RNA-seq and data analysis
Library construction and RNA sequencing were conducted by the Beijing
Genomics Institute (BGI) using the BGISEQ-500 platform, producing
approximately 6.8 Gb data of 100-base long paired reads per sample.
RNA-seq data have been deposited in the National Center for
Biotechnology Information Gene Expression Omnibus (GEO) database under
accession number GSE157400. All clean reads were mapped to theOryzae sativa L. cv. Nipponbare reference genome using Hisat2
(Kim, Langmead, & Salzberg, 2015) and transformed into a count per gene
per library using HTseq (Anders, Pyl, & Huber, 2015). Statistical
analysis of the RNA-seq data was performed in the R environment with the
DEseq2 package (L. Wang, Feng, Wang, Wang, & Zhang, 2010). To extract
significantly differentially expressed genes, a cut-off of
log2 (fold change) ≥ 1 or ≤ −1 and adjusted P-value ≤
0.001 was applied. Heatmaps were generated with webtool Morpheus
(https://software.broadinstitute.org/morpheus/) using one minus
the Pearson correlation and average linkage clustering. Transcriptome
similarity analysis and cis -regulatory motif enrichment were
performed with the webtool Plant Regulomics
(http://bioinfo.sibs.ac.cn/plant-regulomics) (Ran et al., 2020).