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. 2022 Feb 16;21(2):146–156. doi: 10.2450/2022.0291-21

Whole transcriptome analysis of platelet concentrates during storage

Hasiyati Heililahong 1,2,*, Peipei Jin 1,*, Hang Lei 1,3, Haihui Gu 4, Baohua Qian 4, Xuefeng Wang 1,3, Jing Dai 1, Xiaohong Cai 1,3,✉
PMCID: PMC10072990  PMID: 35175191

Abstract

Background

Platelets are anucleated blood cells and contain various RNA species. We investigated the changes in the whole transcriptome expression profile of platelet concentrates (PC) during storage to explore biological functions and biomarkers in platelet storage damage.

Materials and methods

Platelets were collected by apheresis from eight healthy blood donors and stored from day 0 to day 4. Platelet phenotyping and function analysis were used to detect platelet activity during storage. RNA-sequencing was used to detect changes in expression of mRNA, lncRNA and circRNA in the PC during storage. Gene ontology and KEGG analyses were applied to predict the functional distribution of differential expression of mRNA. Gene set enrichment analysis was used to analyze the differential levels of gene pathways. Finally, polymerase chain reaction (PCR) analysis was performed to verify the expression of three mRNA (POLE2, DCUN1D4, DAD1).

Results

In total, 10,767 mRNA, 2,923 lncRNA and 68,550 circRNA were detected in the PC by RNA-sequencing. The expression levels of 222 mRNA changed significantly from day 0 to day 4 of storage: 58 increased continuously and 145 decreased continuously. Differentially expressed mRNA may be involved in physiological processes such as platelet activation, platelet aggregation, endocytosis, and apoptosis. Expression levels of 1,413 lncRNA were obvious. The levels of 42 species increased and the levels of 28 species decreased. The expression levels of 198 species of circRNA changed significantly, with those of 13 species changing continuously. The differential levels of expression of DAD1, DCUN1D4 and POLE1 mRNA, shown by RNA sequencing, were validated by PCR assay.

Discussion

Changes in mRNA, lncRNA and circRNA during platelet storage may be closely related to platelet apoptosis and physiological functions in the platelet storage lesion. The expression levels of DAD1, DCUN1D4 and POLE1 could be biomarkers to monitor platelet status in PC bags.

Keywords: transcriptome, apheresis platelets, mRNA, circRNA, lncRNA

INTRODUCTION

Platelet transfusion is an indispensable clinical treatment, both for cancer patients receiving intensive treatment, and for patients with hematological diseases or massive blood loss1. In order to achieve a good clinical effect, the transfused platelets need to maintain sufficient function to deal with vascular injury. The life span of platelets in vivo is about 10 days, while in vitro, the current international standard for platelet preservation is to store platelets for no more than 5 days, in a special storage bag capable of gas exchange, at 22±2°C2. During in vitro preservation, with the accumulation of lactic acid and the consumption of glucose, platelets gradually lose their activity and function, a process called the platelet storage lesion (PSL). These modifications to platelet concentrates (PC) include morphological and physiological changes, platelet activation, changes in membrane glycoproteins and proteolysis, and expression of platelet surface receptors3,4. After a large set of strict screens, such as bacterial culture and nucleic acid testing, the platelets available for clinical use are usually near the end of preservation and after 5 days of storage, all unused PC bags are discarded as a result of PSL. However, many of these bags may still contain functional platelets, since the kinetics of cellular aging are influenced by the age of the blood donors as well as their type of diet and exposure to environmental agents3. The short shelf-life and low activity of platelets caused by PSL seriously affect the scale of platelet collection and the efficacy of transfusion. Although artificial platelet technology is developing5–7, it is still a long way from clinical application and popularization. Therefore, improving platelet preservation and slowing down PSL, thereby improving the effectiveness of clinical platelet infusions, are research hotspots and biomarkers of PC quality are highly sought after in blood bank governance. As special anucleate blood cells, platelets contain many kinds of RNA, such as messenger RNA (mRNA), microRNA, long non-coding RNA (lncRNA), and circular RNA (circRNA). Platelet RNA have become an important target for the study of platelet genetic material. With the development of transcriptomics, the study of the platelet transcriptome has deepened. Platelets lack genomic DNA but retain the ability to synthesize proteins from cytoplasmic mRNA8. Translation of mRNA for two main categories of proteins, including major surface receptors andinflammatory proteins, has been detected in platelets9. Mills et al. found that ribosome profiling of primary human platelets can define the platelet translatome, derived from a biased subset of megakaryocyte mRNA and that restoration of the ribosome rescue/mRNA surveillance factor, Pelota, which is normally absent in wild-type platelets, promotes RNA decay10.

In eukaryotes, lncRNA are transcribed by RNA polymerase II and RNA polymerase III at several loci of the genome. lncRNA participate in and modulate various cellular processes, such as histone modification, DNA methylation, and cellular transcription11. Nan et al. found that differentially expressed lncRNA can participate in platelet activation, platelet aggregation, endocytosis, and regulation of the actin skeleton12. The involvement of lncRNA in platelet activation was confirmed by Zhou et al., who showed that lncRNA metallothionein 1 pseudogene 3 (MT1P3) regulated platelet activation in a murine model of type 2 diabetes by increasing p2y12 expression13.

circRNA are produced from precursor mRNA (pre-mRNA) back-splicing of thousands of genes in eukaryotes. Although circRNA are generally expressed at low levels, recent findings have shed new light on their cell type-specific and tissue-specific expression and on the regulation of their biogenesis14. Alhasan et al. reported that circRNA are enriched in human platelets 17- to 188-fold relative to their levels in nucleated tissues and 14- to 26-fold relative to their levels in samples digested with RNAse R to selectively remove linear RNA. circRNA enrichment in platelets is a signature of transcriptome degradation15. It has also been described that the relative proportion of circRNA in cultured megakaryocytes is much lower than that in mature platelets16.

To our knowledge, there are no reports of whole transcriptome analysis of PC after storage. Therefore, in the present study, we characterized the whole transcriptome, including mRNA, lncRNA and circRNA in PC using RNA sequencing analysis. We further investigated alterations in mRNA, circRNA, and lncRNA levels during storage, and clarified the dynamic changes and related functions. Finally, we validated the expression levels of three mRNA in PC bags by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) assay.

MATERIALS AND METHODS

Collection and processing of platelet samples

Platelets were collected by apheresis from eight healthy volunteer blood donors at the First Affiliated Hospital of Naval Medical University (Shanghai, China). The donors provided written informed consent in accordance with institutional ethics guidelines. The platelets were stored in standard disposable platelet storage bags at 22±2°C under agitation and samples were withdrawn from the bags on days 0, 2, and 4.

Platelet phenotyping and function analysis

On days 0, 2 and 4 of storage, 1 mL samples of platelets were prepared for platelet phenotyping and function analyses including aggregometry17 and flow cytometry. Platelet aggregation was analyzed at 37°C using a Platelet Aggregation Profiler (Chrono-Log, Havertown, PA, USA). Aliquots of 300 μL platelet-rich plasma (PRP; 3×108 platelets/mL) were added to each test-tube into which a small disposable magnet was placed. The PRP was incubated at 37°C for 2 min before addition of 0.6 μL of collagen (Chrono-Log, 1 mg/mL) using a long pipette. After addition of the agonist, the platelet aggregation curve was monitored for 5 min. Three independent experiments were performed to ensure the accuracy of the experimental results obtained.

For the flow cytometry analysis, washed platelets were prepared from the stored platelets. The platelet concentration was diluted to 108/mL with Tyrode’s buffer (NaCl, 4.032 g; KCl, 0.108 g; NaH2PO4·2H2O, 32.76 mg; NaHCO3, 0.5046 g; glucose, 0.4954 g; MgCl2·6H2O, 0.203 g; HEPES, 1.192 g; ddH2O, up to 500 mL), Platelets (25 μL) were added to a new EP tube, to which 5 μL of 10×Binding Buffer and 2 μL FITC-labeled annexin V (BD, Franklin Lakes, NJ, USA) were added, and then 18 μL Tyrode's buffer to make up the reaction system to 50 μL. The contents of the tube were mixed gently and incubated at room temperature for 15 min in the dark, before addition of 200 μL 1×Binding buffer for computer analysis. At the same time, a tube of unlabeled platelets was prepared as a negative control. To prevent fluorescence decay, platelets labeled with annexin V should be analyzed within 1 hour after labeling. FITC-positive cell populations were considered to be platelets in the process of apoptosis. Three independent repeated experiments were performed, and Prism6 software was used for the statistical analysis of the proportion of apoptotic cells.

Total RNA extraction

Before extracting RNA, we performed leukocyte filtration with a disposable leukocyte filter bag. Samples of apheresis platelets (1 mL) were taken on days 0, 2 and 4, and apyrase (final concentration 1U/mL) and EDTA (final concentration 5 mM, pH 8.0) were added. Following centrifugation at room temperature for 10 min at 800×g, 1 mL of TRIzol (Life Technologies, Carlsbad, CA, USA) was added and mixed thoroughly. After extracting total RNA, we used Nanodrop (Thermo Fisher Scientific, Waltham, MA, USA) and Qiaxcel (QIAGEN, Hilden, Germany) to detect the concentration and purity of the extracted RNA.

RNA-sequencing analysis

The samples of total RNA (1 μg) from the PC were treated with Ribo-off ribosomal RNA (rRNA) Depletion Kit (Vazyme, Nanjing, China) before the RNA-sequencing libraries were constructed. The RNA-sequencing libraries were prepared using the VAHTS Total RNA-seq (H/M/R) Library Prep Kit for Illumina (Vazyme) following the manufacturer’s instructions. Briefly, ribosome-depleted RNA samples (approximately 100 ng) were fragmented and then used for first- and second-strand complementary DNA synthesis with random hexamer primers. The cDNA fragments were treated with DNA End Repair Kit to repair the ends, then modified with Klenow to add an A at the 3′ end of the DNA fragments, and finally ligated to adapters. Purified double-stranded DNA was subjected to 12 cycles of PCR amplification, and the libraries were sequenced by the Illumina sequencing platform on a 150 bp paired-end run. The RNA-sequencing analysis procedure is shown in Figure 1. The overall quality of raw FASTA files was assessed by FastQC followed by filtering out low-quality reads. The remaining reads were aligned to the human reference genome (GRCh38 from GENCODE) by STAR in a two-pass mapping mode18. The reads mapped to regions of mRNA or lncRNA genes were counted by feature Counts. Gene expression levels were calculated by fragments per kilobase of transcript per million mapped reads (FPKM). Annotations of mRNA and lncRNA in the human genome were retrieved from the GENCODE V29 (https://www.Gencodegenes.org/human/release_19.html). The genes that were differentially expressed between groups were analyzed using a t-test. The significantly differentially expressed genes were investigated for their involvement in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways (https://www.genome.jp/kegg/) using the Database for Annotation, Visualization and Integrated Discovery (DAVID) v6.8 (https://david.ncifcrf.gov/). The enriched pathways were filtered with p values <0.01. Pre-ranked gene set enrichment analysis (GSEA)19 was run on the ranked list using the Molecular Signatures Database (MSigDB) (https://www.gseamsigdb.org/gsea/msigdb/) as the gene sets. The circRNA were identified, annotated and quantified by the ASJA program20. We calculated the counts per million (CPM) for each circRNA through the number of reads mapped to a circRNA multiplied by 106 and divided by the total number of mapped reads.

Figure 1.

Figure 1

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Whole transcriptome analysis of platelet concentrates during storage

rRna: ribosomal RNA, FPKM: fragments per kilobase of transcript per million; lncRNA: long non-coding RNA: circRNA: circular RNA.

Quantitative reverse transcription polymerase chain reaction

Total RNA was extracted using the TRIzol reagent. Complementary DNA was synthesized using a PrimeScript RT reagent kit (TaKaRa, Tokyo, Japan). The qRT-PCR was carried out using SYBR Premix Ex Taq (TaKaRa) in a 7900 Real-Time PCR System (Applied Biosystems, Thermo Fisher Scientific). β-actin was used as an internal control. The primers are shown in Online Supplementary Content, Table SI.

RESULTS

Whole transcriptome analysis of platelet concentrates during storage

Platelets were collected by apheresis from three healthy, volunteer blood donors and stored with shaking at 22±2°C from day 0 to day 4. During the storage process, the aggregation capacity of the platelets continued to decrease, until the fifth day of storage when the ability of the platelets to aggregate had basically disappeared. This shows that platelets are aging and dying, and that their function declines with the extension of storage time (Figure 2A). Flow cytometry was used to detect the apoptosis of platelets during storage, and the results showed that platelets continued to undergo apoptosis during storage, which corresponded to the results of platelet aggregation function testing (Figure 2B).

Figure 2.

Figure 2

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Phenotype characterization of platelet concentrates during storage

(A) Changes in platelet aggregation activity during storage at day 0, day 2, and day 4. (B) Platelet apoptosis during storage at day 0, day 2, and day 4.****p<0.0001.

We isolated total RNA from PC during storage, and performed rRNA-depleted RNA-sequencing analysis. In total, 10,767 mRNA, 2,923 lncRNA and 68,550 circRNA were detected (FPKM>1) (Figure 1). Over the storage period, from day 0 to day 4, the levels of expression of 222 mRNA changed significantly: 58 increased continuously and 145 decreased continuously. Expression levels of 1,413 lncRNA were obvious: levels of 42 species increased while those of 28 species decreased. The expression levels of 198 species of circRNA changed significantly, with those of 13 species showing a continuous change over time.

Dynamic changes of protein-coding RNA expression in platelet concentrates during storage

Of 10,767 mRNA that were detected (FPKM >1), 222 were differentially expressed between day 0, day 2 and day 4 (Figure 3A). Of these 222 mRNA, 58 were continuously upregulated, and 145 continuously downregulated. Gene ontology (GO) analyses suggested that the differentially expressed upregulated genes were associated with defense against cell death, iron-trafficking protein involved in apoptosis, transcriptional regulation, DNA repair, regulation of insulin secretion, metabolism, replication, and other important functions (Figure 3A). The above-mentioned processes were all closely associated with the PSL. Further investigation of these processes showed that DNA repair and metabolism were the core processes of the GO tree (Figure 3A). KEGG pathway analyses suggested that focal adhesion, the phospholipase D signaling pathway, platelet activation and the insulin signaling pathway were most enriched among the differentially expressed genes (Figure 3B). Fc epsilon RI signaling, chronic myeloid leukemia, bacterial invasion of epithelial cells and Fc gamma R-mediated phagocytosis were the core pathways that were enriched (Figure 3B); and these four pathways were also related to the PSL.

Figure 3.

Figure 3

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Characterization of protein-coding RNA in platelet concentrates during storage

(A) A heatmap showing distinctly defined expression profiles of platelet mRNA of platelet concentrates (PC) stored in a blood bank for 0, 2, and 4 days, using as a metric the Euclidean distance calculated between each PC bag and storage period for hierarchical cluster construction. Red: increased expression; blue: decreased expression. (B) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses in PC during storage. KEGG results showing pathways were also related to the platelet storage lesion.

We also performed GSEA to evaluate the level of gene sets. We found 311 gene sets that were significantly enriched for differentially expressed genes on day 4 compared to day 0. Of these, 73 gene sets were significantly upregulated and 238 gene sets were downregulated. Furthermore, we performed leading-edge analysis with the 237 significantly enriched gene sets in GSEA (Figure 4). The significantly upregulated pathways are responsible for homologous DNA pairing and strand exchange, homology directed repair, mitotic spindle checkpoint, G2, M, DNA damage checkpoint, and DNA double strand break repair (Figure 4A–D). The significantly downregulated pathways included interferon alpha beta signaling, interleukin 4 and interleukin 13 signaling, interferon gamma signaling, interleukin 3, interleukin 5 and GM CSF signaling, and PD 1 signaling (Figure 4E–H).

Figure 4.

Figure 4

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Enrichment plots from gene set enrichment analysis of platelet concentrates during storage

(A–D) Gene set enrichment analysis (CSEA) results showing upregulated pathways. (A) Resolution of D loop structures through synthase dependent strand annealing SDSA, normalized enrichment score (NES)=2.70, p<0.0001. (B) Homologous DNA pairing and strand exchange, NES=2.55, p<0.0001. (C) Resolution of D loop structures. NES=2.45, p<0.0001. (D) Deposition of new CENPA containing nucleosomes at the centromere. NES=2.35, p<0.0001. (E–H) GSEA results showing downregulated pathways. (E) Interferon alpha beta signaling. NES=−2.28, p<0.0001. (F) Interleukin 4 and interleukin 13 signaling, NES=−2.12, p<0.0001. (G), Interferon gamma signaling, NES=−2.10, p<0.0001. (H) Immunoregulatory interactions between a lymphoid and a non-lymphoid Cell NES=−2.07, p<0.0001.

Long non-coding RNA expression in platelet concentrates during storage

lncRNA expression profiles were also characterized and the expression of 2,923 lncRNA was analyzed. The top 20 lncRNA in PC are shown in Online Supplementary Content, Table SII. NORAD (Non-coding RNA Activated by DNA damage) was the top expressed lncRNA. Seventy lncRNA were differentially expressed in PC during storage. The classification of all types of lncRNA is illustrated in Figure 5A, which shows that long intergenic non-coding RNA accounted for about 43% of the non-coding RNA. STXBP5-AS1, CTD-3214H19.6, and ZNF667-AS1 were the three top upregulated lncRNA in PC during storage, and CTD-2562J17.6, RP11-363E7.4, and RP4-591C20.9 were the three most downregulated lncRNA in the PC during storage (Figure 5B).

Figure 5.

Figure 5

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Characterization of long non-coding and circular RNA in platelet concentrates during storage

(A) Pie chart of the types of long non-coding (lnc)RNA in platelet concentrates (PC). (B) Heatmap showing distinctly defined expression profiles of lncRNA in platelets stored in a blood bank for 0, 2, and 4 days, using as a metric the Euclidean distance calculated between each PC bag and storage period for hierarchical cluster construction. Red: increased expression; blue: decreased expression. (C) Pie chart of circular (circ)RNA host genes. (D) Heatmap showing distinctly defined expression profiles of circRNA in platelets stored in a blood bank for 0, 2, and 4 days, using as a metric the Euclidean distance calculated between each PC bag and storage period for hierarchical cluster construction. Red: increased expression; blue: decreased expression.

Circular RNA expression in platelet concentrates during storage

We also explored the circRNA expression profiles of PC during storage. In total, we identified 68,550 circRNA candidates with at least two mapped reads. Most of the circRNA (57,205) were derived from protein-coding genes. Only 5,828 circRNA were from non-coding RNA and 5,517 circRNA were unannotated (Figure 5C). The analysis of differential expression revealed that 198 circRNA were differentially expressed in PC during storage, and that only 13 circRNA changed continuously (Figure 5D). Co-expression between circRNA and mRNA was calculated to predict potential biological functions of these circRNA. The 13 circRNA with continuously changed expression are related to metabolism, DNA repair, mitochondrial small ribosomal subunits, cell growth and division. Notable findings were anti-apoptotic protein (circID: chr2_32473112_32487801_+), which can regulate cell death by controlling caspases and by acting as an E3 ubiquitin-protein ligase, and apoptosis-linked gene-2 (ALG-2; circID: chr3_48451729_48454418_+), which is a gene product of PDCD6, a 22-kDa Ca2+-binding protein. The top 20 circRNA are involved in a variety of cellular processes, including cell cycle progression, signal transduction, apoptosis, gene regulation, cell-cell adhesion and growth, differentiation and platelet activation (Online Supplementary Content, Table SIII).

Quantitative polymerase chain reaction validation of the expression levels of three mRNA during platelet concentrate storage

Finally, we focused on several candidate mRNA as critical regulators of platelet functions and verified the changes in their expression levels using qRT-PCR. We measured mRNA levels of the three most highly expressed mRNA (DAD1, DCUN1D4, and POLE1) which were induced during storage. qRT-PCR assays showed that levels of these three mRNA were significantly upregulated during storage (Figure 6), consistent with the RNA-sequencing results.

Figure 6.

Figure 6

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Quantitative reverse transcriptase polymerase chain reaction verification of DAD1, DCUN1D4, and POLE1 mRNA in platelets collected by apheresis from five healthy blood donors. β-actin was used as an internal control

DISCUSSION

With increasing demand for platelets in hospitals, it is becoming ever more important to understand the mechanism of apoptosis and the PSL. As important genetic material in platelets, platelet RNA provides a basis for understanding the various mechanisms of platelet survival and death. Since platelets are small anucleate cells derived from the cytoplasmic fragmentation of megakaryocytes, they are unable to synthesize new RNA and it would therefore be expected that the levels of expression of most platelet RNA would decrease over time when platelets are stored at room temperature21. However, the expression levels of specific RNA may actually increase under these conditions.

All RNA have distinct inherent half-lives that dictate their level of accumulation. However, the half-life of an RNA molecule can vary and may change rapidly or remain stable for more than a few days22. Most previous studies focused on microRNA in platelets and, to the best of our knowledge, no systematic study has been conducted to investigate the whole transcriptome of PC during storage. There are many kinds of RNA in platelets, including mRNA, microRNA, lncRNA, and circRNA. In this study, we characterized the mRNA, lncRNA and circRNA species using whole transcriptome sequencing analysis. We demonstrated the dynamic profiles of the platelet transcriptome during storage and explored the pathways related to platelet life and the PSL, providing clues on how to prolong platelet storage life in vitro.

In the current study, we comprehensively analyzed mRNA, lncRNA, and circRNA expression of PC during storage by rRNA-depleted RNA-sequencing. We found that during platelet storage, the different expressions of mRNA are usually related to defense against cell death, iron-trafficking protein involved in apoptosis, transcriptional regulation, DNA repair, regulation of insulin secretion, metabolism, and replication. This may reflect the fact that DNA damage in platelet mitochondria tends to increase during platelet aging and death in vitro, and that mitochondrial function continues to decline. Studies have pointed out that platelets contain mitochondria, which are the main site of platelet aerobic respiration. Although there are only a few mitochondria in platelets and these organelles have a simple structure, they play an important role in cell energy metabolism23. Blocking anaerobic glycolysis will not cause a decrease in platelet ATP levels, nor will it inhibit normal platelet function, as mitochondria can alone support the energy requirements of platelets23, and so mitochondrial damage may be one of the important causes of platelet damage. Indeed, platelet mitochondrial DNA plays a key role in the regulation of apoptosis. During the storage of platelets, apoptosis is triggered mainly by shear stress and activation22. Platelet life-span is regulated by the intrinsic pathway of apoptosis. In this study, we found that BCL2L1 is among the top ten continuously downregulated mRNA. Bcl-xl(s) is an isoform of BCL2L1 that promotes apoptosis and BCL2L1 is a potent inhibitor of cell death, by inhibiting activation of caspases24. The continuous downregulation of BCL2L1 may mean that the possibility of platelet apoptosis increases. Among the mRNA whose expression increased continuously during storage, DAD1 was the most upregulated; interestingly, it has been shown that loss of DAD1 protein triggers apoptosis25.

Among the upregulated lncRNA, STXBP5-AS126 and ZNF667-AS127 have been reported to be related to apoptosis, while among the downregulated lncRNA, high expression of MAGI2-AS328 and TSPOAP1-AS1 is correlated with the PTEN pathway. Researchers have reported that STXBP5-AS1 overexpression suppressed cell proliferation and invasion in cervical cancer by acting as a sponge for miR-96-5p to regulate the expression of PTEN, of which the nuclear monoubiquitinated form possesses greater apoptotic potential26. Vrba et al. showed that ZNF667-AS1 is closely associated with the mortal phenotype of cells and is expressed in all normal human cells with a finite lifespan examined to date but is lost in immortalized human mammary epithelial cells27. Decreased expression of lncRNA is involved in transcriptional regulation. The highly expressed top 20 lncRNA are usually associated with characteristics of platelets, and high expression of MAGI2-AS328 and TSPOAP1-AS1 is correlated with the PTEN pathway, of which the nuclear monoubiquitinated form possesses greater apoptotic potential. NORAD functions to preserve genome stability29, modulating the mRNA abundance of Pumilio targets, in particular those involved in mitotic progression29–31, and it has been found that deleting NORAD drives premature aging in mice32. Through an online tool (www.genecards.org), we found that some of the differentially expressed lncRNA are associated with cell growth, such as NEAT133 and MIR4435-2HG34 (Online Supplementary Content, Table SII). Other reports have described that TUG135, MEG336, SMILR37, and RBM1538 play a major role in apoptosis and cell death, especially of blood cells11. These lncRNA were also found in our study.

The majority of circRNA were derived from exons via circularization of pre-mRNA, which is consistent with previous reports that most circRNA are derived from coding sequences. Analysis of circRNA revealed that BIRC6, which is an anti-apoptotic protein (circID: chr2_32473112_32487801_+) can regulate cell death by controlling caspases and by acting as an E3 ubiquitin-protein ligase39–41. Apoptosis-linked gene 2 (ALG-2, circID: chr3_48451729_48454418_+), which is a gene product of PDCD6, participates in T-cell receptor-, Fas-, and glucocorticoid-induced programmed cell death42.

Finally, qRT-PCR analysis of the mRNA showed that DAD1, DCUN1D4, and POLE1 were upregulated. The DAD1 protein (Defender against apoptotic cell death), was identified as a mammalian cell death suppressor that may act downstream of the bcl-2 protein25. DAD1 mRNA is downregulated in human prostatic tumor cells when they undergo apoptosis by staurosporine, a potent inhibitor of protein kinases. Inhibition of this enzyme by tunicamycin can induce apoptosis in human promyelocytic HL-60 cells. Therefore, high expression of DAD1 can activate oligosacchyltransferase (OST) and block apoptosis, thereby enhancing cell survival43. DCUN1D4 contributes to the neddylation of all cullins by transferring NEDD8 from N-terminally acetylated NEDD8-conjugating E2 enzyme to different cullin C-terminal domain-RBX complexes which are necessary for the activation of cullin-RING E3 ubiquitin ligases (CRL). NEDDE8 and CRL are related to the genome for ultraviolet-light-induced DNA damage44,45. We also measured the level of POLE1, which encodes the catalytic subunit of DNA polymerase epsilon. This enzyme is involved in DNA repair and chromosomal DNA replication. Along with DNA polymerase POLD1 and DNA polymerase POLK, has a role in excision repair (NER) synthesis following ultraviolet irradiation46. In brief, DAD1, DCUN1D4, and POLE1 mRNA are all related to DNA repair and apoptosis and could therefore be biomarkers that reflect the status of platelets during storage in PC bags.

CONCLUSIONS

In conclusion, we performed whole transcriptome analysis on stored platelets on day 0, day 2, and day 4, and characterized mRNA, lncRNA, and circRNA profiles. We found that the differentially expressed RNA are closely related to platelet function, metabolism, DNA repair, cell cycle, apoptosis, etc. We highlight candidate mRNA as biomarkers of storage damage which could be used as tools to evaluate the quality of stored PC. The use of mRNA as biomarkers of damage will contribute to improved quality of blood products for transfusions. We also found that most of the pathways are related to DNA repair. We intend to conduct further research on improving the DNA repair pathways of PC during storage to extend the shelf-life of platelets.

Supplementary Information

ACKNOWLEDGMENTS

The Authors thank Prof. Shenglin Huang at Fudan University for support and technical direction of the RNA-sequencing analysis.

Footnotes

FUNDING AND RESOURCES

This work was supported by the Chinese National Natural Science Foundation (82070194, 81770131, 81970127, 81970165) and Wei Gao Science Foundation of the Chinese Society of Blood Transfusion (CSBT-WG-2019-01).

AUTHORSHIP CONTRIBUTIONS

HH and PJ contributed equally to this manuscript as co-first Authors; JD and XC contributed equally as co-last Authors. XC and JD were responsible for the conception and development of the experiments; HG, BQ and XW collected and processed the platelet samples; HH, PJ and HL analyzed the platelet phenotype; HH and PJ collected the platelet concentrates and extracted total RNA; HH, PJ and XC performed the RNA-sequencing polymerase chain reaction analyses; HH, JD and XC wrote and edited the manuscript.

The Authors declare no conflicts of interest.

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