Clones Identification and Genetic Characterization of Garnacha Grapevine by Means of Different PCR-Derived Marker Systems

This study uses PCR-derived marker systems to investigate the extent and distribution of genetic variability of 53 Garnacha accessions coming from Italy, France and Spain. The samples studied include 28 Italian accessions (named Tocai rosso in Vicenza area; Alicante in Sicily and Elba island; Gamay perugino in Perugia province; Cannonau in Sardinia), 19 Spanish accessions of different types (named Garnacha tinta, Garnacha blanca, Garnacha peluda, Garnacha roja, Garnacha erguida, Garnacha roya) and 6 French accessions (named Grenache and Grenache noir). In order to verify the varietal identity of the samples, analyses based on 14 simple sequence repeat (SSR) loci were performed. The presence of an additional allele at ISV3 locus (151 bp) was found in four Tocai rosso accessions and in a Sardinian Cannonau clone, that are, incidentally, chimeras. In addition to microsatellite analysis, intravarietal variability study was performed using AFLP, SAMPL and M-AFLP molecular markers. AFLPs could discriminate among several Garnacha samples; SAMPLs allowed distinguishing few genotypes on the basis of their geographic origin, whereas M-AFLPs revealed plant-specific markers, differentiating all accessions. Italian samples showed the greatest variability among themselves, especially on the basis of their different provenance, while Spanish samples were the most similar, in spite of their morphological diversity.

Future trends in Animal Breeding due to new genetic tecnologies

The Darwin theory of evolution by natural selection is based on three principles: (a) variation; (b) inheritance; and (c) natural selection. Here, I take these principles as an excuse to review some topics related to the future research prospects in Animal Breeding. With respect to the first principle I describe two forms of variation different from mutation that are becoming increasingly important: variation in copy number and microRNAs. With respect to the second principle I comment on the possible relevance of non-mendelian inheritance, the so-called epigenetic effects, of which the genomic imprinting is the best characterized in domestic species. Regarding selection principle I emphasize the importance of selection for social traits and how this could contribute to both productivity and animal welfare. Finally, I analyse the impact of molecular biology in Animal Breeding, the achievements and limitations of quantitative trait locus and classical marker-assisted selection and the future of genomic selection

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.

Mapping Genetic Diversity of Cherimoya (Annona cherimola Mill.): Application of Spatial Analysis for Conservation and Use of Plant Genetic Resources.

There is a growing call for inventories that evaluate geographic patterns in diversity of plant genetic resources maintained on farm and in species' natural populations in order to enhance their use and conservation. Such evaluations are relevant for useful tropical and subtropical tree species, as many of these species are still undomesticated, or in incipient stages of domestication and local populations can offer yet-unknown traits of high value to further domestication. For many outcrossing species, such as most trees, inbreeding depression can be an issue, and genetic diversity is important to sustain local production. Diversity is also crucial for species to adapt to environmental changes. This paper explores the possibilities of incorporating molecular marker data into Geographic Information Systems (GIS) to allow visualization and better understanding of spatial patterns of genetic diversity as a key input to optimize conservation and use of plant genetic resources, based on a case study of cherimoya (Annona cherimola Mill.), a Neotropical fruit tree species. We present spatial analyses to (1) improve the understanding of spatial distribution of genetic diversity of cherimoya natural stands and cultivated trees in Ecuador, Bolivia and Peru based on microsatellite molecular markers (SSRs); and (2) formulate optimal conservation strategies by revealing priority areas for in situ conservation, and identifying existing diversity gaps in ex situ collections. We found high levels of allelic richness, locally common alleles and expected heterozygosity in cherimoya's putative centre of origin, southern Ecuador and northern Peru, whereas levels of diversity in southern Peru and especially in Bolivia were significantly lower. The application of GIS on a large microsatellite dataset allows a more detailed prioritization of areas for in situ conservation and targeted collection across the Andean distribution range of cherimoya than previous studies could do, i.e. at province and department level in Ecuador and Peru, respectively.

Molecular characterization of Glu-B3 locus in wheat cultivars and segregating populations

Bread wheat quality constitutes a key trait for the demands of the baking industry as well as the broad consumer preferences. The role of the low molecular weight glutenin subunits (LMW-GS) with regard to bread quality is so far not well understood owing to their genetic complexity and to the use of different nomenclatures and standards for the LMW-GS assignment by different research groups, which has made difficult the undertaking of association studies between genotypes and bread quality. The development of molecular markers to carry out genetic characterization and allele determination is demanding. Nowadays, the most promising LMW gene marker system is based on PCR and high resolution capillary electrophoresis for the simultaneous analysis of the complete multigene family. The molecular analysis of the bread wheat Glu-B3 locus in F2 and F4:6 populations expressed the expected one-locus Mendelian segregation pattern, thus validating the suitability of this marker system for the characterization of LMW-GS genes in segregating populations, allowing for the successful undertaking of studies related to bread-making quality. Moreover, the Glu-B3 allele characterization of standard cultivars with the molecular marker system has revealed its potential as a complementary tool for the allelic determination of this complex multigene family.

Artificial analysis of molecular marker loci linked to tree resistance response by an artificial neural network

One of the biggest challenges that software developers face is to make an accurate estimate of the project effort. Radial basis function neural networks have been used to software effort estimation in this work using NASA dataset. This paper evaluates and compares radial basis function versus a regression model. The results show that radial basis function neural network have obtained less Mean Square Error than the regression method.