PRESENILIN 1 Mutations Causing Early-Onset Familial Alzheimer’s Disease or Familial Acne Inversa Differ in Their Effects on Genes Facilitating Energy Metabolism and Signal Transduction

Disease Models &Amp; Mechanisms

Newman

Lardelli

2022

Self Cite

Energy production is the most fundamentally important cellular activity supporting all other functions, particularly in highly active organs such as brains, Here we summarise transcriptome analyses of young adult (pre-disease) brains from a collection of eleven early-onset familial Alzheimer's disease (EOfAD)-like and non-EOfAD-like mutations in three zebrafish genes. The one cellular activity consistently predicted as affected by only the EOfAD-like mutations is oxidative phosphorylation that produces most of the brain's energy. All the mutations were predicted to affect protein synthesis. We extended our analysis to knock-in mouse models of APOE alleles and found the same effect for the late onset Alzheimer's disease risk allele ε4. Our results support a common molecular basis for initiation of the pathological processes leading to both early and late onset forms of Alzheimer's disease and illustrate the utility of zebrafish and of knock-in, single EOfAD mutation models for understanding the causes of this disease.

Section: Resultssupporting

confidence: 58%

Section: Discussionmentioning

confidence: 67%

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Brain transcriptomes of zebrafish and mouse Alzheimer's disease knock-in models imply early disrupted energy metabolism

Disease Models &Amp; Mechanisms

Newman

Lardelli

2022

Self Cite

Comparative analysis of Alzheimer’s disease knock-in model brain transcriptomes implies changes to energy metabolism as a causative pathogenic stress

Newman

Lardelli

2021

Preprint

Energy production is the most fundamentally important cellular activity supporting all other functions, particularly in highly active organs such as brains, Here we summarise transcriptome analyses of young adult (pre-disease) brains from a collection of eleven early onset familial Alzheimer's disease (EOfAD)-like and non-EOfAD-like mutations in three zebrafish genes. The one cellular activity consistently predicted as affected by only the EOfAD-like mutations is oxidative phosphorylation that produces most of the brain's energy. All the mutations were predicted to affect protein synthesis. We extended our analysis to knock-in mouse models of APOE alleles and found the same effect for the late onset Alzheimer's disease risk allele E4. Our results support a common molecular basis for initiation of the pathological processes leading to both early and late onset forms of Alzheimer's disease and illustrate the utility of both zebrafish and knock-in, single EOfAD mutation models for understanding the causes of this disease.

Differential allelic representation (DAR) identifies candidate eQTLs and improves transcriptome analysis

Baer

Postlethwait

et al. 2023

Preprint

Self Cite

RNA-sequencing analysis excels in its ability to infer transcriptomic differences between discrete genetic states. This advantage is often leveraged to explore the consequences of single mutations causing disease, where prior knowledge of expected outcomes may not be established. Successful interpretation of such RNA-seq studies reveals the direct impacts of the mutation, as well as the homeostatic responses of the biological system. Recent studies have highlighted that, when homozygous mutations are studied in non-isogenic backgrounds, genes from the same chromosome as the mutation tend to be over-represented among differentially expressed (DE) genes. One hypothesis suggests that DE genes chromosomally linked to the mutation may not be true biological responses to the disruption of the mutation but, instead, result from differences in the representation of expression quantitative trait loci (eQTLs) that differ between the sample groups being compared. This can be problematic since including spurious DE genes in a functional enrichment study may result in incorrect inferences of mutation effect. Here we show thatchromosomally co-located differentially expressed genes(CC-DEGs) can also be observed in analyses of dominant mutations in heterozygotes. We define a method and a metric to quantify, in RNA-seq data, localised differential allelic representation (DAR) between groups of samples subject to DE analysis. We show how the DAR metric can predict regions prone to eQTL-driven differential expression, and how it can improve functional enrichment analyses through gene exclusion or weighting of gene-level rankings. Advantageously, this improved ability to identify probable eQTLs also reveals examples of CC-DEGs thatarelikely to be functionally related to a mutant phenotype. This situation was predicted by R.A. Fisher in 1930 as due to selection for advantageous linkage disequilibrium after chromosomal rearrangements. By comparing the genomes of zebrafish (Danio rerio) and medaka (Oryzias latipes), a teleost with a conserved ancestral karyotype, we find possible examples of chromosomal aggregation of CC-DEGs during evolution of the zebrafish lineage. The ability to identify and exclude eQTL artefacts from true transcriptomic responses to mutation provides exciting opportunities for developing new approaches for analysing RNA-seq data. Our DAR metric provides a solid foundation for addressing the eQTL issue in new and existing datasets because it relies solely on RNA-seq data, which will thus improve our understanding of the mechanisms of disease-causing mutations.