RNA Sequencing and Differential Expression Analysis
The Qst-Fst test indicated that more floral characteristics showed local
adaptation than other plant characteristics; thus, a bud stage was
selected for
transcriptome
sequencing. Considering the abovementioned population genetic analysis
results and clustering results for floral characteristics, ten
populations were selected for transcriptome sequencing. Three samples
were collected from each population as biological replicates to ensure
the stability and reliability of the sequencing results (Table S1).
Total RNA was extracted from the samples using TRIzol (Invitrogen, USA)
according to the manufacturer’s protocol. A NanoDrop 2000
spectrophotometer (Thermo Scientific, USA) and gel electrophoresis were
used to estimate the RNA quality. An Illumina Hiseq system at Novogene
Technologies, Inc. (Beijing, China) was used for genomic library
generation and sequencing with 2 × 150 bp paired reads. Raw reads were
assessed using FastQC (Andrew, 2010) and filtered using Trimmomatic
v.0.39 (Bolger, Lohse, & Usadel, 2014). The trimmed reads of each
sample were mapped to the same reference genome employed above using
STAR
v.2.7.5c (Dobin et al., 2013), and the expression levels were estimated
using
RSEM
v.1.3.0 (B. Li & Dewey, 2011). Based on the obtained read counts, the R
package DESeq2 was used to calculate differential gene expression via
pairwise comparisons (Love, Anders, & Huber, 2014). Transcripts with an
absolute log2FoldChange (LFC) value greater than 1 were considered
significant DEGs. All the DEGs were analyzed using the clusterProfiler
package in R for Kyoto Encyclopedia of Genes and Genomes (KEGG)
enrichment analysis (Yu, Wang, Han, & He, 2012).