891 resultados para genetic population data
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Allele frequency distributions and population data for 12 Y-chromosomal short tandem repeats (STRs) included in the PowerPlex (R) Y Systems (Promega) were obtained for a sample of 200 healthy unrelated males living in S (a) over tildeo Paulo State (Southeast of Brazil). A total of 192 haplotypes were identified, of which 184 were unique and 8 were found in 2 individuals. The average gene diversity of the 12 Y-STR was 0.6746 and the haplotype diversity was 0.9996. Pairwise analysis confirmed that our population is more similar with the Italy, North Portugal and Spain, being more distant of the Japan. (c) 2007 Elsevier B.V. All rights reserved.
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In the present study, allele frequency distributions for the 15 STR loci included in the PowerPlex® 16 Systems (Promega) were obtained from a sample of 55 unrelated individuals living in Araraquara region (SP, Brazil). The frequency of each allele for each locus tested, the exact test and the forensic and paternity parameters were calculated using POWERSTATS ver. 1.2 (Promega) and GENEPOP ver. 3.2 software. All loci are in the Hardy-Weinberg equilibrium and they reached a combined power discrimination of 0.999999999999999973 and combined power exclusion of 0.99999987, showing to be a powerful tool for paternity testing and individual identification in the population analyzed. © 2005 Elsevier B.V. All rights reserved.
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A new method of finding the optimal group membership and number of groupings to partition population genetic distance data is presented. The software program Partitioning Optimization with Restricted Growth Strings (PORGS), visits all possible set partitions and deems acceptable partitions to be those that reduce mean intracluster distance. The optimal number of groups is determined with the gap statistic which compares PORGS results with a reference distribution. The PORGS method was validated by a simulated data set with a known distribution. For efficiency, where values of n were larger, restricted growth strings (RGS) were used to bipartition populations during a nested search (bi-PORGS). Bi-PORGS was applied to a set of genetic data from 18 Chinook salmon (Oncorhynchus tshawytscha) populations from the west coast of Vancouver Island. The optimal grouping of these populations corresponded to four geographic locations: 1) Quatsino Sound, 2) Nootka Sound, 3) Clayoquot +Barkley sounds, and 4) southwest Vancouver Island. However, assignment of populations to groups did not strictly reflect the geographical divisions; fish of Barkley Sound origin that had strayed into the Gold River and close genetic similarity between transferred and donor populations meant groupings crossed geographic boundaries. Overall, stock structure determined by this partitioning method was similar to that determined by the unweighted pair-group method with arithmetic averages (UPGMA), an agglomerative clustering algorithm.
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Genetic population data for five X-STR (DXS6854, DXS7424, DXS101, DXS6808 and DXS7132) were obtained from Bauru population (São Paulo, Brazil). No deviations from the Hardy-Weinberg equilibrium were observed, with the exception of DXS101. The combined powers of discrimination in males and females were 0.99897253 and 0.99999120, respectively. These high values show the potential of this system in human identification and paternity testing. © 2008 Elsevier B.V. All rights reserved.
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Genetic population data for 10 X-STR (DXS8378, DXS9898, DXS7133, GATA31E08, GATA172D05, DXS7423, DXS6809, DXS7132, DXS9902 and DXS6789) were obtained from Vitória population (Espírito Santo State, Brazil). No deviations from the Hardy-Weinberg equilibrium and linkage disequilibrium were observed. The combined powers of discrimination in males and females were 0.9999995 and 0.99999999996, respectively. These high values show the potential of this system in human identification in Vitória population, Brazil. © 2009 Elsevier B.V. All rights reserved.
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The genetic population structure of red snapper Lutjanus malabaricus and Lutjanus erythropterus in eastern Indonesia and northern Australia was investigated by allozyme electrophoresis and sequence variation in the control region of mtDNA. Samples were collected from eight sites in Indonesia and four sites in northern Australia for both species. A total of 13 allozyme loci were scored. More variable loci were observed in L. malabaricus than in L. erythropterus. Sequence variation in the control region (left domain) of the mitochondrial genome was assessed by RFLP and direct sequencing. MtDNA haplotype diversity was high (L. erythropterus, 0.95 and L. malabaricus, 0.97), as was intraspecific sequence divergence, (L. erythropterus, 0.0-12.5% and L. malabaricus, 0.0-9.5%). The pattern of mtDNA haplotype frequencies grouped both species into two broad fisheries stocks with a genetic boundary either between Kupang and Sape (L. malabaricus) or between Kupang and Australian Timor Sea (L. erythropertus). The allozyme analyses revealed similar boundaries for L. erythropterus. Seven allozymes stocks compared to two mtDNA stocks of L. malabaricus including Ambon, which was not sampled with mtDNA, however, were reported. Possible reasons for differences in discrimination between the methods include: i) increased power of multiple allozyme loci over the single mtDNA locus, ii) insufficient gene sampling in the mtDNA control region and iii) relative evolutionary dynamics of nuclear (allozyme loci) and mitochondrial DNA in these taxa. Allozyme and haplotype data did not distinguish separate stocks among the four Australian locations nor the central Indonesian (Bali and Sape locations) for both L. malabaricus and L. erythropterus.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Similar to many small, range-restricted elasmobranchs, the Brazilian sharpnose shark (Rhizoprionodon lalandii) is listed as 'data deficient' by the International Union for the Conservation of Nature (IUCN). Data on stock assessment and sustainability are scarce, and there is no information on population structure. This constitutes a management problem because this shark comprises approximately 50% of the catch of small coastal sharks in Brazil. In this study, populations of R. lalandii distributed from the Caribbean to southern Brazil were investigated using sequences from the mitochondrial DNA control region. Analysis of molecular variance revealed strong structuring between population samples from the Caribbean and those from the Brazilian coast (F{cyrillic}ST=0.254, P<0.0001). Significant differences in the rates of genetic diversity between these major areas were also detected. The observed levels of population structuring are likely to be driven by female phylopatry. Therefore, the identification of both mating and nursery areas with parallel ban/restriction of fishing in these areas may be critical for the long-term sustainability of these populations. © 2013 John Wiley & Sons, Ltd.
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Pollination and seed dispersal are important ecological processes for the regeneration of plant populations and both vectors for gene exchange between plant populations. For my thesis, I studied the pollination ecology of the South African tree Commiphora harveyi (Burseraceae) and compared it with C. guillauminii from Madagascar. Both species have low visitation rates and a low number of pollinating insect species, resulting in a low fruit set. While their pollination ecology is very similar, they differ in their seed dispersal with a low seed dispersal rate in the Malagasy and a high seed dispersal rate in the South African species. This should be reflected in a stronger genetic differentiation among populations in the Malagasy than in the South African species. My results, based on AFLP markers, contradict these expectations, the overall differentiation was lower in the Malagasy (FST = 0.05) than in the South African species (FST = 0.16). However, at a smaller spatial scale (below 3 km), the Malagasy species was genetically more strongly differentiated than the South African species, which was reflected by the high inter-population variance within the sample site (C. guillauminii: 72.2 - 85.5 %; C. harveyi: 8.4 - 14.5 %). This strong differentiation could arise from limited gene flow, which was confirmed by spatial autocorrelation analyses. The shape of the autocorrelogram suggested that gene exchange between individuals occurred only up to 3 km in the Malagasy species, whereas up to 30 km in the South African species. These results on the genetic structure correspond to the expectations based on seed dispersal data. Thus, seed dispersal seems to be a key factor for the genetic structure in plant populations on a local scale.
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Geographic variation in vocalizations is widespread in passerine birds, but its origins and maintenance remain unclear. One hypothesis to explain this variation is that it is associated with geographic isolation among populations and therefore should follow a vicariant pattern similar to that typically found in neutral genetic markers. Alternatively, if environmental selection strongly influences vocalizations, then genetic divergence and vocal divergence may be disassociated. This study compared genetic divergence derived from 11 microsatellite markers with a metric of phenotypic divergence derived from male bower advertisement calls. Data were obtained from 16 populations throughout the entire distribution of the satin bowerbird, an Australian wet-forest-restricted passerine. There was no relationship between call divergence and genetic divergence, similar to most other studies on birds with learned vocalizations. Genetic divergence followed a vicariant model of evolution, with the differentiation of isolated populations and isolation-by-distance among continuous populations. Previous work on Ptilonorhynchus violaceus has shown that advertisement call structure is strongly influenced by the acoustic environment of different habitats. Divergence in vocalizations among genetically related populations in different habitats indicates that satin bowerbirds match their vocalizations to the environment in which they live, despite the homogenizing influence of gene flow. In combination with convergence of vocalizations among genetically divergent populations occurring in the same habitat, this shows the overriding importance that habitat-related selection can have on the establishment and maintenance of variation in vocalizations.
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The East Indies triangle, bordered by the Phillipines, Malay Peninsula and New Guinea, has a high level of tropical marine species biodiversity. Pristipomoides multidens is a large, long-lived, fecund snapper species that is distributed throughout the East Indies and Indo-Pacific. Samples were analysed from central and eastern Indonesia and northern Australia to test for genetic discontinuities in population structure. Fish (n = 377) were collected from the Indonesian islands of Bali, Sumbawa, Flores, West Timor, Tanimbar and Tual along with 131 fish from two northern Australian locations (Arafura and Timor Seas) from a previous study. Genetic variation in the control region of the mitochondrial genome was assayed using restriction fragment length polymorphism and direct sequencing. Haplotype diversity was high (0.67-0.82), as was intraspecific sequence divergence (range 0-5.8%). FST between pairs of populations ranged from 0 to 0.2753. Genetic subdivision was apparent on a small spatial scale; FST was 0.16 over 191 km (Bali/Sumbawa) and 0.17 over 491 km (Bali/Flores). Constraints to dispersal that contribute to, and maintain, the observed degree of genetic subdivision are experienced presumably by all life history stages of this tropical marine finfish. The constraints may include (1) little or no movement of eggs or larvae, (2) little or no home range or migratory movement of adults and (3) loss of larval cohorts due to transport of larvae away from suitable habitat by prevailing currents
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Biodiversity of sharks in the tropical Indo-Pacific is high, but species-specific information to assist sustainable resource exploitation is scarce. The null hypothesis of population genetic homogeneity was tested for scalloped hammerhead shark (Sphyrna lewini, n = 237) and the milk shark (Rhizoprionodon acutus, n = 207) from northern and eastern Australia, using nuclear (S. lewini, eight microsatellite loci; R. acutus, six loci) and mitochondrial gene markers (873 base pairs of NADH dehydrogenase subunit 4). We were unable to reject genetic homogeneity for S. lewini, which was as expected based on previous studies of this species. Less expected were similar results for R. acutus, which is more benthic and less vagile than S. lewini. These features are probably driving the genetic break found between Australian and central Indonesian R. acutus (F-statistics; mtDNA, 0.751–0.903, respectively; microsatellite loci, 0.038–0.047 respectively). Our results support the spatially homogeneous monitoring and management plan for shark species in Queensland, Australia.
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BACKGROUND: Biological processes occur on a vast range of time scales, and many of them occur concurrently. As a result, system-wide measurements of gene expression have the potential to capture many of these processes simultaneously. The challenge however, is to separate these processes and time scales in the data. In many cases the number of processes and their time scales is unknown. This issue is particularly relevant to developmental biologists, who are interested in processes such as growth, segmentation and differentiation, which can all take place simultaneously, but on different time scales. RESULTS: We introduce a flexible and statistically rigorous method for detecting different time scales in time-series gene expression data, by identifying expression patterns that are temporally shifted between replicate datasets. We apply our approach to a Saccharomyces cerevisiae cell-cycle dataset and an Arabidopsis thaliana root developmental dataset. In both datasets our method successfully detects processes operating on several different time scales. Furthermore we show that many of these time scales can be associated with particular biological functions. CONCLUSIONS: The spatiotemporal modules identified by our method suggest the presence of multiple biological processes, acting at distinct time scales in both the Arabidopsis root and yeast. Using similar large-scale expression datasets, the identification of biological processes acting at multiple time scales in many organisms is now possible.