Gene expression profiling using RNA-Seq
About 0.1 g sample was used for total RNA extraction by TRIzol reagent (Invitrogen, USA). The extracted RNA was dissolved in 100 μl of RNase-free water, and then quantified using a NanoDrop spectrophotometer (Thermo Scientific, USA). RNA quality was evaluated using the 6000 Pico LabChip of the Agilent 2100 Bioanalyzer (Agilent, USA). The qualification and quantification of the sample library were performed using an Agilent 2100 Bioanaylzer and StepOnePlus Real-Time PCR System (Applied Biosystem, USA). The library products were sequenced with BGISEQ-500 (BGI, China). Nipponbare reference genome (IRGSP-1.0; https://www.ncbi.nlm.nih.gov) was used to process the RNA-Seq libraries into read mapping and analysis. To ensure good quality and effective mapping, the low-quality reads were removed using the SOAPnuke (V1.4.0) and trimmomatic (V0.36) software (Chen et al., 2018b), and only clean reads were processed for mapping using HISAT2 (V2.1.0) (Kim, Langmead, & Salzberg, 2015). The gene expression level was measured by RSEM (V1.2.8) software (Li & Dewey, 2011), and fragments per kilobase of transcript per million mapped reads (FPKM) values were used for quantifying gene activity. We only considered a gene as expressed if its FKPM value ≥ 1 to inhibit the influence of transcriptomic noise. To confirm the accuracy and authenticity of the three biological repeats, we calculated the Pearson correlation coefficient among them with the normalized expression level of log2 (FPKM value +1) (Figure S1). To identify differentially expressed genes (DEGs), we considered a DEG when it exhibits an absolute value of log2 ratio ≥1 compared with an FDR corrected P-value of ≤0.001 (Wang, Feng, Wang, Wang, & Zhang, 2010).