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Correlation between the secondary structure of pre-mRNA introns and the efficiency of splicing in Saccharomyces cerevisiae.

Rogic S, Montpetit B, Hoos HH, Mackworth AK, Ouellette BF, Hieter P - BMC Genomics (2008)

Bottom Line: The nature of these base-pairing interactions and their effect on splicing efficiency were most extensively studied in ribosomal protein gene RPS17B (previously known as RP51B).We show that it is necessary to consider suboptimal structure predictions and to compute the structural branchpoint distances in order to explain previously published splicing efficiency results.Our findings provide further insights into the role of pre-mRNA secondary structure in gene splicing in yeast and also offer basis for improvement of computational methods for splice site identification and gene-finding.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Computer Science, University of British Columbia, Vancouver, Canada. rogic@bioinformatics.ubc.ca

ABSTRACT

Background: Secondary structure interactions within introns have been shown to be essential for efficient splicing of several yeast genes. The nature of these base-pairing interactions and their effect on splicing efficiency were most extensively studied in ribosomal protein gene RPS17B (previously known as RP51B). It was determined that complementary pairing between two sequence segments located downstream of the 5' splice site and upstream of the branchpoint sequence promotes efficient splicing of the RPS17B pre-mRNA, presumably by shortening the branchpoint distance. However, no attempts were made to compute a shortened, 'structural' branchpoint distance and thus the functional relationship between this distance and the splicing efficiency remains unknown.

Results: In this paper we use computational RNA secondary structure prediction to analyze the secondary structure of the RPS17B intron. We show that it is necessary to consider suboptimal structure predictions and to compute the structural branchpoint distances in order to explain previously published splicing efficiency results. Our study reveals that there is a tight correlation between this distance and splicing efficiency levels of intron mutants described in the literature. We experimentally test this correlation on additional RPS17B mutants and intron mutants within two other yeast genes.

Conclusion: The proposed model of secondary structure requirements for efficient splicing is the first attempt to specify the functional relationship between pre-mRNA secondary structure and splicing. Our findings provide further insights into the role of pre-mRNA secondary structure in gene splicing in yeast and also offer basis for improvement of computational methods for splice site identification and gene-finding.

Show MeSH
A part of the wildtype RPS17B intron secondary structure that shows base-pairing between the donor site and the branchpoint sequence. The highlighted stem is the same as the one identified in [9] using experimental structure probing.
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Figure 4: A part of the wildtype RPS17B intron secondary structure that shows base-pairing between the donor site and the branchpoint sequence. The highlighted stem is the same as the one identified in [9] using experimental structure probing.

Mentions: The branchpoint distance analysis of S. cerevisiae's RPS17B intron suggests that the ability to form highly probable secondary structures (within 5% of the MFE) with short distance between the donor site and the branchpoint sequence seems to be required for efficient splicing of the intron. The short structural branchpoint distance for the RPS17B intron results from two base-pair interactions: between the first intron base (G) and the third base of the branchpoint sequence (C); and between the second base in the intron (U) and the second base of the branchpoint sequence (A) (see Figure 4). It is possible to compute the probability of these base-pairing interactions directly using a dynamic programming algorithm that computes the partition function [21]. The base-pair probability reflects a sum of all probability-weighted structures in which the chosen base-pair occurs. Thus, these base-pairing probabilities also take into account the structures that were not within 5% from the MFE, eliminating the necessity to chose an arbitrary percent suboptimality value. The base-pair probabilities can be computed using RNAfold [22], another frequently used program for RNA secondary structure prediction.


Correlation between the secondary structure of pre-mRNA introns and the efficiency of splicing in Saccharomyces cerevisiae.

Rogic S, Montpetit B, Hoos HH, Mackworth AK, Ouellette BF, Hieter P - BMC Genomics (2008)

A part of the wildtype RPS17B intron secondary structure that shows base-pairing between the donor site and the branchpoint sequence. The highlighted stem is the same as the one identified in [9] using experimental structure probing.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2536676&req=5

Figure 4: A part of the wildtype RPS17B intron secondary structure that shows base-pairing between the donor site and the branchpoint sequence. The highlighted stem is the same as the one identified in [9] using experimental structure probing.
Mentions: The branchpoint distance analysis of S. cerevisiae's RPS17B intron suggests that the ability to form highly probable secondary structures (within 5% of the MFE) with short distance between the donor site and the branchpoint sequence seems to be required for efficient splicing of the intron. The short structural branchpoint distance for the RPS17B intron results from two base-pair interactions: between the first intron base (G) and the third base of the branchpoint sequence (C); and between the second base in the intron (U) and the second base of the branchpoint sequence (A) (see Figure 4). It is possible to compute the probability of these base-pairing interactions directly using a dynamic programming algorithm that computes the partition function [21]. The base-pair probability reflects a sum of all probability-weighted structures in which the chosen base-pair occurs. Thus, these base-pairing probabilities also take into account the structures that were not within 5% from the MFE, eliminating the necessity to chose an arbitrary percent suboptimality value. The base-pair probabilities can be computed using RNAfold [22], another frequently used program for RNA secondary structure prediction.

Bottom Line: The nature of these base-pairing interactions and their effect on splicing efficiency were most extensively studied in ribosomal protein gene RPS17B (previously known as RP51B).We show that it is necessary to consider suboptimal structure predictions and to compute the structural branchpoint distances in order to explain previously published splicing efficiency results.Our findings provide further insights into the role of pre-mRNA secondary structure in gene splicing in yeast and also offer basis for improvement of computational methods for splice site identification and gene-finding.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Computer Science, University of British Columbia, Vancouver, Canada. rogic@bioinformatics.ubc.ca

ABSTRACT

Background: Secondary structure interactions within introns have been shown to be essential for efficient splicing of several yeast genes. The nature of these base-pairing interactions and their effect on splicing efficiency were most extensively studied in ribosomal protein gene RPS17B (previously known as RP51B). It was determined that complementary pairing between two sequence segments located downstream of the 5' splice site and upstream of the branchpoint sequence promotes efficient splicing of the RPS17B pre-mRNA, presumably by shortening the branchpoint distance. However, no attempts were made to compute a shortened, 'structural' branchpoint distance and thus the functional relationship between this distance and the splicing efficiency remains unknown.

Results: In this paper we use computational RNA secondary structure prediction to analyze the secondary structure of the RPS17B intron. We show that it is necessary to consider suboptimal structure predictions and to compute the structural branchpoint distances in order to explain previously published splicing efficiency results. Our study reveals that there is a tight correlation between this distance and splicing efficiency levels of intron mutants described in the literature. We experimentally test this correlation on additional RPS17B mutants and intron mutants within two other yeast genes.

Conclusion: The proposed model of secondary structure requirements for efficient splicing is the first attempt to specify the functional relationship between pre-mRNA secondary structure and splicing. Our findings provide further insights into the role of pre-mRNA secondary structure in gene splicing in yeast and also offer basis for improvement of computational methods for splice site identification and gene-finding.

Show MeSH