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      Effect of the LSD1 inhibitor RN-1 on γ-globin and global gene expression during erythroid differentiation in baboons ( Papio anubis)

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          Abstract

          Elevated levels of Fetal Hemoglobin interfere with polymerization of sickle hemoglobin thereby reducing anemia, lessening the severity of symptoms, and increasing life span of patients with sickle cell disease. An affordable, small molecule drug that stimulates HbF expression in vivo would be ideally suited to treat the large numbers of SCD patients that exist worldwide. Our previous work showed that administration of the LSD1 (KDM1A) inhibitor RN-1 to normal baboons increased Fetal Hemoglobin (HbF) and was tolerated over a prolonged treatment period. HbF elevations were associated with changes in epigenetic modifications that included increased levels of H3K4 di-and tri-methyl lysine at the γ-globin promoter. While dramatic effects of the loss of LSD1 on hematopoietic differentiation have been observed in murine LSD1 gene deletion and silencing models, the effect of pharmacological inhibition of LSD1 in vivo on hematopoietic differentiation is unknown. The goal of these experiments was to investigate the in vivo mechanism of action of the LSD1 inhibitor RN-1 by determining its effect on γ-globin expression in highly purified subpopulations of bone marrow erythroid cells enriched for varying stages of erythroid differentiation isolated directly from baboons treated with RN-1 and also by investigating the effect of RN1 on the global transcriptome in a highly purified population of proerythroblasts. Our results show that RN-1 administered to baboons targets an early event during erythroid differentiation responsible for γ-globin repression and increases the expression of a limited number of genes including genes involved in erythroid differentiation such as GATA2, GFi-1B, and LYN.

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          Most cited references58

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

            Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au
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              featureCounts: an efficient general purpose program for assigning sequence reads to genomic features.

              Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.
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                Author and article information

                Contributors
                Role: InvestigationRole: MethodologyRole: Writing – original draft
                Role: InvestigationRole: Methodology
                Role: InvestigationRole: Methodology
                Role: Data curationRole: Formal analysisRole: Methodology
                Role: Data curationRole: MethodologyRole: Resources
                Role: MethodologyRole: Resources
                Role: ConceptualizationRole: InvestigationRole: SupervisionRole: Writing – original draft
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLOS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                22 December 2023
                2023
                : 18
                : 12
                : e0289860
                Affiliations
                [1 ] Department of Medicine, University of Illinois at Chicago, Chicago, Illinois, United States of America
                [2 ] Jesse Brown VA Medical Center, Chicago, Illinois, United States of America
                [3 ] Research Informatics Core, University of Illinois at Chicago, Chicago, Illinois, United States of America
                [4 ] Ambry Genetics, Aliso Viejo, California, United States of America
                [5 ] Genomics Research Core, University of Illinois at Chicago, Chicago, Illinois, United States of America
                University of East Anglia, UNITED KINGDOM
                Author notes

                Competing Interests: The authors have declared no competing interests exist.

                Author information
                https://orcid.org/0000-0002-0275-7168
                Article
                PONE-D-23-23656
                10.1371/journal.pone.0289860
                10745162
                38134183
                ec7a4a0e-fadd-4be1-8148-98a46f04fc8b

                This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                History
                : 8 August 2023
                : 4 December 2023
                Page count
                Figures: 6, Tables: 0, Pages: 16
                Funding
                Funded by: NHLBI
                Award ID: HL P01 146372
                Award Recipient :
                Funded by: NCATS
                Award ID: UL1TR002003
                Award Recipient :
                DL (UIC site PI) JD Engel (overall PI) HL P01 146372 NHLBI MMC UL1TR002003 NCATS The sponsors had no role in study design, data collection, decision to publish, or manuscript preparation.
                Categories
                Research Article
                Biology and life sciences
                Organisms
                Eukaryota
                Animals
                Vertebrates
                Amniotes
                Mammals
                Primates
                Monkeys
                Old World monkeys
                Baboons
                Biology and life sciences
                Zoology
                Animals
                Vertebrates
                Amniotes
                Mammals
                Primates
                Monkeys
                Old World monkeys
                Baboons
                Biology and Life Sciences
                Genetics
                Gene Expression
                Biology and Life Sciences
                Developmental Biology
                Cell Differentiation
                Biology and Life Sciences
                Physiology
                Immune Physiology
                Bone Marrow
                Biology and Life Sciences
                Immunology
                Immune System
                Bone Marrow
                Medicine and Health Sciences
                Immunology
                Immune System
                Bone Marrow
                Biology and Life Sciences
                Cell Biology
                Cellular Types
                Animal Cells
                Bone Marrow Cells
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Vertebrates
                Amniotes
                Mammals
                Primates
                Biology and Life Sciences
                Zoology
                Animals
                Vertebrates
                Amniotes
                Mammals
                Primates
                Biology and life sciences
                Cell biology
                Chromosome biology
                Chromatin
                Chromatin modification
                DNA methylation
                Biology and life sciences
                Genetics
                Epigenetics
                Chromatin
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                DNA methylation
                Biology and life sciences
                Genetics
                Gene expression
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                Biology and life sciences
                Genetics
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                Biology and life sciences
                Biochemistry
                Nucleic acids
                DNA
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                Biology and life sciences
                Genetics
                Epigenetics
                DNA modification
                DNA methylation
                Biology and life sciences
                Genetics
                Gene expression
                DNA modification
                DNA methylation
                Biology and Life Sciences
                Cell Biology
                Cellular Types
                Animal Cells
                Bone Marrow Cells
                Erythroblasts
                Biology and Life Sciences
                Cell Biology
                Cellular Types
                Animal Cells
                Blood Cells
                Red Blood Cells
                Erythroblasts
                Custom metadata
                The RNA sequence data has been deposited in the GEO database with an assigned accession number of GSE235633. All other data are contained within the paper.

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