DOI: 10.1126/science.1068696. Evolutionary Rate in the Protein Interaction Network

Evolutionary Rate in the Protein Interaction Network

10.1126/science.1068696

Crossref journal-article

American Association for the Advancement of Science (AAAS)

Science (221)

Abstract

High-throughput screens have begun to reveal the protein interaction network that underpins most cellular functions in the yeast Saccharomyces cerevisiae . How the organization of this network affects the evolution of the proteins that compose it is a fundamental question in molecular evolution. We show that the connectivity of well-conserved proteins in the network is negatively correlated with their rate of evolution. Proteins with more interactors evolve more slowly not because they are more important to the organism, but because a greater proportion of the protein is directly involved in its function. At sites important for interaction between proteins, evolutionary changes may occur largely by coevolution, in which substitutions in one protein result in selection pressure for reciprocal changes in interacting partners. We confirm one predicted outcome of this process—namely, that interacting proteins evolve at similar rates.

Bibliography

Fraser, H. B., Hirsh, A. E., Steinmetz, L. M., Scharfe, C., & Feldman, M. W. (2002). Evolutionary Rate in the Protein Interaction Network. Science, 296(5568), 750â752.

Authors 5

Hunter B. Fraser (first)
Aaron E. Hirsh (additional)
Lars M. Steinmetz (additional)
Curt Scharfe (additional)
Marcus W. Feldman (additional)

References 30 Referenced 710

10.1146/annurev.bi.46.070177.003041
E. A. Winzeler et al. Science 285 901 (1999).
S. A. Chervitz et al. Science 282 2022 (1998). (10.1126/science.282.5396.2022)
10.1038/35082561
10.1007/BF01731487
10.1007/BF01659392
10.1038/82360
P. Uetz et al. Nature 403 623 (2000). (10.1038/35001009)
T. Ito et al. Proc. Natl. Acad. Sci. U.S.A. 98 4569 (2001). (10.1073/pnas.061034498)
Our data set of yeast protein-protein interactions was compiled from (7) the “core data” of (9) and 625 interactions identified by the two-hybrid array method [described in (8)] listed at .
Putative orthologs were defined as reciprocal best hits (4 24) with P < 10 −10 and >80% protein sequence alignment in reciprocal searches using Washington University Basic Local Alignment Search Tool for Proteins (WU-BLASTP) (3). Thus if a query of all 19 099 nematode open reading frames (ORFs) with yeast ORF i yielded the set of hits { W } with P < 10 −10 and >80% alignment and a query of all 6217 yeast ORFs with nematode ORF j yielded the set of hits { Y } with P < 10 −10 and >80% alignment then the pair (ORF i ORF j ) was considered a putative ortholog only if i was the member of { Y } with the lowest P value and j was the member of { W } with the lowest P value.
To estimate the number of substitutions per amino acid site we numerically solved the equation q = [ln(1 + 2 K )]/2 K where is the proportion of identical sites between aligned sequences. This method is described in (25) and tested further in (26).
Unless otherwise specified the correlation coefficient r X Y represents Spearman's rank correlation between variables X and Y.
Y. Ho et al. Nature 415 180 (2002).
10.1038/415141a
Supplementary fig. 1 is available on Science Online at www.sciencemag.org/cgi/content/full/296/5568/750/DC1.
10.1126/science.274.5295.2069
10.1038/35075138
The r IF and r FK correlations were also significant when genetic footprint data (27) were used instead of parallel analysis data. When essential proteins are excluded from the analysis which is expected to strengthen the correlation between fitness effect and evolutionary rate (4) r FK = −0.18 P = 1.3 × 10 −8 for 944 nonessential proteins in parallel analysis.
D. Kaplan in Advanced Quantitative Techniques in the Social Sciences J. de Leeuw R. Berk Eds. (Sage Publications Thousand Oaks CA 2000) pp. 13–39.
J. D. Gibbons in Sage University Papers M. S. Lewis-Beck Ed. (Sage Publications Newbury Park CA 1993) pp. 3–29.
Examples of interprotein coevolution are described in (28 29).
10.1093/nar/29.17.3513
10.1073/pnas.95.11.6239
10.1007/BF00175826
10.1007/PL00006155
10.1073/pnas.92.14.6479
10.1016/S0378-1119(00)00145-1
10.1093/oxfordjournals.molbev.a026297
B. Dunn provided genetic footprinting data. P. Uetz assisted with interaction data. J. Davis M. Eisen B. Kerr D. Petrov and C. Winter provided helpful discussion and comments on the manuscript.

Dates

Type	When
Created	23 years, 1 month ago (July 27, 2002, 5:54 a.m.)
Deposited	1 year, 7 months ago (Jan. 9, 2024, 10:37 p.m.)
Indexed	1 week, 4 days ago (Aug. 19, 2025, 7:11 a.m.)
Issued	23 years, 4 months ago (April 26, 2002)
Published	23 years, 4 months ago (April 26, 2002)
Published Print	23 years, 4 months ago (April 26, 2002)

Funders 0

None

BibTeX

@article{Fraser_2002, title={Evolutionary Rate in the Protein Interaction Network}, volume={296}, ISSN={1095-9203}, url={http://dx.doi.org/10.1126/science.1068696}, DOI={10.1126/science.1068696}, number={5568}, journal={Science}, publisher={American Association for the Advancement of Science (AAAS)}, author={Fraser, Hunter B. and Hirsh, Aaron E. and Steinmetz, Lars M. and Scharfe, Curt and Feldman, Marcus W.}, year={2002}, month=apr, pages={750–752} }

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