Selection of reference genes for quantitative studies in acute myeloid leukaemia
The Malaysian Journal of Pathology
; : 313-326, 2019.
Article
in En
| WPRIM
| ID: wpr-821377
Responsible library:
WPRO
ABSTRACT
@#Introduction:
Quantitative polymerase chain reaction (qPCR) is commonly used in the investigation of acute myeloid leukaemias (AML). Stable reference genes (RG) are essential for accurate and reliable reporting but no standard method for selection has been endorsed. Materials andMethods:
We evaluated simple statistics and published model-based approaches. Multiplex-qPCR was conducted to determine the expression of 24 candidate RG in AMLs (N=9). Singleplex-qPCR was carried out on selected RG (SRP14, B2M and ATP5B) and genes of interest in AML (N=15) and healthy controls, HC (N=12).Results:
RG expression levels in AML samples were highly variable and coefficient of variance (CV) ranged from 0.37% to 10.17%. Analysis using GeNorm and Normfinder listed different orders of most stable genes but the top seven (ACTB, UBE2D2, B2M, NF45, RPL37A, GK, QARS) were the same. In singleplex-qPCR, SRP14 maintained the lowest CV in AML samples. B2M, one of most stable reference genes in AML, was expressed near significantly different in AML and HC. GeNorm selected ATP5B+SRP14 while Normfinder chose SRP14+B2M as the best two RG in combination. The median expressions of combined RG genes in AML compared to HC were less significantly different than individually implying smaller expression variation after combination. Genes of interest normalised with RG in combination or individually, displayed significantly different expression patterns.Conclusions:
The selection of best reference gene in qPCR must consider all sample sets. Model-based approaches are important in large candidate gene analysis. This study showed combination of RG SRP14+B2M was the most suitable normalisation factor for qPCR analysis of AML and healthy individuals.
Full text:
1
Database:
WPRIM
Type of study:
Prognostic_studies
Language:
En
Journal:
The Malaysian Journal of Pathology
Year:
2019
Document type:
Article