Caractérisation et délimitation des sous-espèces de Gesneria viridiflora (Gesneriaceae) dans les Antilles

Une taxonomie révisée et une connaissance des limites d’espèces demeurent toujours importantes dans les points chauds en biodiversité comme les Antilles où de nombreuses espèces endémiques sont retrouvées. Des limites d’espèces divergentes impliquent un différent nombre d’espèces retrouvées dans un écosystème, ce qui peut exercer une influence sur les décisions prises face aux enjeux de conservation. Les genres Gesneria et Rhytidophyllum qui forment les principaux représentants de la famille des Gesneriaceae dans les Antilles comprennent plusieurs taxons aux limites d’espèces ambigües et quelques espèces qui ont des sous-espèces reconnues. C’est le cas de Gesneria viridiflora (Decne.) Kuntze qui comprend quatre sous-espèces géographiquement isolées et qui présentent des caractères végétatifs et reproducteurs similaires et variables. Une délimitation d’espèces approfondie de ce complexe d’espèce est effectuée ici à partir d’une approche de taxonomie intégrative considérant des données morphologiques, génétiques et bioclimatiques. Les données morphologiques quantitatives et qualitatives obtenues à partir de spécimens d’herbier sont utilisées pour délimiter des groupes morphologiques à l’aide d’une analyse en coordonnées principales. Ces groupes sont ensuite testés à l’aide de séquences d’ADN de quatre régions nucléaires en utilisant une méthode bayesienne basée sur la théorie de la coalescence. Finalement, les occurrences et les valeurs de variables de température et de précipitation qui y prévalent sont utilisées dans une analyse en composantes principales bioclimatique pour comparer les groupes délimités morphologiquement et génétiquement. Les résultats de l’analyse morphologique multivariée supportent la distinction entre les groupes formés par les sous-espèces actuellement reconnues de G. viridiflora. Les résultats, incluant des données génétiques, suggèrent une distinction jusqu’ici insoupçonnée des populations du Massif de la Hotte au sud-ouest d’Haïti qui sont génétiquement plus rapprochées des populations de Cuba que de celles d’Hispaniola. Bioclimatiquement, les groupes délimités par les analyses morphologiques et génétiques sont distincts. L’approche de taxonomie intégrative a permis de distinguer cinq espèces distinctes plutôt que les quatre sous-espèces acceptées jusqu’à aujourd’hui. Ces espèces sont : G. acrochordonanthe, G. quisqueyana, G. sintenisii, G. sylvicola et G. viridiflora. Une carte de distribution géographique, un tableau de la nouvelle taxonomie applicable et une clé d’identification des espèces sont présentés. La nouvelle taxonomie déterminée dans cette étude démontre un endémisme insoupçonné dans plusieurs régions du point chaud en biodiversité des Antilles et souligne l’importance d’investiguer les limites d’espèces dans les groupes diversifiés comprenant des taxons aux limites d’espèces incomprises.

Phylogenetic inference's algorithms

Phylogenetic inference consist in the search of an evolutionary tree to explain the best way possible genealogical relationships of a set of species. Phylogenetic analysis has a large number of applications in areas such as biology, ecology, paleontology, etc. There are several criterias which has been defined in order to infer phylogenies, among which are the maximum parsimony and maximum likelihood. The first one tries to find the phylogenetic tree that minimizes the number of evolutionary steps needed to describe the evolutionary history among species, while the second tries to find the tree that has the highest probability of produce the observed data according to an evolutionary model. The search of a phylogenetic tree can be formulated as a multi-objective optimization problem, which aims to find trees which satisfy simultaneously (and as much as possible) both criteria of parsimony and likelihood. Due to the fact that these criteria are different there won't be a single optimal solution (a single tree), but a set of compromise solutions. The solutions of this set are called "Pareto Optimal". To find this solutions, evolutionary algorithms are being used with success nowadays.This algorithms are a family of techniques, which aren’t exact, inspired by the process of natural selection. They usually find great quality solutions in order to resolve convoluted optimization problems. The way this algorithms works is based on the handling of a set of trial solutions (trees in the phylogeny case) using operators, some of them exchanges information between solutions, simulating DNA crossing, and others apply aleatory modifications, simulating a mutation. The result of this algorithms is an approximation to the set of the “Pareto Optimal” which can be shown in a graph with in order that the expert in the problem (the biologist when we talk about inference) can choose the solution of the commitment which produces the higher interest. In the case of optimization multi-objective applied to phylogenetic inference, there is open source software tool, called MO-Phylogenetics, which is designed for the purpose of resolving inference problems with classic evolutionary algorithms and last generation algorithms. REFERENCES [1] C.A. Coello Coello, G.B. Lamont, D.A. van Veldhuizen. Evolutionary algorithms for solving multi-objective problems. Spring. Agosto 2007 [2] C. Zambrano-Vega, A.J. Nebro, J.F Aldana-Montes. MO-Phylogenetics: a phylogenetic inference software tool with multi-objective evolutionary metaheuristics. Methods in Ecology and Evolution. En prensa. Febrero 2016.

Dinoflagellate Genomic Organization and Phylogenetic Marker Discovery Utilizing Deep Sequencing Data

Dinoflagellates possess large genomes in which most genes are present in many copies. This has made studies of their genomic organization and phylogenetics challenging. Recent advances in sequencing technology have made deep sequencing of dinoflagellate transcriptomes feasible. This dissertation investigates the genomic organization of dinoflagellates to better understand the challenges of assembling dinoflagellate transcriptomic and genomic data from short read sequencing methods, and develops new techniques that utilize deep sequencing data to identify orthologous genes across a diverse set of taxa. To better understand the genomic organization of dinoflagellates, a genomic cosmid clone of the tandemly repeated gene Alchohol Dehydrogenase (AHD) was sequenced and analyzed. The organization of this clone was found to be counter to prevailing hypotheses of genomic organization in dinoflagellates. Further, a new non-canonical splicing motif was described that could greatly improve the automated modeling and annotation of genomic data. A custom phylogenetic marker discovery pipeline, incorporating methods that leverage the statistical power of large data sets was written. A case study on Stramenopiles was undertaken to test the utility in resolving relationships between known groups as well as the phylogenetic affinity of seven unknown taxa. The pipeline generated a set of 373 genes useful as phylogenetic markers that successfully resolved relationships among the major groups of Stramenopiles, and placed all unknown taxa on the tree with strong bootstrap support. This pipeline was then used to discover 668 genes useful as phylogenetic markers in dinoflagellates. Phylogenetic analysis of 58 dinoflagellates, using this set of markers, produced a phylogeny with good support of all branches. The Suessiales were found to be sister to the Peridinales. The Prorocentrales formed a monophyletic group with the Dinophysiales that was sister to the Gonyaulacales. The Gymnodinales was found to be paraphyletic, forming three monophyletic groups. While this pipeline was used to find phylogenetic markers, it will likely also be useful for finding orthologs of interest for other purposes, for the discovery of horizontally transferred genes, and for the separation of sequences in metagenomic data sets.

Rare HIV-1 subtype J genomes and a new H/U/CRF02_AG recombinant genome suggests an ancient origin of HIV-1 in Angola

This is the author’s version of a work that was accepted for publication in AIDS Research and Human Retroviruses .

Wavelet analysis and hierarchical clustering of ofm phenotypic population's variations originated from southern america and europe and attempts of a first relation to molecular divergence.

In this work we compare Grapholita molesta Busck (Lepidoptera: Tortricidae) populations originated from Brazil, Chile, Spain, Italy and Greece using power spectral density and phylogenetic analysis to detect any similarities between the population macro- and the molecular micro-level. Log-transformed population data were normalized and AR(p) models were developed to generate for each case population time series of equal lengths. The time-frequency/scale properties of the population data were further analyzed using wavelet analysis to detect any population dynamics frequency changes and cluster the populations. Based on the power spectral of each population time series and the hierarchical clustering schemes, populations originated from Southern America (Brazil and Chile) exhibit similar rhythmic properties and are both closer related with populations originated from Greece. Populations from Spain and especially Italy, have higher distance by terms of periodic changes on their population dynamics. Moreover, the members within the same cluster share similar spectral information, therefore they are supposed to participate in the same temporally regulated population process. On the contrary, the phylogenetic approach revealed a less structured pattern that bears indications of panmixia, as the two clusters contain individuals from both Europe and South America. This preliminary outcome will be further assessed by incorporating more individuals and likely employed a second molecular marker.