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Non-coding RNAs play important regulatory roles in multicellular organisms, including innate and adaptive immune pathways, which control bacterial, parasitic, and viral infections. However, the global transcriptomic landscape encompassing both ncRNAs and mRNAs in HL-60 cells invaded by\n                      <jats:italic>A. phagocytophilum<\/jats:italic>\n                      remains unexplored.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Cell apoptosis was evaluated by flow cytometry at multiple time points after HL-60 cell infection with\n                      <jats:italic>A. phagocytophilum<\/jats:italic>\n                      . Total RNA was extracted and analyzed by RNA sequencing (RNA-seq) to delineate expression alterations of long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) at 24\u00a0h post-infection (hpi). Bioinformatics methods were employed for gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses to elucidate the potential functions of these differentially expressed genes. Furthermore, an integrated bioinformatics approach was applied to systematically construct a competing endogenous RNA (ceRNA) network involving lncRNAs, miRNAs, and mRNAs.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      <jats:italic>A. phagocytophilum<\/jats:italic>\n                      infection accelerated HL-60 cell apoptosis at multiple time points, with the most significant effect observed at 24 hpi. Transcriptome profiling at 24 hpi identified substantial differential expression, including 487 lncRNAs, 550 mRNAs, and 22 miRNAs with statistically significant changes in expression. Then, expression patterns of eight lncRNAs, eight mRNAs, and seven miRNAs were experimentally validated through reverse transcription quantitative polymerase chain reaction (RT-qPCR), demonstrating strong correlation with RNA-seq results. Bioinformatics analyses revealed significant enrichment of differentially expressed mRNAs in three key pathways: the PI3K\/Akt signaling pathway, the actin cytoskeleton regulation pathway and the p53 signaling pathway. Differentially expressed lncRNAs were largely related to the phospholipase D signaling pathway and pathways related to cortisol and aldosterone synthesis\/secretion. The altered miRNAs showed predominant enrichment in Rap1 and NF-\u03baB signaling pathways. Notably, computational reconstruction of the lncRNA\u2013miRNA\u2013mRNA ceRNA network identified hsa\u2013miR\u20134518 and hsa\u2013miR\u20133609 as central regulatory nodes.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>\n                      This comprehensive transcriptome study elucidates complex gene regulatory networks activated in HL-60 cells after\n                      <jats:italic>A. phagocytophilum<\/jats:italic>\n                      invasion, with particular emphasis on pathogen-modulated miRNA signatures that coordinate critical pathways governing host immune responses and microbial survival strategies. These findings elucidate previously uncharacterized molecular mechanisms underlying\n                      <jats:italic>A. phagocytophilum<\/jats:italic>\n                      pathogenesis and may provide actionable targets for novel therapeutics.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s13071-026-07381-6","type":"journal-article","created":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T12:45:25Z","timestamp":1778244325000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Whole transcriptome analysis reveals differential gene expression associated with Anaplasma phagocytophilum invading HL-60 cells"],"prefix":"10.1186","volume":"19","author":[{"given":"Ke","family":"Shi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lulu","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuxing","family":"Qiu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yankai","family":"Chang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zi","family":"Yan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yaqun","family":"Yan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fuchun","family":"Jian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junqiang","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rongjun","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Longxian","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Changshen","family":"Ning","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,5,8]]},"reference":[{"key":"7381_CR1","doi-asserted-by":"publisher","DOI":"10.1128\/mbio.02961-22","volume":"13","author":"CB Read","year":"2022","unstructured":"Read CB, Lind MCH, Chiarelli TJ, Izac JR, Adcox HE, Marconi RT, et\u00a0al. 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