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Whole-Transcriptome Analysis by RNA Sequencing for Genetic Diagnosis of Mendelian Skin Disorders in the Context of Consanguinity
Author(s) -
Leila Youssefian,
Amir Hossein Saeidian,
Fahimeh Palizban,
Atefeh Bagherieh,
Fahimeh Abdollahimajd,
Soheila Sotoudeh,
Nikoo Mozafari,
Rahele A. Farahani,
Hamidreza Mahmoudi,
Sadegh Babashah,
Masoud Zabihi,
Sirous Zeinali,
Paolo Fortina,
Julio C. SalasAlanís,
Andrew P. South,
Hassan Vahidnezhad,
Jouni Uitto
Publication year - 2021
Publication title -
clinical chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.705
H-Index - 218
eISSN - 1530-8561
pISSN - 0009-9147
DOI - 10.1093/clinchem/hvab042
Subject(s) - genetics , biology , transcriptome , rna seq , rna , gene , intron , dna sequencing , computational biology , genome , whole genome sequencing , exome sequencing , mutation , gene expression
Background Among the approximately 8000 Mendelian disorders, >1000 have cutaneous manifestations. In many of these conditions, the underlying mutated genes have been identified by DNA-based techniques which, however, can overlook certain types of mutations, such as exonic-synonymous and deep-intronic sequence variants. Whole-transcriptome sequencing by RNA sequencing (RNA-seq) can identify such mutations and provide information about their consequences. Methods We analyzed the whole transcriptome of 40 families with different types of Mendelian skin disorders with extensive genetic heterogeneity. The RNA-seq data were examined for variant detection and prioritization, pathogenicity confirmation, RNA expression profiling, and genome-wide homozygosity mapping in the case of consanguineous families. Among the families examined, RNA-seq was able to provide information complementary to DNA-based analyses for exonic and intronic sequence variants with aberrant splicing. In addition, we tested the possibility of using RNA-seq as the first-tier strategy for unbiased genome-wide mutation screening without information from DNA analysis. Results We found pathogenic mutations in 35 families (88%) with RNA-seq in combination with other next-generation sequencing methods, and we successfully prioritized variants and found the culprit genes. In addition, as a novel concept, we propose a pipeline that increases the yield of variant calling from RNA-seq by concurrent use of genome and transcriptome references in parallel. Conclusions Our results suggest that “clinical RNA-seq” could serve as a primary approach for mutation detection in inherited diseases, particularly in consanguineous families, provided that tissues and cells expressing the relevant genes are available for analysis.

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