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Computing cell state discriminates the aberrant hematopoiesis and activated microenvironment in Myelodysplastic syndrome (MDS) through a single cell genomic study.

Xinyu Guo | Wenyan Jin | Yuchen Wen | Zhiqin Wang | Xiaotong Ren | Zhaoyun Liu | Rong Fu | Zhigang Cai | Lijuan Li
Journal of translational medicine | 2024

Myelodysplastic syndrome (MDS) is a complicated hematopoietic malignancy characterized by bone marrow (BM) dysplasia with symptoms like anemia, neutropenia, or thrombocytopenia. MDS exhibits considerable heterogeneity in prognosis, with approximately 30% of patients progressing to acute myeloid leukemia (AML). Single cell RNA-sequencing (scRNA-seq) is a new and powerful technique to profile disease landscapes. However, the current available scRNA-seq datasets for MDS are only focused on CD34+ hematopoietic progenitor cells. We argue that using entire BM cell for MDS studies probably will be more informative for understanding the pathophysiology of MDS.

Pubmed ID: 39033303

Research resources used in this publication

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Associated grants

  • Agency: Tianjin Medical University Talent Program,
    Id: No.82170173
  • Agency: National Science Foundation of China,
    Id: No. 82371789
  • Agency: Tianjin Medical Key Discipline Construction Project,
    Id: TJYXZDXK-028A

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This is a list of tools and resources that we have found mentioned in this publication.


PRISM (tool)

RRID:SCR_005375

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role.

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ggplot2 (tool)

RRID:SCR_014601

Open source software package for statistical programming language R to create plots based on grammar of graphics. Used for data visualization to break up graphs into semantic components such as scales and layers.

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Seurat (tool)

RRID:SCR_016341

Software as R package designed for QC, analysis, and exploration of single cell RNA-seq data. Enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data.

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