Comparative Genomics of Centrality and Essentiality in Three Eukaryotic Protein-Interaction Networks
Open accessAbstract
Most proteins do not evolve in isolation, but as components of complex genetic networks. Therefore, a protein's position in a network may indicate how central it is to cellular function and, hence, how constrained it is evolutionarily. To look for an effect of position on evolutionary rate, we examined the protein-protein interaction networks in three eukaryotes: yeast, worm, and fly. We find that the three networks have remarkably similar structure, such that the number of interactors per protein and the centrality of proteins in the networks have similar distributions. Proteins that have a more central position in all three networks, regardless of the number of direct interactors, evolve more slowly and are more likely to be essential for survival. Our results are thus consistent with a classic proposal of Fisher's that pleiotropy constrains evolution.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Degree centrality reports how many edges (genes) are directly connected to a node (TF); highly connected nodes are likely to be essential for a biological process.
“Degree centrality is a straightforward measure that reports how many edges (genes) are directly connected to a node (TF); highly connected nodes are likely to be essential for a biological process35,36.”
From Dissecting cell identity via network inference and in silico gene perturbation (2023) · cites this paper as [36]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
The genetical theory of natural selection
Fisher, R. A. (1930) · doi:10.5962/bhl.title.27468 · Cited by 17,617 · see citing works
Social Network Analysis: Methods and Applications
Wasserman, S., & Faust, K. (1994) · doi:10.1017/cbo9780511815478 · Cited by 17,557 · see citing works
(2017) · Sage eBooks · doi:10.4135/9781483381411.n575 · Cited by 6,067 · see citing works
Lethality and centrality in protein networks
Jeong, H., Mason, S., Barabási, A., & Oltvai, Z. (2001) · Nature · doi:10.1038/35075138 · Cited by 5,327 · see citing works
The Large-Scale Organization of Metabolic Networks
Jeong, H., Tombor, B., Albert, R., Oltvai, Z. N., & Barabási, A.-L. (2000) · Nature · doi:10.1038/35036627 · Cited by 4,972 · see citing works
Functional profiling of the Saccharomyces cerevisiae genome
Giaever, G., Chu, A. M., Ni, L., Connelly, C., Riles, L., Véronneau, S., Dow, S., Lucau-Danila, A., Anderson, K., André, B., et al. (2002) · Nature · doi:10.1038/nature00935 · Cited by 4,316 · see citing works
Hierarchical Organization of Modularity in Metabolic Networks
Ravasz, E., Somera, A. L., Mongru, D. A., Oltvai, Z. N., & Barabási, A.-L. (2002) · Science · doi:10.1126/science.1073374 · Cited by 4,224 · see citing works
Systematic functional analysis of the Caenorhabditis elegans genome using RNAi
Kamath, R. S., Fraser, A. G., Yan, D., Poulin, G. B., Durbin, R. M., Gotta, M., Kanapin, A. A., Bot, N. L., Moreno, S., Sohrmann, M., et al. (2003) · Nature · doi:10.1038/nature01278 · Cited by 3,542 · see citing works
A Protein Interaction Map of Drosophila melanogaster
Giot, L., Bader, J. S., Brouwer, C., Chaudhuri, A., Kuang, B., Li, Y., Hao, Y. L., Ooi, C., Godwin, B., Vitols, E., et al. (2003) · Science · doi:10.1126/science.1090289 · Cited by 2,266 · see citing works
A Map of the Interactome Network of the Metazoan C. elegans
Li, S., Armstrong, C. M., Bertin, N., Ge, H., Milstein, S., Boxem, M., Vidalain, P., Han, J.-D. J., Chesneau, A., Hao, T., et al. (2004) · Science · doi:10.1126/science.1091403 · Cited by 1,628 · see citing works
The small world inside large metabolic networks
Wagner, A., & Fell, D. A. (2001) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2001.1711 · Cited by 986 · see citing works
The Genome Sequence of Caenorhabditis briggsae: A Platform for Comparative Genomics
Stein, L. D., Bao, Z., Blasiar, D., Blumenthal, T., Brent, M. R., Chen, N., Chinwalla, A., Clarke, L., Clee, C. M., Coghlan, A., et al. (2003) · PLoS Biology · doi:10.1371/journal.pbio.0000045 · Cited by 931 · see citing works
Evolutionary Rate in the Protein Interaction Network
Fraser, H. B., Hirsh, A. E., Steinmetz, L. M., Scharfe, C., & Feldman, M. W. (2002) · Science · doi:10.1126/science.1068696 · Cited by 869 · see citing works
Understanding quantitative genetic variation
Barton, N., & Keightley, P. D. (2002) · Nature Reviews Genetics · doi:10.1038/nrg700 · Cited by 839 · see citing works
Global organization of metabolic fluxes in the bacterium Escherichia coli
Almaas, E., Kovács, B., Vicsek, T., Oltvai, Z. N., & Barabási, A.-Ĺ. (2004) · Nature · doi:10.1038/nature02289 · Cited by 710 · see citing works
Large-scale analysis of gene function in Caenorhabditis elegans by high-throughput RNAi
Maeda, I., Kohara, Y., Yamamoto, M., et al. (2001) · Current Biology · doi:10.1016/s0960-9822(01)00052-5 · Cited by 698 · see citing works
Essential Genes Are More Evolutionarily Conserved Than Are Nonessential Genes in BacteriaPreprint
Jordan, I. K., Rogozin, I. B., Wolf, Y. I., & Koonin, E. V. (2002) · Genome Research · doi:10.1101/gr.87702 · Cited by 546 · see citing works
ADAPTATION AND THE COST OF COMPLEXITY
Orr, H. A. (2000) · Evolution · doi:10.1111/j.0014-3820.2000.tb00002.x · Cited by 519 · see citing works
The Yeast Protein Interaction Network Evolves Rapidly and Contains Few Redundant Duplicate Genes
Wagner, A. (2001) · Molecular Biology and Evolution · doi:10.1093/oxfordjournals.molbev.a003913 · Cited by 514 · see citing works
Protein dispensability and rate of evolution
Hirsh, A. E., & Fraser, H. B. (2001) · Nature · doi:10.1038/35082561 · Cited by 413 · see citing works
Krylov, D. M., Wolf, Y. I., Rogozin, I. B., & Koonin, E. V. (2003) · Genome Research · doi:10.1101/gr.1589103 · Cited by 391 · see citing works
Do essential genes evolve slowly?
Hurst, L. D., & Smith, N. G. C. (1999) · Current Biology · doi:10.1016/s0960-9822(99)80334-0 · Cited by 259 · see citing works
Patterns of evolutionary rate variation among genes of the anthocyanin biosynthetic pathway
Rausher, M. D., Miller, R. E., & Tiffin, P. (1999) · Molecular Biology and Evolution · doi:10.1093/oxfordjournals.molbev.a026108 · Cited by 222 · see citing works
Protein networks, pleiotropy and the evolution of senescence
Promislow, D. (2004) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2004.2732 · Cited by 174 · see citing works
Molecular Evolution in Large Genetic Networks: Does Connectivity Equal Constraint?
Hahn, M. W., Conant, G. C., & Wagner, A. (2004) · Journal of Molecular Evolution · doi:10.1007/s00239-003-2544-0 · Cited by 147 · see citing works
Self-citationPleiotropy and the Preservation of Perfection
Waxman, D., & Peck, J. R. (1998) · Science · doi:10.1126/science.279.5354.1210 · Cited by 136 · see citing works
Bloom, J. D., & Adami, C. (2003) · BMC Evolutionary Biology · doi:10.1186/1471-2148-3-21 · Cited by 134 · see citing works
Rate of Protein Evolution Versus Fitness Effect of Gene Deletion
Yang, J. (2003) · Molecular Biology and Evolution · doi:10.1093/molbev/msg078 · Cited by 93 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Network pharmacology: the next paradigm in drug discovery
Hopkins, A. L. (2008) · Nature Chemical Biology · doi:10.1038/nchembio.118 · Cited by 4,622 · see citing works
Flexible nets: The roles of intrinsic disorder in protein interaction networks
Dunker, A. K., Cortese, M. S., Romero, P., Iakoucheva, L. M., & Uversky, V. N. (2005) · The FEBS Journal · doi:10.1111/j.1742-4658.2005.04948.x · Cited by 1,122 · see citing works
Dissecting cell identity via network inference and in silico gene perturbation
Kamimoto, K., Stringa, B., Hoffmann, C. M., Jindal, K., Solnica-Krezel, L., & Morris, S. A. (2023) · Nature · doi:10.1038/s41586-022-05688-9 · Cited by 677 · see citing works
Henegar, C., Tordjman, J., Achard, V., Lacasa, D., Cremer, I., Guerre-Millo, M., Poitou, C., Basdevant, A., Stich, V., Viguerie, N., et al. (2008) · Genome Biology · doi:10.1186/gb-2008-9-1-r14 · Cited by 471 · see citing works
When is hub gene selection better than standard meta-analysis?
Langfelder, P., Mischel, P. S., & Horvath, S. (2013) · PLoS ONE · doi:10.1371/journal.pone.0061505 · Cited by 313 · see citing works
Network biology concepts in complex disease comorbidities
Hu, J. X., Thomas, C. E., & Brunak, S. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2016.87 · Cited by 328 · see citing works
Deschamps, M., Laval, G., Fagny, M., Itan, Y., Abel, L., Casanova, J.-L., Patin, E., & Quintana-Murci, L. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.11.014 · Cited by 257 · see citing works
Sharing and Specificity of Co-expression Networks across 35 Human Tissues
Pierson, E., the GTEx Consortium, Koller, D., Battle, A., & Mostafavi, S. (2015) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1004220 · Cited by 177 · see citing works
- Authors
- Hahn, M. W., & Kern, A. D.
- Affiliations
- University of California, Davis (US)
- Corresponding author
- Hahn, Matthew W.
- Venue
- Molecular Biology and Evolution
- Publisher
- Oxford University Press (OUP)
- Published
- 2004-12-22
- Volume
- 22
- Issue
- 4
- Pages
- 803-806
- ISSN
- 0737-4038 (ISSN-L)
- 1537-1719
- OpenAlex
- W2074443723
- Cited by
- 656
- References
- 28
- Citations by year
- 2026: 13 · 2025: 20 · 2024: 30 · 2023: 32 · 2022: 27 · 2021: 39 · 2020: 35 · 2019: 29 · 2018: 30 · 2017: 25 · 2016: 36 · 2015: 43 · 2014: 37 · 2013: 38 · 2012: 41
- FWCI
- 6.16
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Molecular Biology and Evolution (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Science Foundation
- Howard Hughes Medical Institute
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- protein-protein interaction network, network centrality, protein essentiality, evolutionary rates, pleiotropy, network topology, Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster, eukaryotic evolution
- MeSH terms
- Eukaryotic Cells, Biological Evolution, Proteins, Genomics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
