Microbial Genescapes: Phyletic and Functional Patterns of ORF Distribution among Prokaryotes

Gaasterland, Terry; Ragan, Mark A.

doi:10.1089/omi.1.1998.3.199

Cited by 115 publications

(66 citation statements)

References 58 publications

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“…1,030 ORFs produce matches in the Aeropyrum pernix genome (at e Ͻ 10 Ϫ10 ), and 45 of these match A. pernix, exclusively, in the GenBank͞European Molecular Biology Laboratory database. Three hundred fifty seven Sulfolobus ORFs produce a match among bacteria but not eukarya, whereas 67 match eukarya but not bacteria at inclusion and exclusion thresholds e ϭ 10 Ϫ10 and 10 Ϫ5 , respectively (11,12). An additional 701 ORFs give a match in both domains.…”

Section: Genome Sequencing Organization and Annotationmentioning

confidence: 99%

The complete genome of the crenarchaeon Sulfolobus solfataricus P2

She

Singh

Confalonieri

et al. 2001

Proc. Natl. Acad. Sci. U.S.A.

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723

627

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The genome of the crenarchaeon Sulfolobus solfataricus P2 contains 2,992,245 bp on a single chromosome and encodes 2,977 proteins and many RNAs. One-third of the encoded proteins have no detectable homologs in other sequenced genomes. Moreover, 40% appear to be archaeal-specific, and only 12% and 2.3% are shared exclusively with bacteria and eukarya, respectively. The genome shows a high level of plasticity with 200 diverse insertion sequence elements, many putative nonautonomous mobile elements, and evidence of integrase-mediated insertion events. There are also long clusters of regularly spaced tandem repeats. Different transfer systems are used for the uptake of inorganic and organic solutes, and a wealth of intracellular and extracellular proteases, sugar, and sulfur metabolizing enzymes are encoded, as well as enzymes of the central metabolic pathways and motility proteins. The major metabolic electron carrier is not NADH as in bacteria and eukarya but probably ferredoxin. The essential components required for DNA replication, DNA repair and recombination, the cell cycle, transcriptional initiation and translation, but not DNA folding, show a strong eukaryal character with many archaeal-specific features. The results illustrate major differences between crenarchaea and euryarchaea, especially for their DNA replication mechanism and cell cycle processes and their translational apparatus.

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Section: Genome Sequencing Organization and Annotationmentioning

confidence: 99%

The complete genome of the crenarchaeon Sulfolobus solfataricus P2

She

Singh

Confalonieri

et al. 2001

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

723

627

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“…Many studies have focused on specific aspects of genome evolution or have tried to reconstruct a specific ancestral genome (Bruccoleri et al 1998;de Rosa and Labedan 1998;Huynen and Bork 1998;Kyrpides et al 1999;Makarova et al 1999;Aravind et al 2000;Ochman and Jones 2000;Jordan et al 2001). Large-scale studies on the presence and absence of genes have shown that the number of shared genes between genomes depends on the size of genomes (Snel et al 1999), and their evolutionary distance (Gaasterland and Ragan 1998;Huynen and Bork 1998;Fitz-Gibbon and House 1999;Snel et al 1999;Tekaia et al 1999). Correlation in the presence of genes has been used to predict functional interactions between genes (Pellegrini et al 1999;Huynen and Snel 2000).…”

mentioning

confidence: 99%

Genomes in Flux: The Evolution of Archaeal and Proteobacterial Gene Content

Snel¹,

Bork²,

Huynen³

2001

Genome Res.

319

262

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In the course of evolution, genomes are shaped by processes like gene loss, gene duplication, horizontal gene transfer, and gene genesis (the de novo origin of genes). Here we reconstruct the gene content of ancestral Archaea and Proteobacteria and quantify the processes connecting them to their present day representatives based on the distribution of genes in completely sequenced genomes. We estimate that the ancestor of the Proteobacteria contained around 2500 genes, and the ancestor of the Archaea around 2050 genes. Although it is necessary to invoke horizontal gene transfer to explain the content of present day genomes, gene loss, gene genesis, and simple vertical inheritance are quantitatively the most dominant processes in shaping the genome. Together they result in a turnover of gene content such that even the lineage leading from the ancestor of the Proteobacteria to the relatively large genome of Escherichia coli has lost at least 950 genes. Gene loss, unlike the other processes, correlates fairly well with time. This clock-like behavior suggests that gene loss is under negative selection, while the processes that add genes are under positive selection.

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“…A group of genes with the same phylogenetic profile is assumed to encode proteins that are functionally related (for example, they may be part of the same metabolic pathway) and that may or may not interact physically. The drawback of the method is that it can only be applied to complete genomes [83,84]. Conservation of gene neighborhood.…”

Section: Discussionmentioning

confidence: 99%

Accessible Protein Interaction Data for Network Modeling. Structure of the Information and Available Repositories

Gómez

Alonso-Allende

Pazos

et al. 2005

Transactions on Computational Systems Biology I

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Abstract. In recent years there has been an incredible explosion of computational studies of molecular biology systems, particularly those related to the analysis of the structure and organization of molecular networks, as the initial steps toward the possible simulation of the behavior of simple cellular systems. Needless to say, this task will not be possible without the availability of a new class of data derived from experimental proteomics. Large-scale application of the yeast two-hybrid system, affinity purification (TAPs-MS), and other methodologies are for the first time providing overviews of complete protein interaction networks. Interestingly a number of computational methods are also contributing substantially to the identification of protein interactions, by comparing genome organization and evolution. Other disciplines, such as structural biology and computational structural biology, are complementing the information on interaction networks by providing detailed molecular descriptions of the corresponding complexes, which will become essential for the direct manipulation of the networks using theoretical or experimental methods. The storage, manipulation and visualization of the huge volumes of information about protein interactions and networks pose similar problems, irrespective of the source of the information: experimental or computational. In this sense, a number of competing systems and emerging standards have appeared in parallel with the publication of the data. In this review, we will provide an overview of the main experimental, high-throughput methods for the study of protein interactions, the parallel developments of computational methods for the prediction of protein interactions based on genome and sequence information, and the development of databases and standards that facilitate the analysis of all this information.

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Microbial Genescapes: Phyletic and Functional Patterns of ORF Distribution among Prokaryotes

Cited by 115 publications

References 58 publications

The complete genome of the crenarchaeon Sulfolobus solfataricus P2

The complete genome of the crenarchaeon Sulfolobus solfataricus P2

Genomes in Flux: The Evolution of Archaeal and Proteobacterial Gene Content

Accessible Protein Interaction Data for Network Modeling. Structure of the Information and Available Repositories

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