Evidence map›Paper›PMID 25731894›Full record

ArticleScientific reports2015

Distance-dependent patterns of molecular divergences in Tuatara mitogenomes.

Sankar Subramanian, Elmira Mohandesan, Craig D Millar, David M Lambert

Abstract read
In one paragraph

Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Pseudogenization of theZoological research · 2017
    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

4 authors.

Sankar SubramanianEnviromental Futures Research Institute, Griffith University, Nathan 4111, Australia.
Elmira MohandesanAllan Wilson Centre for Molecular Ecology and Evolution, Massey University, New Zealand.
Craig D MillarAllan Wilson Centre for Molecular Ecology and Evolution, School of Biological Sciences, University of Auckland, Private 92019, Auckland, New Zealand.
David M LambertEnviromental Futures Research Institute, Griffith University, Nathan 4111, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Population genetic models predict that populations that are geographically close to each other are expected to be genetically more similar to each other compared to those that are widely separate. However the patterns of relationships between geographic distance and molecular divergences at neutral and constrained regions of the genome are unclear. We attempted to clarify this relationship by sequencing complete mitochondrial genomes of the relic species Tuatara (Sphenodon punctatus) from ten offshore islands of New Zealand. We observed a positive relationship that showed a proportional increase in the neutral diversity at synonymous sites (dS), with increasing geographical distance. In contrast we showed that diversity at evolutionarily constrained sites (dC) was elevated in the case of comparisons involving closely located populations. Conversely diversity was reduced in the case of comparisons between distantly located populations. These patterns were confirmed by a significant negative relationship between the ratio of dC/dS and geographic distance. The observed high dC/dS could be explained by the abundance of deleterious mutations in comparisons involving closely located populations, due to the recent population divergence times. Since distantly related populations were separated over long periods of time, deleterious mutations might have been removed by purifying selection.

Indexed as

Evolution, MolecularGenetic VariationGenome, MitochondrialAnimalsGenetics, PopulationGeographyIslandsLizardsNew ZealandOpen Reading FramesPhylogeny

Identifiers

PMID25731894
PMCPMC4346810

What OpenQuestion holds

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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.