title: Quantification of mRNA in single cells and modelling of RT-qPCR induced noise.
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 beta-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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, The Churchill Hospital, Oxford, OX3 7LJ, UK. martin.bengtsson@med.lu.se
authors.forename: Martin
authors.initials: M
authors.lastname: Bengtsson
authors.forename: Martin
authors.initials: M
authors.lastname: Hemberg
authors.forename: Patrik
authors.initials: P
authors.lastname: Rorsman
authors.forename: Anders
authors.initials: A
authors.lastname: Ståhlberg
mesh_terms: D000818:Animals; D016477:Artifacts; D002478:Cells, Cultured; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods*; D050417:Insulin-Secreting Cells / Q000378:metabolism*; D051379:Mice; D008954:Models, Biological; D011506:Proteins / Q000235:genetics; D012333:RNA, Messenger / Q000032:analysis* / Q000235:genetics; D020133:Reverse Transcriptase Polymerase Chain Reaction / Q000379:methods* / Q000592:standards
chemical_list: D011506:Proteins; D012333:RNA, Messenger