**2.3. Other loci**

**Abou Tayoun et al., 2013 [25] Trujillano et al., 2014 [26] Bonini et al., 2015 [17]**

99,7% covered by minimum 5

Pindel; Conifer; PeSV-Fisher 5 large deletions, 1 duplication and 1 genomic rearrangement

115 SNV + 28 InDels on average

Variant prediction tools: GATK Unified Genotyper, samtools mpileup, SHORE

GATK Variant filtration (MQ<30.0; QUAL<25.0; QD<4.0; DP<5; DP<2000; GQ<15) GATK Combine Variant

SIFT, PolyPhen2, PhyloP, Mutation

In-house script to determine the c. 1210-34TG(11-13)T(5-9) haplotype

Breakpoints of large genomic rearrangement accurately

GC rich genomic segments (target

Errors in index tags (sequencing)

determined

enrichment)

1000 Genomes project

Exome Variant Server

Taster, phastCons UCSC Genome Browser

dbSNP

CFMDB CFTR2

Annovar

Diagnostic rate ND 98.91% 88.9% (16 / 18)

Human Genome (454 Roche GS Junior data analysis pipeline)

40X

ND

introns)

Reference Mapper Mutalyzer

SeqNext (JSI medical systems)

Heterozygous: Read support: 30-65%

Annovar, HSF, MaxEnt, NNSplice, SIFT, Polyphen2, PhyloP, UCSC Genome Browser,

False positive c.2052del (2184delA) Sanger sequencing to determine the c. 1210-34TG(11-13);-12T(5-9) haplotype

LR-PCR more adapted for complete gene

New intronic mutations identified

SINE/LINE repeats (amplification and

Homopolymer stretches (Sequencing) Uncaptured region in intron 3

Threshold 30% of reads

Homozygous >70%

1000 Genomes project

Ensembl, MutationTaster

resequencing

mapping)

dbSNP

197 variants on average per sample (118 in

Chromosome 7 (454 Roche GS Junior data analysis pipeline)

and picard-tools)

Mean: 231X

reads

independent runs) 100% (8 on 8 variants) ND

per sample

Mapping Human genome Human genome (GATK pipeline

Specificity 97% (22 on 23 mutations) 100% ND Sensitivity 100% (23 on 23 mutations) 100% (122 on 122 variants) ND

> Depth-Of-Coverage tool from the Genome Analysis ToolKit

> --> Log2 ratios < -0.7: deletion

Minimal coverage

Bioinformatics tools

Variant identification and calling

Variant filter

Databases

*In silico* analysis

Performance

Particular cases

Limits

CNV

CFTR Sequencing statistics

Reproducibility 100% (56 on 56 variants in 3

210 Cystic Fibrosis in the Light of New Research

(GATK)

Not notified

dbSNP

CFMDB CFTR2

SIFT Mutation Taster

Min coverage: 20 reads Threshold: 25% reads Both strands

Variant frequency > 1%

Exome Variant Server

False positive c.2052del

(2184delA) Sanger sequencing to determine the c. 1210-34TG(11-13)T(5-9)

haplotype

number of VUCs

SINE/LINE repeats (amplification and mapping) Homopolymer stretches (Sequencing)

**Table 4.** Comparison of three NGS strategies for *CFTR* sequencing

Advantages Robust, specific, limited

SNV 7 variants per sample on average

With the perspectives of high throughput molecular diagnosis in genetics laboratories, CF, CFTR-RDs and CF-like diseases could be simultaneously explored in patients using NGS. Various gene panels could be investigated according to patients' phenotypes. Therefore, NGS approaches could contribute to (i) identify and confirm the implication of modifiers genes and (ii) improve molecular diagnosis of atypical Cystic Fibrosis, CFTR-RDs or CF-like diseases. Several sequence changes located in the so-called 'modifier genes' have been associated with progression of lung disease in CF patients. A decrease of pulmonary function measured by FEV1 (the forced expired volume after 1 s of blowing out) was associated with SNVs in *EDNRA*, *ACER*,*IFRD1*,*IL8*, *MUC5AC*and *TGF-β1* genes. Haplotype 8.1 and variants in MBL2 gene were relatedto*Pseudomonas aeruginosa* colonization[28, 29]. SNVs in*SNAP23,PPP2R4,PPP2R1Aand KRT19* were recently associated with a decrease of lung function. Interactions between CFTR and these altered proteins may modify CFTR trafficking and membrane stability and there‐ fore modify phenotype of CF patients [30]. Moreover, changes in other modifier genes were suspected to have an effect on intestinal obstruction (*DCTN4*, *ADIPOR2* and *MSRA* genes), CFassociated diabetes (*TCF7L2* gene) or liver disease (*SERPIN1A1*) [31].

CFTR-Related disorders comprise congenital bilateral absence of vas deferens (CBAVD), pancreatitis, diffuse bronchiectasis and nasal polyposis. Classically, two *CFTR* mutations (a severe and a mild mutation or two mild mutations) are found in well-characterized CBAVD patients [32]. In addition, Sharma *et al*. reported 2 SNVs on *TGF-β1* and *ENDRA* genes associat‐ ed with urogenital anomalies [33]. Chronic pancreatitis is caused by *CFTR* variations in some cases,andmutations in*CTRC*,*PRSS1*,*PRSS2*or*SPINK1*are alsoinvolvedandmustbeanalysed.

The implication of *CFTR* in diffuse bronchiectasis or nasal polyposis is more controversial [34]; variants in other genes were previously reported as possibly causative. However, the identifi‐ cation of mutations in other genes with sufficient significance remains difficult and needs large patient cohorts.Infact,inairwaytractdiseases,the influenceof environment(pollutants,drugs/ therapy and way of life) complicated the achievement of unbiased studies. Nevertheless, the hypothesis of oligogenism is supported by a study that reported mutations in ENaC channel genes (*SCNN1A*, *SCNN1B*, *SCNN1G*) or *SERPIN1A1* in CF-like patients (borderline sweattest and suggestive CF clinical features without two *CFTR* mutations) [35].

Finally, apleiotropic effect of *SLC26A9* onmeconiumileus,pancreaticdamage andlungdisease has been identified [36], as well as *SLC9A3* for meconium ileus and lung disease and *SLC6A14* for meconium ileus and both lung disease and age at first *P. aeruginosa* infection [37]. Thus, the existence of pleiotropic effect of modifier genes on CF evolution may encourage the develop‐ ment of new therapeutic targets with multi-organ benefits.
