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Performance Comparison of Reverse Transcriptases for Single-Cell Studies
D. Zucha, P. Androvic, M. Kubista, L. Valihrach,
Jazyk angličtina Země Velká Británie
Typ dokumentu srovnávací studie, časopisecké články, práce podpořená grantem
NLK
ProQuest Central
od 2002-12-01 do 2022-04-30
Open Access Digital Library
od 1955-02-01
Medline Complete (EBSCOhost)
od 2010-01-01 do Před 1 rokem
Nursing & Allied Health Database (ProQuest)
od 2002-12-01 do 2022-04-30
Health & Medicine (ProQuest)
od 2002-12-01 do 2022-04-30
Public Health Database (ProQuest)
od 2002-12-01 do 2022-04-30
- MeSH
- analýza jednotlivých buněk MeSH
- DNA primery metabolismus MeSH
- kvantitativní polymerázová řetězová reakce metody MeSH
- lidé MeSH
- polymerázová řetězová reakce s reverzní transkripcí metody MeSH
- reprodukovatelnost výsledků MeSH
- reverzní transkriptasa metabolismus MeSH
- RNA metabolismus MeSH
- superoxiddismutasa 1 genetika MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- srovnávací studie MeSH
BACKGROUND: Recent advances allowing quantification of RNA from single cells are revolutionizing biology and medicine. Currently, almost all single-cell transcriptomic protocols rely on reverse transcription (RT). However, RT is recognized as a known source of variability, particularly with low amounts of RNA. Recently, several new reverse transcriptases (RTases) with the potential to decrease the loss of information have been developed, but knowledge of their performance is limited. METHODS: We compared the performance of 11 RTases in quantitative reverse transcription PCR (RT-qPCR) on single-cell and 100-cell bulk templates, using 2 priming strategies: a conventional mixture of random hexamers with oligo(dT)s and a reduced concentration of oligo(dT)s mimicking common single-cell RNA-sequencing protocols. Depending on their performance, 2 RTases were further tested in a high-throughput single-cell experiment. RESULTS: All tested RTases demonstrated high precision (R2 > 0.9445). The most pronounced differences were found in their ability to capture rare transcripts (0%-90% reaction positivity rate) and in their absolute reaction yield (7.3%-137.9%). RTase performance and reproducibility were compared with Z scores. The 2 best-performing enzymes were Maxima H- and SuperScript IV. The validity of the obtained results was confirmed in a follow-up single-cell model experiment. The better-performing enzyme (Maxima H-) increased the sensitivity of the single-cell experiment and improved resolution in the clustering analysis over the commonly used RTase (SuperScript II). CONCLUSIONS: Our comprehensive comparison of 11 RTases in low RNA input conditions identified 2 best-performing enzymes. Our results provide a point of reference for the improvement of current single-cell quantification protocols.
Citace poskytuje Crossref.org
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- $a BACKGROUND: Recent advances allowing quantification of RNA from single cells are revolutionizing biology and medicine. Currently, almost all single-cell transcriptomic protocols rely on reverse transcription (RT). However, RT is recognized as a known source of variability, particularly with low amounts of RNA. Recently, several new reverse transcriptases (RTases) with the potential to decrease the loss of information have been developed, but knowledge of their performance is limited. METHODS: We compared the performance of 11 RTases in quantitative reverse transcription PCR (RT-qPCR) on single-cell and 100-cell bulk templates, using 2 priming strategies: a conventional mixture of random hexamers with oligo(dT)s and a reduced concentration of oligo(dT)s mimicking common single-cell RNA-sequencing protocols. Depending on their performance, 2 RTases were further tested in a high-throughput single-cell experiment. RESULTS: All tested RTases demonstrated high precision (R2 > 0.9445). The most pronounced differences were found in their ability to capture rare transcripts (0%-90% reaction positivity rate) and in their absolute reaction yield (7.3%-137.9%). RTase performance and reproducibility were compared with Z scores. The 2 best-performing enzymes were Maxima H- and SuperScript IV. The validity of the obtained results was confirmed in a follow-up single-cell model experiment. The better-performing enzyme (Maxima H-) increased the sensitivity of the single-cell experiment and improved resolution in the clustering analysis over the commonly used RTase (SuperScript II). CONCLUSIONS: Our comprehensive comparison of 11 RTases in low RNA input conditions identified 2 best-performing enzymes. Our results provide a point of reference for the improvement of current single-cell quantification protocols.
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