54 research outputs found

    Strong Selection for Behavioural Resilience in Australian Stock Working Dogs Identified by Selective Sweep Analysis

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    Background: Working dog handlers and breeders have strong opinions on characteristics that are desirable in the breeds that they use to handle stock. Most of these characteristics are related to conformation or behaviour. This study explored whether the genetics underlying desirable working behaviour traits might be identified by selective sweep analysis; a method that identifies long regions of strong homozygosity combined with allelic divergence from a comparison group. For this analysis, we compared genomic haplotype architecture in two breeds derived from common founder stock but subjected to divergent selective pressures. The breeds studied were the Australian Kelpie, which is registered with the Australian National Kennel Council, and the Australian Working Kelpie, which is registered with the Working Kelpie Council. Results: A selective sweep spanning 3 megabases on chromosome 3 was identified in the Australian Working Kelpie. This region is the location of genes related to fear-memory formation and pain perception. Selective sweep loci of similar magnitude were observed in the Australian Kelpie. On chromosome 8 is a locus which may be related to behavioural excitability and on chromosome 30 is a smaller locus which most likely is related to morphology. Conclusions: Active working stock dogs of the Australian Working Kelpie breed have been bred primarily for gene loci influencing pain perception and fear memory formation. By contrast Australian Kelpies are commonly maintained in urban environments where these characteristics are not required and have been affected by selection for conformation and coat colour. The identified loci may aid in the identification of superior working dogs

    Thymoquinone inhibits tumor growth and induces apoptosis in a breast cancer xenograft mouse model: The role of p38 MAPK and ROS

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    Due to narrow therapeutic window of cancer therapeutic agents and the development of resistance against these agents, there is a need to discover novel agents to treat breast cancer. The antitumor activities of thymoquinone (TQ), a compound isolated from Nigella sativa oil, were investigated in breast carcinoma in vitro and in vivo. Cell responses after TQ treatment were assessed by using different assays including MTT assay, annexin V-propidium iodide staining, Mitosox staining and Western blot. The antitumor effect was studied by breast tumor xenograft mouse model, and the tumor tissues were examined by histology and immunohistochemistry. The level of antioxidant enzymes/molecules in mouse liver tissues was measured by commercial kits. Here, we show that TQ induced p38 phosphorylation and ROS production in breast cancer cells. These inductions were found to be responsible for TQ’s anti-proliferative and pro-apoptotic effects. Moreover, TQ-induced ROS production regulated p38 phosphorylation but not vice versa. TQ treatment was found to suppress the tumor growth and this effect was further enhanced by combination with doxorubicin. TQ also inhibited the protein expression of anti-apoptotic genes, such as XIAP, survivin, Bcl-xL and Bcl-2, in breast cancer cells and breast tumor xenograft. Reduced Ki67 and increased TUNEL staining were observed in TQ-treated tumors. TQ was also found to increase the level of catalase, superoxide dismutase and glutathione in mouse liver tissues. Overall, our results demonstrated that the antiproliferative and pro-apoptotic effects of TQ in breast cancer are mediated through p38 phosphorylation via ROS generation

    CHEMICAL CARTOGRAPHY with APOGEE: METALLICITY DISTRIBUTION FUNCTIONS and the CHEMICAL STRUCTURE of the MILKY WAY DISK

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    Using a sample of 69,919 red giants from the SDSS-III/APOGEE Data Release 12, we measure the distribution of stars in the [/Fe] versus [Fe/H] plane and the metallicity distribution functions (MDFs) across an unprecedented volume of the Milky Way disk, with radius 3 < R < 15 kpc and height kpc. Stars in the inner disk (R < 5 kpc) lie along a single track in [/Fe] versus [Fe/H], starting with -enhanced, metal-poor stars and ending at [/Fe] ∼ 0 and [Fe/H] ∼ +0.4. At larger radii we find two distinct sequences in [/Fe] versus [Fe/H] space, with a roughly solar- sequence that spans a decade in metallicity and a high- sequence that merges with the low- sequence at super-solar [Fe/H]. The location of the high- sequence is nearly constant across the disk

    ABUNDANCES, STELLAR PARAMETERS, AND SPECTRA FROM THE SDSS-III/APOGEE SURVEY

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    The SDSS-III/Apache Point Observatory Galactic Evolution Experiment (APOGEE) survey operated from 2011–2014 using the APOGEE spectrograph, which collects high-resolution (R ~ 22,500), near-IR (1.51–1.70 µm) spectra with a multiplexing (300 fiber-fed objects) capability. We describe the survey data products that are publicly available, which include catalogs with radial velocity, stellar parameters, and 15 elemental abundances for over 150,000 stars, as well as the more than 500,000 spectra from which these quantities are derived. Calibration relations for the stellar parameters (Teff , log g, [M/H], [a/M]) and abundances (C, N, O, Na, Mg, Al, Si, S, K, Ca, Ti, V, Mn, Fe, Ni) are presented and discussed. The internal scatter of the abundances within clusters indicates that abundance precision is generally between 0.05 and 0.09 dex across a broad temperature range; it is smaller for some elemental abundances within more limited ranges and at high signal-to-noise ratio. We assess the accuracy of the abundances using comparison of mean cluster metallicities with literature values, APOGEE observations of the solar spectrum and of Arcturus, comparison of individual star abundances with other measurements, and consideration of the locus of derived parameters and abundances of the entire sample, and find that it is challenging to determine the absolute abundance scale; external accuracy may be good to 0.1–0.2 dex. Uncertainties may be larger at cooler temperatures (Teff < 4000 K). Access to the public data release and data products is described, and some guidance for using the data products is provided

    The Eleventh and Twelfth Data Releases of the Sloan Digital Sky Survey: Final Data from SDSS-III

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    The third generation of the Sloan Digital Sky Survey (SDSS-III) took data from 2008 to 2014 using the original SDSS wide-field imager, the original and an upgraded multi-object fiber-fed optical spectrograph, a new near-infrared high-resolution spectrograph, and a novel optical interferometer. All of the data from SDSS-III are now made public. In particular, this paper describes Data Release 11 (DR11) including all data acquired through 2013 July, and Data Release 12 (DR12) adding data acquired through 2014 July (including all data included in previous data releases), marking the end of SDSS-III observing. Relative to our previous public release (DR10), DR12 adds one million new spectra of galaxies and quasars from the Baryon Oscillation Spectroscopic Survey (BOSS) over an additional 3000 deg2 of sky, more than triples the number of H-band spectra of stars as part of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE), and includes repeated accurate radial velocity measurements of 5500 stars from the Multi-object APO Radial Velocity Exoplanet Large-area Survey (MARVELS). The APOGEE outputs now include the measured abundances of 15 different elements for each star. In total, SDSS-III added 5200 deg2 of ugriz imaging; 155,520 spectra of 138,099 stars as part of the Sloan Exploration of Galactic Understanding and Evolution 2 (SEGUE-2) survey; 2,497,484 BOSS spectra of 1,372,737 galaxies, 294,512 quasars, and 247,216 stars over 9376 deg2; 618,080 APOGEE spectra of 156,593 stars; and 197,040 MARVELS spectra of 5513 stars. Since its first light in 1998, SDSS has imaged over 1/3 of the Celestial sphere in five bands and obtained over five million astronomical spectra. \ua9 2015. The American Astronomical Society

    Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

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    Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

    The Seventeenth Data Release of the Sloan Digital Sky Surveys: Complete Release of MaNGA, MaStar and APOGEE-2 Data

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    This paper documents the seventeenth data release (DR17) from the Sloan Digital Sky Surveys; the fifth and final release from the fourth phase (SDSS-IV). DR17 contains the complete release of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, which reached its goal of surveying over 10,000 nearby galaxies. The complete release of the MaNGA Stellar Library (MaStar) accompanies this data, providing observations of almost 30,000 stars through the MaNGA instrument during bright time. DR17 also contains the complete release of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) survey which publicly releases infra-red spectra of over 650,000 stars. The main sample from the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), as well as the sub-survey Time Domain Spectroscopic Survey (TDSS) data were fully released in DR16. New single-fiber optical spectroscopy released in DR17 is from the SPectroscipic IDentification of ERosita Survey (SPIDERS) sub-survey and the eBOSS-RM program. Along with the primary data sets, DR17 includes 25 new or updated Value Added Catalogs (VACs). This paper concludes the release of SDSS-IV survey data. SDSS continues into its fifth phase with observations already underway for the Milky Way Mapper (MWM), Local Volume Mapper (LVM) and Black Hole Mapper (BHM) surveys

    Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

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    Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

    Sloan Digital Sky Survey IV: Mapping the Milky Way, Nearby Galaxies, and the Distant Universe

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    We describe the Sloan Digital Sky Survey IV (SDSS-IV), a project encompassing three major spectroscopic programs. The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is observing hundreds of thousands of Milky Way stars at high resolution and high signal-to-noise ratios in the near-infrared. The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey is obtaining spatially resolved spectroscopy for thousands of nearby galaxies (median z0.03z\sim 0.03). The extended Baryon Oscillation Spectroscopic Survey (eBOSS) is mapping the galaxy, quasar, and neutral gas distributions between z0.6z\sim 0.6 and 3.5 to constrain cosmology using baryon acoustic oscillations, redshift space distortions, and the shape of the power spectrum. Within eBOSS, we are conducting two major subprograms: the SPectroscopic IDentification of eROSITA Sources (SPIDERS), investigating X-ray AGNs and galaxies in X-ray clusters, and the Time Domain Spectroscopic Survey (TDSS), obtaining spectra of variable sources. All programs use the 2.5 m Sloan Foundation Telescope at the Apache Point Observatory; observations there began in Summer 2014. APOGEE-2 also operates a second near-infrared spectrograph at the 2.5 m du Pont Telescope at Las Campanas Observatory, with observations beginning in early 2017. Observations at both facilities are scheduled to continue through 2020. In keeping with previous SDSS policy, SDSS-IV provides regularly scheduled public data releases; the first one, Data Release 13, was made available in 2016 July

    Sloan Digital Sky Survey IV: mapping the Milky Way, nearby galaxies, and the distant universe

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    We describe the Sloan Digital Sky Survey IV (SDSS-IV), a project encompassing three major spectroscopic programs. The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is observing hundreds of thousands of Milky Way stars at high resolution and high signal-to-noise ratios in the near-infrared. The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey is obtaining spatially resolved spectroscopy for thousands of nearby galaxies (median ). The extended Baryon Oscillation Spectroscopic Survey (eBOSS) is mapping the galaxy, quasar, and neutral gas distributions between and 3.5 to constrain cosmology using baryon acoustic oscillations, redshift space distortions, and the shape of the power spectrum. Within eBOSS, we are conducting two major subprograms: the SPectroscopic IDentification of eROSITA Sources (SPIDERS), investigating X-ray AGNs and galaxies in X-ray clusters, and the Time Domain Spectroscopic Survey (TDSS), obtaining spectra of variable sources. All programs use the 2.5 m Sloan Foundation Telescope at the Apache Point Observatory; observations there began in Summer 2014. APOGEE-2 also operates a second near-infrared spectrograph at the 2.5 m du Pont Telescope at Las Campanas Observatory, with observations beginning in early 2017. Observations at both facilities are scheduled to continue through 2020. In keeping with previous SDSS policy, SDSS-IV provides regularly scheduled public data releases; the first one, Data Release 13, was made available in 2016 July
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