RESUMO
In addition to commonly associated environmental factors, genomic factors may cause cerebral palsy. We performed whole-exome sequencing of 250 parent-offspring trios, and observed enrichment of damaging de novo mutations in cerebral palsy cases. Eight genes had multiple damaging de novo mutations; of these, two (TUBA1A and CTNNB1) met genome-wide significance. We identified two novel monogenic etiologies, FBXO31 and RHOB, and showed that the RHOB mutation enhances active-state Rho effector binding while the FBXO31 mutation diminishes cyclin D levels. Candidate cerebral palsy risk genes overlapped with neurodevelopmental disorder genes. Network analyses identified enrichment of Rho GTPase, extracellular matrix, focal adhesion and cytoskeleton pathways. Cerebral palsy risk genes in enriched pathways were shown to regulate neuromotor function in a Drosophila reverse genetics screen. We estimate that 14% of cases could be attributed to an excess of damaging de novo or recessive variants. These findings provide evidence for genetically mediated dysregulation of early neuronal connectivity in cerebral palsy.
Assuntos
Paralisia Cerebral/genética , Proteínas F-Box/genética , Tubulina (Proteína)/genética , Proteínas Supressoras de Tumor/genética , beta Catenina/genética , Animais , Paralisia Cerebral/patologia , Ciclina D/genética , Citoesqueleto/genética , Drosophila/genética , Exoma/genética , Matriz Extracelular/genética , Feminino , Adesões Focais/genética , Predisposição Genética para Doença , Genoma Humano/genética , Humanos , Masculino , Mutação/genética , Neuritos/metabolismo , Neuritos/patologia , Fatores de Risco , Análise de Sequência de DNA , Transdução de Sinais/genética , Sequenciamento do Exoma , Proteína rhoB de Ligação ao GTP/genéticaRESUMO
Tumor heterogeneity, the cellular mosaic of multiple lineages arising from the process of clonal evolution, has continued to thwart multi-omics analyses using traditional bulk sequencing methods. The application of single-cell sequencing, in concert with existing genomics methods, has enabled high-resolution interrogation of the genome, transcriptome, epigenome, and proteome. Applied to cancers, these single-cell multi-omics methods bypass previous limitations on data resolution and have enabled a more nuanced understanding of the evolutionary dynamics of tumor progression, immune evasion, metastasis, and treatment resistance. This review details the growing number of novel single-cell multi-omics methods applied to tumors and further discusses recent discoveries emerging from these approaches, especially in regard to immunotherapy.