Developmental sources of conservation and variation in the evolution of the primate eye

Dyer, Michael A.; Martins, Rodrigo A. P.; Filho, Manoel da Silva; Muniz, José Augusto Pereira Carneiro; Silveira, Luiz Carlos de Lima; Cepko, Constance L.; Finlay, Barbara L.

doi:10.1073/pnas.0901484106

Cited by 68 publications

(71 citation statements)

References 40 publications

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“…The cells with delayed onset of terminal divisions are either rods or cells with direct connections to rods (bipolar cell generation has not been measured in the cat). This result is directly comparable to empirical observations we have made in the nocturnal owl monkey(Aotus azarae) retina where rod and bipolar cell numbers greatly increase, compared with much smaller changes in cone and retinal ganglion cell numbers, all compared with a closely related diurnal monkey, the capuchin monkey (Cebus apella) (Dyer et al, 2009). While the cat is not the only nocturnal mammal in this dataset, its adaptation to nocturnality resembles that seen in primates (Ross and Kirk, 2007) contrasted with the nocturnal ferret, rodents, and metatherian mammals described here.…”

Section: The Interaction Termssupporting

confidence: 76%

“…However, the organization of this database is designed to be hospitable to evo-devo hypothesis testing, where suggestive trends observed in the existing data can be followed by predictions of the relative timing in new species for neural events not yet measured, or predictions can be made for categories not yet explored here. Our prediction and test of later retinogenesis in the cat, derived from our observations in the nocturnal owl monkey (Dyer et al, 2009), are of that kind.…”

Section: Considerations In the Choice Of Modelmentioning

confidence: 99%

“…We confirmed high predictability in early brain development, but also identified developmental adjustments related to speciation. For example, cortex enlargement in primates ) and nocturnal adaptation of the retina in the owl monkey (Dyer et al, 2009) are both associated with selective delays in neurogenesis.…”

Section: Introductionmentioning

confidence: 99%

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Modeling Transformations of Neurodevelopmental Sequences across Mammalian Species

et al. 2013

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A general model of neural development is derived to fit 18 mammalian species, including humans, macaques, several rodent species, and six metatherian (marsupial) mammals. The goal of this work is to describe heterochronic changes in brain evolution within its basic developmental allometry, and provide an empirical basis to recognize equivalent maturational states across animals. The empirical data generating the model comprises 271 developmental events, including measures of initial neurogenesis, axon extension, establishment, and refinement of connectivity, as well as later events such as myelin formation, growth of brain volume, and early behavioral milestones, to the third year of human postnatal life. The progress of neural events across species is sufficiently predictable that a single model can be used to predict the timing of all events in all species, with a correlation of modeled values to empirical data of 0.9929. Each species' rate of progress through the event scale, described by a regression equation predicting duration of development in days, is highly correlated with adult brain size. Neural heterochrony can be seen in selective delay of retinogenesis in the cat, associated with greater numbers of rods in its retina, and delay of corticogenesis in all species but rodents and the rabbit, associated with relatively larger cortices in species with delay. Unexpectedly, precocial mammals (those unusually mature at birth) delay the onset of first neurogenesis but then progress rapidly through remaining developmental events.

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Section: The Interaction Termssupporting

confidence: 76%

Section: Considerations In the Choice Of Modelmentioning

confidence: 99%

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Modeling Transformations of Neurodevelopmental Sequences across Mammalian Species

et al. 2013

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“…This delay is accompanied by the emergence of a 'sub-ventricular zone' [92], analogous to that observed in large-brained mammals which is thought to underpin cortical expansion [94]. A similar mechanism may facilitate the expansion of the retina in nocturnal owl monkeys (Aotus azarae) [93].…”

Section: (E) Developmental Models Of Mosaic Evolutionmentioning

confidence: 92%

Brain evolution and development: adaptation, allometry and constraint

2016

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Phenotypic traits are products of two processes: evolution and development. But how do these processes combine to produce integrated phenotypes? Comparative studies identify consistent patterns of covariation, or allometries, between brain and body size, and between brain components, indicating the presence of significant constraints limiting independent evolution of separate parts. These constraints are poorly understood, but in principle could be either developmental or functional. The developmental constraints hypothesis suggests that individual components (brain and body size, or individual brain components) tend to evolve together because natural selection operates on relatively simple developmental mechanisms that affect the growth of all parts in a concerted manner. The functional constraints hypothesis suggests that correlated change reflects the action of selection on distributed functional systems connecting the different sub-components, predicting more complex patterns of mosaic change at the level of the functional systems and more complex genetic and developmental mechanisms. These hypotheses are not mutually exclusive but make different predictions. We review recent genetic and neurodevelopmental evidence, concluding that functional rather than developmental constraints are the main cause of the observed patterns. How brains evolve: the importance of scaling relationshipsThe components of any adaptive complex by definition undergo coordinated evolution. Brains, bodies and individual brain components therefore exhibit distinctive patterns of correlated evolution. But what do these patterns tell us about the roles of adaptation and constraint in shaping phenotypes? In particular, how and to what extent do constraints imposed by shared developmental programmes dictate allometric relationships between components, limiting their response to selection? These questions have shaped two key debates central to how we view brain evolution: the functional relevance of brain size and the adaptive potential of brain structure [1][2][3]. These debates hinge on whether observed patterns of scaling relationships, between brain and body size or different brain components, are the product of selection to maintain functional correspondence or constraints imposed by shared developmental programmes. Crucially, however, a sound understanding of the significance of scaling relationships in brain evolution has been limited by a lack of data on the genetic and developmental mechanisms that regulate brain size and structure. Here we discuss how recent discoveries about the genetic control of neural development shed new light on the issue.(a) Brain: body coevolution and the importance of size

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“…Overall, our data show that there are several mechanisms for evolutionary alterations in brain size. Previous studies focused on the length of development and neurogenesis timing (Finlay & Darlington 1995;Clancy et al 2001;Dyer et al 2009). We show that species differences in cell cycle rates prior to neurogenesis account for at least some adult species differences in brain size.…”

Section: Discussionmentioning

confidence: 99%

Bigger brains cycle faster before neurogenesis begins: a comparison of brain development between chickens and bobwhite quail

Charvet

Striedter

2010

Proc. R. Soc. B.

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The chicken brain is more than twice as big as the bobwhite quail brain in adulthood. To determine how this species difference in brain size emerges during development, we examined whether differences in neurogenesis timing or cell cycle rates account for the disparity in brain size between chickens and quail. Specifically, we examined the timing of neural events (e.g. neurogenesis onset) from Nissl-stained sections of chicken and quail embryos. We estimated brain cell cycle rates using cumulative bromodeoxyuridine labelling in chickens and quail at embryonic day (ED) 2 and at ED5. We report that the timing of neural events is highly conserved between chickens and quail, once time is expressed as a percentage of overall incubation period. In absolute time, neurogenesis begins earlier in chickens than in quail. Therefore, neural event timing cannot account for the expansion of the chicken brain relative to the quail brain. Cell cycle rates are also similar between the two species at ED5. However, at ED2, before neurogenesis onset, brain cells cycle faster in chickens than in quail. These data indicate that chickens have a larger brain than bobwhite quail mainly because of species differences in cell cycle rates during early stages of embryonic development.

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Developmental sources of conservation and variation in the evolution of the primate eye

Cited by 68 publications

References 40 publications

Modeling Transformations of Neurodevelopmental Sequences across Mammalian Species

Modeling Transformations of Neurodevelopmental Sequences across Mammalian Species

Brain evolution and development: adaptation, allometry and constraint

Bigger brains cycle faster before neurogenesis begins: a comparison of brain development between chickens and bobwhite quail

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