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DksA involvement in transcription fidelity buffers stochastic epigenetic change.

ABSTRACT: DksA is an auxiliary transcription factor that interacts with RNA polymerase and influences gene expression. Depending on the promoter, DksA can be a positive or negative regulator of transcription initiation. Moreover, DksA has a substantial effect on transcription elongation where it prevents the collision of transcription and replication machineries, plays a key role in maintaining transcription elongation when translation and transcription are uncoupled and has been shown to be involved in transcription fidelity. Here, we assessed the role of DksA in transcription fidelity by monitoring stochastic epigenetic switching in the lac operon (with and without an error-prone transcription slippage sequence), partial phenotypic suppression of a lacZ nonsense allele, as well as monitoring the number of lacI mRNA transcripts produced in the presence and absence of DksA via an operon fusion and single molecule fluorescent in situ hybridization studies. We present data showing that DksA acts to maintain transcription fidelity in vivo and the role of DksA seems to be distinct from that of the GreA and GreB transcription fidelity factors.

SUBMITTER: Satory D

PROVIDER: S-EPMC4666387 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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DksA involvement in transcription fidelity buffers stochastic epigenetic change.

Satory Dominik D Gordon Alasdair J E AJ Wang Mengyu M Halliday Jennifer A JA Golding Ido I Herman Christophe C

Nucleic acids research 20150824 21

DksA is an auxiliary transcription factor that interacts with RNA polymerase and influences gene expression. Depending on the promoter, DksA can be a positive or negative regulator of transcription initiation. Moreover, DksA has a substantial effect on transcription elongation where it prevents the collision of transcription and replication machineries, plays a key role in maintaining transcription elongation when translation and transcription are uncoupled and has been shown to be involved in t ...[more]

PMID: 26304546

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Project description:Species distribution modeling (SDM) is an important tool to assess the impact of global environmental change. Many species exhibit ecologically relevant intraspecific variation, and few studies have analyzed its relevance for SDM. Here, we compared three SDM techniques for the highly variable species Pinus contorta. First, applying a conventional SDM approach, we used MaxEnt to model the subject as a single species (species model), based on presence-absence observations. Second, we used MaxEnt to model each of the three most prevalent subspecies independently and combined their projected distributions (subspecies model). Finally, we used a universal growth transfer function (UTF), an approach to incorporate intraspecific variation utilizing provenance trial tree growth data. Different model approaches performed similarly when predicting current distributions. MaxEnt model discrimination was greater (AUC - species model: 0.94, subspecies model: 0.95, UTF: 0.89), but the UTF was better calibrated (slope and bias - species model: 1.31 and -0.58, subspecies model: 1.44 and -0.43, UTF: 1.01 and 0.04, respectively). Contrastingly, for future climatic conditions, projections of lodgepole pine habitat suitability diverged. In particular, when the species' intraspecific variability was acknowledged, the species was projected to better tolerate climatic change as related to suitable habitat without migration (subspecies model: 26% habitat loss or UTF: 24% habitat loss vs. species model: 60% habitat loss), and given unlimited migration may increase amount of suitable habitat (subspecies model: 8% habitat gain or UTF: 12% habitat gain vs. species model: 51% habitat loss) in the climatic period 2070-2100 (SRES A2 scenario, HADCM3). We conclude that models derived from within-species data produce different and better projections, and coincide with ecological theory. Furthermore, we conclude that intraspecific variation may buffer against adverse effects of climate change. A key future research challenge lies in assessing the extent to which species can utilize intraspecific variation under rapid environmental change.

Dataset Information

DksA involvement in transcription fidelity buffers stochastic epigenetic change.

Publications

DksA involvement in transcription fidelity buffers stochastic epigenetic change.

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