Quantification of mRNA in single cells and modelling of RT-qPCR induced noise

Martin Bengtsson¹^,2 , Martin Hemberg³^,5 , Patrik Rorsman¹ and Anders Ståhlberg⁴^,6

¹Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, The Churchill Hospital, Oxford, OX3 7LJ, UK

²Department of Clinical Sciences, Lund University, Clinical Research Centre, 205 02 Malmö, Sweden

³Department of Bioengineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK

⁴Stem Cell Center, Lund University, BMC B10, 221 84 Lund, Sweden

⁵Department of Ophthalmology and Program in Neurobiology, Children's Hospital Boston, Harvard Medical School, 1 Blackfan Circle, Boston, MA 02115, USA

⁶Department of Clinical Neuroscience and Rehabilitation, Institute of Neurosciences and Physiology, Sahlgrenska Academy at Göteborg University, Medicinaregatan 9A, 413 90 Göteborg, Sweden

author email corresponding author email

BMC Molecular Biology 2008, 9:63doi:10.1186/1471-2199-9-63


Published:	17 July 2008

Abstract

Background

Gene expression has a strong stochastic element resulting in highly variable mRNA levels between individual cells, even in a seemingly homogeneous cell population. Access to fundamental information about cellular mechanisms, such as correlated gene expression, motivates measurements of multiple genes in individual cells. Quantitative reverse transcription PCR (RT-qPCR) is the most accessible method which provides sufficiently accurate measurements of mRNA in single cells.

Results

Low concentration of guanidine thiocyanate was used to fully lyse single pancreatic β-cells followed by RT-qPCR without the need for purification. The accuracy of the measurements was determined by a quantitative noise-model of the reverse transcription and PCR. The noise is insignificant for initial copy numbers >100 while at lower copy numbers the noise intrinsic of the PCR increases sharply, eventually obscuring quantitative measurements. Importantly, the model allows us to determine the RT efficiency without using artificial RNA as a standard. The experimental setup was applied on single endocrine cells, where the technical and biological noise levels were determined.

Conclusion

Noise in single-cell RT-qPCR is insignificant compared to biological cell-to-cell variation in mRNA levels for medium and high abundance transcripts. To minimize the technical noise in single-cell RT-qPCR, the mRNA should be analyzed with a single RT reaction, and a single qPCR reaction per gene.