Evidence map›Paper›PMID 22942677›Full record

ArticleCurrent genomics2012

Using genetic networks and homology to understand the evolution of phenotypic traits.

Amy R McCune, John C Schimenti

Abstract read
In one paragraph

Article in Current genomics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Review
  10. Shared developmental and evolutionary origins for neural basis of vocal-acoustic and pectoral-gestural signaling.Proceedings of the National Academy of Sciences of the United States of America · 2012
    Review
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

2 authors.

Amy R McCuneDepartment of Ecology and Evolutionary Biology, Corson Hall, Cornell University, Ithaca, NY 14853, USA.
John C Schimenti

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Homology can have different meanings for different kinds of biologists. A phylogenetic view holds that homology, defined by common ancestry, is rigorously identified through phylogenetic analysis. Such homologies are taxic homologies (=synapomorphies). A second interpretation, "biological homology" emphasizes common ancestry through the continuity of genetic information underlying phenotypic traits, and is favored by some developmental geneticists. A third kind of homology, deep homology, was recently defined as "the sharing of the genetic regulatory apparatus used to build morphologically and phylogenetically disparate features." Here we explain the commonality among these three versions of homology. We argue that biological homology, as evidenced by a conserved gene regulatory network giving a trait its "essential identity" (a Character Identity Network or "ChIN") must also be a taxic homology. In cases where a phenotypic trait has been modified over the course of evolution such that homology (taxic) is obscured (e.g. jaws are modified gill arches), a shared underlying ChIN provides evidence of this transformation. Deep homologies, where molecular and cellular components of a phenotypic trait precede the trait itself (are phylogenetically deep relative to the trait), are also taxic homologies, undisguised. Deep homologies inspire particular interest for understanding the evolutionary assembly of phenotypic traits. Mapping these deeply homologous building blocks on a phylogeny reveals the sequential steps leading to the origin of phenotypic novelties. Finally, we discuss how new genomic technologies will revolutionize the comparative genomic study of non-model organisms in a phylogenetic context, necessary to understand the evolution of phenotypic traits.

Indexed as

deep homologyGene regulatory networksgenomicsNext Gen Sequencing.taxic homologytransformational homology

Identifiers

PMID22942677
PMCPMC3269019

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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.