Analysis of genomic context: prediction of functional associations from conserved bidirectionally transcribed gene pairs

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Analysis of genomic context : prediction of functional associations from conserved bidirectionally transcribed gene pairs. / Korbel, Jan O; Jensen, Lars J; von Mering, Christian; Bork, Peer.

In: Nature Biotechnology, Vol. 22, No. 7, 2004, p. 911-7.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Korbel, JO, Jensen, LJ, von Mering, C & Bork, P 2004, 'Analysis of genomic context: prediction of functional associations from conserved bidirectionally transcribed gene pairs', Nature Biotechnology, vol. 22, no. 7, pp. 911-7. https://doi.org/10.1038/nbt988

APA

Korbel, J. O., Jensen, L. J., von Mering, C., & Bork, P. (2004). Analysis of genomic context: prediction of functional associations from conserved bidirectionally transcribed gene pairs. Nature Biotechnology, 22(7), 911-7. https://doi.org/10.1038/nbt988

Vancouver

Korbel JO, Jensen LJ, von Mering C, Bork P. Analysis of genomic context: prediction of functional associations from conserved bidirectionally transcribed gene pairs. Nature Biotechnology. 2004;22(7):911-7. https://doi.org/10.1038/nbt988

Author

Korbel, Jan O ; Jensen, Lars J ; von Mering, Christian ; Bork, Peer. / Analysis of genomic context : prediction of functional associations from conserved bidirectionally transcribed gene pairs. In: Nature Biotechnology. 2004 ; Vol. 22, No. 7. pp. 911-7.

Bibtex

@article{a2fad52717a445a69b374a7bb3599580,
title = "Analysis of genomic context: prediction of functional associations from conserved bidirectionally transcribed gene pairs",
abstract = "Several widely used methods for predicting functional associations between proteins are based on the systematic analysis of genomic context. Efforts are ongoing to improve these methods and to search for novel aspects in genomes that could be exploited for function prediction. Here, we use gene expression data to demonstrate two functional implications of genome organization: first, chromosomal proximity indicates gene coregulation in prokaryotes independent of relative gene orientation; and second, adjacent bidirectionally transcribed genes (that is,'divergently' organized coding regions) with conserved gene orientation are strongly coregulated. We further demonstrate that such bidirectionally transcribed gene pairs are functionally associated and derive from this a novel genomic context method that reliably predicts links between >2,500 pairs of genes in approximately 100 species. Around 650 of these functional associations are supported by other genomic context methods. In most instances, one gene encodes a transcriptional regulator, and the other a nonregulatory protein. In-depth analysis in Escherichia coli shows that the vast majority of these regulators both control transcription of the divergently transcribed target gene/operon and auto-regulate their own biosynthesis. The method thus enables the prediction of target processes and regulatory features for several hundred transcriptional regulators.",
author = "Korbel, {Jan O} and Jensen, {Lars J} and {von Mering}, Christian and Peer Bork",
year = "2004",
doi = "10.1038/nbt988",
language = "English",
volume = "22",
pages = "911--7",
journal = "Nature Biotechnology",
issn = "1087-0156",
publisher = "nature publishing group",
number = "7",

}

RIS

TY - JOUR

T1 - Analysis of genomic context

T2 - prediction of functional associations from conserved bidirectionally transcribed gene pairs

AU - Korbel, Jan O

AU - Jensen, Lars J

AU - von Mering, Christian

AU - Bork, Peer

PY - 2004

Y1 - 2004

N2 - Several widely used methods for predicting functional associations between proteins are based on the systematic analysis of genomic context. Efforts are ongoing to improve these methods and to search for novel aspects in genomes that could be exploited for function prediction. Here, we use gene expression data to demonstrate two functional implications of genome organization: first, chromosomal proximity indicates gene coregulation in prokaryotes independent of relative gene orientation; and second, adjacent bidirectionally transcribed genes (that is,'divergently' organized coding regions) with conserved gene orientation are strongly coregulated. We further demonstrate that such bidirectionally transcribed gene pairs are functionally associated and derive from this a novel genomic context method that reliably predicts links between >2,500 pairs of genes in approximately 100 species. Around 650 of these functional associations are supported by other genomic context methods. In most instances, one gene encodes a transcriptional regulator, and the other a nonregulatory protein. In-depth analysis in Escherichia coli shows that the vast majority of these regulators both control transcription of the divergently transcribed target gene/operon and auto-regulate their own biosynthesis. The method thus enables the prediction of target processes and regulatory features for several hundred transcriptional regulators.

AB - Several widely used methods for predicting functional associations between proteins are based on the systematic analysis of genomic context. Efforts are ongoing to improve these methods and to search for novel aspects in genomes that could be exploited for function prediction. Here, we use gene expression data to demonstrate two functional implications of genome organization: first, chromosomal proximity indicates gene coregulation in prokaryotes independent of relative gene orientation; and second, adjacent bidirectionally transcribed genes (that is,'divergently' organized coding regions) with conserved gene orientation are strongly coregulated. We further demonstrate that such bidirectionally transcribed gene pairs are functionally associated and derive from this a novel genomic context method that reliably predicts links between >2,500 pairs of genes in approximately 100 species. Around 650 of these functional associations are supported by other genomic context methods. In most instances, one gene encodes a transcriptional regulator, and the other a nonregulatory protein. In-depth analysis in Escherichia coli shows that the vast majority of these regulators both control transcription of the divergently transcribed target gene/operon and auto-regulate their own biosynthesis. The method thus enables the prediction of target processes and regulatory features for several hundred transcriptional regulators.

U2 - 10.1038/nbt988

DO - 10.1038/nbt988

M3 - Journal article

C2 - 15229555

VL - 22

SP - 911

EP - 917

JO - Nature Biotechnology

JF - Nature Biotechnology

SN - 1087-0156

IS - 7

ER -

ID: 40749521