Data supporting a saturation mutagenesis assay for Tat-driven transcription with the GigaAssay

Ronald Benjamin; Christopher J. Giacoletto; Zachary T. FitzHugh; Danielle Eames; Lindsay Buczek; Xiaogang Wu; Jacklyn Newsome; Mira V. Han; Tony Pearson; Zhi Wei; Atoshi Banerjee; Lancer Brown; Liz J. Valente; Shirley Shen; Hong Wen Deng; Martin R. Schiller

doi:10.1016/j.dib.2022.108641

Data supporting a saturation mutagenesis assay for Tat-driven transcription with the GigaAssay

Ronald Benjamin, Christopher J. Giacoletto, Zachary T. FitzHugh, Danielle Eames, Lindsay Buczek, Xiaogang Wu, Jacklyn Newsome, Mira V. Han, Tony Pearson, Zhi Wei, Atoshi Banerjee, Lancer Brown, Liz J. Valente, Shirley Shen, Hong Wen Deng, Martin R. Schiller

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

2 Scopus citations

Abstract

The data in this article are associated with the research paper “GigaAssay – an adaptable high-throughput saturation mutagenesis assay” [1]. The raw data are sequence reads of HIV-1 Tat cDNA amplified from cellular genomic DNA in a new single-pot saturation mutagenesis assay designated the “GigaAssay”. A bioinformatic pipeline and parameters used to analyze the data. Raw, processed, analyzed, and filtered data are reported. The data is processed to calculate the Tat-driven transcription activity for cells with each possible single amino acid substitution in Tat. This data can be reused to interpret Tat intermolecular interactions and HIV latency. This is one of the largest and most complete datasets regarding the impact of amino acid substitutions within a single protein on a molecular function.

Original language	English (US)
Article number	108641
Journal	Data in Brief
Volume	45
DOIs	https://doi.org/10.1016/j.dib.2022.108641
State	Published - Dec 2022
Externally published	Yes

All Science Journal Classification (ASJC) codes

General

Keywords

High-throughput assay
Intragenic epistasis
Loss of Function (LOF)
Protein structure
Saturation mutagenesis
Tat
Transcription

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10.1016/j.dib.2022.108641

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Benjamin, R., Giacoletto, C. J., FitzHugh, Z. T., Eames, D., Buczek, L., Wu, X., Newsome, J., Han, M. V., Pearson, T., Wei, Z., Banerjee, A., Brown, L., Valente, L. J., Shen, S., Deng, H. W., & Schiller, M. R. (2022). Data supporting a saturation mutagenesis assay for Tat-driven transcription with the GigaAssay. Data in Brief, 45, Article 108641. https://doi.org/10.1016/j.dib.2022.108641

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title = "Data supporting a saturation mutagenesis assay for Tat-driven transcription with the GigaAssay",

abstract = "The data in this article are associated with the research paper “GigaAssay – an adaptable high-throughput saturation mutagenesis assay” [1]. The raw data are sequence reads of HIV-1 Tat cDNA amplified from cellular genomic DNA in a new single-pot saturation mutagenesis assay designated the “GigaAssay”. A bioinformatic pipeline and parameters used to analyze the data. Raw, processed, analyzed, and filtered data are reported. The data is processed to calculate the Tat-driven transcription activity for cells with each possible single amino acid substitution in Tat. This data can be reused to interpret Tat intermolecular interactions and HIV latency. This is one of the largest and most complete datasets regarding the impact of amino acid substitutions within a single protein on a molecular function.",

keywords = "High-throughput assay, Intragenic epistasis, Loss of Function (LOF), Protein structure, Saturation mutagenesis, Tat, Transcription",

author = "Ronald Benjamin and Giacoletto, {Christopher J.} and FitzHugh, {Zachary T.} and Danielle Eames and Lindsay Buczek and Xiaogang Wu and Jacklyn Newsome and Han, {Mira V.} and Tony Pearson and Zhi Wei and Atoshi Banerjee and Lancer Brown and Valente, {Liz J.} and Shirley Shen and Deng, {Hong Wen} and Schiller, {Martin R.}",

note = "Publisher Copyright: {\textcopyright} 2022 The Author(s)",

year = "2022",

month = dec,

doi = "10.1016/j.dib.2022.108641",

language = "English (US)",

volume = "45",

journal = "Data in Brief",

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T1 - Data supporting a saturation mutagenesis assay for Tat-driven transcription with the GigaAssay

AU - Benjamin, Ronald

AU - Giacoletto, Christopher J.

AU - FitzHugh, Zachary T.

AU - Eames, Danielle

AU - Buczek, Lindsay

AU - Wu, Xiaogang

AU - Newsome, Jacklyn

AU - Han, Mira V.

AU - Pearson, Tony

AU - Wei, Zhi

AU - Banerjee, Atoshi

AU - Brown, Lancer

AU - Valente, Liz J.

AU - Shen, Shirley

AU - Deng, Hong Wen

AU - Schiller, Martin R.

PY - 2022/12

Y1 - 2022/12

N2 - The data in this article are associated with the research paper “GigaAssay – an adaptable high-throughput saturation mutagenesis assay” [1]. The raw data are sequence reads of HIV-1 Tat cDNA amplified from cellular genomic DNA in a new single-pot saturation mutagenesis assay designated the “GigaAssay”. A bioinformatic pipeline and parameters used to analyze the data. Raw, processed, analyzed, and filtered data are reported. The data is processed to calculate the Tat-driven transcription activity for cells with each possible single amino acid substitution in Tat. This data can be reused to interpret Tat intermolecular interactions and HIV latency. This is one of the largest and most complete datasets regarding the impact of amino acid substitutions within a single protein on a molecular function.

AB - The data in this article are associated with the research paper “GigaAssay – an adaptable high-throughput saturation mutagenesis assay” [1]. The raw data are sequence reads of HIV-1 Tat cDNA amplified from cellular genomic DNA in a new single-pot saturation mutagenesis assay designated the “GigaAssay”. A bioinformatic pipeline and parameters used to analyze the data. Raw, processed, analyzed, and filtered data are reported. The data is processed to calculate the Tat-driven transcription activity for cells with each possible single amino acid substitution in Tat. This data can be reused to interpret Tat intermolecular interactions and HIV latency. This is one of the largest and most complete datasets regarding the impact of amino acid substitutions within a single protein on a molecular function.

KW - High-throughput assay

KW - Intragenic epistasis

KW - Loss of Function (LOF)

KW - Protein structure

KW - Saturation mutagenesis

KW - Tat

KW - Transcription

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DO - 10.1016/j.dib.2022.108641

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JO - Data in Brief

JF - Data in Brief

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ER -

Data supporting a saturation mutagenesis assay for Tat-driven transcription with the GigaAssay

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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