Evidence map›Paper›PMID 27628687›Full record

ArticleNature communications2016

An experimental phylogeny to benchmark ancestral sequence reconstruction.

Ryan N Randall, Caelan E Radford, Kelsey A Roof, Divya K Natarajan, Eric A Gaucher

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed
4.9field-weighted citation impact, top 4% of its field
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

45 citing papers in PubMed, 82 citations in OpenAlex.

  1. Highly efficient production ofSynthetic and systems biotechnology · 2027
    Article
  2. Ancient enzymes, new biotechnology applications.Nature reviews. Molecular cell biology · 2026
    Article
  3. Article
  4. High-stoichiometry mRNA (New York, N.Y.) · 2026
    Article
  5. Article
  6. Article
  7. Article
  8. Applications of ancestral sequence reconstruction for understanding the evolution of plant specialized metabolism.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
    Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Methodologies for Microbial Ancestral Sequence Reconstruction.Methods in molecular biology (Clifton, N.J.) · 2022
    Review
  20. Ancestral Sequence Reconstruction for Exploring Alkaloid Evolution.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
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

5 authors at 1 institution in 1 country.

Ryan N RandallSchool of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
Caelan E RadfordSchool of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
Kelsey A RoofSchool of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
Divya K NatarajanSchool of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
Eric A GaucherSchool of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
Georgia Institute of Technology · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ancestral sequence reconstruction (ASR) is a still-burgeoning method that has revealed many key mechanisms of molecular evolution. One criticism of the approach is an inability to validate its algorithms within a biological context as opposed to a computer simulation. Here we build an experimental phylogeny using the gene of a single red fluorescent protein to address this criticism. The evolved phylogeny consists of 19 operational taxonomic units (leaves) and 17 ancestral bifurcations (nodes) that display a wide variety of fluorescent phenotypes. The 19 leaves then serve as 'modern' sequences that we subject to ASR analyses using various algorithms and to benchmark against the known ancestral genotypes and ancestral phenotypes. We confirm computer simulations that show all algorithms infer ancient sequences with high accuracy, yet we also reveal wide variation in the phenotypes encoded by incorrectly inferred sequences. Specifically, Bayesian methods incorporating rate variation significantly outperform the maximum parsimony criterion in phenotypic accuracy. Subsampling of extant sequences had minor effect on the inference of ancestral sequences.

Indexed as

Base SequenceGenetic TechniquesPhenotypePhylogenyAlgorithmsBayes TheoremComputer SimulationLuminescent ProteinsRed Fluorescent ProteinLuminescent ProteinsRed Fluorescent Protein

Identifiers

PMID27628687
PMCPMC5027606
OpenAlexW2520644633

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.