Machine learning for geospatial data : algorithms, software tools and case studies

Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.

Feasibility of Visualization and Simulation Applications to Improve Work Zone Safety and Mobility

Visualization is a relatively recent tool available to engineers for enhancing transportation project design through improved communication, decision making, and stakeholder feedback. Current visualization techniques include image composites, video composites, 2D drawings, drive-through or fly-through animations, 3D rendering models, virtual reality, and 4D CAD. These methods are used mainly to communicate within the design and construction team and between the team and external stakeholders. Use of visualization improves understanding of design intent and project concepts and facilitates effective decision making. However, visualization tools are typically used for presentation only in large-scale urban projects. Visualization is not widely accepted due to a lack of demonstrated engineering benefits for typical agency projects, such as small- and medium-sized projects, rural projects, and projects where external stakeholder communication is not a major issue. Furthermore, there is a perceived high cost of investment of both financial and human capital in adopting visualization tools. The most advanced visualization technique of virtual reality has only been used in academic research settings, and 4D CAD has been used on a very limited basis for highly complicated specialty projects. However, there are a number of less intensive visualization methods available which may provide some benefit to many agency projects. In this paper, we present the results of a feasibility study examining the use of visualization and simulation applications for improving highway planning, design, construction, and safety and mobility.

Feasibility of Visualization and Simulation Applications, Tech Transfer Summary, 2008

Visualization is a relatively recent tool available to engineers for enhancing transportation project design through improved communication, decision making, and stakeholder feedback. Current visualization techniques include image composites, video composites, 2D drawings, drive-through or fly-through animations, 3D rendering models, virtual reality, and 4D CAD. These methods are used mainly to communicate within the design and construction team and between the team and external stakeholders. Use of visualization improves understanding of design intent and project concepts and facilitates effective decision making. However, visualization tools are typically used for presentation only in large-scale urban projects. Visualization is not widely accepted due to a lack of demonstrated engineering benefits for typical agency projects, such as small- and medium-sized projects, rural projects, and projects where external stakeholder communication is not a major issue. Furthermore, there is a perceived high cost of investment of both financial and human capital in adopting visualization tools. The most advanced visualization technique of virtual reality has only been used in academic research settings, and 4D CAD has been used on a very limited basis for highly complicated specialty projects. However, there are a number of less intensive visualization methods available which may provide some benefit to many agency projects. In this paper, we present the results of a feasibility study examining the use of visualization and simulation applications for improving highway planning, design, construction, and safety and mobility.

Visual realism enhances realistic response in an immersive virtual environment

Participants in an immersive virtual environment interact with the scene from an egocentric point of view that is, where there bodies appear to be located rather than from outside as if looking through a window. People interact through normal body movements, such as head-turning,reaching, and bending, and within the tracking limitations move through the environment or effect changes within it in natural ways.

Beaming into the rat world: enabling real-time intereaction between rat and human each at their own scale

Immersive virtual reality (IVR) typically generates the illusion in participants that they are in the displayed virtual scene where they can experience and interact in events as if they were really happening. Teleoperator (TO) systems place people at a remote physical destination embodied as a robotic device, and where typically participants have the sensation of being at the destination, with the ability to interact with entities there. In this paper, we show how to combine IVR and TO to allow a new class of application. The participant in the IVR is represented in the destination by a physical robot (TO) and simultaneously the remote place and entities within it are represented to the participant in the IVR. Hence, the IVR participant has a normal virtual reality experience, but where his or her actions and behaviour control the remote robot and can therefore have physical consequences. Here, we show how such a system can be deployed to allow a human and a rat to operate together, but the human interacting with the rat on a human scale, and the rat interacting with the human on the rat scale. The human is represented in a rat arena by a small robot that is slaved to the human"s movements, whereas the tracked rat is represented to the human in the virtual reality by a humanoid avatar. We describe the system and also a study that was designed to test whether humans can successfully play a game with the rat. The results show that the system functioned well and that the humans were able to interact with the rat to fulfil the tasks of the game. This system opens up the possibility of new applications in the life sciences involving participant observation of and interaction with animals but at human scale.

A Threat to a Virtual Hand Elicits Motor Cortex Activation

We report an experiment where participants observed an attack on their virtual body as experienced in an immersive virtual reality (IVR) system. Participants sat by a table with their right hand resting upon it. In IVR, they saw a virtual table that was registered with the real one, and they had a virtual body that substituted their real body seen from a first person perspective. The virtual right hand was collocated with their real right hand. Event-related brain potentials were recorded in two conditions, one where the participant"s virtual hand was attacked with a knife and a control condition where the knife only struck the virtual table. Significantly greater P450 potentials were obtained in the attack condition confirming our expectations that participants had a strong illusion of the virtual hand being their own, which was also strongly supported by questionnaire responses. Higher levels of subjective virtual hand ownership correlated with larger P450 amplitudes. Mu-rhythm event-related desynchronization in the motor cortex and readiness potential (C3C4) negativity were clearly observed when the virtual hand was threatened as would be expected, if the real hand was threatened and the participant tried to avoid harm. Our results support the idea that event-related potentials may provide a promising non-subjective measure of virtual embodiment. They also support previous experiments on pain observation and are placed into context of similar experiments and studies of body perception and body ownership within cognitive neuroscience.

Acting Rehearsal in Collaborative Multimodal Mixed Reality Environments

This paper presents the use of our multimodal mixed reality telecommunication system to support remote acting rehearsal. The rehearsals involved two actors, located in London and Barcelona, and a director in another location in London. This triadic audiovisual telecommunication was performed in a spatial and multimodal collaborative mixed reality environment based on the 'destination-visitor' paradigm, which we define and put into use. We detail our heterogeneous system architecture, which spans the three distributed and technologically asymmetric sites, and features a range of capture, display, and transmission technologies. The actors' and director's experience of rehearsing a scene via the system are then discussed, exploring successes and failures of this heterogeneous form of telecollaboration. Overall, the common spatial frame of reference presented by the system to all parties was highly conducive to theatrical acting and directing, allowing blocking, gross gesture, and unambiguous instruction to be issued. The relative inexpressivity of the actors' embodiments was identified as the central limitation of the telecommunication, meaning that moments relying on performing and reacting to consequential facial expression and subtle gesture were less successful.

Fluid flow and dispersion predictions in porous media by utilizing advanced numerical methods

Diplomityön tavoitteena oli tarkastella numeerisen virtauslaskennan avulla virtaukseen liittyviä ilmiöitä ja kaasun dispersiota. Diplomityön sisältö on jaettu viiteen osaan; johdantoon, teoriaan, katsaukseen virtauksen mallinnukseen huokoisessa materiaalissa liittyviin tutkimusselvityksiin, numeeriseen mallinnukseen sekä tulosten esittämiseen ja johtopäätöksiin. Diplomityön alussa kiinnitettiin huomiota erilaisiin kokeellisiin, numeerisiin ja teoreettisiin mallinnusmenetelmiin, joilla voidaan mallintaa virtausta huokoisessa materiaalissa. Kirjallisuusosassa tehtiin katsaus aikaisemmin julkaistuihin puoliempiirisiin ja empiirisiin tutkimusselvityksiin, jotka liittyvät huokoisen materiaalin aiheuttamaan painehäviöön. Numeerisessa virtauslaskenta osassa rakennettiin ja esitettiin huokoista materiaalia kuvaavat numeeriset mallit käyttäen kaupallista FLUENT -ohjelmistoa. Työn lopussa arvioitiin teorian, numeerisen virtauslaskennan ja kokeellisten tutkimusselvitysten tuloksia. Kolmiulotteisen huokoisen materiaalinnumeerisessa mallinnuksesta saadut tulokset vaikuttivat lupaavilta. Näiden tulosten perusteella tehtiin suosituksia ajatellen tulevaa virtauksen mallinnusta huokoisessa materiaalissa. Osa tässä diplomityössä esitetyistä tuloksista tullaan esittämään 55. Kanadan Kemiantekniikan konferenssissa Torontossa 1619 Lokakuussa 2005. ASME :n kansainvälisessä tekniikan alan julkaisussa. Työ on hyväksytty esitettäväksi esitettäväksi laskennallisen virtausmekaniikan (CFD) aihealueessa 'Peruskäsitteet'. Lisäksi työn yksityiskohtaiset tulokset tullaan lähettämään myös CES:n julkaisuun.

Touching the void: exploring virtual objects through a vibrotactile glove

This paper describes a simple low-cost approach toadding an element of haptic interaction within a virtualenvironment. Using off-the-shelf hardware and software wedescribe a simple setup that can be used to explore physically virtual objects in space. This setup comprises of a prototype glove with a number of vibrating actuators to provide the haptic feedback, a Kinect camera for the tracking of the user's hand and a virtual reality development environment. As proof of concept and to test the efficiency of the system as well as its potential applications, we developed a simple application where we created 4 different shapes within a virtual environment in order to try toexplore them and guess their shape through touch alone.

Acting rehearsal in collaborative multimodal mixed reality environments

This paper presents the use of our multimodal mixed reality telecommunication system to support remote acting rehearsal. The rehearsals involved two actors, located in London and Barcelona, and a director in another location in London. This triadic audiovisual telecommunication was performed in a spatial and multimodal collaborative mixed reality environment based on the 'destination-visitor' paradigm, which we define and put into use. We detail our heterogeneous system architecture, which spans the three distributed and technologically asymmetric sites, and features a range of capture, display, and transmission technologies. The actors' and director's experience of rehearsing a scene via the system are then discussed, exploring successes and failures of this heterogeneous form of telecollaboration. Overall, the common spatial frame of reference presented by the system to all parties was highly conducive to theatrical acting and directing, allowing blocking, gross gesture, and unambiguous instruction to be issued. The relative inexpressivity of the actors' embodiments was identified as the central limitation of the telecommunication, meaning that moments relying on performing and reacting to consequential facial expression and subtle gesture were less successful.

Modeling competencies and capabilities in knowledge intensive business environment

Tämän diplomityön päämääränä oli tutkia Perloksen teknologiaosaamisia. Perloksen tavoitteena on tulevaisuudessa yhdistää ja soveltaa uusia teknologioita ja älykkäitä materiaaleja muovimekaniikkaan.Ideana oli mallintaa Perloksen osaamisia ja osaamisgapeja ottaen huomioon heidän tulevaisuuden visionsa. Projektituotteena osaamisten mallintamisessa oli Perlos Healthcaren asiakkaan analysoiva mittauslaite. Tutkimuksen arvo on huomattava sillä tunnistamalla osaamisensa ja kyvykkyytensä yritys pystyy luomaan paremman tarjooman vastatessaan koko ajan kasvaviin asiakasvaatimuksiin. Tutkimus on osa TEKESin rahoittamaa LIIMA -projektia. Työn ensimmäisessä osassa esitellään osaamiseen ja partneroitumiseen liittyviä teorioita. Osaamisten mallintaminen tehtiin Excel -pohjaisella työkalulla. Se sisältää projektituotteeseen liittyen osaamisriippuvuuksien mallintamisen ja gap -analyysin. Yhtenä tutkimusmetodina käytettiin haastattelututkimusta. Työ ja sen tulokset antavat operatiivista hyötyä teknologioiden ja markkinoiden välisessä kentässä.

What makes one person paranoid and another person anxious? The differential prediction of social anxiety and persecutory ideation in an experimental situation

The study shows that social anxiety and persecutory ideation share many of the same predictive factors. Non-clinical paranoia may be a type of anxious fear. However, perceptual anomalies are a distinct predictor of paranoia. In the context of an individual feeling anxious, the occurrence of odd internal feelings in social situations may lead to delusional ideas through a sense of" things not seeming right". The study illustrates the approach of focusing on experiences such as paranoid thinking rather than diagnoses such as schizophrenia.

Beaming into the rat world: enabling real-time intereaction between rat and human each at their own scale

Immersive virtual reality (IVR) typically generates the illusion in participants that they are in the displayed virtual scene where they can experience and interact in events as if they were really happening. Teleoperator (TO) systems place people at a remote physical destination embodied as a robotic device, and where typically participants have the sensation of being at the destination, with the ability to interact with entities there. In this paper, we show how to combine IVR and TO to allow a new class of application. The participant in the IVR is represented in the destination by a physical robot (TO) and simultaneously the remote place and entities within it are represented to the participant in the IVR. Hence, the IVR participant has a normal virtual reality experience, but where his or her actions and behaviour control the remote robot and can therefore have physical consequences. Here, we show how such a system can be deployed to allow a human and a rat to operate together, but the human interacting with the rat on a human scale, and the rat interacting with the human on the rat scale. The human is represented in a rat arena by a small robot that is slaved to the human"s movements, whereas the tracked rat is represented to the human in the virtual reality by a humanoid avatar. We describe the system and also a study that was designed to test whether humans can successfully play a game with the rat. The results show that the system functioned well and that the humans were able to interact with the rat to fulfil the tasks of the game. This system opens up the possibility of new applications in the life sciences involving participant observation of and interaction with animals but at human scale.

Beaming into the rat world: enabling real-time intereaction between rat and human each at their own scale

Immersive virtual reality (IVR) typically generates the illusion in participants that they are in the displayed virtual scene where they can experience and interact in events as if they were really happening. Teleoperator (TO) systems place people at a remote physical destination embodied as a robotic device, and where typically participants have the sensation of being at the destination, with the ability to interact with entities there. In this paper, we show how to combine IVR and TO to allow a new class of application. The participant in the IVR is represented in the destination by a physical robot (TO) and simultaneously the remote place and entities within it are represented to the participant in the IVR. Hence, the IVR participant has a normal virtual reality experience, but where his or her actions and behaviour control the remote robot and can therefore have physical consequences. Here, we show how such a system can be deployed to allow a human and a rat to operate together, but the human interacting with the rat on a human scale, and the rat interacting with the human on the rat scale. The human is represented in a rat arena by a small robot that is slaved to the human"s movements, whereas the tracked rat is represented to the human in the virtual reality by a humanoid avatar. We describe the system and also a study that was designed to test whether humans can successfully play a game with the rat. The results show that the system functioned well and that the humans were able to interact with the rat to fulfil the tasks of the game. This system opens up the possibility of new applications in the life sciences involving participant observation of and interaction with animals but at human scale.

Characterization and functional identification of a novel plant extradiol 4,5-dioxygenase involved in betalain pigment biosynthesis in Portulaca Grandiflora

RESUME Les bétalaïnes sont des pigments chromo-alcaloïdes violets et jaunes présents dans les plantes appartenant à l'ordre des Caryophyllales et dans les champignons des genres Amanita et Hygrocybe. Leur courte voie de biosynthèse est élucidée chimiquement depuis de nombreuses années, mais les enzymes impliquées dans cette biosynthèse chez les plantes ne sont toujours pas caractérisées. L'enzyme de la DOPA-dioxygénase d' Amanita muscaria a été identifiée (Girod et Zryd, 1991a), mais de nombreuses tentatives d'isolation d'un homologue chez les plantes ont échoué. Afin d'isoler les gènes spécifiques des bétalaïnes chez les plantes, nous avons construit des banques soustraites d'ADNc à partir d'ARN total de pétales immatures de Portulaca grandiflora (Pg) de génotypes jaunes et blancs, respectivement violets et blancs. Les clones couleur- spécifiques ont été détectés en premier par analyse Northem du RNA de pétales blancs et colorés. Les candidats positifs ont alors été soumis à une analyse de transcription au niveau des tiges colorées, vertes et des feuilles, afin d'établir leur expression spécifique. Deux ARNs messagers complets ont une expression corrélée avec l'accumulation des bétalaïnes dans les tissus. Le premier de ces clones, A.16, code pour une oxydase de l'acyl-Coenzyme A (ACX) putative, mais le domaine de liaison du FAD essentiel pour l'activité d'ACX est absent. Toutes nos tentatives pour démontrer sa fonction ont échoué. Le rôle de cette protéine dans la voie de synthèse des bétalaïnes reste inconnu. Le deuxième de ces clones spécifique aux bétalaïnes, L.6 (isolé par Zaiko, 2000), a été renommé DODA en raison de son homologie avec le domaine LigB (pfam02900) d'une 4,5-dioxygénase extradiol bactérienne. DODA a été identifié in silico comme une dioxygénase extradiol en raison de la conservation stricte, au niveau de sa séquence peptidique, des résidus catalytiques de LigB et de ceux liant le cofacteur fer. Une analyse de transfert Southem a montré que ce gène est unique dans Pg. L'expression transitoire de DODA par transformation biolistique dans des pétales blancs de Pg a produit des taches violettes ou jaunes dans des cellules transformées. Une analyse HPLC de ces taches a démontré leur identité avec les bétalaïnes présentes naturellement dans les pétales violets et jaunes de Pg, confirmant ainsi la complémentation par le gène Pg DODA de l'allèle récessif cc présent dans les pétales blancs de Pg. Des homologues de DODA (DOPA-dioxygénase) ont été identifiés dans de nombreuses espèces de plantes, y compris dans celles sans bétalaïne. L'alignement de ces homologues a permis l'identification d'un motif spécifique aux bétalaïnes à côté d'une histidine catalytique conservée. Ce motif [H-P-(S,A)-(N,D)-x-T-P] remplace le motif [H-N-L-R] conservé dans les plantes sans bétalaïne et le motif [H-N-L-x] présent dans tous les homologues bactériens et archaebactériens. Une modélisation tridimensionnelle préliminaire du site actif de Pg DODA et de son homologue dans la mousse Physcomitrella patens a montré l'importance de ce motif spécifique aux bétalaïnes pour l'accessibilité du substrat au site actif. L'analyse phylogénétique de DODA a confirmé l'évolution séparée de cette protéine chez les plantes à bétalaïnes par comparaison avec celle des plantes sans bétalaïne. Nous avons donc conclu que les bétalaïnes sont apparues par modification de l'affinité pour un substrat d'enzymes similaires à DODA, chez un ancêtre unique des Caryophyllales qui a perdu toute capacité de biosynthèse des anthocyanes. Finalement, Pg DODA n'a aucune similarité avec la protéine DODA d' Amanita muscaria, bien que celle-ci complémente aussi la pigmentation des pétales blancs de Pg. La biosynthèse des bétalaïnes est un exemple remarquable de convergence évolutive biochimique indépendante entre espèces de règnes différents. ABSTRACT Betalains are violet and yellow chromo-alkaloid pigments present in plants belonging to the order Caryophyllales and also in the fungal genera Amanita and Hygrocybe. Their short biosynthetic pathway is chemically well understood since many years, but enzymes involved in the plant pathway are still uncharacterized. The DOPA-dioxygenase from Amanita muscaria was identified (Girod and Zryd, 1991a), but numerous attempts to identify a plant homologue to the corresponding gene, failed. In order to isolate betalain-specific genes in plants, subtractive cDNA libraries were built with total RNA from white and yellow and respectively, violet immature petals from Portulaca grandiflora (Pg) genotypes. Colour-specific clones were first detected by Northern blot analysis using RNA from white and coloured petals. Positive candidates were submitted to further transcription analysis in coloured, green stems and leaves in order to assess their specific expression. Two full-length mRNAs showed a correlated expression with betalain accumulation in tissues. One of them, A.16, encodes a putative acyl-Coenzyme A oxidase (ACX), but missing the FAD binding domain essential for the ACX activity. Thus, all attempts to demonstrate its function failed. The role of this protein in the betalain biosynthesis pathway, if any, is still unknown. The second betalain-specific mRNA, L.6 (isolated by Zaiko, 2000) shows a homology with a LigB domain (pfam02900) from a bacterial extradiol 4,5-dioxygenase. It was then renamed DODA (DOPA-dioxygenase). DODA was identified in silico as a highly conserved extradiol dioxygenase due to the strict conservation of its peptidic sequence with LigB catalytic residues and iron-binding cofactor residues. Southern blot analysis showed that this gene is a single copy-gene in Pg. Transient expression of DODA protein through biolistic transformation of Pg white petals produced violet or yellow spots in individual cells. HPLC analysis of these spots showed an identity with betalain pigments present naturally in yellow and violet Pg petals, thus confirming the complementation of the recessive cc allele present in Pg white petals by Pg DODA gene. DODA homologues were identified in numerous plant species including those without betalain. Alignment of these homologues allowed the identification of a betalain-specific pattern beside a highly conserved catalytic histidine. This [H-P-(S,A)-(N,D)-x-T-P] pattern replaces a [H-N-L-R] pattern strictly conserved in non-betalain plants and a [H-N-L-x] pattern present in all bacterial and archaebacterial homologues. Preliminary three-dimensional modeling of the active site of Pg DODA and its Physcomitrella patens moss homologue revealed the importance of this betalain-specific pattern for the substrate accessibility to the DODA active site. DODA phylogenetic analysis confirmed the separate evolution of this protein in betalain-producing plants. We conclude that betalain pigments appeared in a unique ancestor of the Caryophyllales order in which anthocyanin biosynthetic pathway was impaired, by a modification of enzymes of the DODA family for substrate affinity. The Pg DODA protein has no sequence similarity with Amanita muscaria DODA, despite the fact that they both complement Pg white petals for their pigmentation. Betalain biosynthesis is an interesting example of independent biochemical evolutionary convergence between species from different kingdoms.