elevation model (DEM). Geographical locations with topographic characteristics favorable to enforce repeatable and persistent orographic precipitation such as stationary cells, upslope rainfall enhancement, and repeated convective initiation are detected by analyzing the spatial distribution of a set of precipitation cells extracted from radar imagery. Topographic features such as terrain convexity and gradients computed from the DEM at multiple spatial scales as well as velocity fields estimated from sequences of weather radar images are used as explanatory factors to describe the occurrence of localized precipitation enhancement. The latter is represented as a binary process by defining a threshold on the number of cell occurrences at particular locations. Both two-class and one-class support vector machine classifiers are tested to separate the presumed orographic cells from the nonorographic ones in the space of contributing topographic and flow features. Site-based validation is carried out to estimate realistic generalization skills of the obtained spatial prediction models. Due to the high class separability, the decision function of the classifiers can be interpreted as a likelihood or susceptibility of orographic precipitation enhancement. The developed approach can serve as a basis for refining radar-based quantitative precipitation estimates and short-term forecasts or for generating stochastic precipitation ensembles conditioned on the local topography.