Genetic heterogeneity of individuals highlights the need to enhance personalized medicine to achieve effective treatments of human diseases. Spinal muscular atrophy (SMA) is an autosomal recessive neuromuscular disease characterized by degeneration of α-motorneurons in the spinal cord. The primary SMA-determining gene is SMN1, absent in about 95% of patients. The neighbouring nearly identical SMN2 gene fails to generate adequate levels of full-length SMN protein (FL-SMN). Still, SMN2 copy numbers can vary between 1 and 6, potentially modifying the severity of the disease. However, all SMN2 alleles are not functionally equivalent since they produce FL-transcripts with different efficiencies, most probably due to variations in their sequence.
We established a new method to identify genetic polymorphisms in the complete genomic region of SMN2. Samples were sequenced by Illumina platform and a pooled indexing strategy. The estimated variant frequencies are usually indicative of the number of variant gene copies per subject when related to the individual’s SMN2 copy numbers.
The method we described is ready to be used to identify variants/haplotypes associated with a particular SMA phenotype.
