TY - JOUR
T1 - Two DNA-encoded strategies for increasing expression with opposing effects on promoter dynamics and transcriptional noise
AU - Dadiani, Maya
AU - Van Dijk, Dijk, David
AU - Segal, Barak
AU - Field, Yair
AU - Ben Artzi, Artzi, Gil
AU - Raveh - Sadka, - Sadka, Tali
AU - Levo, Michal
AU - Kaplow, Irene
AU - Weinberger, Adina
AU - Segal, Eran
N1 - European Research Council (ERC); U.S. National Institutes of Health (NIH); FP7 FET Open project "DynaNets'' (EU) [233847]; FP7 FET Open project "ViroLab'' (EU) [IST-027446]; EMBO Short-Term Fellowship; BioRange program of the Netherlands Bioinformatics Centre (NBIC); Netherlands Genomics Initiative (NGI)This work was supported by grants from the European Research Council (ERC) and the U.S. National Institutes of Health (NIH) to E.S. E.S. is the incumbent of the Soretta and Henry Shapiro Career Development Chair. D.D. was supported by FP7 FET Open project "DynaNets'' (EU Grant Agreement no. 233847), "ViroLab'' (EU project no. IST-027446), and by an EMBO Short-Term Fellowship and a travel grant from the BioRange program of the Netherlands Bioinformatics Centre (NBIC) and Netherlands Genomics Initiative (NGI). We thank Ilya Soifer and Gil Hornung from Naama Barkai's laboratory for their assistance.
PY - 2013/6
Y1 - 2013/6
N2 - Individual cells from a genetically identical population exhibit substantial variation in gene expression. A significant part of this variation is due to noise in the process of transcription that is intrinsic to each gene, and is determined by factors such as the rate with which the promoter transitions between transcriptionally active and inactive states, and the number of transcripts produced during the active state. However, we have a limited understanding of how the DNA sequence affects such promoter dynamics. Here, we used single-cell time-lapse microscopy to compare the effect on transcriptional dynamics of two distinct types of sequence changes in the promoter that can each increase the mean expression of a cell population by similar amounts but through different mechanisms. We show that increasing expression by strengthening a transcription factor binding site results in slower promoter dynamics and higher noise as compared with increasing expression by adding nucleosome-disfavoring sequences. Our results suggest that when achieving the same mean expression, the strategy of using stronger binding sites results in a larger number of transcripts produced from the active state, whereas the strategy of adding nucleosome-disfavoring sequences results in a higher frequency of promoter transitions between active and inactive states. In the latter strategy, this increased sampling of the active state likely reduces the expression variability of the cell population. Our study thus demonstrates the effect of cis-regulatory elements on expression variability and points to concrete types of sequence changes that may allow partial decoupling of expression level and noise.
AB - Individual cells from a genetically identical population exhibit substantial variation in gene expression. A significant part of this variation is due to noise in the process of transcription that is intrinsic to each gene, and is determined by factors such as the rate with which the promoter transitions between transcriptionally active and inactive states, and the number of transcripts produced during the active state. However, we have a limited understanding of how the DNA sequence affects such promoter dynamics. Here, we used single-cell time-lapse microscopy to compare the effect on transcriptional dynamics of two distinct types of sequence changes in the promoter that can each increase the mean expression of a cell population by similar amounts but through different mechanisms. We show that increasing expression by strengthening a transcription factor binding site results in slower promoter dynamics and higher noise as compared with increasing expression by adding nucleosome-disfavoring sequences. Our results suggest that when achieving the same mean expression, the strategy of using stronger binding sites results in a larger number of transcripts produced from the active state, whereas the strategy of adding nucleosome-disfavoring sequences results in a higher frequency of promoter transitions between active and inactive states. In the latter strategy, this increased sampling of the active state likely reduces the expression variability of the cell population. Our study thus demonstrates the effect of cis-regulatory elements on expression variability and points to concrete types of sequence changes that may allow partial decoupling of expression level and noise.
UR - http://www.scopus.com/inward/record.url?scp=84875214621&partnerID=8YFLogxK
U2 - https://doi.org/10.1101/gr.149096.112
DO - https://doi.org/10.1101/gr.149096.112
M3 - مقالة
C2 - 23403035
SN - 1088-9051
VL - 23
SP - 966
EP - 976
JO - Genome Research
JF - Genome Research
IS - 6
ER -