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).

Estudio molecular de gluteninas de alto y bajo peso molecular en Triticum aestivum ssp. vulgare L. y su relación con la calidad panadera

El trigo blando (Triticum aestivum ssp vulgare L., AABBDD, 2n=6x=42) presenta propiedades viscoélasticas únicas debidas a la presencia en la harina de las prolaminas: gluteninas y gliadinas. Ambos tipos de proteínas forman parte de la red de gluten. Basándose en la movilidad en SDS-PAGE, las gluteninas se clasifican en dos grupos: gluteninas de alto peso molecular (HMW-GS) y gluteninas de bajo peso molecular (LMW-GS). Los genes que codifican para las HMW-GS se encuentran en tres loci del grupo 1 de cromosomas: Glu-A1, Glu-B1 y Glu-D1. Cada locus codifica para uno o dos polipéptidos o subunidades. La variación alélica de las HMW-GS es el principal determinante de de la calidad harino-panadera y ha sido ampliamente estudiado tanto a nivel de proteína como de ADN. El conocimiento de estas proteínas ha contribuido sustancialmente al progreso de los programas de mejora para la calidad del trigo. Comparadas con las HMW-GS, las LMW-GS forman una familia proteica mucho más compleja. La mayoría de los genes LMW se localizan en el grupo 1 de cromosomas en tres loci: Glu-A3, Glu-B3 y Glu-D3 que se encuentran estrechamente ligados a los loci que codifican para gliadinas. El número de copias de estos genes ha sido estimado entre 10-40 en trigo hexaploide, pero el número exacto aún se desconoce debido a la ausencia de un método eficiente para diferenciar los miembros de esta familia multigénica. La nomenclatura de los alelos LMW-GS por electroforesis convencional es complicada, y diferentes autores asignan distintos alelos a la misma variedad lo que dificulta aún más el estudio de esta compleja familia. El uso de marcadores moleculares para la discriminación de genes LMW, aunque es una tarea dificil, puede ser muy útil para los programas de mejora. El objetivo de este trabajo ha sido profundizar en la relación entre las gluteninas y la calidad panadera y desarrollar marcadores moleculares que permitan ayudar en la correcta clasificación de HMW-GS y LMW-GS. Se han obtenido dos poblaciones de líneas avanzadas F4:6 a partir de los cruzamientos entre las variedades ‘Tigre’ x ‘Gazul’ y ‘Fiel’ x ‘Taber’, seleccionándose para los análisis de calidad las líneas homogéneas para HMW-GS, LMW-GS y gliadinas. La determinación alélica de HMW-GS se llevó a cabo por SDS-PAGE, y se complementó con análisis moleculares, desarrollándose un nuevo marcador de PCR para diferenciar entre las subunidades Bx7 y Bx7*del locus Glu-B1. Resumen 2 La determinación alélica para LMW-GS se llevó a cabo mediante SDS-PAGE siguiendo distintas nomenclaturas y utilizando variedades testigo para cada alelo. El resultado no fue concluyente para el locus Glu-B3, así que se recurrió a marcadores moleculares. El ADN de los parentales y de los testigos se amplificó usando cebadores diseñados en regiones conservadas de los genes LMW y fue posteriormente analizado mediante electroforesis capilar. Los patrones de amplificación obtenidos fueron comparados entre las distintas muestras y permitieron establecer una relación con los alelos de LMW-GS. Con este método se pudo aclarar la determinación alélica de este locus para los cuatro parentales La calidad de la harina fue testada mediante porcentaje de contenido en proteína, prueba de sedimentación (SDSS) y alveógrafo de Chopin (parámetros P, L, P/L y W). Los valores fueron analizados en relación a la composición en gluteninas. Las líneas del cruzamiento ‘Fiel’ x ‘Taber’ mostraron una clara influencia del locus Glu-A3 en la variación de los valores de SDSS. Las líneas que llevaban el nuevo alelo Glu-A3b’ presentaron valores significativamente mayores que los de las líneas con el alelo Glu-A3f. En las líneas procedentes del cruzamiento ‘Tigre ’x ‘Gazul’, los loci Glu-B1 y Glu-B3 loci mostraron ambos influencia en los parámetros de calidad. Los resultados indicaron que: para los valores de SDSS y P, las líneas con las HMW-GS Bx7OE+By8 fueron significativamente mejores que las líneas con Bx17+By18; y las líneas que llevaban el alelo Glu-B3ac presentaban valores de P significativamente superiores que las líneas con el alelo Glu-B3ad y significativamente menores para los valores de L . El análisis de los valores de calidad en relación a los fragmentos LMW amplificados, reveló un efecto significativo entre dos fragmentos (2-616 y 2-636) con los valores de P. La presencia del fragmento 2-636 estaba asociada a valores de P mayores. Estos fragmentos fueron clonados y secuenciados, confirmándose que correspondían a genes del locus Glu-B3. El estudio de la secuencia reveló que la diferencia entre ambos se hallaba en algunos SNPs y en una deleción de 21 nucleótidos que en la proteína correspondería a un InDel de un heptapéptido en la región repetida de la proteína. En este trabajo, la utilización de líneas que difieren en el locus Glu-B3 ha permitido el análisis de la influencia de este locus (el peor caracterizado hasta la fecha) en la calidad panadera. Además, se ha validado el uso de marcadores moleculares en la determinación alélica de las LMW-GS y su relación con la calidad panadera. Summary 3 Bread wheat (Triticum aestivum ssp vulgare L., AABBDD, 2n=6x=42) flour has unique dough viscoelastic properties conferred by prolamins: glutenins and gliadins. Both types of proteins are cross-linked to form gluten polymers. On the basis of their mobility in SDS-PAGE, glutenins can be classified in two groups: high molecular weight glutenins (HMW-GS) and low molecular weight glutenins (LMW-GS). Genes encoding HMW-GS are located on group 1 chromosomes in three loci: Glu-A1, Glu-B1 and Glu-D1, each one encoding two polypeptides, named subunits. Allelic variation of HMW-GS is the most important determinant for bread making quality, and has been exhaustively studied at protein and DNA level. The knowledge of these proteins has substantially contributed to genetic improvement of bread quality in breeding programs. Compared to HMW-GS, LMW-GS are a much more complex family. Most genes encoded LMW-GS are located on group 1 chromosomes. Glu-A3, Glu-B3 and Glu-D3 loci are closely linked to the gliadin loci. The total gene copy number has been estimated to vary from 10–40 in hexaploid wheat. However, the exact copy number of LMW-GS genes is still unknown, mostly due to lack of efficient methods to distinguish members of this multigene family. Nomenclature of LMW-GS alleles is also unclear, and different authors can assign different alleles to the same variety increasing confusion in the study of this complex family. The use of molecular markers for the discrimination of LMW-GS genes might be very useful in breeding programs, but their wide application is not easy. The objective of this work is to gain insight into the relationship between glutenins and bread quality, and the developing of molecular markers that help in the allele classification of HMW-GS and LMW-GS. Two populations of advanced lines F4:6 were obtained from the cross ‘Tigre’ x ‘Gazul’ and ‘Fiel’ x ‘Taber’. Lines homogeneous for HMW-GS, LMW-GS and gliadins pattern were selected for quality analysis. The allele classification of HMW-GS was performed by SDS-PAGE, and then complemented by PCR analysis. A new PCR marker was developed to undoubtedly differentiate between two similar subunits from Glu-B1 locus, Bx7 and Bx7*. The allele classification of LMW-GS was initially performed by SDS-PAGE following different established nomenclatures and using standard varieties. The results were not completely concluding for Glu-B3 locus, so a molecular marker system was applied. DNA from parental lines and standard varieties was amplified using primers designed in conserved domains of LMW genes and analyzed by capillary electrophoresis. The pattern of amplification products obtained was compared among samples and related to the protein allele classification. It was possible to establish a correspondence between specific amplification products and almost all LMW alleles analyzed. With this method, the allele classification of the four parental lines was clarified. Flour quality of F4:6 advanced lines were tested by protein content, sedimentation test (SDSS) and alveograph (P, L, P/L and W). The values were analyzed in relation to the lines prolamin composition. In the ‘Fiel’ x ‘Taber’ population, Glu-A3 locus showed an influence in SDSS values. Lines carrying new allele Glu-A3b’, presented a significantly higher SDSS value than lines with Glu-A3f allele. In the ‘Tigre ’x ‘Gazul’ population, the Glu-B1 and Glu-B3 loci also showed an effect in quality parameters, in SDSS, and P and L values. Results indicated that: for SDSS and P, lines with Bx7OE+By8 were significantly better than lines with Bx17+By18; lines carrying Glu-B3ac allele had a significantly higher P values than Glu-B3ad allele values. lines with and lower L The analysis of quality parameters and amplified LMW fragments revealed a significant influence of two peaks (2-616 y 2-636) in P values. The presence of 2-636 peak gave higher P values than 2-616. These fragments had been cloned and sequenced and identified as Glu-B3 genes. The sequence analysis revealed that the molecular difference between them was some SNPs and a small deletion of 21 nucleotides that in the protein would produce an InDel of a heptapeptide in the repetitive region. In this work, the analysis of two crosses with differences in Glu-3 composition has made possible to study the influence of LMG-GS in quality parameters. Specifically, the influence of Glu-B3, the most interesting and less studied loci has been possible. The results have shown that Glu-B3 allele composition influences the alveograph parameter P (tenacity). The existence of different molecular variants of Glu-B3 alleles have been assessed by using a molecular marker method. This work supports the use of molecular approaches in the study of the very complex LMW-GS family, and validates their application in the analysis of advanced recombinant lines for quality studies.

The family of DOF transcription factors in Brachypodium distachyon: BdDof24 in germinating seeds

The DOF (DNA binding with One Finger) transcription factor (TF) family is characterized by a binding domain of 52 amino acid residues that is structured as a Cys2/Cys2 Zn2+ finger that recognizes the common core 5?-T/AAAAG-3? in the promoter regions of their target genes. DOF TFs have been associated with biological processes exclusive to higher plants and their close ancestors (algae, mosses and ferns).

Desarrollo de un modelo de predimensionado de costes de construcción en el proyecto arquitectónico

El objetivo de la presente investigación es el desarrollo de un modelo de cálculo rápido, eficiente y preciso, para la estimación de los costes finales de construcción, en las fases preliminares del proyecto arquitectónico. Se trata de una herramienta a utilizar durante el proceso de elaboración de estudios previos, anteproyecto y proyecto básico, no siendo por tanto preciso para calcular el “predimensionado de costes” disponer de la total definición grafica y literal del proyecto. Se parte de la hipótesis de que en la aplicación práctica del modelo no se producirán desviaciones superiores al 10 % sobre el coste final de la obra proyectada. Para ello se formulan en el modelo de predimensionado cinco niveles de estimación de costes, de menor a mayor definición conceptual y gráfica del proyecto arquitectónico. Los cinco niveles de cálculo son: dos que toman como referencia los valores “exógenos” de venta de las viviendas (promoción inicial y promoción básica) y tres basados en cálculos de costes “endógenos” de la obra proyectada (estudios previos, anteproyecto y proyecto básico). El primer nivel de estimación de carácter “exógeno” (nivel .1), se calcula en base a la valoración de mercado de la promoción inmobiliaria y a su porcentaje de repercusión de suelo sobre el valor de venta de las viviendas. El quinto nivel de valoración, también de carácter “exógeno” (nivel .5), se calcula a partir del contraste entre el valor externo básico de mercado, los costes de construcción y los gastos de promoción estimados de la obra proyectada. Este contraste entre la “repercusión del coste de construcción” y el valor de mercado, supone una innovación respecto a los modelos de predimensionado de costes existentes, como proceso metodológico de verificación y validación extrínseca, de la precisión y validez de las estimaciones resultantes de la aplicación práctica del modelo, que se denomina Pcr.5n (Predimensionado costes de referencia con .5niveles de cálculo según fase de definición proyectual / ideación arquitectónica). Los otros tres niveles de predimensionado de costes de construcción “endógenos”, se estiman mediante cálculos analíticos internos por unidades de obra y cálculos sintéticos por sistemas constructivos y espacios funcionales, lo que se lleva a cabo en las etapas iniciales del proyecto correspondientes a estudios previos (nivel .2), anteproyecto (nivel .3) y proyecto básico (nivel .4). Estos cálculos teóricos internos son finalmente evaluados y validados mediante la aplicación práctica del modelo en obras de edificación residencial, de las que se conocen sus costes reales de liquidación final de obra. Según va evolucionando y se incrementa el nivel de definición y desarrollo del proyecto, desde los estudios previos hasta el proyecto básico, el cálculo se va perfeccionando en su nivel de eficiencia y precisión de la estimación, según la metodología aplicada: [aproximaciones sucesivas en intervalos finitos], siendo la hipótesis básica como anteriormente se ha avanzado, lograr una desviación máxima de una décima parte en el cálculo estimativo del predimensionado del coste real de obra. El cálculo del coste de ejecución material de la obra, se desarrolla en base a parámetros cúbicos funcionales “tridimensionales” del espacio proyectado y parámetros métricos constructivos “bidimensionales” de la envolvente exterior de cubierta/fachada y de la huella del edificio sobre el terreno. Los costes funcionales y constructivos se ponderan en cada fase del proceso de cálculo con sus parámetros “temáticos/específicos” de gestión (Pg), proyecto (Pp) y ejecución (Pe) de la concreta obra presupuestada, para finalmente estimar el coste de construcción por contrata, como resultado de incrementar al coste de ejecución material el porcentaje correspondiente al parámetro temático/especifico de la obra proyectada. El modelo de predimensionado de costes de construcción Pcr.5n, será una herramienta de gran interés y utilidad en el ámbito profesional, para la estimación del coste correspondiente al Proyecto Básico previsto en el marco técnico y legal de aplicación. Según el Anejo I del Código Técnico de la Edificación (CTE), es de obligado cumplimiento que el proyecto básico contenga una “Valoración aproximada de la ejecución material de la obra proyectada por capítulos”, es decir , que el Proyecto Básico ha de contener al menos un “presupuesto aproximado”, por capítulos, oficios ó tecnologías. El referido cálculo aproximado del presupuesto en el Proyecto Básico, necesariamente se ha de realizar mediante la técnica del predimensionado de costes, dado que en esta fase del proyecto arquitectónico aún no se dispone de cálculos de estructura, planos de acondicionamiento e instalaciones, ni de la resolución constructiva de la envolvente, por cuanto no se han desarrollado las especificaciones propias del posterior proyecto de ejecución. Esta estimación aproximada del coste de la obra, es sencilla de calcular mediante la aplicación práctica del modelo desarrollado, y ello tanto para estudiantes como para profesionales del sector de la construcción. Como se contiene y justifica en el presente trabajo, la aplicación práctica del modelo para el cálculo de costes en las fases preliminares del proyecto, es rápida y certera, siendo de sencilla aplicación tanto en vivienda unifamiliar (aisladas y pareadas), como en viviendas colectivas (bloques y manzanas). También, el modelo es de aplicación en el ámbito de la valoración inmobiliaria, tasaciones, análisis de viabilidad económica de promociones inmobiliarias, estimación de costes de obras terminadas y en general, cuando no se dispone del proyecto de ejecución y sea preciso calcular los costes de construcción de las obras proyectadas. Además, el modelo puede ser de aplicación para el chequeo de presupuestos calculados por el método analítico tradicional (estado de mediciones pormenorizadas por sus precios unitarios y costes descompuestos), tanto en obras de iniciativa privada como en obras promovidas por las Administraciones Públicas. Por último, como líneas abiertas a futuras investigaciones, el modelo de “predimensionado costes de referencia 5 niveles de cálculo”, se podría adaptar y aplicar para otros usos y tipologías diferentes a la residencial, como edificios de equipamientos y dotaciones públicas, valoración de edificios históricos, obras de urbanización interior y exterior de parcela, proyectos de parques y jardines, etc….. Estas lineas de investigación suponen trabajos paralelos al aquí desarrollado, y que a modo de avance parcial se recogen en las comunicaciones presentadas en los Congresos internacionales Scieconf/Junio 2013, Rics‐Cobra/Septiembre 2013 y en el IV Congreso nacional de patología en la edificación‐Ucam/Abril 2014. ABSTRACT The aim of this research is to develop a fast, efficient and accurate calculation model to estimate the final costs of construction, during the preliminary stages of the architectural project. It is a tool to be used during the preliminary study process, drafting and basic project. It is not therefore necessary to have the exact, graphic definition of the project in order to be able to calculate the cost‐scaling. It is assumed that no deviation 10% higher than the final cost of the projected work will occur during the implementation. To that purpose five levels of cost estimation are formulated in the scaling model, from a lower to a higher conceptual and graphic definition of the architectural project. The five calculation levels are: two that take as point of reference the ”exogenous” values of house sales (initial development and basic development), and three based on calculation of endogenous costs (preliminary study, drafting and basic project). The first ”exogenous” estimation level (level.1) is calculated over the market valuation of real estate development and the proportion the cost of land has over the value of the houses. The fifth level of valuation, also an ”exogenous” one (level.5) is calculated from the contrast between the basic external market value, the construction costs, and the estimated development costs of the projected work. This contrast between the ”repercussions of construction costs” and the market value is an innovation regarding the existing cost‐scaling models, as a methodological process of extrinsic verification and validation, of the accuracy and validity of the estimations obtained from the implementation of the model, which is called Pcr.5n (reference cost‐scaling with .5calculation levels according to the stage of project definition/ architectural conceptualization) The other three levels of “endogenous” construction cost‐scaling are estimated from internal analytical calculations by project units and synthetic calculations by construction systems and functional spaces. This is performed during the initial stages of the project corresponding to preliminary study process (level.2), drafting (level.3) and basic project (level.4). These theoretical internal calculations are finally evaluated and validated via implementation of the model in residential buildings, whose real costs on final payment of the works are known. As the level of definition and development of the project evolves, from preliminary study to basic project, the calculation improves in its level of efficiency and estimation accuracy, following the applied methodology: [successive approximations at finite intervals]. The basic hypothesis as above has been made, achieving a maximum deviation of one tenth, in the estimated calculation of the true cost of predimensioning work. The cost calculation for material execution of the works is developed from functional “three‐dimensional” cubic parameters for the planned space and constructive “two dimensional” metric parameters for the surface that envelopes around the facade and the building’s footprint on the plot. The functional and building costs are analyzed at every stage of the process of calculation with “thematic/specific” parameters of management (Pg), project (Pp) and execution (Pe) of the estimated work in question, and finally the cost of contractual construction is estimated, as a consequence of increasing the cost of material execution with the percentage pertaining to the thematic/specific parameter of the projected work. The construction cost‐scaling Pcr.5n model will be a useful tool of great interest in the professional field to estimate the cost of the Basic Project as prescribed in the technical and legal framework of application. According to the appendix of the Technical Building Code (CTE), it is compulsory that the basic project contains an “approximate valuation of the material execution of the work, projected by chapters”, that is, that the basic project must contain at least an “approximate estimate” by chapter, trade or technology. This approximate estimate in the Basic Project is to be performed through the cost‐scaling technique, given that structural calculations, reconditioning plans and definitive contruction details of the envelope are still not available at this stage of the architectural project, insofar as specifications pertaining to the later project have not yet been developed. This approximate estimate of the cost of the works is easy to calculate through the implementation of the given model, both for students and professionals of the building sector. As explained and justified in this work, the implementation of the model for cost‐scaling during the preliminary stage is fast and accurate, as well as easy to apply both in single‐family houses (detached and semi‐detached) and collective housing (blocks). The model can also be applied in the field of the real‐estate valuation, official appraisal, analysis of the economic viability of real estate developments, estimate of the cost of finished projects and, generally, when an implementation project is not available and it is necessary to calculate the building costs of the projected works. The model can also be applied to check estimates calculated by the traditional analytical method (state of measurements broken down into price per unit cost details), both in private works and those promoted by Public Authorities. Finally, as potential lines for future research, the “five levels of calculation cost‐scaling model”, could be adapted and applied to purposes and typologies other than the residential one, such as service buildings and public facilities, valuation of historical buildings, interior and exterior development works, park and garden planning, etc… These lines of investigation are parallel to this one and, by way of a preview, can be found in the dissertations given in the International Congresses Scieconf/June 2013, Rics‐Cobra/September 2013 and in the IV Congress on building pathology ‐Ucam/April 2014.

Can small horticulture crops improve family farm incomes in mountains areas of Central America?

Small family farm in mountain areas can found in horticulture one alternative to increase incomes. Horticulture crop required more labour and increased the land intensification. Market of production will be the key factor in the future of this family farms.

Parametric and structural self-adaptation of embedded systems using evolvable hardware

Los sistemas empotrados han sido concebidos tradicionalmente como sistemas de procesamiento específicos que realizan una tarea fija durante toda su vida útil. Para cumplir con requisitos estrictos de coste, tamaño y peso, el equipo de diseño debe optimizar su funcionamiento para condiciones muy específicas. Sin embargo, la demanda de mayor versatilidad, un funcionamiento más inteligente y, en definitiva, una mayor capacidad de procesamiento comenzaron a chocar con estas limitaciones, agravado por la incertidumbre asociada a entornos de operación cada vez más dinámicos donde comenzaban a ser desplegados progresivamente. Esto trajo como resultado una necesidad creciente de que los sistemas pudieran responder por si solos a eventos inesperados en tiempo diseño tales como: cambios en las características de los datos de entrada y el entorno del sistema en general; cambios en la propia plataforma de cómputo, por ejemplo debido a fallos o defectos de fabricación; y cambios en las propias especificaciones funcionales causados por unos objetivos del sistema dinámicos y cambiantes. Como consecuencia, la complejidad del sistema aumenta, pero a cambio se habilita progresivamente una capacidad de adaptación autónoma sin intervención humana a lo largo de la vida útil, permitiendo que tomen sus propias decisiones en tiempo de ejecución. Éstos sistemas se conocen, en general, como sistemas auto-adaptativos y tienen, entre otras características, las de auto-configuración, auto-optimización y auto-reparación. Típicamente, la parte soft de un sistema es mayoritariamente la única utilizada para proporcionar algunas capacidades de adaptación a un sistema. Sin embargo, la proporción rendimiento/potencia en dispositivos software como microprocesadores en muchas ocasiones no es adecuada para sistemas empotrados. En este escenario, el aumento resultante en la complejidad de las aplicaciones está siendo abordado parcialmente mediante un aumento en la complejidad de los dispositivos en forma de multi/many-cores; pero desafortunadamente, esto hace que el consumo de potencia también aumente. Además, la mejora en metodologías de diseño no ha sido acorde como para poder utilizar toda la capacidad de cómputo disponible proporcionada por los núcleos. Por todo ello, no se están satisfaciendo adecuadamente las demandas de cómputo que imponen las nuevas aplicaciones. La solución tradicional para mejorar la proporción rendimiento/potencia ha sido el cambio a unas especificaciones hardware, principalmente usando ASICs. Sin embargo, los costes de un ASIC son altamente prohibitivos excepto en algunos casos de producción en masa y además la naturaleza estática de su estructura complica la solución a las necesidades de adaptación. Los avances en tecnologías de fabricación han hecho que la FPGA, una vez lenta y pequeña, usada como glue logic en sistemas mayores, haya crecido hasta convertirse en un dispositivo de cómputo reconfigurable de gran potencia, con una cantidad enorme de recursos lógicos computacionales y cores hardware empotrados de procesamiento de señal y de propósito general. Sus capacidades de reconfiguración han permitido combinar la flexibilidad propia del software con el rendimiento del procesamiento en hardware, lo que tiene la potencialidad de provocar un cambio de paradigma en arquitectura de computadores, pues el hardware no puede ya ser considerado más como estático. El motivo es que como en el caso de las FPGAs basadas en tecnología SRAM, la reconfiguración parcial dinámica (DPR, Dynamic Partial Reconfiguration) es posible. Esto significa que se puede modificar (reconfigurar) un subconjunto de los recursos computacionales en tiempo de ejecución mientras el resto permanecen activos. Además, este proceso de reconfiguración puede ser ejecutado internamente por el propio dispositivo. El avance tecnológico en dispositivos hardware reconfigurables se encuentra recogido bajo el campo conocido como Computación Reconfigurable (RC, Reconfigurable Computing). Uno de los campos de aplicación más exóticos y menos convencionales que ha posibilitado la computación reconfigurable es el conocido como Hardware Evolutivo (EHW, Evolvable Hardware), en el cual se encuentra enmarcada esta tesis. La idea principal del concepto consiste en convertir hardware que es adaptable a través de reconfiguración en una entidad evolutiva sujeta a las fuerzas de un proceso evolutivo inspirado en el de las especies biológicas naturales, que guía la dirección del cambio. Es una aplicación más del campo de la Computación Evolutiva (EC, Evolutionary Computation), que comprende una serie de algoritmos de optimización global conocidos como Algoritmos Evolutivos (EA, Evolutionary Algorithms), y que son considerados como algoritmos universales de resolución de problemas. En analogía al proceso biológico de la evolución, en el hardware evolutivo el sujeto de la evolución es una población de circuitos que intenta adaptarse a su entorno mediante una adecuación progresiva generación tras generación. Los individuos pasan a ser configuraciones de circuitos en forma de bitstreams caracterizados por descripciones de circuitos reconfigurables. Seleccionando aquellos que se comportan mejor, es decir, que tienen una mejor adecuación (o fitness) después de ser evaluados, y usándolos como padres de la siguiente generación, el algoritmo evolutivo crea una nueva población hija usando operadores genéticos como la mutación y la recombinación. Según se van sucediendo generaciones, se espera que la población en conjunto se aproxime a la solución óptima al problema de encontrar una configuración del circuito adecuada que satisfaga las especificaciones. El estado de la tecnología de reconfiguración después de que la familia de FPGAs XC6200 de Xilinx fuera retirada y reemplazada por las familias Virtex a finales de los 90, supuso un gran obstáculo para el avance en hardware evolutivo; formatos de bitstream cerrados (no conocidos públicamente); dependencia de herramientas del fabricante con soporte limitado de DPR; una velocidad de reconfiguración lenta; y el hecho de que modificaciones aleatorias del bitstream pudieran resultar peligrosas para la integridad del dispositivo, son algunas de estas razones. Sin embargo, una propuesta a principios de los años 2000 permitió mantener la investigación en el campo mientras la tecnología de DPR continuaba madurando, el Circuito Virtual Reconfigurable (VRC, Virtual Reconfigurable Circuit). En esencia, un VRC en una FPGA es una capa virtual que actúa como un circuito reconfigurable de aplicación específica sobre la estructura nativa de la FPGA que reduce la complejidad del proceso reconfiguración y aumenta su velocidad (comparada con la reconfiguración nativa). Es un array de nodos computacionales especificados usando descripciones HDL estándar que define recursos reconfigurables ad-hoc: multiplexores de rutado y un conjunto de elementos de procesamiento configurables, cada uno de los cuales tiene implementadas todas las funciones requeridas, que pueden seleccionarse a través de multiplexores tal y como ocurre en una ALU de un microprocesador. Un registro grande actúa como memoria de configuración, por lo que la reconfiguración del VRC es muy rápida ya que tan sólo implica la escritura de este registro, el cual controla las señales de selección del conjunto de multiplexores. Sin embargo, esta capa virtual provoca: un incremento de área debido a la implementación simultánea de cada función en cada nodo del array más los multiplexores y un aumento del retardo debido a los multiplexores, reduciendo la frecuencia de funcionamiento máxima. La naturaleza del hardware evolutivo, capaz de optimizar su propio comportamiento computacional, le convierten en un buen candidato para avanzar en la investigación sobre sistemas auto-adaptativos. Combinar un sustrato de cómputo auto-reconfigurable capaz de ser modificado dinámicamente en tiempo de ejecución con un algoritmo empotrado que proporcione una dirección de cambio, puede ayudar a satisfacer los requisitos de adaptación autónoma de sistemas empotrados basados en FPGA. La propuesta principal de esta tesis está por tanto dirigida a contribuir a la auto-adaptación del hardware de procesamiento de sistemas empotrados basados en FPGA mediante hardware evolutivo. Esto se ha abordado considerando que el comportamiento computacional de un sistema puede ser modificado cambiando cualquiera de sus dos partes constitutivas: una estructura hard subyacente y un conjunto de parámetros soft. De esta distinción, se derivan dos lineas de trabajo. Por un lado, auto-adaptación paramétrica, y por otro auto-adaptación estructural. El objetivo perseguido en el caso de la auto-adaptación paramétrica es la implementación de técnicas de optimización evolutiva complejas en sistemas empotrados con recursos limitados para la adaptación paramétrica online de circuitos de procesamiento de señal. La aplicación seleccionada como prueba de concepto es la optimización para tipos muy específicos de imágenes de los coeficientes de los filtros de transformadas wavelet discretas (DWT, DiscreteWavelet Transform), orientada a la compresión de imágenes. Por tanto, el objetivo requerido de la evolución es una compresión adaptativa y más eficiente comparada con los procedimientos estándar. El principal reto radica en reducir la necesidad de recursos de supercomputación para el proceso de optimización propuesto en trabajos previos, de modo que se adecúe para la ejecución en sistemas empotrados. En cuanto a la auto-adaptación estructural, el objetivo de la tesis es la implementación de circuitos auto-adaptativos en sistemas evolutivos basados en FPGA mediante un uso eficiente de sus capacidades de reconfiguración nativas. En este caso, la prueba de concepto es la evolución de tareas de procesamiento de imagen tales como el filtrado de tipos desconocidos y cambiantes de ruido y la detección de bordes en la imagen. En general, el objetivo es la evolución en tiempo de ejecución de tareas de procesamiento de imagen desconocidas en tiempo de diseño (dentro de un cierto grado de complejidad). En este caso, el objetivo de la propuesta es la incorporación de DPR en EHW para evolucionar la arquitectura de un array sistólico adaptable mediante reconfiguración cuya capacidad de evolución no había sido estudiada previamente. Para conseguir los dos objetivos mencionados, esta tesis propone originalmente una plataforma evolutiva que integra un motor de adaptación (AE, Adaptation Engine), un motor de reconfiguración (RE, Reconfiguration Engine) y un motor computacional (CE, Computing Engine) adaptable. El el caso de adaptación paramétrica, la plataforma propuesta está caracterizada por: • un CE caracterizado por un núcleo de procesamiento hardware de DWT adaptable mediante registros reconfigurables que contienen los coeficientes de los filtros wavelet • un algoritmo evolutivo como AE que busca filtros wavelet candidatos a través de un proceso de optimización paramétrica desarrollado específicamente para sistemas caracterizados por recursos de procesamiento limitados • un nuevo operador de mutación simplificado para el algoritmo evolutivo utilizado, que junto con un mecanismo de evaluación rápida de filtros wavelet candidatos derivado de la literatura actual, asegura la viabilidad de la búsqueda evolutiva asociada a la adaptación de wavelets. En el caso de adaptación estructural, la plataforma propuesta toma la forma de: • un CE basado en una plantilla de array sistólico reconfigurable de 2 dimensiones compuesto de nodos de procesamiento reconfigurables • un algoritmo evolutivo como AE que busca configuraciones candidatas del array usando un conjunto de funcionalidades de procesamiento para los nodos disponible en una biblioteca accesible en tiempo de ejecución • un RE hardware que explota la capacidad de reconfiguración nativa de las FPGAs haciendo un uso eficiente de los recursos reconfigurables del dispositivo para cambiar el comportamiento del CE en tiempo de ejecución • una biblioteca de elementos de procesamiento reconfigurables caracterizada por bitstreams parciales independientes de la posición, usados como el conjunto de configuraciones disponibles para los nodos de procesamiento del array Las contribuciones principales de esta tesis se pueden resumir en la siguiente lista: • Una plataforma evolutiva basada en FPGA para la auto-adaptación paramétrica y estructural de sistemas empotrados compuesta por un motor computacional (CE), un motor de adaptación (AE) evolutivo y un motor de reconfiguración (RE). Esta plataforma se ha desarrollado y particularizado para los casos de auto-adaptación paramétrica y estructural. • En cuanto a la auto-adaptación paramétrica, las contribuciones principales son: – Un motor computacional adaptable mediante registros que permite la adaptación paramétrica de los coeficientes de una implementación hardware adaptativa de un núcleo de DWT. – Un motor de adaptación basado en un algoritmo evolutivo desarrollado específicamente para optimización numérica, aplicada a los coeficientes de filtros wavelet en sistemas empotrados con recursos limitados. – Un núcleo IP de DWT auto-adaptativo en tiempo de ejecución para sistemas empotrados que permite la optimización online del rendimiento de la transformada para compresión de imágenes en entornos específicos de despliegue, caracterizados por tipos diferentes de señal de entrada. – Un modelo software y una implementación hardware de una herramienta para la construcción evolutiva automática de transformadas wavelet específicas. • Por último, en cuanto a la auto-adaptación estructural, las contribuciones principales son: – Un motor computacional adaptable mediante reconfiguración nativa de FPGAs caracterizado por una plantilla de array sistólico en dos dimensiones de nodos de procesamiento reconfigurables. Es posible mapear diferentes tareas de cómputo en el array usando una biblioteca de elementos sencillos de procesamiento reconfigurables. – Definición de una biblioteca de elementos de procesamiento apropiada para la síntesis autónoma en tiempo de ejecución de diferentes tareas de procesamiento de imagen. – Incorporación eficiente de la reconfiguración parcial dinámica (DPR) en sistemas de hardware evolutivo, superando los principales inconvenientes de propuestas previas como los circuitos reconfigurables virtuales (VRCs). En este trabajo también se comparan originalmente los detalles de implementación de ambas propuestas. – Una plataforma tolerante a fallos, auto-curativa, que permite la recuperación funcional online en entornos peligrosos. La plataforma ha sido caracterizada desde una perspectiva de tolerancia a fallos: se proponen modelos de fallo a nivel de CLB y de elemento de procesamiento, y usando el motor de reconfiguración, se hace un análisis sistemático de fallos para un fallo en cada elemento de procesamiento y para dos fallos acumulados. – Una plataforma con calidad de filtrado dinámica que permite la adaptación online a tipos de ruido diferentes y diferentes comportamientos computacionales teniendo en cuenta los recursos de procesamiento disponibles. Por un lado, se evolucionan filtros con comportamientos no destructivos, que permiten esquemas de filtrado en cascada escalables; y por otro, también se evolucionan filtros escalables teniendo en cuenta requisitos computacionales de filtrado cambiantes dinámicamente. Este documento está organizado en cuatro partes y nueve capítulos. La primera parte contiene el capítulo 1, una introducción y motivación sobre este trabajo de tesis. A continuación, el marco de referencia en el que se enmarca esta tesis se analiza en la segunda parte: el capítulo 2 contiene una introducción a los conceptos de auto-adaptación y computación autonómica (autonomic computing) como un campo de investigación más general que el muy específico de este trabajo; el capítulo 3 introduce la computación evolutiva como la técnica para dirigir la adaptación; el capítulo 4 analiza las plataformas de computación reconfigurables como la tecnología para albergar hardware auto-adaptativo; y finalmente, el capítulo 5 define, clasifica y hace un sondeo del campo del hardware evolutivo. Seguidamente, la tercera parte de este trabajo contiene la propuesta, desarrollo y resultados obtenidos: mientras que el capítulo 6 contiene una declaración de los objetivos de la tesis y la descripción de la propuesta en su conjunto, los capítulos 7 y 8 abordan la auto-adaptación paramétrica y estructural, respectivamente. Finalmente, el capítulo 9 de la parte 4 concluye el trabajo y describe caminos de investigación futuros. ABSTRACT Embedded systems have traditionally been conceived to be specific-purpose computers with one, fixed computational task for their whole lifetime. Stringent requirements in terms of cost, size and weight forced designers to highly optimise their operation for very specific conditions. However, demands for versatility, more intelligent behaviour and, in summary, an increased computing capability began to clash with these limitations, intensified by the uncertainty associated to the more dynamic operating environments where they were progressively being deployed. This brought as a result an increasing need for systems to respond by themselves to unexpected events at design time, such as: changes in input data characteristics and system environment in general; changes in the computing platform itself, e.g., due to faults and fabrication defects; and changes in functional specifications caused by dynamically changing system objectives. As a consequence, systems complexity is increasing, but in turn, autonomous lifetime adaptation without human intervention is being progressively enabled, allowing them to take their own decisions at run-time. This type of systems is known, in general, as selfadaptive, and are able, among others, of self-configuration, self-optimisation and self-repair. Traditionally, the soft part of a system has mostly been so far the only place to provide systems with some degree of adaptation capabilities. However, the performance to power ratios of software driven devices like microprocessors are not adequate for embedded systems in many situations. In this scenario, the resulting rise in applications complexity is being partly addressed by rising devices complexity in the form of multi and many core devices; but sadly, this keeps on increasing power consumption. Besides, design methodologies have not been improved accordingly to completely leverage the available computational power from all these cores. Altogether, these factors make that the computing demands new applications pose are not being wholly satisfied. The traditional solution to improve performance to power ratios has been the switch to hardware driven specifications, mainly using ASICs. However, their costs are highly prohibitive except for some mass production cases and besidesthe static nature of its structure complicates the solution to the adaptation needs. The advancements in fabrication technologies have made that the once slow, small FPGA used as glue logic in bigger systems, had grown to be a very powerful, reconfigurable computing device with a vast amount of computational logic resources and embedded, hardened signal and general purpose processing cores. Its reconfiguration capabilities have enabled software-like flexibility to be combined with hardware-like computing performance, which has the potential to cause a paradigm shift in computer architecture since hardware cannot be considered as static anymore. This is so, since, as is the case with SRAMbased FPGAs, Dynamic Partial Reconfiguration (DPR) is possible. This means that subsets of the FPGA computational resources can now be changed (reconfigured) at run-time while the rest remains active. Besides, this reconfiguration process can be triggered internally by the device itself. This technological boost in reconfigurable hardware devices is actually covered under the field known as Reconfigurable Computing. One of the most exotic fields of application that Reconfigurable Computing has enabled is the known as Evolvable Hardware (EHW), in which this dissertation is framed. The main idea behind the concept is turning hardware that is adaptable through reconfiguration into an evolvable entity subject to the forces of an evolutionary process, inspired by that of natural, biological species, that guides the direction of change. It is yet another application of the field of Evolutionary Computation (EC), which comprises a set of global optimisation algorithms known as Evolutionary Algorithms (EAs), considered as universal problem solvers. In analogy to the biological process of evolution, in EHW the subject of evolution is a population of circuits that tries to get adapted to its surrounding environment by progressively getting better fitted to it generation after generation. Individuals become circuit configurations representing bitstreams that feature reconfigurable circuit descriptions. By selecting those that behave better, i.e., with a higher fitness value after being evaluated, and using them as parents of the following generation, the EA creates a new offspring population by using so called genetic operators like mutation and recombination. As generations succeed one another, the whole population is expected to approach to the optimum solution to the problem of finding an adequate circuit configuration that fulfils system objectives. The state of reconfiguration technology after Xilinx XC6200 FPGA family was discontinued and replaced by Virtex families in the late 90s, was a major obstacle for advancements in EHW; closed (non publicly known) bitstream formats; dependence on manufacturer tools with highly limiting support of DPR; slow speed of reconfiguration; and random bitstream modifications being potentially hazardous for device integrity, are some of these reasons. However, a proposal in the first 2000s allowed to keep investigating in this field while DPR technology kept maturing, the Virtual Reconfigurable Circuit (VRC). In essence, a VRC in an FPGA is a virtual layer acting as an application specific reconfigurable circuit on top of an FPGA fabric that reduces the complexity of the reconfiguration process and increases its speed (compared to native reconfiguration). It is an array of computational nodes specified using standard HDL descriptions that define ad-hoc reconfigurable resources; routing multiplexers and a set of configurable processing elements, each one containing all the required functions, which are selectable through functionality multiplexers as in microprocessor ALUs. A large register acts as configuration memory, so VRC reconfiguration is very fast given it only involves writing this register, which drives the selection signals of the set of multiplexers. However, large overheads are introduced by this virtual layer; an area overhead due to the simultaneous implementation of every function in every node of the array plus the multiplexers, and a delay overhead due to the multiplexers, which also reduces maximum frequency of operation. The very nature of Evolvable Hardware, able to optimise its own computational behaviour, makes it a good candidate to advance research in self-adaptive systems. Combining a selfreconfigurable computing substrate able to be dynamically changed at run-time with an embedded algorithm that provides a direction for change, can help fulfilling requirements for autonomous lifetime adaptation of FPGA-based embedded systems. The main proposal of this thesis is hence directed to contribute to autonomous self-adaptation of the underlying computational hardware of FPGA-based embedded systems by means of Evolvable Hardware. This is tackled by considering that the computational behaviour of a system can be modified by changing any of its two constituent parts: an underlying hard structure and a set of soft parameters. Two main lines of work derive from this distinction. On one side, parametric self-adaptation and, on the other side, structural self-adaptation. The goal pursued in the case of parametric self-adaptation is the implementation of complex evolutionary optimisation techniques in resource constrained embedded systems for online parameter adaptation of signal processing circuits. The application selected as proof of concept is the optimisation of Discrete Wavelet Transforms (DWT) filters coefficients for very specific types of images, oriented to image compression. Hence, adaptive and improved compression efficiency, as compared to standard techniques, is the required goal of evolution. The main quest lies in reducing the supercomputing resources reported in previous works for the optimisation process in order to make it suitable for embedded systems. Regarding structural self-adaptation, the thesis goal is the implementation of self-adaptive circuits in FPGA-based evolvable systems through an efficient use of native reconfiguration capabilities. In this case, evolution of image processing tasks such as filtering of unknown and changing types of noise and edge detection are the selected proofs of concept. In general, evolving unknown image processing behaviours (within a certain complexity range) at design time is the required goal. In this case, the mission of the proposal is the incorporation of DPR in EHW to evolve a systolic array architecture adaptable through reconfiguration whose evolvability had not been previously checked. In order to achieve the two stated goals, this thesis originally proposes an evolvable platform that integrates an Adaptation Engine (AE), a Reconfiguration Engine (RE) and an adaptable Computing Engine (CE). In the case of parametric adaptation, the proposed platform is characterised by: • a CE featuring a DWT hardware processing core adaptable through reconfigurable registers that holds wavelet filters coefficients • an evolutionary algorithm as AE that searches for candidate wavelet filters through a parametric optimisation process specifically developed for systems featured by scarce computing resources • a new, simplified mutation operator for the selected EA, that together with a fast evaluation mechanism of candidate wavelet filters derived from existing literature, assures the feasibility of the evolutionary search involved in wavelets adaptation In the case of structural adaptation, the platform proposal takes the form of: • a CE based on a reconfigurable 2D systolic array template composed of reconfigurable processing nodes • an evolutionary algorithm as AE that searches for candidate configurations of the array using a set of computational functionalities for the nodes available in a run time accessible library • a hardware RE that exploits native DPR capabilities of FPGAs and makes an efficient use of the available reconfigurable resources of the device to change the behaviour of the CE at run time • a library of reconfigurable processing elements featured by position-independent partial bitstreams used as the set of available configurations for the processing nodes of the array Main contributions of this thesis can be summarised in the following list. • An FPGA-based evolvable platform for parametric and structural self-adaptation of embedded systems composed of a Computing Engine, an evolutionary Adaptation Engine and a Reconfiguration Engine. This platform is further developed and tailored for both parametric and structural self-adaptation. • Regarding parametric self-adaptation, main contributions are: – A CE adaptable through reconfigurable registers that enables parametric adaptation of the coefficients of an adaptive hardware implementation of a DWT core. – An AE based on an Evolutionary Algorithm specifically developed for numerical optimisation applied to wavelet filter coefficients in resource constrained embedded systems. – A run-time self-adaptive DWT IP core for embedded systems that allows for online optimisation of transform performance for image compression for specific deployment environments characterised by different types of input signals. – A software model and hardware implementation of a tool for the automatic, evolutionary construction of custom wavelet transforms. • Lastly, regarding structural self-adaptation, main contributions are: – A CE adaptable through native FPGA fabric reconfiguration featured by a two dimensional systolic array template of reconfigurable processing nodes. Different processing behaviours can be automatically mapped in the array by using a library of simple reconfigurable processing elements. – Definition of a library of such processing elements suited for autonomous runtime synthesis of different image processing tasks. – Efficient incorporation of DPR in EHW systems, overcoming main drawbacks from the previous approach of virtual reconfigurable circuits. Implementation details for both approaches are also originally compared in this work. – A fault tolerant, self-healing platform that enables online functional recovery in hazardous environments. The platform has been characterised from a fault tolerance perspective: fault models at FPGA CLB level and processing elements level are proposed, and using the RE, a systematic fault analysis for one fault in every processing element and for two accumulated faults is done. – A dynamic filtering quality platform that permits on-line adaptation to different types of noise and different computing behaviours considering the available computing resources. On one side, non-destructive filters are evolved, enabling scalable cascaded filtering schemes; and on the other, size-scalable filters are also evolved considering dynamically changing computational filtering requirements. This dissertation is organized in four parts and nine chapters. First part contains chapter 1, the introduction to and motivation of this PhD work. Following, the reference framework in which this dissertation is framed is analysed in the second part: chapter 2 features an introduction to the notions of self-adaptation and autonomic computing as a more general research field to the very specific one of this work; chapter 3 introduces evolutionary computation as the technique to drive adaptation; chapter 4 analyses platforms for reconfigurable computing as the technology to hold self-adaptive hardware; and finally chapter 5 defines, classifies and surveys the field of Evolvable Hardware. Third part of the work follows, which contains the proposal, development and results obtained: while chapter 6 contains an statement of the thesis goals and the description of the proposal as a whole, chapters 7 and 8 address parametric and structural self-adaptation, respectively. Finally, chapter 9 in part 4 concludes the work and describes future research paths.

A third member of the synapsin gene family

Synapsins are a family of neuron-specific synaptic vesicle-associated phosphoproteins that have been implicated in synaptogenesis and in the modulation of neurotransmitter release. In mammals, distinct genes for synapsins I and II have been identified, each of which gives rise to two alternatively spliced isoforms. We have now cloned and characterized a third member of the synapsin gene family, synapsin III, from human DNA. Synapsin III gives rise to at least one protein isoform, designated synapsin IIIa, in several mammalian species. Synapsin IIIa is associated with synaptic vesicles, and its expression appears to be neuron-specific. The primary structure of synapsin IIIa conforms to the domain model previously described for the synapsin family, with domains A, C, and E exhibiting the highest degree of conservation. Synapsin IIIa contains a novel domain, termed domain J, located between domains C and E. The similarities among synapsins I, II, and III in domain organization, neuron-specific expression, and subcellular localization suggest a possible role for synapsin III in the regulation of neurotransmitter release and synaptogenesis. The human synapsin III gene is located on chromosome 22q12–13, which has been identified as a possible schizophrenia susceptibility locus. On the basis of this localization and the well established neurobiological roles of the synapsins, synapsin III represents a candidate gene for schizophrenia.

A member of the Ran-binding protein family, Yrb2p, is involved in nuclear protein export

Yeast cells mutated in YRB2, which encodes a nuclear protein with similarity to other Ran-binding proteins, fail to export nuclear export signal (NES)-containing proteins including HIV Rev out of the nucleus. Unlike Xpo1p/Crm1p/exportin, an NES receptor, Yrb2p does not shuttle between the nucleus and the cytoplasm but instead remains inside the nucleus. However, by both biochemical and genetic criteria, Yrb2p interacts with Xpo1p and not with other members of the importin/karyopherin β superfamily. Moreover, the Yrb2p region containing nucleoporin-like FG repeats is important for NES-mediated protein export. Taken together, these data suggest that Yrb2p acts inside the nucleus to mediate the action of Xpo1p in at least one of several nuclear export pathways.

Identification and characterization of a conserved family of protein serine/threonine phosphatases homologous to Drosophila retinal degeneration C (rdgC)

The Drosophila retinal degeneration C (rdgC) gene encodes an unusual protein serine/threonine phosphatase in that it contains at least two EF-hand motifs at its carboxy terminus. By a combination of large-scale sequencing of human retina cDNA clones and searches of expressed sequence tag and genomic DNA databases, we have identified two sequences in mammals [Protein Phosphatase with EF-hands-1 and 2 (PPEF-1 and PPEF-2)] and one in Caenorhabditis elegans (PPEF) that closely resemble rdgC. In the adult, PPEF-2 is expressed specifically in retinal rod photoreceptors and the pineal. In the retina, several isoforms of PPEF-2 are predicted to arise from differential splicing. The isoform that most closely resembles rdgC is localized to rod inner segments. Together with the recently described localization of PPEF-1 transcripts to primary somatosensory neurons and inner ear cells in the developing mouse, these data suggest that the PPEF family of protein serine/threonine phosphatases plays a specific and conserved role in diverse sensory neurons.

The role of alternative mRNA splicing in generating heterogeneity within the Anopheles gambiae class I glutathione S-transferase family

The class I glutathione S-transferases (GSTs) of Anopheles gambiae are encoded by a complex gene family. We describe the genomic organization of three members of this family, which are sequentially arranged on the chromosome in divergent orientations. One of these genes, aggst1-2, is intronless and has been described. In contrast, the two A. gambiae GST genes (aggst1α and aggst1β) reported within are interrupted by introns. The gene aggst1α contains five coding exons that are alternatively spliced to produce four mature GST transcripts, each of which contains a common 5′ exon encoding the N termini of the GST protein spliced to one of four distinct 3′ exons encoding the carboxyl termini. All four of the alternative transcripts of aggst1α are expressed in A. gambiae larvae, pupae, and adults. We report on the involvement of alternative RNA splicing in generating multiple functional GST transcripts. A cDNA from the aggst1β gene was detected in adult mosquitoes, demonstrating that this GST gene is actively transcribed. The percentage similarity of the six cDNAs transcribed from the three GST genes range from 49.5% to 83.1% at the nucleotide level.

Social transmission of reproductive behavior increases frequency of inherited disorders in a young-expanding population

The observation of high frequencies of certain inherited disorders in the population of Saguenay–Lac Saint Jean can be explained in terms of the variance and the correlation of effective family size (EFS) from one generation to the next. We have shown this effect by using the branching process approach with real demographic data. When variance of EFS is included in the model, despite its profound effect on mutant allele frequency, any mutant introduced in the population never reaches the known carrier frequencies (between 0.035 and 0.05). It is only when the EFS correlation between generations is introduced into the model that we can explain the rise of the mutant alleles. This correlation is described by a c parameter that reflects the dependency of children’s EFS on their parents’ EFS. The c parameter can be considered to reflect social transmission of demographic behavior. We show that such social transmission dramatically reduces the effective population size. This could explain particular distributions in allele frequencies and unusually high frequency of certain inherited disorders in some human populations.

p53CP, a putative p53 competing protein that specifically binds to the consensus p53 DNA binding sites: A third member of the p53 family?

p53 tumor suppressor protein negatively regulates cell growth, mainly through the transactivation of its downstream target genes. As a sequence-specific DNA binding transcription factor, p53 specifically binds to a 20-bp consensus motif 5′-PuPuPuC(A/T) (T/A)GPyPyPyPuPuPuC(A/T)(T/A)GPyPyPy-3′. We have now identified, partially purified, and characterized an additional ≈40-kDa nuclear protein, p53CP (p53 competing protein), that specifically binds to the consensus p53 binding sites found in several p53 downstream target genes, including Waf-1, Gadd45, Mdm2, Bax, and RGC. The minimal sequence requirement for binding is a 14-bp motif, 5′-CTTGCTTGAACAGG-3′ [5′-C(A/T)(T/A)GPyPyPyPuPuPuC(A/T)(T/A)G-3′], which includes the central nucleotides of the typical p53 binding site with one mismatch. p53CP and p53 (complexed with antibody) showed a similar binding specificity to Waf-1 site but differences in Gadd45 and T3SF binding. Like p53, p53CP also binds both double- and single-stranded DNA oligonucleotides. Important to note, cell cycle blockers and DNA damaging reagents, which induce p53 binding activity, were found to inhibit p53CP binding in p53-positive, but not in p53-negative, cells. This finding suggested a p53-dependent coordinate regulation of p53 and p53CP in response to external stimuli. p53CP therefore could be a third member of the p53 family, in addition to p53 and p73, a newly identified p53 homolog. p53CP, if sequestering p53 from its DNA binding sites through competitive binding, may provide a novel mechanism of p53 inactivation. Alternatively, p53CP may have p53-like functions by binding and transactivating p53 downstream target genes. Cloning of the p53CP gene ultimately will resolve this issue.

GERp95, a Membrane-associated Protein that Belongs to a Family of Proteins Involved in Stem Cell Differentiation

A panel of mAbs was elicited against intracellular membrane fractions from rat pancreas. One of the antibodies reacted with a 95-kDa protein that localizes primarily to the Golgi complex or the endoplasmic reticulum (ER), depending on cell type. The corresponding cDNA was cloned and sequenced and found to encode a protein of 97.6 kDa that we call GERp95 (Golgi ER protein 95 kDa). The protein copurifies with intracellular membranes but does not contain hydrophobic regions that could function as signal peptides or transmembrane domains. Biochemical analysis suggests that GERp95 is a cytoplasmically exposed peripheral membrane protein that exists in a protease-resistant complex. GERp95 belongs to a family of highly conserved proteins in metazoans and Schizosaccharomyces pombe. It has recently been determined that plant and Drosophila homologues of GERp95 are important for controlling the differentiation of stem cells (Bohmert et al., 1998; Cox et al., 1998; Moussian et al., 1998). In Caenorhabditis elegans, there are at least 20 members of this protein family. To this end, we have used RNA interference to show that the GERp95 orthologue in C. elegans is important for maturation of germ-line stem cells in the gonad. GERp95 and related proteins are an emerging new family of proteins that have important roles in metazoan development. The present study suggests that these proteins may exert their effects on cell differentiation from the level of intracellular membranes.

The Malthusian parameter of ascents: What prevents the exponential increase of one’s ancestors?

The reason that the indefinite exponential increase in the number of one’s ancestors does not take place is found in the law of sibling interference, which can be expressed by the following simple equation:\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} \begin{equation*}\begin{matrix}{\mathit{N}}_{{\mathit{n}}} \enskip & \\ {\mathit{{\blacksquare}}} \enskip & \\ {\mathit{ASZ}} \enskip & \end{matrix} {\mathrm{\hspace{.167em}{\times}\hspace{.167em}2\hspace{.167em}=\hspace{.167em}}}{\mathit{N_{n+1},}}\end{equation*}\end{document} where Nn is the number of ancestors in the nth generation, ASZ is the average sibling size of these ancestors, and Nn+1 is the number of ancestors in the next older generation (n + 1). Accordingly, the exponential increase in the number of one’s ancestors is an initial anomaly that occurs while ASZ remains at 1. Once ASZ begins to exceed 1, the rate of increase in the number of ancestors is progressively curtailed, falling further and further behind the exponential increase rate. Eventually, ASZ reaches 2, and at that point, the number of ancestors stops increasing for two generations. These two generations, named AN SA and AN SA + 1, are the most critical in the ancestry, for one’s ancestors at that point come to represent all the progeny-produced adults of the entire ancestral population. Thereafter, the fate of one’s ancestors becomes the fate of the entire population. If the population to which one belongs is a successful, slowly expanding one, the number of ancestors would slowly decline as you move toward the remote past. This is because ABZ would exceed 2. Only when ABZ is less than 2 would the number of ancestors increase beyond the AN SA and AN SA + 1 generations. Since the above is an indication of a failing population on the way to extinction, there had to be the previous AN SA involving a far greater number of individuals for such a population. Simulations indicated that for a member of a continuously successful population, the AN SA ancestors might have numbered as many as 5.2 million, the AN SA generation being the 28th generation in the past. However, because of the law of increasingly irrelevant remote ancestors, only a very small fraction of the AN SA ancestors would have left genetic traces in the genome of each descendant of today.

A novel member of the RING finger family, KRIP-1, associates with the KRAB-A transcriptional repressor domain of zinc finger proteins

The Krüppel-associated box A (KRAB-A) domain is an evolutionarily conserved transcriptional repressor domain present in approximately one-third of zinc finger proteins of the Cys2-His2 type. Using the yeast two-hybrid system, we report the isolation of a cDNA encoding a novel murine protein, KRAB-A interacting protein 1 (KRIP-1) that physically interacts with the KRAB-A region. KRIP-1 is a member of the RBCC subfamily of the RING finger, or Cys3HisCys4, family of zinc binding proteins whose other members are known to play important roles in differentiation, oncogenesis, and signal transduction. The KRIP-1 protein has high homology to TIF1, a putative modulator of ligand-dependent activation function of nuclear receptors. A 3.5-kb mRNA for KRIP-1 is ubiquitously expressed among all adult mouse tissues studied. When a GAL4–KRIP-1 fusion protein is expressed in COS cells with a chloramphenicol acetyltransferase reporter construct with five GAL4 binding sites, there is dose-dependent repression of transcription. Thus, KRIP-1 interacts with the KRAB-A region of C2H2 zinc finger proteins and may mediate or modulate KRAB-A transcriptional repressor activity.