72-hour diurnal RNA-seq analysis of fully expanded third leaves from maize, sorghum, and foxtail millet at 3-hour resolution

Authors: LAI, XIANJUN - University Of Nebraska; BENDIX, CLAIRE - University Of California; ZHANG, YANG - University Of Nebraska; SCHNABLE, JAMES - University Of Nebraska; Harmon, Frank

Submitted to: BMC Research Notes
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/24/2020
Publication Date: 1/14/2021
Citation: Lai, X., Bendix, C., Zhang, Y., Schnable, J.C., Harmon, F.G. 2021. 72-hour diurnal RNA-seq analysis of fully expanded third leaves from maize, sorghum, and foxtail millet at 3-hour resolution. BMC Research Notes. 14. Article 24. https://doi.org/10.1186/s13104-020-05431-5.
DOI: https://doi.org/10.1186/s13104-020-05431-5

Interpretive Summary: This publication describes 72 publicly released next generation sequencing files, known as FASTQ files, to the National Center for Biotechnology Information Short Read Archive. Collectively, this data set indicates gene expression activity, analyzed with a method known as RNA-seq transcriptome profiling, for the evolutionarily distant, but related, grasses sorghum, maize (or corn), and foxtail millet. The purpose of the experiment associated with this data set was to identify how these three keystone crop plants adapt to daily changes in light availability and air temperature. The released files are gene expression levels at 3-hour intervals in fully mature third leaves from seedlings over 72-hours. Plants were cultivated in a growth chamber under equal intervals of light and darkness. These data are the cornerstone of a larger published project that examined the conservation and divergence of gene expression networks between these grasses to determine how gene expression networks are put together and the regulatory DNA sequences responsible for this structure, collectively known as the network architecture. The utility of this data set is to inform selection of key regulatory genes for breeding and engineering efforts to adapt cereal crops to novel growth conditions.

Technical Abstract: Objectives: The purpose of this data set is to use RNA-seq transcriptome profiling to capture the complete diurnal (i.e., daily) transcriptome of fully expanded third leaves from the C4 panacoid grasses sorghum (Sorghum bicolor), maize (Zea mays), and foxtail millet (Setaria italica). These data are the cornerstone of a larger project that examined the conservation and divergence of gene expression networks within these crop plants. This data set focuses on temporal changes in gene expression to identify the network architecture responsible for daily regulation of plant growth and metabolic activities. The power of this data set is fine temporal resolution combined with continuous sampling over multiple days. Data description: The data set is 72 individual RNA-seq samples representing 24 time course samples each for sorghum, maize, and foxtail millet plants cultivated in a growth chamber under equal intervals of light and darkness. The 24 samples are separated by 3-hour intervals so that the data set is a fine scale 72-hour analysis of gene expression in the leaves of each plant type. FASTQ files from Illumina sequencing are available at the National Center for Biotechnology Information Short Read Archive.