Abstract
Autosomal recessive diseases (ARD) are typically caused by a limited number of mutations whose identification is challenged by their low prevalence. Our purpose was to develop a novel approach allowing an efficient search for mutations causing ARD and evaluation of their pathogenicity without a control group. We developed Iterative Sequencing and Variant Screening (ISVS) approach based on iterative cycles of gene sequencing and mutation screening, and ISVS Simulator software (http://zsibio.ii.pw.edu.pl/shiny/isvs/) for assessment of detected variants’ significance. As shown by simulations, ISVS efficiently identifies and correctly classifies pathogenic mutations except for cases where the gene of interest has extremely high number of low frequency nonpathogenic variants. By applying ISVS, we found 4 known and 9 novel (p.C73Y, p.S124L, p.C194Mfs*17, c.782 + 2 T > A, c.953-5 A > G, p.L325Q, p.D334Mfs*24, p.R436G, p.M448T) TMPRSS3 variants among deaf patients. For 3 known and 5 novel variants the disease association was supported by ISVS Simulator odds >90:1. Pathogenicity of 6 novel mutations has been supported by in-silico predictions of variants’ deleteriousness. By directly comparing variant prevalence in patients and controls, disease association was demonstrated only for two variants and it was relatively weak (P < 0.05). Summarizing, ISVS strategy and ISVS Simulator are useful for detection of genetic variants causing AR diseases.
Highlights
Autosomal recessive diseases (ARD) are often caused by a limited number of mutations
Iterative Sequencing and Variant Screening (ISVS) simulations with parameters adjusted for TMPRSS gene and sensorineural hearing loss (SNHL) we found that, on average, by 4.75 steps of an ISVS experiment the success rate was 0.98
In order to facilitate the more broad use of ISVS we developed software (ISVS Simulator) that enables user to test the performance of the method under scenarios different than the considered by us TMPRSS mutation screen in SNHL subjects
Summary
Autosomal recessive diseases (ARD) are often caused by a limited number of mutations. Whereas numerous in silico tools for mutation effect prediction are available they are not perfect and the assignment of pathogenicity remains a challenge, especially for variants with very low population frequency[1]. For such rare variants the association with disease defined as more frequent occurrence of a variant among the patients than controls is an important sine qua non criterion of pathogenicity[2]. The purpose of our work was to develop and validate a novel approach allowing: (i) an efficient search for mutations causing ARD, (ii) evaluation of their pathogenicity by testing for disease association without using a control group. ISVS simulations showed for six of these variants (4 novel) strong (>1000:1) evidence for disease association, for two (1 novel) the evidence was moderate (90:1) and for five (4 novel) - weak
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