Background: Clinical studies and genetic analyses have revealed that juvenile myelomonocytic leukemia (JMML) is caused by somatic and/or germline mutations of genes involved in the RAS/MAPK signalling pathway. Given the vastly different clinical prognosis among individual patients that have had this disease, mutations in genes of other pathways may be involved. Methods: In this study, we conducted whole-exome and cancer-panel sequencing analyses on a bone marrow sample from a 2-year old juvenile myelomonocytic leukemia patient. We also measured the microRNA profile of the same patient's bone marrow sample and the results were compared with the normal mature monocytic cells from the pooled peripheral blood. Results: We identified additional novel mutations in the PI3K/AKT pathway and verified with a cancer panel targeted sequencing. We have confirmed the previously tested PTPN11 gene mutation (exon 3 181G > T) in the same sample and identified new nonsynonymous mutations in NTRK1, HMGA2, MLH3, MYH9 and AKT1 genes. Many of the microRNAs found to be differentially expressed are known to act as oncogenic MicroRNAs (onco-MicroRNAs or oncomiRs), whose target genes are enriched in the PI3K/AKT signalling pathway. Conclusions: Our study suggests an alternative mechanism for JMML pathogenesis in addition to RAS/MAPK pathway. This discovery may provide new genetic markers for diagnosis and new therapeutic targets for JMML patients in the future.Keywords: single-cell; RNA-Seq; differential expression Author summary: We conducted whole-exome sequencing and microRNA profiling to analyze a patient of juvenile myelomonocytic leukemia. Our sequencing data and computational studies identified novel mutations in NTRK1, HMGA2, MLH3, MYH9, and AKT1 genes, which can potentially be used as diagnostic biomarkers and therapeutic targets. We suggest an alternative mechanism for JMML pathogenesis in addition to the RAS/MAPK pathway. We also identified a number of differentially expressed microRNAs that are known to act as oncogenic MicroRNAs in the patient sample. Our work provides an example of precision medicine to characterize the rare disease using a single-patient data.