Limits...
Real-time imaging of cotranscriptional splicing reveals a kinetic model that reduces noise: implications for alternative splicing regulation.

Schmidt U, Basyuk E, Robert MC, Yoshida M, Villemin JP, Auboeuf D, Aitken S, Bertrand E - J. Cell Biol. (2011)

Bottom Line: All small nuclear ribonucleoproteins (snRNPs) are loaded on nascent pre-mRNAs, and spliceostatin A inhibits splicing but not snRNP recruitment.Each pre-mRNA molecule is predicted to require a similar time to splice, reducing kinetic noise and improving the regulation of alternative splicing.This model is relevant to other kinetically controlled processes acting on few molecules.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institut de Génétique Moléculaire de Montpellier, Centre National de la Recherche Scientifique UMR 5535, 34293 Montpellier Cedex 5, France.

ABSTRACT
Splicing is a key process that expands the coding capacity of genomes. Its kinetics remain poorly characterized, and the distribution of splicing time caused by the stochasticity of single splicing events is expected to affect regulation efficiency. We conducted a small-scale survey on 40 introns in human cells and observed that most were spliced cotranscriptionally. Consequently, we constructed a reporter system that splices cotranscriptionally and can be monitored in live cells and in real time through the use of MS2-GFP. All small nuclear ribonucleoproteins (snRNPs) are loaded on nascent pre-mRNAs, and spliceostatin A inhibits splicing but not snRNP recruitment. Intron removal occurs in minutes and is best described by a model where several successive steps are rate limiting. Each pre-mRNA molecule is predicted to require a similar time to splice, reducing kinetic noise and improving the regulation of alternative splicing. This model is relevant to other kinetically controlled processes acting on few molecules.

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Analysis of splicing kinetics by FRAP. (A) Time series of FRAP experiments. WT_MS2ex2 (top) or WT_MS2in (bottom) cells were transfected with vectors expressing Tat and MS2–GFPnsl_nes. Transcription sites were bleached and 3D images were captured for 9–11 min. The time after the bleach is indicated in seconds. pre, prebleach image; post, post-bleach image. The arrow points to the transcription site. Bar, 10 µm. (B) FRAP recovery plots. Normalized fluorescence intensity at the transcription site is plotted as a function of time (±SEM). Time is in seconds, and the zero time point corresponds to the bleach. (C) Scheme describing the kinetic models. (top) A single step is rate limiting (kspl; red). (bottom) Multiple steps are rate-limiting, all with the same rate (kspl; red). (D) Determination of the number of limiting steps. Plot of the AIC values for the optimal choice of the rate of the limiting steps (α) as a function of the number of limiting steps. L is the linear model that was included as a  hypothesis. (E) Optimal fit of the model to the experimental curve. The FRAP curve of WT_MS2in cells was fitted with either a single-step model (red), a three-step model (green), or a nine-step model (blue).
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fig3: Analysis of splicing kinetics by FRAP. (A) Time series of FRAP experiments. WT_MS2ex2 (top) or WT_MS2in (bottom) cells were transfected with vectors expressing Tat and MS2–GFPnsl_nes. Transcription sites were bleached and 3D images were captured for 9–11 min. The time after the bleach is indicated in seconds. pre, prebleach image; post, post-bleach image. The arrow points to the transcription site. Bar, 10 µm. (B) FRAP recovery plots. Normalized fluorescence intensity at the transcription site is plotted as a function of time (±SEM). Time is in seconds, and the zero time point corresponds to the bleach. (C) Scheme describing the kinetic models. (top) A single step is rate limiting (kspl; red). (bottom) Multiple steps are rate-limiting, all with the same rate (kspl; red). (D) Determination of the number of limiting steps. Plot of the AIC values for the optimal choice of the rate of the limiting steps (α) as a function of the number of limiting steps. L is the linear model that was included as a hypothesis. (E) Optimal fit of the model to the experimental curve. The FRAP curve of WT_MS2in cells was fitted with either a single-step model (red), a three-step model (green), or a nine-step model (blue).

Mentions: The presence of the MS2 tag within the intron allows its visualization in live cells (Fusco et al., 2003). To determine the half-life of the intron, MS2–GFP was bleached at the MINX transcription site (Fig. 3). As the measurements improve when the signal of the transcription sites increases over the nucleoplasmic background, a nuclear export signal was added to the original nuclear MS2–GFPnls protein. This way, the MS2–GFPnls-nes displays lower nucleoplasmic signals and allows for a better visualization of nuclear RNAs (Fig. 3). Using this technique, we measured a half-life of 105 s for the MS2–GFP labeled intron, significantly shorter than the 165 s for exon 2.


Real-time imaging of cotranscriptional splicing reveals a kinetic model that reduces noise: implications for alternative splicing regulation.

Schmidt U, Basyuk E, Robert MC, Yoshida M, Villemin JP, Auboeuf D, Aitken S, Bertrand E - J. Cell Biol. (2011)

Analysis of splicing kinetics by FRAP. (A) Time series of FRAP experiments. WT_MS2ex2 (top) or WT_MS2in (bottom) cells were transfected with vectors expressing Tat and MS2–GFPnsl_nes. Transcription sites were bleached and 3D images were captured for 9–11 min. The time after the bleach is indicated in seconds. pre, prebleach image; post, post-bleach image. The arrow points to the transcription site. Bar, 10 µm. (B) FRAP recovery plots. Normalized fluorescence intensity at the transcription site is plotted as a function of time (±SEM). Time is in seconds, and the zero time point corresponds to the bleach. (C) Scheme describing the kinetic models. (top) A single step is rate limiting (kspl; red). (bottom) Multiple steps are rate-limiting, all with the same rate (kspl; red). (D) Determination of the number of limiting steps. Plot of the AIC values for the optimal choice of the rate of the limiting steps (α) as a function of the number of limiting steps. L is the linear model that was included as a  hypothesis. (E) Optimal fit of the model to the experimental curve. The FRAP curve of WT_MS2in cells was fitted with either a single-step model (red), a three-step model (green), or a nine-step model (blue).
© Copyright Policy - openaccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC3105549&req=5

fig3: Analysis of splicing kinetics by FRAP. (A) Time series of FRAP experiments. WT_MS2ex2 (top) or WT_MS2in (bottom) cells were transfected with vectors expressing Tat and MS2–GFPnsl_nes. Transcription sites were bleached and 3D images were captured for 9–11 min. The time after the bleach is indicated in seconds. pre, prebleach image; post, post-bleach image. The arrow points to the transcription site. Bar, 10 µm. (B) FRAP recovery plots. Normalized fluorescence intensity at the transcription site is plotted as a function of time (±SEM). Time is in seconds, and the zero time point corresponds to the bleach. (C) Scheme describing the kinetic models. (top) A single step is rate limiting (kspl; red). (bottom) Multiple steps are rate-limiting, all with the same rate (kspl; red). (D) Determination of the number of limiting steps. Plot of the AIC values for the optimal choice of the rate of the limiting steps (α) as a function of the number of limiting steps. L is the linear model that was included as a hypothesis. (E) Optimal fit of the model to the experimental curve. The FRAP curve of WT_MS2in cells was fitted with either a single-step model (red), a three-step model (green), or a nine-step model (blue).
Mentions: The presence of the MS2 tag within the intron allows its visualization in live cells (Fusco et al., 2003). To determine the half-life of the intron, MS2–GFP was bleached at the MINX transcription site (Fig. 3). As the measurements improve when the signal of the transcription sites increases over the nucleoplasmic background, a nuclear export signal was added to the original nuclear MS2–GFPnls protein. This way, the MS2–GFPnls-nes displays lower nucleoplasmic signals and allows for a better visualization of nuclear RNAs (Fig. 3). Using this technique, we measured a half-life of 105 s for the MS2–GFP labeled intron, significantly shorter than the 165 s for exon 2.

Bottom Line: All small nuclear ribonucleoproteins (snRNPs) are loaded on nascent pre-mRNAs, and spliceostatin A inhibits splicing but not snRNP recruitment.Each pre-mRNA molecule is predicted to require a similar time to splice, reducing kinetic noise and improving the regulation of alternative splicing.This model is relevant to other kinetically controlled processes acting on few molecules.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institut de Génétique Moléculaire de Montpellier, Centre National de la Recherche Scientifique UMR 5535, 34293 Montpellier Cedex 5, France.

ABSTRACT
Splicing is a key process that expands the coding capacity of genomes. Its kinetics remain poorly characterized, and the distribution of splicing time caused by the stochasticity of single splicing events is expected to affect regulation efficiency. We conducted a small-scale survey on 40 introns in human cells and observed that most were spliced cotranscriptionally. Consequently, we constructed a reporter system that splices cotranscriptionally and can be monitored in live cells and in real time through the use of MS2-GFP. All small nuclear ribonucleoproteins (snRNPs) are loaded on nascent pre-mRNAs, and spliceostatin A inhibits splicing but not snRNP recruitment. Intron removal occurs in minutes and is best described by a model where several successive steps are rate limiting. Each pre-mRNA molecule is predicted to require a similar time to splice, reducing kinetic noise and improving the regulation of alternative splicing. This model is relevant to other kinetically controlled processes acting on few molecules.

Show MeSH
Related in: MedlinePlus