Robust physical methods that enrich genomic regions identical by descent for linkage studies: confirmation of a locus for osteogenesis imperfecta

<p>Abstract</p> <p>Background</p> <p>The monogenic disease osteogenesis imperfecta (OI) is due to single mutations in either of the collagen genes ColA1 or ColA2, but within the same family a given mutation is accompanied by a wide range of disease severity. Although this phenotypic variability implies the existence of modifier gene variants, genome wide scanning of DNA from OI patients has not been reported. Promising genome wide marker-independent physical methods for identifying disease-related loci have lacked robustness for widespread applicability. Therefore we sought to improve these methods and demonstrate their performance to identify known and novel loci relevant to OI.</p> <p>Results</p> <p>We have improved methods for enriching regions of identity-by-descent (IBD) shared between related, afflicted individuals. The extent of enrichment exceeds 10- to 50-fold for some loci. The efficiency of the new process is shown by confirmation of the identification of the Col1A2 locus in osteogenesis imperfecta patients from Amish families. Moreover the analysis revealed additional candidate linkage loci that may harbour modifier genes for OI; a locus on chromosome 1q includes COX-2, a gene implicated in osteogenesis.</p> <p>Conclusion</p> <p>Technology for physical enrichment of IBD loci is now robust and applicable for finding genes for monogenic diseases and genes for complex diseases. The data support the further investigation of genetic loci other than collagen gene loci to identify genes affecting the clinical expression of osteogenesis imperfecta. The discrimination of IBD mapping will be enhanced when the IBD enrichment procedure is coupled with deep resequencing.</p

Detection and Attribution of Temperature Changes in the Mountainous Western United States

Large changes in the hydrology of the western United States have been observed since the mid-twentieth century. These include a reduction in the amount of precipitation arriving as snow, a decline in snowpack at low and midelevations, and a shift toward earlier arrival of both snowmelt and the centroid (center of mass) of streamflows. To project future water supply reliability, it is crucial to obtain a better understanding of the underlying cause or causes for these changes. A regional warming is often posited as the cause of these changes without formal testing of different competitive explanations for the warming. In this study, a rigorous detection and attribution analysis is performed to determine the causes of the late winter/early spring changes in hydrologically relevant temperature variables over mountain ranges of the western United States. Natural internal climate variability, as estimated from two long control climate model simulations, is insufficient to explain the rapid increase in daily minimum and maximum temperatures, the sharp decline in frost days, and the rise in degree-days above 0°C (a simple proxy for temperature-driven snowmelt). These observed changes are also inconsistent with the model-predicted responses to variability in solar irradiance and volcanic activity. The observations are consistent with climate simulations that include the combined effects of anthropogenic greenhouse gases and aerosols. It is found that, for each temperature variable considered, an anthropogenic signal is identifiable in observational fields. The results are robust to uncertainties in model-estimated fingerprints and natural variability noise, to the choice of statistical downscaling method, and to various processing options in the detection and attribution method.California Energy Commission///Estados UnidosU.S. Department of Energy/[DE-AC52-07NA27344]//Estados UnidosUniversidad de Costa Rica//UCR/Costa RicaUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigaciones Geofísicas (CIGEFI

durolib 1.0.0

First release available through anaconda/durack

Isolation and characterisation of the RAD51 and DMC1 homologs from Arabidopsis thaliana.

International audienceBy using RT-PCR and degenerate oligonucleotides based on the sequence homology between the yeast RAD51 and DMC1 genes, two genes belonging to the RAD51 and DMC1 families were isolated from Arabidopsis thaliana ecotype Columbia. A RAD51 genomic DNA was also sequenced which is almost identical to its Landsberg erecta counterpart, except for a few translationally silent substitutions and for the presence of a 527-bp element downstream of the polyadenylation site. This element is repeated in the genome of Arabidopsis. Northern analyses were conducted to characterize the expression pattern of both these genes. AtRAD51 and AtDMC1 are expressed in flower buds, but also in the mitotically active cells from a suspension culture. AtRAD51, but not AtDMC1, transcript level increases after gamma irradiation of the cells. Finally, a synchronisation experiment conducted with the suspension culture indicated that not only AtRAD51 but also AtDMC1 are regulated during the cell cycle, with S-phase-specific induction. Since DMC1 genes have always been regarded as being specifically meiotic, we discuss the significance of this mitotic transcriptional regulation in Arabidopsis

pcmdi_metrics: Version 1.1.1

Self contained packages to run PCMDI Metric

The Flexible Climate Data Analysis Tools (CDAT) for Multi-model Climate Simulation Data

Being able to incorporate, inspect, and analyze data with newly developed technologies, diagnostics, and visualizations in an easy and flexible way has been a longstanding challenge for scientists interested in understanding the intrinsic and extrinsic empirical assessment of multi-model climate output. To improve research ability and productivity, these technologies and tool must be made easily available to help scientists understand and solve complex scientific climate changes. To increase productivity and ease the challenges of incorporating new tools into the hands of scientists, the Program for Climate Model Diagnosis and Intercomparison (PCMDI) developed the Climate Data Analysis Tools (CDAT). CDAT is an application fo

eflows4hpc/PyOphidia: v3.0

&lt;p&gt;v3.0&lt;/p&gt