TY - JOUR
T1 - Evaluating dynamic effects of copy number alterations on gene expression using a single transcription model
AU - Hsu, Fang Han
AU - Serpedin, Erchin
AU - Chen, Yidong
AU - Dougherty, Edward R.
N1 - Funding Information:
Manuscript received March 14, 2012; revised May 28, 2012; accepted July 5, 2012. Date of publication July 13, 2012; date of current version September 14, 2012. This work was supported by the National Science Foundation under Grant 0915444. Asterisk indicates corresponding author.
PY - 2012
Y1 - 2012
N2 - DNA copy number alterations (CNAs) are known to be related to genetic diseases, including cancer. The unlimited transcription (UT) model, in which transcription occurs permissively with a simple activation probability, has been proposed to investigate long-term effects of CNAs on gene expression values. Queueing theory was applied, and the copy-number-gene-expression relationship has been shown to be generally nonlinear in the UT model. However, the dynamic effects of CNAs on transcription and the underlying disorders related to diseases remain greatly unknown. Since most genes in a single cell are permissively transcribed in short periods of time interspersed by long periods of limited transcription, an alternative model for transcription in the restrictive state is needed for unraveling the effects of CNAs on gene expression levels with time. To address these issues, herein a single transcription (ST) model is proposed, in which bound TFs are assumed to be unloaded immediately after stimulating a transcription. Using the Laplace-Stieltjes transform and numerical analysis, the relationship between DNA copy number and gene expression level is evaluated. Dynamic modeling reveals that CNAs would potentially alter, or even reverse, the burst-like gene expression modifications while shifting from the ST model to the UT model. Moreover, functional disorders in transcriptional oscillation due to CNAs are shown via simulation. This paper demonstrates how mathematical theories could be helpful to interpret statistical findings from real data and achieve a better understanding of cancer biology.
AB - DNA copy number alterations (CNAs) are known to be related to genetic diseases, including cancer. The unlimited transcription (UT) model, in which transcription occurs permissively with a simple activation probability, has been proposed to investigate long-term effects of CNAs on gene expression values. Queueing theory was applied, and the copy-number-gene-expression relationship has been shown to be generally nonlinear in the UT model. However, the dynamic effects of CNAs on transcription and the underlying disorders related to diseases remain greatly unknown. Since most genes in a single cell are permissively transcribed in short periods of time interspersed by long periods of limited transcription, an alternative model for transcription in the restrictive state is needed for unraveling the effects of CNAs on gene expression levels with time. To address these issues, herein a single transcription (ST) model is proposed, in which bound TFs are assumed to be unloaded immediately after stimulating a transcription. Using the Laplace-Stieltjes transform and numerical analysis, the relationship between DNA copy number and gene expression level is evaluated. Dynamic modeling reveals that CNAs would potentially alter, or even reverse, the burst-like gene expression modifications while shifting from the ST model to the UT model. Moreover, functional disorders in transcriptional oscillation due to CNAs are shown via simulation. This paper demonstrates how mathematical theories could be helpful to interpret statistical findings from real data and achieve a better understanding of cancer biology.
KW - DNA copy number
KW - gene expression
KW - queueing theory
KW - transcriptional bursting
KW - transcriptional oscillation
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U2 - 10.1109/TBME.2012.2208749
DO - 10.1109/TBME.2012.2208749
M3 - Article
C2 - 22996722
AN - SCOPUS:84866526721
SN - 0018-9294
VL - 59
SP - 2726
EP - 2736
JO - IEEE Transactions on Biomedical Engineering
JF - IEEE Transactions on Biomedical Engineering
IS - 10
M1 - 8
ER -