Julie Demars

Sylvie Rossignol

Irène Netchine

Kai Syin Lee

Mansur Shmela

Laurence Faivre

Jacques Weill

Sylvie Odent

Salah Azzi

Patrick Callier

Irene Netchine

Josette Lucas

Christèle Dubourg

Joris Andrieux

Yves Le Bouc

Assam El-Osta

Christine Gicquel
email: christine.gicquel@bakeridi.edu.au

New insights into the

Keywords: genomic imprinting, copy number variation, 11p15 region, Silver-Russell syndrome, Beckwith-Wiedemann syndrome, fetal growth

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Introduction Human chromosome 11p15.5 contains a cluster of imprinted genes that play a crucial role in the control of fetal growth [START_REF] Reik | Genomic imprinting: parental influence on the genome[END_REF][START_REF] Delaval | Epigenetic regulation of mammalian genomic imprinting[END_REF][START_REF] Gicquel | Hormonal regulation of fetal growth[END_REF][START_REF] Hudson | Genomic imprinting mechanisms in embryonic and extraembryonic mouse tissues[END_REF] . This cluster is organized in two neighboring imprinted domains, the IGF2/H19 and the KCNQ1OT1/CDKN1C domains, each of them under the control of its own imprinting control region, ICR1 and ICR2 respectively. Aberrant genomic imprinting of the 11p15 region has a pivotal role in both Beckwith-Wiedemann (BWS; MIM 130650) and Silver-Russell (SRS; MIM 180860) syndromes. BWS is characterized by pre-and/or postnatal overgrowth and other features including hemihyperplasia and an increased risk of childhood tumors. SRS is characterized by severe preand postnatal growth retardation, dysmorphic facial features, feeding difficulties and body asymmetry.

Various 11p15 molecular aberrations including genetic and epigenetic abnormalities have been demonstrated in BWS and SRS [START_REF] Gaston | Analysis of the methylation status of the KCNQ1OT and H19 genes in leukocyte DNA for the diagnosis and prognosis of Beckwith-Wiedemann syndrome[END_REF][START_REF] Cooper | Molecular subtypes and phenotypic expression of Beckwith-Wiedemann syndrome[END_REF][START_REF] Gicquel | Epimutation of the telomeric imprinting center region on chromosome 11p15 in Silver-Russell syndrome[END_REF][START_REF] Weksberg | Beckwith-Wiedemann syndrome[END_REF] . Among genetic defects, paternal isodisomy of the 11p15 region involving the two imprinted domains is a classical cause of BWS and accounts for 20-25% of BWS cases [START_REF] Gaston | Analysis of the methylation status of the KCNQ1OT and H19 genes in leukocyte DNA for the diagnosis and prognosis of Beckwith-Wiedemann syndrome[END_REF][START_REF] Henry | Uniparental paternal disomy in a genetic cancer-predisposing syndrome[END_REF][START_REF] Cooper | Mitotic recombination and uniparental disomy in Beckwith-Wiedemann syndrome[END_REF] , whereas maternal isodisomy has been reported in only one SRS case [START_REF] Bullman | Mosaic maternal uniparental disomy of chromosome 11 in a patient with Silver-Russell syndrome[END_REF] . Approximately ten unbalanced translocations (gain CNV) involving both imprinted domains have also been described. When familial, these translocations result in a fetal growth retardation phenotype when maternally-inherited and an overgrowth phenotype when paternally-inherited, as reviewed in [START_REF] Bliek | Phenotypic discordance upon paternal or maternal transmission of duplications of the 11p15 imprinted regions[END_REF] . Nevertheless, epigenetic defects (i.e gain or loss of DNA methylation at either ICR1 or ICR2) are very frequent and account for approximately 60-70% of BWS and SRS patients. DNA methylation defects involving ICR2 (loss of methylation) result in BWS (60% of cases) whereas DNA methylation defects involving ICR1 result in both BWS (gain of methylation, 10% of cases) and SRS (loss of methylation, 50-60% of cases) [START_REF] Gaston | Analysis of the methylation status of the KCNQ1OT and H19 genes in leukocyte DNA for the diagnosis and prognosis of Beckwith-Wiedemann syndrome[END_REF][START_REF] Cooper | Molecular subtypes and phenotypic expression of Beckwith-Wiedemann syndrome[END_REF][START_REF] Gicquel | Epimutation of the telomeric imprinting center region on chromosome 11p15 in Silver-Russell syndrome[END_REF][START_REF] Netchine | 11p15 imprinting center region 1 loss of methylation is a common and specific cause of typical Russell-Silver syndrome: clinical scoring system and epigeneticphenotypic correlations[END_REF] . For a small percentage of those patients, the DNA methylation defect is secondary.

Mutations/deletions in ICR1 cis-regulatory elements account for 20% of BWS patients with ICR1 gain of methylation [START_REF] Sparago | Microdeletions in the human H19 DMR result in loss of IGF2 imprinting and Beckwith-Wiedemann syndrome[END_REF][START_REF] Prawitt | Microdeletion of target sites for insulator protein CTCF in a chromosome 11p15 imprinting center in Beckwith-Wiedemann syndrome and Wilms' tumor[END_REF][START_REF] Sparago | Mechanisms causing imprinting defects in familial Beckwith-Wiedemann syndrome with Wilms' tumour[END_REF][START_REF] Scott | Constitutional 11p15 abnormalities, including heritable imprinting center mutations, cause nonsyndromic Wilms tumor[END_REF][START_REF] Demars | Analysis of the IGF2/H19 imprinting control region uncovers new genetic defects, including mutations of OCT-binding sequences, in patients with 11p15 fetal growth disorders[END_REF] , whereas deletions in ICR2 cis-regulatory elements in BWS patients have been exceptionally reported [START_REF] Niemitz | Microdeletion of LIT1 in familial Beckwith-Wiedemann syndrome[END_REF]20 . On the other hand, in a subset of BWS patients (25%) with 29/7/11 ICR2 loss of methylation and SRS patients (10%) with ICR1 loss of methylation, the loss of methylation involves imprinted loci other than 11p15 suggesting the dysregulation of an unidentified trans-acting factor controlling the establishment and/or the maintenance of genomic imprinting at several loci [START_REF] Rossignol | The epigenetic imprinting defect of patients with Beckwith-Wiedemann syndrome born after assisted reproductive technology is not restricted to the 11p15 region[END_REF][START_REF] Azzi | Multilocus methylation analysis in a large cohort of 11p15-related foetal growth disorders (Russell Silver and Beckwith Wiedemann syndromes) reveals simultaneous loss of methylation at paternal and maternal imprinted loci[END_REF][START_REF] Bliek | Lessons from BWS twins: complex maternal and paternal hypomethylation and a common source of haematopoietic stem cells[END_REF][START_REF] Bliek | Hypomethylation at multiple maternally methylated imprinted regions including PLAGL1 and GNAS loci in Beckwith-Wiedemann syndrome[END_REF][START_REF] Lim | Clinical and molecular genetic features of Beckwith-Wiedemann syndrome associated with assisted reproductive technologies[END_REF][START_REF] Meyer | Germline mutation in NLRP2 (NALP2) in a familial imprinting disorder (Beckwith-Wiedemann Syndrome)[END_REF] . Altogether, these secondary DNA methylation defects (deletion of a cis-regulatory element or involvement of a trans-acting regulatory factor) account for a small group of BWS and SRS cases and the mechanism of the DNA methylation defect remains unexplained in most cases.

Conventional diagnostic tools used in 11p15 fetal growth disorders present either a low resolution level (> 500 kb), (i.e caryotype, FISH analysis) or high resolution level (< 5 kb), (sequencing, DNA methylation analysis, Multiplex ligation-dependent probe amplification, long-range PCR) and they might fail to recognize intermediate CNVs, ranging from 5 to 500 kb. Assessment of small segmental CNVs has not been systematically addressed in SRS and BWS patients with isolated DNA methylation defects. To investigate whether cryptic CNVs account for 11p15 isolated DNA methylation defects, we designed a customized Single Nucleotide Polymorphism (SNP) array (1536 SNPs) covering the whole 11p15 imprinted region. We genotyped a large series of one hundred eighty five SRS and BWS cases with loss or gain of DNA methylation at either ICR1 or ICR2. We describe herein novel gain and loss CNVs in both BWS and SRS patients.

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Subjects and Methods

Subjects

This study was conducted in compliance with institutional guidelines for research studies in human genetics (approval no. 253/07, Alfred Hospital Ethics Committee and agreement numbers 681 and 682, Assistance Publique-Hôpitaux de Paris) and informed consent was obtained from participating individuals and/or their parents. The study population consisted of 50 ethnically matched control subjects and 185 patients with growth disorders caused by a DNA methylation defect of the 11p15 domain. A subset of BWS and SRS patients with abnormal DNA methylation at ICR1 was analyzed in a previous study [START_REF] Demars | Analysis of the IGF2/H19 imprinting control region uncovers new genetic defects, including mutations of OCT-binding sequences, in patients with 11p15 fetal growth disorders[END_REF] . Patients with cytogenetic abnormalities, 11p15 parental isodisomy or CDKN1C gene mutation and patients with a multilocus imprinting disorder 21; 22 were excluded from the study. Biparental inheritance of the 11p15 region was shown by Southern-blot and/or microsatellite analysis.

One hundred and thirteen patients were diagnosed with BWS. Seventyeight of them displayed a loss of methylation at ICR2. Thirty-five BWS patients displayed a gain of methylation at ICR1. Nine BWS cases (six with ICR2 loss of methylation and three with ICR1 gain of methylation) were fetal cases (medically terminated pregnancies in 50% of cases and spontaneous abortion in 50% of cases). Five BWS cases were familial forms (one with ICR2 loss of methylation and four cases from two families with ICR1 gain of methylation).

Seventy-two patients were SRS patients who displayed loss of methylation at ICR1. Parental DNA was available for 110 (59%) BWS or SRS patients. In 93 cases, DNA was available from both parents. Non-paternity was found in three BWS cases with ICR2 loss of DNA methylation and only maternal DNA was considered in those cases.

The clinical and molecular data of BWS and SRS patients are summarized in tables 1 and 2.

Methods

Selection of SNP probes and Oligo Pool Assay design

An

Preparation of SNP data

We generated a total of ~ 735 000 genotypes in 473 samples. Genotypes were analyzed using the Illumina GenomeStudio software (http://www.illumina.com). After reclustering, 8 samples with a call rate <95% and 340 probes with excessive noise or aberrant clustering patterns (based on the GenTrain Score and manual inspection) were permanently excluded from further analysis. Following a series of quality control steps, an initial design using 1536 SNPs and 473 individuals was reduced to a final dataset of 1196 SNPs and 465 samples (including the 185 patients and 50 control subjects).

CNVs detection by Illumina and QuantiSNP v2.3 softwares

Analysis of CNVs was done based on log R ratio and B allele frequency

values issued from the Illumina GenomeStudio and Beadstudio v3.1 softwares. Firstly, we used the cnvPartition v2.4.4 plug-in (http://www.illumina.com) implemented in the Illumina GenomeStudio software to identify CNVs. Given the density of probes in the OPA (one to three per kb), CNVs as small as 1 kb could be potentially detected. We performed a non-stringent analysis considering 3 consecutive probes, a minimum size of 1,000 bp and a threshold of 35 according to the 29/7/11 program. Because the cnvPartition algorithm uses an undocumented method of CNV detection, we also used the QuantiSNP v2.3 software developed by Colella et al. 27 . QuantiSNP based on Objective Bayes Hidden-Markov Model treats independently log R ratio and B allele frequency and has been shown to outperform other softwares [START_REF] Dellinger | Comparative analyses of seven algorithms for copy number variant identification from single nucleotide polymorphism arrays[END_REF] . The analysis was performed using default parameters 27 and a score (Log Bayes Factor) was assigned to each identified CNV; only CNVs with a stringent threshold score (Log Bayes Factor >30) have been considered.

Secondly, to identify runs of homozygosity, we used the Homozygosity Detector plug-in (http://www.illumina.com) implemented in the Illumina BeadStudio v3.1 software as well as the QuantiSNP v2.3 software. The analysis was performed using the default parameters of the Homozygosity Detector program. All regions with more than 50 homozygous and a cutoff significance χ2>23.5 were marked as runs of homozygosity. For the analysis using the QuantiSNP v2.3 software, only runs of homozygosity with a Log Bayes Factor > 30 were considered.

Validation of identified CNVs by quantitative real-time PCR analysis and CGH array

Quantitative real-time PCR: Validation of CNVs identified from the SNP array was performed by quantitative real time PCR. We designed at least 5 primer sets located within and outside the region of interest to confirm the CNVs and map their limits. Quantitative real time PCR was carried out by using a 7500 fast real time PCR system (ABI systems) and Fast SYBR green mix (Roche). Data expressed as the relative quantification were normalized to a region located in the neurogenin 1 gene in which no genetic variation has been described. Two normal individuals were included. All primers used in this study are listed in Supplementary table 1.

CGH array: Validation of some CNVs identified from the SNP array was performed using the 244K Agilent -Human CpG Island Microarray Kit (patient S72P) or the 4x180K Agilent-Human Genome Microarray Kit (patient H47P) (Agilent Technologies, Santa Clara, CA, USA).

Bisulfite sequencing

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Bisulfite sequencing was performed as previously described [START_REF] Demars | Analysis of the IGF2/H19 imprinting control region uncovers new genetic defects, including mutations of OCT-binding sequences, in patients with 11p15 fetal growth disorders[END_REF] . Primers used in this study are listed in Supplementary table 1.

Karyotyping and FISH characterisation

Chromosomes were prepared from peripheral blood lymphocyte cultures following standard procedures. Fluorescence in situ hybridization (FISH) using chromosome 11 specific subtelomeric probes (patient H47P) was performed according to the manufacturer's specifications (Abbott molecular/Vysis, USA). The BAC probes used in other FISH analyses include RP11-295K3 and RP3-416J11 (patient S72P) and CTD-2242D18 (patient L65P).

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Results

Several parameters were used to assess the likelihood of pathogenicity of a CNV in this study: i) the specific localization of a CNV within the 11p15 region (i.e the CNV involves key regulatory elements such as ICR2 in BWS patients with loss of methylation involving the centromeric domain or ICR1 in BWS and SRS patients with a DNA methylation defect of the telomeric domain). ii) the parental transmission of the CNV in familial cases: when inherited, a CNV inherited from a healthy parent was considered as potentially pathogenic. iii) copy-neutral CNVs (runs of homozygosity) were considered as potentially pathogenic as losses and gains, as they might reflect segmental uniparental isodisomy. iv) variants that are seen in healthy individuals are less likely to account for a patient's phenotype. To this purpose, the database of genomic variants (http://projects.tcag.ca/variation/) was consulted.

New intermediate CNVs in BWS or SRS patients with DNA methylation defect at ICR1 or ICR2

Six CNVs (2 deletions and 4 duplications) were identified in six patients, by using the cnvPartition v2.4.4 and/or the QuantiSNP v2.3 softwares (Table 3). Three CNVs (4 to 22 kb) were only identified with the cnvPartition software and they were not confirmed by quantitative PCR. Three CNVs, all duplications, were identified with both softwares and were confirmed by quantitative real-time PCR. Those three validated duplications were further characterized.

H47P BWS patient:

The male patient was a first child, born after 38 weeks of gestation following ovarian stimulation. Prenatal sonography identified cystic hygroma and unilateral pyelectasis. Antenatal karyotype was normal.

There was no familial history of BWS. At birth, the patient displayed severe macrosomia (birth length 56 cm, +3.4 SD; birth weight 5490 g, +5.9 SD), macroglossia, umbilical hernia and facial dysmorphia and the first months of post-natal life were marked by feeding difficulties. In early post-natal life, the patient was diagnosed with developmental delay, expressed primarily in the form of hypotonia and non-specific speech retardation. He walked at the age of 17 months. He underwent pyeloplasty for 29/7/11 ureteropyelic junction stenosis at the age of 1 year and glossoplasty at the age of 3 years. Physical examination at the age of 5 1/12 years showed a slight asymmetry of the face, lower limbs and kidneys and advanced growth (+3.5 SD for height and +4.5 SD for weight).

Analysis of the 11p15 region showed a partial gain of methylation at ICR1

[methylation index at 72% (normal: 53.9 ± 2%)] with a normal methylation status at ICR2 [methylation index at 45% (51.6 ± 2.5%)]. Analysis of SNP array data (Log R Ratio and B allele frequency) identified a duplication (Figure 1A). The duplication covered the whole IGF2/H19 domain, involving the most telomeric probe (position 1,970,084, NCBI36/hg18 Assembly), with a centromeric breakpoint located within the 3' end of the CD81 gene (between position 2,374,469 and 2,375,108). Quantitative PCR showed that the duplication extends to the telomeric end of the short arm (Figure 1B) refining the size of the duplication to approximately 2.4

Mb. SNP analysis showed that the duplication involved the paternal allele (Figure 1C). CGH array confirmed the telomeric duplication at 11p15.5 and also identified a 2 Mb telomeric deletion at 11q25 (breakpoint between position 132,431,292 and 134,432,465) (Figure 1D). Metaphase FISH analysis of H47P with a 11p subtelomeric probe showed signals at both telomeres of a derivative chromosome 11, whereas FISH analysis using a 11q subtelomeric probe confirmed a deletion of 11qter by showing a fluorescent signal on the normal chromosome 11 only (Figure 1E). FISH analysis in parents identified a pericentric inversion in the father, with the 11p subtelomeric probe hybridizing the end of 11q and the 11q subtelomeric probe hybridizing the end of 11p on the inverted chromosome (Figure 1E). As the size of the inverted segment is in the range of 130 Mb, the karyotypes were considered as normal in both H47P and his father (data not shown). This observation shows that partial trisomy 11p15 and partial monosomy 11q25 in H47P resulted from unequal crossing over during paternal meiosis.

S72P SRS patient:

The female patient was the second child, conceived naturally from non consanguineous parents (Figure 2A). At birth (term of 36 weeks), she displayed intrauterine growth retardation [birth weight of 1690 g (-2.6 SD), 29/7/11 birth length of 39.5 cm (-4.4 SD)] with relative macrocephaly (-0.4 SD).

Early postnatal life was marked by severe feeding difficulties and growth deceleration (-3 SD at the age by 7 months and -3.7 SD by the age of 15 months) with a BMI of -2 SD. SRS was diagnosed during the second year of life on the basis of postnatal growth retardation with conserved head circumference, bossed forehead, clinodactyly of the fifth digits, body asymmetry and feeding difficulties. The parents and the older brother were clinically normal and there was no familial history of SRS on the maternal side.

Analysis of the 11p15 region showed a partial loss of methylation at ICR1

(methylation index at 25%) with a normal methylation status at ICR2

(methylation index at 47%). Analysis of SNP array data identified a maternally-inherited duplication covering part of the IGF2/H19 domain, including the H19 gene and ICR1 but not the IGF2 gene (Figure 2B).

Characterization of the duplication by quantitative PCR and CGH array

estimated its size between 562 and 575 kb with the telomeric breakpoint located between 1,522,259 and 1,530,602 bp (within the HCCA2 gene) and the centromeric breakpoint located between 2,092,578 and 2,097,357 bp (Figures 2C and2D). Two color FISH analysis of S72P and her mother with two BAC probes (RP11-295K3 within the duplication and RP3-416J11 outside the duplication) excluded an unbalanced translocation and showed an increased signal at 11p with RP11-295K3, providing indirect evidence for cis-duplication of the affected region (Figure 2E). FISH on S72P's interphased nuclei clearly showed three hybridization signals confirming the cis-duplication (Figure 2F). Methylation analysis in the mother showed a gain of methylation at ICR1 (methylation index at 68%). The mother's phenotype was normal and no clinical history in early childhood was indicative of BWS. Both maternal grandparents had normal phenotypes and there was no familial history suggesting SRS or BWS cases.

Assuming that the grand paternal allele was methylated in the mother, we performed genomic and bisulfite sequencing of the ICR1 B6 repeat (1,980,297-1,980,616 bp) in S72P and her mother. An allelic imbalance was observed for the informative rs61383602 SNP in the mother, suggesting that the C allele was the duplicated allele (Figure 2 G). Bisulfite 29/7/11 sequencing showed that in the mother, the duplicated C allele peak was methylated confirming that the duplication originated from the maternal grandfather (Figure 2G).

Familial L65P BWS case:

The family was previously reported as a clinical description in 1983 [START_REF] Nivelon-Chevallier | Familial Wiedeman-Beckwith syndrome: prenatal echography diagnosis and histologic confirmation[END_REF] . All the affected subjects were conceived from normal sisters (Figure 3A). Patient L65P (III.7, Figure 3A 3B). The ICR2 methylation pattern was also normal in the individuals whom DNA was available, including the maternal grandmother (Figure 3B). Search for a deletion involving ICR2 was negative (PCR and quantitative PCR) and this hypothesis was unlikely as the ICR2 DNA methylation profile was normal in L65P's mother and her sisters. ICR2 was also sequenced (position 2,677,063 to 2,679,536 bp) and no small deletions or mutations were identified.

Analysis of SNP array and Log R Ratio data identified an approximately 50 kb duplication ranging from approximately 2,485,000 to 2,533,000 bp 29/7/11 (Figure 3C), involving the 3' part of intron 1, exon 2 and 5' part of intron 2 of the KCNQ1 gene (isoform NM000218.2). The duplication was confirmed by quantitative PCR with the telomeric breakpoint located between 2,472,581 and 2,486,398 bp and the centromeric breakpoint located between 2,526,347 and 2,540,424 bp (Figure 3D). The duplication was also found in the three sisters (obligate carriers) and also in unaffected individuals II.5 and III.5. Subject I.1 did not display the duplication (Figures 3C and3D), suggesting that the duplication was transmitted from L65P's maternal grandfather (DNA not available) to the five siblings (II.1 to II.5).

The duplication was also absent in the only unaffected child (III.3) born from one (II.1) of the three sisters (Figures 3A and3D). FISH analysis with the CTD-2242D18 probe (position: 2,469,461-2,575,865) did not detect an increased hybridization signal on chromosome 11. It is likely that the small size of the duplication prevented its identification by FISH. The absence of an extra signal on another chromosome is in favor of a 11p15 cisduplication.

As the duplication encompasses two CpG islands, we investigated the methylation status of those CpG islands in three control subjects, L65P, his mother (II.3) and his maternal grandmother (I.1). Bisulfite sequencing analysis of the CpG island in position 2,510,680-2,510,907 showed that both parental alleles were unmethylated (Figure 3F) in control subjects, patient L65P and subjects II.3 and I.1. Analysis of the CpG island in position 2,511,982-2,512,194 showed that the CpG island was predominantly methylated with no allele-specific DNA methylation in controls (Figure 3F). In patient L65P, subjects II.3 and I.1, the DNA methylation pattern was the same as in control subjects.

Small CNVs in BWS patients with gain of DNA methylation at ICR1

A few ICR1 deletions have been previously reported, essentially in BWS patients. They are small in the range of 1-2 kb and as they involve very few markers, they might be missed by the CNV detection methods. We therefore performed an accurate analysis of respective imprinting control regions in patients with abnormal DNA methylation at ICR1 or ICR2, assuming that homozygous calls (B allele frequency) with a reduced copy 29/7/11 number (log R ratio) for SNPs mapping to ICR1 (1,976,000-1,981,000 bp) or ICR2 (2,676,000-2,679,000 bp) will reflect the occurence of a hemizygous deletion.

Three BWS patients with ICR1 gain of methylation displayed a low log R ratio for two or three SNPs located within ICR1 (Figure 4A). Two of them, H32P (previously reported, [START_REF] Demars | Analysis of the IGF2/H19 imprinting control region uncovers new genetic defects, including mutations of OCT-binding sequences, in patients with 11p15 fetal growth disorders[END_REF] ) and H50P presented as apparently sporadic BWS cases. H63P had a familial history of Wilms tumors on the maternal side (Figure 4B). H63P's mother herself displayed a phenotype indicative of BWS, including macrosomia at birth, organomegaly and body asymmetry. She also developed a Wilms tumor when she was 5 years old.

Deletions were characterized by long range PCR, quantitative PCR and sequencing (Figures 4C, 4D and4E). All deletions were maternallyinherited (Figure 4C). The two 1834 bp deletions (H32P and H50P) fusion blocks B6 with B3, removing two CTCF binding sites but involve different breakpoints (Figure 4F and Table 4). The 2240 bp H63P deletion fusions blocks B6 with B2 and removes CTCF binding sites 2, 3 and 4 (Figures 4E,4F and Table 4).

No ICR1 deletion was detected in a series of 72 SRS patients displaying ICR1 loss of methylation. Similarly, investigation of a large series of 78 BWS with ICR2 loss of methylation did not identify any deletion.

Copy neutral CNVs

Copy neutral CNVs correspond to runs of homozygosity without any change in copy number. They might reflect uniparental isodisomy (UPiD) or autozygosity. UPiDs previously identified in BWS and SRS patients involve both ICR1 and ICR2 and display a mosaic pattern. The density of the SNP array and the availability of parental DNA for 60% of patients made possible the identification of segmental UPiDs. Analysis of the data for shift in B allele frequency for heterozygous SNPs (not centered at 0.5), associated with a normal log R ratio and mendelian inconsistency (when parental DNA was available) did not identify mosaic segmental UPiD in SRS or BWS patients with loss or gain of DNA methylation at either ICR1 or ICR2.

However, runs of homozygosity, ranging from 86 to 335 kb (156 to 592 29/7/11 probes) were identified in the various groups of patients and controls (Figure 5). Although runs of homozygosity were identified within the whole 11p15 region, two locations were overrepresented after analysis with the two softwares. The first region (position 2,170,000 to 2,270,000 bp), encompassing the paternally-imprinted ASCL2 gene, was homozygous in 17% of both patients and controls (Box A in Figure 5 and supplementary Table 2). The second region (position 2,270,000 to 2,370,000 bp), encompassing the C11ORF21 and TSPAN32 genes, was homozygous in 23% and 15% of patients and controls respectively (Box B in Figure 5 and supplementary Table 2).

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Discussion

Recent modifications to SNP arrays enhance the opportunity to discover

CNVs along with concomitant SNP genotypes. We designed a custom SNP array to target the analysis to the 11p15 region including the two imprinting control regions and investigate whether intermediate lesions (which cannot be recognized by routine diagnostic tools) account for a subset of 11p15 growth disorders with abnormal DNA methylation at either ICR1 or ICR2. A SNP array was favored to CGH array as it has the ability to (i) simultaneously measure both intensity differences and allelic ratios and therefore to investigate both DNA copy-number and copy-neutral variation and (ii) identify the parental origin of CNVs.

-We identified three novel duplications which have not been previously described.

Two duplications involved the IGF2/H19 domain. In the H47P BWS case, CGH showed that a 2 Mb deletion of the distal part of 11q was associated with an apparently de novo 2.4 Mb duplication of the whole IGF2/H19 domain on the paternal chromosome. FISH analysis of H47P and his parents demonstrated that H47P displayed recombination of a paternallyinherited pericentric inversion of chromosome 11, with a large inverted segment of approximately 130 Mb (i.e more than 95% of the chromosome). A few 11p pericentric inversions have been previously described [START_REF] Waziri | Abnormality of chromosome 11 in patients with features of Beckwith-Wiedemann syndrome[END_REF][START_REF] Stratakis | A syndrome of overgrowth and acromegaloidism with normal growth hormone secretion is associated with chromosome 11 pericentric inversion[END_REF][START_REF] Gadzicki | Jacobsen syndrome and Beckwith-Wiedemann syndrome caused by a parental pericentric inversion inv(11)(p15q24)[END_REF] , some of them with a predominant BWS phenotype [START_REF] Waziri | Abnormality of chromosome 11 in patients with features of Beckwith-Wiedemann syndrome[END_REF] .

Those previously described pericentric inversions led to the duplication of the whole 11p15 imprinted domain with breakpoints between 11p13 and 11p15.1. The H47P case is unique as the duplication of the short arm involves only part of the 11p15 imprinted region (i.e the IGF2/H19 domain). The deletion of 11q25 involves 10 genes and might account for the developmental delay.

The second duplication of the IGF2/H19 domain represents the first observation of a genetic abnormality within the IGF2/H19 domain in SRS.

The S72P cis-duplication involves only part of the IGF2/H19 domain (the imprinting control region and the H19 gene) and results in a SRS phenotype only if maternally-inherited when there is no phenotype upon paternal transmission. Both the parental transmission pattern and the 29/7/11 phenotype are different from previously reported ICR1 duplications [START_REF] Bliek | Phenotypic discordance upon paternal or maternal transmission of duplications of the 11p15 imprinted regions[END_REF][START_REF] Russo | Molecular and genomic characterisation of cryptic chromosomal alterations leading to paternal duplication of the 11p15.5 Beckwith-Wiedemann region[END_REF][START_REF] Algar | Paternally inherited submicroscopic duplication at 11p15.5 implicates insulin-like growth factor II in overgrowth and Wilms' tumorigenesis[END_REF] .

Cis-duplications (0.3 to 1.8 Mb in size) involving the whole IGF2/H19 domain have been previously reported in two familial [START_REF] Bliek | Phenotypic discordance upon paternal or maternal transmission of duplications of the 11p15 imprinted regions[END_REF][START_REF] Algar | Paternally inherited submicroscopic duplication at 11p15.5 implicates insulin-like growth factor II in overgrowth and Wilms' tumorigenesis[END_REF] and one sporadic [START_REF] Russo | Molecular and genomic characterisation of cryptic chromosomal alterations leading to paternal duplication of the 11p15.5 Beckwith-Wiedemann region[END_REF] BWS cases. They resulted in a BWS only if the paternal chromosome was involved. The main difference between the S72P duplication and other duplications of the IGF2/H19 domain ( [START_REF] Bliek | Phenotypic discordance upon paternal or maternal transmission of duplications of the 11p15 imprinted regions[END_REF][START_REF] Russo | Molecular and genomic characterisation of cryptic chromosomal alterations leading to paternal duplication of the 11p15.5 Beckwith-Wiedemann region[END_REF][START_REF] Algar | Paternally inherited submicroscopic duplication at 11p15.5 implicates insulin-like growth factor II in overgrowth and Wilms' tumorigenesis[END_REF] and the H47P case) is that the S72P duplication involves ICR1 and the H19 gene but does not involve the IGF2 gene. Hence, a partial maternal cisduplication of the IGF2/H19 domain results in a SRS phenotype (S72P case) whereas a maternal cis-duplication involving the whole IGF2/H19 domain does not result in any phenotype [START_REF] Bliek | Phenotypic discordance upon paternal or maternal transmission of duplications of the 11p15 imprinted regions[END_REF] (Supplementary figure 1).

Although two copies of the active maternal H19 gene are expressed in both cases, the chromatin organization is likely to be different. In the partial cis-duplication, one maternal H19 gene is not engaged in a ciseffect. It was recently shown that, apart from a cis-effect, the H19 noncoding RNA also regulates the expression of Igf2 by a transacting mechanism [START_REF] Gabory | H19 acts as a trans regulator of the imprinted gene network controlling growth in mice[END_REF] . Indeed, H19 transgenic expression is able to rescue the overgrowth phenotype of mice with targeted deletions of the H19 gene and also to reduce Igf2 expression [START_REF] Gabory | H19 acts as a trans regulator of the imprinted gene network controlling growth in mice[END_REF] . We hypothesize that an extra copy of a functional maternal H19 gene (not engaged in a cis-effect) can affect the expression of IGF2 by a transacting mechanism and result in growth retardation. Two deletions within or overlapping the S72P duplicated region have been registered as rare variations, in apparently normal subjects (http://projects.tcag.ca/variation/; variations 29891, 29893), but the parental origin of these deletions are not known.

The third duplication case is a familial BWS case with ICR2 loss of methylation, involving four affected subjects conceived from three phenotypically normal sisters. The pattern of transmission of this cisduplication supports its pathogenicity with no phenotype when the duplication is transmitted through the male germline and a BWS phenotype when the duplication is transmitted through the female germline. Moreover, the absence of the duplication in an unaffected subject born from a female carrier strengthens the significance of the duplication. Little is known on the centromeric 11p15 imprinting region 29/7/11 apart from the ICR2 imprinting control region. One deletion within the L65P duplicated region has been registered as a rare variation (http://projects.tcag.ca/variation/; variation 29897) but the parental origin of this deletion is not known. Nevertheless, the 50 kb cis-duplication region displays evidence of open chromatin and encompasses two CpG islands and three CTCF binding sites. Analysis of the DNA methylation status of the two CpG islands had not been previously documented. Those two CpG islands are not allele-specific differentially methylated in control subjects, with one being predominantly methylated and the other one unmethylated. In the patient displaying the cis-duplication, we showed that the pattern of DNA methylation was similar to the pattern of control subjects. The location of the duplication also corresponds to the centromeric breakpoint of a 1.8 Mb cis-duplication responsible for a BWS [START_REF] Russo | Molecular and genomic characterisation of cryptic chromosomal alterations leading to paternal duplication of the 11p15.5 Beckwith-Wiedemann region[END_REF] and the Tm87-16 rhabdoid tumor translocation breakpoint within BWSCR1 [START_REF] Lee | Human KVLQT1 gene shows tissue-specific imprinting and encompasses Beckwith-Wiedemann syndrome chromosomal rearrangements[END_REF][START_REF] Prawitt | Identification and characterization of MTR1, a novel gene with homology to melastatin (MLSN1) and the trp gene family located in the BWS-WT2 critical region on chromosome 11p15.5 and showing allele-specific expression[END_REF] . All together, this data strongly supports the relevance of the cis-duplication in the BWS phenotype and suggests that the cis-duplication affects the chromatin conformation and impairs the apposition and/or maintenance of DNA methylation at ICR2.

-Precise analysis of the two imprinting control regions (ICR1 and ICR2) led to the identification of new small deletions. Those deletions were only identified in BWS patients with ICR1 gain of methylation. As for previous identified deletions [START_REF] Demars | Analysis of the IGF2/H19 imprinting control region uncovers new genetic defects, including mutations of OCT-binding sequences, in patients with 11p15 fetal growth disorders[END_REF] , the deletion breakpoints in those new cases map repetitive sequences within the B repeats of ICR1, suggesting that these repetitive sequences within ICR1 promote the risk of deletion. No ICR1 deletions were identified in SRS patients with ICR1 loss of methylation and this agrees with previous publications which show the absence of phenotype upon paternal transmission of ICR1 deletions [START_REF] Sparago | Microdeletions in the human H19 DMR result in loss of IGF2 imprinting and Beckwith-Wiedemann syndrome[END_REF][START_REF] Sparago | Mechanisms causing imprinting defects in familial Beckwith-Wiedemann syndrome with Wilms' tumour[END_REF] . Moreover, we did not identify ICR2 deletions in this large series of BWS patients with ICR2 loss of methylation. Although ICR2 deletions (0.25 and 0.9 Mb) have been occasionally reported in BWS with loss of methylation at ICR2 [START_REF] Niemitz | Microdeletion of LIT1 in familial Beckwith-Wiedemann syndrome[END_REF]20 , the data presented here establishes that they are extremely rare.

-A major advantage of the SNP array is the possibility to combine detection of gain/loss CNVs with copy-neutral CNVs (runs of homozygosity). Such segments of homozygosity could represent 29/7/11 uniparental isodisomy or autozygosity. Uniparental isodisomy is a classical cause of BWS and accounts for 20 to 25% of BWS cases 5 9, 10 , whereas maternal isodisomy has been reported in only one SRS case [START_REF] Bullman | Mosaic maternal uniparental disomy of chromosome 11 in a patient with Silver-Russell syndrome[END_REF] . When the frequency of uniparental isodisomy is well established in BWS, its extent on chromosome 11 has not been extensively analyzed. In a recent study, Cooper et al. showed that the extent of isodisomy along chromosome 11 is variable but always involves the two 11p15.5 imprinted domains [START_REF] Cooper | Mitotic recombination and uniparental disomy in Beckwith-Wiedemann syndrome[END_REF] . In this study, we investigated for the first time whether smaller uniparental isodisomies, confined to one of the two 11p15 imprinted domains, might account for DNA methylation defects restricted to ICR1 or ICR2. Although we identified runs of homozygosity in BWS and SRS patients, the B allele frequency was not indicative of mosaicism and there was no mendelian inconsistency when parental DNA was available. This data shows that segmental uniparental isodisomies confined to the IGF2/H19 or the KCNQ1OT1/CDKN1C domains do not account for DNA methylation defects restricted to one of the two 11p15 imprinted domains.

In summary, investigation by SNP array of a large series of BWS and SRS patients with isolated ICR1 or ICR2 DNA methylation defects led to the identification of new molecular defects including novel segmental cisduplications in both SRS and BWS patients and new ICR1 deletions in BWS patients. This study also establishes, for the first time, that segmental uniparental isodisomies do not account for isolated ICR1 or ICR2 DNA methylation defects. We also demonstrate in a large series of BWS patients that ICR2 deletions are not a common mechanism for loss of methylation at ICR2. Our data also illustrates the difficulty of genetic counseling in patients with 11p15 related growth disorders. Indeed, in more than 50% of cases, the clinical presentation was sporadic rather than familial despite a maternallyinherited genetic defects. This study and a previous one [START_REF] Demars | Analysis of the IGF2/H19 imprinting control region uncovers new genetic defects, including mutations of OCT-binding sequences, in patients with 11p15 fetal growth disorders[END_REF] also emphasize that molecular defects in cis are more common than initially thought in BWS patients with ICR1 gain of methylation and affect at least 20% of cases.

Supplemental Data:

Supplemental Data include one figure and two tables and can be found

  Oligo Pool Assay (OPA) of 1536 SNPs covering the whole 11p15 29/7/11 region (location on chromosome 11: position 1,970,084-2,869,522, NCBI 36/hg18 assembly) and including the two imprinted domains was designed. To allow a high success rate of genotyping, only SNPs with an Illumina SNP_score >0.6 were selected among the 6214 polymorphisms present in dbSNP130 and located in the region of interest. SNPs already genotyped in the HapMap CEU population (our disease panel consists mostly of European individuals) were preferentially chosen. They represent 648 SNPs out of the 1536 final dataset. We selected SNPs dispersed homogenously along the domain with a final density of 1 to 3 probes per kilobase. Moreover, regions corresponding to the two imprinting control regions (ICR1 and ICR2) were enriched with a density of one probe every 300 bp. The customized OPA was used to genotype patients, their parents and some of the family members as well as control samples on the iScan System (http://www.illumina.com) according to the manufacturer's protocol.

  ) was born after 40 weeks of a normal gestation from non consanguineous parents. The clinical presentation at birth included macroglossia, exomphalos, hypospadias, bilateral cryptorchidism, bilateral inguinal hernias, posterior helical pits and severe neonatal hypoglycemia. Patient L65P had no macrosomia at birth (birth weight 3200 gr, -0.6 SD) but then displayed advanced growth (+ 2.5 SD at the age of 5 years) with a final height at 196 cms (+ 2.8 SD). The familial history includes three other cases. The first pregnancy of individual II.1 was complicated at five months of gestation by acute hydramnios resulting in fetal death. Pathologic findings of the male fetus (III.1) included exomphalos, adrenal cytomegaly and leydigian hyperplasia. A second pregnancy was terminated after 25 weeks of gestation after ultrasound examination showed an exomphalos. The first pregnancy of individual II.4 was also terminated after 18 weeks of gestation after ultrasound diagnosis of exomphalos. Pathologic findings of the female fetus (III.8) included exomphalos, adrenal cytomegaly and ovarian hyperplasia. A second pregnancy resulted in spontaneous abortion at 9 weeks. Analysis of the 11p15 region showed a complete loss of methylation at ICR2 in patient III.7 whereas the ICR2 methylation status in the mother (II.3) and her two sisters (II.1 and II.4), obligate carriers, was normal (Figure

Figure 1 :

 1 Figures titles and legends:Figure 1: ICR1 duplication resulting from recombination of a paternal pericentric inversion in a BWS patient with ICR1 gain of methylation (A) Graphical overview of B allele frequency and log R Ratio obtained from the SNP array in H47P and his parents, showing a duplication of the IGF2/H19 domain in H47P. The location of the duplication is highlighted by the grey box. (B) Genomic real-time PCR quantification assay at various loci along the IGF2/H19 domain validating the duplication. (C) Sequencing at various informative SNPs within the duplication showing that the duplication involves the paternally-inherited allele. (D) Graphical overview of the results obtained from the array-CGH analysis of H47P, showing a distal 11p duplication and a distal 11q deletion. (E) FISH analysis with subtelomeric probes for 11p (green) and 11q (red). The normal chromosome 11 has one green and one red signal for 11p and 11q, respectively. In H47P, the recombinant chromosome 11 [rec(11) dup p inv(11)] has green signals for 11p on both ends and no red signal. In H47P's father, the inverted chromosome 11 [inv(11) p15.5q25] has a red signal on 11p and a green signal on 11q. Small white arrows indicate the centromeres.

Figure 2 :

 2 Figure 2: Familial ICR1 duplication in a SRS patient with ICR1 loss of methylation (A) Pedigree of the S72P SRS case. (B) Graphical overview of B allele frequency and log R Ratio obtained from the SNP array in S72P and her parents, showing a maternally-inherited segmental duplication of part of the IGF2/H19 domain in S72P. The location of the duplication is highlighted by the grey box. (C) Genomic real-time PCR quantification assay at various loci along the IGF2/H19 domain validating the duplication in S72P and her mother. (D) Graphical overview of the results obtained from the array-CGH analysis of S72P. The duplication interval (from 1,530,602 to 2,092,578 bp) is underlined with the pink rectangle. (E) Partial metaphases of patient S72P. FISH with the BAC probe RP11-295K3 within the duplication shows an increased hybridization signal (green signal) on one of the chromosomes 11 (arrow) when the signal with the BAC probe RP3-416J11 outside the duplication (red signal) is similar

Figure 3 :

 3 Figure 3: Familial ICR2 BWS case (A) Pedigree of the familial BWS case and segregation. Subjects identified with the duplication are indicated with a star. SB: stillbirth. (B) DNA methylation at ICR2, assayed by methyl-sensitive Southern blotting using genomic DNA from the indicated individuals. The upper band (6 kb) is methylated and corresponds to the maternal allele. The lower band (4.2 kb) is unmethylated and corresponds to the paternal (ICR2) allele. (C) Graphical overview of log R Ratio results obtained from the SNP array in L65P (III.7), his mother (II.3) and maternal grandmother (I.1), showing a maternally-inherited duplication in L65P and his mother. The location of the duplication is highlighted by the grey box. (D) Genomic real-time PCR quantification assay at several loci along the ICR2 domain validating the duplication. (E) DNA methylation profiles of the two CpG islands included in the cis-duplication determined by bisulfite sequencing in a control subject, the propositus (L65P/III.7), his mother (II.3) and maternal grandmother (I.1). Each line corresponds to an individual cloned DNA fragment and each circle represents a CpG dinucleotide. Methylated CpGs are indicated by filled circles and unmethylated CpGs by open circles. Parental alleles were distinguished by the rs179436 nucleotide polymorphism for the 2,510,680-2,510,907 CpG island and the rs2074247 nucleotide polymorphism for the 2,511,982-2,512,194 CpG island. The 16 and 17 CpG islands are framed.

  Fig 3

Table 1 :

 1 Clinical and molecular features of patients with Beckwith-

	Wiedemann syndrome
		BWS with ICR2	BWS with ICR1
		loss of methylation	gain of methylation
	n	78	35
	sex F/M	36/42	17/18
	gestational age a , weeks mean ± SD; (range) 36.2 ± 3.2 (27-41)	36.7 ± 3.1 (30-40)
	ART, n	9	1
	monozygotic twins	7	0
	fetal cases	6	3
	familial cases	1	4 c
	phenotype
	macrosomia at birth b , n (%)	31/65 (48%)	24/35 (69%)
	birth weight (SDS)	1.7 ± 1.6	2.8 ± 1.9
	macroglossia, n (%)	75/77 (97.5%)	31/33 (94%)
	abdominal wall defect, n (%)	54/77 (70%)	20/32 (62%)
	diastasis recti, n (%)	4	12
	umbilical hernia, n (%)	21	7
	exomphalos, n (%)	29	1
	organomegaly, n (%)	33/69 (48%)	24/32 (75%)
	body asymmetry, n (%)	20/71 (28%)	12/33 (36%)
	hypoglycaemia, n (%)	26/63 (41%)	9/30 (30%)
	ear abnormalities, n (%)	54/74 (73%)	9/30 (30%)
	tumour, n (%)	0/71 (0%)	8/32 (25%) d
	others
	ICR1 MI, mean ± (SD)	52.8 ± 4.1	76 ± 10.3
	(N=53.9 ± 2%)
	ICR2 MI, mean ± (SD)	8.5 ± 7.7	47.9 ± 3.8
	(N=51.6 ± 2.5%)
	parental DNA, n(%)	62/78 (79.5%)	18/35 (51%)
	Both parents	57	14
	One parent	5	4
	a: gestational age is in weeks of amenorrhea
	b: twins not included
	c: 4 subjects from 2 families (two siblings in one family and a son and his
	mother in the other family)
	d: all tumors were Wilms tumors
	ART: assisted reproductive technology; MI: methylation index

Table 2 :

 2 Clinical and molecular features of patients with Silver-Russell syndrome

		SRS with ICR1
		loss of methylation
	n	72
	sex F/M	25/47
	gestational age a , weeks	38.2 ± 2
	ART, n	6
	monozygotic twins	3
	phenotype
	IUGR, n (%)	66/68 (97%)
	birth weight (SDS) b	-3.1 ± 0.7
	post-natal growth retardation, n (%)	61/64 (95%)
	relative macrocephaly at birth, n (%)	59/62 (95%)
	facial dysmorphy, n (%)	49/57 (86%)
	body asymmetry, n (%)	51/68 (75%)
	feeding difficulties, n (%)	47/63 (75%)
	severe, n	16
	moderate, n	31
	BMI (SDS) BMI ≤ -2 SDS developmental delay, n (%)	-2.2 ± 1.1 40/59 (69%) 9/57 (16%)
	clinodactyly, n (%)	51/61 (84%)
	others
	ICR1 MI, mean ± (SD)	23 ± 8.3
	(N=53.9 ± 2%)
	ICR2 MI, mean ± (SD)	47.6 ± 4.1
	(N=51.6 ± 2.5%)
	parental DNA, n(%)	30 (39%)
	both parents	22
	one parent	8
	a: gestational age is in weeks of amenorrhea
	b: twins not included
	ART: assisted reproductive technology; IUGR: intrauterine growth retardation;
	MI: methylation index

Table 3 :

 3 Copy number variations detected in SRS and BWS patients with cnvPartition v2.4.4 and QuantiSNP v2.3 softwares

	patients	patients' group	CNV type	origin	parental	size	markers	detection cnvPartition/	detection QuantiSNP /	qPCR
					chromosome	kb	n	confidence score	Log Bayes Factor	validation
	H4P	BWS ICR1	duplicatio	NA*	/	22	15	yes/45.74	no	no
			n
	H47P	BWS ICR1	duplicatio	de novo	paternal	400**	526	yes/1900.99	yes/30.33	yes
			n
	L65P	BWS ICR2	duplicatio	inherited	maternal	50	78	yes/232.11	yes/63.94	yes
			n
	L263P	BWS ICR2	deletion	de novo	maternal	4.4	3	yes/73.93	no	no
	S63P	SRS ICR1	deletion	de novo	paternal	4	3	yes/230.73	no	no
	S72P	SRS ICR1	duplicatio	inherited	maternal	80**	89	yes/398.29	yes/44.24	yes
			n
	* NA: parental DNA not available
	** These CNVs include the most telomeric probe of the OPA.
	BWS ICR1: BWS patients with ICR1 gain of methylation. BWS ICR2: BWS patients with ICR2 loss of methylation. SRS ICR1:
	SRS patients with ICR1 loss of methylation.

Table 4 :

 4 Characterization of ICR1 deletions in BWS patients with ICR1 gain of methylation

		familial history	size (bp)	breakpoints	fused repeats	deleted CTCF
						binding sites
	H32P	no	1834	1978828-1978846/1980662-1980680	B6/B3	2, 3
	H50P	no	1834	1978576-1978605 /1980411-1980431	B6/B3	3, 4
	H63P	yes	2240	1978248 -1978293/1980488-1980533	B6/B2	2, 3, 4
	* Genomic positions were assigned according to the data provided by the UCSC genome browser (hg18, NCBI 36)

Acknowledgments:

We thank Annick Blaise for her technical assistance and the physicians for patients' referrals and collection of clinical data. We are grateful to the willingness of the patients and their families to contribute to this study.

Funding: This work was supported by the National Health and Medical Research Council of Australia (Project grant 472637), the Baker IDI Heart and Diabetes Institute, the Institut National de la Santé et de la Recherche Médicale UMPC U938, Université Pierre et Marie Curie Paris 6 and Assistance Publique Hopitaux de Paris.

Conflict of interest statement. None declared.

Web Resources:

The URLs for data presented herein are as follows: Supplementary figure 1: Schematic diagram of the 11p15 region with a summary of the duplications identified in the cohort and duplications previously described [START_REF] Bliek | Phenotypic discordance upon paternal or maternal transmission of duplications of the 11p15 imprinted regions[END_REF][START_REF] Russo | Molecular and genomic characterisation of cryptic chromosomal alterations leading to paternal duplication of the 11p15.5 Beckwith-Wiedemann region[END_REF][START_REF] Algar | Paternally inherited submicroscopic duplication at 11p15.5 implicates insulin-like growth factor II in overgrowth and Wilms' tumorigenesis[END_REF][START_REF] Schonherr | Runs of homozygosity detected in control subjects and patients Sample id. Start Position (bp) End Position (bp) Length (bp) Probes (n) Score Max[END_REF] . no phenotype no BWS H47P duplication involving the paternal chromosome BWS [START_REF] Russo | Molecular and genomic characterisation of cryptic chromosomal alterations leading to paternal duplication of the 11p15.5 Beckwith-Wiedemann region[END_REF] Suppl fig 1

Position (Mb)


Michèle Pijolat

Stéphane Perrin

Françoise Valdivieso

Eric Touboul

Michel Soustelle

Kais Nahdi

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Modélisation cinétique non isotherme de la déshydroxylation de la kaolinite

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Cédric Buche
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Pierre De Loor
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Generic Model for Experimenting and Using a Family of Classifiers Systems: Description and Basic Applications

Classifiers systems are tools adapted to learn interactions between autonomous agents and their environments. However, there are many kinds of classifiers systems which differ in subtle technical ways. This article presents a generic model (called GEMEAU) that is common to the major kinds of classifiers systems. GEMEAU was developed for different simple applications which are also described.

1 GEMEAU: GEneric Model for Experimenting And Using a family of classifiers systems.

Introduction

Defining the behavior of autonomous artificial entities is faced with the problem of selecting a model able to account for the link between perceptions and actions in an efficient manner. There are a great number of proposed solutions to this issue. However, they require detailed descriptions which are difficult to achieve, either because they require a definition based on a priori rules and symbols [START_REF] Carver | The evolution of blackboard control architectures[END_REF][START_REF] Mateas | An Oz-centric review of interactive drama and believable agents[END_REF], or because they are subject to configuration difficulties and behavioral indeterminism [START_REF] Brooks | Elephants don't play chess[END_REF][START_REF] Maes | The dynamics of action selection[END_REF]. Another solution would be to define the entities' initial approximate behavior, which would then adapt according to its environment. This solution is implemented by classifiers systems. It uses a set of competing rules and incorporates learning processes by choosing and improving these rules. A great deal of literature exists on the subject [START_REF] Cliff | Adding Temporary Memory to ZCS[END_REF][START_REF] Stolzmann | Anticipatory classifier systems[END_REF][START_REF] Lanzi | Optimal classifier system performance in non-Markov environments[END_REF][START_REF] Tomlinson | A zeroth level corporate classifier system[END_REF][START_REF] Sigaud | Learning classifier systems: A survey[END_REF]. A number of authors have put forward different variations of the approach, each offering different mechanisms adapted to specific problems. Our objective is to be able to test and advance these mechanisms without difficulty, consequently we are interested in designing and implementing a generic model. This article is organized as following: first we present the general mechanisms of classifiers system. We then go on to present a generic model, called GEMEAU 1 , which integrates these mechanisms, and with which we can easily test different versions. Next we explain how we applied this model to different types of applications: multiplexers and woods environments.

Classifiers Systems

Principles

A classifiers system is an adaptive system that learns to perform the best action given its input. The system manage a combination of "condition-action" rules called classifiers, pondered by quality parameters. The system perceives its environment (usually a vector of numerical values), deduces the applicable rules, carries out an action as a result of these rules. Technically, when a particular input occurs, classifiers whose conditions are satisfied by that input are selected and the system chooses one of the possible actions (from selected rules) according to the quality parameters. The system is able to receive a reward from the environment which it then uses to modify the rules or their quality parameters.

Through experimentation, classifiers system can therefore be used to learn the association between conditions and actions, thus maximizing credit intake. In order to avoid a combinatorial explosion of the quantity of rules, they are generalized; they apply to different perceptions of the environment. Mechanisms which allow the creation, enrichment (specialization/generalization), or destruction of these rules must therefore be used. Evolutionary algorithms are often used to do this, even though other heuristic approaches are available. The qualities of the rules are modified dynamically through reinforcement learning, and the rules themselves are modified by genetic algorithms.

Formalization

In this section we propose the incremental and generic formalization of classifiers systems, and gradually introduce learning mechanisms.

The global structure of a classifier system, is a 7-uplet (Ii, [P], [M], [A], Matching, Selection, Io) :

-Ii is the interface input due to which each Perception within the environment corresponds to a binary code. -[P], (population), is the set of the system's classifiers, coded by a succession of n bits2 . The generalizing representations contain # symbols which correspond to an indeterminate value. A rule is a (C, A) pair with C ∪ A ∈ {0, 1, #} n where :

• C : the condition for application of the rule.

• A : the action(s) associated with the application of the rule. Let us take the example of a robot with four 'all-or-nothing' sensors and one action. The input interface converts the state of the sensors into a binary value and the output interface triggers the action depending on the action's bit value. Thus, a {011#, 1} rule means that the rule is applicable if the first sensor is inactive and the two following sensors active. The state of the fourth sensor has no influence, and applying the rule triggers the action.

-[M] ⊆ [P] is the set of classifiers of which the condition element pairs with the perceived environmental information during a selection cycle. This is known as Match-set.

-[A] ⊆ [M]
is the set of classifiers representing the selected action. This is known as Action-set. -Matching is the mechanism which makes the transition from [P] to [M] possible. This is generally achieved using a matching rule between C and the information derived from Ii. This rule is able to interpret the generalization symbols that make up the classifier conditions. -Selection is the mechanism which makes the transition from [M] to [A] possible. Depending on the details of the different versions of classifiers systems, it is able to determine the desired action. -Io is the output interface through which the activated Action corresponds to a binary code.

Learning occurs due to an evaluation of the quality of the rules represented by one or a number of additional parameters. The definition of a classifier is thus extended to a R = (C, A, f ) triplet where f characterizes its quality. Learning developed by Rewarding the rules, by altering their quality using reinforcement learning algorithms and by Generating rules using evolutionary and heuristic covering algorithms. The dynamics of learning classifiers systems are therefore based on the following cycle:

Perception / Matching / Generation (covering) / Selection / Action / Reward / Generation (evolutionary algorithm).
Selection is guided by the quality of the rules, which are grouped together depending on their [A] element. Often, a 'wheel of fortune' mechanism 3 is applied, which means that each package has a probability proportional to its capacity to be selected. The credit assignment (Reward) mechanism distributes credit to the rules that have contributed to its acquisition. It increases the quality of the rules triggered prior to the acquisition of the credit and decreases that of the others. Its definition affects the relevant length of a series of actions: i.e. the number of rules in a sequence considered necessary in order to achieve a certain goal. The generation mechanism must both minimize the number of rules and conserve those which assist in achieving credit. A good rule is therefore a high-quality generalizing rule (relative to the others). The two generation (rules discovery) mechanisms used are covering (creation of rules when no classifiers match the perception of the environment) and evolutionary algorithms.

GEMEAU

Classical classifiers systems (ZCS, XCS, ACS, Hierachichal ...) [START_REF] Wilson | ZCS: A zeroth level classifier system[END_REF][START_REF] Wilson | Classifier Fitness Based on Accuracy[END_REF][START_REF] Stolzmann | Anticipatory classifier systems[END_REF][START_REF] Dorigo | Alecsys and the AutonoMouse: Learning to Control a Real Robot by Distributed Classifier Systems[END_REF] go some way to finding optimal solutions in Markovian or non-Markovian environments. Nevertheless, as Sanza notes [START_REF] Sanza | Evolution and cooperation of virtual entities with classifier systems[END_REF], the improvements and supplementary systems are suitable only for specific cases and none of the models are able to supply an overall solution for all of the problems (XCS is only effective if the credits are discrete and of a fixed quantity; ACS is only useful if each action leads to a modification in the perception of the world ...).

There are, therefore, a great number of classifiers systems [START_REF] Urbanowicz | Learning classifier systems: A complete introduction, review, and roadmap[END_REF]. Developing and testing a variety of such systems take time and is not easy. Using the structure and dynamics analysis conducted previously we were able to come up with a generic background for a whole family of classifiers systems. Our architecture claims to be generic, in the sense that it can be used to implement ZCS and XCS systems (ZCS, XCS, ZCSM, XCSM).

Architecture

The architecture is displayed in Fig. 1 as a UML classes diagram. The system is called GEMEAU. It is based around two components: interface with the environment and system.

The interface with the environment determines the interactions between the system and environment, both of which are common to different classifiers systems. In our model, the different interfaces are implemented using three categories: CS II, CS IO and CS R (respectively entry interface, output interface and credit). Communication between the interfaces and the environment takes place in the form of messages, enabling the classifiers system to have an implementation in parallel to the environment.

The System defines the elements and the mechanisms of our classifiers system in concrete terms. Let us consider the following elements: We put forward the following mechanisms:

-A classifier (CS Classifier)
-The Matching mechanism, with which the classifiers that match the information coming from the environment can be extracted. It is included in the CS Classifier List by the match() method; -The Generation mechanism by covering, which creates rules according to the content of [M] after Matching. It is included in the CS ClassifierList by the cover() method which can be configured (notably for the number of #); -The general (CS System) method represents the workings of a given cycle (step() method); -The Selection mechanisms of the winning (CS SelectorAlgo) actions (which must be able to differ according to the desired learning); -The Reward mechanism, (CS AOCAlgo), modifying the classifiers' configuration.

-The Generation genetic algoritm, (CS GeneticAlgo), where different operators must be specified, i.e. crossing or mutation.

Use

GEMEAU can be specialized in order to obtain a ZCS (Fig. 1). Through inheritance, we can define: The rest of the system uses the pre-existing default mechanisms such as covering. We implemented the XCS classifier system using the same techniques. In order to do so, we must overdefine CS Parameter.

We can also easily add memory to ZCS in order to obtain a ZCSM [START_REF] Cliff | Adding Temporary Memory to ZCS[END_REF]. In that case, we must increase the result of perception using an internal classifier system register which is modified by part of the last action to have been carried out. Using GEMEAU, the step() method can be redefined simply by inheriting from the CS System. We implemented the XCSM classifier system using these same principles.

By using these specialization and extension mechanisms we were able to use our architecture to implement and test ZCS and XCS family classifiers systems (ZCS, ZCSM, XCS, XCSM). Our perspectives are based on the implementation of supplementary traditional anticipatory or hierarchical systems (ACS: anticipation [START_REF] Stolzmann | Anticipatory classifier systems[END_REF] and ALECSYS: hierarchy [START_REF] Dorigo | Alecsys and the AutonoMouse: Learning to Control a Real Robot by Distributed Classifier Systems[END_REF]). Implementing these systems could well be less simple that for the family of ZCS and XCS, and the architecture may need to be modified.

Validation

One simple and frequently used evaluation environment is a multiplexer. Let us consider a multiplexer with an input of 6 bits a 0 , a 1 , d 0 , d 1 , d 2 , d 3 and an output of one bit. a 0 and a 1 correspond to address bits. The multiplexer equation is output = a 0 .a 1 .d 0 + a 0 .a 1 .d 1 + a 0 .a 1 .d 2 + a 0 .a 1 .d 3 . The output will be either the value of d 0 , d 1 , d 2 or d 3 , depending on the address. The aim is to find this multiplexing function.

Using GEMEAU, we must simply determine the detectors and effectors that interface with the environment the reinforcement to be distributed, and then instantiate a CS System (Fig. 2). The conditions and actions of the classifiers here correspond to the multiplexer's input and output respectively. The classifier system is rewarded when the rule selected corresponds to the multiplexing function. Another advantageous evaluation environment is the woods environment. It corresponds to a graphical representation based on an infinitely repeating pattern. It represents a forest and the aim of a situated agent is to find food. Within this forest there are insurmountable obstacles (trees) and areas of unrestricted movement. The perception of the agent corresponds to a representation of the 8 squares surrounding the occupied position. The simplest of these environments is woods1 (Fig. 3a). This is a deterministic Markovian environment 4 The woods100 (Fig. 3b), however, is non-Markovian. Indeed the optimum displacement from square number 2 is to the right although for square number 5 it is to the left even though these two squares are perceived identically.

The system learns by alternating between an iteration in exploration mode (selecting the action using the 'wheel of fortune' mechanism) and an iteration in exploitation mode (choosing the best action). The curves only take into account the results in exploitation mode, dealing with the average of the last ten iterations.

GEMEAU can deal with this two classical examples, it converges for the multiplexer (Fig. 4a) and for woods1 (Fig. 4b). For the multiplexer, we achieve a 100% success 4 There are no perceptions values corresponding to different states of the agent. rate. For woods1, we achieve solutions similar to the minimum number of movements. The results are conclusive: in both cases we reported performances similar to those described in the results of [START_REF] Wilson | ZCS: A zeroth level classifier system[END_REF]. Furthermore GEMEAU allows the rapid evaluation of derived classifier systems. We compared the ZCS and ZCSM results in the woods100 non-Markovian environment (Fig. 4c). Our results rediscover the ZCS' difficulties obtaining optimal rules in non-Markovian environments. They also confirm that our architecture can be used to extend the capacities of ZCS to non-Markovian environments.

Conclusion

Having described existing classifiers systems, we illustrated a more general classifiers system which groups together the traditional systems. We put forward our model called GEMEAU enabling traditional systems and their variants to be both modelled and extended. This implementation is flexible enough to be used for a variety of problems as it proposes an interface between the environment and the classifier system (input/output/reinforcement). It has been used to test many types of classifiers systems and different conceptual hypotheses quickly, as well as to obtain significant comparative results. Among other things, these tests showed us the interest of being able to access a library of classifiers systems with which we should be able to define a methodology for choosing learning algorithms based on certain stages of the tests.

  is made up of several parts: condition (CS Condition), action (CS Action) and configuration (CS Parameter); -The sets [P],[M],[A] and [A] -1 are lists of CS ClassifierList-type classifiers.

Fig. 1 .

 1 Fig. 1. UML diagram of GEMEAU augmented by a ZCS using inheritance

Fig. 2 .

 2 Fig. 2. Use of GEMEAU for a multiplexer-type environment

Fig. 3 .Fig. 4 .

 34 Fig. 3. Markovian woods1 (a) and non-Markovian woods100 (b) environments

Even if certain systems work with other alphabets[START_REF] Matteucci | Fuzzy learning classifier system: Issues and architecture[END_REF][START_REF] Wilson | Get real! XCS with continuous-valued inputs[END_REF][START_REF] Heguy | GXCS: A generic classifier system and its application in a real time cooperative behavior simulations[END_REF].

The wheel of fortune mechanism consists of picking elements randomly, so that their probability of being chosen is proportional to their selectivity.


Lise Crevier-Buchman

Cédric Gendrot

Bruce Denby

Claire Pillot-Loiseau

Pierre Roussel

Antonia Colazo-Simon

Gérard Dreyfus

ARTICULATORY STRATEGIES FOR LIP AND TONGUE MOVEMENTS IN SILENT VERSUS VOCALIZED SPEECH

Keywords: Silent speech, articulation, labial imaging, ultrasound imaging, tongue movement

In the context of Silent Speech Communication (SSC) development after total laryngectomy rehabilitation, tongue and lip movements were recorded with a portable ultrasound transducer and a CCD video camera respectively. A list of 60 French minimal-pairs and a list of 50 most frequent French words were pronounced in vocalized and silent mode by one speaker. Amplitude and timing of the articulatory movements were measured and compared in the two modes. This study showed for silent speech, i) a reduced duration of words, ii) a general hypoarticulation for lips, but non significant changes for tongue movements depending on the type of vowel and consonant.

INTRODUCTION

Silent Speech Communication (SSC) is an emerging technology intended to enable speech communication in the absence of an intelligible acoustic signal [START_REF] Denby | Silent speech interfaces[END_REF][START_REF] Fagan | Development of a (silent) speech recognition system for patients following laryngectomy[END_REF]. Silent Speech Interface (SSI) devices aim to recognize speech from non-audible signals captured through multisensors placed externally on different parts of the vocal tract. They intend to capture articulatory movements such as lip and tongue movements and resituate appropriate signals for oral communication. Different applications could be proposed such as an alternative voice for total laryngectomized patients. Recent studies [START_REF] Florescu | Silent vs Vocalized Articulation for a Portable Ultrasound-Based Silent Speech Interface[END_REF][START_REF] Hueber | Development of a Silent Speech Interface Driven by Ultrasound and Optical Images of the Tongue and Lips[END_REF] have proposed a portable system analyzing in near real time the tongue and lip movements captured by an Ultrasound (US) transducer and a video camera, respectively. It could be interesting to understand on a phonetic level the articulatory differences between normal and SSC speech, to improve recognition performance in the case of SSC, to help and guide rehabilitation to allow patients after total laryngectomy to use efficiently a future SSI after total laryngectomy; to improve recognizersynthesizer system by better understanding some articulation similarities that are not visible for SSI, and articulatory strategies that are different between vocalized and silent speech; to contribute to a better understanding of some confusion that can occur in SSI and to better train the accuracy of a recognizer-synthesizer system for communication in silent conditions.

The phonetic aspects and specificities of SSC are challenging research fields. Many studies have been conducted to characterize whispered speech [START_REF] Higashikawa | Lip Kinematics for /p/ and /b/ Production during Whispered and Voiced Speech[END_REF] but silent speech is a quite new field. In silent speech, the phonological feature [+ voice] cannot be realized at the glottis level as there are no laryngeal activities with any vocal fold vibration. Furthermore, there is no build-up of pressure as there is no airflow passing through the glottis. Therefore, vowel and consonant contrasts depend on articulators such as the jaw, the tongue and the lip movements. [START_REF] Stevens | Articulatory-acoustic-auditory relationships[END_REF]. Our study aimed to characterize the difference in duration and amplitude parameters of tongue and lip articulation movements for 44 monosyllabic and 29 disyllabic words in silent and vocalized mode.

SPEECH DATA ACQUISITION

For tongue and speech investigation, different ultrasound devices have been described [START_REF] Florescu | Silent vs Vocalized Articulation for a Portable Ultrasound-Based Silent Speech Interface[END_REF]. A portable multisensor system as compared to a fixed one has fewer constraints for the speaker and is closer to the actual situation that would be offered to voice-handicapped patients.

Our subject was a 50-years-old French native female with no known articulation problems.

Corpus

The non-verbal signals used for SSI such as lips and tongue movements may lead to certain confusion predominantly for labial and lingual look-alike phonems.

• Therefore we selected a list of 60 minimal pairs with 3 vowel-position in the word (initial, intervocalic and final position such as:

Recording material

An industrial CCD video camera from The Imaging Source, with a 60 fps, fitted with a LED ring light to capture lip movements in a frontal position was used.

The ultrasound (US) system is the lightweight t3000™ developed by Terason, using an 8MC4 microconvex transducer (opening angle: 140°, frequency range: 4-8 MHz) at 60 fps.

The audio signal (16 KHz, 16 bits) was recorded with a head-mounted microphone. It was placed at a constant 5 cm distance from the speaker's lips. This recording was used to confirm the absence of any voicing during silent speech.

A helmet-based system (Fig. 1), described in [START_REF] Hueber | Acquisition of ultrasound, video and acoustic speech data for a silent-speech interface application[END_REF] was used for our recordings. The helmet is commercialized by Articulate Instruments Ltd. [START_REF] Wrench | Evaluation of a helmet to hold an ultrasound probe[END_REF] and was used to stabilize the ultrasound probe to maintain close contact perpendicular to the mouth floor and the hard palate. In order to also acquire frontal lip video images, the CCD camera and LED ring were placed on a small horizontal platform attached to the anterior part of the helmet by a pair of adjustable slides, as shown in Fig. 1. The system maintains the ultrasound probe and the camera in a stable and fixed position, without restricting head movement.

Recording started by defining a rest position for the tongue, flat in the mouth, and for the lips slightly opened. Each word started from this rest position and ended the same way. This was to avoid confusion that might have occurred with bilabial consonants in initial or final position.

To prevent speaker fatigue, the acquisition procedure was split into 3 sessions each separated by a 15 min. pause. The helmet was removed and the speaker was able to move around. Each session was represented by the reading of the 2 lists in the 2 modes and lasted about one hour. After each break, before restarting the recordings, a recalibration was done for tongue and lip rest position. Ultraspeech software: the 3 signals recorded from the US, the video camera and the microphone are controlled by a stand-alone dedicated graphical software interface called Ultraspeech [START_REF] Florescu | Silent vs Vocalized Articulation for a Portable Ultrasound-Based Silent Speech Interface[END_REF], allowing synchronous acquisition of the recorded visual signals along with the acoustic signal. After each acquisition, data are directly available as series of bitmaps for the image streams, and .wav files for the audio. Ultraspeech provides also an interactive intersession recalibration mechanism that allows recording of large audiovisual speech databases in multiple acquisition sessions. It was employed to maintain the positioning accuracy of the video sensors (camera and US) across all sessions.

Visual speech feature extraction

Lips

Movies were recorded for each word and individual pictures were extracted for analysis. A Matlab program was built-up in order to allow for analysis. On every other frame, points were placed manually in 6 reference places (Fig 2 ) to measure the external and internal opening, and the stretching-rounding of the lips and euclidean distances were then calculated (in pixels) between these points. Each word was composed of about 70 to 100 frames.

Tongue

Decomposition was used to extract visual speech features from the ultrasound images. In this technique, every second ultrasound image is measured. The images were measured with the software Edge Track and Matlab. After all reference points from the tongue movements were recorded, data were computed so as to measure the global height and frontness of the tongue for each word.

EXPERIMENTAL RESULTS

The words of each list were grouped depending on the number of syllables and the structure of the syllable: for the monosyllables, the first group was structured as V, C-V, V-C; the second group of monosyllables was CVC; the third group was represented by disyllables.

Six measures were analyzed: duration of the complete articulation of the word of each list calculated from the number of frames of the words, 3 parameters for the lip and 2 for the tongue, each of them in silent and vocalized mode. They were compared using two-way ANOVAS with mode (silence vs. speech) and words as predictors.

Monosyllable words (V, CV and VC)

They were statistically longer in the vocalized mode compared to the silent mode (t(1,24)=87, p=0).. The internal and external aperture was wider in vocalized speech (t(1,24)=21.6, p=0).

However, there was en exception for vowels such as [a, e, u, ɑ, ɛ, ɔ] where silent speech had a wider mouth opening, that could represents hyperarticulation. IN addition, vertical tongue movements were significantly wider in silent mode while horizontal movements were significantly wider in vocalized mode. Finally, lip rounding represented by the spread parameter was significantly higher in silent speech (t(1,24)=2.5, p=0.11).

Monosyllable words (CVC)

They were statistically longer in vocalized mode compared to silent mode (t(1,14)=88, p=0.0). Lips movements were significantly wider in vocalized speech compared to silent speech (t(1,14)=48, p=0.0). No difference was found for tongue movements (t(1,14)=0.8, p=0.37 and t(1,14)=0.008, p=0.92).

Disyllables words

We found the same results as above with significant difference between vocalized and silent speech for lip movements, with the vocalized words having greater amplitude. No difference was found for tongue movements. Words were statistically longer in vocalized mode compared to silent mode.

DISCUSSION AND CONCLUSIONS

The aim of this preliminary study was to identify articulatory strategies in silent speech compared to vocalized speech. The objective was to better understand possibilities and limitations of a SSI and to gain from our results, some recommendations for alaryngeal patients' rehabilitation. After total laryngectomy, there is no more laryngeal vibration and the situation is quite similar to that of silent speech. The absence of voicing features has to be replaced by other features produced in the vocal tract, manly the tongue and the lips in the oral cavity. To represent everyday speech we selected a restricted database composed of frequently used French words and minimal pairs for look-alike phoneme possible confusion. This database has significant limitation for a structured study at the level of segmental phonetics as we didn't control the vowel and consonant environment and contextual effects. Nevertheless, several conclusions can be addressed.

Word length

Regardless of word structure in our database, we found a general shortening of word length in silent speech. This is contrary to what has been found for whispered speech [START_REF] Jovicic | Acouustic Analysis of Consonants in Whispered Speech[END_REF].

Lips kinematics

Recent studies on Ultrasound-based SSI interface [START_REF] Fagan | Development of a (silent) speech recognition system for patients following laryngectomy[END_REF] showed the prevailing importance of tongue compared to lips for an imaging -based SSI. Furthermore, our results showed hypoarticulation movements of the lips in SSC compared to vocalized speech.

The presence of consonants (CVC) in the word seems to stabilize the lip articulation with reduced amplitude of articulatory movement in silent speech; on the contrary, vowels alone showed greater variability in the articulatory pattern when produced silently. One hypothesis could be related to the theory of degrees of freedom [START_REF] Stevens | Articulatory-acoustic-auditory relationships[END_REF] depending on the vocal tract shape; in the silent speech situation, the absence of a consonant in a monosyllable could deprive the mental image of the oral cavity during articulation. Understanding segmental particularities of silent speech should improve the accuracy of articulation rehabilitation for patients after total laryngectomy. Therefore, training patients to improve their articulatory behavior can improve their communication skills as well as the visual signal for SSI.

Tongue movements

When producing silent speech, in addition to the loss of auditory feedback, there is a loss of aerodynamic information and of intraoral pressure; the consequence is a modification of the adaptation of tongue gestures. For monosyllable (CVC) and disyllables, our results suggest a non-consistent behavior with no significant different movements during silent and vocalized speech. On the contrary, vertical movements are more pronounced in a vocalic or CV context for silent speech. No evident explanation has been proposed yet.

There is still considerable work to be carried out to shed light on silent speech articulatory strategies. A complete set of controlled phonemes would be necessary to outline a typology of this particular mode of communication and a larger population should be tested to circumvent individual variations.

  [aby] /[oby]; [sil]/[sal]; [kaʁa]/[kaʁo]. Words were represented by either monosyllables with vowel and consonant /V-C/, /C-V/, /CVC/ or disyllables. • A second list was constructed from the 50 most frequent French words according to the National Education Corpus [7]. In this list we selected 13 monosyllables with isolated vowels such as: [a, e, u, ɑ, ɛ, ɔ]. Each list was repeated 3 times using two types of articulation: (1) normal vocalized articulation and (2) silent articulation. Within each repetition, the 60 and 13 words of the corpus were pronounced individually. Each word is represented by between 70 to 120 video frames and 70 to 140 Ultrasound frames. Thus, the image database contains 73x2 words (vocalized + silent) repeated 3 times x 200 images/word (100 video+100 US) for a total of ~ 87,600 images.

Figure 1 :

 1 Figure 1: Helmet fixed on the head with camera mounted in front of the mouth, head-mounted microphone and US fixed under the chin.

Figure 2 :

 2 Figure 2: Picture of the lips at rest position taken with the video camera (60 fps), and the 6 points that served to determine on the vertical axis, the inner and extern aperture, and on the horizontal axis, the stretching between the commissural of the lips.

Figure 3 :

 3 Figure 3: UltraSound image of the tongue (left) and contours extracted with EdgeTrack software and Matlab program (right).

ACKNOWLEDGMENTS

This work was supported by the French National Research Agency (ANR) under contract numbers ANR-09-ETEC-005-01 and ANR-09-ETEC-005-02 REVOIX