The DOI matches its Crossref record; 75 of the 75 references it cites were found in a registry or an index.
Horizontal Transfer, Not Duplication, Drives the Expansion of Protein Families in Prokaryotes
Open accessAbstract
Gene duplication followed by neo- or sub-functionalization deeply impacts the evolution of protein families and is regarded as the main source of adaptive functional novelty in eukaryotes. While there is ample evidence of adaptive gene duplication in prokaryotes, it is not clear whether duplication outweighs the contribution of horizontal gene transfer in the expansion of protein families. We analyzed closely related prokaryote strains or species with small genomes (Helicobacter, Neisseria, Streptococcus, Sulfolobus), average-sized genomes (Bacillus, Enterobacteriaceae), and large genomes (Pseudomonas, Bradyrhizobiaceae) to untangle the effects of duplication and horizontal transfer. After removing the effects of transposable elements and phages, we show that the vast majority of expansions of protein families are due to transfer, even among large genomes. Transferred genes--xenologs--persist longer in prokaryotic lineages possibly due to a higher/longer adaptive role. On the other hand, duplicated genes--paralogs--are expressed more, and, when persistent, they evolve slower. This suggests that gene transfer and gene duplication have very different roles in shaping the evolution of biological systems: transfer allows the acquisition of new functions and duplication leads to higher gene dosage. Accordingly, we show that paralogs share most protein-protein interactions and genetic regulators, whereas xenologs share very few of them. Prokaryotes invented most of life's biochemical diversity. Therefore, the study of the evolution of biology systems should explicitly account for the predominant role of horizontal gene transfer in the diversification of protein families.
Overview
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
Verification
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Recent theoretical, comparative genomic and experimental research on microbial evolution clearly indicates that HGT is the principal factor in microbial adaptation and innovation (46, 65, 66, 80).”
From Origin and Evolution of the Universal Genetic Code (2017) · cites this paper as [80]
Experimental — accuracy not yet measuredIn the citing paper
“Given that HGT, even if limited by both physical and selective barriers, remained a key factor of microbial evolution [36,37,38,39,40], and apparently, a condition for long term survival of microbial populations [41,42]”
From Frozen Accident Pushing 50: Stereochemistry, Expansion, and Chance in the Evolution of the Genetic Code (2017) · cites this paper as [40]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Basic local alignment search tool
Altschul, S. F., Gish, W., Miller, W., Myers, E. W., & Lipman, D. J. (1990) · Journal of Molecular Biology · doi:10.1006/jmbi.1990.9999 · Cited by 98,669 · cited 7×
“OrthoMCL defines putative orthologous relationships between a pair of genomes as BLASTP reciprocal better/best hits.”
MethodInfluentialMUSCLE: multiple sequence alignment with high accuracy and high throughput
Edgar, R. C. (2004) · Nucleic Acids Research · doi:10.1093/nar/gkh340 · Cited by 44,662 · cited 1×
“Protein alignments were generated using MUSCLE [73] and then back-translated to DNA.”
MethodOrthoMCL: Identification of Ortholog Groups for Eukaryotic Genomes
Li, L., Stoeckert, C. J., & Roos, D. S. (2003) · Genome Research · doi:10.1101/gr.1224503 · Cited by 5,707 · cited 2×
“OrthoMCL defines putative orthologous relationships between a pair of genomes as BLASTP reciprocal better/best hits.”
MethodPAML: a program package for phylogenetic analysis by maximum likelihood
Yang, Z. (1997) · Computer applications in the biosciences · doi:10.1093/bioinformatics/13.5.555 · Cited by 5,377 · cited 1×
“Non-synonymous (dN) and synonymous (dS) substitution rates in paralogs (blue; dashed linear fit) and xenologs (red; solid linear fit) in all clades computed using Codeml from PAML [76] (model = 1, fix_omega = 0).”
MethodSharp, P. M., & Li, W.-H. (1987) · Nucleic Acids Research · doi:10.1093/nar/15.3.1281 · Cited by 3,992 · cited 1×
“We first tested if the two classes of protein families have different gene expression levels using the codon adaptation index (CAI; [44]).”
MethodLateral gene transfer and the nature of bacterial innovation
Ochman, H., Lawrence, J. G., & Groisman, E. A. (2000) · Nature · doi:10.1038/35012500 · Cited by 3,816 · cited 1×
“Horizontal gene transfer (HGT) results in the acquisition of radically new genetic information, liberating genomic evolutionary processes from tinkering exclusively with pre-existing genes”
BackgroundAn efficient algorithm for large-scale detection of protein families
Enright, A. J. (2002) · Nucleic Acids Research · doi:10.1093/nar/30.7.1575 · Cited by 3,536 · cited 4×
“OrthoMCL defines putative orthologous relationships between a pair of genomes as BLASTP reciprocal better/best hits.”
MethodInfluentialISfinder: the reference centre for bacterial insertion sequences
Siguier, P. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkj014 · Cited by 2,767 · cited 2×
“coli our databank contained all IS present in IS Finder [67].”
BackgroundTREE-PUZZLE: maximum likelihood phylogenetic analysis using quartets and parallel computing
Schmidt, H. A., Strimmer, K., Vingron, M., & von Haeseler, A. (2002) · Bioinformatics · doi:10.1093/bioinformatics/18.3.502 · Cited by 2,512 · cited 1×
“Tree-Puzzle [74] was used to generate the matrix of distances by maximum likelihood with the HKY+C model and exact parameter estimates.”
MethodBIONJ: an improved version of the NJ algorithm based on a simple model of sequence data
Gascuel, O. (1997) · Molecular Biology and Evolution · doi:10.1093/oxfordjournals.molbev.a025808 · Cited by 1,850 · cited 2×
“The trees were then computed from these distance matrices using BIONJ [75].”
MethodInfluential
Flagged first, then by citations
Research works printed but not linked: 1
- G Vernikos, 2007, Genetic flux over time in the Salmonella lineage., Genome Biology, 8, R100, 10.1186/gb-2007-8-6-r100 · DOI
Cited by
Sorted by citations
Items 501–514 of 514
Native‐Alien Dichotomy in Pathogen Genomics: Host Specialization Versus Environmental Decoupling
Li, Y., Perry, G. L. W., Padamsee, M., & Yu, S. (2026) · Ecology Letters · doi:10.1111/ele.70394
Genus-wide Homologous Recombination of Tail Fibers Maintains Tailocin Diversity in Pectobacterium
Pardeshi, L. A., Kupczok, A., de Ridder, D., Smit, S., & van der Lee, T. (2026) · Genome Biology and Evolution · doi:10.1093/gbe/evag106
Kente: A Graph-based Pangenomic Approach for Horizontal Gene Transfer Detection in MicrobiomesPreprint
Kokroko, N., Jayanti, R., Sapoval, N., Nute, M., Nakhleh, L. K., & Treangen, T. J. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.06.22.733643
“Horizontal gene transfer (HGT) is a major driver of bacterial genome evolution, enabling the rapid dissemination of antibiotic resistance genes, virulence factors, and metabolic innovations across microbial communities (Treangen and Rocha, 2011).”
Self-citationFit for purpose: evaluation and evolution of agricultural bioinoculants across production landscapes
Hemara, L. M., Doyle, R., diCenzo, G. C., Bakker, M. G., Hopkins, K. R., Lee, J., Oresnik, I. J., & Bell, T. H. (2026) · ISME Communications · doi:10.1093/ismeco/ycag190
“Horizontal gene transfer within microbiomes is another driver of evolutionary innovation, allowing bacteria to rapidly adapt to new environmental niches [ 102– 104].”
Huang, W.-C., Dombrowski, N., Mahendrarajah, T., Wahl, N. A., Stamatakis, A., Szöllősi, G. J., Williams, T. A., & Spang, A. (2026) · Nature Communications · doi:10.1038/s41467-026-76386-7 · Cited by 7
“Speci fi cally, we found that gene transfers are on average 10.87-11.18 times more frequent than duplication events in archaeal evolution (Supplementary Data 20), in agreement with the fi nding that transfers are more frequent than duplications in prokaryotic genomes 80,81 .”
InfluentialThe dynamics of gene copy-number mutations: transient changes with long-lasting consequences
Tomanek, I., & Guet, C. C. (2026) · Genetics · doi:10.1093/genetics/iyag262
Babu, K. R., Sobhana, K. S., Alex, A., Neethu, K. P., Umar, M., Jayasree, V., & George, G. (2026) · Indian Journal of Fisheries · doi:10.21077/ijf.2026.73.3.182102-14
“Such localised genomic variation, including prophages, genomic islands, and other mobile genetic elements, leads to strain level diversification, while maintaining the overall chromosomal framework (Treangen and Rocha, 2011).”
mGem: Bacterial aversion to making new genes
uz‐Zaman, M. H., & Ochman, H. (2026) · mBio · doi:10.1128/mbio.02016-26
Rubio, A., Moreno-Rodríguez, A., Ceballos-Romero, L., Garzón, A., Marqués-Hinojosa, J. A., Luque-Jiménez, E., Sánchez-Suero, M. P., Pachón, J., Pachón-Ibáñez, M. E., & Pérez‐Pulido, A. J. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.10.09.757860
“…a broader evolutionary paradigm where gene amplification and subfunctionalization allow a protein family to specialize within a specific genetic niche, after which horizontal gene transfer enables distantly related bacteria to rapidly co-opt these pre adapted functional innovations ( 28 , 29 ).”
Ten rules for identifying horizontal gene transfers in deep plant phylogenies
Fjellheim, S., Pereira, L., & Sandve, S. R. (2026) · New Phytologist · doi:10.1111/nph.71680
Metadata
- Authors
- Treangen, T. J., & Rocha, E. P. C.
- Affiliations
- Centre National de la Recherche Scientifique (FR)
- Corresponding author
- Treangen, Todd J.
- Venue
- PLoS Genetics
- Publisher
- Public Library of Science (PLoS)
- Published
- 2011-01-27
- Volume
- 7
- Issue
- 1
- Pages
- e1001284
- ISSN
- 1553-7390 (ISSN-L)
- 1553-7404
- PMC
- PMC3029252
- OpenAlex
- W2022927779
- Cited by
- 509
- References
- 75
- Citations by year
- 2026: 18 · 2025: 34 · 2024: 36 · 2023: 26 · 2022: 29 · 2021: 32 · 2020: 52 · 2019: 27 · 2018: 33 · 2017: 31 · 2016: 38 · 2015: 29 · 2014: 34 · 2013: 33 · 2012: 28
- FWCI
- 15.99
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS Genetics (publishedVersion, cc-by)
- PubMed Central (publishedVersion, other-oa)
- PubMed (publishedVersion)
- HAL (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Funders
- Centre National de la Recherche Scientifique
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Chromosomal and Genetic Variations
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
- Keywords
- horizontal gene transfer, gene duplication, protein family expansion, prokaryotes, paralogs, functional novelty, gene dosage, protein-protein interaction, regulatory genes, genome size, Helicobacter, Neisseria, Streptococcus, Sulfolobus, Bacillus, Enterobacteriaceae, Pseudomonas, Bradyrhizobiaceae
- MeSH terms
- Bacillus, Bacteria, Enterobacteriaceae, Multigene Family, Neisseria, Phylogeny, Pseudomonas, Streptococcus, Genome, Bacterial, Sulfolobus, Helicobacter, Evolution, Molecular, Computational Biology, Gene Duplication, Gene Transfer, Horizontal, Bradyrhizobiaceae
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
