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Cited by 360Morphological variations and asymmetryEvolution and Paleontology StudiesEvolution and Genetic Dynamics

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The macroevolutionary consequences of phenotypic integration: from development to deep time

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Goswami, A., Smaers, J. B., Soligo, C., Polly, P. D.·2014·Philosophical Transactions of the Royal Society B: Biological Sciences
DOI 10.1098/rstb.2013.0254PMC PMC4084539
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Abstract

Phenotypic integration is a pervasive characteristic of organisms. Numerous analyses have demonstrated that patterns of phenotypic integration are conserved across large clades, but that significant variation also exists. For example, heterochronic shifts related to different mammalian reproductive strategies are reflected in postcranial skeletal integration and in coordination of bone ossification. Phenotypic integration and modularity have been hypothesized to shape morphological evolution, and we extended simulations to confirm that trait integration can influence both the trajectory and magnitude of response to selection. We further demonstrate that phenotypic integration can produce both more and less disparate organisms than would be expected under random walk models by repartitioning variance in preferred directions. This effect can also be expected to favour homoplasy and convergent evolution. New empirical analyses of the carnivoran cranium show that rates of evolution, in contrast, are not strongly influenced by phenotypic integration and show little relationship to morphological disparity, suggesting that phenotypic integration may shape the direction of evolutionary change, but not necessarily the speed of it. Nonetheless, phenotypic integration is problematic for morphological clocks and should be incorporated more widely into models that seek to accurately reconstruct both trait and organismal evolution.

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Integrity signals

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Crossref · 10.1098/rstb.2013.0254

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Figures

Figure 1. Modularity is hypothesized to increase, and overall integration to decrease, through evolutionary and developmental time.
Figure 1. Modularity is hypothesized to increase, and overall integration to decrease, through evolutionary and developmental time.CC BY · PubMed Central
Figure 2. Cranial and postcranial modularity shift during mammalian evolution. Coloured symbols or elements refer to significantly correlated traits in previous morphometric analyses.
Figure 2. Cranial and postcranial modularity shift during mammalian evolution. Coloured symbols or elements refer to significantly correlated traits in previous morphometric analyses.CC BY · PubMed Central
Figure 3. Number of significant sister group comparisons for postcranial modules. Elements involved in each postcranial module are shown in red on dog skeletons. Marsupials (in black) show more coordination of modules that involve either anterior or posterior elements, whereas placentals (in green) predominantly display significant coordination of modules that involve both anterior and posterior elements. Adapted from [34].
Figure 3. Number of significant sister group comparisons for postcranial modules. Elements involved in each postcranial module are shown in red on dog skeletons. Marsupials (in black) show more coordination of modules that involve either anterior or posterior elements, whereas placentals (in green) predominantly display significant coordination of modules that involve both anterior and posterior elements. Adapted from [34].CC BY · PubMed Central
Figure 4. Relationship among one measure of integration (λrel s.d.) and various measures of response to selection. (a) λrel s.d. and respondability; (b) λrel s.d. and evolvability; (c) λrel s.d. and constraint; (d) flexibility and constraint. Integration, respondability, flexibility and constraint are highly intercorrelated, whereas evolvability and integration show no substantial relationship.
Figure 4. Relationship among one measure of integration (λrel s.d.) and various measures of response to selection. (a) λrel s.d. and respondability; (b) λrel s.d. and evolvability; (c) λrel s.d. and constraint; (d) flexibility and constraint. Integration, respondability, flexibility and constraint are highly intercorrelated, whereas evolvability and integration show no substantial relationship.CC BY · PubMed Central
Figure 5. Examples of simulated trait evolution with (grey; red in online version) and without (black) trait integration. (a) Simulation of covariance matrix with λrel s.d. = 0.28. (b) Simulation of covariance matrix with λrel s.d. = 0.46. (c) Relationship between λrel s.d. and ratio of range for integrated traits against range for uncorrelated traits. Range is positively correlated with magnitude of phenotypic integration. (Online version in colour.)
Figure 5. Examples of simulated trait evolution with (grey; red in online version) and without (black) trait integration. (a) Simulation of covariance matrix with λrel s.d. = 0.28. (b) Simulation of covariance matrix with λrel s.d. = 0.46. (c) Relationship between λrel s.d. and ratio of range for integrated traits against range for uncorrelated traits. Range is positively correlated with magnitude of phenotypic integration. (Online version in colour.)CC BY · PubMed Central
Figure 6. Graphs showing phenotypic divergence over time of 1000 simulations of uncorrelated (grey; red in online version) and correlated (black) shape variables. (a) Ten traits with variances of 1.0 and covariances of 0.0 and 0.9, respectively. (b) Skull shape of carnivorans defined by the variance–covariance matrix described above. Phenotypes for uncorrelated trait complexes have a tighter distribution with respect to time since divergence than do correlated trait complexes and demonstrate both the effects of trait integration on morphological range and the problem that it creates for morphological clocks. (Online version in colour.)
Figure 6. Graphs showing phenotypic divergence over time of 1000 simulations of uncorrelated (grey; red in online version) and correlated (black) shape variables. (a) Ten traits with variances of 1.0 and covariances of 0.0 and 0.9, respectively. (b) Skull shape of carnivorans defined by the variance–covariance matrix described above. Phenotypes for uncorrelated trait complexes have a tighter distribution with respect to time since divergence than do correlated trait complexes and demonstrate both the effects of trait integration on morphological range and the problem that it creates for morphological clocks. (Online version in colour.)CC BY · PubMed Central
Figure 7. Landmark variance and relative rate of evolution, grouped by cranial module. Symbols are as follows: squares, anterior oral–nasal; triangles, molar–palate; open circles, orbit; inverted triangles, cranial vault; diamonds, zygomatic–pterygoid; closed circles, basicranium.
Figure 7. Landmark variance and relative rate of evolution, grouped by cranial module. Symbols are as follows: squares, anterior oral–nasal; triangles, molar–palate; open circles, orbit; inverted triangles, cranial vault; diamonds, zygomatic–pterygoid; closed circles, basicranium.CC BY · PubMed Central

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Citations

Cites

Research works printed but not linked: 11

  1. Schlosser G, 2004, Modularity in development and evolution
  2. Atchley WR, 1993, The skull. 1 Development, 207
  3. Cheverud JM, 2004, Modularity in development and evolution, 132
  4. Goswami A, 2010, Quantitative methods in paleobiology, 213
  5. 10.1002/1096-8644(2000)43:31 <117::AID-AJPA5>3.3.CO;2-9 · DOI
  6. Klingenberg CP, 2008, MorphoJ
  7. Schlosser G, 2005, Modularity in development and evolution, 519
  8. Shubin N, 2004, Modularity in development and evolution, 429
  9. Zelditch ML, 2001, Beyond heterochrony: the evolution of development, 145
  10. Polly PD, 2012, Phylogenetics for mathematica, 2.1 edn
  11. Polly PD, 2004, On the simulation of the evolution of morphological shape: multivariate shape under selection and drift, Palaeontol. Electron., 7, 1

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Metadata

Authors
Goswami, A., Smaers, J. B., Soligo, C., & Polly, P. D.
Affiliations
  • University College London (GB)
  • Indiana University Bloomington (US)
Corresponding author
Goswami, A.
ORCID
Venue
Philosophical Transactions of the Royal Society B: Biological Sciences
Publisher
The Royal Society
Published
2014-08-19
Volume
369
Issue
1649
Pages
20130254
ISSN
  • 0962-8436 (ISSN-L)
  • 1471-2970
DOI
10.1098/rstb.2013.0254
PMC
PMC4084539
OpenAlex
W2158213278
Cited by
359
References
133
Citations by year
2026: 20 · 2025: 30 · 2024: 27 · 2023: 39 · 2022: 30 · 2021: 40 · 2020: 30 · 2019: 42 · 2018: 34 · 2017: 19 · 2016: 26 · 2015: 17 · 2014: 5
FWCI
31.00
Type
journal article
Language
en
Open access
Licence
Locations
  • Philosophical Transactions of the Royal Society B Biological Sciences (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • UCL Discovery (University College London) (submittedVersion)
Funders
  • National Science Foundation (0308765, 0502186)
  • American Museum of Natural History
  • University of Chicago
  • Field Museum
  • Royal Society
  • University of New South Wales
  • National Museum of Natural History
  • Natural Environment Research Council (NE/J012432/1, NE/H022937/1)
  • Office of International Science and Engineering
  • University of California Museum of Paleontology
Topics
  • Life Sciences › Agricultural and Biological Sciences › Ecology, Evolution, Behavior and Systematics › Morphological variations and asymmetry
  • Physical Sciences › Earth and Planetary Sciences › Paleontology › Evolution and Paleontology Studies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
Keywords
phenotypic integration, modularity, morphological evolution, heterochrony, postcranial skeleton, ossification, selection response, morphological disparity, homoplasy, convergent evolution, evolutionary rates, random walks
MeSH terms
Animals, Biological Evolution, Models, Biological, Phenotype, Phylogeny, Selection, Genetic, Time Factors, Vertebrates, Developmental Biology, Body Patterning, Biodiversity, Systems Biology

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