Molecular mechanisms of RNA polymerase II transcription elongation elucidated by kinetic network models

Ilona Christy Unarta; Lizhe Zhu; Carmen Ka Man Tse; Peter Pak-Hang Cheung; Jin Yu; Xuhui Huang

doi:10.1016/j.sbi.2018.01.002

Molecular mechanisms of RNA polymerase II transcription elongation elucidated by kinetic network models

Ilona Christy Unarta, Lizhe Zhu, Carmen Ka Man Tse, Peter Pak-Hang Cheung, Jin Yu, Xuhui Huang

Research output: Contribution to journal › Article › peer-review

22 Scopus citations

Abstract

Transcription elongation cycle (TEC) of RNA polymerase II (Pol II) is a process of adding a nucleoside triphosphate to the growing messenger RNA chain. Due to the long timescale events in Pol II TEC, an advanced computational technique, such as Markov State Model (MSM), is needed to provide atomistic mechanism and reaction rates. The combination of MSM and experimental results can be used to build a kinetic network model (KNM) of the whole TEC. This review provides a brief protocol to build MSM and KNM of the whole TEC, along with the latest findings of MSM and other computational studies of Pol II TEC. Lastly, we offer a perspective on potentially using a sequence dependent KNM to predict genome-wide transcription error.

Original language	English (US)
Pages (from-to)	54-62
Number of pages	9
Journal	Current Opinion in Structural Biology
Volume	49
DOIs	https://doi.org/10.1016/j.sbi.2018.01.002
State	Published - Apr 2018
Externally published	Yes

Bibliographical note

KAUST Repository Item: Exported on 2021-04-06
Acknowledged KAUST grant number(s): OSR-2016-CRG5-3007
Acknowledgements: This work was supported by the Hong Kong Research Grant Council (HKUST C6009-15G, 16305817, 16302214, 16304215, 16318816, AoE/P-705/16, M-HKUST601/13, and T13-607/12R), King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) (OSR-2016-CRG5-3007), Shenzhen Science and Technology Innovation Committee (JCYJ20170413173837121), Innovation and Technology Commission (ITCPD/17-9 and ITC-CNERC14SC01), and National Natural Science Foundation of China (11275022, 11635002). XH is the Padma Harilela Associate Professor of Science.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

ASJC Scopus subject areas

Structural Biology
Molecular Biology

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10.1016/j.sbi.2018.01.002

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title = "Molecular mechanisms of RNA polymerase II transcription elongation elucidated by kinetic network models",

abstract = "Transcription elongation cycle (TEC) of RNA polymerase II (Pol II) is a process of adding a nucleoside triphosphate to the growing messenger RNA chain. Due to the long timescale events in Pol II TEC, an advanced computational technique, such as Markov State Model (MSM), is needed to provide atomistic mechanism and reaction rates. The combination of MSM and experimental results can be used to build a kinetic network model (KNM) of the whole TEC. This review provides a brief protocol to build MSM and KNM of the whole TEC, along with the latest findings of MSM and other computational studies of Pol II TEC. Lastly, we offer a perspective on potentially using a sequence dependent KNM to predict genome-wide transcription error.",

author = "Unarta, {Ilona Christy} and Lizhe Zhu and Tse, {Carmen Ka Man} and Cheung, {Peter Pak-Hang} and Jin Yu and Xuhui Huang",

note = "KAUST Repository Item: Exported on 2021-04-06 Acknowledged KAUST grant number(s): OSR-2016-CRG5-3007 Acknowledgements: This work was supported by the Hong Kong Research Grant Council (HKUST C6009-15G, 16305817, 16302214, 16304215, 16318816, AoE/P-705/16, M-HKUST601/13, and T13-607/12R), King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) (OSR-2016-CRG5-3007), Shenzhen Science and Technology Innovation Committee (JCYJ20170413173837121), Innovation and Technology Commission (ITCPD/17-9 and ITC-CNERC14SC01), and National Natural Science Foundation of China (11275022, 11635002). XH is the Padma Harilela Associate Professor of Science. This publication acknowledges KAUST support, but has no KAUST affiliated authors.",

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doi = "10.1016/j.sbi.2018.01.002",

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AU - Zhu, Lizhe

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AU - Yu, Jin

AU - Huang, Xuhui

N1 - KAUST Repository Item: Exported on 2021-04-06 Acknowledged KAUST grant number(s): OSR-2016-CRG5-3007 Acknowledgements: This work was supported by the Hong Kong Research Grant Council (HKUST C6009-15G, 16305817, 16302214, 16304215, 16318816, AoE/P-705/16, M-HKUST601/13, and T13-607/12R), King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) (OSR-2016-CRG5-3007), Shenzhen Science and Technology Innovation Committee (JCYJ20170413173837121), Innovation and Technology Commission (ITCPD/17-9 and ITC-CNERC14SC01), and National Natural Science Foundation of China (11275022, 11635002). XH is the Padma Harilela Associate Professor of Science. This publication acknowledges KAUST support, but has no KAUST affiliated authors.

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N2 - Transcription elongation cycle (TEC) of RNA polymerase II (Pol II) is a process of adding a nucleoside triphosphate to the growing messenger RNA chain. Due to the long timescale events in Pol II TEC, an advanced computational technique, such as Markov State Model (MSM), is needed to provide atomistic mechanism and reaction rates. The combination of MSM and experimental results can be used to build a kinetic network model (KNM) of the whole TEC. This review provides a brief protocol to build MSM and KNM of the whole TEC, along with the latest findings of MSM and other computational studies of Pol II TEC. Lastly, we offer a perspective on potentially using a sequence dependent KNM to predict genome-wide transcription error.

AB - Transcription elongation cycle (TEC) of RNA polymerase II (Pol II) is a process of adding a nucleoside triphosphate to the growing messenger RNA chain. Due to the long timescale events in Pol II TEC, an advanced computational technique, such as Markov State Model (MSM), is needed to provide atomistic mechanism and reaction rates. The combination of MSM and experimental results can be used to build a kinetic network model (KNM) of the whole TEC. This review provides a brief protocol to build MSM and KNM of the whole TEC, along with the latest findings of MSM and other computational studies of Pol II TEC. Lastly, we offer a perspective on potentially using a sequence dependent KNM to predict genome-wide transcription error.

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JO - Current Opinion in Structural Biology

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ER -

Molecular mechanisms of RNA polymerase II transcription elongation elucidated by kinetic network models

Abstract

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