Co-expression Profiling of Autism Genes in the Mouse Brain

Autism spectrum disorder (ASD) is one of the most prevalent and highly heritable neurodevelopmental disorders in humans. There is significant evidence that the onset and severity of ASD is governed in part by complex genetic mechanisms affecting the normal development of the brain. To date, a number of genes have been associated with ASD. However, the temporal and spatial co-expression of these genes in the brain remain unclear. To address this issue, we examined the co-expression network of 26 autism genes from AutDB (http://mindspec.org/autdb.html), in the framework of 3,041 genes whose expression energies have the highest correlation between the coronal and sagittal images from the Allen Mouse Brain Atlas database (http://mouse.brain-map.org). These data were derived from in situ hybridization experiments conducted on male, 56-day old C57BL/6J mice co-registered to the Allen Reference Atlas, and were used to generate a normalized co-expression matrix indicating the cosine similarity between expression vectors of genes in this database. The network formed by the autism-associated genes showed a higher degree of co-expression connectivity than seen for the other genes in this dataset (Kolmogorov–Smirnov P = 5×10−28). Using Monte Carlo simulations, we identified two cliques of co-expressed genes that were significantly enriched with autism genes (A Bonferroni corrected P<0.05). Genes in both these cliques were significantly over-expressed in the cerebellar cortex (P = 1×10−5) suggesting possible implication of this brain region in autism. In conclusion, our study provides a detailed profiling of co-expression patterns of autism genes in the mouse brain, and suggests specific brain regions and new candidate genes that could be involved in autism etiology

Micro-, Meso- and Macro-Connectomics of the Brain

Neurosciences, Neurolog

Functional genomics studies of human brain development and implications for autism spectrum disorder

Human neurodevelopment requires the coordinated expression of thousands of genes, exquisitely regulated in both spatial and temporal dimensions, to achieve the proper specialization and inter-connectivity of brain regions. Consequently, the dysregulation of complex gene networks in the developing brain is believed to underlie many neurodevelopmental disorders, such as autism spectrum disorders (ASD). Autism has a significant genetic etiology, but there are hundreds of genes implicated, and their functions are heterogeneous and complex. Therefore, an understanding of shared molecular and cellular pathways underlying the development ASD has remained elusive, hampering attempts to develop common diagnostic biomarkers or treatments for this disorder. I hypothesized that analyzing functional genomics relationships among ASD candidate genes during normal human brain development would provide insight into common cellular and molecular pathways that are affected in autistic individuals, and may help elucidate how hundreds of diverse genes can all be linked to a single clinical phenotype. This thesis describes a coordinated set of bioinformatics experiments that first (i) assessed for gene expression and co-expression properties among ASD candidates and other non-coding RNAs during normal human brain development to discover potential shared mechanisms; and then (ii) directly assessed for changes in these pathways in autistic post-mortem brain tissue. The results demonstrated that when examined in the context of normal human brain gene expression during early development, autism candidate genes appear to be strongly related to the neurodevelopmental pathways of synaptogenesis, mitochondrial function, glial cytokine signaling, and transcription/translation regulation. Furthermore, the known sex bias in ASD prevalence appeared to relate to differences in gene expression between the developing brains of males and females. Follow up studies in autistic brain tissue confirmed that changes in mitochondrial gene expression networks, glial pathways, and gene expression regulatory mechanisms are all altered in the brains of autistic individuals. Together, these results show that the heterogeneous set of autism candidate genes are related to each other through shared transcriptional networks that funnel into common molecular mechanisms, and that these mechanisms are aberrant in autistic brains

Reconstructing and analysing protein-protein interaction networks of synaptic molecular machines

EPSRC Doctorate Training Centres (DTC) programme (EP/D505984/1)The postsynaptic density (PSD) is a complex, dynamic structure composed of ~2000 distinct proteins, found at the postsynaptic membrane. Interactions, of transient and non-transient nature, organise the PSD’s constituent parts into a protein complex, which functions as an intricately regulated molecular machine, orchestrating the mediation and regulation of synaptic transmission and synaptic plasticity. Furthermore, many of the proteins found in this complex have been linked to synaptic and behavioural plasticity, basic cognition or disease. Although, through proteomics we have accumulated a lot of information on the constituent parts of this machine as well smaller sub-networks representing pathways, not a lot is known about the organisational principles of the PSD. In this project our aim is to develop a standardised approach to reconstructing protein interaction networks from PSD proteomics data, providing a descriptive integrative model. Using these models we also performed an analysis elucidating parts of these organisational principles. We applied this method on two murine postsynaptic density proteomics datasets and found a persistent modular architecture of biological significance. Furthermore, given the lack of substantial evidence on the composition and architecture of postsynaptic density interaction networks of other model organisms, we decided to perform an affinity purification of Drosophila melanogaster postsynaptic density proteins and perform a similar analysis. The resulting model corroborated theoretical predictions of a lower complexity but similar functionality and also showed a modular architecture. As a final analysis we compared the two models from a structural and evolutionary perspective attempting to elucidate the mechanisms of evolution of this molecular machine. The results of this analysis implied that a whole component rather than just individual proteins of the fly protein interaction network have been conserved, highlighting the importance of the aforementioned organisational principles

Sexual orientation and gender-identity in high functioning individuals with autism spectrum disorder.

When compared to typically-developing individuals, individuals with Autism Spectrum Disorder(ASD) demonstrated significantly higher sexual diversity, with higher rates of non-heterosexuality, and reported more gender non-conforming identities. The ASD group reported poorer mental health than typically-developing individuals and belonging to a sexual or gender-diverse group worsened this effect

Pacific Symposium on Biocomputing 2023

The Pacific Symposium on Biocomputing (PSB) 2023 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2023 will be held on January 3-7, 2023 in Kohala Coast, Hawaii. Tutorials and workshops will be offered prior to the start of the conference.PSB 2023 will bring together top researchers from the US, the Asian Pacific nations, and around the world to exchange research results and address open issues in all aspects of computational biology. It is a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling, and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology.The PSB has been designed to be responsive to the need for critical mass in sub-disciplines within biocomputing. For that reason, it is the only meeting whose sessions are defined dynamically each year in response to specific proposals. PSB sessions are organized by leaders of research in biocomputing's 'hot topics.' In this way, the meeting provides an early forum for serious examination of emerging methods and approaches in this rapidly changing field