Wiskott-Aldrich syndrome (WAS) is a rare X-linked primary immunodeficiency characterized by microthrombocytopenia, eczema, recurrent infection and increased incidence of autoimmune disorders and malignancy. WAS is caused by mutations in the
Wiskott-Aldrich Syndrome (WAS) is a rare X-linked primary immunodeficiency disorder that affects males with a frequency of one in 10,000,000(
The WASp protein contains multiple functional domains and serves a key role in the regulation of branched actin chain polymerization, primarily regulating the actin cytoskeleton in hematopoietic cells (
Studies have found that IL-10 production of regulatory B cells is decreased in WASp-knockout (WAS-KO) mice (
The present study investigated the differences in the spleen transcriptome of 10-week-old WAS-KO and wild-type (WT) mice. Differentially expressed genes (DEGs) that were significantly altered were identified and Gene Ontology (GO) analysis to determine the specific functions of genes and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis to evaluate the enrichment of gene sets was performed. In addition, DisGeNET and Reactome analyses were performed to find possible novel autoimmune complications. To the best of our knowledge, the present study is the first to investigate transcriptome sequences in the spleen of WAS-KO mice, which may facilitate understanding of the cellular and molecular mechanisms in WAS.
RNA-seq library was prepared by a TruSeq RNA sample preparation kit (Illumina, Inc.) and sequencing of libraries was conducted on an Illumina HiSeq system. A total of three samples were collected from each group. The read depth was 30-50x106 bp for each sample. Skewer (v0.2.2) software (
DEG analysis was conducted between WT and WAS-KO mice to identify significantly up- or downregulated genes. DEGs were assessed by DESeq 2 (v1.16.1) software (
DEGs were selected according to the criteria |log2 (fold-change) |≥1 and P<0.05. DEGs are shown in
To determine the functions of the identified DEGs, GO enrichment analysis was performed for significantly upregulated and downregulated DEGs (
GO analysis of downregulated DEGs showed that they were involved in ‘microtubule bundle formation’, ‘anatomical structure formation involved in morphogenesis’ and ‘cellular component assembly involved in morphogenesis’ BPs. In terms of CC annotation, ‘extracellular matrix component’ and ‘extrinsic component of membrane’ showed significant enrichment. In terms of the MF annotation, ‘ion binding’, ‘heparin binding’ and ‘glycosaminoglycan binding’ showed significant enrichment (
To determine which pathways may be directly affected by gene deficiency in WAS-KO mice, the significantly upregulated and downregulated DEGs were analyzed using the KEGG pathway database. The significantly upregulated DEGs were primarily involved in signaling pathways including ‘cellular senescence’, ‘p53 signaling pathway’ and ‘ferroptosis’ (a cell death pathway). A number of other DEGs were found to participate in different metabolic pathways, such as ‘glutathione metabolism’, ‘glycolysis/gluconeogenesis’ and ‘glycerophospholipid metabolism’ (
KEGG results of downregulated DEGs showed that these genes were involved in ‘platelet activation’, ‘Th1 and Th2 cell differentiation’ and ‘antigen processing and presentation’ for the immune system and ‘MAPK signaling pathway’, ‘calcium signaling pathway’ and ‘cAMP signaling pathway’ for signal transduction (
To investigate potential symptoms caused by DEGs, a disease enrichment analysis was performed using the DisGeNET database. Analysis of the top 30 clusters of disease terms showed that ‘anemia, hemolytic’, ‘anemia, sickle cell’, ‘hereditary spherocytic hemolytic’, ‘spherocytosis’, ‘thalassemia’ and ‘hemoglobin H disease’ were highly enriched (
To elucidate the mechanisms by which these diseases may occur in WAS-KO mice, enrichment analysis was performed using the Reactome database. Analysis of the top 30 clusters of Reactome terms showed that ‘heme biosynthesis’, ‘activation of ATR in response to replication stress’, ‘collagen degradation’, ‘G1-TP53 regulates transcription of genes involved in G1 cell cycle arrest’ and ‘glutathione synthesis and recycling’ were highly enriched (
To validate the aforementioned signaling pathways and determine potential novel marker genes in WAS, expression levels of marker genes were compared between WT and WAS-KO mice (
WAS has a wide clinical spectrum ranging from mild with thrombocytopenia, recurrent infections and eczema to severe presentation, which can include complications such as life-threatening hemorrhage, immunodeficiency, atopy, autoimmunity and cancer (
The large amount of cell senescence and apoptosis in the spleens of WAS-KO mice promoted cell division and cofactor biosynthesis processes, but dysfunction in cell structure formation and microtubule bundle formation may lead to functional defects in newly generated cells and ultimately cause splenic damage spleen in these mice. Rawlings
WASp is a cytoskeletal scaffolding adapter that coordinates transmission of stimulatory signals to downstream inducers of actin remodeling and cytoskeletal-dependent T cell responses (
In addition, WASp serves an essential role in signal transduction and effector functions of T cells; signal transduction regulating the function of T cells in immune response is impaired in WAS (
Studies have found hemolysis and thrombocytopenia in WAS (
The present study detected 1,964 DEGs between WAS-KO and WT mice but only showed the top 30 enrichment results; other results indicated that the role of the spleen in WAS needs more attention in further studies (data not shown). In addition, the present study did not verify expression changes of DEGs by other methods. Further analysis of transcriptome data available may aid in discovering novel mechanisms to improve therapies for WAS, especially in the context of anemia and primary immunodeficiency. Moreover, clinical samples are being collected from patients with WAS; analysis of differences in transcriptome levels between WAS-KO mice and patients with WAS in future studies and identification of marker genes may provide the basis for clinical gene therapy.
Not applicable.
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. The RNA-seq data used in this manuscript are publicly available in the Gene Expression Omnibus repository (accession no. GSE214745;
FFL, JY, QG, YX, LLW, YYH and CP contributed to the study design. FFL, JY and CP analyzed the data. QG, YX, LLW and YYH collected data. FFL wrote the manuscript. CP revised the manuscript. CP and FFL confirm the authenticity of all the raw data. All authors have read and approved the final manuscript.
All experiments were approved by the Medical Ethics Committee of The Third People's Hospital of Shenzhen (approval no. 2021038).
Not applicable.
The authors declare that they have no competing interests.
Volcano plot and heatmap of significant DEGs. (A) DEGs between WT and WAS-KO mice included 1,964 transcripts that were significantly altered (P<0.05, |log2 FC|≥1), with 996 upregulated and 968 downregulated transcripts. (B) DEGs between the WT and WAS-KO groups were cluster analyzed and the results are shown as heatmaps. DEG, differentially expressed gene; WT, wild-type; WAS-KO, Wiskott-Aldrich syndrome knockout; FC, fold-change.
GO identifiers in the cluster of overlapping DEGs in WAS-KO and WT mice. (A) Top GO identifiers in the cluster of overlapping upregulated DEGs in WAS-KO and WT mice. (B) Network analysis of the top 20 GO clusters in the upregulated DEGs. (C) Top GO identifiers in the cluster of overlapping downregulated DEGs in WAS-KO and WT mice. (D) Network analysis of the top 20 GO clusters in the downregulated DEGs. BP, biological process; CC, cellular component; MF, molecular function; GO, Gene Ontology; DEG, differentially expressed gene; WT, wild-type; WAS-KO, Wiskott-Aldrich syndrome knockout; FDR, false discovery rate.
KEGG pathway analysis of DEGs in WAS-KO and WT mice. (A) Top KEGG pathways in the cluster of upregulated DEGs in WAS-KO and WT mice. (B) Network analysis of the top 20 KEGG pathways in the upregulated DEGs. (C) Top KEGG pathways in the cluster of downregulated DEGs in WAS-KO and WT mice. (D) Network analysis of the top 20 KEGG pathways in downregulated DEGs. DEG, differentially expressed gene; WT, wild-type; WAS-KO, Wiskott-Aldrich syndrome knockout; KEGG, Kyoto Encyclopedia of Genes and Genomes.
DisGeNET and Reactome analyses of DEGs in WAS-KO and WT mice. (A) Top disease analyses in the cluster of DEGs in WAS-KO and WT mice. (B) Network analysis of the top 20 DEGs. (C) Top Reactome analysis in the cluster of DEGs in WAS-KO and WT mice. (D) Network analysis of the top 20 Reactome analyses in DEGs. DEG, differentially expressed gene; WT, wild-type; WAS-KO, Wiskott-Aldrich syndrome knockout; FDR, false discovery rate.
Relative expression of marker genes in WAS. Heatmap of differentially expressed marker genes involved in (A) cellular morphogenesis, (B) cell death, (C) immune system and (D) signal transduction. Expression is showed with log10(fragments per kilobase of transcript per million fragments mapped). WT, wild-type; WAS-KO, Wiskott-Aldrich syndrome knockout.