How do non-coding enhancer RNAs confer genetic risk in amyotrophic lateral sclerosis (ALS)?

Amyotrophic Lateral Sclerosis (ALS) is an aggressive neurodegenerative disease with no effective therapy. The established genetic causes of ALS can only explain a small fraction of the observed disease phenotypes. This project will explore how newly uncovered disease mutations in non-coding regions of the genome contribute to ALS.

Large scale whole genome sequencing (WGS) in ALS patients has highlighted the importance of new mutations in non-coding enhancers. Enhancers are gene regulatory elements crucial for cell-lineage specific gene expression, and are transcribed into non-coding RNAs called enhancer RNAs (eRNAs). You will lead a project to investigate whether novel non-coding ALS mutations affect the structure of eRNAs, and whether this affects epigenetic chromatin modifications and gene expression to drive ALS disease progression.

The project will establish a new and exciting collaboration between two Wellcome Trust Funded groups at the University of Sheffield. The Bose Lab is at the forefront of efforts to uncover the molecular basis for eRNA function. The Cooper-Knock lab leads analysis of the non-coding genome for WGS consortium Project MinE (www.projectmine.com), enabling identification and analysis of rare genetic associations in ALS. The project therefore provides a unique opportunity to work in some of the newest and fastest moving fields in science: molecular mechanisms of non-coding RNAs and the contribution of non-coding disease mutations to complex diseases.

Training
You will receive a broad, multidisciplinary training in functional genomics approaches. This will include techniques for both high-throughout (in-cell) and targeted (in vitro) determination of RNA structure; next-generation and Nanopore sequencing (ChIPseq, NETseq and long-read RNAseq); targeted genome and epigenome editing (CRISPR/CRISPRa/i). Importantly, the project offers a unique opportunity to link these experimental approaches at the bench to bioinformatics training, including development of new deep-learning models for predicting genetic variants in ALS. The work will provide a new understanding of one of the most relevant questions in biology, with broad implications for disease mechanisms in common human diseases.

Community
You will be supervised by Dr Daniel Bose (Dept. of Molecular Biology and Biotechnology) and Dr Johnathan Cooper-Knock