Transcriptomics

Dataset Information

0

Small Perturbation Approach Reveals Transcriptomic Steady State


ABSTRACT: The ‘small perturbation’ approach is critical in studying the ‘steady state’ of a biological system. In our experiments, small perturbations were generated by applying a series of repeating intermittent small doses of ultraviolet radiation to a human keratinocyte cell line, HaCaT. The biological response was assessed by monitoring the gene expression profiles using a high reliability and high resolution cDNA microarray system. Following intermittent 10 J/m2 UVB small perturbations, two opposite classes of genes, down-regulated and up-regulated, exhibited an immediate response followed by relaxation between each small perturbation, but were prolonged down- or up-regulated without relaxation while larger doses (233 or 582.5 J/m2) of UVB were applied. A repeated cycle pattern of gene expression following small perturbations is an indication of the existence of steady states. This cycle pattern is suppressed when large perturbations are applied. We believe that this is a universal phenomenon. In our experiments, the functions of up-regulated genes were mainly associated with anti-proliferation, anti-mitogenesis, and apoptosis. On the other hand, down-regulated genes were mainly related to proliferation, mitogenesis, and anti-apoptosis. In conclusion, this study experimentally proves the concept of steady state at the transcription level and demonstrates the feasibility of using small perturbation approaches for investigating steady states. This study could also set a foundation of computational systems biology, which has implicitly used the concept of steady state. Keywords: time course

ORGANISM(S): Homo sapiens

PROVIDER: GSE7060 | GEO | 2009/01/30

SECONDARY ACCESSION(S): PRJNA98461

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2010-06-24 | E-GEOD-7060 | biostudies-arrayexpress
| PRJNA98461 | ENA
2011-10-18 | E-GEOD-22083 | biostudies-arrayexpress
2009-03-26 | GSE15409 | GEO
2024-09-02 | BIOMD0000000933 | BioModels
2018-10-30 | GSE113874 | GEO
2011-10-04 | E-GEOD-28463 | biostudies-arrayexpress
2015-06-01 | GSE48177 | GEO
2011-02-17 | E-GEOD-27360 | biostudies-arrayexpress
2023-12-01 | GSE240077 | GEO