Evidence map›Paper›PMID 31154982›Full record

ReviewPhilosophical transactions of the Royal Society of London. Series B, Biological sciences2019

Integrating natural history collections and comparative genomics to study the genetic architecture of convergent evolution.

Sangeet Lamichhaney, Daren C Card, Phil Grayson, João F R Tonini, Gustavo A Bravo, Kathrin Näpflin, Flavia Termignoni-Garcia, Christopher Torres, Frank Burbrink, Julia A Clarke and 2 more

Abstract readReview
In one paragraph

Review in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

  1. Article
  2. Review
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  5. Article
  6. Article
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  9. Genomics expands the mammalverse.Science (New York, N.Y.) · 2023
    Article
  10. Article
  11. Article
  12. Genomic basis of parallel adaptation varies with divergence inProceedings of the National Academy of Sciences of the United States of America · 2021
    Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
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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

12 authors.

Sangeet Lamichhaney1 Department of Organismic and Evolutionary Biology, Harvard University , Cambridge, MA 02138 , USA.
Daren C Card1 Department of Organismic and Evolutionary Biology, Harvard University , Cambridge, MA 02138 , USA.
Phil Grayson1 Department of Organismic and Evolutionary Biology, Harvard University , Cambridge, MA 02138 , USA.
João F R Tonini1 Department of Organismic and Evolutionary Biology, Harvard University , Cambridge, MA 02138 , USA.
Gustavo A Bravo1 Department of Organismic and Evolutionary Biology, Harvard University , Cambridge, MA 02138 , USA.
Kathrin Näpflin1 Department of Organismic and Evolutionary Biology, Harvard University , Cambridge, MA 02138 , USA.
Flavia Termignoni-Garcia1 Department of Organismic and Evolutionary Biology, Harvard University , Cambridge, MA 02138 , USA.
Christopher Torres5 Department of Biology, The University of Texas at Austin , Austin, MA 78712 , USA.
Frank Burbrink7 Department of Herpetology, The American Museum of Natural History , New York, NY 10024 , USA.
Julia A Clarke5 Department of Biology, The University of Texas at Austin , Austin, MA 78712 , USA.
Timothy B Sackton3 Informatics Group, Harvard University , Cambridge, MA 02138 , USA.
Scott V Edwards1 Department of Organismic and Evolutionary Biology, Harvard University , Cambridge, MA 02138 , USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Evolutionary convergence has been long considered primary evidence of adaptation driven by natural selection and provides opportunities to explore evolutionary repeatability and predictability. In recent years, there has been increased interest in exploring the genetic mechanisms underlying convergent evolution, in part, owing to the advent of genomic techniques. However, the current 'genomics gold rush' in studies of convergence has overshadowed the reality that most trait classifications are quite broadly defined, resulting in incomplete or potentially biased interpretations of results. Genomic studies of convergence would be greatly improved by integrating deep 'vertical', natural history knowledge with 'horizontal' knowledge focusing on the breadth of taxonomic diversity. Natural history collections have and continue to be best positioned for increasing our comprehensive understanding of phenotypic diversity, with modern practices of digitization and databasing of morphological traits providing exciting improvements in our ability to evaluate the degree of morphological convergence. Combining more detailed phenotypic data with the well-established field of genomics will enable scientists to make progress on an important goal in biology: to understand the degree to which genetic or molecular convergence is associated with phenotypic convergence. Although the fields of comparative biology or comparative genomics alone can separately reveal important insights into convergent evolution, here we suggest that the synergistic and complementary roles of natural history collection-derived phenomic data and comparative genomics methods can be particularly powerful in together elucidating the genomic basis of convergent evolution among higher taxa. This article is part of the theme issue 'Convergent evolution in the genomics era: new insights and directions'.

Indexed as

Evolution, MolecularAnimalsGenomeGenomicsInvertebratesPhylogenySelection, GeneticVertebratesamino acidbirdenhancereusocialitypleiotropyregulatory evolution

Identifiers

PMID31154982
PMCPMC6560268

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.