CFTR transcription defects in pancreatic sufficient cystic fibrosis patients with only one mutation in the coding region of CFTR

doi:10.1136/jmg.2010.083287

J Med Genet. Author manuscript; available in PMC 2011 April 1.

Published in final edited form as:

J Med Genet. 2011 April; 48(4): 235–241.

Published online 2010 November 20. doi: 10.1136/jmg.2010.083287

PMCID: PMC3065505

NIHMSID: NIHMS277100

CFTR transcription defects in pancreatic sufficient cystic fibrosis patients with only one mutation in the coding region of CFTR

Molly B Sheridan,^1,² Timothy W Hefferon,³ Nulang Wang,¹ Christian Merlo,⁴ Carlos Milla,^5,⁶ Drucy Borowitz,⁷ Eric D Green,^3,⁸ Peter J Mogayzel, Jr,⁹ and Garry R Cutting¹

¹McKusick–Nathans Institute of Genetic Medicine, Johns Hopkins Medical Institutions, Baltimore, Maryland, USA

²Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA

³National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA

⁴Department of Medicine, Johns Hopkins Medical Institutions, Baltimore, Maryland, USA

⁵Department of Pediatrics, University of Minnesota School of Medicine, Minneapolis, Minnesota, USA

⁶Department of Pediatrics, Stanford University School of Medicine, Palo Alto, California, USA

⁷Department of Pediatrics, State University of New York at Buffalo, Buffalo, New York, USA

⁸NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA

⁹Eudowood Division of Pediatric Respiratory Sciences, Johns Hopkins Medical Institutions, Baltimore, Maryland, USA

Correspondence to Dr Garry R Cutting, BRB 559; 733 North Broadway, Johns Hopkins Medical Institutions, Baltimore, MD 21205, USA; Email: gcutting/at/jhmi.edu

The publisher's final edited version of this article is available at J Med Genet

Abstract

Background

Patients with cystic fibrosis (CF) manifest a multisystem disease due to deleterious mutations in each gene encoding the cystic fibrosis transmembrane conductance regulator (CFTR). However, the role of dysfunctional CFTR is uncertain in individuals with mild forms of CF (ie, pancreatic sufficiency) and mutation in only one CFTR gene.

Methods

Eleven pancreatic sufficient (PS) CF patients with only one CFTR mutation identified after mutation screening (three patients), mutation scanning (four patients) or DNA sequencing (four patients) were studied. Bi-directional sequencing of the coding region of CFTR was performed in patients who had mutation screening or scanning. If a second CFTR mutation was not identified, CFTR mRNA transcripts from nasal epithelial cells were analysed to determine if any PS-CF patients harboured a second CFTR mutation that altered RNA expression.

Results

Sequencing of the coding regions of CFTR identified a second deleterious mutation in five of the seven patients who previously had mutation screening or mutation scanning. Five of the remaining six patients with only one deleterious mutation identified in the coding region of one CFTR gene had a pathologic reduction in the amount of RNA transcribed from their other CFTR gene (8.4–16% of wild type).

Conclusions

These results show that sequencing of the coding region of CFTR followed by analysis of CFTR transcription could be a useful diagnostic approach to confirm that patients with mild forms of CF harbour deleterious alterations in both CFTR genes.

INTRODUCTION

Cystic fibrosis (CF) is an autosomal recessive disorder caused by mutations in the cystic fibrosis transmembrane conductance regulator gene (CFTR).¹ Typically patients develop disease in multiple organ systems leading to obstructive lung disease, pancreatic insufficiency, male infertility, and sweat electrolyte abnormalities. This constellation of symptoms is referred to as ‘classic’ or pancreatic insufficient (PI)-CF.² However, approximately 10% of CF patients manifest symptoms in only a subset of the organ systems affected in PI-CF. This phenotype is variable and frequently milder as the majority of these patients are pancreatic sufficient (PS-CF). Diagnosis of PS-CF can be difficult due to the incomplete clinical presentation and inconclusive results of sweat chloride testing. Testing of the CFTR gene for mutations can aid in diagnosis, particularly in adults who present late in life with an atypical phenotype.

The most common CFTR mutation associated with CF, ΔF508 [p.Phe508del], accounts for approximately 70% of CF alleles. However, over 1800 other mutations have been identified in CFTR (http://www.genet.sickkids.on.ca/cftr/).³ Genetic testing for CF generally begins with a panel of 23 CFTR mutations recommended by the American College of Medical Genetics (ACMG) that identifies approximately 85% of the CF alleles in Caucasians.⁴ Most PI-CF patients carry two mutations present in the ACMG panel. Most PS-CF patients have two mutations in the coding regions of the CFTR gene.^5,6 At least one mutation permits residual CFTR function, allowing the patient to escape the classic CF phenotype.^7,8 While the 23 mutation ACMG panel includes several mutations frequently associated with PS-CF (eg, R117H [p.Arg117His], A455E [p.Arg455Glu], 2789+5G→A [c.2657+5G→A], and 3849+10kbC→T [c.3717+12191C→T]), it is not uncommon for a PS-CF patient to carry a rare CFTR mutation that is not present in the panel.⁹ Detection of less common mutations can be accomplished by use of extended mutation panels¹⁰ or by comprehensive analysis of the coding regions of the CFTR gene using scanning^11–13 or DNA sequencing methods.¹⁴ Scanning techniques detect 85–99% of CFTR mutations^15–17 while DNA sequencing has a higher sensitivity because it allows analysis of individual nucleotides.^18,19 However, these techniques do not identify gene rearrangements and mutations in non-coding regions that affect splicing or expression of RNA transcripts. Gene rearrangements are unlikely to be found in patients with PS-CF as they would be expected to cause absent or severe CFTR dysfunction. On the other hand, mutations that affect RNA processing and transcription are more likely in PS-CF since these mutations generally allow production of reduced amounts of wild-type protein.²⁰

The regulatory sequences that control CFTR expression are not well understood. Elements that regulate CFTR’s epithelial specific expression pattern are absent from the promoter, but rather appear to lie in intronic regions and outside of the gene.^21–23 Deleterious mutations in these non-coding regions may have a mild effect and are likely to be associated with PS-CF.²⁴ However, it is currently not feasible to sequence the 190 000 base pairs (bp) that comprise the entire CFTR gene to identify mutations in a diagnostic setting. Thus, we chose to use RNA based methods to identify PS-CF patients who may have a second, occult mutation in a non-coding region of CFTR. To assess the diagnostic utility of RNA studies, we analysed mRNA transcripts from nasal epithelial cells derived from PS-CF patients with only one CFTR mutation identified after CFTR genetic testing.

PATIENTS AND METHODS

Patient population

Eleven patients with PS-CF, including one set of siblings, were recruited from 2004 to 2006 from five CF Care Centers. Each patient had only one CFTR mutation identified after CFTR screening (n=3), scanning (n=4), or sequencing (n=4). Patients who underwent CFTR screening were tested for a minimum of 70 previously described CFTR mutations.¹⁰ CFTR scanning was performed using modified temporal temperature gradient electrophoresis (mTTGE).¹⁶ Patients underwent a complete history and physical examination, pulmonary function testing, and sputum culture. Chest and sinus CTs, semen analysis, and stool pancreatic elastase were obtained if not previously collected for clinical care. Nasal potential difference (NPD) measurements were made in four subjects.^25,26 PS-CF was defined as: (1) chloride transport abnormality defined as sweat [Cl⁻] >40 mmol/l or abnormal NPD; (2) respiratory disease characterised by recurrent infections, chronic cough or airway obstruction; and/or (3) congenital absence of the vas deferens in males (CBAVD), in patients with no clinical evidence of pancreatic insufficiency. All studies were approved by the Johns Hopkins University and University of Minnesota institutional review boards and written consent was obtained from all patients or their parents. Verbal or written assent was obtained from children >5 years old.

CFTR DNA sequencing

To identify mutations in the coding regions of CFTR, the 27 exons, bordering introns, two regions containing intronic mutations known to cause abnormal splicing (3849+10kbC→T and 1811+1.6kbA→G [c.1679+1.6kbA→G]) and 360 bp of 5′-flanking DNA containing the basal promoter of CFTR were amplified from genomic DNA using PCR and sequenced as previously described.⁵

RNA extraction, cDNA synthesis, and CFTR splicing analysis

Epithelial cells were collected from the inferior turbinate of each nostril using a cytology brush.²⁷ RNA was extracted using RNAbee (TelTest, Friendswood, TX, USA). cDNA was synthesised using StrataScript reverse transcriptase (Stratagene, La Jolla, CA, USA) and random primers (Invitrogen, Carlsbad, CA, USA). Splicing analysis was performed using cDNA amplified with seven sets of CFTR specific primers designed to produce overlapping products that were separated by size by electrophoresis. Primer sequences are available in supplementary table 1.

Quantitative CFTR transcript analysis

Reverse transcriptase (RT)-PCR was performed with CFTR specific primers fluorescently labelled with 6-FAM (carboxy-fluorescein) and products were separated by capillary electrophoresis using an ABI 3100 genetic analyser (ABI, Carlsbad, CA, USA). Sizes were estimated against an internal standard (ROX 500, 6-Carboxyl-X-Rhodamine) with GeneScan software (ABI). Analysis was performed using primers that amplified CFTR exons 3–6 (621+1 G→T [c.489+1G→T] and 711+3 A→G [c.579+3A→G]) or exons 10–12 (ΔF508). The amount of full length CFTR transcript in patients carrying ΔF508 was calculated using methods described by Ramalho et al²⁸ taking into account the estimated amount of exon 9-containing transcripts based on the intron 8 T tract status of the patient (9T/7T in all patients with ΔF508).²⁹ Nasal epithelial mRNA from healthy ΔF508 (n=3) and 621+1 G→T (n=3) carriers was used as a control.

CFTR transcript quantification by sequencing

RT-PCR was performed using primers that amplified CFTR exons 13–14a and sequenced as above. The amount of CFTR transcript was calculated in a qualitative manner by comparing chromatogram peak heights. RNA from a healthy R764X (p.Arg764X) carrier was used as a control.

Statistical analysis

A descriptive analysis was performed with calculations of means and SDs using Microsoft Excel. A two tailed Student t test with unequal variance was used to assess statistical significance. Values of p<0.05 were assumed significant.

RESULTS

Identification of a second CFTR mutation in five patients

The phenotype and genotypes of the 11 patients evaluated in this study are summarised in table 1. To determine if any mutations in the coding regions of CFTR had been missed during initial genetic testing, we sequenced the CFTR genomic DNA of the seven patients who had CFTR screening (patients 3–5) or scanning (patients 1, 2, 9, 10). A second CFTR mutation associated with PS-CF was identified in five of the seven patients, including the two siblings (figure 1 and table 1).^30–33 Two of these mutations have been shown to alter CFTR function (table 2).^34–36 However, the functional consequence of 711+3 A→G, found in siblings 4 and 5, had not been previously evaluated. Analysis of CFTR RNA from nasal epithelial cells of patient 4 revealed two products; one due to normal splicing (exon5+: 390 bp) and the other due to missplicing of exon 5 (exon5−: 300 bp; figure 2). The patient’s other mutation, (R553X [p.Arg553X]) is associated with a low amount of CFTR transcript due to nonsense mediated RNA decay (NMRD) (figure 2B).^37,38 The RNA transcripts lacking exon 5 (exon5−), were 2.7 times more abundant than the transcripts containing exon 5 (exon5+/R553X) (figure 2B). The CFTR RNA containing exon 5 may be transcript bearing R533X that escapes NMRD, the result of normal splicing from the 711+3 A→G allele, or a combination of both. Our results do not distinguish between these possibilities. Nevertheless, the majority of RNA transcript generated by the CFTR gene bearing 711+3 A→G is abnormal due to the absence of exon 5.

Table 1

CFTR genotypes and clinical characteristics of patients with one CFTR mutation after CFTR screening or scanning

Figure 1

Flow chart illustrating the results of studies performed on patients with one CFTR mutation identified after scanning, screening, or sequencing.

Table 2

Functional consequences of CFTR mutations identified after CFTR sequencing

Figure 2

Reverse transcriptase (RT)-PCR analysis of patient 4 carrying R553X and 711+3 A to G. (A) Diagram of RNA splicing of CFTR exons 3–6 and the predicted effect of 711+3 A→G on CFTR splicing. (B) Electropherogram showing products from RT-PCR (more ...)

Reduction in CFTR RNA transcripts in five of six patients with only one identified CFTR mutation

To determine if any of the patients with only one mutation identified in the coding region of CFTR had a second mutation in a non-coding region that affected expression of CFTR RNA, we evaluated the expression from each CFTR gene, by comparing the level of RNA expression from the CFTR gene with the identified mutation to the expression of the other CFTR gene. Four of the six patients (patients 6–9) carried the common CFTR mutation, ΔF508 (table 1). RT-PCR of exons 10–12 surrounding ΔF508 from patient cDNA and three healthy ΔF508 carriers produced two transcripts: one from the CFTR gene bearing ΔF508 (333 bp), and one from the other CFTR gene that was 3 bp longer as a result of the wild type (‘wt’ exon 10 sequence) (figure 3A). The ratio of wild type to ΔF508 transcript was >1.0 in the controls (1.22±0.25 mean peak area±SD; figure 3B). This is consistent with previous studies showing that ΔF508 alleles are expressed at about 85% of wild type CFTR.²⁸ However, the ratio of ‘wild type’ (transcript from the second CFTR gene) to ΔF508 transcript in patients 6–8 were significantly lower than controls (mean wild type/ΔF508 peak area±SD: patient 6: 0.5±0.17, n=4, p=0.0002; patient 7: 0.85±0.11, n=4, p=0.0038; patient 8: 0.95±0.18, n=5, p=0.0456; figure 3B). The ratio of ‘wild-type’ to ΔF508 transcript from patient 9 did not differ from the normal controls (mean wt/ΔF508 peak area=1.24, n=1; figure 3). The amount of each transcript was then adjusted for the lower level of expression resulting from alternate splicing of exon 9 due to the intron 8 T/TG tract length (see Methods). After these adjustments, the amount of wild-type CFTR transcript in each patient compared to normal individuals was estimated as: patient 6: 8.5±0.2.8%; patient 7: 14.3±1.8%; and patient 8: 16.0±3.1%.

Figure 3

RT-PCR results from patients 6–10 with one mutation in the CFTR coding region. (A) Electropherograms illustrating a product of 333 bp amplified from the CFTR gene bearing ΔF508 and the 336 bp product amplified from a ‘wild type’ (more ...)

Patient 10 carries 621+1 G→T (table 1). This mutation changes the canonical splice donor sequence in CFTR intron 4 leading to two aberrantly spliced transcripts^40,41; one lacks all of exon 4 while the other lacks 93 bp of exon 4 due to the use of a cryptic splice donor. To detect these transcripts, we amplified CFTR exons 3 to 6 from nasal epithelial cell cDNA from patient 10, his mother (who is a healthy carrier of 621+1 G→T), and from two unrelated healthy carriers of 621+1 G→T. As expected, the 621+1 G→T carriers had three different RNA transcripts: ‘wild type’ (384 bp) and two products corresponding to aberrant splicing of exon 4 (figure 3C, lower trace). In the carriers, the ratio of wild type to aberrant transcript is 1.58±0.78 (mean±SD). The same three transcripts are seen in patient 10 (figure 3C, upper trace); however, the ratio of the wild-type transcript from the CFTR gene not bearing 621+1G→T to the two aberrant transcripts is significantly reduced (mean±SD 0.27±0.13; n=4, p=0.04; figure 3D). Amplification of the entire CFTR transcript in overlapping segments did not identify any alternatively spliced transcripts. Thus, patient 10 has a reduction in the level of RNA transcripts expressed from the CFTR gene without an identified mutation.

The remaining patient (patient 11) carries R764X (table 1). Because this mutation is not predicted to cause aberrant RNA splicing, we estimated transcript levels of each CFTR allele by sequencing of reverse transcribed RNA. Amplification of the region containing R764X (exons 13–14a) from a healthy carrier of R764X revealed minimal amounts of transcript bearing the R764X mutation, indicating that this mutation induces NMRD (red peak, third sequence trace, figure 4). However, transcript bearing R764X in patient 11 is present at a higher level than the RNA transcript from the other CFTR gene (red peak versus blue peak in bottom trace, figure 4). This indicates that patient 11 harbours a mutation in the second CFTR gene that reduces RNA transcript to a level less than that associated with NMRD.

Figure 4

Quantification of CFTR RNA transcripts in cells from patient 11. Electropherograms from DNA sequencing of genomic DNA and cDNA. The R764X mutation is caused by the replacement of a C nucleotide at 2422 by a T nucleotide (compare upper and second tracings). (more ...)

DISCUSSION

In this study, we used DNA and RNA based methods to determine if occult mutations were responsible for the clinical features of CF in 11 patients with only one identified CFTR mutation. We found that the CF phenotype in 10 of these patients can be explained by either (1) deleterious mutations in the coding region of each CFTR gene (five patients) or (2) one deleterious CFTR mutation plus reduced transcript from the second CFTR gene (five patients). These studies support the observation that patients with clinical features of CF and one known deleterious CFTR mutation are likely to harbour a defect in their other CFTR gene⁶ and illustrate the utility of CFTR sequencing and RNA analysis in the diagnosis of CF in patients with PS-CF. Furthermore, prudent genetic counselling of a patient with PS-CF and a single identified CFTR mutation should take into account the high likelihood that the patient carries deleterious mutations in each CFTR gene.

Screening for common CF causing mutations using the ACMG recommended panel is an appropriate initial approach in Caucasian patients with features of CF. However, about 25% of CF patients have only one mutation identified after screening, even with expanded mutation panels.^4,42 Many of these patients have a second CFTR mutation that can be identified by analysing the entire coding regions of the CFTR gene.⁵ In our study, three patients had mutations that were not present on the expanded CFTR mutation screening panels. Scanning methods, as opposed to DNA sequencing, have the potential to miss mutations that do not change the physical properties of DNA strands.^15,43 In our study, we identified a second CFTR mutation in half of the patients who had only one mutation identified after scanning. In some patients, genomic rearrangements and mutations in non-coding sequences of CFTR that are not identified by standard sequencing may be present.^44,45 Consequently, a small percentage of patients with CF will still have unidentified deleterious mutations even after sequencing of the coding regions of CFTR.^5,14 As every method of mutation identification has limitations in sensitivity, it is important for clinicians to take the method of genetic testing into account when interpreting results, particularly when two CFTR mutations are not identified in a patient with biochemical and clinical features of CF.

Analysis of nasal epithelial CFTR RNA can help identify mutations that are not detected by sequencing. Using this approach, we were able to show that five of the six remaining PS-CF patients studied had a statistically significant reduction in RNA transcription from the CFTR gene without a coding region mutation compared to the CFTR gene with an identified mutation. The amount of normal CFTR RNA expressed in these patients ranges from approximately 8.4–16%. Variable transcript levels and skipping of exons 9 and 12 have been observed in healthy individuals.^46–48 Because the primers used to quantify the amount of ΔF508 were located in exon 12 it is possible that we did not account for CFTR transcripts lacking these exons in our calculations. Using RT-PCR of overlapping CFTR exons we determined that patients 6–8 did not express any CFTR transcripts missing exon 12. However, we did not assess exon 12 splicing in patient 9. Thus, it is possible that our estimates of CFTR transcript level may be inaccurate if this patient missplices exon 12.

The amount of CFTR expression needed to maintain a normal pulmonary phenotype has been inferred from a number of studies. Several investigators have suggested that expression of full length CFTR RNA above 20% of normal is necessary to escape a CF phenotype.^20,28,49,50 Therefore, we concluded that the reduced level of RNA transcript from the CFTR gene without an identified mutation in the five patients was clinically significant. The significant but not complete reduction in CFTR RNA transcript likely explains the PS phenotype observed in each patient, as shown for splicing mutations such as 3849 +10kbC→T.²⁰ The precise molecular cause of the reduction in CFTR transcript in these patients is currently not known and is the focus of future studies.

In conclusion, these results demonstrate that identification of only one CFTR mutation in patients with a clinical diagnosis of PS-CF does not exclude CFTR as the cause of their disease. When appropriate, methods such as DNA sequencing and RNA analysis can provide molecular evidence that CFTR is dysfunctional. These studies highlight the potential of using RNA analysis to identify patients who may benefit from sequencing of the entire CFTR gene.⁵¹ More broadly, these findings illustrate the utility of RNA analysis in the molecular diagnosis of CF and suggest that RNA analysis might be useful in other recessive disorders, particularly those where mutations in regulatory elements are known to contribute to disease.

Acknowledgements

Special thanks to Gail Sharpless for technical assistance; Lois Brass for performing NPD measurements; Robert Castille, MD, James Yankaskas, MD, and Bradley Chipps, MD for referring patients to this study; and Nadine Caci and Brooke Noren for data collection. Most of all, we would like to thank the patients and families for their willingness to participate in this study.

Funding This work was supported by grants from the National Institutes of Health (NIDDK R37 99003 to GRC) and the Cystic Fibrosis Foundation.

Footnotes

An additional table is published online only. To view this file please visit the journal online (http://jmg.bmj.com).

Competing interests None.

Patient consent Obtained.

Ethics approval All studies were approved by the Johns Hopkins University and University of Minnesota IRBs and written consent was obtained from all patients or their parents.

Provenance and peer review Not commissioned; externally peer reviewed.

To order reprints go to: http://journals.bmj.com/cgi/reprintform

REFERENCES

1. Riordan JR, Rommens JM, Kerem B, Alon N, Rozmahel R, Grzelczak Z, Zielenski J, Lok S, Plavsic N, Chou JL, Drumm ML, Iannuzzi MC, Collins FS, Tsui LC. Identification of the cystic fibrosis gene: cloning and characterization of complementary DNA. Science. 1989;245:1066–1073. [PubMed]

2. Welsh MJ, Ramsey BW, Accurso FJ, Cutting GR. Cystic fibrosis. In: Scriver CR, Beaudet AL, Valle D, Sly WS, editors. The Metabolic and Molecular Bases of Inherited Disease. New York: McGraw-Hill, Inc.; 2001. pp. 5121–5188.

3. Cystic Fibrosis Mutation Data Base. 2010 http://www.genet.sickkids.on.ca.

4. Watson MS, Cutting GR, Desnick RJ, Driscoll DA, Klinger K, Mennuti M, Palomaki GE, Popovich BW, Pratt VM, Rohlfs EM, Strom CM, Richards CS, Witt DR, Grody WW. Cystic fibrosis population carrier screening: 2004 revision of American College of Medical Genetics mutation panel. Genet Med. 2004;6:387–391. [PMC free article] [PubMed]

5. Groman JD, Meyer ME, Wilmott RW, Zeitlin PL, Cutting GR. Variant cystic fibrosis phenotypes in the absence of CFTR mutations. N Engl J Med. 2002;347:401–407. [PubMed]

6. Groman JD, Karczeski B, Sheridan M, Robinson TE, Fallin MD, Cutting GR. Phenotypic and genetic characterization of patients with features of “nonclassic” forms of cystic fibrosis. J Pediatr. 2005;146:675–680. [PMC free article] [PubMed]

7. Kristidis P, Bozon D, Corey M, Markiewicz D, Rommens J, Tsui LC, Durie P. Genetic determination of exocrine pancreatic function in cystic fibrosis. Am J Hum Genet. 1992;50:1178–1184. [PubMed]

8. Wilschanski M, Dupuis A, Ellis L, Jarvi K, Zielenski J, Tullis E, Martin S, Corey M, Tsui LC, Durie P. Mutations in the cystic fibrosis transmembrane regulator gene and in vivo transepithelial potentials. Am J Respir Crit Care Med. 2006;174:787–794. [PMC free article] [PubMed]

9. Farrell PM, Rosenstein BJ, White TB, Accurso FJ, Castellani C, Cutting GR, Durie PR, LeGrys VA, Massie J, Parad RB, Rock MJ, Campbell PW. Cystic Fibrosis Foundation. Guidelines for diagnosis of cystic fibrosis in newborns through older adults: Cystic Fibrosis Foundation consensus report. J Pediatr. 2008;153:S4–S14. [PMC free article] [PubMed]

10. Heim RA, Sugarman EA, Allitto BA. Improved detection of cystic fibrosis mutations in the heterogeneous U.S. population using an expanded, pan-ethnic mutation panel. Genet Med. 2001;3:168–176. [PubMed]

11. Wong LJ, Alper OM. Detection of CFTR mutations using temporal temperature gradient gel electrophoresis. Electrophoresis. 2004;25:2593–2601. [PubMed]

12. Chou LS, Lyon E, Wittwer CT. A comparision of high-resolution melting analysis with denaturing high-performance liquid chromoatography for mutation scanning: cystic fibrosis transmembrane conductance regulator gene as a model. Am J Clin Pathology. 2005;124:330–338. [PubMed]

13. Alonso MJ, Heine-Suner D, Calvo M, Rosell J, Gimenex J, Ramos MD, Telleria JJ, Palacio A, Estivill X, Casals T. Spectrum of mutations in the CFTR gene in cystic fibrosis patients of Spanish ancestry. Ann Hum Genet. 2007;71(Pt 2):194–201. [PubMed]

14. McGinniss MJ, Chen C, Redman JB, Buller A, Quan F, Peng M, Giusti R, Hantash FM, Huang D, Sun W, Strom CM. Extensive sequencing of the CFTR gene: Lessons learned from the first 157 patient samples. Hum Genet. 2005;118:331–338. [PubMed]

15. Alper OM, Luleci G, Wong LC. Mutation analysis by the use of temporal temperature gradient gel electrophoresis. Turk J Med Sci. 2005;35:279–282.

16. Kammesheidt A, Kharrazi M, Graham S, Young S, Pearl M, Dunlop C, Keiles S. Comprehensive genetic analysis of the cystic fibrosis transmembrane conductance regulator from dried blood specimens- Implications for newborn screening. Genet Med. 2006;8:557–562. [PubMed]

17. Audrezet MP, Dabricot A, Le Marechal C, Ferec C. Validation of high-resolution DNA melting analysis for mutation scanning of the cystic fibrosis transmembrane conductance regulator (CFTR) gene. J Mol Diagn. 2008;10:424–434. [PubMed]

18. Boehm CD, Cutting GR, Lachtermacher MB, Moser HW, Chong SS. Accurate DNA-based diagnostic and carrier testing for X-linked adrenoleukodystrophy. Mol Genet Metab. 1999;66:128–136. [PubMed]

19. Lucarelli M, Narzi L, Piergentili R, Ferraguti G, Grandoni F, Quattrucci S, Strom R. A 96-well formatted method for exon and exon/intron boundary full sequencing of the CFTR gene. Anal Biochem. 2006;353:226–235. [PubMed]

20. Highsmith WE, Jr, Burch LH, Zhou Z, Olsen JC, Boat TE, Spock A, Gorvoy JD, Quittell L, Friedman KJ, Silverman LM, Boucher RC, Knowles MR. A novel mutation in the cystic fibrosis gene in patients with pulmonary disease but normal sweat chloride concentrations. N Engl J Med. 1994;331:974–980. [PubMed]

21. Ott CJ, Blackledge NP, Lier SH, Harris A. Novel regulatory mechanism for the CFTR gene. Biochem Soc Trans. 2009;37(Pt 4):843–848. [PMC free article] [PubMed]

22. Ott CJ, Blackledge NP, Kerschner JL, Lier SH, Crawford GE, Cotton CU, Harris A. Intronic enhancers coordinate epithelial-specific looping of the active CFTR locus. Proc Natl Acad Sci U S A. 2009;106:19934–19939. [PubMed]

23. Smith DJ, Nuthall HN, Majetti ME, Harris A. Multiple potential intragenic regulatory elements in the CFTR gene. Genomics. 2000;64:90–96. [PubMed]

24. Kryukov GV, Schmidt S, Sunyaev S. Small fitness effect of mutations in highly conserved non-coding regions. Hum Mol Genet. 2005;14:2221–2229. [PubMed]

25. Knowles MR, Paradiso AM, Boucher RC. In vivo nasal potential difference: Techniques and protocols for assessing efficacy of gene transfer in cystic fibrosis. Human Gene Therapy. 1995;6:445–455. [PubMed]

26. Standaert TA, Boitano L, Emerson J, Milgram LJ, Konstan MW, Hunter J, Berclaz PY, Brass L, Zeitlin PL, Hammond K, Davies Z, Foy C, Noone PG, Knowles MR. Standardized procedure for measurement of nasal potential difference: An outcome measure in multicenter cystic fibrosis trials. Pediatr Pulmonol. 2004;37:385–392. [PubMed]

27. Trapnell BC, Chu C-S, Paakko P, Banks TC, Yoshimura K, Ferrans VJ, Chernick MS, Crystal RG. Expression of the cystic fibrosis transmembrane conductance regulator gene in the respiratory tract of normal individuals and individuals with cystic fibrosis. Proc Natl Acad Sci U S A. 1991;88:6565–6569. [PubMed]

28. Ramalho AS, Beck S, Meyer M, Penque D, Cutting GR, Amaral MD. Five percent of normal cystic fibrosis transmembrane conductance regulator mRNA ameliorates the severity of pulmonary disease in cystic fibrosis. Am J Respir Cell Mol Biol. 2002;27:619–627. [PubMed]

29. Mak V, Jarvi K, Zielenski J, Durie P, Tsui LC. Higher proportion of intact exon 9 CFTR mRNA in nasal epithelium compared with vas deferens. Hum Mol Genet. 1997;6:2099–2107. [PubMed]

30. Chu CS, Trapnell BC, Curristin S, Cutting GR, Crystal RG. Genetic basis of variable exon 9 skipping in cystic fibrosis transmembrane conductance regulator mRNA. Nature Genet. 1993;3:151–156. [PubMed]

31. Ferec C, Audrezet MP, Mercier B, Guillermit H, Moullier P, Quere I, Verlingue C. Detection of over 98% cystic fibrosis mutations in a Celtic population. Nat Genet. 1992;1:188–191. [PubMed]

32. Petreska L, Koceva S, Gordova-Muratovska A, Nestorov R, Efremov GD. Identification of two new mutations (711+3A->G and V1397E) in chromosomes of Albanian and Macedonian origin. Hum Mol Genet. 1994;3:999–1000. [PubMed]

33. Chillon M, Casals T, Nunes V, Gimenez J, Perez RE, Estivill X. Identification of a new missense mutation (P205S) in the first transmembrane domain of the CFTR gene associated with a mild cystic fibrosis phenotype. Hum Mol Genet. 1993;2:1741–1742. [PubMed]

34. Sheppard DN, Travis SM, Ishihara H, Welsh MJ. Contribution of proline residues in the membrane-spanning domains of cystic fibrosis transmembrane conductance regulator to chloride channel function. J Biol Chem. 1996;271:14995–15001. [PubMed]

35. Cuppens H, Lin W, Jaspers M, Costes B, Teng H, Vankeerberghen A, Jorissen M, Droogmans G, Reynaert I, Goossens M, Nilius B, Cassiman JJ. Polyvariant mutant cystic fibrosis transmembrane conductance regulator genes: the polymorphic (TG)m locus explains the partial penetrance of the 5T polymorphism as a disease mutation. J Clin Invest. 1998;101:487–496. [PMC free article] [PubMed]

36. Groman JD, Hefferon TW, Casals T, Bassas L, Estivill X, Des GM, Guittard C, Koudova M, Fallin MD, Nemeth K, Fekete G, Kadasi L, Friedman K, Schwarz M, Bombieri C, Pignatti PF, Kanavakis E, Tzetis M, Schwartz M, Novelli G, D’Apice MR, Sobczynska-Tomaszewska A, Bal J, Stuhrmann M, Macek M, Jr, Claustres M, Cutting GR. Variation in a repeat sequence determines whether a common variant of the cystic fibrosis transmembrane conductance regulator gene is pathogenic or benign. Am J Hum Genet. 2004;74:176–179. [PubMed]

37. Hamosh A, Trapnell BC, Zeitlin PL, Montrose-Rafizadeh C, Rosenstein BJ, Crystal RG, Cutting GR. Severe deficiency of CFTR mRNA carrying nonsense mutations R553X and W1316X in respiratory epithelial cells of patients with cystic fibrosis. J Clin Invest. 1991;88:1880–1885. [PMC free article] [PubMed]

38. Aznarez I, Zielenski J, Rommens JM, Blencowe BJ, Tsui LC. Exon skipping through the creation of a putative exonic splicing silencer as a consequence of the cystic fibrosis mutation R553X. J Med Genet. 2007;44:341–346. [PMC free article] [PubMed]

39. Wine JJ, Kuo E, Hurlock G, Moss RB. Comprehensive mutation screening in a cystic fibrosis center. Pediatrics. 2001;107:280–286. [PubMed]

40. Zielenski J, Bozon D, Markiewicz D, Aubin G, Simard F, Rommens JM, Tsui LC. Analysis of CFTR transcripts in nasal epithelial cells and lymphoblasts of a cystic fibrosis patient with 621+1G -> T and 711+1G -> T mutations. Hum Mol Genet. 1993;2:683–687. [PubMed]

41. Hull J, Shackleton S, Harris A. Abnormal mRNA splicing resulting from three different mutations in the CFTR gene. Hum Mol Genet. 1993;2:689–692. [PubMed]

42. Richards CS, Bradley LA, Amos J, Allitto B, Grody WW, Maddalena A, McGinnis MJ, Prior TW, Popovich BW, Watson MS, Palomaki GE. Standards and guidelines for CFTR mutation testing. Genet Med. 2002;4:379–391. [PubMed]

43. Gerhardus A, Schleberger H, Schlegelberger B, Gadziki D. Diagnostic accuracy of methods for the detection of BRCA1 and BRCA2 mutations: a systemic review. Eur J Hum Genet. 2007;15:619–627. [PubMed]

44. Ferec C, Casals T, Chuzhanova N, Macek M, Jr, Bienvenu T, Holubova A, King C, McDevitt T, Castellani C, Farrell PM, Sheridan M, Pantaleo S, Loumi O, Messaoud T, Cuppens H, Torricelli F, Cutting GR, Williamson R, Ramos MJ, Pignatti PF, Raquenes O, Cooper DN, Audrezet MP, Chen JM. Gross genomic rearrangements involving deletions in the CFTR gene: Characterization of six new events from a large cohort of hitherto unidentified cystic fibrosis chromosomes and meta-analysis of the underlying mechanisms. Eur J Hum Genet. 2006;14:567–576. [PubMed]

45. Paracchini V, Seia M, Coviello D, Porcaro L, Costantino L, Capasso P, Degiorgio D, Padoan R, Corbetta C, Claut L, Constantini D, Colombo C. Molecular and clinical features associated with CFTR gene rearrangements in Italian population: Identification of a new duplication and recurrent deletions. Clin Genet. 2008;73:346–352. [PubMed]

46. Slomski R, Schloesser M, Berg LP, Wagner M, Kakkar VV, Cooper DN, Reiss J. Omission of exon 12 in cystic fibrosis transmembrane conductance regulator (CFTR) gene transcripts. Hum Genet. 1992;89:615–619. [PubMed]

47. Hull J, Shackleton S, Harris A. Analysis of mutations and alternative splicing patterns in the CFTR gene using mRNA derived from nasal epithelial cells. Hum Mol Genet. 1994;3:1141–1146. [PubMed]

48. Steiner B, Truninger K, Sanz J, Schaller A, Gallati S. The role of common single-nucleotide polymorphisms on exon 9 and exon 12 skipping in nonmutated CFTR alleles. Hum Mutat. 2004;24:120–129. [PubMed]

49. Rave-Harel N, Kerem E, Nissim-Rafinia M, Madjar I, Goshen R, Augarten A, Rahat A, Hurwitz A, Darvasi A, Kerem B. The molecular basis of partial penetrance of splicing mutations in cystic fibrosis. Am J Hum Genet. 1997;60:87–94. [PubMed]

50. Tzetis M, Efthymiadou A, Doudounakis S, Kanavakis E. Qualitative and quantitative analysis of mRNA associated with four putative splicing mutations (621+3Ae>G, 2751+2Te>A, 296+1Ge>C, 1717-9Te>C-D565G) and one nonsense mutation (E822X) in the CFTR gene. Hum Genet. 2001;109:592–601. [PubMed]

51. ten Bosch JR, Grody WW. Keeping up with the next generation: massively parallel sequencing in clinical diagnostics. J Mol Diagn. 2008;10:484–492. [PubMed]