917 research outputs found

    The SWI/SNF protein ATRX co-regulates pseudoautosomal genes that have translocated to autosomes in the mouse genome

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    <p>Abstract</p> <p>Background</p> <p>Pseudoautosomal regions (PAR1 and PAR2) in eutherians retain homologous regions between the X and Y chromosomes that play a critical role in the obligatory X-Y crossover during male meiosis. Genes that reside in the PAR1 are exceptional in that they are rich in repetitive sequences and undergo a very high rate of recombination. Remarkably, murine PAR1 homologs have translocated to various autosomes, reflecting the complex recombination history during the evolution of the mammalian X chromosome.</p> <p>Results</p> <p>We now report that the SNF2-type chromatin remodeling protein ATRX controls the expression of eutherian ancestral PAR1 genes that have translocated to autosomes in the mouse. In addition, we have identified two potentially novel mouse PAR1 orthologs.</p> <p>Conclusion</p> <p>We propose that the ancestral PAR1 genes share a common epigenetic environment that allows ATRX to control their expression.</p

    Unifying the analysis of high-throughput sequencing datasets: characterizing RNA-seq, 16S rRNA gene sequencing and selective growth experiments by compositional data analysis.

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    BACKGROUND: Experimental designs that take advantage of high-throughput sequencing to generate datasets include RNA sequencing (RNA-seq), chromatin immunoprecipitation sequencing (ChIP-seq), sequencing of 16S rRNA gene fragments, metagenomic analysis and selective growth experiments. In each case the underlying data are similar and are composed of counts of sequencing reads mapped to a large number of features in each sample. Despite this underlying similarity, the data analysis methods used for these experimental designs are all different, and do not translate across experiments. Alternative methods have been developed in the physical and geological sciences that treat similar data as compositions. Compositional data analysis methods transform the data to relative abundances with the result that the analyses are more robust and reproducible. RESULTS: Data from an in vitro selective growth experiment, an RNA-seq experiment and the Human Microbiome Project 16S rRNA gene abundance dataset were examined by ALDEx2, a compositional data analysis tool that uses Bayesian methods to infer technical and statistical error. The ALDEx2 approach is shown to be suitable for all three types of data: it correctly identifies both the direction and differential abundance of features in the differential growth experiment, it identifies a substantially similar set of differentially expressed genes in the RNA-seq dataset as the leading tools and it identifies as differential the taxa that distinguish the tongue dorsum and buccal mucosa in the Human Microbiome Project dataset. The design of ALDEx2 reduces the number of false positive identifications that result from datasets composed of many features in few samples. CONCLUSION: Statistical analysis of high-throughput sequencing datasets composed of per feature counts showed that the ALDEx2 R package is a simple and robust tool, which can be applied to RNA-seq, 16S rRNA gene sequencing and differential growth datasets, and by extension to other techniques that use a similar approach

    Early Detection of Poor Adherers to Statins: Applying Individualized Surveillance to Pay for Performance

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    Background: Medication nonadherence costs $300 billion annually in the US. Medicare Advantage plans have a financial incentive to increase medication adherence among members because the Centers for Medicare and Medicaid Services (CMS) now awards substantive bonus payments to such plans, based in part on population adherence to chronic medications. We sought to build an individualized surveillance model that detects early which beneficiaries will fall below the CMS adherence threshold. Methods: This was a retrospective study of over 210,000 beneficiaries initiating statins, in a database of private insurance claims, from 2008-2011. A logistic regression model was constructed to use statin adherence from initiation to day 90 to predict beneficiaries who would not meet the CMS measure of proportion of days covered 0.8 or above, from day 91 to 365. The model controlled for 15 additional characteristics. In a sensitivity analysis, we varied the number of days of adherence data used for prediction. Results: Lower adherence in the first 90 days was the strongest predictor of one-year nonadherence, with an odds ratio of 25.0 (95% confidence interval 23.7-26.5) for poor adherence at one year. The model had an area under the receiver operating characteristic curve of 0.80. Sensitivity analysis revealed that predictions of comparable accuracy could be made only 40 days after statin initiation. When members with 30-day supplies for their first statin fill had predictions made at 40 days, and members with 90-day supplies for their first fill had predictions made at 100 days, poor adherence could be predicted with 86% positive predictive value. Conclusions: To preserve their Medicare Star ratings, plan managers should identify or develop effective programs to improve adherence. An individualized surveillance approach can be used to target members who would most benefit, recognizing the tradeoff between improved model performance over time and the advantage of earlier detection

    Ultraviolet-Optical observations of the Seyfert 2 Galaxies NGC 7130, NGC 5135 and IC 3639: Implications for the Starburst-AGN Connection

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    We present and discuss HST (WFPC2 and FOC) images and UV GHRS spectra plus ground-based near UV through to near IR spectra of three Seyfert 2 nuclei (NGC 7130, NGC 5135 and IC 3639). These galaxies, together to Mrk 477, were selected from a bigger sample that comprises the 20 brightest Seyfert 2 nuclei, with the goal to study the origin of the UV-optical-near IR featureless continuum in Seyfert 2 nuclei. These four galaxies have bolometric luminosities, as computed with the four IRAS bands, of 10^11 Lsol. They are close enough to be resolved with HST the nuclear zone. This makes these Seyfert 2 galaxies benchmarks to study the Starburst-AGN connection in more distant galaxies. The data provide direct evidence of the existence of a central nuclear starburst that dominates the UV light, and that seem to be responsible for the origin of the so called featureless continuum. These starbursts are dusty and compact. They have sizes (from less than 100 pc to a few hundred pc) much smaller and closer to the nucleus than that seen in the prototype Seyfert 2 galaxy NGC 1068. The bolometric luminosity of these starbursts is similar to the estimated bolometric luminosities of their obscured Seyfert 1 nuclei, and thus they contribute in the same amount to the overall energetics of these galaxies.Comment: to be published in ApJ 505, September issue. The figures are in a tar files at: http://www.iaa.es/~rosa/Seyfert

    Single-atom imaging of fermions in a quantum-gas microscope

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    Single-atom-resolved detection in optical lattices using quantum-gas microscopes has enabled a new generation of experiments in the field of quantum simulation. Fluorescence imaging of individual atoms has so far been achieved for bosonic species with optical molasses cooling, whereas detection of fermionic alkaline atoms in optical lattices by this method has proven more challenging. Here we demonstrate single-site- and single-atom-resolved fluorescence imaging of fermionic potassium-40 atoms in a quantum-gas microscope setup using electromagnetically-induced-transparency cooling. We detected on average 1000 fluorescence photons from a single atom within 1.5s, while keeping it close to the vibrational ground state of the optical lattice. Our results will enable the study of strongly correlated fermionic quantum systems in optical lattices with resolution at the single-atom level, and give access to observables such as the local entropy distribution and individual defects in fermionic Mott insulators or anti-ferromagnetically ordered phases.Comment: 7 pages, 5 figures; Nature Physics, published online 13 July 201

    ESET histone methyltransferase is essential to hypertrophic differentiation of growth plate chondrocytes and formation of epiphyseal plates

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    AbstractThe ESET (also called SETDB1) protein contains an N-terminal tudor domain that mediates protein–protein interactions and a C-terminal SET domain that catalyzes methylation of histone H3 at lysine 9. We report here that ESET protein is transiently upregulated in prehypertrophic chondrocytes in newborn mice. To investigate the in vivo effects of ESET on chondrocyte differentiation, we generated conditional knockout mice to specifically eliminate the catalytic SET domain of ESET protein only in mesenchymal cells. Such deletion of the ESET gene caused acceleration of chondrocyte hypertrophy in both embryos and young animals, depleting chondrocytes that are otherwise available to form epiphyseal plates for endochondral bone growth. ESET-deficient mice are thus characterized by defective long bone growth and trabecular bone formation. To understand the underlying mechanism for ESET regulation of chondrocytes, we carried out co-expression experiments and found that ESET associates with histone deacetylase 4 to bind and inhibit the activity of Runx2, a hypertrophy-promoting transcription factor. Repression of Runx2-mediated gene transactivation by ESET is dependent on its H3–K9 methyltransferase activity as well as its associated histone deacetylase activity. In addition, knockout of ESET is associated with repression of Indian hedgehog gene in pre- and early hypertrophic chondrocytes. Together, these results provide clear evidence that ESET controls hypertrophic differentiation of growth plate chondrocytes and endochondral ossification during embryogenesis and postnatal development

    Deleterious Mutation Burden and Its Association with Complex Traits in Sorghum (Sorghum bicolor)

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    Sorghum (Sorghum bicolor L.) is a major food cereal for millions of people worldwide. The sorghum genome, like other species, accumulates deleterious mutations, likely impacting its fitness. The lack of recombination, drift, and the coupling with favorable loci impede the removal of deleterious mutations from the genome by selection. To study how deleterious variants impact phenotypes, we identified putative deleterious mutations among ∼5.5 M segregating variants of 229 diverse biomass sorghum lines. We provide the whole-genome estimate of the deleterious burden in sorghum, showing that ∼33% of nonsynonymous substitutions are putatively deleterious. The pattern of mutation burden varies appreciably among racial groups. Across racial groups, the mutation burden correlated negatively with biomass, plant height, specific leaf area (SLA), and tissue starch content (TSC), suggesting that deleterious burden decreases trait fitness. Putatively deleterious variants explain roughly one-half of the genetic variance. However, there is only moderate improvement in total heritable variance explained for biomass (7.6%) and plant height (average of 3.1% across all stages). There is no advantage in total heritable variance for SLA and TSC. The contribution of putatively deleterious variants to phenotypic diversity therefore appears to be dependent on the genetic architecture of traits. Overall, these results suggest that incorporating putatively deleterious variants into genomic models slightly improves prediction accuracy because of extensive linkage. Knowledge of deleterious variants could be leveraged for sorghum breeding through either genome editing and/or conventional breeding that focuses on the selection of progeny with fewer deleterious alleles

    Microbiome profiling by Illumina sequencing of combinatorial sequence-tagged PCR products

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    We developed a low-cost, high-throughput microbiome profiling method that uses combinatorial sequence tags attached to PCR primers that amplify the rRNA V6 region. Amplified PCR products are sequenced using an Illumina paired-end protocol to generate millions of overlapping reads. Combinatorial sequence tagging can be used to examine hundreds of samples with far fewer primers than is required when sequence tags are incorporated at only a single end. The number of reads generated permitted saturating or near-saturating analysis of samples of the vaginal microbiome. The large number of reads al- lowed an in-depth analysis of errors, and we found that PCR-induced errors composed the vast majority of non-organism derived species variants, an ob- servation that has significant implications for sequence clustering of similar high-throughput data. We show that the short reads are sufficient to assign organisms to the genus or species level in most cases. We suggest that this method will be useful for the deep sequencing of any short nucleotide region that is taxonomically informative; these include the V3, V5 regions of the bac- terial 16S rRNA genes and the eukaryotic V9 region that is gaining popularity for sampling protist diversity.Comment: 28 pages, 13 figure

    Preparation of anti-vicinal amino alcohols: asymmetric synthesis of D-erythro-Sphinganine, (+)-spisulosine and D-ribo-phytosphingosine

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    Two variations of the Overman rearrangement have been developed for the highly selective synthesis of anti-vicinal amino alcohol natural products. A MOM-ether directed palladium(II)-catalyzed rearrangement of an allylic trichloroacetimidate was used as the key step for the preparation of the protein kinase C inhibitor D-erythro-sphinganine and the antitumor agent (+)-spisulosine, while the Overman rearrangement of chiral allylic trichloroacetimidates generated by asymmetric reduction of an alpha,beta-unsaturated methyl ketone allowed rapid access to both D-ribo-phytosphingosine and L-arabino-phytosphingosine
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