Evidence map›Paper›PMID 27304973›Full record

ArticleBiology2016

Cryptic Genetic Variation in Evolutionary Developmental Genetics.

Annalise B Paaby, Greg Gibson

Abstract read
In one paragraph

Article in Biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Tradeoffs in Modeling Context Dependency in Complex Trait Genetics.bioRxiv : the preprint server for biology · 2025
    Article
  4. Review
  5. The AncestralG3 (Bethesda, Md.) · 2020
    Article
  6. Article
  7. 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

2 authors.

Annalise B PaabySchool of Biology, Georgia Institute of Technology, Atlanta, GA 30332, USA. annalise.paaby@biology.gatech.edu.
Greg GibsonSchool of Biology, Georgia Institute of Technology, Atlanta, GA 30332, USA. greg.gibson@biology.gatech.edu.

Funding

Statistical Methods for X-Chromosome Genetic DataP01GM099568 · NIGMS · UNIVERSITY OF WASHINGTON · PI WEIR, BRUCE S. · 2012 to 2016
$7.3M
Genetic Architecture and Developmental Consequences of Conditionally Functional MutationsR35GM119744 · NIGMS · GEORGIA INSTITUTE OF TECHNOLOGY · PI PAABY, ANNALISE BLOSS · 2016 to 2020
$1.8M
NIGMS NIH HHS P01 GM099568NIGMS NIH HHS R35 GM119744
6 · The paper itself

Abstract

Evolutionary developmental genetics has traditionally been conducted by two groups: Molecular evolutionists who emphasize divergence between species or higher taxa, and quantitative geneticists who study variation within species. Neither approach really comes to grips with the complexities of evolutionary transitions, particularly in light of the realization from genome-wide association studies that most complex traits fit an infinitesimal architecture, being influenced by thousands of loci. This paper discusses robustness, plasticity and lability, phenomena that we argue potentiate major evolutionary changes and provide a bridge between the conceptual treatments of macro- and micro-evolution. We offer cryptic genetic variation and conditional neutrality as mechanisms by which standing genetic variation can lead to developmental system drift and, sheltered within canalized processes, may facilitate developmental transitions and the evolution of novelty. Synthesis of the two dominant perspectives will require recognition that adaptation, divergence, drift and stability all depend on similar underlying quantitative genetic processes-processes that cannot be fully observed in continuously varying visible traits.

Indexed as

cryptic genetic variationdevelopmentevolutiongeneticsquantitative genetics

Identifiers

PMID27304973
PMCPMC4929542

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.