Background:Copy‐number alteration (CNA) is a hallmark of cancer genomes and has been implicated in the development of human cancers, including myeloid neoplasms. We developed a novel, next‐generation sequencing‐based platform for highly sensitive detection of CNAs, which was applied to sequencing data from more than 2,000 patients.Aims:To delineate a comprehensive landscape of CNAs in myeloid neoplasms and differential impacts of CNAs on clinical and biological phenotype.Methods:Whole‐exome sequencing (WES) was performed on samples from 260 patients with de novo acute myeloid leukemia (de novo AML, n = 136), myelodysplastic syndrome (MDS, n = 75), myelodysplastic/myeloproliferative neoplasms (MDS/MPN, n = 32), or AML‐MDS (n = 17). Additionally, almost 2,000 cases with de novo AML, MDS, MDS/MPN, AML‐MDS, or myeloproliferative neoplasms (MPN) were examined by targeted deep sequencing, 763 of which were pre‐transplantation peripheral blood provided by Japan Marrow Donor Program.Total copy numbers and allele‐specific copy numbers (ASCNs) were quantified based on sequencing depths and allelic ratios on genome‐wide probes. To enhance the precision of analyses, copy‐number signals were corrected for multiple known biases (e.g. those due to GC content, ASCN, and PCR duplication). We also corrected residual biases by comparing signals in a tumor sample with those in normal samples. Copy‐number polymorphisms reported in Database of Genomic Variants were excluded.Results:Analyses on 260 cases using WES identified a total of 821 CNAs (497 deletions, 246 amplifications, 78 UPD), where 57% of the patients harbored at least one alteration. Using GISTIC 2.0 algorism, we identified significantly altered regions involving myeloid driver genes: losses of 7q22.1 (CUX1), 12p13.2 (ETV6), 17p13.1 (TP53), and 17q11.2 (NF1), and gains of 3q26–27 (EVI1), 8q24.21 (MYC), 11q23.3 (MLL), 11q24–25 (ETS1), 13q12.2 (FLT3), 21q22.2 (ERG). Comparing between myelodysplasia (MDS, MDS/MPN, AML‐MDS) and de novo AML, deletions of 13q14 were significantly enriched in myelodysplasia (Odds ratio [OR]: 5.07, P = 0.040) while amplifications of 11q24–25 (OR: 5.54, P = 0.028), and 21q22.2 (OR: 6.10, P = 0.020) in de novo AML, suggesting a specific role of these events in each disease entity.Expanding our findings, we combined cases examined by WES with those examined by targeted deep sequencing. In the whole cohort, the landscape of CNAs is largely consistent with that in WES data, and we additionally highlighted less frequent but recurrent alterations, resulting in a comprehensive landscape of CNAs in myeloid neoplasms. This allowed us to assess the associations of CNAs with disease characteristics in details. A set of CNAs correlated with specific disease subtypes. For example, del(5q), del(7q), del(12p), and loss of heterozygosity (LOH) of 17p were enriched in AML‐MDS as compared with MDS, while LOH of 4q and 11q were enriched in Chronic myelomonocytic leukemia. In prognostic analyses, del(16q), amp(11q), amp(19q), amp(22q) were most strongly associated with poor survivals among all CNAs (Hazard ratio: >2.0, P < 0.001), independently of complex karyotypes or TP53 mutations.Summary/Conclusion:We obtained the comprehensive landscape of CNAs in myeloid neoplasms based on the sequencing data from more than 2,000 patients. We found that CNAs targeted specific myeloid driver genes and were differentially correlated with disease subtypes and prognosis. Collectively, our analysis uncovered the clinical and biological implications of CNAs in myeloid neoplasms.