http://www.cell.com/abstract/S0092-8674(07)01476-6
Genome-wide high-resolution mapping of exosome substrates reveals hidden features in the
Arabidopsis transcriptome
Cell 2007 Dec 28;131(7):1340-53
Chekanova JA, Gregory BD, Reverdatto SV, Chen H, Kumar R, Hooker T, Yazaki J, Li P,
Skiba N, Peng Q, Alonso J, Brukhin V, Grossniklaus U, Ecker JR, Belostotsky DA
School of Biological Sciences, University of Missouri-Kansas City, Kansas City, MO 64110,
USA
The exosome complex plays a central and essential role in RNA metabolism. However,
comprehensive studies of exosome substrates and functional analyses of its subunits are
lacking. Here, we demonstrate that as opposed to yeast and metazoans the plant exosome
core possesses an unanticipated functional plasticity and present a genome-wide atlas of
Arabidopsis exosome targets. Additionally, our study provides evidence for widespread
polyadenylation- and exosome-mediated RNA quality control in plants, reveals unexpected
aspects of stable structural RNA metabolism, and uncovers numerous novel exosome
substrates. These include a select subset of mRNAs, miRNA processing intermediates, and
hundreds of noncoding RNAs, the vast majority of which have not been previously described
and belong to a layer of the transcriptome that can only be visualized upon inhibition of
exosome activity. These first genome-wide maps of exosome substrates will aid in illuminating
new fundamental components and regulatory mechanisms of eukaryotic transcriptomes.
----------------------------------------------------------------------------------------------------------------------
http://www.nature.com/nature/journal/v446/n7137/abs/nature05649.html
Functional dissection of protein complexes involved in yeast chromosome biology using a
genetic interaction map
Nature 2007 Apr 12;446(7137):806-10
Collins SR, Miller KM, Maas NL, Roguev A, Fillingham J, Chu CS, Schuldiner M, Gebbia M,
Recht J, Shales M, Ding H, Xu H, Han J, Ingvarsdottir K, Cheng B, Andrews B, Boone C,
Berger SL, Hieter P, Zhang Z, Brown GW, Ingles CJ, Emili A, Allis CD, Toczyski DP, Weissman
JS, Greenblatt JF, Krogan NJ
Department of Cellular and Molecular Pharmacology, University of California, San Francisco,
California 94158, USA
Defining the functional relationships between proteins is critical for understanding virtually all
aspects of cell biology. Large-scale identification of protein complexes has provided one
important step towards this goal; however, even knowledge of the stoichiometry, affinity and
lifetime of every protein-protein interaction would not reveal the functional relationships
between and within such complexes. Genetic interactions can provide functional information
that is largely invisible to protein-protein interaction data sets. Here we present an epistatic
miniarray profile (E-MAP) consisting of quantitative pairwise measurements of the genetic
interactions between 743 Saccharomyces cerevisiae genes involved in various aspects of
chromosome biology (including DNA replication/repair, chromatid segregation and
transcriptional regulation). This E-MAP reveals that physical interactions fall into two
well-represented classes distinguished by whether or not the individual proteins act
coherently to carry out a common function. Thus, genetic interaction data make it possible to
dissect functionally multi-protein complexes, including Mediator, and to organize distinct
protein complexes into pathways. In one pathway defined here, we show that Rtt109 is the
founding member of a novel class of histone acetyltransferases responsible for
Asf1-dependent acetylation of histone H3 on lysine 56. This modification, in turn, enables a
ubiquitin ligase complex containing the cullin Rtt101 to ensure genomic integrity during DNA
replication.
----------------------------------------------------------------------------------------------------------------------
http://www.nature.com/nmeth/journal/v4/n10/abs/nmeth1098.html
High-throughput genetic interaction mapping in the fission yeast Schizosaccharomyces pombe
Nat Methods 2007 Oct;4(10):861-6
Roguev A, Wiren M, Weissman JS, Krogan NJ
Department of Cellular and Molecular Pharmacology, University of California, San Francisco,
1700 4th Street San Francisco, California 94158, USA.
Epistasis analysis, which reports on the extent to which the function of one gene depends on
the presence of a second, is a powerful tool for studying the functional organization of the
cell. Systematic genome-wide studies of epistasis, however, have been limited, with the
majority of data being collected in the budding yeast, Saccharomyces cerevisiae. Here we
present two 'pombe epistasis mapper' strategies, PEM-1 and PEM-2, which allow for
high-throughput double mutant generation in the fission yeast, S. pombe. These approaches
take advantage of a previously undescribed, recessive, cycloheximide-resistance mutation.
Both systems can be used for genome-wide screens or for the generation of high-density,
quantitative epistatic miniarray profiles (E-MAPs). Since S. cerevisiae and S. pombe are
evolutionary distant, this methodology will provide insight into conserved biological pathways
that are present in S. pombe, but not S. cerevisiae, and will enable a comprehensive analysis
of the conservation of genetic interaction networks.
----------------------------------------------------------------------------------------------------------------------
http://www.ploscompbiol.org/article/info:doi%2F10.1371%2Fjournal.pcbi.1000065
Functional maps of protein complexes from quantitative genetic interaction data.
PLoS Comput Biol. 2008 Apr 18;4(4):e1000065
Bandyopadhyay S, Kelley R, Krogan NJ, Ideker T.
Program in Bioinformatics, University of California San Diego, La Jolla, California, United
States of America
Recently, a number of advanced screening technologies have allowed for the comprehensive
quantification of aggravating and alleviating genetic interactions among gene pairs. In
parallel, TAP-MS studies (tandem affinity purification followed by mass spectroscopy) have
been successful at identifying physical protein interactions that can indicate proteins
participating in the same molecular complex. Here, we propose a method for the joint learning
of protein complexes and their functional relationships by integration of quantitative genetic
interactions and TAP-MS data. Using 3 independent benchmark datasets, we demonstrate
that this method is >50% more accurate at identifying functionally related protein pairs than
previous approaches. Application to genes involved in yeast chromosome organization
identifies a functional map of 91 multimeric complexes, a number of which are novel or have
been substantially expanded by addition of new subunits. Interestingly, we find that complexes
that are enriched for aggravating genetic interactions (i.e., synthetic lethality) are more likely
to contain essential genes, linking each of these interactions to an underlying mechanism.
These results demonstrate the importance of both large-scale genetic and physical
interaction data in mapping pathway architecture and function.
Genome-wide high-resolution mapping of exosome substrates reveals hidden features in the
Arabidopsis transcriptome
Cell 2007 Dec 28;131(7):1340-53
Chekanova JA, Gregory BD, Reverdatto SV, Chen H, Kumar R, Hooker T, Yazaki J, Li P,
Skiba N, Peng Q, Alonso J, Brukhin V, Grossniklaus U, Ecker JR, Belostotsky DA
School of Biological Sciences, University of Missouri-Kansas City, Kansas City, MO 64110,
USA
The exosome complex plays a central and essential role in RNA metabolism. However,
comprehensive studies of exosome substrates and functional analyses of its subunits are
lacking. Here, we demonstrate that as opposed to yeast and metazoans the plant exosome
core possesses an unanticipated functional plasticity and present a genome-wide atlas of
Arabidopsis exosome targets. Additionally, our study provides evidence for widespread
polyadenylation- and exosome-mediated RNA quality control in plants, reveals unexpected
aspects of stable structural RNA metabolism, and uncovers numerous novel exosome
substrates. These include a select subset of mRNAs, miRNA processing intermediates, and
hundreds of noncoding RNAs, the vast majority of which have not been previously described
and belong to a layer of the transcriptome that can only be visualized upon inhibition of
exosome activity. These first genome-wide maps of exosome substrates will aid in illuminating
new fundamental components and regulatory mechanisms of eukaryotic transcriptomes.
----------------------------------------------------------------------------------------------------------------------
http://www.nature.com/nature/journal/v446/n7137/abs/nature05649.html
Functional dissection of protein complexes involved in yeast chromosome biology using a
genetic interaction map
Nature 2007 Apr 12;446(7137):806-10
Collins SR, Miller KM, Maas NL, Roguev A, Fillingham J, Chu CS, Schuldiner M, Gebbia M,
Recht J, Shales M, Ding H, Xu H, Han J, Ingvarsdottir K, Cheng B, Andrews B, Boone C,
Berger SL, Hieter P, Zhang Z, Brown GW, Ingles CJ, Emili A, Allis CD, Toczyski DP, Weissman
JS, Greenblatt JF, Krogan NJ
Department of Cellular and Molecular Pharmacology, University of California, San Francisco,
California 94158, USA
Defining the functional relationships between proteins is critical for understanding virtually all
aspects of cell biology. Large-scale identification of protein complexes has provided one
important step towards this goal; however, even knowledge of the stoichiometry, affinity and
lifetime of every protein-protein interaction would not reveal the functional relationships
between and within such complexes. Genetic interactions can provide functional information
that is largely invisible to protein-protein interaction data sets. Here we present an epistatic
miniarray profile (E-MAP) consisting of quantitative pairwise measurements of the genetic
interactions between 743 Saccharomyces cerevisiae genes involved in various aspects of
chromosome biology (including DNA replication/repair, chromatid segregation and
transcriptional regulation). This E-MAP reveals that physical interactions fall into two
well-represented classes distinguished by whether or not the individual proteins act
coherently to carry out a common function. Thus, genetic interaction data make it possible to
dissect functionally multi-protein complexes, including Mediator, and to organize distinct
protein complexes into pathways. In one pathway defined here, we show that Rtt109 is the
founding member of a novel class of histone acetyltransferases responsible for
Asf1-dependent acetylation of histone H3 on lysine 56. This modification, in turn, enables a
ubiquitin ligase complex containing the cullin Rtt101 to ensure genomic integrity during DNA
replication.
----------------------------------------------------------------------------------------------------------------------
http://www.nature.com/nmeth/journal/v4/n10/abs/nmeth1098.html
High-throughput genetic interaction mapping in the fission yeast Schizosaccharomyces pombe
Nat Methods 2007 Oct;4(10):861-6
Roguev A, Wiren M, Weissman JS, Krogan NJ
Department of Cellular and Molecular Pharmacology, University of California, San Francisco,
1700 4th Street San Francisco, California 94158, USA.
Epistasis analysis, which reports on the extent to which the function of one gene depends on
the presence of a second, is a powerful tool for studying the functional organization of the
cell. Systematic genome-wide studies of epistasis, however, have been limited, with the
majority of data being collected in the budding yeast, Saccharomyces cerevisiae. Here we
present two 'pombe epistasis mapper' strategies, PEM-1 and PEM-2, which allow for
high-throughput double mutant generation in the fission yeast, S. pombe. These approaches
take advantage of a previously undescribed, recessive, cycloheximide-resistance mutation.
Both systems can be used for genome-wide screens or for the generation of high-density,
quantitative epistatic miniarray profiles (E-MAPs). Since S. cerevisiae and S. pombe are
evolutionary distant, this methodology will provide insight into conserved biological pathways
that are present in S. pombe, but not S. cerevisiae, and will enable a comprehensive analysis
of the conservation of genetic interaction networks.
----------------------------------------------------------------------------------------------------------------------
http://www.ploscompbiol.org/article/info:doi%2F10.1371%2Fjournal.pcbi.1000065
Functional maps of protein complexes from quantitative genetic interaction data.
PLoS Comput Biol. 2008 Apr 18;4(4):e1000065
Bandyopadhyay S, Kelley R, Krogan NJ, Ideker T.
Program in Bioinformatics, University of California San Diego, La Jolla, California, United
States of America
Recently, a number of advanced screening technologies have allowed for the comprehensive
quantification of aggravating and alleviating genetic interactions among gene pairs. In
parallel, TAP-MS studies (tandem affinity purification followed by mass spectroscopy) have
been successful at identifying physical protein interactions that can indicate proteins
participating in the same molecular complex. Here, we propose a method for the joint learning
of protein complexes and their functional relationships by integration of quantitative genetic
interactions and TAP-MS data. Using 3 independent benchmark datasets, we demonstrate
that this method is >50% more accurate at identifying functionally related protein pairs than
previous approaches. Application to genes involved in yeast chromosome organization
identifies a functional map of 91 multimeric complexes, a number of which are novel or have
been substantially expanded by addition of new subunits. Interestingly, we find that complexes
that are enriched for aggravating genetic interactions (i.e., synthetic lethality) are more likely
to contain essential genes, linking each of these interactions to an underlying mechanism.
These results demonstrate the importance of both large-scale genetic and physical
interaction data in mapping pathway architecture and function.
Arabidopsis 2010 Program:
Supported by the National Science Foundation
Supported by the National Science Foundation
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