• Título:  DECIPHERING THE NON-CODING GENOME IN AUTISM SPECTRUM DISORDERS (ASD): IN SILICO CHARACTERIZATION OF COMMON, SPLICING AND REGULATORY VARIANTS
• Autor:  Domínguez Alonso, Sara
• Universidad:  Universidad de Santiago de Compostela
• Departamento:  Escuela de Doctorado Internacional (EDIUS)
• Fecha de Lectura:  11/06/2024
• Mención Europeo / Mención Internacional: concedido
• Programa de doctorado:  Programa de Doctorado en Medicina Molecular por la Universidad de Santiago de Compostela
• Dirección: 
  • CARRACEDO ALVAREZ, ANGEL MARIA (DIRECTOR)
  • Rodríguez Fontenla, María Cristina (DIRECTOR)
• Tribunal: 
  • Sánchez Piñón, Laura (PRESIDENTE)
  • GARCÍA BUENO, BORJA (SECRETARIO)
  • Cantagrel, Vincent (VOCAL)
• Descriptores: 
  • GENETICA HUMANA
• Localización:  BIBLIOTECA XERAL USC
• 788274_1685566.pdf
• Resumen:
  Despite the high heritability estimates in autism spectrum disorders (ASD), there is a lack of direct confirmation from current genetic studies, leading to the term missing heritability, which signifies the incomplete understanding of the genetic factors contributing to ASD etiology. In recent years, speculation surrounding this named missing heritability has shifted towards the non-coding genome, a portion nearly 99 times larger in genomic size than protein-coding genes. However, elucidating the role of the non-coding genome in genetic studies is challenging because, unlike coding regions that directly produce proteins, the functions of many non-coding regions are not as well annotated or understood. Thus, identifying and characterizing these functional elements requires specific bioinformatic analysis. In this PhD thesis, we have applied specific bioinformatic workflows aiming to decipher part of the missing heritability lying within the non-coding genome, elucidating novel genes, biological pathways, and molecular functions. This was achieved by (i) conducting an eQTL colocalization analysis that integrates expression data from GTEX with summary statistics from the largest ASD GWAS to date, (ii) assessing the role of splicing variation in ASD by mining exome data using deep learning methods, and (iii) conducting a targeted sequencing study of a selection of regulatory elements (cCREs) from ENCODE in ASD trios to detect de novo and inherited mutations and their functional implications. Through a combination of bioinformatics methods and diverse genetic data collections, we have uncovered insights into a broad spectrum of genetic variation. In summary, the findings from this in silico characterization of common, splicing, and regulatory variants include the identification of specific genes most likely to be affected by non-coding common variation, a deeper understanding of how splicing variation may mediate disease risk, and the establishment of a crucial role for chromatin conformation in ASD. This thesis aims to further investigate the role of missing heritability in ASD genetics using different genetic and bioinformatic study strategies. In this way, novel potential ASD risk genes were pinpointed, and the role of mutations within regulatory elements and chromatin structure has been unveiled. Future functional validation of these targets will open new avenues for improving ASD diagnosis and, subsequently, treatment.