Biology subjects

Fisher, E.

Publications and source records attributed to Fisher, E..

4 recordsLinked to original sources

bioRxiv2019

Nova proteins direct synaptic integration of somatostatin interneurons through activity-dependent alternative splicing

Somatostatin interneurons are the earliest born population of cortical inhibitory cells. They are crucial to support normal brain development and function; however, the mechanisms underlying their integration into nascent cortical circuitry are not well understood. In this study, we begin by demonstrating that the maturation of somatostatin interneurons is activity dependent. We then investigated the relationship between activity, alternative splicing and synapse formation within this population. Specifically, we discovered that the Nova family of RNA-binding proteins are activity-dependent and are essential for the maturation of somatostatin interneurons, as well as their afferent and efferent connectivity. Within this population, Nova2 preferentially mediates the alternative splicing of genes required for axonal formation and synaptic function independently from its effect on gene expression. Hence, our work demonstrates that the Nova family of proteins through alternative splicing are centrally involved in coupling developmental neuronal activity to cortical circuit formation.

neuroscience↗

bioRxiv2019

High-sensitivity monitoring of ctDNA by patient-specific sequencing panels and integration of variant reads

Circulating tumor-derived DNA (ctDNA) can be used to monitor cancer dynamics noninvasively. Patients with small tumors have few copies of ctDNA in plasma, resulting in limited sensitivity to detect low-volume or residual disease. We show that sampling limitations can be overcome and sensitivity for ctDNA detection can be improved by massively parallel sequencing when hundreds to thousands of mutations are identified by tumor genotyping. We describe the INtegration of VAriant Reads (INVAR) analysis pipeline, which combines patient-specific mutation lists with both custom error-suppression methods and signal enrichment based on biological features of ctDNA. In this framework, the sensitivity can be estimated independently for each sample based on the number of informative reads, which is the product of the number of mutations analyzed and the average depth of unique sequencing reads. We applied INVAR to deep sequencing data generated by custom hybrid-capture panels, and showed that when ~106 informative reads were obtained INVAR allowed detection of tumor-derived DNA fractions to parts per million (ppm). In serial samples from patients with advanced melanoma on treatment, we detected ctDNA when imaging confirmed tumor volume of ~1cm3. In patients with resected early-stage melanoma, ctDNA was detected in 40% of patients who later relapsed, with higher rates of detection when more informative reads were obtained. We further demonstrated that INVAR can be generalized and allows improved detection of ctDNA from whole-exome and low-depth whole-genome sequencing data.

cancer biology↗

bioRxiv2019

A landmark-free morphometric pipeline: Application to characterise a Down syndrome model skull phenotype

Characterising phenotypes often requires quantification of anatomical shapes. Quantitative shape comparison (morphometrics) traditionally uses anatomical landmarks and is therefore limited by the number of landmarks and operator accuracy when landmarks are located manually. Here we apply a landmark-free method to characterise the craniofacial skeletal phenotype of the Dp1Tyb mouse model of Down syndrome (DS), validating it against a landmark-based approach. We identify cranial dysmorphologies in Dp1Tyb mice, especially smaller size and brachycephaly (front-back shortening) homologous to the human phenotype. The landmark-free phenotyping was less labour-intensive and required less user training than the landmark-based method. It also enabled mapping of local differences as planar expansion or shrinkage. This higher resolution and local mapping pinpointed reductions in interior mid-snout structures and occipital bones in this DS model that were not as apparent using a traditional landmark-based method. This approach could make morphometrics widely-accessible beyond traditional niches in zoology and palaeontology, especially in characterising mutant phenotypes.

genetics↗

bioRxiv2019

FUS ALS-causative mutations impact FUS autoregulation and the processing of RNA-binding proteins through intron retention

Mutations in the RNA-binding protein FUS cause amyotrophic lateral sclerosis (ALS), a devastating neurodegenerative disease in which the loss of motor neurons induces progressive weakness and death from respiratory failure, typically only 3-5 years after onset. FUS plays a role in numerous aspects of RNA metabolism, including mRNA splicing. However, the impact of ALS-causative mutations on splicing has not been fully characterised, as most disease models have been based on FUS overexpression, which in itself alters its RNA processing functions. To overcome this, we and others have recently created knock-in models, and have generated high depth RNA-sequencing data on FUS mutants in parallel to FUS knockout. We combined three independent datasets with a joint modelling approach, allowing us to compare the mutation-induced changes to genuine loss of function. We find that FUS ALS-mutations induce a widespread loss of function on expression and splicing, with a preferential effect on RNA binding proteins. Mutant FUS induces intron retention changes through RNA binding, and we identify an intron retention event in FUS itself that is associated with its autoregulation. Altered FUS regulation has been linked to disease, and intriguingly, we find FUS autoregulation to be altered not only by FUS mutations, but also in other genetic forms of ALS, including those caused by TDP-43, VCP and SOD1 mutations, supporting the concept that multiple ALS genes interact in a regulatory network.

neuroscience↗