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).