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Coulson DT
Brockbank S
Quinn JG
Murphy S
Ravid R
Irvine GB
Johnston JA

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Brockbank S
Quinn JG
Murphy S
Ravid R
Irvine GB
Johnston JA
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Research article

Identification of valid reference genes for the normalization of RT qPCR gene expression data in human brain tissue

David TR Coulson¹ , Simon Brockbank¹ , Joseph G Quinn¹ , Suzanne Murphy¹ , Rivka Ravid² , G Brent Irvine¹ and Janet A Johnston¹

¹Division of Psychiatry and Neuroscience, School of Medicine and Dentistry, Queen's University Belfast, Whitla Medical Building, Belfast, BT9 7BL, Northern Ireland, UK

²Netherlands Brain Bank, Amsterdam, The Netherlands

author email corresponding author email

BMC Molecular Biology 2008, 9:46doi:10.1186/1471-2199-9-46


Published:	6 May 2008

Additional files

Additional file 1:

RT qPCR Efficiency Plots Mean cycle threshold (C_t) values for each dilution were plotted against the log₁₀of the cDNA input for each gene to generate efficiency plots. The reaction efficiency for each gene assay was calculated using the following equation: E = 10^(-1/slope)where E is the reaction efficiency and 'slope' is the slope of the line generated in the efficiency plots.

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Additional file 2:

Stability of candidate reference genes in medial temporal gyrus. Expression stability plot showing the average expression stability (M) for the remaining genes following the sequential elimination of the least stable gene at each round in the medial temporal gyrus of control and PD subjects (A), and control and DLB subjects (B). Least stable (left) and the two most stable (right).

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Additional file 3:

Pairwise variation of the candidate reference genes in medial temporal gyrus. Pairwise variation analysis to determine the optimal number of reference genes for use in RT qPCR data normalization from cerebellum of control and PD subjects (A), and control and DLB subjects (B). To determine the optimal number of genes required for geometric mean normalization, geNorm calculates the pairwise variation (V_n/V_n+1) between sequential normalization factors (NF) (NF_nand NF_n+1). A large variation indicates that the gene included at that stage has a significant effect and should therefore be included for normalization.

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Additional file 4:

Stability of candidate reference genes in cerebellum. Expression stability plot showing the average expression stability (M) for the remaining genes following the sequential elimination of the least stable gene at each round in cerebellum of control and AD subjects (A), control and PD subjects (B), and control and DLB subjects (C). Least stable (left) and the two most stable (right).

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Additional file 5:

Pairwise variation of the candidate reference genes in cerebellum. Pairwise variation analysis to determine the optimal number of reference genes for use in RT qPCR data normalization from cerebellum of control and AD subjects (A), control and PD subjects (B), and control and DLB subjects (C). To determine the optimal number of genes required for geometric mean normalization, geNorm calculates the pairwise variation (V_n/V_n+1) between sequential normalization factors (NF) (NF_nand NF_n+1). A large variation indicates that the gene included at that stage has a significant effect and should therefore be included for normalization.

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Additional file 6:

Stability of candidate reference genes in cerebellum and medial temporal gyrus. Expression stability plot showing the average expression stability (M) for the remaining genes following the sequential elimination of the least stable gene at each round in cerebellum and medial temporal gyrus of control and AD subjects (A), control and PD subjects (B), and control and DLB subjects (C). Least stable (left) and the two most stable (right).

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Additional file 7:

Pairwise variation of the candidate reference genes in cerebellum and medial temporal gyrus. Pairwise variation analysis to determine the optimal number of reference genes for use in RT qPCR data normalization from cerebellum of control and AD subjects (A), control and PD subjects (B), and control and DLB subjects (C). To determine the optimal number of genes required for geometric mean normalization, geNorm calculates the pairwise variation (V_n/V_n+1) between sequential normalization factors (NF) (NF_nand NF_n+1). A large variation indicates that the gene included at that stage has a significant effect and should therefore be included for normalization.

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Additional file 8:

Stable Reference Genes as Determined by NormFinder. The expression data for each of the candidate reference genes was analysed using the Excel based application 'NormFinder'.

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