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Institution

University of Dundee

EducationDundee, United Kingdom
About: University of Dundee is a education organization based out in Dundee, United Kingdom. It is known for research contribution in the topics: Population & Protein kinase A. The organization has 19258 authors who have published 39640 publications receiving 1919433 citations. The organization is also known as: Universitas Dundensis & Dundee University.


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Journal ArticleDOI
TL;DR: The roles of the transition metals in redox catalysts can in broad terms be related to their redox chemistry and to their availability to organisms at the time when the pathways evolved.
Abstract: Iron is the quantitatively most important trace metal involved in thylakoid reactions of all oxygenic organisms since linear (= non-cyclic) electron flow from H2O to NADP+ involves PS II (2–3 Fe), cytochrome b6-f (5 Fe), PS I (12 Fe), and ferredoxin (2 Fe); (replaceable by metal-free flavodoxin in certain cyanobacteria and algae under iron deficiency). Cytochrome c6 (1 Fe) is the only redox catalyst linking the cytochrome b6-f complex to PS I in most algae; in many cyanobacteria and Chlorophyta cytochrome c6 and the copper-containing plastocyanin are alternatives, with the availability of iron and copper regulating their relative expression, while higher plants only have plastocyanin. Iron, copper and zinc occur in enzymes that remove active oxygen species and that are in part bound to the thylakoid membrane. These enzymes are ascorbate peroxidase (Fe) and iron-(cyanobacteria, and most al gae) and copper-zinc- (some algae; higher plants) superoxide dismutase. Iron-containing NAD(P)H-PQ oxidoreductase in thylakoids of cyanobacteria and many eukaryotes may be involved in cyclic electron transport around PS I and in chlororespiration. Manganese is second to iron in its quantitative role in the thylakoids, with four Mn (and 1 Ca) per PS II involved in O2 evolution. The roles of the transition metals in redox catalysts can in broad terms be related to their redox chemistry and to their availability to organisms at the time when the pathways evolved. The quantitative roles of these trace metals varies genotypically (e.g. the greater need for iron in thylakoid reactions of cyanobacteria and rhodophytes than in other O2-evolvers as a result of their lower PS II:PS I ratio) and phenotypically (e.g. as a result of variations in PS II:PS I ratio with the spectral quality of incident radiation).

605 citations

Journal ArticleDOI
28 Mar 2016-RNA
TL;DR: For future RNA-seq experiments, results suggest that at least six biological replicates should be used, rising to at least 12 when it is important to identify SDE genes for all fold changes, and if fewer than 12 replicates are used, a superior combination of true positive and false positive performances makes edgeR and DESeq2 the leading tools.
Abstract: RNA-seq is now the technology of choice for genome-wide differential gene expression experiments, but it is not clear how many biological replicates are needed to ensure valid biological interpretation of the results or which statistical tools are best for analyzing the data. An RNA-seq experiment with 48 biological replicates in each of two conditions was performed to answer these questions and provide guidelines for experimental design. With three biological replicates, nine of the 11 tools evaluated found only 20%–40% of the significantly differentially expressed (SDE) genes identified with the full set of 42 clean replicates. This rises to >85% for the subset of SDE genes changing in expression by more than fourfold. To achieve >85% for all SDE genes regardless of fold change requires more than 20 biological replicates. The same nine tools successfully control their false discovery rate at ≲5% for all numbers of replicates, while the remaining two tools fail to control their FDR adequately, particularly for low numbers of replicates. For future RNA-seq experiments, these results suggest that at least six biological replicates should be used, rising to at least 12 when it is important to identify SDE genes for all fold changes. If fewer than 12 replicates are used, a superior combination of true positive and false positive performances makes edgeR and DESeq2 the leading tools. For higher replicate numbers, minimizing false positives is more important and DESeq marginally outperforms the other tools.

605 citations

Journal ArticleDOI
01 Aug 1984-Nature
TL;DR: The basal ganglia of mammalian brain contain a region-specific neuronal phosphoprotein that is a protein phosphatase inhibitor, and like inhibitor-110, DARPP-32 is effective as an inhibitor in its phosphorylated but not its dephosphorylated form.
Abstract: The neurotransmitter dopamine has been demonstrated by biochemical, histochemical and immunocytochemical techniques to be unevenly distributed in the mammalian central nervous system. DARPP-32 (dopamine- and cyclic-AMP-regulated phosphoprotein of molecular weight 32,000) is a neuronal phosphoprotein that displays a regional distribution in the mammalian brain very similar to that of dopamine-containing nerve terminals, being highly concentrated in the basal ganglia. The state of phosphorylation of DARPP-32 can be regulated by dopamine and by cyclic AMP in intact nerve cells, suggesting a role for this phosphoprotein in mediating certain of the effects of dopamine on dopaminoceptive cells. The observation that many of the physical and chemical properties of purified DARPP-32 resemble those of phosphatase inhibitor-1 (inhibitor-1), a widely distributed inhibitor of protein phosphatase-1, suggests that DARPP-32 might also function as a phosphatase inhibitor. We report here that DARPP-32 inhibits protein phosphatase-1 at nanomolar concentrations. Moreover, like inhibitor-1, DARPP-32 is effective as an inhibitor in its phosphorylated but not its dephosphorylated form. Thus, the basal ganglia of mammalian brain contain a region-specific neuronal phosphoprotein that is a protein phosphatase inhibitor.

604 citations

Journal ArticleDOI
Robert A. Scott1, Laura J. Scott2, Reedik Mägi3, Letizia Marullo4  +213 moreInstitutions (66)
01 Nov 2017-Diabetes
TL;DR: This article conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel.
Abstract: To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects) We identified 13 novel T2D-associated loci (P < 5 × 10-8), including variants near the GLP2R, GIP, and HLA-DQA1 genes Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action-associated loci These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology

601 citations


Authors

Showing all 19404 results

NameH-indexPapersCitations
Matthias Mann221887230213
Mark I. McCarthy2001028187898
Stefan Schreiber1781233138528
Kenneth C. Anderson1781138126072
Masayuki Yamamoto1711576123028
Salvador Moncada164495138030
Jorge E. Cortes1632784124154
Andrew P. McMahon16241590650
Philip Cohen154555110856
Dirk Inzé14964774468
Andrew T. Hattersley146768106949
Antonio Lanzavecchia145408100065
Kim Nasmyth14229459231
David Price138168793535
Dario R. Alessi13635474753
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202361
2022205
20211,653
20201,520
20191,473
20181,524