Oregon State University

About: Oregon State University is a education organization based out in Corvallis, Oregon, United States. It is known for research contribution in the topics: Population & Gene. The organization has 28192 authors who have published 64044 publications receiving 2634108 citations. The organization is also known as: Oregon Agricultural College & OSU.

Snowball Earth climate dynamics and Cryogenian geology-geobiology

Abstract: Geological evidence indicates that grounded ice sheets reached sea level at all latitudes during two long-lived Cryogenian (58 and ≥5 My) glaciations. Combined uranium-lead and rhenium-osmium dating suggests that the older (Sturtian) glacial onset and both terminations were globally synchronous. Geochemical data imply that CO2 was 102 PAL (present atmospheric level) at the younger termination, consistent with a global ice cover. Sturtian glaciation followed breakup of a tropical supercontinent, and its onset coincided with the equatorial emplacement of a large igneous province. Modeling shows that the small thermal inertia of a globally frozen surface reverses the annual mean tropical atmospheric circulation, producing an equatorial desert and net snow and frost accumulation elsewhere. Oceanic ice thickens, forming a sea glacier that flows gravitationally toward the equator, sustained by the hydrologic cycle and by basal freezing and melting. Tropical ice sheets flow faster as CO2 rises but lose mass and become sensitive to orbital changes. Equatorial dust accumulation engenders supraglacial oligotrophic meltwater ecosystems, favorable for cyanobacteria and certain eukaryotes. Meltwater flushing through cracks enables organic burial and submarine deposition of airborne volcanic ash. The subglacial ocean is turbulent and well mixed, in response to geothermal heating and heat loss through the ice cover, increasing with latitude. Terminal carbonate deposits, unique to Cryogenian glaciations, are products of intense weathering and ocean stratification. Whole-ocean warming and collapsing peripheral bulges allow marine coastal flooding to continue long after ice-sheet disappearance. The evolutionary legacy of Snowball Earth is perceptible in fossils and living organisms.

Genome-wide discovery and characterization of maize long non-coding RNAs

Abstract: Background: Long non-coding RNAs (lncRNAs) are transcripts that are 200 bp or longer, do not encode proteins, and potentially play important roles in eukaryotic gene regulation. However, the number, characteristics and expression inheritance pattern of lncRNAs in maize are still largely unknown. Results: By exploiting available public EST databases, maize whole genome sequence annotation and RNA-seq datasets from 30 different experiments, we identified 20,163 putative lncRNAs. Of these lncRNAs, more than 90% are predicted to be the precursors of small RNAs, while 1,704 are considered to be high-confidence lncRNAs. High confidence lncRNAs have an average transcript length of 463 bp and genes encoding them contain fewer exons than annotated genes. By analyzing the expression pattern of these lncRNAs in 13 distinct tissues and 105 maize recombinant inbred lines, we show that more than 50% of the high confidence lncRNAs are expressed in a tissue-specific manner, a result that is supported by epigenetic marks. Intriguingly, the inheritance of lncRNA expression patterns in 105 recombinant inbred lines reveals apparent transgressive segregation, and maize lncRNAs are less affected by cis- than by trans-genetic factors. Conclusions: We integrate all available transcriptomic datasets to identify a comprehensive set of maize lncRNAs, provide a unique annotation resource of the maize genome and a genome-wide characterization of maize lncRNAs, and explore the genetic control of their expression using expression quantitative trait locus mapping. Background While the central dogma defines the primary role for RNA as a messenger molecule in the process of gene expression, there is ample evidence for additional functions of RNA molecules. These RNA molecules include small nuclear RNAs (snRNAs), small nucleolar RNAs (snoRNAs; mainly tRNAs and rRNAs), signal recognition particle (7SL/SRP) RNAs, microRNAs (miRNAs), small interfering RNAs (siRNAs), piwi RNAs (piRNAs) and trans-acting siRNAs (ta-siRNAs), natural cis-acting siRNAs and long noncoding RNAs (lncRNAs). lncRNAs have been arbitrarily defined as non-protein coding RNAs more than 200 bp in length, distinguishing them from short noncoding RNAs such as miRNAs and

Oxidation of LDL by Myeloperoxidase and Reactive Nitrogen Species Reaction Pathways and Antioxidant Protection

Abstract: Oxidative modification of low density lipoprotein (LDL) appears to play an important role in atherogenesis Although the precise mechanisms of LDL oxidation in vivo are unknown, several lines of evidence implicate myeloperoxidase and reactive nitrogen species, in addition to ceruloplasmin and 15-lipoxygenase Myeloperoxidase generates a number of reactive species, including hypochlorous acid, chloramines, tyrosyl radicals, and nitrogen dioxide These reactive species oxidize the protein, lipid, and antioxidant components of LDL Modification of apolipoprotein B results in enhanced uptake of LDL by macrophages with subsequent formation of lipid-laden foam cells Nitric oxide synthases produce nitric oxide and, under certain conditions, superoxide radicals Numerous other sources of superoxide radicals have been identified in the arterial wall, including NAD(P)H oxidases and xanthine oxidase Nitric oxide and superoxide readily combine to form peroxynitrite, a reactive nitrogen species capable of modifying LDL In this review, we examine the reaction pathways involved in LDL oxidation by myeloperoxidase and reactive nitrogen species and the potential protective effects of the antioxidant vitamins C and E

Resolving the paradox of stasis: models with stabilizing selection explain evolutionary divergence on all timescales.

Abstract: We tested the ability of six quantitative genetic models to explain the evolution of phenotypic means using an extensive database compiled by Gingerich. Our approach differs from past efforts in that we use explicit models of evolutionary process, with parameters estimated from contemporary populations, to analyze a large sample of divergence data on many different timescales. We show that one quantitative genetic model yields a good fit to data on phenotypic divergence across timescales ranging from a few generations to 10 million generations. The key feature of this model is a fitness optimum that moves within fixed limits. Conversely, a model of neutral evolution, models with a stationary optimum that undergoes Brownian or white noise motion, a model with a moving optimum, and a peak shift model all fail to account for the data on most or all timescales. We discuss our results within the framework of Simpson's concept of adaptive landscapes and zones. Our analysis suggests that the underlying process causing phenotypic stasis is adaptation to an optimum that moves within an adaptive zone with stable boundaries. We discuss the implication of our results for comparative studies and phylogeny inference based on phenotypic characters.