Biology subjects

Lelliott, C. J.

Publications and source records attributed to Lelliott, C. J..

5 recordsLinked to original sources

bioRxiv2022

Mouse and cellular models of KPTN-related disorder implicate mTOR signalling in cognitive and progressive overgrowth phenotypes

KPTN-related disorder (KRD) is an autosomal recessive disorder associated with germline variants in KPTN (kaptin), a component of the mTOR regulatory complex KICSTOR. To gain further insights into the pathogenesis of KRD, we analysed mouse knockout and human stem cell KPTN loss-of-function models. Kptn-/- mice display many of the key KRD phenotypes, including brain overgrowth, behavioural abnormalities, and cognitive deficits. Assessment of affected individuals has identified concordant selectivity of cognitive deficits, postnatal onset of brain overgrowth, and a previously unrecognised KPTN dosage-sensitivity, resulting in increased head circumference in their heterozygous parents. Molecular and structural analysis of Kptn-/- mice revealed pathological changes, including differences in brain size, shape, and cell numbers primarily due to abnormal postnatal brain development. Both the mouse and differentiated iPSC models of the disorder display transcriptional and biochemical evidence for altered mTOR pathway signalling, supporting the role of KPTN in regulating mTORC1. Increased mTOR signalling downstream of KPTN is rapamycin sensitive, highlighting possible therapeutic avenues with currently available mTOR inhibitors. These findings place KRD in the broader group of mTORC1 related disorders affecting brain structure, cognitive function, and network integrity.

genetics↗

bioRxiv2020

Osteocyte Transcriptome Mapping Identifies a Molecular Landscape Controlling Skeletal Homeostasis and Susceptibility to Skeletal Disease

Osteocytes are master regulators of the skeleton. We mapped the transcriptome of osteocytes from different skeletal sites, across age and sexes in mice to reveal genes and molecular programs that control this complex cellular-network. We define an osteocyte transcriptome signature of 1239 genes that distinguishes osteocytes from other cells. 77% have no previously known role in the skeleton and are enriched for genes regulating neuronal network formation, suggesting this program is important in osteocyte communication. We evaluated 19 skeletal parameters in 733 knockout mouse lines and reveal 26 osteocyte transcriptome signature genes that control bone structure and function. We showed osteocyte transcriptome signature genes are enriched for human orthologs that cause monogenic skeletal disorders (P=2.4x10-22) and are associated with the polygenic diseases osteoporosis (P=1.8x10-13) and osteoarthritis (P=1.6x10-7). Thus, we reveal the molecular landscape that regulates osteocyte network formation and function and establish the importance of osteocytes in human skeletal disease.

systems biology↗

bioRxiv2019

Decoding the genomic basis of osteoarthritis

Osteoarthritis causes pain and functional disability for a quarter of a billion people worldwide, with no disease-stratifying tools nor modifying therapy. Here, we use primary cartilage and synovium from osteoarthritis patients to construct a molecular quantitative trait locus map of gene expression and protein abundance. By integrating data across omics levels, we identify likely effector genes for osteoarthritis-associated genetic signals. We detect pronounced molecular differences between macroscopically intact and highly degenerated cartilage. We identify molecularly-defined patient subgroups that correlate with clinical characteristics, stratifying patients on the basis of their molecular profile. We construct and validate a 7-gene classifier that reproducibly distinguishes between these disease subtypes, and identify potentially actionable compounds for disease modification and drug repurposing.

genomics↗

bioRxiv2019

Accelerating functional gene discovery in osteoarthritis

Osteoarthritis causes debilitating pain and disability, resulting in a huge socioeconomic burden, yet no drugs are available that prevent disease onset or progression. Here, we develop, validate and use rapid-throughput imaging techniques to identify abnormal joint phenotypes in unselected mutant mice generated by the International Knockout Mouse Consortium. We identify 14 genes with functional involvement in osteoarthritis pathogenesis, including the homeobox gene Pitx1, and functionally characterize 6 candidate human osteoarthritis genes in mouse models. We demonstrate sensitivity of the methods by identifying age-related degenerative joint damage in wild-type mice. Finally, we generate mutant mice with an osteoarthritis-associated polymorphism in the Dio2 gene by Crispr/Cas9 genome editing and demonstrate a protective role in disease onset with public health implications. This expanding resource of unselected mutant mice will transform the field by accelerating functional gene discovery in osteoarthritis and offering unanticipated drug discovery opportunities for this common and incapacitating chronic disease.

genetics↗

bioRxiv2019

Human and mouse essentiality screens as a resource for disease gene discovery

Although genomic sequencing has been transformative in the study of rare genetic diseases, identifying causal variants remains a considerable challenge that can be addressed in part by new gene-specific knowledge. Here, we integrate measures of how essential a gene is to supporting life, as inferred from the comprehensive viability and phenotyping screens performed on knockout mice by the International Mouse Phenotyping Consortium and from human cell line essentiality screens. We propose a novel, cross-species gene classification across the Full Spectrum of Intolerance to Loss-of-function (FUSIL) and demonstrate that genes in five mutually exclusive FUSIL categories have differing characteristics in the biological processes they regulate, tissue expression levels and human mutation rates. Most notably, Mendelian disease genes, particularly those associated with developmental disorders, are highly overrepresented in the developmental lethal category, representing genes not essential for cell survival but required for organism development. Exploiting this finding, we have screened developmental disorder cases from three independent disease sequencing consortia and identified potentially pathogenic, de novo variants shared in different patients for several developmental lethal genes that have not previously been associated with rare disease. We therefore propose FUSIL as an efficient resource for disease gene discovery.

genomics↗