10x genomics single cell sequencing of yak hair follicle
Ontology highlight
ABSTRACT:
ORGANISM(S): Bos grunniens
PROVIDER: GSE205456 | GEO | 2022/12/10
REPOSITORIES: GEO
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Project description:Hair follicles undergo recurrent cycling of controlled growth (anagen), regression (catagen), and relative quiescence (telogen) with a defined periodicity. Taking a genomics approach to study gene expression during synchronized mouse hair follicle cycling, we discovered that, in addition to circadian fluctuation, CLOCK-regulated genes are also modulated in phase with the hair growth cycle. During telogen and early anagen, circadian clock genes are prominently expressed in the secondary hair germ, which contains precursor cells for the growing follicle. Analysis of Clock and Bmal1 mutant mice reveals a delay in anagen progression, and the secondary hair germ cells show decreased levels of phosphorylated Rb and lack mitotic cells, suggesting that circadian clock genes regulate anagen progression via their effect on the cell cycle. Consistent with a block at the G1 phase of the cell cycle, we show a significant upregulation of p21 in Bmal1 mutant skin. While circadian clock mechanisms have been implicated in a variety of diurnal biological processes, our findings indicate that circadian clock genes may be utilized to modulate the progression of non-diurnal cyclic processes. To investigate the molecular control of hair follicle cycling, we profiled mRNA expression in mouse dorsal skin at multiple representative time points in the synchronized second postnatal hair growth cycle and in a depilation-induced hair growth cycle. For profiling of second synchronized and depilation-induced hair growth cycle, the same upper-mid region of dorsal skin was excised from C57BL/6 mice at representative postnatal days (P). The time points for second hair growth cycle are classified into different phases of the hair growth cycle based on established morphological guidelines as follow: early anagen (P23, P25), mid anagen (P27), late anagen (P29, P34), early catagen (P37, P39), mid catagen (P41), and telogen (P44). Depilation-induced hair growth cycle by applying wax/rosin mixture on the dorsal skin of seven-week old mice (all follicles in telogen) was performed on mice. The corresponding phases of the hair growth cycle at number of days following depilation (D) is as follow: early anagen (D3), mid anagen (D5), late anagen (D8, D12), and early catagen (D17). For each time point, multiple biological replicates were profiled, with each mouse dorsal skin separately hybridized to an Affymetrix array.
2009-07-17 | E-GEOD-11186 | biostudies-arrayexpress
Project description:Fgf18 gene is strongly expressed in hair follicles of mouse dorsal skin during regressing (catagen) and resting (telogen) phases of hair cycle, but not in growth (anagen) phase. This study aims at identifying the function of Fgf18 in the regulation of hair cycle.
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Project description:This a model from the article:
The follicular automaton model: effect of stochasticity and of synchronization
of hair cycles.
Halloy J, Bernard BA, Loussouarn G, Goldbeter A. J Theor Biol
2002 Feb 7;214(3):469-79 11846603
,
Abstract:
Human scalp hair consists of a set of about 10(5)follicles which progress
independently through developmental cycles. Each hair follicle successively goes
through the anagen (A), catagen (C), telogen (T) and latency (L) phases that
correspond, respectively, to growth, arrest and hair shedding before a new
anagen phase is initiated. Long-term experimental observations in a group of ten
male, alopecic and non-alopecic volunteers allowed determination of the
characteristics of hair follicle cycles. On the basis of these observations, we
previously proposed a follicular automaton model to simulate the dynamics of
human hair cycles and the development of different patterns of alopecia [Halloy
et al. (2000) Proc. Natl Acad. Sci. U.S.A.97, 8328-8333]. The automaton model is
defined by a set of rules that govern the stochastic transitions of each
follicle between the successive states A, T, L and the subsequent return to A.
These transitions occur independently for each follicle, after time intervals
given stochastically by a distribution characterized by a mean and a standard
deviation. The follicular automaton model was shown to account both for the
dynamical transitions observed in a single follicle, and for the behaviour of an
ensemble of independently cycling follicles. Here, we extend these results and
investigate additional properties of the model. We present a deterministic
version of the follicular automaton. We show that numerical simulations of the
stochastic version of the automaton yield steady-state level of follicles in the
different phases which approach the levels predicted by the deterministic
equations as the number of follicles progressively increases. Only the
stochastic version can successfully reproduce the fluctuations of the fractions
of follicles in each of the three phases, observed in small follicle
populations. When the standard deviation is reduced or when the follicles become
otherwise synchronized, e.g. by a periodic external signal inducing the
transition of anagen follicles into telogen phase, large-amplitude oscillations
occur in the fractions of follicles in the three phases. These oscillations are
not observed in humans but are reminiscent of the phenomenon of moulting
observed in a number of mammalian species. Copyright 2002 Elsevier Science Ltd.
This model was taken from the CellML repository
and automatically converted to SBML.
The original model was:
Halloy J, Bernard BA, Loussouarn G, Goldbeter A. (2002) - version=1.0
The original CellML model was created by:
Catherine Lloyd
c.lloyd@auckland.ac.nz
The University of Auckland
This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team.
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for more information.
In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not..
To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.
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