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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.

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Distribution histograms of structural branchpoint distances for (a) wt, (b) 3mUB1, (c) 5mUB1, (d) 8mUB1, (e) 3mDB1, (f) 5mDB1, (g) 3mUB1_3mDB1, (h) 5mUB1_5mDB1, (i) 6mUB1, and (j) 4mUB1 introns.
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Figure 1: Distribution histograms of structural branchpoint distances for (a) wt, (b) 3mUB1, (c) 5mUB1, (d) 8mUB1, (e) 3mDB1, (f) 5mDB1, (g) 3mUB1_3mDB1, (h) 5mUB1_5mDB1, (i) 6mUB1, and (j) 4mUB1 introns.

Mentions: For each secondary structure prediction, we computed the exact distance between the donor site and the branchpoint sequences (ds) using the shortest-path algorithm. The average structural branchpoint distances are given in Table 1. We assigned descriptive splicing efficiency labels based on the gel images in Figure 2A in [8]. The distributions of computed structural branchpoint distances for each of the RPS17B mutants are given in Figure 1.


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)

Distribution histograms of structural branchpoint distances for (a) wt, (b) 3mUB1, (c) 5mUB1, (d) 8mUB1, (e) 3mDB1, (f) 5mDB1, (g) 3mUB1_3mDB1, (h) 5mUB1_5mDB1, (i) 6mUB1, and (j) 4mUB1 introns.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 1: Distribution histograms of structural branchpoint distances for (a) wt, (b) 3mUB1, (c) 5mUB1, (d) 8mUB1, (e) 3mDB1, (f) 5mDB1, (g) 3mUB1_3mDB1, (h) 5mUB1_5mDB1, (i) 6mUB1, and (j) 4mUB1 introns.
Mentions: For each secondary structure prediction, we computed the exact distance between the donor site and the branchpoint sequences (ds) using the shortest-path algorithm. The average structural branchpoint distances are given in Table 1. We assigned descriptive splicing efficiency labels based on the gel images in Figure 2A in [8]. The distributions of computed structural branchpoint distances for each of the RPS17B mutants are given in Figure 1.

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