Pre-mRNA secondary structures influence exon recognition Michael Hiller Bioinformatics Group...

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Pre-mRNA secondary structures influence exon recognition Michael Hiller Bioinformatics Group University of Freiburg, Germany

Transcript of Pre-mRNA secondary structures influence exon recognition Michael Hiller Bioinformatics Group...

Page 1: Pre-mRNA secondary structures influence exon recognition Michael Hiller Bioinformatics Group University of Freiburg, Germany.

Pre-mRNA secondary structures influence exon recognition

Michael HillerBioinformatics Group

University of Freiburg, Germany

Page 2: Pre-mRNA secondary structures influence exon recognition Michael Hiller Bioinformatics Group University of Freiburg, Germany.

Michael Hiller

Current model of splicing

enhancersilencer

Page 3: Pre-mRNA secondary structures influence exon recognition Michael Hiller Bioinformatics Group University of Freiburg, Germany.

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)

Page 4: Pre-mRNA secondary structures influence exon recognition Michael Hiller Bioinformatics Group University of Freiburg, Germany.

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

Page 5: Pre-mRNA secondary structures influence exon recognition Michael Hiller Bioinformatics Group University of Freiburg, Germany.

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

Page 6: Pre-mRNA secondary structures influence exon recognition Michael Hiller Bioinformatics Group University of Freiburg, Germany.

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

Page 7: Pre-mRNA secondary structures influence exon recognition Michael Hiller Bioinformatics Group University of Freiburg, Germany.

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

Page 8: Pre-mRNA secondary structures influence exon recognition Michael Hiller Bioinformatics Group University of Freiburg, Germany.

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

Page 9: Pre-mRNA secondary structures influence exon recognition Michael Hiller Bioinformatics Group University of Freiburg, Germany.

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

Page 10: Pre-mRNA secondary structures influence exon recognition Michael Hiller Bioinformatics Group University of Freiburg, Germany.

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

Page 11: Pre-mRNA secondary structures influence exon recognition Michael Hiller Bioinformatics Group University of Freiburg, Germany.

Michael Hiller

Experimental testinginserts with known splicing motifs (TAGGGT, hnRNP A1)

Page 12: Pre-mRNA secondary structures influence exon recognition Michael Hiller Bioinformatics Group University of Freiburg, Germany.

Michael Hiller

Experimental testing

secondary structure of ESE / ESS affects splicing

Page 13: Pre-mRNA secondary structures influence exon recognition Michael Hiller Bioinformatics Group University of Freiburg, Germany.

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

Page 14: Pre-mRNA secondary structures influence exon recognition Michael Hiller Bioinformatics Group University of Freiburg, Germany.

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

Page 15: Pre-mRNA secondary structures influence exon recognition Michael Hiller Bioinformatics Group University of Freiburg, Germany.

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?

Page 16: Pre-mRNA secondary structures influence exon recognition Michael Hiller Bioinformatics Group University of Freiburg, Germany.

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

Page 17: Pre-mRNA secondary structures influence exon recognition Michael Hiller Bioinformatics Group University of Freiburg, Germany.

Michael Hiller

Implications – splicing effect of mutations

human CFTR exon 12:

25GA mutation reduces exon inclusion from 80 to 25%

Page 18: Pre-mRNA secondary structures influence exon recognition Michael Hiller Bioinformatics Group University of Freiburg, Germany.

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

Page 19: Pre-mRNA secondary structures influence exon recognition Michael Hiller Bioinformatics Group University of Freiburg, Germany.

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’

Page 20: Pre-mRNA secondary structures influence exon recognition Michael Hiller Bioinformatics Group University of Freiburg, Germany.

Michael Hiller

Thank you

University Freiburg– Rolf Backofen

University of Erlangen-Nürnberg – Stefan Stamm – Zhaiyi Zhang