Area de Hemato-Oncología, Centro de Investigación Médica Aplicada, Universidad de Navarra, Instituto de investigación sanitaria de Navarra (IDISNA), Pamplona, Spain; Centro de Investigación Biomédica en Red de Cáncer, Madrid, Spain
Teresa Ezponda
Area de Hemato-Oncología, Centro de Investigación Médica Aplicada, Universidad de Navarra, Instituto de investigación sanitaria de Navarra (IDISNA), Pamplona, Spain; Centro de Investigación Biomédica en Red de Cáncer, Madrid, Spain
Nerea Berastegui
Area de Hemato-Oncología, Centro de Investigación Médica Aplicada, Universidad de Navarra, Instituto de investigación sanitaria de Navarra (IDISNA), Pamplona, Spain
Ana Alfonso-Pierola
Centro de Investigación Biomédica en Red de Cáncer, Madrid, Spain; Clinica Universidad de Navarra, Pamplona, Spain
Amaia Vilas-Zornoza
Area de Hemato-Oncología, Centro de Investigación Médica Aplicada, Universidad de Navarra, Instituto de investigación sanitaria de Navarra (IDISNA), Pamplona, Spain; Centro de Investigación Biomédica en Red de Cáncer, Madrid, Spain
Patxi San Martin-Uriz
Area de Hemato-Oncología, Centro de Investigación Médica Aplicada, Universidad de Navarra, Instituto de investigación sanitaria de Navarra (IDISNA), Pamplona, Spain; Centro de Investigación Biomédica en Red de Cáncer, Madrid, Spain
Diego Alignani
Flow Cytometry Core, Universidad de Navarra, Pamplona, Spain
Hospital Universitario de Salamanca, Salamanca, Spain
Felix Lopez
Hospital Universitario de Salamanca, Salamanca, Spain
Sandra Muntion
Hospital Universitario de Salamanca, Salamanca, Spain; Red de Investigación Cooperativa en Terapia Celular TerCel, ISCIII., Madrid, Spain
Fermin Sanchez-Guijo
Hospital Universitario de Salamanca, Salamanca, Spain; Red de Investigación Cooperativa en Terapia Celular TerCel, ISCIII., Madrid, Spain
Antonieta Molero
Department of Hematology, Vall d'Hebron Hospital Universitari, Barcelona, Spain
Julia Montoro
Department of Hematology, Vall d'Hebron Hospital Universitari, Barcelona, Spain
Guillermo Serrano
Computational Biology Program, Universidad de Navarra, Pamplona, Spain
Aintzane Diaz-Mazkiaran
Centro de Investigación Biomédica en Red de Cáncer, Madrid, Spain; Computational Biology Program, Universidad de Navarra, Pamplona, Spain
Miren Lasaga
Translational Bioinformatics Unit, NavarraBiomed, Pamplona, Spain
David Gomez-Cabrero
Translational Bioinformatics Unit, NavarraBiomed, Pamplona, Spain; Biological & Environmental Sciences & Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
Maria Diez-Campelo
Hospital Universitario de Salamanca, Salamanca, Spain
David Valcarcel
Department of Hematology, Vall d'Hebron Hospital Universitari, Barcelona, Spain
Mikel Hernaez
Computational Biology Program, Universidad de Navarra, Pamplona, Spain
Area de Hemato-Oncología, Centro de Investigación Médica Aplicada, Universidad de Navarra, Instituto de investigación sanitaria de Navarra (IDISNA), Pamplona, Spain; Centro de Investigación Biomédica en Red de Cáncer, Madrid, Spain
Area de Hemato-Oncología, Centro de Investigación Médica Aplicada, Universidad de Navarra, Instituto de investigación sanitaria de Navarra (IDISNA), Pamplona, Spain; Centro de Investigación Biomédica en Red de Cáncer, Madrid, Spain; Clinica Universidad de Navarra, Pamplona, Spain; Red de Investigación Cooperativa en Terapia Celular TerCel, ISCIII., Madrid, Spain
Early hematopoiesis is a continuous process in which hematopoietic stem and progenitor cells (HSPCs) gradually differentiate toward specific lineages. Aging and myeloid malignant transformation are characterized by changes in the composition and regulation of HSPCs. In this study, we used single-cell RNA sequencing (scRNA-seq) to characterize an enriched population of human HSPCs obtained from young and elderly healthy individuals. Based on their transcriptional profile, we identified changes in the proportions of progenitor compartments during aging, and differences in their functionality, as evidenced by gene set enrichment analysis. Trajectory inference revealed that altered gene expression dynamics accompanied cell differentiation, which could explain aging-associated changes in hematopoiesis. Next, we focused on key regulators of transcription by constructing gene regulatory networks (GRNs) and detected regulons that were specifically active in elderly individuals. Using previous findings in healthy cells as a reference, we analyzed scRNA-seq data obtained from patients with myelodysplastic syndrome (MDS) and detected specific alterations of the expression dynamics of genes involved in erythroid differentiation in all patients with MDS such as TRIB2. In addition, the comparison between transcriptional programs and GRNs regulating normal HSPCs and MDS HSPCs allowed identification of regulons that were specifically active in MDS cases such as SMAD1, HOXA6, POU2F2, and RUNX1 suggesting a role of these transcription factors (TFs) in the pathogenesis of the disease. In summary, we demonstrate that the combination of single-cell technologies with computational analysis tools enable the study of a variety of cellular mechanisms involved in complex biological systems such as early hematopoiesis and can be used to dissect perturbed differentiation trajectories associated with perturbations such as aging and malignant transformation. Furthermore, the identification of abnormal regulatory mechanisms associated with myeloid malignancies could be exploited for personalized therapeutic approaches in individual patients.