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Biology subjects

Craig, D. W.

Publications and source records attributed to Craig, D. W..

2 recordsLinked to original sources

Complex genetic network underlying the convergent of Rett Syndrome like (RTT-L) phenotype in neurodevelopmental disorders

Mutations of the X-linked gene encoding methyl-CpG-binding protein 2 (MECP2) cause classical forms of Rett syndrome (RTT) in girls. Patients with features of classical Rett syndrome, but do not fulfill all the diagnostic criteria (e.g. absence of a MECP2 mutation), are defined as atypical Rett syndrome. Genes encoding for cyclin-dependent kinase-like 5 (CDKL5) and forkhead box G1 (FOXG1) are more commonly found in patients with atypical Rett syndrome. Nevertheless, a subset of patients who are recognized to have an overlapping phenotype with RTT but are lacking a mutation in a gene that causes typical or atypical RTT are described as having Rett syndrome like phenotype (RTT-L). Whole Exome Sequencing (WES) of 8 RTT-L patients from our cohort revealed mutations in the genes GABRG2, GRIN1, ATP1A2, KCNQ2, KCNB1, TCF4, SEMA6B, and GRIN2A, which are seemingly unrelated to Rett syndrome genes. We hypothesized that the phenotypic overlap in RTT and RTT-L is caused by mutations in genes that affect common cellular pathways critical for normal brain development and function. We annotated the list of genes identified causing RTT-L from peer-reviewed articles and performed a protein-protein interaction (PPI) network analysis. We also investigated their interaction with RTT (typical or atypical) genes such as MECP2, CDKL5, NTNG1, and FOXG1. We found that the RTT-L-causing genes were enriched in the biological pathways such as circadian entrainment, the CREB pathway, and RET signaling, and neuronal processes like ion transport, synaptic transmission, and transcription. We conclude that genes that significantly interact with the PPI network established by RTT genes cause RTT-L, explaining the considerable feature overlap between genes that are indicated for RTT-L and RTT.

genomics

Resolving sub-clonal heterogeneity within cell-line growths by single cell sequencing genomic DNA

We performed shallow single-cell sequencing of genomic DNA across 1,475 cells from a well-studied cell-line, COLO829, to resolve overall tumor complexity and clonality. This melanoma tumor-line has been previously characterized by multiple technologies and provides a benchmark for evaluating somatic alterations, though has exhibited conflicting and indeterminate copy number states. We identified at least four major sub-clones by discriminant analysis of principal components (DAPC) of single cell copy number data. Break-point and loss of heterozygosity (LOH) analysis of aggregated data from sub-clones revealed a complex rearrangement of chromosomes 1, 10 and 18 that was maintained in all but two sub-clones. Likewise, two of the sub-clones were distinguished by loss of 1 copy of chromosome 8. Re-analysis of previous spectral karyotyping data and bulk sequencing data recapitulated these sub-clone hallmark features and explains why the original bulk sequencing experiments generated conflicting copy number results. Overall, our results demonstrate how shallow copy number profiling together with clustering analysis of single cell sequencing can uncover significant hidden insights even in well studied cell-lines.

genomics