Evidence map›Paper›PMID 28902834›Full record

ArticleNature2017

Alternative evolutionary histories in the sequence space of an ancient protein.

Tyler N Starr, Lora K Picton, Joseph W Thornton

Abstract readValidation Study
In one paragraph

Article in Nature, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 120 papers.

0numbers the graph read from it
0cells of the map it votes in
120citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

120 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Structural and evolutionary constraints of organophosphate resistance in dipteran carboxylesterases.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. TF paralogs-Natural experiments in DNA binding.Current opinion in structural biology · 2025
    Review
  14. Epistatic drift in protein evolution.Current opinion in genetics & development · 2025
    Review
  15. BTK autoinhibition analyzed by high-throughput swaps of SH2 domains.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  16. Review
  17. Favorable epistasis in ancestral diterpene synthases promoted convergent evolution of a resin acid precursor in conifers.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  18. Article
  19. Inference and visualization of complex genotype-phenotype maps withbioRxiv : the preprint server for biology · 2025
    Article
  20. Article

60 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Tyler N StarrDepartment of Biochemistry and Molecular Biology, University of Chicago, Chicago, Illinois 60637, USA.
Lora K PictonDepartment of Ecology and Evolution, University of Chicago, Chicago, Illinois 60637, USA.
Joseph W ThorntonDepartment of Ecology and Evolution, University of Chicago, Chicago, Illinois 60637, USA.

Funding

Molecular And Cellular Biology Training ProgramT32GM007183 · NIGMS · UNIVERSITY OF CHICAGO · PI GLICK, BENJAMIN S, RICE, PHOEBE A · 1985 to 2021
$23.9M
Re-Engineering Translational Research at the University of ChicagoUL1TR000430 · NCATS · UNIVERSITY OF CHICAGO · PI SOLWAY, JULIAN · 2012 to 2016
$20.2M
Mechanisms for the evolution of novel DNA specificity in a transcription factor fR01GM104397 · NIGMS · UNIVERSITY OF CHICAGO · PI THORNTON, JOSEPH W · 2013 to 2016
$1.3M
Deep characterization of the sequence space and evolutionary trajectories of reconstructed ancestral proteins - Resubmission 01R01GM121931 · NIGMS · UNIVERSITY OF CHICAGO · PI THORNTON, JOSEPH W · 2017 to 2020
$1.3M
NCATS NIH HHS UL1 TR000430NIGMS NIH HHS R01 GM104397NIGMS NIH HHS R01 GM121931NIGMS NIH HHS T32 GM007183
6 · The paper itself

Abstract

To understand why molecular evolution turned out as it did, we must characterize not only the path that evolution followed across the space of possible molecular sequences but also the many alternative trajectories that could have been taken but were not. A large-scale comparison of real and possible histories would establish whether the outcome of evolution represents an optimal state driven by natural selection or the contingent product of historical chance events; it would also reveal how the underlying distribution of functions across sequence space shaped historical evolution. Here we combine ancestral protein reconstruction with deep mutational scanning to characterize alternative histories in the sequence space around an ancient transcription factor, which evolved a novel biological function through well-characterized mechanisms. We find hundreds of alternative protein sequences that use diverse biochemical mechanisms to perform the derived function at least as well as the historical outcome. These alternatives all require prior permissive substitutions that do not enhance the derived function, but not all require the same permissive changes that occurred during history. We find that if evolution had begun from a different starting point within the network of sequences encoding the ancestral function, outcomes with different genetic and biochemical forms would probably have resulted; this contingency arises from the distribution of functional variants in sequence space and epistasis between residues. Our results illuminate the topology of the vast space of possibilities from which history sampled one path, highlighting how the outcome of evolution depends on a serial chain of compounding chance events.

Indexed as

Evolution, MolecularAmino Acid SequenceBase SequenceDNADNA-Binding ProteinsMutationReceptors, SteroidResponse ElementsSelection, GeneticSubstrate SpecificityDNADNA-Binding ProteinsReceptors, Steroid

Identifiers

PMID28902834
PMCPMC6214350

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.