An Effective and Universal Long-Read Sequencing-Based Approach for SMN1 2 + 0 Carrier Screening through Family Trio Analysis.

Journal: Clinical Chemistry
Published:
Abstract

Background: Population-wide carrier screening for spinal muscular atrophy (SMA) is recommended by professional organizations to facilitate informed reproductive options. However, genetic screening for SMN1 2 + 0 carriers, accounting for 3%-8% of all SMA carriers, has been challenging due to the large gene size and long distance between the 2 SMN genes.

Methods: Here we repurposed a previously developed long-read sequencing-based approach, termed comprehensive analysis of SMA (CASMA), to identify SMN1 2 + 0 carriers through haplotype analysis in family trios (CASMA-trio). Bioinformatics pipelines were developed for accurate haplotype analysis and SMN1 2 + 0 deduction. Seventy-nine subjects from 24 families composed of, at the minimum, 3 were enrolled, and CASMA-trio was employed to determine whether an index subject with 2 SMN1 copies was a 2 + 0 carrier in these families. For the proof-of-principle, SMN2 2 + 0 was also analyzed.

Results: Among the 16 subjects with 2 SMN1 copies, CASMA-trio identified 5 subjects from 4 families as SMN1 2 + 0 carriers, which was consistent with pedigree analysis involving an affected proband. CASMA-trio also identified SMN2 2 + 0 in six out of 43 subjects with 2 SMN2 copies. Additionally, CASMA-trio successfully determined the distribution pattern of SMN1 and SMN2 genes on 2 alleles in all 79 subjects.

Conclusions: CASMA-trio represents an effective and universal approach for SMN1 2 + 0 carriers screening, as it does not reply on the presence of an affected proband, certain single-nucleotide polymorphisms, ethnicity-specific haplotypes, or complicated single-nucleotide polymorphism analysis across 3 generations. Incorporating CASMA-trio into existing SMA carrier screening programs will greatly reduce residual risk ratio.

Authors
Shuyuan Li, Xu Han, Liang Zhang, Yan Xu, Chunxin Chang, Li Gao, Jiahan Zhan, Renyi Hua, Aiping Mao, Yanlin Wang