- Email: [email protected]
High resolution melting analysis for mutation detection for PTPN11 gene: Applications of this method for diagnosis of Noonan syndrome
Clinica Chimica Acta 409 (2009) 75–77
Contents lists available at ScienceDirect
Clinica Chimica Acta j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / c l i n c h i m
High resolution melting analysis for mutation detection for PTPN11 gene: Applications of this method for diagnosis of Noonan syndrome Fu-Sung Lo a,b, Ji-Dung Luo c, Yann-Jinn Lee d,e, San-Ging Shu f, Min-Tzu Kuo a, Chiuan-Chian Chiou g,⁎ a
Division of Pediatric Endocrinology, Chang Gung Memorial Hospital, Taoyuan, Taiwan College of Medicine, Chung Gung University, Taoyuan, Taiwan Graduate Institute of Biomedical Science, Chang Gung University, Taoyuan, Taiwan d Department of Pediatrics, Mackay Memorial Hospital, Taipei, Taiwan e Department of Medical Research, Mackay Memorial Hospital, Taipei, Taiwan f Department of Pediatrics, Taichung Veterans General Hospital, Taichung, Taiwan g Department of Medical Biotechnology and Laboratory Science, Chang Gung University, Taoyuan, Taiwan b c
a r t i c l e
i n f o
Article history: Received 12 June 2009 Received in revised form 28 August 2009 Accepted 28 August 2009 Available online 6 September 2009 Keywords: Noonan syndrome PTPN11 High resolution melting analysis Mutation scanning
a b s t r a c t Background: Noonan syndrome (NS, OMIM 163950) is a relatively common autosomal dominant disorder and has significant phenotypic overlap with Costello Syndrome and cardio-facio-cutaneous syndrome. Molecular diagnosis is useful for differential diagnosis. PTPN11 gene mutation is the most common mutation associated with NS and hence is a suitable target for molecular diagnostics. Methods: High resolution melting (HRM) analysis was used for screening of PTPN11 mutations. Eleven DNA samples with 10 known PTPN11 mutations were used for HRM calibration. Said calibrations were then applied to mutation screening of a panel of 50 additional NS patients. Results: HRM analysis differentiated all of the 10 known mutations and identified 9 additional mutations from 10 patients in the blind study, which is in line with results obtained by sequencing. Conclusions: HRM analysis is a rapid, reliable, and low-cost tool for detection of PTPN11 genetic variants. © 2009 Elsevier B.V. All rights reserved.
1. Introduction Noonan syndrome (NS) (OMIM 163950) is a relatively common autosomal dominant disorder with a frequency estimated between 1:1000 and 1:2500 live births. Mutations in a tyrosine phosphatase gene, PTPN11 (OMIM 176876), are the most common mutations associated with Noonan syndrome, accounting for 31–60% of individuals with this disorder [1]. PTPN11 is located on 12q24.1 and contains 15 exons. Ninety different germline PTPN11 mutations have so far been identified in patients with Noonan syndrome [2]. All are dispersed in 10 exons (exon 1, 2, 3, 4, 7, 8, 11, 12, 13 and 14). Our laboratory previously reported 10 different PTPN11 mutations in four exons (exons 3, 4, 8 and 13) from 13 Taiwanese patients with NS [3]. Therefore, molecular detection of PTPN11 mutation is challenging, owing to the size of this gene, its broad mutation spectrum, and its highly polymorphic nature. To date, most mutational screening of PTPN11 has been performed by single strand conformation poly-
Abbreviations: CS, Costello Syndrome; CFC, cardio-facio-cutaneous; DHPLC, denatured high-performance liquid chromatography; HRM, high resolution melting; NS, Noonan syndrome; SSCP, single strand conformation polymorphism. ⁎ Corresponding author. Department of Medical Biotechnology and Laboratory Science, Chang Gung University, 259 Wen-Hwa 1st Road, Kwei-Shan, Taoyuan, 333, Taiwan. Tel.: +886 3 2118800x5204; fax: +886 3 2118035. E-mail address: [email protected] (C.-C. Chiou). 0009-8981/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.cca.2009.08.021
morphism (SSCP)/sequencing, denatured high-performance liquid chromatography (DHPLC)/sequencing or direct sequencing [4–6]. These methods for large-scale detection of mutations are expensive and time-consuming. Recently, a powerful and cost-effective tool, high resolution melting (HRM) curve analysis, has been developed for genotyping and mutation scanning. This method uses a saturating dye to generate an accurate melting curve with resolution that can differentiate even a single-nucleotide variation in an amplicon [7,8]. This method does not require any processing after PCR and melting analysis and is thus suitable for screening large numbers of samples. In this study, we used HRM analysis to develop a rapid protocol for scanning PTPN11 gene mutations. 2. Patients and methods 2.1. Patients Informed consent for DNA study was obtained from all patients, according to protocols approved by the Medical Ethics and the Human Clinical Trials Committee of Chang Gung Memorial Hospital. NS was diagnosed according to the major (typical facial findings, cardiac defects, and pterygium colli) and minor criteria (short stature, psychomotor retardation or speech delay, bleeding diathesis, family history of NS, and other additional features) [9]. Eleven DNA samples
76
F.-S. Lo et al. / Clinica Chimica Acta 409 (2009) 75–77
Table 1 Primers and HRM conditions for mutation scanning of the PTPN11 gene. Exon
Amplicona
Forward/reverse primers (5′ → 3′)
Size (bp)
HRM normalization (°C) Pre-melting slider setting
3
3-1
3
3-2
4
4-1
4
4-2
7
7
8
8
13
13
a
ACGTGGAAGATGAGATCTG CCCGTGATGTTCCATGTAAT ACTATGACCTGTATGGAGGG GGAGCAGCAGACTTTGT AGAACAACATGAACCCATAGTAGA CGTCATTGCTCTCCCCT GAGAGAGCCAGAGCCAC AACATCTTGCCAGACCC TGTGACTCTTTGACACGTAATAA GAGTGACTATTACTGAGCGG TGAAGCAGTCCAGGACTTAT ATAGGCTAGAAATGTATGGTCAG GGCTCTGCAGTTTCTCTTT CTAGCAAGAGAATGAGAATCCG
Post-melting slider setting
Temperature shift
200
77–78
77–78
7.37
186
77.5–78.5
77.5–78.5
8.42
212
79.5–80.5
83.5–84.5
11.58
151
79–80
83.5–84.5
7.37
178
75–76
80–81
10.53
175
77–78
82–83
10.53
241
82.5–83.5
85.5–86.5
10.53
Exons 3 and 4 were amplified as two overlapping amplicons.
from as many patients with previously identified PTPN11 mutations were used for optimization and validation of HRM. Optimized HRM conditions were applied to further screening of PTPN11 mutations in a panel of 50 additional NS patients from 7 medical centers (Chang Gung Children Hospital, Mackay Memorial Hospital, Taichung Veteran General Hospital, Changhua Christian Hospital, National Cheng Kung University Hospital, Kaoshiung Medical University Hospital, Kaoshiung Veteran General Hospital) of Taiwan.
these exons. HRM analysis was optimized using six wild-type DNA samples and 11 DNA samples carrying 10 different PTPN11 variants that have been previously identified (Table 2) [3]. The 10 known variants are located at amplicons 3-1, 3-2, 4, 8, and 13. For exon 7, HRM optimization was performed only with control DNA, as DNA carrying genetic variations in this exon was not available in our laboratory. In the optimized condition, HRM identified all the known variants (Fig. 1A–E).
2.2. Amplification of PTPN11 exons
3.2. Mutation scanning of PTPN11 gene mutations in 50 NS patients
Genomic DNA samples were extracted from peripheral whole blood using the Easy Pure Genomic DNA Isolation Kit (Bioman Scientific, Taipei, Taiwan). Exons 3, 4, 7, 8, and 13 of PTPN11 gene were amplified from genomic DNA by polymerase chain reaction (PCR) using seven sets of primers (Table 1). For exon 3 and exon 4, which are longer than 250 bp, two sets of primers were used to amplify the exons in two overlapping segments. All primers were designed using LightCycler® Probe Design Software v.2.0. PCR was performed on a LightCycler® 480 thermal cycler (Roche) using a Lightcycler® 480 High Resolution Melting Master kit. The 20-μl amplification mixture consisted of 1× master reagent provided by the kit, 0.2 μM of each primer, and 100 ng of template DNA. The cycling program was 10 min at 95 °C for activation of FasStart Taq DNA polymerase and denaturation of template DNA, followed by 35 cycles of denaturation at 95 °C for 15 s, annealing at 59 °C to 61 °C for 15 s, and 72 °C for 30 s.
Optimized HRM analysis was applied for scanning of PTPN11 mutations in 50 additional NS patients. Nine different variants were identified in 10 patients by this method (Fig. 1F–I), which were then confirmed by direct sequencing as point mutations (Table 2). All 9 mutations were missense and had been noted in previous studies [3,4].
2.3. Melting curve acquisition and analysis Melting analysis was performed after PCR, using the same instrument. Samples were heated to 95 °C for 5 min, rapidly cooled to 40 °C, heated to 60 °C for 30 s, and then ramped to 95 °C. Twentyfive data points were acquired for every 1 °C, from 60 °C to 95 °C. Melting data was analyzed using LightCycler® 480 gene scanning software (Roche). Pre and post-melting slider settings, as well as the temperature shift for normalization of each amplicon, are listed in Table 1. Differential plots were also generated by the software, using the wild types as references. 3. Results 3.1. Optimization of HRM curve analysis Complete PTPN11 mutational screening required investigation of 15 exons. However, in this study, we only analyzed exons 3, 4, 7, 8, and 13, since they contain the majority (90%) of mutations [4]. Seven pairs of primers were designed for amplification and amplicon melting of
4. Discussion NS was first reported by Jacqueline Noonan in 1963 [9]. However, definite clinical diagnosis of this condition is difficult because it is clinically heterogeneous and its phenotypic expression is highly variable and changes with age [10,11]. NS has significant phenotypic overlap with Costello Syndrome (CS) (OMIM 218040) and cardiofacio-cutaneous (CFC) syndrome (OMIM 115150). Molecular diagnosis is therefore useful for differential diagnosis between these three syndromes. However, there are many genes in the Ras signaling pathway that could cause NS, CS, and CFC: PTPN11, KRAS, and SOS1 for NS, HRAS for CS, KRAS, BRAF, MEK1 and MEK2 for CFC. We need a Table 2 List of PTPN11 genetic variants described in this study. Amplicon
Variants for calibrationa
Variants identified by HRMa
3-1
c.184A > G c.188A > G c.214G > T c.218C > T c.317A > C c.417G > C (2 patients)
c.172A > G c.179G > C (2 patients) c.211T > C c.215C > G
3-2
4 7 8
c.755T > A
13
a
c.855T > G c.922A > G c.1493G > T c.1510A > G
c.1504T > A c.1507G > C c.1508G > A c.1517A > C
GenBank RefSeq: NM_0028343.3. A of the ATG start codon is designated as +1.
F.-S. Lo et al. / Clinica Chimica Acta 409 (2009) 75–77
77
Fig. 1. The subtractive fluorescent difference plots of wild-type and patient mutations of the PTPN11 gene for validation study (A–E) and blind analysis (F–I) using HRM analysis.
rapid, powerful, and cost-effective tool for large-scale detection of gene mutations. PTPN11 gene mutation is the most common mutation associated with NS and hence is a suitable target for molecular diagnostics of NS. Many methods have been used for detecting PTPN11 mutations, including SSCP, DHPLC, denaturing gradient gel electrophoresis, temperature gradient capillary electrophoresis, PCR-RFLP and direct sequencing. However, these methods require separation of PCR products on a gel or a column and are time-consuming and cost ineffective. In contrast, PCR and HRM analysis can be completed in a closed tube. After PCR amplification, melting curves are generated by monitoring the fluorescence of a saturating dye. No post-PCR manipulations or sequence specific probes are required. Therefore, HRM has distinct advantages over current techniques for genotyping and mutation scanning of PTPN11. We demonstrated the efficacy of HRM for mutation scanning of the PTPN11 gene in patients with Noonan syndrome. This method differentiated all of the 10 known mutations from wild types and identified another 9 mutations in a blind study, which are in line with results obtained by sequencing. The mutation rate in the blind study was only 20% (10/50), less than that from previous reports [1]. One possible reason is that some mutations are located in the exons that we have not analyzed. Another reason is that some of the patients were misclassified, as NS is highly heterogeneous and difficult to conduct definite diagnosis, which emphasizes the importance of a reliable molecular diagnostic method. In summary, PTPN11 provided an excellent gene model, enabling us to analyze these different mutations that span it. These results demonstrate the potential of this technology to reduce the burden of sequencing and to develop a rapid molecular diagnostic method for NS.
Acknowledgements This research was supported by Grant CMRPG470071, awarded by Chang Gung Memorial Hospital, Taiwan.
References [1] Zenker M, Buheitel G, Rauch R, et al. Genotype-phenotype correlations in Noonan syndrome. J Pediatr 2004;144:368–74. [2] Aoki Y, Niihori T, Narumi Y, Kure S, Matsubara Y. The RAS/MAPK syndromes: novel roles of the RAS pathway in human genetic disorders. Hum Mutat 2008;29:992–1006. [3] Hung CS, Lin JL, Lee YJ, Lin SP, Chao MC, Lo FS. Mutational analysis of PTPN11 gene in Taiwanese children with Noonan syndrome. J Formos Med Assoc 2007;106:169–72. [4] Kosaki K, Suzuki T, Muroya K, et al. PTPN11 (protein-tyrosine phosphatase, nonreceptortype 11) mutations in seven Japanese patients with Noonan syndrome. J Clin Endocrinol Metab 2002;87:3529–33. [5] Sarkozy A, Conti E, Seripa D, et al. Correlation between PTPN11 gene mutations and congenital heart defects in Noonan and LEOPARD syndromes. J Med Genet 2003;40:704–8. [6] Tartaglia M, Mehler EL, Goldberg R, et al. Mutations in PTPN11, encoding the protein tyrosine phosphatase SHP-2, cause Noonan syndrome. Nat Genet 2001;29:465–8. [7] Wittwer CT, Reed GH, Gundry CN, Vandersteen JG, Pryor RJ. High-resolution genotyping by amplicon melting analysis using LCGreen. Clin Chem 2003;49:853–60. [8] Wittwer CT. High-resolution DNA melting analysis: advancements and limitations. Hum Mutat 2009;30:857–9. [9] Noon JA, Ehmke DA. Associated non cardiac malformations in children with congenital heart disease. J Pediatr 1963;63:468–70. [10] Sharland M, Burch M, McKenna WM, Paton MA. A clinical study of Noonan syndrome. Arch Dis Child 1992;67:178–83. [11] van der Burgt I, Thoonen G, Roosenboom N, et al. Patterns of cognitive functioning in school-aged children with Noonan syndrome associated with variability in phenotypic expression. J Pediatr 1999;135:707–13.
Contents lists available at ScienceDirect
Clinica Chimica Acta j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / c l i n c h i m
High resolution melting analysis for mutation detection for PTPN11 gene: Applications of this method for diagnosis of Noonan syndrome Fu-Sung Lo a,b, Ji-Dung Luo c, Yann-Jinn Lee d,e, San-Ging Shu f, Min-Tzu Kuo a, Chiuan-Chian Chiou g,⁎ a
Division of Pediatric Endocrinology, Chang Gung Memorial Hospital, Taoyuan, Taiwan College of Medicine, Chung Gung University, Taoyuan, Taiwan Graduate Institute of Biomedical Science, Chang Gung University, Taoyuan, Taiwan d Department of Pediatrics, Mackay Memorial Hospital, Taipei, Taiwan e Department of Medical Research, Mackay Memorial Hospital, Taipei, Taiwan f Department of Pediatrics, Taichung Veterans General Hospital, Taichung, Taiwan g Department of Medical Biotechnology and Laboratory Science, Chang Gung University, Taoyuan, Taiwan b c
a r t i c l e
i n f o
Article history: Received 12 June 2009 Received in revised form 28 August 2009 Accepted 28 August 2009 Available online 6 September 2009 Keywords: Noonan syndrome PTPN11 High resolution melting analysis Mutation scanning
a b s t r a c t Background: Noonan syndrome (NS, OMIM 163950) is a relatively common autosomal dominant disorder and has significant phenotypic overlap with Costello Syndrome and cardio-facio-cutaneous syndrome. Molecular diagnosis is useful for differential diagnosis. PTPN11 gene mutation is the most common mutation associated with NS and hence is a suitable target for molecular diagnostics. Methods: High resolution melting (HRM) analysis was used for screening of PTPN11 mutations. Eleven DNA samples with 10 known PTPN11 mutations were used for HRM calibration. Said calibrations were then applied to mutation screening of a panel of 50 additional NS patients. Results: HRM analysis differentiated all of the 10 known mutations and identified 9 additional mutations from 10 patients in the blind study, which is in line with results obtained by sequencing. Conclusions: HRM analysis is a rapid, reliable, and low-cost tool for detection of PTPN11 genetic variants. © 2009 Elsevier B.V. All rights reserved.
1. Introduction Noonan syndrome (NS) (OMIM 163950) is a relatively common autosomal dominant disorder with a frequency estimated between 1:1000 and 1:2500 live births. Mutations in a tyrosine phosphatase gene, PTPN11 (OMIM 176876), are the most common mutations associated with Noonan syndrome, accounting for 31–60% of individuals with this disorder [1]. PTPN11 is located on 12q24.1 and contains 15 exons. Ninety different germline PTPN11 mutations have so far been identified in patients with Noonan syndrome [2]. All are dispersed in 10 exons (exon 1, 2, 3, 4, 7, 8, 11, 12, 13 and 14). Our laboratory previously reported 10 different PTPN11 mutations in four exons (exons 3, 4, 8 and 13) from 13 Taiwanese patients with NS [3]. Therefore, molecular detection of PTPN11 mutation is challenging, owing to the size of this gene, its broad mutation spectrum, and its highly polymorphic nature. To date, most mutational screening of PTPN11 has been performed by single strand conformation poly-
Abbreviations: CS, Costello Syndrome; CFC, cardio-facio-cutaneous; DHPLC, denatured high-performance liquid chromatography; HRM, high resolution melting; NS, Noonan syndrome; SSCP, single strand conformation polymorphism. ⁎ Corresponding author. Department of Medical Biotechnology and Laboratory Science, Chang Gung University, 259 Wen-Hwa 1st Road, Kwei-Shan, Taoyuan, 333, Taiwan. Tel.: +886 3 2118800x5204; fax: +886 3 2118035. E-mail address: [email protected] (C.-C. Chiou). 0009-8981/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.cca.2009.08.021
morphism (SSCP)/sequencing, denatured high-performance liquid chromatography (DHPLC)/sequencing or direct sequencing [4–6]. These methods for large-scale detection of mutations are expensive and time-consuming. Recently, a powerful and cost-effective tool, high resolution melting (HRM) curve analysis, has been developed for genotyping and mutation scanning. This method uses a saturating dye to generate an accurate melting curve with resolution that can differentiate even a single-nucleotide variation in an amplicon [7,8]. This method does not require any processing after PCR and melting analysis and is thus suitable for screening large numbers of samples. In this study, we used HRM analysis to develop a rapid protocol for scanning PTPN11 gene mutations. 2. Patients and methods 2.1. Patients Informed consent for DNA study was obtained from all patients, according to protocols approved by the Medical Ethics and the Human Clinical Trials Committee of Chang Gung Memorial Hospital. NS was diagnosed according to the major (typical facial findings, cardiac defects, and pterygium colli) and minor criteria (short stature, psychomotor retardation or speech delay, bleeding diathesis, family history of NS, and other additional features) [9]. Eleven DNA samples
76
F.-S. Lo et al. / Clinica Chimica Acta 409 (2009) 75–77
Table 1 Primers and HRM conditions for mutation scanning of the PTPN11 gene. Exon
Amplicona
Forward/reverse primers (5′ → 3′)
Size (bp)
HRM normalization (°C) Pre-melting slider setting
3
3-1
3
3-2
4
4-1
4
4-2
7
7
8
8
13
13
a
ACGTGGAAGATGAGATCTG CCCGTGATGTTCCATGTAAT ACTATGACCTGTATGGAGGG GGAGCAGCAGACTTTGT AGAACAACATGAACCCATAGTAGA CGTCATTGCTCTCCCCT GAGAGAGCCAGAGCCAC AACATCTTGCCAGACCC TGTGACTCTTTGACACGTAATAA GAGTGACTATTACTGAGCGG TGAAGCAGTCCAGGACTTAT ATAGGCTAGAAATGTATGGTCAG GGCTCTGCAGTTTCTCTTT CTAGCAAGAGAATGAGAATCCG
Post-melting slider setting
Temperature shift
200
77–78
77–78
7.37
186
77.5–78.5
77.5–78.5
8.42
212
79.5–80.5
83.5–84.5
11.58
151
79–80
83.5–84.5
7.37
178
75–76
80–81
10.53
175
77–78
82–83
10.53
241
82.5–83.5
85.5–86.5
10.53
Exons 3 and 4 were amplified as two overlapping amplicons.
from as many patients with previously identified PTPN11 mutations were used for optimization and validation of HRM. Optimized HRM conditions were applied to further screening of PTPN11 mutations in a panel of 50 additional NS patients from 7 medical centers (Chang Gung Children Hospital, Mackay Memorial Hospital, Taichung Veteran General Hospital, Changhua Christian Hospital, National Cheng Kung University Hospital, Kaoshiung Medical University Hospital, Kaoshiung Veteran General Hospital) of Taiwan.
these exons. HRM analysis was optimized using six wild-type DNA samples and 11 DNA samples carrying 10 different PTPN11 variants that have been previously identified (Table 2) [3]. The 10 known variants are located at amplicons 3-1, 3-2, 4, 8, and 13. For exon 7, HRM optimization was performed only with control DNA, as DNA carrying genetic variations in this exon was not available in our laboratory. In the optimized condition, HRM identified all the known variants (Fig. 1A–E).
2.2. Amplification of PTPN11 exons
3.2. Mutation scanning of PTPN11 gene mutations in 50 NS patients
Genomic DNA samples were extracted from peripheral whole blood using the Easy Pure Genomic DNA Isolation Kit (Bioman Scientific, Taipei, Taiwan). Exons 3, 4, 7, 8, and 13 of PTPN11 gene were amplified from genomic DNA by polymerase chain reaction (PCR) using seven sets of primers (Table 1). For exon 3 and exon 4, which are longer than 250 bp, two sets of primers were used to amplify the exons in two overlapping segments. All primers were designed using LightCycler® Probe Design Software v.2.0. PCR was performed on a LightCycler® 480 thermal cycler (Roche) using a Lightcycler® 480 High Resolution Melting Master kit. The 20-μl amplification mixture consisted of 1× master reagent provided by the kit, 0.2 μM of each primer, and 100 ng of template DNA. The cycling program was 10 min at 95 °C for activation of FasStart Taq DNA polymerase and denaturation of template DNA, followed by 35 cycles of denaturation at 95 °C for 15 s, annealing at 59 °C to 61 °C for 15 s, and 72 °C for 30 s.
Optimized HRM analysis was applied for scanning of PTPN11 mutations in 50 additional NS patients. Nine different variants were identified in 10 patients by this method (Fig. 1F–I), which were then confirmed by direct sequencing as point mutations (Table 2). All 9 mutations were missense and had been noted in previous studies [3,4].
2.3. Melting curve acquisition and analysis Melting analysis was performed after PCR, using the same instrument. Samples were heated to 95 °C for 5 min, rapidly cooled to 40 °C, heated to 60 °C for 30 s, and then ramped to 95 °C. Twentyfive data points were acquired for every 1 °C, from 60 °C to 95 °C. Melting data was analyzed using LightCycler® 480 gene scanning software (Roche). Pre and post-melting slider settings, as well as the temperature shift for normalization of each amplicon, are listed in Table 1. Differential plots were also generated by the software, using the wild types as references. 3. Results 3.1. Optimization of HRM curve analysis Complete PTPN11 mutational screening required investigation of 15 exons. However, in this study, we only analyzed exons 3, 4, 7, 8, and 13, since they contain the majority (90%) of mutations [4]. Seven pairs of primers were designed for amplification and amplicon melting of
4. Discussion NS was first reported by Jacqueline Noonan in 1963 [9]. However, definite clinical diagnosis of this condition is difficult because it is clinically heterogeneous and its phenotypic expression is highly variable and changes with age [10,11]. NS has significant phenotypic overlap with Costello Syndrome (CS) (OMIM 218040) and cardiofacio-cutaneous (CFC) syndrome (OMIM 115150). Molecular diagnosis is therefore useful for differential diagnosis between these three syndromes. However, there are many genes in the Ras signaling pathway that could cause NS, CS, and CFC: PTPN11, KRAS, and SOS1 for NS, HRAS for CS, KRAS, BRAF, MEK1 and MEK2 for CFC. We need a Table 2 List of PTPN11 genetic variants described in this study. Amplicon
Variants for calibrationa
Variants identified by HRMa
3-1
c.184A > G c.188A > G c.214G > T c.218C > T c.317A > C c.417G > C (2 patients)
c.172A > G c.179G > C (2 patients) c.211T > C c.215C > G
3-2
4 7 8
c.755T > A
13
a
c.855T > G c.922A > G c.1493G > T c.1510A > G
c.1504T > A c.1507G > C c.1508G > A c.1517A > C
GenBank RefSeq: NM_0028343.3. A of the ATG start codon is designated as +1.
F.-S. Lo et al. / Clinica Chimica Acta 409 (2009) 75–77
77
Fig. 1. The subtractive fluorescent difference plots of wild-type and patient mutations of the PTPN11 gene for validation study (A–E) and blind analysis (F–I) using HRM analysis.
rapid, powerful, and cost-effective tool for large-scale detection of gene mutations. PTPN11 gene mutation is the most common mutation associated with NS and hence is a suitable target for molecular diagnostics of NS. Many methods have been used for detecting PTPN11 mutations, including SSCP, DHPLC, denaturing gradient gel electrophoresis, temperature gradient capillary electrophoresis, PCR-RFLP and direct sequencing. However, these methods require separation of PCR products on a gel or a column and are time-consuming and cost ineffective. In contrast, PCR and HRM analysis can be completed in a closed tube. After PCR amplification, melting curves are generated by monitoring the fluorescence of a saturating dye. No post-PCR manipulations or sequence specific probes are required. Therefore, HRM has distinct advantages over current techniques for genotyping and mutation scanning of PTPN11. We demonstrated the efficacy of HRM for mutation scanning of the PTPN11 gene in patients with Noonan syndrome. This method differentiated all of the 10 known mutations from wild types and identified another 9 mutations in a blind study, which are in line with results obtained by sequencing. The mutation rate in the blind study was only 20% (10/50), less than that from previous reports [1]. One possible reason is that some mutations are located in the exons that we have not analyzed. Another reason is that some of the patients were misclassified, as NS is highly heterogeneous and difficult to conduct definite diagnosis, which emphasizes the importance of a reliable molecular diagnostic method. In summary, PTPN11 provided an excellent gene model, enabling us to analyze these different mutations that span it. These results demonstrate the potential of this technology to reduce the burden of sequencing and to develop a rapid molecular diagnostic method for NS.
Acknowledgements This research was supported by Grant CMRPG470071, awarded by Chang Gung Memorial Hospital, Taiwan.
References [1] Zenker M, Buheitel G, Rauch R, et al. Genotype-phenotype correlations in Noonan syndrome. J Pediatr 2004;144:368–74. [2] Aoki Y, Niihori T, Narumi Y, Kure S, Matsubara Y. The RAS/MAPK syndromes: novel roles of the RAS pathway in human genetic disorders. Hum Mutat 2008;29:992–1006. [3] Hung CS, Lin JL, Lee YJ, Lin SP, Chao MC, Lo FS. Mutational analysis of PTPN11 gene in Taiwanese children with Noonan syndrome. J Formos Med Assoc 2007;106:169–72. [4] Kosaki K, Suzuki T, Muroya K, et al. PTPN11 (protein-tyrosine phosphatase, nonreceptortype 11) mutations in seven Japanese patients with Noonan syndrome. J Clin Endocrinol Metab 2002;87:3529–33. [5] Sarkozy A, Conti E, Seripa D, et al. Correlation between PTPN11 gene mutations and congenital heart defects in Noonan and LEOPARD syndromes. J Med Genet 2003;40:704–8. [6] Tartaglia M, Mehler EL, Goldberg R, et al. Mutations in PTPN11, encoding the protein tyrosine phosphatase SHP-2, cause Noonan syndrome. Nat Genet 2001;29:465–8. [7] Wittwer CT, Reed GH, Gundry CN, Vandersteen JG, Pryor RJ. High-resolution genotyping by amplicon melting analysis using LCGreen. Clin Chem 2003;49:853–60. [8] Wittwer CT. High-resolution DNA melting analysis: advancements and limitations. Hum Mutat 2009;30:857–9. [9] Noon JA, Ehmke DA. Associated non cardiac malformations in children with congenital heart disease. J Pediatr 1963;63:468–70. [10] Sharland M, Burch M, McKenna WM, Paton MA. A clinical study of Noonan syndrome. Arch Dis Child 1992;67:178–83. [11] van der Burgt I, Thoonen G, Roosenboom N, et al. Patterns of cognitive functioning in school-aged children with Noonan syndrome associated with variability in phenotypic expression. J Pediatr 1999;135:707–13.