G1 Phase Regulation, Area-Specific Cell Cycle Control, and Cytoarchitectonics in the Primate Cortex

Lukaszewicz, Agnès; Savatier, Pierre; Cortay, Véronique; Giroud, Pascale; Huissoud, Cyril; Berland, Michel; Kennedy, Henry; Dehay, Colette

doi:10.1016/j.neuron.2005.06.032

Cited by 293 publications

(312 citation statements)

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“…The duration of S‐phase in the different progenitor subpopulations showed a much greater variation, ranging from 1.9 hours (bIPs in ISVZ) to 22.6 hours (bRG in OSVZ) (Table 1). These results place the cell cycle duration of ferret neocortical progenitors closer to those of primates (Betizeau et al, 2013; Kornack and Rakic, 1998; Lukaszewicz et al, 2005) than to rodents (Arai et al, 2011; Takahashi et al, 1995), consistent with the overall longer neurogenic period in the gyrencephalic species studied so far.…”

Section: Resultssupporting

confidence: 78%

“…Observations of cell cycle shortening toward the end of neurogenesis in other species (Kornack and Rakic, 1998; Reillo and Borrell, 2012), as well as studies in the macaque showing that progenitors cycle faster when generating neurons for the supragranular‐dense cortical area 17, compared with those in area 18 (Lukaszewicz et al, 2005), suggest a role of cell cycle length in both the regulation of greater neuron output in specific areas during development and the overall generation of neurons in evolution.…”

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confidence: 95%

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S‐phase duration is the main target of cell cycle regulation in neural progenitors of developing ferret neocortex

García

Chang

Arai

et al. 2015

J of Comparative Neurology

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The evolutionary expansion of the neocortex primarily reflects increases in abundance and proliferative capacity of cortical progenitors and in the length of the neurogenic period during development. Cell cycle parameters of neocortical progenitors are an important determinant of cortical development. The ferret (Mustela putorius furo), a gyrencephalic mammal, has gained increasing importance as a model for studying corticogenesis. Here, we have studied the abundance, proliferation, and cell cycle parameters of different neural progenitor types, defined by their differential expression of the transcription factors Pax6 and Tbr2, in the various germinal zones of developing ferret neocortex. We focused our analyses on postnatal day 1, a late stage of cortical neurogenesis when upper‐layer neurons are produced. Based on cumulative 5‐ethynyl‐2′‐deoxyuridine (EdU) labeling as well as Ki67 and proliferating cell nuclear antigen (PCNA) immunofluorescence, we determined the duration of the various cell cycle phases of the different neocortical progenitor subpopulations. Ferret neocortical progenitors were found to exhibit longer cell cycles than those of rodents and little variation in the duration of G1 among distinct progenitor types, also in contrast to rodents. Remarkably, the main difference in cell cycle parameters among the various progenitor types was the duration of S‐phase, which became shorter as progenitors progressively changed transcription factor expression from patterns characteristic of self‐renewal to those of neuron production. Hence, S‐phase duration emerges as major target of cell cycle regulation in cortical progenitors of this gyrencephalic mammal. J. Comp. Neurol. 524:456–470, 2016. © 2015 The Authors The Journal of Comparative Neurology Published by Wiley Periodicals, Inc.

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Section: Resultssupporting

confidence: 78%

mentioning

confidence: 95%

S‐phase duration is the main target of cell cycle regulation in neural progenitors of developing ferret neocortex

García

Chang

Arai

et al. 2015

J of Comparative Neurology

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“…Fetuses from timed‐pregnant cynomolgus monkeys ( Macaca fascicularis , gestation period 165 days) were delivered by caesarian section as described elsewhere (Lukaszewicz et al, 2005). All experiments are in compliance with national and European regulations as well as with institutional guidelines concerning animal experimentation.…”

Section: Methodsmentioning

confidence: 99%

“…In addition, in both human and nonhuman primate cortex there has been a selective enlargement of the supragranular layer compartment (Marín‐Padilla, 1992), which has an important role in the computational processes of the brain (reviewed in Douglas and Martin, 2004; Kennedy et al, 2007). The enlarged supragranular layers of the primates arise from a specialized precursor pool, the outer subventricular zone (OSVZ) (Smart et al, 2002; Lukaszewicz et al, 2005). The OSVZ is the major germinal zone of the developing primate cerebral cortex and harbors the bulk of cortical progenitors from midcorticogenesis onward (Smart et al, 2002; Lukaszewicz et al, 2005; Fietz et al, 2010; Hansen et al, 2010; Fietz and Huttner, 2011; Lui et al, 2011; Reillo and Borrell, 2012; Betizeau et al, 2013).…”

mentioning

confidence: 99%

“…The enlarged supragranular layers of the primates arise from a specialized precursor pool, the outer subventricular zone (OSVZ) (Smart et al, 2002; Lukaszewicz et al, 2005). The OSVZ is the major germinal zone of the developing primate cerebral cortex and harbors the bulk of cortical progenitors from midcorticogenesis onward (Smart et al, 2002; Lukaszewicz et al, 2005; Fietz et al, 2010; Hansen et al, 2010; Fietz and Huttner, 2011; Lui et al, 2011; Reillo and Borrell, 2012; Betizeau et al, 2013). Although significant progress has been made in identifying the OSVZ precursor types in human (Hansen et al, 2010; Fietz and Huttner, 2011) and non‐human (Betizeau et al, 2013) primates, understanding the cellular and molecular properties of OSVZ precursors that drive its expansion in the primate lineage remains a major challenge (Lui et al, 2011; Dehay et al, 2015).…”

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confidence: 99%

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Unsupervised lineage‐based characterization of primate precursors reveals high proliferative and morphological diversity in the OSVZ

Pfeiffer

Betizeau

Waltispurger

et al. 2015

J of Comparative Neurology

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Generation of the primate cortex is characterized by the diversity of cortical precursors and the complexity of their lineage relationships. Recent studies have reported miscellaneous precursor types based on observer classification of cell biology features including morphology, stemness, and proliferative behavior. Here we use an unsupervised machine learning method for Hidden Markov Trees (HMTs), which can be applied to large datasets to classify precursors on the basis of morphology, cell‐cycle length, and behavior during mitosis. The unbiased lineage analysis automatically identifies cell types by applying a lineage‐based clustering and model‐learning algorithm to a macaque corticogenesis dataset. The algorithmic results validate previously reported observer classification of precursor types and show numerous advantages: It predicts a higher diversity of progenitors and numerous potential transitions between precursor types. The HMT model can be initialized to learn a user‐defined number of distinct classes of precursors. This makes it possible to 1) reveal as yet undetected precursor types in view of exploring the significant features of precursors with respect to specific cellular processes; and 2) explore specific lineage features. For example, most precursors in the experimental dataset exhibit bidirectional transitions. Constraining the directionality in the HMT model leads to a reduction in precursor diversity following multiple divisions, thereby suggesting that one impact of bidirectionality in corticogenesis is to maintain precursor diversity. In this way we show that unsupervised lineage analysis provides a valuable methodology for investigating fundamental features of corticogenesis. J. Comp. Neurol. 524:535–563, 2016. © 2015 The Authors The Journal of Comparative Neurology Published by Wiley Periodicals, Inc.

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Self‐Organization and Pattern Formation in Primate Cortical Networks

Kennedy

Douglas

Knoblauch

et al. 2008

Novartis Foundation Symposia

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The primate neocortex is characterized by a highly expanded supragranular layer (SGL). The interareal connectivity of the neurons in the SLG largely determines the cortical hierarchy that constrains information fl ow through the cortex. Inter-areal connectivity is made by precise numbers of connections, raising the possibility that the physiology of a target area is dictated by the numbers of connections and hierarchical distance in each of the pathways that it receives. The developmental mechanisms ensuring the precision of these interareal networks is in part determined by (i) the numbers of SGL neurons generated by the OSVZ, a primate-specifi c germinal zone. Neuron generation rate in the OSVZ is determined by regulation of the G1 phase of the cellcycle. This regulation is area-specifi c and is linked to thalamic projections to the OSVZ; (ii) Prolonged pre-and postnatal pruning of connections originating from the SGL when the infant monkey visually explores its environment. Remodelling serves to sharpen initial patterns of connections and establishes the adult hierarchy. These results suggest that primate cortical networks underlying high-level function undergo prolonged selforganization via regressive phenomena in the cortical plate (axon elimination) and progressive phenomena (directed growth of cortical axons).

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G1 Phase Regulation, Area-Specific Cell Cycle Control, and Cytoarchitectonics in the Primate Cortex

Cited by 293 publications

References 65 publications

S‐phase duration is the main target of cell cycle regulation in neural progenitors of developing ferret neocortex

S‐phase duration is the main target of cell cycle regulation in neural progenitors of developing ferret neocortex

Unsupervised lineage‐based characterization of primate precursors reveals high proliferative and morphological diversity in the OSVZ

Self‐Organization and Pattern Formation in Primate Cortical Networks

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