Lucia Guidugli

Chiara Rugani

Grazia Lombardi

Paolo Aretini

Alvaro Galli

Maria Adelaide Caligo
email: m.caligo@med.unipi.it

A recombination-based method to characterize human BRCA1 missense variants

Keywords: Homologous Recombination, Non Homologous End Joining, Unclassified Variants, BRCA1, breast cancer, functional assay

Purpose. Many missense variants in BRCA1 are of unclear clinical significance. Functional and genetic approaches have been proposed for elucidating the clinical significance of such variants.

The purpose of the present study was to evaluate BRCA1 missense variants for their effect on both Homologous Recombination (HR) and Non Homologous End Joining (NHEJ).

Methods. HR frequency evaluation: HeLaG1 cells, containing a stably integrated plasmid that allows to measure HR events by gene conversion events were transfected with the pcDNA3β expression vector containing the BRCA1-wild type (BRCA1-WT) or the BRCA1-Unclassified Variants (BRCA1-UCVs).

The NHEJ was measured by a random plasmid integration assay.

Results. This assays suggested a BRCA1 involvement mainly in the NHEJ. As a matter of fact, the Y179C and the A1789T variant altered significantly the NHEJ activity as compared to the wild type, suggesting that they may be related to BRCA1 associated pathogenicity by affecting this function. The variants N550H and I1766S, and the mutation M1775R did not alter the NHEJ frequency. Conclusions. These data, beside proposing a method for the study of BRCA1 variants effect on HR and NHEJ, highlighted the need for a range of functional assays to be performed in order to identify variants with altered function.

INTRODUCTION

Breast cancer is the most common neoplasia in women and the second cause of death after cardiovascular diseases in the Western world. About 10% of breast cancer cases is inheritable and about 40% of those is caused by mutations in BRCA1 or BRCA2 genes.

BRCA1 is a tumor suppressor gene that encodes a nuclear protein involved in several cellular processes including DNA double strand break repair by Homologous Recombination (HR) and Non Homologous End Joining (NHEJ), cell cycle control, apoptosis and maintenance of the genomic stability [START_REF] Chen | Stable interaction between the products of the BRCA1 and BRCA2 tumor suppressor genes in mitotic and meiotic cells[END_REF][START_REF] Scully | Association of BRCA1 with RAD51 in mitotic and meiotic cells[END_REF][START_REF] Wu | The ubiquitin E3 ligase activity of BRCA1 and its biological functions[END_REF]. BRCA1 gene is highly polymorphic. Nonsense or frameshift BRCA1 mutations encoding truncated not functional proteins predispose women to early-onset breast and ovarian cancer. However, several missense variants of uncertain pathological significance have been identified.

A variety of predictive approaches have been reported to distinguish cancer-related variants from neutral polymorphisms. These methods are based on: the degree of conservation among species, the nature and position of amino acid substitution, the analysis of co-segregation pattern of the variant with disease in affected family members, the inactivation of the wild type allele either by loss of heterozygosity or by promoter hypermethylation in the tumor [START_REF] Goldgar | Integrated evaluation of DNA sequence variants of unknown clinical significance: Application to brca1 and brca2[END_REF][START_REF] Abkevich | Analysis of missense variation in human brca1 in the context of interspecific sequence variation[END_REF][START_REF] Mirkovic | Structurebased assessment of missense mutations in human BRCA1: implications for breast and ovarian cancer predisposition[END_REF]. Moreover, several functional assays biologically evaluating the variant effect on the ability of the protein to perform some of the key cellular functions, are currently used. They can potentially be used to predict whether the variant predisposes to disease or alternatively has no significant influence on cancer risk [START_REF] Couch | IARC Unclassified Genetic Variants Working Group (2008) Assessment of functional effects of unclassified genetic variants[END_REF].

In this study, we used two functional assays in HeLa cells that specifically evaluate the effect of the over-expression of the wild type or mutated BRCA1 on spontaneous HR and on random chromosomal integration of a linearized plasmid DNA, a subtype of non HR in order to better elucidate the clinical relevance of some BRCA1 unclassified variants.

There are several evidences of BRCA1 involvement in DNA double strand break repair by HR.

BRCA1 colocalizes with RAD51 protein into sub-nuclear complexes in mitotic cells and clinical mutations at the C-terminal BRCA1 BRCT domain disrupt the nuclear foci localization [START_REF] Scully | Association of BRCA1 with RAD51 in mitotic and meiotic cells[END_REF]. Moreover, BRCA1 deficient cells are highly sensitive to ionizing radiation and display chromosome instability [START_REF] Deng | Brca1: Cell cycle checkpoint, genetic instability, DNA damage response and cancer evolution[END_REF]. BRCA1 -/-mouse embryonic stem cells have impaired HR [START_REF] Hakem | The tumor suppressor gene brca1 is required for embryonic cellular proliferation in the mouse[END_REF]. On the other hand, even though BRCA1 binds in vitro and in vivo to Mre11//Rad50/Nbs1 complex [START_REF] Zhong | Association of brca1 with the hrad50-hmre11-p95 complex and the DNA damage response[END_REF], its role in NHEJ pathway has not been yet completely clarified. As a matter of fact the frequency of random plasmid integration in transiently BRCA1-wt transfected HCC1937 cells is significantly increased as compared to the parental cell line [START_REF] Bau | Breast cancer risk and the DNA double-strand break end-joining capacity of nonhomologous endjoining genes are affected by BRCA1[END_REF] whereas this phenomenon is also impaired in BRCA1 -/- mouse embryonic fibroblasts but contradictory results were obtained [10] [11,12].

In this study, we selected some missense variants from a mutational screening of 276 breast and/or ovarian cancer families. Four non synonymous variants, that localized in different BRCA1 functional domains, were identified as potentially deleterious and likely disrupting the gene function by using three predictive software: SIFT, Polyphen and Align-GVGD. These variants were the Y179C, the N550H, the I1766S and the A1789T. One known missense variant (M1775R), previously reported as deleterious mutation, was chosen as positive control. We evaluated the effect of the overexpression of the wild type or these mutated BRCA1 protein on spontaneous HR and NHEJ events in HeLa cells.

MATERIALS & METHODS

SAMPLES AND MUTATION SELECTION

DNA samples from 276 individuals belonging to 276 breast and/or ovarian cancer families, collected at the University Hospital of Pisa, were analyzed for BRCA1 and BRCA2 germline mutations using an automated DNA sequencer (ABI 3100; Applera-Applied Biosystems). We used the following selection criteria: 1) occurrence of two or more cases of breast and/or ovarian cancer in first or second degree relatives;

2) early onset of the disease;

3) occurrence of bilateral breast cancer or occurrence of breast and ovarian cancer in the same individual.

The screening revealed several known as well as novel Unclassified Variants (UCVs) localized across all the BRCA1 gene sequence. To identify non-synonymous amino acid changes likely to disrupt BRCA1 gene function three comparative evolutionary bioinformatic programs were used: Sorting Intolerant From Tolerant (SIFT); [START_REF] Ng | Sift: Predicting amino acid changes that affect protein function[END_REF]. http://blocks.fhcrc.org/sift/SIFT.html), Polymorphism Phenotyping (PolyPhen); [START_REF] Ramensky | Human non-synonymous snps: Server and survey[END_REF]; http://tux.embl-heidelberg.de/ramensky/pilyphen.cgi and Align-GVGD (http://agvgd.iarc.fr/alignments). [START_REF] Tavtigian | Comprehensive statistical study of 452 brca1 missense substitutions with classification of eight recurrent substitutions as neutral[END_REF].

Plasmids

To determine whether the expression of BRCA1 wild type or mutated affects homologous and non homologous recombination in human cells, we used pcDNA3-BRCA1 expression plasmid (a gift from David Livingston, Boston MA , USA ) [START_REF] Scully | Association of BRCA1 with RAD51 in mitotic and meiotic cells[END_REF]. In this vector, the  globin gene was inserted in order to optimise the expression of BRCA1 [START_REF] Scully | Association of BRCA1 with RAD51 in mitotic and meiotic cells[END_REF]. To express the BRCA1 missense variant Y179C, N550H, A1789T and I1766S and the pathogenic control M1775R, we constructed the corresponding pcDNA3-BRCA1 derivative vector by site specific mutagenesis using the QuikChange II XL Site-Directed Mutagenesis Kit (Stratagene Inc) following the protocol recommended by the manufacturer. To measure the effect of the expression of BRCA1wt or mutated on random plasmid integration we used the plasmid pBlue-puro (a kind gift from Roland Kanaar, Erasmus University, Rotterdam, NL) that contains the puromycin resistance gene driven by cytomegalovirus promoter.

CELL CULTURE AND TRANSFECTION

HeLaG1 and HeLa cell line was routinely cultured in Dulbecco's modified Eagle's medium, DMEM (GIBCO), supplemented with 10% (v/v) fetal calf serum, 100 units/ml penicillin and 100 mg/ml streptomycin (GIBCO). Cultures were incubated at 37°C in 5% CO2 and 95% relative humidity. Transfections were performed using Lipofectamine 2000 (Invitrogen) according to the manufacturer's protocol. The efficiency of transfection was determined using the pGFP plasmid (a gift from Giuseppe Rainaldi, Pisa Italy) followed by direct count of GFP positive cells by FACS analysis (Becton Dickinson Biosciences). Usually, the efficiency of transfection was ranging from 70-85%.

IMMUNOBLOTTING

Twenty four hours after transfection of pcDNA3BRCA1, aliquots of 4x10 5 cells were washed twice in Phosphate Buffered Saline (PBS) 1X and lysed in the Laemmli Sample Buffer 1X (Tris-HCl 50 Mm pH 6.8, SDS 2%, glycerol 10%, bromophenol blue 0.1 %, β-mercaptoethanol 100mM) together with the Protease Inhibitor Cocktail 1X (Sigma). The protein extracts were denaturated at 100°C for 5 minutes. A total of ~ 120 μg of whole cell extract was subjected to electrophoresis at 10 to 20 mA for ~ 3 hours in a 6% SDS-polyacrylamide gel; thereafter, the proteins were transferred to polyvinylidene fluoride membrane at 170 mA for 17 hours at 4°C using a Mini-PROTEAN ® Cell apparatus (Bio-Rad). BRCA1 was detected using anti-BRCA1 monoclonal antibody Ab4 (Calbiochem, Gibbstown, NJ) diluted 1:100 with 3% of BSA. This antibody recognizes aa 1005-1313 in the exon 11 of the BRCA1 protein. Anti-mouse horseradish peroxidase-linked antibody (Amersham Biosciences, Piscataway, NJ), diluted 1:15,000, was used as secondary antibody. The BRCA1 protein was detected using the ECL chemioluminescence solution (Bio-Rad) and the signals were developed on photographic films (Sigma).

HOMOLOGOUS RECOMBINATION ASSAY

The HeLaG1 cells (a gift from Margherita Bignami, Rome Italy) contain a stably integrated plasmid that allows to measure gene conversion events between two differentially mutated hygromycin-resistance (Hyg R ) genes [START_REF] Ciotta | Increased somatic recombination in methylation tolerant human cells with defective DNA mismatch repair[END_REF]. One Hyg R gene is mutated at the PvuI site (hyg1), the other Hyg R at the SacII site (hyg2) (Figure 3). An intrachromosomal recombination event leads the restoration of wt Hyg R gene; therefore, the frequency of intrachromosomal recombination was calculated as total number of Hyg R clones x 10 -5 viable cells. HeLaG1 cells were transfected with the pcDNA3β expression vector containing the wild type BRCA1 or the BRCA1-UCVs. 24 hours after transfection, cells were harvested and plated (6x10 5 cells/10 cm dish and 10 2 cells/6cm dish, for plating efficiency (PE) evaluation). For the selection of the recombination events, 24 hours later we added hygromicin 0.2 mg/ml (Sigma) to the medium. Medium was changed twice and, after 10 to 15 days, plates were stained with crystal violet and clones were counted [START_REF] Franken | Clonogenic assay of cells in vitro[END_REF].

RANDOM PLASMID INTEGRATION ASSAY

The effect of BRCA1 expression on NHEJ was determined, as previously reported, by testing the effect of these proteins on random plasmid integration in HeLa cells [START_REF] Primio | Potentiation of gene targeting in human cells by expression of saccharomyces cerevisiae rad52[END_REF].The frequency of NHEJ was determined by co-transfecting the HeLa cells with 2µg of the pcDNA3 .BRCA1-wt or BRCA1-UCV vectors and 2µg of pBlue-puro that carries no homology with the genome of HeLa cells and, therefore, it stably integrates by non homologous recombination [START_REF] Primio | Potentiation of gene targeting in human cells by expression of saccharomyces cerevisiae rad52[END_REF]. One day after transfection, cells were collected and plated (2 x 10 5 cells/dish) in 10 cm dishes containing 0.2 µg/ml puromycin. Culture medium was changed after 7 days and replaced with puromycin free fresh medium. The colonies were stained and counted 7 days later and the frequency of recombination was calculated by dividing the number of puromycin-resistant colonies by the number of seeded cells corrected by the plating efficiency.

STATISTICAL ANALYSIS

The frequency of Hyg R clones obtained after the transfection of the empty-vector was used as reference. The results were analysed by the t-Student Test. All the analysis were performed by using Statgraphics (StatPoint Inc.USA).

RESULTS

Variants Selection

We selected four non synonymous UCVs suggested by Sift, Polyphen and Align-GVGD software as likely disrupting the protein function: the Y179C, the N550H, the I1766S and the A1789T (Table 1 and Figure 1) identified in four out of 276 breast and breast-ovarian cancer families.

The M1775R, classified as deleterious, was used as positive control [START_REF] Williams | Structural consequences of a cancer-causing brca1-brct missense mutation[END_REF]. The A1789T variant has never been described previously. It was found in one family. The proband was affected by breast cancer at 32 years of age. The mother of the proband, affected by breast and ovarian cancer diagnosed at 46 and 50 years of age, respectively, was found to be a carrier of the variant (figure 2a). The I1766S was classified as a deleterious amino acidic change by Carvalho et al. [START_REF] Carvalho | Determination of cancer risk associated with germ line brca1 missense variants by functional analysis[END_REF]. It was found in one family: the proband had ovarian carcinoma diagnosed at 42 years of age. A DNA sample was available from a sister of the proband unaffected at 50 years of age. She tested negative for the mutation (figure 2b).

The Y179C was classified as neutral by Judkins [START_REF] Judkins | Application of embryonic lethal or other obvious phenotypes to characterize the clinical significance of genetic variants found in trans with known deleterious mutations[END_REF]. The N550H was classified as probably neutral by Tavtigian [START_REF] Tavtigian | Comprehensive statistical study of 452 brca1 missense substitutions with classification of eight recurrent substitutions as neutral[END_REF]. These two UCVs were inherited together with the polymorphism F486L in two apparently unrelated families (figure 2c-d). The proband from one family was affected by breast cancer at 42 years of age. Two second degree relatives in the paternal branch, the proband's grandmother and a cousin, were affected by breast cancer. The affected cousin was found negative for the variants. The proband from the other family was affected by bilateral metacronous breast cancer at 48 and 53 years of age. The proband's mother and two cousins were affected by breast cancer. Unfortunately no one of them was available for mutation testing.

Functional assays

Homologous recombination in HeLa cells

In order to set up a novel functional assay to distinguish between neutral polymorphisms and deleterious mutations, we created several vectors derived from pcDNA3 -BRCA1-wt, by site directed mutagenesis, each of them expressing a selected UCV. These vectors were transfected in the HeLaG1 cells that carry a recombination substrate measuring intrachromosomal recombination events between the mutated hyg1 and hyg2 alleles (see Materials and Methods, Figure 3). First, we checked if the expression of the wild type and mutated BRCA1 was detectable 24 hours after transfection. Then, we prepared the total lysate, as described in the methods, and carried out Western blot analysis. In the figure 4, we showed that all the proteins were expressed roughly at similar level as compared to the α-tubulin, suggesting that the proteins are equally stable in the cells. Importantly, the transgene expression was clearly detectable in the blot after few minutes of exposure when the endogenous BRCA1 was not visible (figure 4). The expression of endogenous BRCA1 was seen only after 2 hours of exposure (data not shown). Thus, under these conditions, we concluded that the exogenous BRCA1 proteins were over-expressed. This prompted us to determine if this transient expression of the BRCA1 protein affected recombination. For such reason, 24 hours after transfection the cells were seeded in the presence of hygromicin to score for intrachromosomal recombinants. Under these conditions, the wild type increased the recombination frequency of 1.6 fold compared to the empty vector and this difference was statistically significant (t-test P<0.005) (Table2): the HR frequency of HeLa G1 cells transfected with empty vector was 5.99±2.3 x 10 -5 viable cells. All the UCVs tested showed an increase in HR ranging from 0.98 to 1.3 fold compared to the empty vector. Thus, a functional assay based on homologous recombination in human cells would be presumably not helpful to characterize BRCA1 UCVs.

Random plasmid integration in HeLa cells

To evaluate whether BRCA1 UCVs had an influence on NHEJ, we determined the effect of the expression of these proteins on random (non-homologous) plasmid integration in HeLa cells.

The plasmid expressing the BRCA1 wt or BRCA1 UCVs was co-transfected with the pBlue-puro plasmid; after 24 hours, the puromycin was added and the frequency of random plasmid integration was measured as number of puromycin resistant clones on 10 3 viable cells.

The expression of exogenous wild type and the mutant I1766S BRCA1 protein increased the plasmid random integration in HeLa by 2.3 and 2.5 fold respectively as compared to the control (Table 2). The over-expression of the mutant BRCA1 protein N550H and the M1775R stimulated the plasmid random integration by 3.1 and 3.2 fold respectively as compared to the control (Table 2). The over-expression of variants Y179C and A1789T induced the highest increase of plasmid random integration by 3.5 and 4.6 fold respectively as compared to the control (p≤0.001). In conclusion, the I1766S and the M1775R UCVs behaved similarly to the wt, whereas the Y179C and the A1789T induced a significant increase of random integration (Table 3).

DISCUSSION

Only a very small fraction of BRCA1 missense variants have been classified either as deleterious or neutral while the majority remains as unclassified variants significance (UCVs).

Interpreting such variants poses significant challenges for both clinicians and patients. To predict the clinical relevance of unclassified variants, several approaches are recommended. Bioinformatic prediction software supported by functional assays, classical genetic analysis and tumor phenotype, are useful to produce a prediction algorithm as proposed by Golgdar and Tavtigian [START_REF] Goldgar | Genetic evidence and integration of various data sources for classifying uncertain variants into a single model[END_REF] [START_REF] Tavtigian | Assessing pathogenicity: Overview of results from the iarc unclassified genetic variants working group[END_REF]. However, in general, it is easier to conclude that a variant is non-pathogenic than pathogenic [START_REF] Chenevix-Trench | Genetic and histopathologic evaluation of brca1 and brca2 DNA sequence variants of unknown clinical significance[END_REF].

BRCA1 acts a tumor suppressor gene and germ-line mutations which disrupt its functions culminate, after the loss of the wild type allele, in cancer development. Although its precise biochemical functions, relevant for tumor suppression, still remains to be clarified, BRCA1 has been demonstrated to play a role in several cellular processes including DNA Double Strand Breaks repair, transcriptional regulation, chromatin remodelling, cell cycle checkpoint control, protein ubiquitination and centrosome replication [START_REF] Venkitaraman | Linking the cellular functions of brca genes to cancer pathogenesis and treatment[END_REF].

Several functional assays have been used to distinguish between BRCA1 cancer-related mutations and neutral polymorphisms but due to its multitasking characteristic there is not comprehensive functional assay available for BRCA1 [START_REF] Mirkovic | Structure-based assessment of missense mutations in human brca1: Implications for breast and ovarian cancer predisposition[END_REF][START_REF] Phelan | Classification of brca1 missense variants of unknown clinical significance[END_REF]. In this paper, we propose two functional assays: the first one based on transient expression of the UCVs in HeLa G1 cells containing a HR substrate and the second one on random chromosomal integration of a linearized plasmid DNA in the genome of HeLa cells transiently expressing the UCVs. We studied a total of five BRCA1 missense variants of which one was already classified as pathogenic and used as a control. The variants were tested for their effect on both HR and NHEJ. The HR assay consists in the evaluation of the frequency of Hyg R clones due to the cell ability to reconstitute the wild type Hyg gene that is located, in two mutated copies, in the vector pTPSN stably integrated in the cell genome.

The NHEJ assay consists in the evaluation of the frequency of puromycin resistant clones due on random chromosomal integration of a plasmid DNA containing the puromycin-resistance gene (Figure 3). We showed that in our experimental conditions, BRCA1-WT increases the HR frequency.

Moreover, none of the BRCA1-UCVs altered the HR frequency when compared to the BRCA1-WT. As a matter of fact, the low increase in HR frequency obtained when the BRCA1-WT was over-expressed, even if statistically significant, could be not biologically relevant. A 2 fold increase in HR frequency has been proposed as cut-off value to be considered as biologically relevant [START_REF] Galli | Effects of salmonella assay negative and positive carcinogens on intrachromosomal recombination in g1-arrested yeast cells[END_REF][START_REF] Galli | Salmonella test positive and negative carcinogens show different effects on intrachromosomal recombination in g2 cell cycle arrested yeast cells[END_REF]. In our experiments, no BRCA1 missense variant increased HR by 2 fold, therefore we can conclude that this assay does not distinguish between pathogenic mutation and neutral polymorphism. Recently, we have developed a yeast-recombination assay that could be helpful to characterize BRCA1 missense variants [START_REF] Caligo | A yeast recombination assay to characterize human brca1 missense variants of unknown pathological significance[END_REF]. In yeast, the over-expression of pathogenic BRCA1 variants induce HR by 2-4 fold as compare to the wild type or neutral polymorphism [START_REF] Caligo | A yeast recombination assay to characterize human brca1 missense variants of unknown pathological significance[END_REF](Table 3). Thus, the yeast Saccharomyces cerevisiae assay is able to distinguish the pathogenic from the neutral BRCA1 missense variants. So far, we do not exactly understand this different effect of the BRCA1 variants on yeast HR as compared to HeLa cells (Table 3); the ratio between NHEJ and HR varies greatly across phylogenetic groups. Yeast rely heavily on HR while in mammals and plants NHEJ is the preferred pathway. The choice may be dictated by genome composition. In large repetitive genomes of plants and animals overly efficient HR may lead to deleterious genomic rearrangements, such that NHEJ may be a safer choice [START_REF] Mao | Comparison of nonhomologous end joining and homologous recombination in human cells[END_REF]. This is the main reason why we measured the effect of BRCA1 missense variants on NHEJ in a plasmid random integration assay.

Notably, BRCA1 was shown to be involved also in the regulation of random integration by NHEJ , even if the molecular mechanism has not fully understood [START_REF] Zhong | Deficient nonhomologous end-joining activity in cell-free extracts from brca1-null fibroblasts[END_REF]. Different kinds of assays support this involvement such as in vitro reconstitution of a linearized plasmid, in vivo overall end-joining and microhomology mediated end-joining [START_REF] Zhong | Brca1 facilitates microhomology-mediated end joining of DNA double strand breaks[END_REF][START_REF] Baldeyron | A single mutated brca1 allele leads to impaired fidelity of double strand break end-joining[END_REF].

Our results confirmed a clear involvement of BRCA1 in random chromosomal integration of a linearized plasmid DNA. The over-expression of BRCA1-Y179C and BRCA1-A1789T UCVs increased the frequency of random integration as compared to the wild type. It was observed that the over-expression of BRCA1-Y179C induces a hyper-recombination phenotype also in yeast (Table 3) [START_REF] Caligo | A yeast recombination assay to characterize human brca1 missense variants of unknown pathological significance[END_REF]. Moreover, we have previously reported that the in vivo analysis on tumor tissue revealed that the proband carrier of the Y179C showed loss of heterozigosity (LoH) of the wild type allele and the proband carrier of A1789T showed hypermethylation of the wild type allele. Both LoH and hypermethylation are considered to be indicative of the pathogenicity of the variant [START_REF] Caligo | A yeast recombination assay to characterize human brca1 missense variants of unknown pathological significance[END_REF].

The UCVs I1766S and N550H did not affect the NHEJ frequency, as well as the pathogenetic control M1775R, suggesting that their roles are not related to the NHEJ pathway.

However, both the I1766S and the mutation M1775R affected the transcriptional activation ability of BRCA1 both in yeast and mammalian cells [START_REF] Carvalho | Determination of cancer risk associated with germ line brca1 missense variants by functional analysis[END_REF]. The A1789T variant also, in addition to its effect in the NHEJ assay, showed to abrogate the BRCA1 transcriptional activity (Guidugli unpublished results), suggesting to be potentially pathogenic. These findings suggest that the BRCA1 protein may have completely independent functions related to specific protein regions. In terms of defining the influence of UCVs on BRCA1 function, these findings indicate that all UCVs should be analyzed by all the functional methods available. If only one assay is used, it is possible that a UCV that inactivates a different function of BRCA1 might be identified as having no clinical relevance. Fig. 3 The intrachromosomal recombination in human cells. HeLaG1 cells contain two copies of HygR genes inactivated by 10 bp insertions, either at a unique PvuI site (hyg1) or at a unique SacII site (hyg2); the two mutated hyg genes are in direct repeat orientation and are separated by a sequence containing the amino-glycoside phosphotransferase (Neo) gene conferring resistance to G418; an intrachromosomal recombination event occurring by gene conversion between the two hyg sequences results in restoration of one of the mutant hyg genes to wild type; the intrachromosomal deletion of the DNA sequence between the two mutated hyg genes leads to the formation of a HygR wild type (Hyg WT) with loss of intervening sequence; the intrachromosomal recombination was measured after transfecting HeLaG1 cells with either BRCA1wt or UCVs Fig. 4 Western Blot analysis to measure the expression of the BRCA1 wt and UCVs protein in a HeLa cell line extract. The monoclonal Ab-4 antibody specifically directed towards exon 11 BRCA1 protein was used, as well as the polyclonal anti-β-tubulin control antibody. 1) pcDNA3.1; 2) pcDNA3-BRCA1 wt; 3) pcDNA3-BRCA1-M1775R; 4) pcDNA3-BRCA-A1789T; 5) pcDNA3-BRCA1-I1766S; 6) pcDNA3-BRCA1Y179C; 7) pcDNA3-BRCA1-N550H.

Fig . 1 Fig. 2

 12 Fig . 1 Localization of the UCVs in the BRCA1 cDNA sequence. The numbers indicate the exons. *Mutation localized in BRCT Domain; # Pathogenetic control variant

ACKNOWLEDGEMENTS

The authors thank David Livingston, Giuseppe Rainaldi and Roland Kanaar for plasmids. The authors are also grateful to Margherita Bignami for the HeLaG1 cell line. The work was supported by a grant from " Fondazione Cassa di Risparmio di Pisa" and from " AIRC regional Grant 2005-2007" to M.A.C.

CONFLICTS OF INTEREST

The authors declare that they have no conflicts of interest.


M Hawkins
email: ross.hawkins@nibsc.hpa.org.uk

J Boyle

K E Wright

R Elles

S C Ramsden

A O'grady

M Sweeney

D E Barton

T Burgess

M Moore

C Burns

G Stacey

E Gray

P Metcalfe

J R Hawkins

Preparation and validation of the first WHO international genetic reference panel for Fragile X syndrome

Keywords: Fragile X syndrome, FMR1, certified reference materials, genetic reference panel

Fragile X syndrome is the most common inherited form of mental retardation. It is caused by expansion of a trinucleotide (CGG)n repeat sequence in the 5' untranslated region of the FMR1 gene, resulting in promoter hypermethylation and suppression of FMR1 transcription. Additionally, pre-mutation alleles in carrier males and females may result in Fragile X Tremor/Ataxia Syndrome and primary ovarian insufficiency respectively.

Fragile X is one of the most commonly requested molecular genetic tests worldwide.

Quality assessment schemes have identified a wide disparity in allele sizing between laboratories. It is therefore important that clinical laboratories have access to characterized reference materials (RMs) to aid accurate allele sizing and diagnosis. With this in mind, a panel of genotyping reference materials for Fragile X syndrome has been developed which should be stable over many years and available to all diagnostic laboratories. Immortalised cell lines were produced by Epstein-Barr virus transformation of lymphocytes from consenting patients. Genomic DNA was extracted in bulk and reference material aliquots were freeze-dried in glass ampoules. Twenty one laboratories from seventeen countries participated in a collaborative study to assess their suitability.

Participants evaluated the samples (blinded, in triplicate) in their routine methods alongside in-house and commercial controls. The panel of five genomic DNA samples

Introduction

Fragile X syndrome is the most common heritable cause of mental retardation, affecting approximately 1 in 5,000 males and 1 in 10,000 females. It is caused by the expansion of a tract of CGG repeats in the 5'-untranslated region of the Fragile X mental retardation 1 (FMR1) gene located at Xq27.3, with consequent hypermethylation of promotor regions and silencing of gene expression [START_REF] Sherman | Fragile X syndrome: diagnostic and carrier testing[END_REF] . As the phenotypic presentation and frequency of clinical signs are variable, clinical diagnosis is challenging and definitive diagnosis in suspected individuals requires molecular measurement of the (CGG)n allele size. The size of the (CGG)n repeat tract is highly polymorphic in the general population, containing from 6 to about 50 repeats and most commonly 29-30 repeats [START_REF] Fu | Variation of the CGG repeat at the Fragile X site results in genetic instability: resolution of the Sherman paradox[END_REF][START_REF] Kunst | Cryptic and polar variation of the Fragile X repeat could result in predisposing normal alleles[END_REF][START_REF] Macpherson | Insert size and flanking haplotype in Fragile X and normal populations: possible multiple origins for the Fragile X mutation[END_REF] . Individuals with alleles of 59-200 repeats, known as pre-mutations, are considered to be carriers as alleles of this length are highly unstable in maternal transmission and at very high risk of expansion into 'full mutation' alleles of >200 repeats which are causative of the Fragile X syndrome.

Selected screening is highly justified among mentally retarded individuals, not only to provide the benefits of early clinical intervention, but also to enable prenatal diagnosis to be offered to related carriers [START_REF] Macpherson | Practice Guidelines for molecular diagnosis of Fragile X Syndrome[END_REF]6 . Genetic testing for Fragile X syndrome is widespread but it has been acknowledged by leading laboratories in the field to be one of the most technically challenging genetic tests. Performance in proficiency testing has been shown to be sub-optimal in several EQA schemes [START_REF] Falbo | The Italian External Quality Assessment scheme for Fragile X syndrome: the results of a 5-year survey[END_REF]8 . Any assay using PCR amplification to determine (CGG)n must overcome the problem of amplifying long sections of repetitive CG-rich sequence. Validation of the assays used is difficult because of the lack of reliable reference materials. Accurate allele sizing becomes essential when distinguishing between alleles around the normal/pre-mutation and pre-mutation/full mutation thresholds. Most laboratories use DNA samples from patients which have been characterised by their own laboratory as controls. As such, allele sizing accuracy may vary between laboratories. Laboratories that are new to the field often rely on small finite amounts of materials supplied by other genetic reference laboratories, for example as part of external quality assessment schemes. However, these control materials are in short supply because of the relatively large amount needed for investigation (by Southern The high frequency of male and female carriers of FMR1 pre-mutation alleles (~1/813 to 1/251 and ~1/259 to 1/113 respectively) [START_REF] Dombrowski | Premutation and intermediate-size FMR1 alleles in 10572 males from the general population: loss of an AGG interruption is a late event in the generation of Fragile X syndrome alleles[END_REF][START_REF] Fernandez-Carvajal | Screening for expanded alleles of the FMR1 gene in blood spots from newborn males in a Spanish population[END_REF][START_REF] Rousseau | Prevalence of carriers of premutation-size alleles of the FMRI gene--and implications for the population genetics of the Fragile X syndrome[END_REF][START_REF] Toledano-Alhadef | Fragile-X carrier screening and the prevalence of premutation and full-mutation carriers in Israel[END_REF][START_REF] Cronister | Prevalence and instability of Fragile X alleles: implications for offering Fragile X prenatal diagnosis[END_REF] and the occurrence of pre-mutation phenotypes such as Fragile X Tremor Ataxia Syndrome (FXTAS) 14 and Fragile Xassociated primary ovarian insufficiency (FXPOI) [START_REF] Cronister | Heterozygous Fragile X female: historical, physical, cognitive, and cytogenetic features[END_REF] will doubtless lead to increased FMR1 genotyping and possibly to screening of the general population. The case for certified reference materials to aid accuracy in FMR1 genotyping is therefore increasing in strength.

There are no internationally certified genetic reference materials available for in vitro diagnosis of Fragile X syndrome. A panel of nine PCR amplicons with a variety of FMR1 trinucleotide repeat length standards are available from the US National Institute of Standards and Technology (NIST). However, the panel does not contain any full mutations and the materials can only be used in PCR and not in the more definitive Southern blot assay. Genomic DNA (gDNA) reference materials would be preferable as these more closely resemble patient specimens. Well-characterized genomic DNA materials are available from Coriell Cell Repositories but are not approved or intended for in vitro diagnostic use [START_REF] Wilson | Consensus characterization of 16 FMR1 reference materials: a consortium study[END_REF] . Furthermore, there may be differences in DNA quality and performance (and also possibly even differences in allele sizes due to somatic cell mutation [START_REF] Bonilla | Epstein-Barr virus transformation of human lymphoblastoid cells from patients with Fragile X syndrome induces variable changes on CGG repeats size and promoter methylation[END_REF] [& KEW, JRH unpublished data]) in future batches.

We have therefore chosen to produce in bulk a panel of gDNA materials which could be certified and, when eventually required, can be replenished from the same source. Bulk genomic DNA was extracted from immortalised cell lines produced by Epstein-Barr virus (EBV) transformation of lymphocytes from donors who were known to carry the wild type, pre-mutation and full mutation genotypes. Following validation by an international collaborative study, a panel of five gDNAs was endorsed by the European Society of Human Genetics and then approved as an International Standard by the Expert Committee on Biological Standardization at the World Health Organization (WHO) in November 2008.

Materials and Methods

Patients and Cell Lines

A protocol for approaching patients, obtaining informed consent and anonymizing samples was approved by a local research ethics committee. Patient blood samples were collected from six consenting donors as part of 'CRMGEN', an EU 5 th framework project to evaluate and develop certified reference materials for genetic testing. One donor was a normal female individual and the remainder had been identified after previous molecular genetic investigation. Classifications of these patients were: female pre-mutation, male pre-mutation, male full mutation, female full mutation (x2). Lymphoblastoid cell lines were established after EBV transformation, ensuring continued future supply. Each cell line was tested for Hepatitis A, Hepatitis B, Hepatitis C, Parvovirus B19 and HIV1.

Master and working cell banks were established and stored to ensure continual future supplies of the same cells. Safety of storage was guaranteed by distribution to multiple liquid nitrogen vessels at multiple locations. Cell banks were identity-tested by DNA profiling with the Applied Biosystems 11-locus SGM+ kit. FMR1 (CCG)n repeat genotypes of the cell lines were confirmed to match those of the donor patients, except for the 2 female full mutation cell lines which prior to the collaborative study, remained unconfirmed. For that reason, two female full mutation samples were included in the panel for the collaborative study, in case one proved more suitable than the other for use as a reference material.

DNA Extraction and Freeze Drying

Cells were bulk cultured (ECACC, UK) to approximately 10 10 cells and frozen as pellets of 10 8 cells. Genomic DNA was extracted from cell pellets using the PureGene DNA purification and Autopure LS equipment (Qiagen, UK). The integrity of the extracted DNA was confirmed by electrophoresis in agarose gels. Each of the DNA samples were dissolved at a concentration of approximately 29µg/ml in 0.8mM Tris/0.08mM EDTA buffer with 2.5mg/ml Trehalose. 0.8ml of this solution was dispensed into a minimum of 1200 glass ampoules and freeze-dried. Sealed ampoules were stored at -20°C.

Homogeneity Testing

Samples were tested for homogeneity by determining DNA concentration by spectrophotometric absorbance analysis (Nanodrop, USA). After reconstitution in distilled water, the samples were allowed to equilibrate to room temperature for 1 hour with mixing by pipetting after 30 minutes before quantitation. Accuracy and precision of the spectrophotometer was determined by performing multiple reads on a control sample of commercial genomic DNA (Promega, UK).

Accelerated Degradation Study

Ampoules were tested for degradation by agarose gel and quantitative PCR comparison of samples stored at +56°C and -20°C with samples stored at -150°C. For agarose gel electrophoresis, the size marker was Hyper Ladder VI (Bioline, UK). For Q-PCR, the PCR primers sequences (5' to 3'): Forward-TGCCCAGTGCTTAACAAGACCA and Reverse-CTTGAAGGAAATGCCCCATTA, were used at 10μM to amplify a 486bp sequence of F2 on chromosome 11. Cycling conditions were 95°C 10 mins then 45 cycles of 95°C for 10s, 60°C 20s and 72°C 30s using the LightCycler FastStart DNA Master plus SYBR Green I kit on a LightCycler 480 thermal cycler (Roche, UK).

Methylation Analysis

For analysis of methylation status at the FMR1 promoter, Methyl Primer Express v1.0 was used to design bisulphite specific sequence primers for the amplification a 192bp region, covering 22 CpG's, of the FMR1 gene promoter region (position 3435241-3437401 of NT_011681 of Chromosome X, NC_000023), upstream of the CGG repeat region. Primers used were forward 5'-TTGAGTGTATTTTTGTAGAAATGG-3' and reverse 5' -CCCTCTCTCTTCAAATAACCT-3'. Ampoules were reconstituted in 40µl water and left to reconstitute for 60 min. Approximately 50ng of bisulphite converted DNA was used in the final HRM reaction mix, containing 1U Hot Star Taq (Qiagen, UK), 3mM MgCl2, 5pmol primers, 200µM dNTPs and 5µM Syto9. PCR was performed on the Rotorgene 6000, and consisted of an initial 10 minute 95°C denaturation step, followed by 40 cycles of 30 s at 95°C, 30 s at 55°C and 45 s at 72°C with a final 7 minute extension at 72°C . This PCR was followed by a melting step for HRM which consisted of 95°C for 5 s, followed by 50°C for 5 minutes and a temperature ramping from 70°C to 95°C at a rate of 0.2°C/sec. Fluorescence was acquired on the HRM channel. HRM data was analysed using Rotorgene 6000 software. The leading and trailing edges were normalised at 72-74°C and 83-86°C respectively. The assay was performed on 3 ampoules of each sample.

Collaborative Validation Study

Each of the six gDNA materials were sent in triplicate and blinded to each laboratory with instructions for reconstitution and storage. Each laboratory was asked to perform their routine test(s) for Fragile X syndrome on each of the 18 coded samples and to genotype the samples in groups of six on three separate days as indicated on the results sheet, using different lots of reagents or different operators if possible. Laboratories were asked to report the number of trinucleotide repeats. Overall findings of each sample and raw data e.g. images of autoradiographs, were to be returned together with full details of techniques used, any in house or commercial controls and reasons for failure of any of the samples tested. In all cases cell line DNA profiles matched the profile of the original blood samples. No samples showed evidence of cross-contamination. However, sample 07/174, showed a very small additional peak at just two short tandem repeat marker loci. These peaks were not detected in the original blood samples.

Results

Each cell line was found negative for

Bulk genomic DNA was filled into glass ampoules, freeze-dried and sealed. Upon reconstitution with 40µl sterile water the DNA concentration is approximately 580µg/ml in 16mM Tris; 1.6mM EDTA; 50mg/ml Trehalose. The pH of the reconstituted candidate materials was measured and was found to be within 7.4 and 7.8 in all six. Table 1 shows the product summary for the six materials. Residual moisture and oxygen levels were consistent with those obtained in previous fills and within the levels acceptable for International Standards by the WHO [START_REF]Recommendations for the preparation, characterization and establishment of international and other biological reference standards[END_REF] .

Homogeneity

Random ampoules were weighed periodically during the ampoule filling of each material.

The coefficient of variation for each fill (0.15% to 0.31%; Table 1) indicates a very low level of variation in volumes aliquotted during each fill run.

The materials were tested for DNA homogeneity after reconstitution both within ampoules and between ampoules by DNA quantitation. Ten randomly selected ampoules of each material were reconstituted in 40ul distilled water. The DNA concentration of each ampoule was measured in triplicate. The triplicate reads were highly consistent, giving a modal coefficient of variability of just 2.9%. The distribution of variability is displayed in Figure 1a. This data indicates that the material in the ampoules is highly homogeneous 1 hour after reconstitution.

DNA concentrations showed more variation between individual ampoules of each material and between the different materials (Figure 1). However, the intended purpose is independent of DNA concentration above a minimum level and the amount supplied in each ampoule is enough for several tests by Southern blotting. Mean concentrations of each material varied from 568 to 818μg/ml, equating to a mean of at least 23μg per ampoule. Coefficients of variability between ampoules of a single material ranged from 7.2 to 15.3%.

Stability

An accelerated degradation study on samples stored at +56°C was carried out. When compared with samples stored at -150°C, after 2 years storage there was no detectable degradation in samples 07/122; 07/168; 07/170 or 07/174 as assessed by Q-PCR (Figure 2a). Ampoule 07/120 showed an increase in Cp value of 0.54 between the -150°C and +56°C samples, indicating a 31% decrease in DNA yield. This difference however may be the result of ampoule to ampoule variability or due to a 'baking' effect resulting in incomplete solubilisation. The Q-PCR findings were confirmed by agarose gel electrophoresis, where there was a slight increase in band mobility for the +56°C sample as well as a slight decrease in band intensity, but no visible increase in low molecular weight DNA (Figure 2b). Densitometry analysis of the gel bands indicates an average signal reduction of 22% for the +56°C samples. Together the Q-PCR and electrophoresis data indicates some, but limited degradation at +56°C. However, the limited degradation at +56°C and the absence of degradation at the storage temperature of -20°C after 2 years indicates that the DNA should be stable for many years.

Validation

To validate that the materials are fit for purpose as Reference Materials in the laboratory diagnosis of Fragile X syndrome, laboratories were invited to participate in an international collaborative study. Thirty eight laboratories were invited to take part in the study, 23 laboratories agreed to participate and results were returned by 21 laboratories.

Seventeen different countries were represented among participants returning results: 13 from Europe, 4 from North America, 3 from Australasia, 1 from Asia. Collaborative validation study participants were requested to test the 18 coded samples on 3 separate days using different lots of reagents or different operators if possible. The methods used by the participants are listed in Table 2. Seventeen laboratories used in-house assays and four laboratories used a commercial kit developed by Celera and available from Abbott Molecular (Des Plaines, Illinois, USA). Some laboratories usually refer selected samples to another laboratory to complete their investigation (laboratories 11, 15) and others were unable to carry out their usual testing protocol because of technical difficulties (laboratories 8, 14 & 19). Laboratory 14 could not obtain any useful Southern blotting results with the samples supplied, while their in-house controls gave the expected results, as did the study samples in their PCR test.

No two in-house methods were entirely identical. Some laboratories indicated that their method was based on a previous publication (see Supplementary Data). Eight laboratories were able to use more than one batch of reagents and the testing was carried out by more than one operator in five laboratories. There is no evidence of the study materials performing differently between different methods. The materials performed similarly to patient samples in Southern blotting, with a spread of bands from expanded alleles, although none of the spreads were as extreme as can be seen in some patient samples (Figure 3). The methylation states of the alleles are indicated in Figure 3. The normal female and female premutation samples gave a 2 peak melting profile, with the larger peak indicating unmethylated, and the smaller peak indicating methylated. This melting profile corresponds with the two alleles present in these samples, one of which is Xinactivated and appears as the higher Tm methylated peak. The female full mutation-1 sample also gave the 2 peak melting profile, which indicates that the FMR1 expansion lies largely on the inactivated X-chromosome. In contrast, the female full mutation-2 sample gave a single methylated melting peak profile indicating that the FMR1 expansion lies largely lies largely on the active X-chromosome. Male samples however have a simpler melting profile as they possess only a single X allele. The male premutation sample gave a single low Tm peak, indicating that the Fragile X promoter is unmethylated. The male full mutation sample shows a single fully methylated peak, indicating the presence of only a fully methylated Fragile X promoter.

The controls used by participants were as follows: 17 laboratories used in-house materials Exceptions to this interpretation were: Lab.11 did not get a PCR product with 1 out of the 3 samples, reported normal female for the other 2 samples. Lab.19 obtained genotypes in all 3 samples but was unable to complete the investigation and made no interpretation. Samples 2, 7 & 14 (female, pre-mutation): 16 labs reported 'female, premutation'. Exceptions to this interpretation were: Lab.14 which detected the pre-mutation in only 1 out of 3 samples and was unable to make an interpretation for 2 samples; samples as 'normal female'; Lab.19 obtained genotypes in all 3 samples but was unable to complete the investigation and made no interpretation. Samples 3, 8 & 17 (female, full mutation): 14 labs reported 'female full mutation'. Exceptions to this interpretation were: Lab.16 reported 'female full mutation' with only 2 out of 3 samples and would refer the 3rd sample for Southern blotting; Labs.11, 14 & 15 would refer all samples for Southern blotting; Lab.17 reported a different result for all 3 samples (normal male, male or Turner syndrome, female full mutation); Lab.19 only tested 2 samples and obtained genotypes but was unable to complete the investigation and made no interpretation; Lab.21 reported only 'one allele detected by PCR' and made no clinical interpretation. Samples 4, 10 & 18 (male full mutation): 14 labs reported 'male full mutation'.

Exceptions to this interpretation were: Labs.11, 15 & 16 suspected a full mutation and would refer all samples for Southern blotting; Lab.8 reported 'normal male' with all 3 samples; Lab.17 reported 'male pre-mutation' with 2 out of 3 samples and 'male full mutation' with the third sample; Lab.19 was unable to complete the investigation and made no interpretation. Lab.21 did not amplify a PCR product and made no interpretation. Samples 5, 15 & 16 (female, full mutation): 14 labs reported 'female full mutation'. Exceptions to this interpretation were: Lab.8 suspected a full mutation but was unable to obtain Southern blot data; Labs.11, 14 & 15 would refer all samples for Southern blotting; Lab.17 reported 'normal female' with 2 out of 3 samples and 'female full mutation for the third sample; Lab.19 was unable to complete the investigation and made no interpretation; Lab.21 reported only 'one allele detected by PCR'. Sample 6, 9 & 13 (male, pre-mutation): 17 labs reported 'male pre-mutation'. Exceptions to this interpretation were: Labs.11 & 15 suspected a pre-mutation and would refer all samples for Southern blotting; Lab.17 reported 'normal male' for 2 samples and 'male full mutation' for the third sample; Lab 19 was unable to complete the investigation and made no interpretation.

A total of 18 non consensus results were reported, giving an overall rate of non concordance of 4.9% (21 laboratories x 18 samples -7 samples not tested), although these were clustered in three laboratories. There was no correlation between the non concordant results and any particular sample or a specific method.

One laboratory reported 12 of the 18 non concordant results. This laboratory was contacted, and their testing protocol was changed. Genotyping results are presented in Figure 4. The sample testing mean allele sizes and ranges obtained are summarized in Table 3. Three outliers identified by Grubb's Test were omitted from the data analysis 19 .

These were: female full mutation 1 -allele 2: 575 repeats; female full mutation 2 -allele 1: 26 repeats; male full mutation -7 repeats.

The detection of a very small 7 repeat allele in the male full mutation samples by two laboratories was unexpected. Such minimal repeats are occasionally detected in full mutation clinical samples and it is unclear if the small repeat is an assay artefact or a true mosaic allele. In this study one laboratory (lab. 8) found the 7 repeats by PCR and interpreted the result as a normal male without carrying out Southern blotting, while the other lab (lab. 18) found a similar peak by PCR but noted it as a likely artefact and continued to identify a full expansion by Southern blotting.

Discussion

In the absence of reference materials, genetic tests are being performed without adequate controls and new assays are difficult to validate. The need for reference materials in Fragile X syndrome testing is particularly pressing as it is a technically challenging test.

For use in in vitro diagnostic assays, reference materials in the EU must be CE-marked or in the U.S. must be FDA-approved. Alternatively, according to the EU IVD directive (Directive 98/79/EC of the European Parliament and of the Council of 27 October 1998 on in vitro diagnostic medical devices), reference materials of "higher order" are exempted from CE marking. WHO international standards are accepted as internationally recognised "highest order" measurement standards.

Whilst aimed to promote the wider availability and safety of commercial products for in vitro diagnostics, the European IVD directive may have hampered reference material development and use by preventing the distribution of 'in-house' quality control samples between laboratories. This also hampers harmonization of quality between laboratories.

Despite the existence of a PCR-product based certified reference material for Fragile X testing (NIST, USA), there was a need for a more commutable, i.e. cellular or genomic, certified reference material. As EBV-positive cell lines are classified as requiring handling in Category 2 facilities and their shipment must be handled as 'infectious', the use of EBV-established cell lines as reference materials is not practical. We therefore chose to produce a panel of genomic DNA's derived from cell lines which could be certified as a 'higher order' reference material panel. Purified genomic DNA was freezedried in glass ampoules. Twenty one laboratories from seventeen countries collaborated in a validation study of the panel of proposed reference materials.

Analysis of material homogeneity showed a significant level of variability between fills and between ampoules. Reasons for this are not clear. That the source of the variation is not due to the spectrophotometer is demonstrated by the low level of variability within ampoules and within the control sample reads (n=10; %CV=1.84). Variation in DNA concentration between fills may be due to inaccurate quantitation prior to ampoule filling, or due to poor homogeneity of the bulk DNA prior to filling. Variation between ampoules of the same fill may also be due to poor homogeneity of the bulk DNA. It is difficult to achieve complete homogeneity in solution whilst retaining the high molecular weight DNA required for this application. Because of this variability, users are requested to determine the DNA concentration of each ampoule themselves. The high level of homogeneity within the reconstituted ampoules however, means that the user can be confident that the sample concentrations will not significantly vary between aliquots from a single ampoule.

Analysis of material stability by Q-PCR and gel electrophoresis of accelerated degradation samples shows some degradation at +56°C after 2 years. However, the limited extent of degradation at elevated temperature and the absence of degradation at the storage temperature of -20°C after 2 years indicates that the DNA should be stable for many years. Further samples stored at these temperatures as well as others stored at intermediate temperatures will be monitored at regular intervals in the future as part of planned quality control testing.

DNA profiling of the materials showed very small additional peaks at two loci in one sample (07/174). These peaks were not detected in the original blood samples. As the participants of the collaborative study did not obtain any anomalous results specific to this material and the lack of additional peaks at other loci is suggestive that these very minor peaks are caused by microsatellite mosaicism rather than contamination.

The wide spread of allele sizes obtained in the collaborative validation study is typical of that obtained in Fragile X testing external quality assessment schemes. A total of 18 incorrect results were reported, giving an overall error rate of 4.9%. This error rate is similar to the 5% level found in an Italian 5-year quality assessment 7 but higher than that observed in our previous studies with different panels (Factor V Leiden: 0.7%; Prothrombin mutation G20210A: 0.7%; Haemophilia A Intron 22 Inversion: 1.8%) 22 [& E.G. unpublished data]. The high variability of the results, both in reported repeat numbers and the interpretation of results, emphasise the difficulty of FMR1 repeat sizing and the need for Fragile X syndrome reference materials. The finding by two laboratories of an unexpected 7-repeat PCR product is a concern. It is unclear if this small additional putative allele is representative of the clinical sample from which it was derived or is a cell culture or typing artefact. To avoid confusion in the use of this sample as a referencematerial, a caution on the possibility of detecting this putative allele is included in the 'Instructions for Use' for the panel. While the presence of this allele makes the sample unsuitable for use in external quality assessment, it does not detract from the sample's utility as a reference material, once the user is aware of it.

By producing the reference panel from a single large batch of pooled DNA derived from a single bulk cell culture batch, the need to repeatedly re-culture the cells for the production of multiple small batches is avoided. This is important as new size alleles can be generated over time in cell culture, particularly when allelic methylation is only partial. It is therefore possible that if this reference material batch is ever exhausted, that the genotype of the replacement batch may not be identical. However, at that stage a repeat collaborative validation study would be performed to characterise the materials fully.

Two female full mutation samples were included in the study as neither had been previously genotyped and demonstrated to be suitable for inclusion in a reference panel.

Both samples performed well. To maintain the widest variety of allele sizes, sample 1 (07/168) was included in the reference panel of five samples (normal female, female premutation, male pre-mutation, female full mutation, male full mutation).

All laboratories that participated in the collaborative study were sent a study report and their approval was sought. All laboratories agreed that the candidate material is suitable for use as a genetic reference panel for Fragile X syndrome. The most frequent comment from the participants (n=6) was that the DNA was of good quality. Three laboratories reported that the DNA concentration varied more than expected and two laboratories did not like the glass ampoules. The report was then endorsed by the board of the European Society for Human Genetics and was finally submitted to the Expert Committee on Biological Standardization at the World Health Organization (WHO). In November 2008, the panel was established as a WHO International Standard and made available through the NIBSC product catalogue (http://www.nibsc.ac.uk/products/catalogue.html -code: 08/158).

The panel is the only certified set of genomic DNA reference materials for Fragile X testing and is available to all diagnostic laboratories worldwide to aid accuracy in Fragile X syndrome testing. The panel will be of particular importance for the validation of commercial diagnostic kits for Fragile X syndrome which are beginning to enter the market, for laboratories setting up new in-house methods such as methylation analysis and for validating existing techniques after a change of reagents, operator or equipment.

The Full data from the homogeneity study, the collaborative study and participant methods used is available as supplementary information at the European Journal of

Human Genetics website

Titles and Legends to Figures Table 1. Ampoule product summaries of the six candidate materials

B. Accelerated degradation-Agarose Gel

Legend: 0.7% agarose gel of 200ng of each sample. The size marker is Hyperladder VI (Bioline).

Table 2. Testing procedures used by the participants

Legend:

The graphs show the number of laboratories (Y axis) detecting each allele length (Xaxis). The number of repeats was calculated for each sample in all laboratories, where possible, by taking a mean of all three replicates of the same sample tested in one or more techniques. Where a range of repeats was given the mean value was used. Values reported with 'greater than' or 'less than' symbols (>, <) were omitted. Where an approximate size was given, this was taken as definitive. All values have been rounded up to whole numbers for clarity. Sample outliers as identified by Grubbs Test have been omitted.

Table 3. Summary of allele sizes and ranges

B.

A.

Accelerated degradation-Real-Time PCR

Material

  blotting) and sample distribution restrictions in Europe imposed by the IVD Directive (Directive 98/79/EC of the European Parliament and of the Council of 27 October 1998 on in vitro diagnostic medical devices).

  Hepatitis A, Hepatitis B, Hepatitis C, Parvovirus B19 and HIV1. All EBV-transformed cell lines remain positive for the presence of the EBV genome. Whilst there is an unquantified risk of EBV infectivity in the cell lines, infective viral particles are unlikely to survive DNA extraction and have not been detected in electron microscopy studies or in infectivity assays (JRH unpublished data).

(

  previously characterised clinical samples from patients and normal controls), six laboratories used DNA samples supplied by the Coriell Institute and one lab used NIST PCR product controls. Tables listing the full genotyping results of the validation study are available as Supplementary Data. Summaries of the clinical interpretations are as follows: Samples 1, 11 & 12 (normal female): 19 labs reported 'normal female' (or 'normal genotype').

Figure 1

 1 Figure 1. Homogeneity

Figure 2

 2 Figure 2. Accelerated Degradation

Figure 3 .A.

 3 Figure 3.

Figure 4 .

 4 Figure 4. Distribution of allele repeat numbers reported by study participants.

Table 1 . Product summaries of the six candidate materials

 1

	NIBSC Code:	07/120	07/122	07/168	07/170	07/172	07/174
		Female,	Female,	Female,	Male,	Female,	Male,
		Wild-type	Pre-	Full	Full	Full	Pre-mutation
			mutation	mutation	mutation	mutation
				1		2
	Date filled	19.04.07	26.04.07	07.06.07	08.06.07	14.06.07	21.06.07.
	Coefficient of	0.31	0.15	0.20	0.16	0.25	0.24
	variation of the fill
	(%) (n=39-44)
	Residual moisture	3.62	3.127	1.145	1.443	0.618	0.823
	after lyophilisation
	(%) (n=12)
	Mean dry weight (g)	0.0025	0.0022	0.0019	0.0020	0.0021	0.0024
	(n=6)
	Residual oxygen%	0.41	0.61	0.27	0.29	0.16	0.59
	(n=12)
	Mean OD ratio	1.85	1.79	1.88	1.83	1.86	1.89
	260/280 nm (n=6)
	Mean DNA conc.	573.4	488.0	581.4	502.1	576.0	740.4
	following
	resuspension in 40ul
	water ng/µL (n=6)
	pH following	7.4	7.6	7.4	7.5	7.8	7.4
	resuspension
	No of ampoules	1728	2132	1758	2061	1774	1211
	available
	Presentation	Sealed, glass DIN ampoules
	Excipient	Trehalose 2.5mg/ml in Tris/EDTA buffer

Table 2 . Testing procedure used by the participants Testing procedure Participant laboratory code number

 2

					Storage Temperature
			-150°C	-20°C	+56°C
			Cp	CV%	Cp	CV%	Cp	CV%
	07/120 (normal female)	20.51	0.11	20.71	0.20	21.05	0.07
	07/122 (♀ pre-mutation)	21.23	0.03	20.57	0.10	20.80	0.13
	07/168 (♀ full mutation 1)	20.97	0.06	20.61	0.13	20.77	0.36
	07/170 (♂ full mutation)	21.13	0.08	20.98	0.10	20.99	0.10
	07/172 (♀ full mutation 2)	N/D		N/D		N/D
	07/174 (♂ pre-mutation)	21.25	0.12	20.91	0.18	20.70	0.12
	B.	Accelerated degradation-Agarose Gel

Acknowledgements

We thank Emma Gillaspy and Jacqueline Rice (Manchester) & James Macpherson (Salisbury) for preliminary testing and field trials. We gratefully acknowledge the following individuals who participated in the collaborative study: Prof C Beldjord, Paris; Dr B Bennetts, Sydney; Dr J Macpherson, Salisbury; Dr M Mila, Barcelona; Dr Z Musova, Prague, Dr E Raukas, Turku; Dr Reena Ray, Dr E Spriggs, Winnipeg; Dr K Richie, Gaithersburg; Dr F Rousseau, Dr J-S Côté, Quebec City; Dr M R Dos Santos, Porto; Dr R Saxena, Dr I C Verma, Dr S Kohli, New Delhi, Prof M Schwartz, Copenhagen; Dr H Slater, Melbourne, Dr I Vlasak, Salzburg; Dr J Weiss, Dr M Losekoot, Leiden; E Doherty, R Williams, A Zhang, C Yang, Auckland; Dr T lenk, Mr K Young, Celera, USA; Dr M Zannusi, Milan. This work was partly funded by: 1. The UK Department of Health through the National Genetics Reference Laboratory (Manchester); 2. An EU FP5 grant "CRMGEN" Contract No. G6RD-2001-00581; 3. EU FP6 Network of Excellence EuroGentest" Contract 512148

Conflict of Interest Statement

A fee is charged for the panel by NIBSC to cover handling and shipping.


Jaume Bertranpetit
email: jaume.bertranpetit@upf.edu

Martin Sikora

Hafid Laayouni

David Comas

Francesc Calafell

A genomic analysis identifies a novel component in the genetic structure of Sub-Saharan African populations

Keywords: population genetics, Africa, population history

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INTRODUCTION

Human population genetics has recently completed a circle. It started with the so-called classical polymorphisms (i.e., blood groups and other protein polymorphisms) that were analyzed on the basis of their allele frequencies with potent statistical instruments such as principal component analysis (PCA). This era culminated with the landmark publication of the magnificent book by Cavalli-Sforza et al. [START_REF] Cavalli-Sforza | The history and geography of human genes[END_REF] ; however, a few shortcomings of classical polymorphisms can be pointed out: relatively few loci were used; their relationship to the underlying genetic variation was mostly unknown; and they could have been subjected to confounding by natural selection. PCR and automated sequencing heralded the uniparental marker era: mtDNA and the non-recombining region of the Y chromosome (NRY) could be routinely analyzed, and a firm phylogeography could be established for both genomic regions, allowing the dissection of population structure with unprecedented precision and reliability. But yet, they behave as just two loci, where natural selection cannot be ruled out, as well as the peculiarities associated with their sex-specific transmission. Another technological development spearheaded a new breakthrough in human population genetics: single nucleotide polymorphism (SNP) array genotyping platforms have made it affordable to genotype hundreds of thousands of markers. The results are again treated in terms of allele frequencies and subjected to PCA or to newer techniques such as Bayesian classification algorithms. Now, the whole genome is covered, and the action of selection is masked by a vast majority of putatively neutral markers.

The genetics of African populations, of paramount interest given the recent African origin of humankind, has been through the full cycle of studies. Cavalli-Sforza et al. [START_REF] Cavalli-Sforza | The history and geography of human genes[END_REF] identified a north-south gradient in the continent that could be attributed to the Bantu expansion, while other principal components had a less clear interpretation.

African mtDNA phylogeography was firmly established by Salas et al. [START_REF] Salas | The making of the African mtDNA landscape[END_REF] , who described the structure of maternal lineages in the continent, and identified some haplogroups involved in human expansions such as the Bantu expansion. Deep analyses of maternal lineages in African hunter-gatherers (Khoisan speakers and Pygmies) have revealed a clearly structured phylogeny for the mtDNA [START_REF] Batini | Phylogeography of the human mitochondrial L1c haplogroup: genetic signatures of the prehistory of Central Africa[END_REF][START_REF] Quintana-Murci | Maternal traces of deep common ancestry and asymmetric gene flow between Pygmy hunter-gatherers and Bantuspeaking farmers[END_REF][START_REF] Behar | The dawn of human matrilineal diversity[END_REF] . A number of papers have approached both the general and the more local aspects of non-recombining part of the Ychromosome in Africa 6; 7 , although its phylogeographic structure has not been as refined as its maternal counterpart. More recently, in a landmark paper by Tishkoff et al. [START_REF] Tishkoff | The genetic structure and history of Africans and African Americans[END_REF] , 1327 nuclear microsatellite markers were analyzed in 121 African populations, identifying a number of layers in the African population structure that could be related to history, language, and geography. The continent, south of the Sahara, seems to be dominated by a component mostly correlated with Niger-Congo speaking populations, while other components are found in the Sahel, among Nilo-Saharan speakers, and in Afro-Asiatic speakers in the north and northeast. Among the hunter-gatherer populations, the Khoisan-speaking Hadza of Tanzania were clearly distinct, while Pygmies could not be discriminated from the South African Khoisan. At higher discrimination level, western Pygmies became distinct, but the eastern Pygmies remained similar to the Khoisan. In another recent publication, Bryc et al. analyzed SNP data obtained from West Africans (and African Americans), revealing a structure reflecting primarily language and secondarily geographical distances [START_REF] Bryc | Genome-wide patterns of population structure and admixture in West Africans and African Americans[END_REF] . Unfortunately, this work is restricted mainly to populations in Central West Africa, around the Gulf of Guinea. Both of these recent studies have greatly advanced our understanding of the genetic structure of Sub-Saharan Africa. However, both in Tishkoff et al. and Bryc et al. as well as in previous works, the area between Central and South Africa remains under sampled. However, southeast Africa is a key geographical zone to understand the Bantu expansion routes, making it a region of particular interest for the population history of Sub-Saharan Africa.

DATA

In a case-control study for placental malaria, we obtained, with appropriate informed consent, 180 cases and 180 controls from Mozambique, in southeast Africa.

These samples were genotyped with the Affymetrix GeneChip® Human Immune and Inflammation 9K SNP Kit, resulting in a total of 279 samples with reliable data after stringent quality control. Other African samples with genome wide SNP data available are Biaka Pygmies, Mbuti Pygmies, Mandenka, Yoruba, San, and Bantu-speakers from the HGDP panel [START_REF] Li | Worldwide human relationships inferred from genome-wide patterns of variation[END_REF] , and the Maasai, Luhya, Yoruba, and African-Americans from HapMap Phase 3 (http://hapmap.ncbi.nlm.nih.gov/). The intersection of all arrays provides a common set of 2,841 SNPs with genotype data for all populations (see Supplementary Information for details).

RESULTS

First, we wanted to test if the number of SNPs available (2,841 SNPs) provides enough genetic resolution to detect any structure in African populations and provide a reference for the number of SNPs needed in population studies. To that effect, we combined the global Human Genome Diversity Panel (HGDP) and HapMap Phase 3 genotype data (~460,000 SNPs) and subjected them to PCA (see Supplementary Information for details). Results are similar to those obtained with the HGDP samples, with the first and second PC (Figure 1A) separating East Asia (upper left corner of the plot) from Europe (bottom centre) and sub-Saharan Africa (upper right) 10; 11 . The same structure is recovered when random subsamples of 100,000 (Figure 1B), 10,000 (Fig. 1C), and 1,000 (Figure 1D) SNPs are considered, although inter-individual variation increases. A random set of 2,841 SNPs from this pooled HGDP-HapMap dataset (Figure 1E) performs similarly to the set of 2,841 SNPs related to immunity and inflammation (Figure 1F), despite of the slightly reduced inter-population differentiation of the latter, which is expected as they are gene-based SNPs [START_REF] Barreiro | Natural selection has driven population differentiation in modern humans[END_REF] . We can conclude that the common set of 2,841 SNPs genotyped is an appropriate tool to study population structure in African populations; in general, worldwide patterns are evident and robust when using a minimum of 1,000 SNPs.

Next, we applied PCA [START_REF] Patterson | Population structure and eigenanalysis[END_REF] and STRUCTURE 14; 15 to 775 individuals in 11 populations of sub-Saharan African descent. The first PC (Figure 2A) and STRUCTURE with K=2 (Figure 3) separate the Nilo-Saharan-speaking Maasai from all other populations, with neighboring Luhya and African Americans in an intermediate position. Both the second PC and K=3 separate the hunter-gatherer samples, presumably ancestral Pygmy and San populations from the rest. The third PC allows us to discriminate between western/central (Mandenka, Yoruba), eastern (Maasai, Luhya), and southeastern populations (Mozambique), irrespectively of language family. This is the PC that is mostly correlated with geography (Figure 2C), and the fact that it is the third rather than the first component, as would be expected if isolation by distance was the predominant force shaping genetic diversity [START_REF] Novembre | Interpreting principal component analyses of spatial population genetic variation[END_REF] , implies that directional population movements (such as the Bantu expansion) and barriers to gene flow (such as that between food producers and hunter-gatherers) are more relevant than geographic distance to understand the genetic landscape of sub-Saharan Africa. The distinction between west and southeast Africa is also shown with at K=4; at K=5, the Niger-Congo speaking Luhya are separated from the rest. The new component that appears at K=6 is restricted to African Americans and Biaka Pygmies, and is the last component that can be attributed to specific populations.

DISCUSSION

The preceding results are in agreement with what was found previously by Tishkoff et al. using microsatellites, and goes beyond with new findings and refinement of previous genetic studies:

i) The main distinction is among Niger-Congo groups and the rest, including Nilo-Saharan speakers and hunter-gatherers (with the Khoisan having preserved their ancestral language but not Pygmies). Among Niger-Congo populations, geography is the main factor explaining the genetic differences, with a remarkable similarity among western populations (Yorubas and Mandenka), which could reflect a burst in the expansion to the west, related to iron technology and Niger-Congo languages.

ii) The southeastern Bantu from Mozambique are remarkably differentiated from the western Niger-Congo speaking populations, such as the Mandenka and the Yoruba, and also differentiated from geographically closer Eastern Bantu samples, such as Luhya. These results suggest that the Bantu expansion of languages, which started ~5,000 years ago at the present day border region of Nigeria and Cameroon, and was probably related to the spread of agriculture and the emergence of iron technology [START_REF] Vansina | New Linguistic Evidence and 'the Bantu Expansion[END_REF][START_REF] Phillipson | African archaeology[END_REF][START_REF] Newman | The peopling of Africa : a geographic interpretation[END_REF] , was not a demographic homogeneous migration with population replacement in the southernmost part of the continent, but acquired more divergence, likely due to the integration of pre-Bantu people.

The complexity of the expansion of Bantu languages to the south (with an eastern and a western route [START_REF] Oslisly | The middle Ogooué valley, Gabon: cultural changes and palaeoclimatic implications of the last fourmillenia[END_REF] ), might have produced differential degrees of assimilation of previous populations of hunter-gatherers. This assimilation has been detected through uniparental markers due to the genetic comparison of nowadays hunter-gatherers (Pygmies and Khoisan) with Bantu-speaker agriculturalists 2; 21-24 . Nonetheless, the singularity of the southeastern population of Mozambique (poorly related to present Khoisan) could be attributed to a complete assimilation of ancient genetically differentiated populations (presently unknown) by Bantu-speakers in southeastern Africa, without leaving any pre-Bantu population in the area to compare with.

iii) The difference between hunter-gatherers and the rest of South Saharan populations is important but it is not the main trait in the African genetics. To note is the strong similarity among the three studied populations, with no specific Pygmy component, but an important Bantu introgression (as seen in K=3) in Biaka Pygmies.

Pygmies should be included along with Khoisan in the search for deep-rooted African and Human lineages. Moreover, the specific component that identifies the three huntergatherer populations is found at a small amount in all other African populations, as a possible result of introgression with previous settlers of most African territory.

As a more general observation, we found that as little as 1,000 genome wide SNPs are enough to robustly recover the patterns of genetic structure among worldwide populations. It has to be noted that even though this low number seems to be sufficient for inferring major demographic events and broad population structure, it remains doubtful whether it will be sufficient for more fine-scale inference, as for example within a genetically uniform region such as Europe. Nevertheless, the high level of genetic structure in Sub-Saharan Africa allows us to be confident in our conclusions.

Furthermore, the fact that our dataset of 2,841 SNPs has only limited fine-scale resolution makes the observed strong differentiation of the population from Mozambique even more striking. The genetic analysis of a large number of SNPs is thus providing a robust tool to refine our understanding of past populations history.

Figure 1 .

 1 Figure 1. PCA of merged HGDP and Hap Map 3 samples.Panels show the results of the PCA for the full merged set of SNPs (A; 460,147 SNPs), for random subsets of 100,000 (B), 10,000 (C), 1,000 (D), and 2,841 SNPs (E), as well as for the 2,841 SNPs in the merged analysis set including the samples from Mozambique (F). As can be seen, the general pattern of differentiation is reproduced even using only a random subset of 1,000 SNPs. Different colors indicate continental region for the respective populations (SSAFR: Sub-Saharan Africa; MENA: Middle East and North Africa; EUR: Europe; CSASIA: Central and South Asia; EASIA: East Asia; OCE: Oceania; AME: Americas).

Figure 2 .

 2 Figure 2. PCA of sub-Saharan African populations. Panels show plots of the first three principal components obtained from the 11 sub-Saharan African populations. 2A -first and second components. 2B -first and third components. 2C -Biplot of rotated PC1 and PC3 superimposed onto a map of Africa. Geographical locations of the populations are indicated by their names and their respective enlarged plot symbols. Different colors indicate linguistic or cultural group for the respective populations (light green: Nilo -Saharan; light blue: Niger-Congo; orange: Hunter-Gatherer; grey: admixed).

Figure 3 .

 3 Figure 3. STRUCTURE results for sub-Saharan African populations.Depicted are the results of 5 runs each for the number of clusters ranging from K = 2 to K = 7, combined using CLUMPP.

Acknowledgements

This research was supported by Dirección General de Investigación, Ministerio de Ciencia y Tecnología, Spain (grants SAF2007-63171, BFU2007-63657) and Direcció General de Recerca, Generalitat de Catalunya (2009 SGR 1101). SNP genotyping services were provided by the Spanish "Centro Nacional de Genotipado" (CEGEN; http://www.cegen.org); Bioinformatic services were kindly provided by the Genomic Diversity node, Spanish Bioinformatic Institute (www.inab.org). MS was supported by a PhD fellowship from the Programa de becas FPU del Ministerio de Educación y Ciencia, Spain (AP2005-3982).


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