Decoding Cystic Fibrosis Phenotype
Аутори
Divac Rankov, AleksandraUšjak, Dušan
Mitić, Martina Mia
Kusić Tisma, Jelena
Остала ауторства
Morić, IvanaĐorđević, Valentina
Конференцијски прилог (Објављена верзија)
,
© 2023 Institute of Molecular Genetics and Genetic Engineering, University of Belgrade
Метаподаци
Приказ свих података о документуАпстракт
Cystic fibrosis (CF) is a monogenic autosomal recessive disease caused by mutations in
transmembrane conductance regulator (CFTR) gene. The golden standard for the diagnosis
of CF is sweat chloride testing (>60 mmol/L) together with the identification of two CFcausing
variants of CFTR gene. Nevertheless, about 0.01% of patients with elevated sweat
chloride and high clinical suspicion of CF do not carry any CF-causing variants.
Here we present analysis of whole exome sequencing (WES) results for two patients with
elevated sweat chloride levels and clinical presentation of CF in whom no CF-causing
mutations were detected after CFTR gene whole coding region sequencing, and large
insertion/deletion testing.
Genomic DNA was extracted from whole blood, subjected to library preparation using
DNA nanoball technology from BGI and sequenced on DNBSEQ-G400 (MGI). Produced
fastq files were mapped to hg38 reference genome using BWA/SAM tools. VCF files were
generated using GATK (BaseRec...alibrator, HaplotypeCaller) and annotated with InterVar
and AnnoVar tools. Filtering of detected variants for disease relevance was done using
the following criteria: QC Filter, GnomAD Allele Frequency, Functional consequences and
phenotype-genotype relationship.
In both patients, similar number of variants predicted to impair protein function were
detected (27 and 25). In two genes (CACNA1H and MUC5B) missense type variants
were found in both patients and loss of function variants were found in 7 and 11 genes,
respectively. Functional assessment of selected variants is underway.
Bioinformatics analyses are a valuable tool enabling identification of underlining genetic
bases of disease phenotype, important in the context of optimal patient management and
targeted therapies.
Кључне речи:
whole exome sequencing (WES) / cystic fibrosis / variant assessmentИзвор:
4th Belgrade Bioinformatics Conference, 2023, 4, 44-44Издавач:
- Belgrade : Institute of molecular genetics and genetic engineering
Финансирање / пројекти:
- Министарство науке, технолошког развоја и иновација Републике Србије, институционално финансирање - 200042 (Универзитет у Београду, Институт за молекуларну генетику и генетичко инжењерство) (RS-MESTD-inst-2020-200042)
Напомена:
- Book of abstract: 4th Belgrade Bioinformatics Conference, June 19-23, 2023
Институција/група
Institut za molekularnu genetiku i genetičko inženjerstvoTY - CONF AU - Divac Rankov, Aleksandra AU - Ušjak, Dušan AU - Mitić, Martina Mia AU - Kusić Tisma, Jelena PY - 2023 UR - https://belbi.bg.ac.rs/ UR - https://imagine.imgge.bg.ac.rs/handle/123456789/1985 AB - Cystic fibrosis (CF) is a monogenic autosomal recessive disease caused by mutations in transmembrane conductance regulator (CFTR) gene. The golden standard for the diagnosis of CF is sweat chloride testing (>60 mmol/L) together with the identification of two CFcausing variants of CFTR gene. Nevertheless, about 0.01% of patients with elevated sweat chloride and high clinical suspicion of CF do not carry any CF-causing variants. Here we present analysis of whole exome sequencing (WES) results for two patients with elevated sweat chloride levels and clinical presentation of CF in whom no CF-causing mutations were detected after CFTR gene whole coding region sequencing, and large insertion/deletion testing. Genomic DNA was extracted from whole blood, subjected to library preparation using DNA nanoball technology from BGI and sequenced on DNBSEQ-G400 (MGI). Produced fastq files were mapped to hg38 reference genome using BWA/SAM tools. VCF files were generated using GATK (BaseRecalibrator, HaplotypeCaller) and annotated with InterVar and AnnoVar tools. Filtering of detected variants for disease relevance was done using the following criteria: QC Filter, GnomAD Allele Frequency, Functional consequences and phenotype-genotype relationship. In both patients, similar number of variants predicted to impair protein function were detected (27 and 25). In two genes (CACNA1H and MUC5B) missense type variants were found in both patients and loss of function variants were found in 7 and 11 genes, respectively. Functional assessment of selected variants is underway. Bioinformatics analyses are a valuable tool enabling identification of underlining genetic bases of disease phenotype, important in the context of optimal patient management and targeted therapies. PB - Belgrade : Institute of molecular genetics and genetic engineering C3 - 4th Belgrade Bioinformatics Conference T1 - Decoding Cystic Fibrosis Phenotype EP - 44 SP - 44 VL - 4 UR - https://hdl.handle.net/21.15107/rcub_imagine_1985 ER -
@conference{ author = "Divac Rankov, Aleksandra and Ušjak, Dušan and Mitić, Martina Mia and Kusić Tisma, Jelena", year = "2023", abstract = "Cystic fibrosis (CF) is a monogenic autosomal recessive disease caused by mutations in transmembrane conductance regulator (CFTR) gene. The golden standard for the diagnosis of CF is sweat chloride testing (>60 mmol/L) together with the identification of two CFcausing variants of CFTR gene. Nevertheless, about 0.01% of patients with elevated sweat chloride and high clinical suspicion of CF do not carry any CF-causing variants. Here we present analysis of whole exome sequencing (WES) results for two patients with elevated sweat chloride levels and clinical presentation of CF in whom no CF-causing mutations were detected after CFTR gene whole coding region sequencing, and large insertion/deletion testing. Genomic DNA was extracted from whole blood, subjected to library preparation using DNA nanoball technology from BGI and sequenced on DNBSEQ-G400 (MGI). Produced fastq files were mapped to hg38 reference genome using BWA/SAM tools. VCF files were generated using GATK (BaseRecalibrator, HaplotypeCaller) and annotated with InterVar and AnnoVar tools. Filtering of detected variants for disease relevance was done using the following criteria: QC Filter, GnomAD Allele Frequency, Functional consequences and phenotype-genotype relationship. In both patients, similar number of variants predicted to impair protein function were detected (27 and 25). In two genes (CACNA1H and MUC5B) missense type variants were found in both patients and loss of function variants were found in 7 and 11 genes, respectively. Functional assessment of selected variants is underway. Bioinformatics analyses are a valuable tool enabling identification of underlining genetic bases of disease phenotype, important in the context of optimal patient management and targeted therapies.", publisher = "Belgrade : Institute of molecular genetics and genetic engineering", journal = "4th Belgrade Bioinformatics Conference", title = "Decoding Cystic Fibrosis Phenotype", pages = "44-44", volume = "4", url = "https://hdl.handle.net/21.15107/rcub_imagine_1985" }
Divac Rankov, A., Ušjak, D., Mitić, M. M.,& Kusić Tisma, J.. (2023). Decoding Cystic Fibrosis Phenotype. in 4th Belgrade Bioinformatics Conference Belgrade : Institute of molecular genetics and genetic engineering., 4, 44-44. https://hdl.handle.net/21.15107/rcub_imagine_1985
Divac Rankov A, Ušjak D, Mitić MM, Kusić Tisma J. Decoding Cystic Fibrosis Phenotype. in 4th Belgrade Bioinformatics Conference. 2023;4:44-44. https://hdl.handle.net/21.15107/rcub_imagine_1985 .
Divac Rankov, Aleksandra, Ušjak, Dušan, Mitić, Martina Mia, Kusić Tisma, Jelena, "Decoding Cystic Fibrosis Phenotype" in 4th Belgrade Bioinformatics Conference, 4 (2023):44-44, https://hdl.handle.net/21.15107/rcub_imagine_1985 .