Publications of J. Muller
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2012 1 publication(s).
11.
eggNOG v3.0: orthologous groups covering 1133 organisms at 41 different taxonomic ranges.
Powell S, Szklarczyk D, Trachana K, Roth A, Kuhn M, Muller J, Arnold R, Rattei T, Letunic I, Doerks T, Jensen LJ, von Mering C, Bork P
2012 Jan 1; 40: D284-9. Epub 2011 Nov 16; PubMed: 22096231.
Abstract + PDFOrthologous relationships form the basis of most comparative genomic and metagenomic studies and are essential for proper phylogenetic and functional analyses. The third version of the eggNOG database (http://eggnog.embl.de) contains non-supervised orthologous groups constructed from 1133 organisms, doubling the number of genes with orthology assignment compared to eggNOG v2. The new release is the result of a number of improvements and expansions: (i) the underlying homology searches are now based on the SIMAP database; (ii) the orthologous groups have been extended to 41 levels of selected taxonomic ranges enabling much more fine-grained orthology assignments; and (iii) the newly designed web page is considerably faster with more functionality. In total, eggNOG v3 contains 721 801 orthologous groups, encompassing a total of 4 396 591 genes. Additionally, we updated 4873 and 4850 original COGs and KOGs, respectively, to include all 1133 organisms. At the universal level, covering all three domains of life, 101 208 orthologous groups are available, while the others are applicable at 40 more limited taxonomic ranges. Each group is amended by multiple sequence alignments and maximum-likelihood trees and broad functional descriptions are provided for 450 904 orthologous groups (62.5%).
2011 4 publication(s).
10.
The ecoresponsive genome of Daphnia pulex.
Colbourne JK, Pfrender ME, Gilbert D, Thomas WK, Tucker A, Oakley TH, Tokishita S, Aerts A, Arnold GJ, Basu MK, Bauer DJ, Cáceres CE, Carmel L, Casola C, Choi JH, Detter JC, Dong Q, Dusheyko S, Eads BD, Fröhlich T, Geiler-Samerotte KA, Gerlach D, Hatcher P, Jogdeo S, Krijgsveld J, Kriventseva EV, Kültz D, Laforsch C, Lindquist E, Lopez J, Manak JR, Muller J, Pangilinan J, Patwardhan RP, Pitluck S, Pritham EJ, Rechtsteiner A, Rho M, Rogozin IB, Sakarya O, Salamov A, Schaack S, Shapiro H, Shiga Y, Skalitzky C, Smith Z, Souvorov A, Sung W, Tang Z, Tsuchiya D, Tu H, Vos H, Wang M, Wolf YI, Yamagata H, Yamada T, Ye Y, Shaw JR, Andrews J, Crease TJ, Tang H, Lucas SM, Robertson HM, Bork P, Koonin EV, Zdobnov EM, Grigoriev IV, Lynch M, Boore JL
Abstract + PDFWe describe the draft genome of the microcrustacean Daphnia pulex, which is only 200 megabases and contains at least 30,907 genes. The high gene count is a consequence of an elevated rate of gene duplication resulting in tandem gene clusters. More than a third of Daphnia's genes have no detectable homologs in any other available proteome, and the most amplified gene families are specific to the Daphnia lineage. The coexpansion of gene families interacting within metabolic pathways suggests that the maintenance of duplicated genes is not random, and the analysis of gene expression under different environmental conditions reveals that numerous paralogs acquire divergent expression patterns soon after duplication. Daphnia-specific genes, including many additional loci within sequenced regions that are otherwise devoid of annotations, are the most responsive genes to ecological challenges.
9.
Identifying single copy orthologs in metazoa.
2011 Dec; 7(12): e1002269. PubMed: 22144877.
Abstract + PDFThe identification of single copy (1-to-1) orthologs in any group of organisms is important for functional classification and phylogenetic studies. The Metazoa are no exception, but only recently has there been a wide-enough distribution of taxa with sufficiently high quality sequenced genomes to gain confidence in the wide-spread single copy status of a gene.Here, we present a phylogenetic approach for identifying overlooked single copy orthologs from multigene families and apply it to the Metazoa. Using 18 sequenced metazoan genomes of high quality we identified a robust set of 1,126 orthologous groups that have been retained in single copy since the last common ancestor of Metazoa. We found that the use of the phylogenetic procedure increased the number of single copy orthologs found by over a third more than standard taxon-count approaches. The orthologs represented a wide range of functional categories, expression profiles and levels of divergence.To demonstrate the value of our set of single copy orthologs, we used them to assess the completeness of 24 currently published metazoan genomes and 62 EST datasets. We found that the annotated genes in published genomes vary in coverage from 79% (Ciona intestinalis) to 99.8% (human) with an average of 92%, suggesting a value for the underlying error rate in genome annotation, and a strategy for identifying single copy orthologs in larger datasets. In contrast, the vast majority of EST datasets with no corresponding genome sequence available are largely under-sampled and probably do not accurately represent the actual genomic complement of the organisms from which they are derived.
8.
The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored.
Szklarczyk D, Franceschini A, Kuhn M, Simonovic M, Roth A, Minguez P, Doerks T, Stark M, Muller J, Bork P, Jensen LJ, von Mering C
2011 Jan 2; 39: D561-8. Epub 2010 Nov 2; PubMed: 21045058.
Abstract + PDFAn essential prerequisite for any systems-level understanding of cellular functions is to correctly uncover and annotate all functional interactions among proteins in the cell. Toward this goal, remarkable progress has been made in recent years, both in terms of experimental measurements and computational prediction techniques. However, public efforts to collect and present protein interaction information have struggled to keep up with the pace of interaction discovery, partly because protein-protein interaction information can be error-prone and require considerable effort to annotate. Here, we present an update on the online database resource Search Tool for the Retrieval of Interacting Genes (STRING); it provides uniquely comprehensive coverage and ease of access to both experimental as well as predicted interaction information. Interactions in STRING are provided with a confidence score, and accessory information such as protein domains and 3D structures is made available, all within a stable and consistent identifier space. New features in STRING include an interactive network viewer that can cluster networks on demand, updated on-screen previews of structural information including homology models, extensive data updates and strongly improved connectivity and integration with third-party resources. Version 9.0 of STRING covers more than 1100 completely sequenced organisms; the resource can be reached at http://string-db.org.
7.
Orthology prediction methods: A quality assessment using curated protein families.
Abstract + PDFThe increasing number of sequenced genomes has prompted the development of several automated orthology prediction methods. Tests to evaluate the accuracy of predictions and to explore biases caused by biological and technical factors are therefore required. We used 70 manually curated families to analyze the performance of five public methods in Metazoa. We analyzed the strengths and weaknesses of the methods and quantified the impact of biological and technical challenges. From the latter part of the analysis, genome annotation emerged as the largest single influencer, affecting up to 30% of the performance. Generally, most methods did well in assigning orthologous group but they failed to assign the exact number of genes for half of the groups. The publicly available benchmark set (http://eggnog.embl.de/orthobench/) should facilitate the improvement of current orthology assignment protocols, which is of utmost importance for many fields of biology and should be tackled by a broad scientific community.
2010 3 publication(s).
6.
AQUA: Automated quality improvement for multiple sequence alignments.
2010 Jan 15; 26(2): 263-5. Epub 2009 Nov 19; PubMed: 19926669.
Abstract + PDFSUMMARY: Multiple Sequence Alignment (MSA) is a central tool in most modern biology studies. However, despite generations of valuable tools, human experts are still able to improve automatically generated MSAs. In an effort to automatically identify the most reliable MSA for a given protein family, we propose a very simple protocol, named AQUA for "Automated quality improvement for multiple sequence alignments". Our current implementation relies on 2 alignment programs (MUSCLE and MAFFT), one refinement program (RASCAL) and one assessment program (NORMD) but other programs could be incorporated at any of the 3 steps. AVAILABILITY: AQUA is implemented in Tcl/Tk and runs in command line on all platforms. The source code is available under the GNU GPL license. Source code, README and Supplementary data are available at http://www.bork.embl.de/Docu/AQUA. CONTACT: muller@embl.de, bork@embl.de.
5.
eggNOG v2.0: extending the evolutionary genealogy of genes with enhanced non-supervised orthologous groups, species and functional annotations.
Muller J, Szklarczyk D, Julien P, Letunic I, Roth A, Kuhn M, Powell S, von Mering C, Doerks T, Jensen LJ, Bork P
2010 Jan 9; 38: D190-5. Epub 2009 Nov 9; PubMed: 19900971.
Abstract + PDFThe identification of orthologous relationships forms the basis for most comparative genomics studies. Here, we present the second version of the eggNOG database, which contains orthologous groups (OGs) constructed through identification of reciprocal best BLAST matches and triangular linkage clustering. We applied this procedure to 630 complete genomes (529 bacteria, 46 archaea and 55 eukaryotes), which is a 2-fold increase relative to the previous version. The pipeline yielded 224 847 OGs, including 9724 extended versions of the original COG and KOG. We computed OGs for different levels of the tree of life; in addition to the species groups included in our first release (i.e. fungi, metazoa, insects, vertebrates and mammals), we have now constructed OGs for archaea, fishes, rodents and primates. We automatically annotate the non-supervised orthologous groups (NOGs) with functional descriptions, protein domains, and functional categories as defined initially for the COG/KOG database. In-depth analysis is facilitated by precomputed high-quality multiple sequence alignments and maximum-likelihood trees for each of the available OGs. Altogether, eggNOG covers 2 242 035 proteins (built from 2 590 259 proteins) and provides a broad functional description for at least 1 966 709 (88%) of them. Users can access the complete set of orthologous groups via a web interface at: http://eggnog.embl.de.
4.
Functional and evolutionary insights from the genomes of three parasitoid Nasonia species.
Nasonia Genome Working Group , Werren JH, Richards S, Desjardins CA, Niehuis O, Gadau J, Colbourne JK, Beukeboom LW, Desplan C, Elsik CG, Grimmelikhuijzen CJ, Kitts P, Lynch JA, Murphy T, Oliveira DC, Smith CD, van de Zande L, Worley KC, Zdobnov EM, Aerts M, Albert S, Anaya VH, Anzola JM, Barchuk AR, Behura SK, Bera AN, Berenbaum MR, Bertossa RC, Bitondi MM, Bordenstein SR, Bork P, Bornberg-Bauer E, Brunain M, Cazzamali G, Chaboub L, Chacko J, Chavez D, Childers CP, Choi JH, Clark ME, Claudianos C, Clinton RA, Cree AG, Cristino AS, Dang PM, Darby AC, de Graaf DC, Devreese B, Dinh HH, Edwards R, Elango N, Elhaik E, Ermolaeva O, Evans JD, Foret S, Fowler GR, Gerlach D, Gibson JD, Gilbert DG, Graur D, Gründer S, Hagen DE, Han Y, Hauser F, Hultmark D, Hunter HC, Hurst GD, Jhangian SN, Jiang H, Johnson RM, Jones AK, Junier T, Kadowaki T, Kamping A, Kapustin Y, Kechavarzi B, Kim J, Kim J, Kiryutin B, Koevoets T, Kovar CL, Kriventseva EV, Kucharski R, Lee H, Lee SL, Lees K, Lewis LR, Loehlin DW, Logsdon JM, Lopez JA, Lozado RJ, Maglott D, Maleszka R, Mayampurath A, Mazur DJ, McClure MA, Moore AD, Morgan MB, Muller J, Munoz-Torres MC, Muzny DM, Nazareth LV, Neupert S, Nguyen NB, Nunes FM, Oakeshott JG, Okwuonu GO, Pannebakker BA, Pejaver VR, Peng Z, Pratt SC, Predel R, Pu LL, Ranson H, Raychoudhury R, Rechtsteiner A, Reese JT, Reid JG, Riddle M, Robertson HM, Romero-Severson J, Rosenberg M, Sackton TB, Sattelle DB, Schlüns H, Schmitt T, Schneider M, Schüler A, Schurko AM, Shuker DM, Simões ZL, Sinha S, Smith Z, Solovyev V, Souvorov A, Springauf A, Stafflinger E, Stage DE, Stanke M, Tanaka Y, Telschow A, Trent C, Vattathil S, Verhulst EC, Viljakainen L, Wanner KW, Waterhouse RM, Whitfield JB, Wilkes TE, Williamson M, Willis JH, Wolschin F, Wyder S, Yamada T, Yi SV, Zecher CN, Zhang L, Gibbs RA
Abstract + PDFWe report here genome sequences and comparative analyses of three closely related parasitoid wasps: Nasonia vitripennis, N. giraulti, and N. longicornis. Parasitoids are important regulators of arthropod populations, including major agricultural pests and disease vectors, and Nasonia is an emerging genetic model, particularly for evolutionary and developmental genetics. Key findings include the identification of a functional DNA methylation tool kit; hymenopteran-specific genes including diverse venoms; lateral gene transfers among Pox viruses, Wolbachia, and Nasonia; and the rapid evolution of genes involved in nuclear-mitochondrial interactions that are implicated in speciation. Newly developed genome resources advance Nasonia for genetic research, accelerate mapping and cloning of quantitative trait loci, and will ultimately provide tools and knowledge for further increasing the utility of parasitoids as pest insect-control agents.
2009 1 publication(s).
3.
STRING 8--a global view on proteins and their functional interactions in 630 organisms.
Jensen LJ, Kuhn M, Stark M, Chaffron S, Creevey CJ, Muller J, Doerks T, Julien P, Roth A, Simonovic M, Bork P, von Mering C
2009 Jan 21; 37: D412-6. Epub 2008 Oct 21; PubMed: 18940858.
Abstract + PDFFunctional partnerships between proteins are at the core of complex cellular phenotypes, and the networks formed by interacting proteins provide researchers with crucial scaffolds for modeling, data reduction and annotation. STRING is a database and web resource dedicated to protein-protein interactions, including both physical and functional interactions. It weights and integrates information from numerous sources, including experimental repositories, computational prediction methods and public text collections, thus acting as a meta-database that maps all interaction evidence onto a common set of genomes and proteins. The most important new developments in STRING 8 over previous releases include a URL-based programming interface, which can be used to query STRING from other resources, improved interaction prediction via genomic neighborhood in prokaryotes, and the inclusion of protein structures. Version 8.0 of STRING covers about 2.5 million proteins from 630 organisms, providing the most comprehensive view on protein-protein interactions currently available. STRING can be reached at http://string-db.org/.
2008 2 publication(s).
2.
A Nitrile Hydratase in the Eukaryote Monosiga brevicollis.
Abstract + PDFBacterial nitrile hydratase (NHases) are important industrial catalysts and waste water remediation tools. In a global computational screening of conventional and metagenomic sequence data for NHases, we detected the two usually separated NHase subunits fused in one protein of the choanoflagellate Monosiga brevicollis, a recently sequenced unicellular model organism from the closest sister group of Metazoa. This is the first time that an NHase is found in eukaryotes and the first time it is observed as a fusion protein. The presence of an intron, subunit fusion and expressed sequence tags covering parts of the gene exclude contamination and suggest a functional gene. Phylogenetic analyses and genomic context imply a probable ancient horizontal gene transfer (HGT) from proteobacteria. The newly discovered NHase might open biotechnological routes due to its unconventional structure, its new type of host and its apparent integration into eukaryotic protein networks.
1.
eggNOG: automated construction and annotation of orthologous groups of genes.
2008 Jan 16; 36: D250-4. Epub 2007 Oct 16; PubMed: 17942413.
Abstract + PDFThe identification of orthologous genes forms the basis for most comparative genomics studies. Existing approaches either lack functional annotation of the identified orthologous groups, hampering the interpretation of subsequent results, or are manually annotated and thus lag behind the rapid sequencing of new genomes. Here we present the eggNOG database ('evolutionary genealogy of genes: Non-supervised Orthologous Groups'), which contains orthologous groups constructed from Smith-Waterman alignments through identification of reciprocal best matches and triangular linkage clustering. Applying this procedure to 312 bacterial, 26 archaeal and 35 eukaryotic genomes yielded 43 582 course-grained orthologous groups of which 9724 are extended versions of those from the original COG/KOG database. We also constructed more fine-grained groups for selected subsets of organisms, such as the 19 914 mammalian orthologous groups. We automatically annotated our non-supervised orthologous groups with functional descriptions, which were derived by identifying common denominators for the genes based on their individual textual descriptions, annotated functional categories, and predicted protein domains. The orthologous groups in eggNOG contain 1 241 751 genes and provide at least a broad functional description for 77% of them. Users can query the resource for individual genes via a web interface or download the complete set of orthologous groups at http://eggnog.embl.de.