Selecting control genes for RT-QPCR using public microarray
data

J 2009

Selecting control genes for RT-QPCR using public microarray data

POPOVICI, Vlad; Darlene R GOLDSTEIN; Janine ANTONOV; Rolf JAGGI; Mauro DELORENZI et al.

Základní údaje

Originální název

Selecting control genes for RT-QPCR using public microarray data

Autoři

POPOVICI, Vlad; Darlene R GOLDSTEIN; Janine ANTONOV; Rolf JAGGI; Mauro DELORENZI a Pratyaksha WIRAPATI

Vydání

BMC Bioinformatics, LONDON, BioMed Central, 2009, 1471-2105

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Utajení

není předmětem státního či obchodního tajemství

Impakt faktor

Impact factor: 3.428

Označené pro přenos do RIV

DOI

https://doi.org/10.1186/1471-2105-10-42

UT WoS

000264007300001

Změněno: 4. 3. 2013 15:29, doc. Ing. Vlad Popovici, PhD

Anotace

V originále

Background: Gene expression analysis has emerged as a major biological research area, with real-time quantitative reverse transcription PCR (RT-QPCR) being one of the most accurate and widely used techniques for expression profiling of selected genes. In order to obtain results that are comparable across assays, a stable normalization strategy is required. In general, the normalization of PCR measurements between different samples uses one to several control genes (e. g. housekeeping genes), from which a baseline reference level is constructed. Thus, the choice of the control genes is of utmost importance, yet there is not a generally accepted standard technique for screening a large number of candidates and identifying the best ones. Results: We propose a novel approach for scoring and ranking candidate genes for their suitability as control genes. Our approach relies on publicly available microarray data and allows the combination of multiple data sets originating from different platforms and/or representing different pathologies. The use of microarray data allows the screening of tens of thousands of genes, producing very comprehensive lists of candidates. We also provide two lists of candidate control genes: one which is breast cancer-specific and one with more general applicability. Two genes from the breast cancer list which had not been previously used as control genes are identified and validated by RT-QPCR. Open source R functions are available at http://www.isrec.isb-sib.ch/similar to vpopovic/research/ Conclusion: We proposed a new method for identifying candidate control genes for RT-QPCR which was able to rank thousands of genes according to some predefined suitability criteria and we applied it to the case of breast cancer. We also empirically showed that translating the results from microarray to PCR platform was achievable.

Citovat

POPOVICI, Vlad; Darlene R GOLDSTEIN; Janine ANTONOV; Rolf JAGGI; Mauro DELORENZI a Pratyaksha WIRAPATI. Selecting control genes for RT-QPCR using public microarray data. BMC Bioinformatics. LONDON: BioMed Central, 2009, roč. 10, 10 s. ISSN 1471-2105. Dostupné z: https://doi.org/10.1186/1471-2105-10-42.

@article{1090312,
   author = {Popovici, Vlad and Goldstein, Darlene R and Antonov, Janine and Jaggi, Rolf and Delorenzi, Mauro and Wirapati, Pratyaksha},
   article_location = {LONDON},
   doi = {https://doi.org/10.1186/1471-2105-10-42},
   language = {eng},
   issn = {1471-2105},
   journal = {BMC Bioinformatics},
   title = {Selecting control genes for RT-QPCR using public microarray data},
   volume = {10},
   year = {2009}
}

TY  - JOUR
ID  - 1090312
AU  - Popovici, Vlad - Goldstein, Darlene R - Antonov, Janine - Jaggi, Rolf - Delorenzi, Mauro - Wirapati, Pratyaksha
PY  - 2009
TI  - Selecting control genes for RT-QPCR using public microarray data
JF  - BMC Bioinformatics
VL  - 10
PB  - BioMed Central
SN  - 14712105
N2  - Background: Gene expression analysis has emerged as a major biological research area, with real-time quantitative reverse transcription PCR (RT-QPCR) being one of the most accurate and widely used techniques for expression profiling of selected genes. In order to obtain results that are comparable across assays, a stable normalization strategy is required. In general, the normalization of PCR measurements between different samples uses one to several control genes (e. g. housekeeping genes), from which a baseline reference level is constructed. Thus, the choice of the control genes is of utmost importance, yet there is not a generally accepted standard technique for screening a large number of candidates and identifying the best ones. Results: We propose a novel approach for scoring and ranking candidate genes for their suitability as control genes. Our approach relies on publicly available microarray data and allows the combination of multiple data sets originating from different platforms and/or representing different pathologies. The use of microarray data allows the screening of tens of thousands of genes, producing very comprehensive lists of candidates. We also provide two lists of candidate control genes: one which is breast cancer-specific and one with more general applicability. Two genes from the breast cancer list which had not been previously used as control genes are identified and validated by RT-QPCR. Open source R functions are available at http://www.isrec.isb-sib.ch/similar to vpopovic/research/ Conclusion: We proposed a new method for identifying candidate control genes for RT-QPCR which was able to rank thousands of genes according to some predefined suitability criteria and we applied it to the case of breast cancer. We also empirically showed that translating the results from microarray to PCR platform was achievable.
ER  -

POPOVICI, Vlad; Darlene R GOLDSTEIN; Janine ANTONOV; Rolf JAGGI; Mauro DELORENZI a Pratyaksha WIRAPATI. Selecting control genes for RT-QPCR using public microarray data. \textit{BMC Bioinformatics}. LONDON: BioMed Central, 2009, roč.~10, 10 s. ISSN~1471-2105. Dostupné z: https://doi.org/10.1186/1471-2105-10-42.

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