Analysis of miRNA rare variants in amyotrophic lateral sclerosis and in silico prediction of their biological effects.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease affecting upper and/or lower motor neurons and characterized by complex etiology. Familial cases show high genetic heterogeneity and sporadic cases (90%) are associated with several genetic and environmental risk factors. Among the genetic risk factors, the contribution of non-coding elements, such as microRNAs (miRNAs), to ALS disease susceptibility remains largely unexplored. This work aims to identify rare variants in miRNA genes in sporadic ALS (sALS) patients which may cause a defective miRNA maturation or altered target gene recognition by changing miRNA secondary structure or seed sequence, respectively. Rare variants located in miRNA loci with a minor allele frequency (MAF) < 0.01 were extracted from whole genome sequencing (WGS) data of 100 sALS patients. The secondary pre-miRNA structures were predicted using MiRVas to evaluate the impact of the variants on RNA folding process. Human TargetScan was used to retrieve all the potential target genes of miRNAs with variants in the seed region. Over Representation Analysis (ORA) was conducted to compare the lists of target genes for the reference and mutated miRNAs in the seed sequence. Our analysis identified 86 rare variants in 77 distinct miRNAs and distributed in different parts of the miRNA precursors. The presence of these variants changed miRNA secondary structures in ∼70% of MiRVas predictions. By focusing on the 6 rare variants mapping within the seed sequence, the predicted target genes increased in number compared to the reference miRNA and included novel targets in a proportion ranging from 30 to 82%. Interestingly, ORA revealed significant changes in gene set enrichment only for mutated miR-509-1 and miR-941-3 for which the Gene Ontology term related to "nervous system development" was absent and present, respectively, compared to target lists of the reference miRNA. We here developed a workflow to study miRNA rare variants from WGS data and to predict their biological effects on miRNA folding, maturation and target gene recognition. Although this approach certainly needs functional validation and , it may help define the role of miRNA variability in ALS and complex diseases.