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