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Updated: Aug 29, 2026

Determining Genome-wide Transcript Decay Rates in Proliferating and Quiescent Human Fibroblasts
Published on: January 2, 2018
Zipf's law and human transcriptomes: an explanation with an evolutionary model
Osamu Ogasawara1, Shoko Kawamoto, Kousaku Okubo
1Division of Gene Expression analysis, The Center for Information Biology and DNA Data Bank of Japan, National Institute of Genetics, Mishima 411-8540, Shizuoka, Japan.
Abstract:
Detailed analysis of human gene expression data reveals several patterns of relationship between transcript frequency and abundance rank. In muscle and liver, organs composed primarily of a homogeneous population of differentiated cells, they obey Zipf's law. In cell lines, epithelial tissue and compiled transcriptome data, only high-rankers deviate from it. We propose an evolutionary process model during which expression level changes stochastically proportionally to its intensity, providing a novel interpretation of transcriptome data and of evolutionary constraints on gene expression.
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