Identifying and understanding the disease relevance of novel transcripts in human brain development

Background:
Gene definitions (namely genic coordinates and the isoforms/exons of which they are composed) are required for the quantification of expression or splicing from RNA-sequencing experiments, interpretation of significant genome-wide association studies (GWAS) signals and perhaps most importantly, variant interpretation from genetic tests. Yet, there is growing evidence to suggest that human gene annotation remains incomplete, with a disproportionate impact on the human brain transcriptome1. Annotation-independent analysis of RNA-sequencing (RNA-seq) data from my group has already shown that genes which are highly expressed in human brain, including those already linked to paediatric and adult neurogenetic disorders, are often mis-annotated and this is likely to be limiting our ability to diagnose and understand neurogentic disorders2. Furthermore, this analysis suggested that many brain-expressed genes are poorly annotated because they are specific to a brain region or a cell type2. This implies that the difficulties of “sampling” human brain comprehensively are restricting our understanding of key areas of the transcriptome3. This includes not only the problem of sampling across all cell types, but also across brain development.  This PhD project will address this knowledge gap through the integrated analysis of public bulk tissue RNA-sequencing data, targeted single nuclear RNA-seq of human brain and iPSC-derived cell type modelling. Collectively the knowledge gained will be used to try and improved the diagnostic rate for paediatric neurogenetic disorders.

Aims/Objectives:
1. Identification of novel transcripts of known disease-associated genes expressed during brain development using publicly available and in-house resources.
2. Assessment of the relevance of novel transcripts to human disease through rare variant burden analysis using WGS data generated by the 100,000 Genomes Project.
3. Functional assessment of novel transcripts of disease relevance using iPSC-derived cortical neurons/organoids.

Methods:

• Annotation-independent analysis of RNA-seq data: The student will use existing laboratory pipelines based on derfinder to analyse i) public short read RNA-seq data originating from post-mortem brain across development, ii) targeted short and long-read RNA-seq data generated using ICH samples (in collaboration with Professor Jacques) and iii) from iPSC-derived purified cell types and/or organoids (in collaboration with Professor Livesey).
• Rare variant burden analyses in novel transcripts amongst children recruited to the 100,000 Genomes project with neurological conditions: The student will SKAT-O analyses to calculate the burden of rare potentially variants predicted to be missense or loss-of-function amongst paediatric patients with neurological disease in order to identify sets of transcripts of interest.
• Use of iPSC-derived models of brain development to investigate the functional significance of specific transcripts of interest: The student will use established iPSC models of neuronal development and maturation to study the functional significance of specific transcripts of interest (in collaboration with Professor Livesey). Combining functional assays with a range of approaches to knockdown/over-express specific transcripts, the student will investigate disease-relevant transcripts highlighted through the analyses above.

Timeline:

References:
1. Jaffe AE et al. Developmental regulation of human cortex transcription and its clinical relevance at single base resolution. Nat Neurosci. 2015.
2. Zhang D et al. Incomplete annotation of OMIM genes is likely to be limiting the diagnostic yield of genetic testing, particularly for neurogenetic disorders. Science Adv. 2020.
3. Reynolds RH et al. Informing disease modelling with brain-relevant functional genomic annotations. Brain. 2019.