18 resultados para gene location

em Consorci de Serveis Universitaris de Catalunya (CSUC), Spain


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Background: Despite its pervasiveness, the genetic basis of adaptation resulting in variation directly or indirectly related to temperature (climatic) gradients is poorly understood. By using 3-fold replicated laboratory thermal stocks covering much of the physiologically tolerable temperature range for the temperate (i.e., cold tolerant) species Drosophila subobscura we have assessed whole-genome transcriptional responses after three years of thermal adaptation, when the populations had already diverged for inversion frequencies, pre-adult life history components, and morphological traits. Total mRNA from each population was compared to a reference pool mRNA in a standard, highly replicated two-colour competitive hybridization experiment using cDNA microarrays.Results: A total of 306 (6.6%) cDNA clones were identified as 'differentially expressed' (following a false discovery rate correction) after contrasting the two furthest apart thermal selection regimes (i.e., 13°C vs . 22°C), also including four previously reported candidate genes for thermotolerance in Drosophila (Hsp26, Hsp68, Fst, and Treh). On the other hand, correlated patterns of gene expression were similar in cold- and warm-adapted populations. Analysis of functional categories defined by the Gene Ontology project point to an overrepresentation of genes involved in carbohydrate metabolism, nucleic acids metabolism and regulation of transcription among other categories. Although the location of differently expressed genes was approximately at random with respect to chromosomes, a physical mapping of 88 probes to the polytene chromosomes of D. subobscura has shown that a larger than expected number mapped inside inverted chromosomal segments.Conclusion: Our data suggest that a sizeable number of genes appear to be involved in thermal adaptation in Drosophila, with a substantial fraction implicated in metabolism. This apparently illustrates the formidable challenge to understanding the adaptive evolution of complex trait variation. Furthermore, some clustering of genes within inverted chromosomal sections was detected. Disentangling the effects of inversions will be obviously required in any future approach if we want to identify the relevant candidate genes.

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Background: The arrangement of regulatory motifs in gene promoters, or promoterarchitecture, is the result of mutation and selection processes that have operated over manymillions of years. In mammals, tissue-specific transcriptional regulation is related to the presence ofspecific protein-interacting DNA motifs in gene promoters. However, little is known about therelative location and spacing of these motifs. To fill this gap, we have performed a systematic searchfor motifs that show significant bias at specific promoter locations in a large collection ofhousekeeping and tissue-specific genes.Results: We observe that promoters driving housekeeping gene expression are enriched inparticular motifs with strong positional bias, such as YY1, which are of little relevance in promotersdriving tissue-specific expression. We also identify a large number of motifs that show positionalbias in genes expressed in a highly tissue-specific manner. They include well-known tissue-specificmotifs, such as HNF1 and HNF4 motifs in liver, kidney and small intestine, or RFX motifs in testis,as well as many potentially novel regulatory motifs. Based on this analysis, we provide predictionsfor 559 tissue-specific motifs in mouse gene promoters.Conclusion: The study shows that motif positional bias is an important feature of mammalianproximal promoters and that it affects both general and tissue-specific motifs. Motif positionalconstraints define very distinct promoter architectures depending on breadth of expression andtype of tissue.

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Differences in development among wheat cultivars are not only restricted to photoperiod and vernalization responses. When both requirements are fully satisfied differences may still arise due to earliness per se. It is not clear at present to what extent this trait is ‘ intrinsically ’ expressed (a constitutive trait) independently of the environmental conditions so that it might be selected under any thermal condition or if it may be altered to the extent of showing a crossover interaction with temperature in which the ranking of wheat genotypes may be altered. The present study assessed the influence of temperature on the intrinsic earliness for lines of diploid wheat characterized for their differences in a major gene for intrinsic earliness, but also possibly differing in their genetic background for other factors controlling this polygenic trait. To do so the lines were grown individually in two temperature regimes (16 and 23 xC) under long days having previously been fully vernalized. Multiple comparisons analyses were carried out among lines of the same allelic group for the Eps-Am1 gene. Results indicated that within each group there were lines that did not differ in their earliness per se, others differed but without exhibiting any linertemperature interaction and finally different types of interaction were shown, including cases where the ranking of lines was altered depending on the growing temperature. It is thus possible that the selection of a genotype based on its earliness per se in an environment might not represent the same performance in another location where temperature varied significantly.

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Gene flow (defined as allele exchange between populations) and gene flux (defined as allele exchange during meiosis in heterokaryotypic females) are important factors decreasing genetic differentiation between populations and inversions. Many chromosomal inversions are under strong selection and their role in recombination reduction enhances the maintenance of their genetic distinctness. Here we analyze levels and patterns of nucleotide diversity, selection and demographic history, using 37 individuals of Drosophila subobscura from Mount Parnes (Greece) and Barcelona (Spain). Our sampling focused on two frequent O-chromosome arrangements that differ by two overlapping inversions (OST and O3+4), which are differentially adapted to the environment as observed by their opposing latitudinal clines in inversion frequencies. The six analyzed genes (Pif1A, Abi, Sqd, Yrt, Atpa and Fmr1) were selected for their location across the O-chromosome and their implication in thermal adaptation. Despite the extensive gene flux detected outside the inverted region, significant genetic differentiation between both arrangements was found inside it. However, high levels of gene flow were detected for all six genes when comparing the same arrangement among populations. These results suggest that the adaptive value of inversions is maintained, regardless of the lack of genetic differentiation within arrangements from different populations, and thus favors the Local Adaptation hypothesis over the Coadapted Genome hypothesis as the basis of the selection acting on inversions in these populations.

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This paper assesses empirically the importance of size discrimination and disaggregate data for deciding where to locate a start-up concern. We compare three econometric specifications using Catalan data: a multinomial logit with 4 and 41 alternatives (provinces and comarques, respectively) in which firm size is the main covariate; a conditional logit with 4 and 41 alternatives including attributes of the sites as well as size-site interactions; and a Poisson model on the comarques and the full spatial choice set (942 municipalities) with site-specific variables. Our results suggest that if these two issues are ignored, conclusions may be misleading. We provide evidence that large and small firms behave differently and conclude that Catalan firms tend to choose between comarques rather than between municipalities. Moreover, labour-intensive firms seem more likely to be located in the city of Barcelona. Keywords: Catalonia, industrial location, multinomial response model. JEL: C250, E30, R00, R12

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This paper contributes to the existing literature on industrial location by discussing some issues regarding the territorial levels that have been used in location analysis. We analyse which could be the advantages and disadvantages of performing locational analysis at a different local levels. We use data for new manufacturing firms located at municipality, county and travel to work areas level. We show that location determinants vary according to the territorial level used in the analysis, so we conclude that the level at which we perform the investigation should be carefully selected. Keywords: industrial location, cities, agglomeration economies, count data models.

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The aim of this article is to assess the effects of several territorial characteristics, specifically agglomeration economies, on industrial location processes in the Spanish region of Catalonia. Theoretically, the level of agglomeration causes economies which favour the location of new establishments, but an excessive level of agglomeration might cause diseconomies, since congestion effects arise. The empirical evidence on this matter is inconclusive, probably because the models used so far are not suitable enough. We use a more flexible semiparametric specification, which allows us to study the nonlinear relationship between the different types of agglomeration levels and location processes. Our main statistical source is the REIC (Catalan Manufacturing Establishments Register), which has plant-level microdata on location of new industrial establishments. Keywords: agglomeration economies, industrial location, Generalized Additive Models, nonparametric estimation, count data models.

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This paper surveys recent evidence on the determinants of (national and/or foreign) industrial location. We find that the basic analytical framework has remained essentially unaltered since the early contributions of the early 1980's while, in contrast, there have been significant advances in the quality of the data and, to a lesser extent, the econometric modelling. We also identify certain determinants (neoclassical and institutional factors) that tend to provide largely consistent results across the reviewed studies. In light of this evidence, we finally suggest future lines of research.

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This paper analyses empirically how differences in local taxes affect the intraregional location of new manufacturing plants. These effects are examined within the random profit maximization framework while accounting for the presence of different types of agglomeration economies (localization/ urbanization/ Jacobs’ economies) at the municipal level. We look at the location decision of more than 10,000 establishments locating between 1996 and 2003 across more than 400 municipalities in Catalonia, a Spanish region. It is necessary to restrict the choice set to the local labor market and, above all, to control for agglomeration economies so as to identify the effects of taxes on the location of new establishments.

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Empirical studies on the determinants of industrial location typically use variables measured at the available administrative level (municipalities, counties, etc.). However, this amounts to assuming that the effects these determinants may have on the location process do not extent beyond the geographical limits of the selected site. We address the validity of this assumption by comparing results from standard count data models with those obtained by calculating the geographical scope of the spatially varying explanatory variables using a wide range of distances and alternative spatial autocorrelation measures. Our results reject the usual practice of using administrative records as covariates without making some kind of spatial correction. Keywords: industrial location, count data models, spatial statistics JEL classification: C25, C52, R11, R30

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El objetivo de esta investigación es aportar evidencia sobre las fuentes de las economías de aglomeración para el caso español. De todas las maneras posibles que se han tomado en la literatura para medir las economías de aglomeración, nosotros lo analizamos a partir de las decisiones de localización de las empresas manufactureras. La literatura reciente ha puesto de relieve que el análisis basado en la disyuntiva localización / urbanización (relaciones dentro de un mismo sector) no es suficiente para entender las economías de aglomeración. Sin embargo, las relaciones entre los diferentes sectores sí resultan significativas al examinar por qué las empresas que pertenecen a diferentes sectores se localizan unas al lado de las otras. Con esto en mente, intentamos explicar que relaciones entre diferentes sectores pueden explicar coaglomeración. Para ello, nos centramos en aquellas relaciones entre sectores definidos a partir de los mecanismos de aglomeración de Marshall, es decir, labor market, input sharing y knowledge spillovers. Trabajamos con el labor market pooling en la medida en que los dos sectores utilizan los mismos trabajadores (clasificación de ocupaciones). Con el segundo mecanismo de Marshall, input sharing, introducimos cómo dos sectores tienen una relación de comprador / vendedor. Por último, nos referimos a dos sectores que utilizan las mismas tecnologías en cuanto a los knowledge spillovers. Con el fin de capturar todos los efectos de los mecanismos de aglomeracion en España, en esta investigación trabajamos con dos ámbitos geográficos, los municipios y los mercados de trabajo locales. La literatura existente nunca se ha puesto de acuerdo en cual es el ámbito geográfico en el que mejor trabajan los mecanismos Marshall, por lo que hemos cubierto todas las unidades geográficas potenciales.

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This article analyses how agglomeration economies shaped the location decisions of new manufacturing start-ups in Catalan municipalities in 2001-2005. We estimate whether the locations of new firms are spatially autocorrelated and whether this phenomenon is industry-specific. Our aim is to estimate the geographical scope of agglomeration economies on firm entries. The data set comes from a compulsory register of manufacturing establishments (REIC: Catalan Manufacturing Establishments Register). JEL classification: R1, R3 Keywords: firm location; spatial autocorrelation

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This paper is about the role played by stock of human capital on location decisions of new manufacturing plants. We analyse the effect of several skill levels (from basic school to PhD) on decisions about the location of plants in various industries and, therefore, of different technological levels. We also test whether spatial aggregation level biases the results and determine the most appropriate areas to be considered in analyses of these phenomena. Our main statistical source is the Register of Manufacturing Establishments of Catalonia (REIC), which has plant-level microdata on the locations of new manufacturing plants. Keywords: agglomeration economies, industrial location, human capital, count-data models, spatial econometrics.

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This paper tries to resolve some of the main shortcomings in the empirical literature of location decisions for new plants, i.e. spatial effects and overdispersion. Spatial effects are omnipresent, being a source of overdispersion in the data as well as a factor shaping the functional relationship between the variables that explain a firm’s location decisions. Using Count Data models, empirical researchers have dealt with overdispersion and excess zeros by developments of the Poisson regression model. This study aims to take this a step further, by adopting Bayesian methods and models in order to tackle the excess of zeros, spatial and non-spatial overdispersion and spatial dependence simultaneously. Data for Catalonia is used and location determinants are analysed to that end. The results show that spatial effects are determinant. Additionally, overdispersion is descomposed into an unstructured iid effect and a spatially structured effect. Keywords: Bayesian Analysis, Spatial Models, Firm Location. JEL Classification: C11, C21, R30.

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This article analyzes empirically the main existing theories on income and population city growth: increasing returns to scale, locational fundamentals and random growth. To do this we implement a threshold nonlinearity test that extends standard linear growth regression models to a dataset on urban, climatological and macroeconomic variables on 1,175 U.S. cities. Our analysis reveals the existence of increasing returns when per-capita income levels are beyond $19; 264. Despite this, income growth is mostly explained by social and locational fundamentals. Population growth also exhibits two distinct equilibria determined by a threshold value of 116,300 inhabitants beyond which city population grows at a higher rate. Income and population growth do not go hand in hand, implying an optimal level of population beyond which income growth stagnates or deteriorates