2.1 Cell culture and transfections

PC12 cells (CL-0481, Procell Life Science & Technology Co., Ltd., Wuhan, Hubei, China) were cultured in RPMI-1640 containing 10% fetal bovine serum (FBS, 164210, Procell, Wuhan, Hubei, China), 100 μg/mL streptomycin (SV30010, Hyclone), and 100 U/mL penicillin (Hyclone) at 37°C in an atmosphere of 5% carbon dioxide. Short interfering RNA (siRNA) targeting NQO1 and the control siRNA were transfected into cells using Lipofectamine 2000 (Invitrogen, Carlsbad, CA, USA) according to the manufacturer's manual. All siRNA duplexes were purchased from Gemma (Suzhou, China). The sequences were nontargeting control siRNA (siCtrl) (5′-UUCUCCGAACGUGUCACGUTT-3′ [sense]) and siRNA targeting NQO1 (siNQO1) (5′-CUGACCUCUAUGCUAUGAATT-3′ [sense]).

2.2 Assessment of NQO1 gene expression

After 48 h of transfection, cells were harvested and subjected to quantitative reverse transcription PCR (RT-qPCR) analysis. Complementary DNA (cDNA) was synthesized using Prime Scrip RT Reagent kit (Takara, Dalian, China). RT-qPCR was performed on the Bio-Rad S1000 using Bestar SYBR Green RT-PCR Master Mix (DBI Bioscience, Shanghai, China). Levels of target mRNAs were determined using the 2–ΔΔCT method and normalized to the levels of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) mRNA (Livak & Schmittgen, 2001).

Intergroup differences in expression levels were assessed for significance using the paired Student's t-test in GraphPad Prism software (version 7, San Diego, CA, USA).

2.3 Flow cytometry of cell apoptosis

PC12 cells were plated onto 24-well culture plates (ca. 105 per well) and incubated for 24 h. Cells were double stained with Fluor647-conjugated annexin V and propidium iodide (4A Biotech Co. Ltd., Beijing, China), and apoptosis was detected by flow cytometry (Cytoflex, Beckman, USA).

2.4 RNA extraction and sequencing

Cells were homogenized and total RNA was extracted using TRIzol (Ambion, Austin, TX, USA). RQ1 DNase (Promega, Fitchburg, WI, USA) was applied to remove DNA. The purified RNA was quantified by measuring the absorbance ratio at 260–280 nm using a Smartspec Plus system (BioRad, Hercules, CA, USA), and 1.5% agarose gel electrophoresis was performed to verify RNA integrity.

Total RNA (1 μg) from each sample was used for RNA-seq library preparation with the KAPA Stranded mRNA-Seq Kit for Illumina^® Platforms (#KK8544, Roche, Basel, Switzerland). Polyadenylated mRNAs were purified with VAHTS mRNA capture Beads (N401-01, Vazyme, Nanjing, China), and fragmented mRNAs were converted into double-stranded cDNA. Following end repair and A tailing, the DNAs were ligated to Diluted Roche Adaptor (KK8726). Ligation products corresponding to 300–500 base pairs were amplified, purified, quantified, and stored at −80°C before sequencing. The strand marked with 2′-deoxyuridine 5′-triphosphate (second cDNA strand) was not amplified, allowing strand-specific sequencing. Libraries were prepared for high-throughput sequencing according to the manufacturer's instructions, and 150 nt paired-end sequencing was performed on an Illumina Novaseq 6000 system (ABlife Inc, Wuhan, China).

2.5 Cleaning and alignment of raw RNA-seq data

Raw reads containing more than 2-N bases were first discarded. Then, we used the FASTX-Toolkit (Version 0.0.13) to trim adaptors and low-quality bases from the raw sequencing reads. Reads shorter than 16 nucleotides were discarded. The remaining clean reads were aligned to the RGSC6 genome using TopHat2 (Kim et al., 2013) and allowing four mismatches. Uniquely mapped reads were used for gene read counting and calculation of the fragments per kilobase of transcript per million mapped reads (FPKM) (Trapnell et al., 2010).

2.6 DEG analysis

The R Bioconductor package edgeR (Robinson et al., 2010) was used to screen for DEGs differing between NQO1 knockdown cells and control PC12 cells. A false discovery rate (FDR) <0.05 and fold change >2 or <0.5 were set as the cutoff criteria for identifying DEGs.

2.7 Alternative splicing analysis

ASEs were identified and quantified using the ABLAS pipeline as described (Jin et al., 2017; Xia et al., 2017). The following 10 types of ASEs were detected based on the splice junction reads: intron retention (IntronR), exon skipping (ES), alternative 5′ splice site (A5SS), alternative 3′splice site (A3SS), mutually exclusive exons (MXE), mutually exclusive 5′UTRs (5pMXE), mutually exclusive 3′UTRs (3pMXE), cassette exon, A3SS&ES, and A5SS&ES.

To identify NQO1-regulated ASEs, the ratio alteration of ASEs was assessed for significance using Student's t-test. ASEs were significant at p-value cutoff equivalent to an FDR cutoff of 5% and were considered to be regulated by NQO1.

2.8 RT-qPCR validation of DEGs and ASEs

Some DEGs identified by RNA-seq were validated using RT-qPCR. Total RNA remaining from RNA-seq library preparation was subjected to RT-qPCR. The reverse transcription of RNA into cDNA was performed using M-MLV reverse transcriptase (Vazyme). RT-qPCR was performed on the StepOne RT-PCR System (AT311-03, Transgene, Beijing, China), using the SYBR Green PCR Reagents Kit (Low Rox plus, YEASEN, Shanghai, China) and sequences of primers in Table S1. The PCR conditions were as follows: denaturation at 95°C for 10 min, 40 cycles of denaturation at 95°C for 15 s, and then annealing and extension at 60°C for 1 min. For each sample, PCR amplifications were performed three times. Gene expression was normalized to that of GAPDH mRNA.

ASEs were similarly validated using RT-qPCR and the primers in Table S1. To detect alternative isoforms, a boundary-spanning primer for the sequence encompassing the junction of the constitutive exon and the alternative exon and an opposing primer in a constitutive exon were used. The boundary-spanning primer of the alternative exon was designed according to the “model exon” to detect model splicing or according to “altered exon” to detect altered splicing.

2.9 Functional enrichment analysis

To predict the functional categories of DEGs, the KOBAS 2.0 server was used to identify gene ontology (GO) terms and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways (Xie et al., 2011). Enrichment was determined based on the hypergeometric test and Benjamini–Hochberg FDR procedure.

3.1 NQO1 knockdown increases apoptosis of PC12 cells

To explore the role of NQO1 in AD, we knocked down NQO1 expression in PC12 cells through si-NQO1 transfection and verified the reduced expression using RT-qPCR (Figure 1a). Then we compared the percentage of apoptotic cells in si-NQO1 group and si-NC group. Knockdown of NQO1 led to a significant increase in cell apoptosis (Figure 1b).

3.2 NQO1 knockdown alters the transcriptome of PC12 cells

We compared the transcriptomes of PC12 cells transfected with si-NQO1 or siCtrl using RNA-seq. After removing sequence adaptors and low-quality reads, an average of 85.4 million clean pair-end reads per sample were obtained. These reads were mapped to the RGSC6 genome, resulting in an average of 76.1 million uniquely mapped read pairs per sample. The sequencing showed 15,421 expressed genes with FPKM > 0 and 10,138 genes with FPKM > 1 in at least one sample. The sequencing further confirmed NQO1 knockdown (Figure 2a). Principal component analysis (PCA) revealed that the first component clearly separated genome-wide gene expression profiles of PC12-siNQO1 cell samples from those of control cell samples, suggesting that the experimental replicates strongly correlated with one other, giving reliable results appropriate for subsequent analysis (Figure 2b).

Analysis with edgeR identified DEGs in PC12 cells transfected with siNQO1 and siCrt, revealing 467 upregulated genes and 295 downregulated genes. This suggests that NQO1 knockdown regulates expression of many genes in PC12 cells. A volcano plot was provided to show DEGs associated with NQO1 knockdown (Figure 2c). Heat maps of DEG expression patterns showed strong consistency within the biological replicates of PC12-siNQO1 cell samples or control cell samples (Figure 2d).

To begin to examine the potential functions of these DEGs, GO enrichment analysis was performed. The top biological processes involving NQO1-regulated genes are presented in Figure 2e,g. The genes upregulated in NQO1 knockdown cells were associated mainly with negative regulation of smooth muscle cell proliferation and neuron apoptotic processes, transcription regulation, DNA-templated synthesis, axon guidance, and aging (Figure 2e). The genes downregulated in NQO1 knockdown cells were associated mainly with negative regulation of cell proliferation, nervous system development, response to oxidative stress, and other pathways related to AD (Figure 2g). Interestingly, the upregulated and downregulated DEGs were significantly enriched in apoptotic-related processes, which ranked among the top 10 terms (Figure 2e). As shown by KEGG pathway analysis, the DEGs were enriched in axon guidance, nuclear factor-kappa B signaling pathway, fatty acid biosynthesis, metabolic pathways, and cancer pathways (Figure 2f,h).

3.3 NQO1 regulates the expression of apoptosis-related genes

To verify the impact of NQO1 silencing on DEG expression, we performed RT-qPCR to detect the expression of six DEGs (Cryab, Lgmn, Ngf, Apoe, Brd7, and Stat3) that have been reported to participate in apoptosis pathology. All these DEGs were associated with the GO molecular functional terms “negative regulation of neuron apoptotic processes,” “negative regulation of cell proliferation,” and “aging,” and the FPKM of all these genes was >1 in at least one RNA-seq sample. The results of RT-qPCR confirmed that Cryab, Lgmn, Ngf, and Apoe were upregulated in PC12 cells silencing NQO1, while Brd7 and Stat3 were downregulated by siNQO1 (Figure 3a).

3.4 NQO1 regulates the alternative splicing of genes implicated in apoptosis

The splice reads from PC12 cells transfected with siNQO1 or siCtrl were mapped to the reference genome, and 164,821 annotated exons were detected, accounting for 68.6% of all annotated reads. Then, 68,038 known and 240,124 novel splice junctions were detected using TopHat2. ASEs were identified from the splice junctions using ABLAS, which detected 1534 known and 38,038 novel ASEs.

After applying stringent screening conditions (see Section 2), we identified 247 NQO1-regulated ASEs: 73 examples of intron retention (IntronR), 47 examples of exon skipping (ES), 21 cassette exons, 37 alternative 5′ splice sites (A5SS), two examples of alternative 5′ splice site and exon skipping (A5SS&ES), 39 alternative 3′ splice sites (A3SS), three examples of alternative 3′ splice site and exon skipping (A3SS&ES), 10 mutually exclusive 5′ UTRs (5pMXE), and eight mutually exclusive 3′ UTRs (3pMXE) (Figure 4a). These results suggest that NQO1 knockdown has an extensive influence on splicing. Figure 4b shows four genes (Eea1, Stag2, Pdgfa, and Stk11ip) whose expression and alternative splicing were regulated by NQO1 in PC12 cells.

To explore the potential functions of NQO1-regulated alternative splicing of genes, we analyzed the genes for enrichment in GO terms. They were highly enriched in axonogenesis, metabolic processes, neuron migration, apoptotic processes, signal transduction, protein phosphorylation, and positive regulation of apoptotic processes (Figure 4c). Enriched KEGG pathways included biotin metabolism, endocytosis, cell cycle, and mitogen-activated protein kinase (MAPK) signaling (Figure 4d). These results suggest that by regulating the alternative splicing of transcription factors and co-activators, NQO1 knockdown regulates the expression of genes mainly related to apoptosis.

We validated the results of our transcriptomic analysis using RT‑qPCR (Figures 4e,f and 1). Two important ASEs were located in BIN1 and Picalm, which have been linked to AD pathology and belong to apoptotic pathways.