GSE162493: Cardiac transcriptome in iron-deficiency anemia

Gene Expression Data Explorer
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GROUP CONDITION SAMPLES
Cardiac tissue
GSM4952876 GSM4952877 GSM4952878 GSM4952879 GSM4952880 GSM4952881 GSM4952882 GSM4952883 GSM4952884 GSM4952885
GSM4952886 GSM4952887 GSM4952888 GSM4952889 GSM4952890 GSM4952891 GSM4952892 GSM4952893 GSM4952894 GSM4952895
Description

Submission Date: Dec 02, 2020

Summary: Purpose: The goal of this study was to probe for the effects of iron-deficiency anemia on the cardiac transciprtome using RNA-seq

Methods: C57B6 mice were weaned onto a control or iron-deficient diet for 6 weeks. Hearts were removed and total mRNA was submitted for RNA-seq. Sequencing data was aligned using STAR and differetial gene expression analysis conducted in R using EdgeR and DESeq2. qRT–PCR validation for genes of interest was performed using TaqMan and SYBR Green assays.

Results: We mapped about 24 million sequence reads per sample to the mouse genome (build mm10) and identified 13,590 transcripts in the hearts of control and iron-deficient mice after removing lowly expressed genes and PCR duplicates. Differential gene expression analysis showed approximately 78% downregulated and 22% upregulated genes in iron-deficiency anemia compared to controls. PCA plot showed control and iron-deficient hearts clustering in two distinct and separate clusters.

Conclusions: Our study represents the first whole-transcriptomic study on cardiac samples obtained from iron-deficient and anemic mice, with biologic replicates, generated by RNA-seq technology. The RNA-seq data presented here can be used by others to explore which pathways are affected by iron-deficiency anemia

GEO Accession ID: GSE162493

PMID: 33553263

Description

Submission Date: Dec 02, 2020

Summary: Purpose: The goal of this study was to probe for the effects of iron-deficiency anemia on the cardiac transciprtome using RNA-seq

Methods: C57B6 mice were weaned onto a control or iron-deficient diet for 6 weeks. Hearts were removed and total mRNA was submitted for RNA-seq. Sequencing data was aligned using STAR and differetial gene expression analysis conducted in R using EdgeR and DESeq2. qRT–PCR validation for genes of interest was performed using TaqMan and SYBR Green assays.

Results: We mapped about 24 million sequence reads per sample to the mouse genome (build mm10) and identified 13,590 transcripts in the hearts of control and iron-deficient mice after removing lowly expressed genes and PCR duplicates. Differential gene expression analysis showed approximately 78% downregulated and 22% upregulated genes in iron-deficiency anemia compared to controls. PCA plot showed control and iron-deficient hearts clustering in two distinct and separate clusters.

Conclusions: Our study represents the first whole-transcriptomic study on cardiac samples obtained from iron-deficient and anemic mice, with biologic replicates, generated by RNA-seq technology. The RNA-seq data presented here can be used by others to explore which pathways are affected by iron-deficiency anemia

GEO Accession ID: GSE162493

PMID: 33553263

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Differential Gene Expression Analysis
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Bulk RNA-seq Appyter

This pipeline enables you to analyze and visualize your bulk RNA sequencing datasets with an array of downstream analysis and visualization tools. The pipeline includes: PCA analysis, Clustergrammer interactive heatmap, library size analysis, differential gene expression analysis, enrichment analysis, and L1000 small molecule search.