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).