Click here to close Hello! We notice that you are using Internet Explorer, which is not supported by Xenbase and may cause the site to display incorrectly. We suggest using a current version of Chrome, FireFox, or Safari.
XB-ART-57344
Nucleic Acids Res January 1, 2020; 48 (9): e51.

TimeMeter assesses temporal gene expression similarity and identifies differentially progressing genes.

Jiang P , Chamberlain CS , Vanderby R , Thomson JA , Stewart R .


Abstract
Comparative time series transcriptome analysis is a powerful tool to study development, evolution, aging, disease progression and cancer prognosis. We develop TimeMeter, a statistical method and tool to assess temporal gene expression similarity, and identify differentially progressing genes where one pattern is more temporally advanced than the other. We apply TimeMeter to several datasets, and show that TimeMeter is capable of characterizing complicated temporal gene expression associations. Interestingly, we find: (i) the measurement of differential progression provides a novel feature in addition to pattern similarity that can characterize early developmental divergence between two species; (ii) genes exhibiting similar temporal patterns between human and mouse during neural differentiation are under strong negative (purifying) selection during evolution; (iii) analysis of genes with similar temporal patterns in mouse digit regeneration and axolotl blastema differentiation reveals common gene groups for appendage regeneration with potential implications in regenerative medicine.

PubMed ID: 32123905
PMC ID: PMC7229845
Article link: Nucleic Acids Res
Grant support: [+]

Species referenced: Xenopus
Genes referenced: a1cf abhd2 c1ql1 comt epha8 hs3st3a1 ilk ogdh pdgfd plin2 slc4a10 sult1a1
GO keywords: forebrain neuron development [+]


Article Images: [+] show captions
References [+] :
Aach, Aligning gene expression time series with time warping algorithms. 2001, Pubmed