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Iron metabolism rt2 profiler array

Manufactured by Qiagen

The Iron metabolism RT2 profiler array is a laboratory research tool designed to analyze the expression of genes involved in iron metabolism. It provides a comprehensive assessment of multiple genes associated with iron homeostasis and transport processes.

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2 protocols using iron metabolism rt2 profiler array

1

Comprehensive Iron Metabolism Gene Expression Analysis

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Total RNA was isolated from samples using TRIzol Reagent (ThermoFisher Scientific). cDNA synthesis was done using RT2 First Strand Kit (Qiagen). The Qiagen iron metabolism RT2 profiler array was custom built (Cat. number CLAM25204D) and used with RT2 SYBR Green Fluor qPCR mastermix (Qiagen) on a CFX Connect system (Bio-rad). Analysis of gene expression data was conducted using the online data analysis web portal provided by Qiagen. Briefly, Ct values for each gene in each group (eg. WT, Standard diet) were obtained by taking the average across all mice (n = 9 per group). ΔCt values were then obtained by the following formula: ΔCt = Ct (target gene) – Ct (housekeeping gene). The housekeeping gene used was RPL13a. Gene expression was then calculated by the formula 2^ (- ΔCt). p values for gene expression were calculated using ΔCt values, the corresponding standard deviations and n = 9. The gene expression heatmap was generated by the Heatmapper software and clustering was performed using Pearson’s distance measurement method with average clustering (Babicki et al., 2016 (link)).
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2

Profiling Iron Metabolism Genes

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Total RNA was isolated from samples using TRIzol Reagent (ThermoFisher Scientific). cDNA synthesis was done using RT2 First Strand Kit (Qiagen). The Qiagen iron metabolism RT2 profiler array was custom built (Cat. number CLAM25204D) and used with RT2 SYBR Green Fluor qPCR mastermix (Qiagen) on a CFX Connect system (Bio-rad). Analysis of gene expression data was conducted using the online data analysis web portal provided by Qiagen. Briefly, Ct values for each gene in each group (eg. WT, Standard diet) were obtained by taking the average across all mice (n = 9 per group). ΔCt values were then obtained by the following formula: ΔCt = Ct (target gene) – Ct (housekeeping gene). The housekeeping gene used was RPL13a. Gene expression was then calculated by the formula 2^ (- ΔCt). p values for gene expression were calculated using ΔCt values, the corresponding standard deviations and n = 9. The gene expression heatmap was generated by the Heatmapper software and clustering was performed using Pearson’s distance measurement method with average clustering (Babicki et al., 2016 (link)).
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