Evidence map›Paper›PMID 24939468›Full record

ArticleMolecular biology and evolution2014

Investigating population history using temporal genetic differentiation.

Pontus Skoglund, Per Sjödin, Tobias Skoglund, Martin Lascoux, Mattias Jakobsson

Abstract read
In one paragraph

Article in Molecular biology and evolution, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Sometimes hidden but always there: the assumptions underlying genetic inference of demographic histories.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2021
    Review
  9. Article
  10. Article
  11. Article
  12. FHeredity · 2019
    Article
  13. Article
  14. Inferring genetic connectivity in real populations, exemplified by coastal and oceanic Atlantic cod.Proceedings of the National Academy of Sciences of the United States of America · 2018
    Article
  15. Article
  16. Article
  17. Estimating mobility using sparse data: Application to human genetic variation.Proceedings of the National Academy of Sciences of the United States of America · 2017
    Article
  18. Article
  19. Statistical methods for analyzing ancient DNA from hominins.Current opinion in genetics & development · 2016
    Review
  20. Isolation-by-distance-and-time in a stepping-stone model.Theoretical population biology · 2016
    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.

Pontus SkoglundDepartment of Evolutionary Biology, Uppsala University, Uppsala, Sweden skoglund@genetics.med.harvard.edu mattias.jakobsson@ebc.uu.se.
Per SjödinDepartment of Evolutionary Biology, Uppsala University, Uppsala, Sweden.
Tobias SkoglundDepartment of Evolutionary Biology, Uppsala University, Uppsala, SwedenDepartment of Information Technology, Uppsala University, Uppsala, Sweden.
Martin LascouxDepartment of Ecology and Genetics, Program in Plant Ecology and Evolution, Uppsala University, Uppsala, SwedenScience for Life Laboratory, Uppsala, Sweden.
Mattias JakobssonDepartment of Evolutionary Biology, Uppsala University, Uppsala, SwedenScience for Life Laboratory, Uppsala, Sweden skoglund@genetics.med.harvard.edu mattias.jakobsson@ebc.uu.se.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapid advance of sequencing technology, coupled with improvements in molecular methods for obtaining genetic data from ancient sources, holds the promise of producing a wealth of genomic data from time-separated individuals. However, the population-genetic properties of time-structured samples have not been extensively explored. Here, we consider the implications of temporal sampling for analyses of genetic differentiation and use a temporal coalescent framework to show that complex historical events such as size reductions, population replacements, and transient genetic barriers between populations leave a footprint of genetic differentiation that can be traced through history using temporal samples. Our results emphasize explicit consideration of the temporal structure when making inferences and indicate that genomic data from ancient individuals will greatly increase our ability to reconstruct population history.

Indexed as

Genetic VariationPhylogenyAlgorithmsAnimalsComputational BiologyGenetic DriftHumansPopulation DynamicsSampling Studiesancient DNAFSTgenetic differentiationpopulation structuretime-serial sampling

Identifiers

PMID24939468
PMCPMC4137715

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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.