394 resultados para genetic variations


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The caudate is a subcortical brain structure implicated in many common neurological and psychiatric disorders. To identify specific genes associated with variations in caudate volume, structural magnetic resonance imaging and genome-wide genotypes were acquired from two large cohorts, the Alzheimer's Disease NeuroImaging Initiative (ADNI; N=734) and the Brisbane Adolescent/Young Adult Longitudinal Twin Study (BLTS; N=464). In a preliminary analysis of heritability, around 90% of the variation in caudate volume was due to genetic factors. We then conducted genome-wide association to find common variants that contribute to this relatively high heritability. Replicated genetic association was found for the right caudate volume at single-nucleotide polymorphism rs163030 in the ADNI discovery sample (P=2.36 × 10 -6) and in the BLTS replication sample (P=0.012). This genetic variation accounted for 2.79 and 1.61% of the trait variance, respectively. The peak of association was found in and around two genes, WDR41 and PDE8B, involved in dopamine signaling and development. In addition, a previously identified mutation in PDE8B causes a rare autosomal-dominant type of striatal degeneration. Searching across both samples offers a rigorous way to screen for genes consistently influencing brain structure at different stages of life. Variants identified here may be relevant to common disorders affecting the caudate.

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The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.

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Several genetic variants are thought to influence white matter (WM) integrity, measured with diffusion tensor imaging (DTI). Voxel based methods can test genetic associations, but heavy multiple comparisons corrections are required to adjust for searching the whole brain and for all genetic variants analyzed. Thus, genetic associations are hard to detect even in large studies. Using a recently developed multi-SNP analysis, we examined the joint predictive power of a group of 18 cholesterol-related single nucleotide polymorphisms (SNPs) on WM integrity, measured by fractional anisotropy. To boost power, we limited the analysis to brain voxels that showed significant associations with total serum cholesterol levels. From this space, we identified two genes with effects that replicated in individual voxel-wise analyses of the whole brain. Multivariate analyses of genetic variants on a reduced anatomical search space may help to identify SNPs with strongest effects on the brain from a broad panel of genes.

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To classify each stage for a progressing disease such as Alzheimer’s disease is a key issue for the disease prevention and treatment. In this study, we derived structural brain networks from diffusion-weighted MRI using whole-brain tractography since there is growing interest in relating connectivity measures to clinical, cognitive, and genetic data. Relatively little work has usedmachine learning to make inferences about variations in brain networks in the progression of the Alzheimer’s disease. Here we developed a framework to utilize generalized low rank approximations of matrices (GLRAM) and modified linear discrimination analysis for unsupervised feature learning and classification of connectivity matrices. We apply the methods to brain networks derived from DWI scans of 41 people with Alzheimer’s disease, 73 people with EMCI, 38 people with LMCI, 47 elderly healthy controls and 221 young healthy controls. Our results show that this new framework can significantly improve classification accuracy when combining multiple datasets; this suggests the value of using data beyond the classification task at hand to model variations in brain connectivity.

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Understanding the patterns of genetic structure in the introduced range of invasive species can help elucidate invasion histories and levels of gene flow among populations. Parthenium weed (Parthenium hysterophorus L.; PW) is native to the Gulf of Mexico and central South America but has become globally invasive during the last three decades and little is known about the genetics of this species in its invasive range. The present study was conducted to determine the genetic structure of 95 individual samples from 11 populations (9 from Pakistan and 2 from Australia) of PW using ISSR fingerprinting. A total of 30 ISSR primers were screened; of which eight were selected due to their high polymorphism and reproducibility. In toto 147 bands were amplified, which ranged in size from 200-2000 bp; among which 97 were polymorphic. Genetic diversity within the populations both from Pakistan and Australia ranged between 0.193-0.278. Approximately 18% of genetic variation occurred among and 82% within populations. Principal Coordinate Analysis showed that within the 95 samples two groups were present: one contained samples collected mainly from Pakistan and the second group included the Australian samples along with two populations from Pakistan. Overall, there was limited gene flow among PW populations in Pakistan, although the genetic diversity within populations was high. The degree of genetic variation inferred from various population diversity measures can predict different events of founding populations, which have passed through complicated processes of invasion, experiencing genetic bottlenecks. Taken together, results showed that PW in Pakistan is genetically heterogeneous and may have been the result of multiple introductions.

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Accurate radiocarbon dating of marine samples requires knowledge of the marine radiocarbon reservoir effect. This effect for a particular site/region is generally assumed constant through time when calibrating marine 14C ages. However, recent studies have shown large temporal variations of several hundred to a couple of thousand years in this effect for a number of regions during the late Quaternary and Holocene. Here we report marine radiocarbon reservoir correction (ΔRΔR) for Heron Reef and Moreton Bay in southwestern (SW) Pacific for the last 8 ka derived from 14C analysis of 230Th-dated corals. Most of our ΔRΔR for the last ∼5.4 ka agree well with their modern value, but large ΔRΔR variability of ∼410 yr (from trough to peak) with possible decadal/centennial fluctuations is evident for the period ∼5.4–8 ka. The latter time interval also has significant variations with similar features in previously published ΔRΔR values for other sites in the Pacific, including southern Peru–northern Chile in southeastern (SE) Pacific, the South China Sea, Vanuatu and Papua New Guinea, with the largest magnitude of ∼920 yr from SE Pacific. The mechanisms for these large ΔRΔR variations across the Pacific during the mid-Holocene are complex processes involving (1) changes in the quantity and 14C content of upwelled waters in tropical east Pacific (TEP) (frequency and intensity of ocean upwelling in the TEP, and contribution of Subantarctic Mode Water to the upwelled waters, which is influenced by the intensity and position of southern westerly winds), and (2) variations in ocean circulation associated with climate change (La Niña/El Niño conditions, intensity of easterly trade winds, positions of the Intertropical Convergence Zone and the South Pacific Convergence Zone), which control the spreading of the older upwelled surface waters in the TEP to the western sites. Our results imply the need for employing temporal changes in ΔRΔR values, instead of constant (modern) values, for age calibration of Holocene marine samples not only for the SW Pacific sites but also for other tropical and subtropical sites in the Pacific.

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With the aim of elucidating the seasonal behaviour of rare earth elements (REEs), surface and groundwaters were collected under dry and wet conditions in different hydrological units of the Teviot Brook catchment (Southeast Queensland, Australia). Sampled waters showed a large degree of variability in both REE abundance and normalised patterns. Overall REE abundance ranged over nearly three orders of magnitude, and was consistently lower in the sedimentary bedrock aquifer (18ppt<∑REE<477ppt) than in the other hydrological systems studied. Abundance was greater in springs draining rhyolitic rocks (∑REE=300 and 2054ppt) than in springs draining basalt ranges (∑REE=25 and 83ppt), yet was highly variable in the shallow alluvial groundwater (16ppt<∑REE<5294ppt) and, to a lesser extent, in streamwater (85ppt<∑REE<2198ppt). Generally, waters that interacted with different rock types had different REE patterns. In order to obtain an unbiased characterisation of REE patterns, the ratios between light and middle REEs (R(M/L)) and the ratios between middle and heavy REEs (R(H/M)) were calculated for each sample. The sedimentary bedrock aquifer waters had highly evolved patterns depleted in light REEs and enriched in middle and heavy REEs (0.17variations. Samples collected from the alluvium exhibited an increasing influence of the sedimentary bedrock from upgradient to downgradient; typically they showed flat patterns in the upstream section of the alluvium (median R(M/L)=0.21 and median R(H/M)=-0.06) gradually evolving towards patterns depleted in light REEs and enriched in middle and heavy REEs downgradient (median R(M/L)=0.48 and median R(H/M)=0.38). To document the seasonal variations in REE patterns, the difference in ratios between dry and wet sampling campaigns was determined for each repeated sampling location. Contributions from the sedimentary bedrock water to the alluvium during the wet season were identified at two locations (increase from R(H/M)=0.03 and 0.35 to R(H/M)=0.62 and 0.89). The effect of recharge through fractured igneous rocks was also observed in two boreholes intercepting the sedimentary bedrock, where the freshly recharged waters likely contributed to the deeper groundwater flow during the wet season (decrease from R(M/L)=0.81 and 0.56 to R(M/L)=0.46 and 0.17). Results from this study suggest that REEs may be usefully applied as indicators of recharge processes and inter-aquifer mixing. They also underline the importance of conducting seasonal sampling campaigns to capture possible short-term variations in REE patterns and abundance, which is essential to enable a better understanding of hydrological and hydrochemical processes in complex geological settings

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This paper considers the legal challenges to the legal validity of the patents held by Myriad Genetics in respect of genetic testing for breast cancer and ovarian cancer. It argues that broad-based patents on gene sequences and medical diagnostics will have a harmful effect upon access to patient care, genetic research, and the administration of public health care.

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This project aimed to identify novel genetic risk variants associated with migraine in the Norfolk Island population. Statistical analysis and bioinformatics approaches such as polygenic modeling and gene clustering methods were carried out to explore genotypic and expression data from high-throughput techniques. This project had a particular focus on hormonal genes and other genetic variants and identified a modest effect size on the migraine phenotype.

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Both red snow crab (Chionoecetes japonicus Rathbun, 1932) and snow crab (Chionoecetes opilio Fabricius, 1788) are commercially important species in Korea. The geographical ranges of the two species overlap in the East Sea, where both species are fished commercially. Morphological identification of the two species and putative hybrids can be difficult because of their overlapping morphological characteristics. The presence of putative hybrids can affect the total allowable catch (TAC) of C. japonicus and C. opilio, and causes problems managing C. japonicus and C. opilio wild resources. To date, however, no natural hybridization has been reported between C. japonicus and C. opilio, despite their overlapping distributions along the coast of the East Sea. In this study, the internal transcribed spacer (ITS) region of major ribosomal RNA genes from the nuclear genome and the cytochrome oxidase I (CO I) gene from the mitochondrial genome were sequenced to determine whether natural hybridization occurs between the two species. Our results revealed that all putative hybrids identified using morphological traits had two distinct types of ITS sequences corresponding to those of both parental species. Mitochondrial CO I gene sequencing showed that all putative hybrids had sequences identical to C. japonicus. A genotyping assay based on single nucleotide polymorphisms in the ITS1 region and the CO I gene produced the most efficient and accurate identification of all hybrid individuals. Molecular data clearly demonstrate that natural hybridization does occur between C. japonicus and C. opilio, but only with C. japonicus as the maternal parent.

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The oily bittering Acheilognathus koreensis is a freshwater species that is endemic to Korea and is experiencing severe declines in natural populations as a result of habitat fragmentation and water pollution. For the conservation and restoration of this species, it is necessary to assess its genetic diversity at the population level. We developed 13 polymorphic microsatellite loci that were used to analyze the genetic diversity of two populations collected from the Kum River and the Tamjin River in Korea. All loci exhibited Mendelian inheritance patterns when examined in controlled crosses. Both populations revealed high levels of variability, with the number of alleles ranging from 3 to 20 and observed and expected heterozygosities ranging from 0.500 to 0.969 and from 0.529 to 0.938, respectively. None of the loci showed significant deviation from Hardy–Weinberg equilibrium, and one pair of loci showed significant linkage disequilibrium after Bonferroni correction. Pairwise F ST and genetic distance estimation showed significant differences between two populations. These results suggest that the microsatellites developed herein can be used to study the genetic diversity, population structure and conservation measure of A. koreensis.

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The Korean black scraper, Thamnaconus modestus, is one of the most economically important maricultural fish species in Korea. However, the annual catch of this fish has been continuously declining over the past several decades. In this study, the genetic diversity and relationships among four wild populations and two hatchery stocks of Korean black scraper were assessed based on 16 microsatellite (MS) markers. A total of 319 different alleles were detected over all loci with an average of 19.94 alleles per locus. The hatchery stocks [mean number of alleles (N A) = 12, allelic richness (A R) = 12, expected heterozygosity (He) = 0.834] showed a slight reduction (P > 0.05) in genetic variability in comparison with wild populations (mean N A = 13.86, A R = 12.35, He = 0.844), suggesting a sufficient level of genetic variation in the hatchery populations. Similarly low levels of inbreeding and significant Hardy–Weinberg equilibrium deviations were detected in both wild and hatchery populations. The genetic subdivision among all six populations was low but significant (overall F ST = 0.008, P < 0.01). Pairwise F ST, a phylogenetic tree, and multidimensional scaling analysis suggested the existence of three geographically structured populations based on different sea basin origins, although the isolation-by-distance model was rejected. This result was corroborated by an analysis of molecular variance. This genetic differentiation may result from the co-effects of various factors, such as historical dispersal, local environment and ocean currents. These three geographical groups can be considered as independent management units. Our results show that MS markers may be suitable not only for the genetic monitoring of hatchery stocks but also for revealing the population structure of Korean black scraper populations. These results will provide critical information for breeding programs, the management of cultured stocks and the conservation of this species.

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Microsatellite markers are important for gene mapping and for marker-assisted selection. Sixty-five polymorphic microsatellite markers were developed with an enriched partial genomic library from olive flounder Paralichthys olivaceus an important commercial fish species in Korea. The variability of these markers was tested in 30 individuals collected from the East Sea (Korea). The number of alleles for each locus ranged from 2 to 33 (mean, 17.1). Observed and expected heterozygosity as well as polymorphism information content varied from 0.313 to 1.000 (mean, 0.788), from 0.323 to 0.977 (mean, 0.820), and from 0.277 to 0.960 (mean, 0.787), respectively. Nine loci showed significant deviation from the Hardy-Weinberg equilibrium after sequential Bonferroni correction. Analysis with MICROCHECKER suggested the presence of null alleles at five of these loci with estimated null allele frequencies of 0.126-0.285. These new microsatellite markers from genomic libraries will be useful for constructing a P. olivaceus linkage map.

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The native Asian oyster, Crassostrea ariakensis is one of the most common and important Crassostrea species that occur naturally along the coast of East Asia. Molecular species diagnosis is a prerequisite for population genetic analysis of wild oyster populations because oyster species cannot be discriminated reliably using external morphological characters alone due to character ambiguity. To date there have been few phylogeographic studies of natural edible oyster populations in East Asia, in particular this is true of the common species in Korea C. ariakensis. We therefore assessed the levels and patterns of molecular genetic variation in East Asian wild populations of C. ariakensis from Korea, Japan, and China using DNA sequence analysis of five concatenated mtDNA regions namely; 16S rRNA, cytochrome oxidase I, cytochrome oxidase II, cytochrome oxidase III, and cytochrome b. Two divergent C. ariakensis clades were identified between southern China and remaining sites from the northern region. In addition, hierarchical AMOVA and pairwise UST analyses showed that genetic diversity was discontinuous among wild populations of C. ariakensis in East Asia. Biogeographical and historical sea level changes are discussed as potential factors that may have influenced the genetic heterogeneity of wild C. ariakensis stocks across this region.

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The increase in data center dependent services has made energy optimization of data centers one of the most exigent challenges in today's Information Age. The necessity of green and energy-efficient measures is very high for reducing carbon footprint and exorbitant energy costs. However, inefficient application management of data centers results in high energy consumption and low resource utilization efficiency. Unfortunately, in most cases, deploying an energy-efficient application management solution inevitably degrades the resource utilization efficiency of the data centers. To address this problem, a Penalty-based Genetic Algorithm (GA) is presented in this paper to solve a defined profile-based application assignment problem whilst maintaining a trade-off between the power consumption performance and resource utilization performance. Case studies show that the penalty-based GA is highly scalable and provides 16% to 32% better solutions than a greedy algorithm.