Next-generation sequencing (NGS) is a useful molecular diagnostic tool for genetic diseases. However, due to the presence of highly homologous pseudogenes, it is challenging to use short-read NGS for analyzing mutations of the Shwachman-Bodian-Diamond syndrome (SBDS) gene. The SBDS mutation spectrum was analyzed in the Chinese population, which revealed that SBDS variants were primarily from sequence exchange between SBDS and its pseudogene at the base-pair level, predominantly in the coding region and splice junction of exon two. The c.258+2T>C and c.185_184TA>GT variants were the two most common pathogenic SBDS variants in the Chinese population, resulting in a total carrier frequency of 1.19%. When analyzing pathogenic variants in the SBDS gene from the NGS data, the misalignment was identified as a common issue, and there were different probabilities of misalignment for different pathogenic variants. Here, we present a novel mathematical method for identifying pathogenic variants in the SBDS gene from the NGS data, which utilizes read-depth of the paralogous sequence variant (PSV) loci of SBDS and its pseudogene. Combined with PCR and STR orthogonal experiments, SBDS gene mutation analysis results were improved in 40% of clinical samples, and various types of mutations such as homozygous, compound heterozygous, and uniparental diploid were explored. The findings effectively reduce the impact of misalignment in NGS-based SBDS mutation analysis and are helpful for the clinical diagnosis of SBDS-related diseases, the research into population variation, and the carrier screening.

Next-generation sequencing (NGS) is a useful molecular diagnostic tool for genetic diseases. However, due to the presence of highly homologous pseudogenes, it is challenging to use short-read NGS for analyzing mutations of the Shwachman-Bodian-Diamond syndrome (SBDS) gene. The SBDS mutation spectrum was analyzed in the Chinese population, which revealed that SBDS variants were primarily from sequence exchange between SBDS and its pseudogene at the base-pair level, predominantly in the coding region and splice junction of exon two. The c.258+2T>C and c.185_184TA>GT variants were the two most common pathogenic SBDS variants in the Chinese population, resulting in a total carrier frequency of 1.19%. When analyzing pathogenic variants in the SBDS gene from the NGS data, the misalignment was identified as a common issue, and there were different probabilities of misalignment for different pathogenic variants. Here, we present a novel mathematical method for identifying pathogenic variants in the SBDS gene from the NGS data, which utilizes read-depth of the paralogous sequence variant (PSV) loci of SBDS and its pseudogene. Combined with PCR and STR orthogonal experiments, the results of SBDS gene mutation analysis were improved in 40% of clinical samples, and various types of mutations such as homozygous, compound heterozygous, and uniparental diploid were explored. The findings effectively reduce the impact of misalignment in NGS-based SBDS mutation analysis and are helpful for the clinical diagnosis of SBDS-related diseases, the research into population variation, and the carrier screening.