Abstract
Mek inhibition and Erk knockout (KO) have quite distinct effects on pluripotency maintenance in mouse embryonic stem cells (ESCs). To test whether there is an Erk-independent function of Mek, RNA-sequencing (RNA-seq) is carried out on six samples, WT KH2 ESCs treated with or without PD0325901 (PD) for 48 h (KH2_PD and KH2, respectively), iErk1; Erk KO ESCs cultured in the presence of Dox (P0), 48 and 96 h after Dox withdrawal (P1 and P2, respectively), and iErk1; Erk KO ESCs cultured without Dox for 96 h, and treated with PD in the last 48 h (P2_PD). These RNA-seq data demonstrate that Mek inhibition has quite different effect on the transcriptional profile of mouse ESCs, compared to Erk KO. Moreover, a significant fraction of genes is regulated by Mek inhibition, regardless of the presence or absence of Erk, indicating an Erk-independent function of Mek. RNA-seq data are deposited in Gene Expression Omnibus (GEO) datasets under accession number GSE70304.
Keywords: Erk, Mek, Mouse embryonic stem cells
| Specifications | |
|---|---|
| Organism/cell line/tissue | KH2 mouse ESC line |
| Sex | Male |
| Sequencer or array type | Illumina HiSeq 2000 |
| Data format | Raw and analyzed |
| Experimental factors | Mek inhibition in WT KH2 ESCs; Mek inhibition in Erk KO ESCs; Erk knockout in iErk1; Erk KO ESCs. |
| Experimental features | Comparison between WT KH2 ESCs treated with or without PD0325901 for 48 h (KH2_PD and KH2, respectively) shows the Mek inhibition effect in WT ESCs. Comparison between iErk1; Erk KO ESCs without Dox for 96 h, with or without PD0325901 treatment (P2_PD and P2, respectively) reveals the Mek inhibition effect in Erk KO ESCs. The Erk KO effect in ESCs is revealed by comparing iErk1; Erk KO ESCs with or without Dox for 48 h (P0 and P1, respectively). |
| Consent | N/A |
| Sample source location | Tianjin, China |
1. Direct link to deposited data
2. Experimental design
2.1. Cell lines
KH2 mouse embryonic stem cell (ESC) line is used as wild type cells [1]. iErk1; Erk KO cell lines are derived from KH2 ESCs as described previously [2]. Briefly, two endogenous Erk1 alleles are disrupted by TALENs. Next, an exogenous Erk1 gene is integrated into the engineered ColA1 locus through FLPe recombinase-mediated recombination, resulting in a doxycycline (Dox)-inducible Erk1 transgene (iErk1; Erk1−/− ESCs). In the presence of Dox, both endogenous Erk2 alleles in iErk1; Erk1−/− cells are disrupted by Cas9. The resulting cell line is named iErk1; Erk KO ESCs. When cultured in medium supplemented with Dox, the exogenous Erk1 transgene is expressed. Forty-eight hours after Dox withdrawal, no Erk protein can be detected. Thus, iErk1; Erk KO ESCs cultured in the absence of Dox for longer than 48 h are considered as Erk KO ESCs.
2.2. Samples prepared for RNA-sequencing
To gain insights into the role of Erk signaling in Mek inhibition of ESCs, six samples, WT KH2 ESCs treated with or without PD for 48 h (KH2_PD and KH2, respectively), iErk1; Erk KO ESCs cultured with Dox (P0), 48 and 96 h after Dox withdrawal (P1 and P2, respectively), and iErk1; Erk KO ESCs cultured without Dox for 96 h and treated with PD in the last 48 h (P2_PD), are subjected to RNA sequencing (RNA-seq) analysis.
Total RNA is extracted from cells using RNeasy Mini Kit (Qiagen). On-column DNase I digestion (DNase-Free DNase Set, Qiagen) is performed according to manufacturer protocols to eliminate genomic DNA contamination. Then the mRNA is enriched with the oligo(dT) magnetic beads (for eukaryotes), and is fragmented into short fragments (about 200 bp). With random hexamer-primer, the first strand of cDNA is synthesized, and then the second strand is synthesized. The double strand cDNA is purified with magnetic beads. The ends of the double strand cDNA are repaired, and a single nucleotide A (adenine) is added to the 3′-ends. Finally, sequencing adaptors are ligated to the fragments. The ligation products are amplified with PCR. For quality control, RNA and library preparation integrity are verified using Agilent 2100 BioAnalyzer system and ABI StepOnePlus Real-Time PCR System. Standard barcoded RNA-seq libraries are generated for sequencing with Illumina HiSeqTM 2000 (SE50). Construction of RNA sequencing library, sequencing with Illumina HiSeqTM 2000, and bioinformatic analysis are performed by BGI Tech (BGI, Shenzhen, China).
2.3. Data analysis
By base calling, the original image data produced by the sequencer is translated into sequences, which are defined as “raw reads”(or “raw data”) and saved as “.fastq” files. Raw data is filtered to remove sequences of low quality, and only high quality reads are retained as the clean reads (clean data) and used for the subsequent analysis. The filtering procedure includes the following three steps: (a) remove reads with adaptor sequences. (b) Remove reads in which the percentage of unknown bases (N) is greater than 10%. (c) Remove low quality reads. If the percentage of the low quality base (base with quality value ≤ 5) is greater than 50% in a read, we define this read as low quality. Clean reads are mapped to reference sequences (mm9) using SOAPaligner/SOAP2 [3]. No more than 2 mismatches are allowed in the alignment. The sequencing and alignment results are summarized in Table 1. Reads Per kilobase per Million reads (RPKM) is calculated to represent the gene expression level, and saved as “.Gene.rpkm.xls” files. The formula is RPKM = 106 × C/(N × L/103) [4]. Here RPKM(A) is the expression level of gene A, C is the number of reads that uniquely aligned to gene A, N is the total number of reads that uniquely aligned to all genes, and L is the number of bases of gene A. If there is more than one transcript for a gene, the longest one is used to calculate its expression level and coverage.
Table 1.
Summary of the sequencing and mapping result.
| Sample ID | Total reads | Total base pairs | Total mapped reads | Perfect match | ≤ 2 bp mismatch | Unique match | Multi-position match | Total unmapped reads |
|---|---|---|---|---|---|---|---|---|
| P0 | 11,451,219 (100.00%) | 561,109,731 (100.00%) | 9,917,796 (86.61%) | 8,844,577 (77.24%) | 1,073,219 (9.37%) | 9,420,231 (82.26%) | 497,565 (4.35%) | 1,533,423 (13.39%) |
| P1 | 11,817,535 (100.00%) | 579,059,215 (100.00%) | 10,238,164 (86.64%) | 9,151,544 (77.44%) | 1,086,620 (9.19%) | 9,716,556 (82.22%) | 521,608 (4.41%) | 1,579,371 (13.36%) |
| P2 | 12,089,054 (100.00%) | 592,363,646 (100.00%) | 10,535,239 (87.15%) | 9,321,739 (77.11%) | 1,213,500 (10.04%) | 9,969,006 (82.46%) | 566,233 (4.68%) | 1,553,815 (12.85%) |
| P2_PD | 11,900,370 (100.00%) | 583,118,130 (100.00%) | 10,431,854 (87.66%) | 9,250,291 (77.73%) | 1,181,563 (9.93%) | 9,845,925 (82.74%) | 585,929 (4.92%) | 1,468,516 (12.34%) |
| KH2 | 11,962,550 (100.00%) | 586,164,950 (100.00%) | 9,761,489 (81.60%) | 8,473,892 (70.84%) | 1,287,597 (10.76%) | 9,105,242 (76.11%) | 656,247 (5.49%) | 2,201,061 (18.40%) |
| KH2_PD | 11,997,433 (100.00%) | 587,874,217 (100.00%) | 9,709,863 (80.93%) | 8,410,837 (70.11%) | 1,299,026 (10.83%) | 9,067,108 (75.58%) | 642,755 (5.36%) | 2,287,570 (19.07%) |
2.4. Analysis of differentially expressed genes
The RPKM values are used for comparing the difference of gene expression among samples. The criteria of more than two fold change and false discovery rate (FDR) < 0.001 are used to identify lists of differentially expressed genes (DEGs) in each compared group. Three lists of DEGs, Meki (WT), Meki (Erk KO), and Erk KO, are generated by paired comparisons of KH2_PD and KH2, P2_PD and P2, and P1 and P0, respectively (Fig. 1A). Further comparison of these three lists of DEGs reveals that Erk KO are quite different from Meki (WT) (Fig. 1B), consistent with our observation that Erk KO and Mek inhibition have distinct effect on the self-renewal and proliferation of mouse ESCs [2]. Moreover, Meki (Erk KO) and Meki (WT) share a significant portion of genes (Fig. 1C), suggesting that these genes are regulated by Mek inhibition, regardless of the presence or absence of Erk.
Fig. 1.
RNA-seq data reveal an Erk-independent function of Mek. (A) Paired comparisons of KH2_PD and KH2, P2_PD and P2, and P1 and P0, generate three lists of DEGs, Meki (WT), Meki (Erk KO), and Erk KO. (B) The DEG lists of Meki (WT) and Erk KO are quite different. (C) There are significant overlaps between the DEG lists of Meki (WT) and Meki (Erk KO), suggesting Mek inhibition still regulates the overlapping genes even in the absence of Erk.
Acknowledgments
This work is supported by the National Natural Science Foundation of China (grant nos. 31271547, 31470081 and 31271587), the Natural Science Foundation of Tianjin, China (no. 14JCYBJC23600), the Program for New Century Excellent Talents (NCET-13-0293), PCSIRT (no. IRT13023), China MOST National Key Basic Research Program (2012CB911202), and the 111 Project Grant (B08011).
Contributor Information
Lin Liu, Email: liulin@nankai.edu.cn.
Lingyi Chen, Email: lingyichen@nankai.edu.cn.
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