Pre-mRNA secondary structures influence exon recognition Michael Hiller Bioinformatics Group...
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Transcript of Pre-mRNA secondary structures influence exon recognition Michael Hiller Bioinformatics Group...
Pre-mRNA secondary structures influence exon recognition
Michael HillerBioinformatics Group
University of Freiburg, Germany
Michael Hiller
Current model of splicing
enhancersilencer
Michael Hiller
Secondary structure of (pre-)mRNA
(pre-)mRNA is not a linear sequence:
• structural elements: IRE, IRES, SECIS, A to I editing
• secondary structure and splicing: – stem structure containing the exon 10 donor leads to exon
skipping of MAPT
– regulation of mutually exclusive exons in FGFR2 and Drosophila DSCAM
• SR proteins / hnRNPs have “single-stranded RNA binding domains”
• bind hairpin loops (Nova1, hnRNP A1, SRp55)
Buratti et al. Mol and Cell Bio. 24(3) 2004 Michael Hiller
Fibronectin EDA exon
General trend for splicing motifs to be single-stranded?
wt mutant
Michael Hiller
1. Data set
Experimentally verified splicing motifs
• AEDB motif database:– motifs with their natural pre-mRNA sequence context– only motifs shorter than 10 nt
final set of 77 motifs
intronic/exonic enhancers/silencers from >6 species including CFTR, FN1, CD44, FGFR1/2, SMN1, tra2beta
Michael Hiller
2. How to measure single-strandedness?
Probability that an mRNA part is completely Unpaired
• the higher PU, the higher the single-strandedness• use all (sub)optimal structures• consider the free energies of structures• allow comparison for motifs of the same length
RT
EE
e=
unpairedall
PU
Michael Hiller
3. In which region is pre-mRNA free to fold?• long range base pairs are less likely
– protein binding– co-transcriptional structure formation– need more time
• experimental evidence that folding is limited to ≈ 50 nt
Michael Hiller
3. In which region is pre-mRNA free to fold?
consider short range base pairs
• symmetrical context lengths 11 – 30 nt• compute average PU
Michael Hiller
Results and Statistics
Results
real data: PU = 0.25
control 1: PU = 0.15 P<0.01
control 2: PU = 0.18 P<0.01
control 3: PU = 0.15 P<0.01
control 4: PU = 0.12 P=0.046
control 5: PU = 0.15 P<0.001
77 experimentally verified motifs: average PU = 0.25
Michael Hiller
Results and Statistics
• negative correlation betweenPU value and GC content of the flanks (r = -0.64)
all null models have the same GC content
Consistent results for: • different measurements for single-strandedness• different context lengths (11-20 nt and 11-50 nt)
verified motifs are significantly more single-stranded
attributed to the flanks
Michael Hiller
Experimental testinginserts with known splicing motifs (TAGGGT, hnRNP A1)
Michael Hiller
Experimental testing
secondary structure of ESE / ESS affects splicing
Michael Hiller
Can we detect structural selection on predicted motifs ?
• divide all 4096 hexamers into [Stadler et al. PLoS Genet. 2006]
– enhancers
– splicing neutral
– silencers
• for each hexamer get „overall PU value“ in – real exons
– pseudo exons
– intronic regions between a real and a decoy donor/acceptor site
Michael Hiller
Selection on structural context of predicted motifs
Compare motifs with equal number of GC´s (e.g. GAAGAA with AACCTA)
higher single-strandedness
- for enhancers in exons
- for silencers in pseudo exons and decoy regions
Michael Hiller
Selection on structural context of predicted motifs
structural context has a widespread and general importance
secondary structures are subject to selection
How often is selection strong enough to overcome the correlation between PU and GC?
Michael Hiller
• SNP can change secondary structures [Shen et al. PNAS, 1999]
• secondary structure might be important for
– design and interpretion of mutagenesis experiments
– basis of mutations that affect splicing
Implications – splicing effect of mutations
Michael Hiller
Implications – splicing effect of mutations
human CFTR exon 12:
25GA mutation reduces exon inclusion from 80 to 25%
Michael Hiller
Implications – splicing effect of mutations
rat beta-tropomyosin exon 8:- mutations in the first enhancer no effect on splicing- mutations in the second enhancer strong effect- mutations in the third enhancer weak effect
Michael Hiller
Conclusion
• verified splicing motifs are more single-stranded• structural context of predicted ESEs/ESSs under natural selection
• selection pressure on a coding exon:– coding sequence – splicing signals– structural context for splicing motifs
• another piece for the ‘mRNA splicing code’
Michael Hiller
Thank you
University Freiburg– Rolf Backofen
University of Erlangen-Nürnberg – Stefan Stamm – Zhaiyi Zhang