Gauss-power mixing distributions comprehensively describe stochastic variations in RNA-seq data

<jats:title>Abstract</jats:title><jats:sec><jats:title>Motivation</jats:title><jats:p>Gene expression levels exhibit stochastic variations among genetically identical organisms under the same environmental conditions. In many recent transcriptome analyses based on RNA sequencing (RNA-seq), variations in gene expression levels among replicates were assumed to follow a negative binomial distribution although the physiological basis of this assumption remain unclear.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>In this study, RNA-seq data were obtained from<jats:italic>Arabidopsis thaliana</jats:italic>under eight conditions (21–27 replicates), and the characteristics of gene-dependent distribution profiles of gene expression levels were analyzed. For<jats:italic>A. thaliana and Saccharomyces cerevisiae,</jats:italic>the distribution profiles could be described by a Gauss-power mixing distribution derived from a simple model of a stochastic transcriptional network containing a feedback loop. The distribution profiles of gene expression levels were roughly classified as Gaussian, power law-like containing a long tail, and mixed. The fitting function predicted that gene expression levels with long-tailed distributions would be strongly influenced by feedback regulation. Thus, the features of gene expression levels are correlated with their functions, with the levels of essential genes tending to follow a Gaussian distribution and those of genes encoding nucleic acid-binding proteins and transcription factors exhibiting long-tailed distributions.</jats:p></jats:sec><jats:sec><jats:title>Availability</jats:title><jats:p>Fastq files of RNA-seq experiments were deposited into the DNA Data Bank of Japan Sequence Read Archive as accession no. DRA005887. Quantified expression data are available in supplementary information.</jats:p></jats:sec><jats:sec><jats:title>Contact</jats:title><jats:p><jats:email>awa@hiroshima-u.ac.jp</jats:email></jats:p></jats:sec><jats:sec id="s5" sec-type="supplementary-material"><jats:title>Supplementary information</jats:title><jats:p>Supplementary data are available at<jats:italic>Bioinformatics</jats:italic>online.</jats:p></jats:sec>