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      Exposure to hypoxia causes stress erythropoiesis and downregulates immune response genes in spleen of mice

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          Abstract

          Background

          The spleen is the largest secondary lymphoid organ and the main site where stress erythropoiesis occurs. It is known that hypoxia triggers the expansion of erythroid progenitors; however, its effects on splenic gene expression are still unclear. Here, we examined splenic global gene expression patterns by time-series RNA-seq after exposing mice to hypoxia for 0, 1, 3, 5, 7 and 13 days.

          Results

          Morphological analysis showed that on the 3rd day there was a significant increase in the spleen index and in the proliferation of erythroid progenitors. RNA-sequencing analysis revealed that the overall expression of genes decreased with increased hypoxic exposure. Compared with the control group, 1380, 3430, 4396, 3026, and 1636 genes were differentially expressed on days 1, 3, 5, 7 and 13, respectively. Clustering analysis of the intersection of differentially expressed genes pointed to 739 genes, 628 of which were upregulated, and GO analysis revealed a significant enrichment for cell proliferation. Enriched GO terms of downregulated genes were associated with immune cell activation. Expression of Gata1, Tal1 and Klf1 was significantly altered during stress erythropoiesis. Furthermore, expression of genes involved in the immune response was inhibited, and NK cells decreased.

          Conclusions

          The spleen of mice conquer hypoxia exposure in two ways. Stress erythropoiesis regulated by three transcription factors and genes in immune response were downregulated. These findings expand our knowledge of splenic transcriptional changes during hypoxia.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12864-021-07731-x.

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          Most cited references73

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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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                Author and article information

                Contributors
                zhangtz@nwipb.cas.cn
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                5 June 2021
                5 June 2021
                2021
                : 22
                : 413
                Affiliations
                [1 ]GRID grid.9227.e, ISNI 0000000119573309, Key Laboratory of Adaptation and Evolution of Plateau Biota, , Northwest Institute of Plateau Biology, Chinese Academy of Sciences, ; Xining, 810001 Qinghai China
                [2 ]GRID grid.262246.6, ISNI 0000 0004 1765 430X, Medical College of Qinghai University, ; Xining, 810016 Qinghai China
                [3 ]Qinghai Provincial Key Laboratory of Animal Ecological Genomics, Xining, 810008 Qinghai China
                [4 ]GRID grid.410726.6, ISNI 0000 0004 1797 8419, University of Chinese Academy of Sciences, ; Beijing, 100049 China
                Article
                7731
                10.1186/s12864-021-07731-x
                8178839
                34090336
                b99651c7-b749-4268-83cf-aa070d905fb3
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 19 February 2021
                : 21 May 2021
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                Genetics
                transcriptome,spleen,stress erythropoiesis,immune response,hypoxia
                Genetics
                transcriptome, spleen, stress erythropoiesis, immune response, hypoxia

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