The family of DOF transcription factors in Brachypodium distachyon: phylogenetic comparison with rice and barley DOFs and expression profiling

ABSTRACT: Transcription factors (TFs) are proteins that have played a central role both in evolution and in domestication, and are major regulators of development in living organisms. Plant genome sequences reveal that approximately 7% of all genes encode putative TFs. The DOF (DNA binding with One Finger) TF family has been associated with vital processes exclusive to higher plants and to their close ancestors (algae, mosses and ferns). These are seed maturation and germination, light-mediated regulation, phytohormone and plant responses to biotic and abiotic stresses, etc. In Hordeum vulgare and Oryza sativa, 26 and 30 different Dof genes, respectively, have been annotated. Brachypodium distachyon has been the first Pooideae grass to be sequenced and, due to its genomic, morphological and physiological characteristics, has emerged as the model system for temperate cereals, such as wheat and barley. RESULTS: Through searches in the B. distachyon genome, 27 Dof genes have been identified and a phylogenetic comparison with the Oryza sativa and the Hordeum vulgare DOFs has been performed. To explore the evolutionary relationship among these DOF proteins, a combined phylogenetic tree has been constructed with the Brachypodium DOFs and those from rice and barley. This phylogenetic analysis has classified the DOF proteins into four Major Cluster of Orthologous Groups (MCOGs). Using RT-qPCR analysis the expression profiles of the annotated BdDof genes across four organs (leaves, roots, spikes and seeds) has been investigated. These results have led to a classification of the BdDof genes into two groups, according to their expression levels. The genes highly or preferentially expressed in seeds have been subjected to a more detailed expression analysis (maturation, dry stage and germination). CONCLUSIONS: Comparison of the expression profiles of the Brachypodium Dof genes with the published functions of closely related DOF sequences from the cereal species considered here, deduced from the phylogenetic analysis, indicates that although the expression profile has been conserved in many of the putative orthologs, in some cases duplication followed by subsequent divergence may have occurred (neo-functionalization).

Methods and Techniques for the Generation and Eficient Exploitation of RDB2RDF Mappings

RDB to RDF Mapping Language (R2RML) es una recomendación del W3C que permite especificar reglas para transformar bases de datos relacionales a RDF. Estos datos en RDF se pueden materializar y almacenar en un sistema gestor de tripletas RDF (normalmente conocidos con el nombre triple store), en el cual se pueden evaluar consultas SPARQL. Sin embargo, hay casos en los cuales la materialización no es adecuada o posible, por ejemplo, cuando la base de datos se actualiza frecuentemente. En estos casos, lo mejor es considerar los datos en RDF como datos virtuales, de tal manera que las consultas SPARQL anteriormente mencionadas se traduzcan a consultas SQL que se pueden evaluar sobre los sistemas gestores de bases de datos relacionales (SGBD) originales. Para esta traducción se tienen en cuenta los mapeos R2RML. La primera parte de esta tesis se centra en la traducción de consultas. Se propone una formalización de la traducción de SPARQL a SQL utilizando mapeos R2RML. Además se proponen varias técnicas de optimización para generar consultas SQL que son más eficientes cuando son evaluadas en sistemas gestores de bases de datos relacionales. Este enfoque se evalúa mediante un benchmark sintético y varios casos reales. Otra recomendación relacionada con R2RML es la conocida como Direct Mapping (DM), que establece reglas fijas para la transformación de datos relacionales a RDF. A pesar de que ambas recomendaciones se publicaron al mismo tiempo, en septiembre de 2012, todavía no se ha realizado un estudio formal sobre la relación entre ellas. Por tanto, la segunda parte de esta tesis se centra en el estudio de la relación entre R2RML y DM. Se divide este estudio en dos partes: de R2RML a DM, y de DM a R2RML. En el primer caso, se estudia un fragmento de R2RML que tiene la misma expresividad que DM. En el segundo caso, se representan las reglas de DM como mapeos R2RML, y también se añade la semántica implícita (relaciones de subclase, 1-N y M-N) que se puede encontrar codificada en la base de datos. Esta tesis muestra que es posible usar R2RML en casos reales, sin necesidad de realizar materializaciones de los datos, puesto que las consultas SQL generadas son suficientemente eficientes cuando son evaluadas en el sistema gestor de base de datos relacional. Asimismo, esta tesis profundiza en el entendimiento de la relación existente entre las dos recomendaciones del W3C, algo que no había sido estudiado con anterioridad. ABSTRACT. RDB to RDF Mapping Language (R2RML) is a W3C recommendation that allows specifying rules for transforming relational databases into RDF. This RDF data can be materialized and stored in a triple store, so that SPARQL queries can be evaluated by the triple store. However, there are several cases where materialization is not adequate or possible, for example, if the underlying relational database is updated frequently. In those cases, RDF data is better kept virtual, and hence SPARQL queries over it have to be translated into SQL queries to the underlying relational database system considering that the translation process has to take into account the specified R2RML mappings. The first part of this thesis focuses on query translation. We discuss the formalization of the translation from SPARQL to SQL queries that takes into account R2RML mappings. Furthermore, we propose several optimization techniques so that the translation procedure generates SQL queries that can be evaluated more efficiently over the underlying databases. We evaluate our approach using a synthetic benchmark and several real cases, and show positive results that we obtained. Direct Mapping (DM) is another W3C recommendation for the generation of RDF data from relational databases. While R2RML allows users to specify their own transformation rules, DM establishes fixed transformation rules. Although both recommendations were published at the same time, September 2012, there has not been any study regarding the relationship between them. The second part of this thesis focuses on the study of the relationship between R2RML and DM. We divide this study into two directions: from R2RML to DM, and from DM to R2RML. From R2RML to DM, we study a fragment of R2RML having the same expressive power than DM. From DM to R2RML, we represent DM transformation rules as R2RML mappings, and also add the implicit semantics encoded in databases, such as subclass, 1-N and N-N relationships. This thesis shows that by formalizing and optimizing R2RML-based SPARQL to SQL query translation, it is possible to use R2RML engines in real cases as the resulting SQL is efficient enough to be evaluated by the underlying relational databases. In addition to that, this thesis facilitates the understanding of bidirectional relationship between the two W3C recommendations, something that had not been studied before.