Compiling polymorphic miRNA-target interactions: the Patrocles database.

1
Compiling polymorphic miRNA-target
interactions the Patrocles database. Samuel
Hiard1, Xavier Tordoir2, Wouter Coppieters2,
Carole Charlier2 and Michel Georges2 1
Bioinformatics and Modeling, GIGA Department of
Electrical Engineering and Computer Science
University of Liège, Sart-Tilman B28, Liège,
Belgium 2 Unit of Animal Genomics, Department of
Animal Production, Faculty of Veterinary Medicine
CBIG, University of Liège (B43), 20 Boulevard
de Colonster, 4000-Liège, Belgium.
Abstract Using positional cloning, we have
recently identified the mutation responsible for
muscular phenotype of the Texel sheep. It is
located in the 3UTR of the GDF8 gene - a known
developmental repressor of muscle growth - and
creates an illegitimate target site for miRNA
expressed in the same tissue. This causes
miRNA-mediated translation inhibition of mutant
GDF8 transcripts which leads to muscle
hypertrophy. We followed up on this finding by
searching for common polymorphisms and mutations
that affect either (i) RNAi silencing machinery
components, (ii) miRNA precursors or (iii) target
sites. These might likewise alter miRNA-target
interaction and could be responsible for
substantial differences in gene expression level.
They have been compiled in a public database
(Patrocles www.patrocles.org), where they are
classified in (i) DNA sequence polymorphisms
(DSP) affecting the silencing machinery, (ii) DSP
affecting miRNA structure or expression and (iii)
DSP affecting miRNA target sites. DSP from the
last category were organized in four classes
destroying a target site conserved between
mammals (DC), destroying a non-conserved target
site (DNC), creating a non-conserved target site
(CNC), or shifting a target site (S). To aid in
the identification of the most relevant DSP (such
as those were a target site is created in an
antitarget gene), we have quantified the level of
coexpression for all miRNA-gene pairs. Analysis
of the numbers of Patrocles-DSP as well as their
allelic frequency distribution indicates that a
substantial proportion of them undergo purifying
selection. The signature of selection was most
pronounced for the DC class but was significant
for the DNC and CNC class as well, suggesting
that a significant proportion of non-conserved
targets is truly functional. The Patrocles
database allowed for the selection of DSP that
are likely to affect gene function and possibly
disease susceptibility. The effect of these DSP
is being studied both in vitro and in vivo. In
conclusion, Patrocles-DSP could be widespread and
underlie an appreciable amount of phenotypic
variation, including common disease
susceptibility.
Introduction miRNA-mediated gene silencing
emerges as a key regulator of cellular
differentiation and homeostasis to which
metazoans devote a considerable amount of
sequence space. This sequence space is bound to
suffer its toll of mutations of which some will
be selectively neutral while others will be
advantageous or more often at least slightly
deleterious. DNA sequence polymorphisms (DSP)
occurring within this sequence space certainly
contribute to phenotypic variation including
disease susceptibility and agronomically
important traits. An important question is how
important their contribution actually is. DSP may
affect miRNA-mediated gene regulation by
perturbing core components of the silencing
machinery, by affecting the structure or
expression level of miRNAs, or by altering target
sites (Table 1). DSP in core components of the
silencing machinery may affect its overall
efficacy. Mutations that drastically perturb RNA
silencing will obviously be rare given their
predictable highly deleterious consequences. Yet,
DSP with subtle effects on gene function may
occur. As distinct targets may be more or less
sensitive to variations in miRNA concentration or
silencing efficiency, such DSP may affect some
pathways more than others. Specific miRNA-target
interactions may be influenced by mutations
affecting either the miRNA or its target. On the
miRNA side of the equation (i) the sequence of
the mature miRNA may be altered, thereby either
stabilizing or destabilizing its interaction with
targets, (ii) mutations in the pri- or pre-miRNA
may affect stability or processing efficiency,
(iii) mutations acting in cis or trans on the
pri-miRNA promoter may influence transcription
rate, and (iv) Copy Number Variants (CNV) may
affect the number of copies of the miRNA or the
integrity of the pri-miRNA host. On the target
side of the equation (i) mutations may affect
functional target sites thereby destabilizing or
stabilizing the interaction with the miRNA, (ii)
mutations may create illegitimate miRNA target
sites (either in the 3UTR or maybe even in other
segments of the transcript) which will be
particularly relevant if occurring in
antitargets, (iii) mutations causing polymorphic
alternative polyadenylation may affect a genes
content in target sites.
Categories of DNA sequence polymorphisms (DSP)
affecting miRNA-mediated gene regulation
Table 1
miR mediated translational inhibition of the
Texel MSTN allele
Target miRNA Silencing machinery
DSP altering miRNA recognition sites in the target Altering existing target sites . Stabilizing or destabilizing the interaction with the miRNA Creating illegitimate target sites DSP altering the targets 3UTR e.g. polymorphic polyadenylation DSP altering the sequence of the miRNA . Stabilizing or destabilizing the interaction with the target (pSNP) DSP altering the concentration of the miRNA Copy Number Variants emcompassing the pri-miRNA DSP altering the transcription rate of the pri-miRNA . Cis or trans-acting DSP affecting the processing efficiency of the pri- or pre-miRNA DSP altering the amino-acid sequence of silencing components DSP altering the concentration of silencing components Copy Number Variants encompassing silencing components
Nature Genetics, 2006
cDNA
genomic
12 Kd MSTN
Reduction of gt3X
Schematic representation of the MSTN gene and
sequence context of the polymorphic miRNA-MSTN
interaction (left). Muscle hypertrophy in Texel
compared to wild-type Romanov sheep (right).
Reduction of 1.5X
Reduced circulating MSTN protein in Texel (T1) vs
WT (W1)
Allelic imbalance of MSTN at the mRNA level Texel
allele (A) lt WT allele (G) in heterozygous
animals
Texel
Romanov
Quantifying miRNA putative target
co-expression Why? For a pSNP to be affect
function, miRNA and putative target need to have
overlapping expression domains. To assist in the
identification of relevant pSNPs, we therefore
have devised a way to quantify the degree of
co-expression for miRNA-gene pairs How? Gene
Expression SymAtlas (http//symatlas.gnf.org/Sym
Atlas/) miRNA Expression - Fahr et al.
2005 - Compute observed frequency
- Compute expected frequency (

) - Kolmogorov-Smirnov test

P-Value Determined by 1000 random

permutation of genes
KS - 80 of miRNAs hosted by genes
- Deduce expression from
corresponding gene expression - Experimental
data CoExpression First try -
CoExpression of known antitarget gene and miRNA
is quite low - Why? This function doesnt
differenciate moderate coexpression across all
tissues and extremely high coexpression in
one tissue
The g6723G-A natural polymorphism causes
translational inhibition of the Texel MSTN allele
by creating an illegitimate target site for two
miRNA expressed in the same tissue, this leads to
muscle hypertrophy.
Compiling candidate pSNPS
Mutations in miRNAs
In Human

• For specific miRNAs
• mutations in the mature miRNA (table 2)
• 6 SNP in the miR seed (yellow)
• 11 SNP in the mature miR (white)
• mutations in the pre-miRNA may affect stability
  or processing efficacy,
• 71 SNP in the premiR eg.

Conserved Not conserved
Created X 0 L 0 B 0 X 5282 L 7967 B 858
Destroyed X 913 L 639 B 225 X 4524 L 7365 B 708
Polymorphic X 0 L 0 B 0 X 391 L 691 B 85
Shifted X 202 L 361 B 16 X 202 L 361 B 16

• mutations acting in cis or trans on the pri-miRNA
  promoter (or host gene) may influence
  transcription rate
• For the 474 human miRNAs in Rfam (oct 2006)
• - 186 host genes for 229 miR (48.3)
• - 245 miR without host gene
• We identified miRNA host genes characterized by
  inherited variation in expression levels,
  reasoning that this might affect the cellular
  concentration of passenger miRNAs. We compiled
  host genes influenced by both trans- and
  cis-acting expression QTL (eQTL) identified
  either by linkage analysis or by association
  studies and host genes having shown allelic
  imbalance in heterozygous individuals (review by
  Pastinen et al., 2006 Spielman et al, 2006).
• At least eight host genes were found amongst the
  differentially regulated genes reported in these
  studies. An additional one is showing allelic
  imbalance.
• Copy Number Variants (CNV) may affect the number
  of copies of the miRNA or the integrity of the
  pri-miRNA host
• A first CNV map of the human genome has been
  recently constructed (Redon et al., 2006). We
  found 43 miRNAs residing in regions involved in
  CNV, 19 without known host gene and 24 in a host
  gene which were completely (18) or partially (6)
  included in a CNV.

Table 2 DSP in mature miRNA
In Mouse
Conserved Not conserved
Created X 0 L 0 B 0 X 3661 L 4325 B 592
Destroyed X 424 L 269 B 73 X 3363 L 4157 B 529
Polymorphic X 0 L 0 B 0 X 1000 L 1313 B 197
Shifted X 14 L 21 B 11 X 14 L 21 B 11
miRNA derived expression

• Globally
• DSP in components of the RNA silencing machinery
  may affect its overall efficacy.
• We followed 19 genes involved in miR biology for
  coding SNP, CNV, eQTL and allelic imbalance
• CNV encompass Drosha and DGCR8 genes and 6 genes
  present non synomymous mutations (table 3)

Table 3 non synonymous SNP in components of
miR pathway
X Xie et al. 2005 Predicted putative miRNA
target sites by identification of octamer motifs
in 3UTRs characterized by unusually high motif
conservation scores (i.e. proportion of conserved
amongst all occurrences). L Lewis et al. 2005
Reverse complement of (A 2 ? 8) of mature miRNA
(MiRBase) B Both
CoExpression distribution of known antitargets
Screen shot
Nb of Known antitargets
CoExpression Score
Patrocles finder Why? Patrocles is built
using the public information provided by Ensembl.
But the laboratories that work on SNPs often
discover new ones. So, there must be a tool that
allows these labs to obtain the information
about stabilized, destabilized or illegitimate
target sites How? End users must provide one
or two sequences for, respectively, (i) the
analysis of the presence of octamers or (ii)
the comparison of the two sequences regarding to
the content in octamers. They also have to
possibility to provide an alignment of each
sequence if they care about conservation.
Screen shots

• Evidence for purifying selection against pSNPs of
  conserved and non-conserved target sites
• Why?
• What is the evidence that any of the candidate
  pSNPs listed above truly affect gene function and
  hence phenotype? Indirect evidence that a
  significant proportion of them are functional can
  be obtained from population genetics. Indeed,
  pSNPs without appreciable effect on gene function
  will evolve neutrally, subject only to the
  vagaries of random genetic drift while pSNPs
  affecting gene function may undergo positive,
  negative or balancing selection via their effect
  on phenotype. Selection may leave distinct
  signatures on the level of inter-species
  divergence, intra-species variability, allelic
  distribution and linkage disequilibrium
• How?
• - Generation of 100 random sets of SNPs
• Processed through pipeline
• Results
• ? Less pSNPs in
  real data
• 
  ? Differences
  between X and L
• 
  ? pSNPs that destroy
  conserved target
• 
  site are highly
  underrepresented
• 
  (expected)

Acknowledgements PAI P5/25 from the Belgian SSTC
(n R.SSTC.0135), EU Callimir STREP project.
C.C. is chercheur qualifié from the FNRS.