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Bevan, M.

Publications and source records attributed to Bevan, M..

3 recordsLinked to original sources

Haploinsufficiency of lysosomal enzyme genes in Alzheimers disease

There is growing evidence suggesting that the lysosome or lysosome dysfunction is associated with Alzheimers disease (AD). Pathway analysis of post mortem brain-derived proteomic data from AD patients shows that the lysosomal system is perturbed relative to similarly aged unaffected controls. However, it is unclear if these changes contributed to the pathogenesis or are a response to the disease. Consistent with the hypothesis that lysosome dysfunction contributes to AD pathogenesis, whole genome sequencing data indicate that heterozygous pathogenic mutations and predicted protein-damaging variants in multiple lysosomal enzyme genes are enriched in AD patients compared to matched controls. Heterozygous loss-of-function mutations in the palmitoyl protein thioesterase-1 (PPT1), -L-iduronidase (IDUA), {beta}-glucuronidase (GUSB), N-acetylglucosaminidase (NAGLU), and galactocerebrosidase (GALC) genes have a gene-dosage effect on A{beta}40 levels in brain interstitial fluid in C57BL/6 mice and significantly increase A{beta} plaque formation in the 5xFAD mouse model of AD, thus providing in vivo validation of the human genetic data. A more detailed analysis of PPT1 heterozygosity in 18-month-old mice revealed changes in -, {beta}-, and {gamma}-secretases that favor an amyloidogenic pathway. Proteomic changes in brain tissue from aged PPT1 heterozygous sheep are consistent with both the mouse data and the potential activation of AD pathways. Finally, CNS-directed, AAV-mediated gene therapy significantly decreased A{beta} plaques, increased life span, and improved behavioral performance in 5xFAD/PPT1+/- mice. Collectively, these data strongly suggest that heterozygosity of multiple lysosomal enzyme genes represent risk factors for AD and may identify precise therapeutic targets for a subset of genetically-defined AD patients. Significance StatementLysosomes play a role in the degradation of aggregation-prone proteins such as amyloid {beta} (A{beta}). Homozygous lysosomal enzyme gene defects result in fatal pediatric lysosomal storage diseases and, historically, carriers were considered normal. However, a human genetic analysis identified deleterious heterozygous variants in multiple lysosomal enzyme genes that are enriched in Alzheimers disease (AD) patients. Those findings were validated in vivo by demonstrating that heterozygous loss-of-function (LoF) mutations in five different lysosomal enzyme genes affect A{beta} processing and exacerbate A{beta} plaque formation. CNS-directed gene therapy ameliorated the effects of a heterozygous LoF mutation in one of those genes in a mouse model of AD. These findings provide insights into the role of lysosomes in AD and have important therapeutic implications.

neuroscience↗

Epigenomic variation across a polyploid wheat diversity collection

Wheat has been domesticated into a large number of agricultural environments and has a remarkable ability to adapt to diverse environments. To understand this process, we survey genotype, repeat content and DNA methylation across a bread wheat landrace collection representing global genetic diversity. We identify independent variation in methylation, genotype and transposon copy number. We show that these, so far unexploited, sources of variation have had a massive impact on the wheat genome and that ancestral methylation states become preferentially hard coded as SNPs via 5-methylcytosine deamination. These mechanisms also drive local adaption, impacting important traits such as heading date and salt tolerance. Methylation and transposon diversity could therefore be used alongside single nucleotide polymorphism (SNP) based markers for breeding.

genomics↗

CropQuant: An automated and scalable field phenotyping platform for crop monitoring and trait measurements to facilitate breeding and digital agriculture

Automated phenotyping technologies are capable of providing continuous and precise measurements of traits that are key to todays crop research, breeding and agronomic practices. In additional to monitoring developmental changes, high-frequency and high-precision phenotypic analysis can enable both accurate delineation of the genotype-to-phenotype pathway and the identification of genetic variation influencing environmental adaptation and yield potential. Here, we present an automated and scalable field phenotyping platform called CropQuant, designed for easy and cost-effective deployment in different environments. To manage infield experiments and crop-climate data collection, we have also developed a web-based control system called CropMonitor to provide a unified graphical user interface (GUI) to enable realtime interactions between users and their experiments. Furthermore, we established a high-throughput trait analysis pipeline for phenotypic analyses so that lightweight machine-learning modelling can be executed on CropQuant workstations to study the dynamic interactions between genotypes (G), phenotypes (P), and environmental factors (E). We have used these technologies since 2015 and reported results generated in 2015 and 2016 field experiments, including developmental profiles of five wheat genotypes, performance-related traits analyses, and new biological insights emerged from the application of the CropQuant platform.

plant biology↗