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Characterization of the transcriptome profiles related to globin gene switching during in vitro erythroid maturation

  • Biaoru Li
    ,
  • Lianghao Ding
    ,
  • Wei Li
    ,
  • Michael D. Story
    ,
  • Betty S. Pace(corresponding author)
*Corresponding author for this work
Scholary Output:
Contribution to journal
Article
Peer-review

Open access

Sustainable Development Goals

  • SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well

Abstract

Background: The fetal and adult globin genes in the human β-globin cluster on chromosome 11 are sequentially expressed to achieve normal hemoglobin switching during human development. The pharmacological induction of fetal γ-globin (HBG) to replace abnormal adult sickle β S-globin is a successful strategy to treat sickle cell disease; however the molecular mechanism of γ-gene silencing after birth is not fully understood. Therefore, we performed global gene expression profiling using primary erythroid progenitors grown from human peripheral blood mononuclear cells to characterize gene expression patterns during the γ-globin to β-globin (γ/β) switch observed throughout in vitro erythroid differentiation.Results: We confirmed erythroid maturation in our culture system using cell morphologic features defined by Giemsa staining and the γ/β-globin switch by reverse transcription-quantitative PCR (RT-qPCR) analysis. We observed maximal γ-globin expression at day 7 with a switch to a predominance of β-globin expression by day 28 and the γ/β-globin switch occurred around day 21. Expression patterns for transcription factors including GATA1, GATA2, KLF1 and NFE2 confirmed our system produced the expected pattern of expression based on the known function of these factors in globin gene regulation. Subsequent gene expression profiling was performed with RNA isolated from progenitors harvested at day 7, 14, 21, and 28 in culture. Three major gene profiles were generated by Principal Component Analysis (PCA). For profile-1 genes, where expression decreased from day 7 to day 28, we identified 2,102 genes down-regulated > 1.5-fold. Ingenuity pathway analysis (IPA) for profile-1 genes demonstrated involvement of the Cdc42, phospholipase C, NF-Kβ, Interleukin-4, and p38 mitogen activated protein kinase (MAPK) signaling pathways. Transcription factors known to be involved in γ-and β-globin regulation were identified.The same approach was used to generate profile-2 genes where expression was up-regulated over 28 days in culture. IPA for the 2,437 genes with > 1.5-fold induction identified the mitotic roles of polo-like kinase, aryl hydrocarbon receptor, cell cycle control, and ATM (Ataxia Telangiectasia Mutated Protein) signaling pathways; transcription factors identified included KLF1, GATA1 and NFE2 among others. Finally, profile-3 was generated from 1,579 genes with maximal expression at day 21, around the time of the γ/β-globin switch. IPA identified associations with cell cycle control, ATM, and aryl hydrocarbon receptor signaling pathways.Conclusions: The transcriptome analysis completed with erythroid progenitors grown in vitro identified groups of genes with distinct expression profiles, which function in metabolic pathways associated with cell survival, hematopoiesis, blood cells activation, and inflammatory responses. This study represents the first report of a transcriptome analysis in human primary erythroid progenitors to identify transcription factors involved in hemoglobin switching. Our results also demonstrate that the in vitro liquid culture system is an excellent model to define mechanisms of global gene expression and the DNA-binding protein and signaling pathways involved in globin gene regulation.

Publication Information

Output type

Scholary Output:
Contribution to journal
Article
Peer-review

Original language

English (US)

Article number

153

Journal (Volume, Issue Number)

BMC Genomics (Volume 13, Issue 1)

Publication milestones

  • Published - 04/26/2012

Publication status

Published - 04/26/2012

ISSN

1471-2164

Publication IDs

  • Scopus: 84860190671
  • PubMed: 22537182

Publication metrics

Metrics

SciVal
citations
15
Scopus
citations
SciVal
FWCI
0.73
SciVal
Author count
5
SciVal
Paper percentile
73
Fractional count
2
Fractional count
0.40
Fractional count
3
Fractional count
0.60
Fractional count
2
Fractional count
1

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Citation count
19
Captures
66

Funding Details

We would like to thank Dr. Hongyan Xu in the Department of Biostatistics at the Georgia Health Sciences University for review of the statistical analysis. This work was supported by grant HL069234 to Dr. Betty S. Pace. The authors would like to acknowledge the assistance of the Genomics Shared Resource at the Harold C. Simmons Cancer Center, UT Southwestern Medical Center, which is supported in part by an NCI Cancer Center Support Grant, 1P30 CA142543-01. The inclusion of trade names or commercial products in this article was solely for the purpose of providing specific information and does not imply recommendation for their products.
FundersFunding numbers
NHLBI
R01HL069234
NCI
1P30 CA142543-01