Dataset Information

Comprehensive Analysis of Differences in Cashmere Production Performance in Liaoning Cashmere Goats by Using Metabolomics and Transcriptomics

ABSTRACT:

This study integrated transcriptomics and metabolomics to analyse the molecular differences in the skin tissues of perennial long wool type (PT-LCG) and seasonal long wool type (ST-LCG) Liaoning cashmere goats to reveal the regulatory mechanisms underlying their differences in cashmere production. Histological observations showed no significant differences in the secondary hair follicle structure between the two types, but PT-LCG exhibited higher hair follicle activity during the catagen phase. Metabolomics analysis identified 92 differentially expressed metabolites (67 up-regulated and 25 down-regulated), primarily enriched in lipid metabolism, amino acid metabolism and energy metabolism pathways. The up-regulation of 3-hydroxypropionic acid and long-chain fatty acids may promote hair follicle growth through energy supply and membrane synthesis. Transcriptomic analysis revealed 145 differentially expressed genes (28 up-regulated and 117 down-regulated), significantly enriched in lipid metabolism, extracellular matrix (ECM), and inflammation-related pathways such as the PPAR and IL-17 signalling pathway. Multi-omics association analysis uncovered a synergistic regulatory network of ‘metabolite-receptor-gene’, indicating that lipid metabolism, energy supply and ECM remodelling are key factors in maintaining hair follicle activity in PT-LCG. This study provides potential targets for molecular breeding of cashmere goats and offers new insights into the regulatory mechanisms of mammalian hair follicle cycles.

INSTRUMENT(S): Gas Chromatography MS - positive

PROVIDER: MTBLS13406 | MetaboLights | 2025-11-27

REPOSITORIES: MetaboLights

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	a_MTBLS13406_GC-MS_positive__metabolite_profiling.txt	Txt
	i_Investigation.txt	Txt
	m_MTBLS13406_GC-MS_positive__metabolite_profiling_v2_maf.tsv	Tabular
	s_MTBLS13406.txt	Txt

Items per page:

1 - 4 of 4

Similar Datasets

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. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication 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.

Dataset Information

Comprehensive Analysis of Differences in Cashmere Production Performance in Liaoning Cashmere Goats by Using Metabolomics and Transcriptomics

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets