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Baer L, Barthelson K, Postlethwait JH, Adelson DL, Pederson SM, Lardelli M. Differential allelic representation (DAR) identifies candidate eQTLs and improves transcriptome analysis. PLoS Comput Biol 2024; 20:e1011868. [PMID: 38346074 PMCID: PMC10890730 DOI: 10.1371/journal.pcbi.1011868] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 02/23/2024] [Accepted: 01/29/2024] [Indexed: 02/25/2024] Open
Abstract
In comparisons between mutant and wild-type genotypes, transcriptome analysis can reveal the direct impacts of a mutation, together with the homeostatic responses of the biological system. Recent studies have highlighted that, when the effects of homozygosity for recessive mutations are studied in non-isogenic backgrounds, genes located proximal to the mutation on the same chromosome often appear over-represented among those genes identified as differentially expressed (DE). One hypothesis suggests that DE genes chromosomally linked to a mutation may not reflect functional responses to the mutation but, instead, result from an unequal distribution of expression quantitative trait loci (eQTLs) between sample groups of mutant or wild-type genotypes. This is problematic because eQTL expression differences are difficult to distinguish from genes that are DE due to functional responses to a mutation. Here we show that chromosomally co-located differentially expressed genes (CC-DEGs) are also observed in analyses of dominant mutations in heterozygotes. We define a method and a metric to quantify, in RNA-sequencing data, localised differential allelic representation (DAR) between those sample groups subjected to differential expression 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-based approaches. Advantageously, this improved ability to identify probable eQTLs also reveals examples of CC-DEGs that are likely to be functionally related to a mutant phenotype. This supports a long-standing prediction that selection for advantageous linkage disequilibrium influences chromosome evolution. 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. Our method for DAR analysis requires only RNA-sequencing data, facilitating its application across new and existing datasets.
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Affiliation(s)
- Lachlan Baer
- School of Biological Sciences, University of Adelaide, Adelaide, South Australia, Australia
| | - Karissa Barthelson
- School of Biological Sciences, University of Adelaide, Adelaide, South Australia, Australia
- Childhood Dementia Research Group, College of Medicine and Public Health, Flinders Health and Medical Research Institute, Flinders University, Bedford Park, South Australia, Australia
| | - John H. Postlethwait
- Institute of Neuroscience, University of Oregon, Eugene, Oregon, United States of America
| | - David L. Adelson
- School of Biological Sciences, University of Adelaide, Adelaide, South Australia, Australia
| | - Stephen M. Pederson
- Black Ochre Data Labs, Indigenous Genomics, Telethon Kids Institute, Adelaide, South Australia, Australia
- Dame Roma Mitchell Cancer Research Laboratories, Adelaide Medical School, University of Adelaide, Adelaide, South Australia, Australia
- John Curtin School of Medical Research, Australian National University, Canberra, Australian Capital Territory, Australia
| | - Michael Lardelli
- School of Biological Sciences, University of Adelaide, Adelaide, South Australia, Australia
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Lardelli M, Baer L, Hin N, Allen A, Pederson SM, Barthelson K. The Use of Zebrafish in Transcriptome Analysis of the Early Effects of Mutations Causing Early Onset Familial Alzheimer's Disease and Other Inherited Neurodegenerative Conditions. J Alzheimers Dis 2024; 99:S367-S381. [PMID: 37742650 DOI: 10.3233/jad-230522] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
The degree to which non-human animals can be used to model Alzheimer's disease is a contentious issue, particularly as there is still widespread disagreement regarding the pathogenesis of this neurodegenerative dementia. The currently popular transgenic models are based on artificial expression of genes mutated in early onset forms of familial Alzheimer's disease (EOfAD). Uncertainty regarding the veracity of these models led us to focus on heterozygous, single mutations of endogenous genes (knock-in models) as these most closely resemble the genetic state of humans with EOfAD, and so incorporate the fewest assumptions regarding pathological mechanism. We have generated a number of lines of zebrafish bearing EOfAD-like and non-EOfAD-like mutations in genes equivalent to human PSEN1, PSEN2, and SORL1. To analyze the young adult brain transcriptomes of these mutants, we exploited the ability of zebrafish to produce very large families of simultaneous siblings composed of a variety of genotypes and raised in a uniform environment. This "intra-family" analysis strategy greatly reduced genetic and environmental "noise" thereby allowing detection of subtle changes in gene sets after bulk RNA sequencing of entire brains. Changes to oxidative phosphorylation were predicted for all EOfAD-like mutations in the three genes studied. Here we describe some of the analytical lessons learned in our program combining zebrafish genome editing with transcriptomics to understand the molecular pathologies of neurodegenerative disease.
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Affiliation(s)
- Michael Lardelli
- Alzheimer's Disease Genetics Laboratory, The University of Adelaide, Adelaide, SA, Australia
| | - Lachlan Baer
- Alzheimer's Disease Genetics Laboratory, The University of Adelaide, Adelaide, SA, Australia
| | - Nhi Hin
- Alkahest Inc., San Carlos, CA, USA
| | - Angel Allen
- Alzheimer's Disease Genetics Laboratory, The University of Adelaide, Adelaide, SA, Australia
| | - Stephen Martin Pederson
- Black Ochre Data Labs, Indigenous Genomics, Telethon Kinds Institute, Adelaide, SA, Australia
- John Curtin School of Medical Research, Australian National University, Canberra, ACT, Australia
| | - Karissa Barthelson
- Alzheimer's Disease Genetics Laboratory, The University of Adelaide, Adelaide, SA, Australia
- Childhood Dementia Research Group, College of Medicine and Public Health, Flinders Health and Medical Research Institute, Flinders University, Bedford Park, SA, Australia
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Baer L, Barthelson K, Postlethwait J, Adelson D, Pederson S, Lardelli M. Differential allelic representation (DAR) identifies candidate eQTLs and improves transcriptome analysis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.02.530865. [PMID: 36945478 PMCID: PMC10028786 DOI: 10.1101/2023.03.02.530865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/08/2023]
Abstract
In comparisons between mutant and wild-type genotypes, transcriptome analysis can reveal the direct impacts of a mutation, together with 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 a mutation often appear over-represented among differentially expressed (DE) genes. One hypothesis suggests that DE genes chromosomally linked to a mutation may not reflect true biological responses to the mutation but, instead, result from differences in representation of expression quantitative trait loci (eQTLs) between sample groups selected on the basis of mutant or wild-type genotype. This is problematic when inclusion of spurious DE genes in a functional enrichment study results in incorrect inferences of mutation effect. Here we show that chromosomally 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-sequencing data, localised differential allelic representation (DAR) between groups of samples subject to differential expression 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 that are likely to be functionally related to a mutant phenotype. This supports a long-standing prediction that selection for advantageous linkage disequilibrium influences chromosome evolution. 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 DAR metric provides a solid foundation for addressing the eQTL issue in new and existing datasets because it relies solely on RNA-sequencing data.
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Affiliation(s)
- Lachlan Baer
- School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia
| | - Karissa Barthelson
- School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia
- Childhood Dementia Research Group, College of Medicine and Public Health, Flinders Health and Medical Research Institute, Flinders University, Bedford Park, SA, Australia
| | | | - David Adelson
- School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia
| | - Stephen Pederson
- Black Ochre Data Labs, Indigenous Genomics, Telethon Kids Institute, Adelaide, SA, Australia
- Dame Roma Mitchell Cancer Research Laboratories, Adelaide Medical School, University of Adelaide, Adelaide, SA, Australia
- John Curtin School of Medical Research, Australian National University, Canberra, ACT, Australia
| | - Michael Lardelli
- School of Biological Sciences, University of Adelaide, Adelaide, SA, Australia
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Barthelson K, Newman M, Lardelli M. Brain transcriptomes of zebrafish and mouse Alzheimer's disease knock-in models imply early disrupted energy metabolism. Dis Model Mech 2021; 15:273566. [PMID: 34842276 PMCID: PMC8807579 DOI: 10.1242/dmm.049187] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2021] [Accepted: 11/17/2021] [Indexed: 11/21/2022] Open
Abstract
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 11 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, which produces most of the energy of the brain. 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 the initiation of the pathological processes leading to both early and late onset forms of Alzheimer's disease, and illustrate the utility of zebrafish and knock-in single EOFAD mutation models for understanding the causes of this disease. Summary: Young adult zebrafish mutants and a mouse model of a genetic variant promoting early- and late-onset Alzheimer's disease, respectively, share changes in brain gene expression, indicating disturbance of oxidative phosphorylation.
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Affiliation(s)
- Karissa Barthelson
- Alzheimer's Disease Genetics Laboratory, School of Biological Sciences, University of Adelaide, North Terrace, Adelaide, SA 5005, Australia
| | - Morgan Newman
- Alzheimer's Disease Genetics Laboratory, School of Biological Sciences, University of Adelaide, North Terrace, Adelaide, SA 5005, Australia
| | - Michael Lardelli
- Alzheimer's Disease Genetics Laboratory, School of Biological Sciences, University of Adelaide, North Terrace, Adelaide, SA 5005, Australia
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Barthelson K, Dong Y, Newman M, Lardelli M. 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. J Alzheimers Dis 2021; 82:327-347. [PMID: 34024832 DOI: 10.3233/jad-210128] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND The most common cause of early-onset familial Alzheimer's disease (EOfAD) is mutations in PRESENILIN 1 (PSEN1) allowing production of mRNAs encoding full-length, but mutant, proteins. In contrast, a single known frameshift mutation in PSEN1 causes familial acne inversa (fAI) without EOfAD. The molecular consequences of heterozygosity for these mutation types, and how they cause completely different diseases, remains largely unexplored. OBJECTIVE To analyze brain transcriptomes of young adult zebrafish to identify similarities and differences in the effects of heterozygosity for psen1 mutations causing EOfAD or fAI. METHODS RNA sequencing was performed on mRNA isolated from the brains of a single family of 6-month-old zebrafish siblings either wild type or possessing a single, heterozygous EOfAD-like or fAI-like mutation in their endogenous psen1 gene. RESULTS Both mutations downregulate genes encoding ribosomal subunits, and upregulate genes involved in inflammation. Genes involved in energy metabolism appeared significantly affected only by the EOfAD-like mutation, while genes involved in Notch, Wnt and neurotrophin signaling pathways appeared significantly affected only by the fAI-like mutation. However, investigation of direct transcriptional targets of Notch signaling revealed possible increases in γ-secretase activity due to heterozygosity for either psen1 mutation. Transcriptional adaptation due to the fAI-like frameshift mutation was evident. CONCLUSION We observed both similar and contrasting effects on brain transcriptomes of the heterozygous EOfAD-like and fAI-like mutations. The contrasting effects may illuminate how these mutation types cause distinct diseases.
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Affiliation(s)
- Karissa Barthelson
- Alzheimer's Disease Genetics Laboratory, School of Biological Sciences, University of Adelaide, North Terrace, Adelaide, SA, Australia
| | - Yang Dong
- Alzheimer's Disease Genetics Laboratory, School of Biological Sciences, University of Adelaide, North Terrace, Adelaide, SA, Australia
| | - Morgan Newman
- Alzheimer's Disease Genetics Laboratory, School of Biological Sciences, University of Adelaide, North Terrace, Adelaide, SA, Australia
| | - Michael Lardelli
- Alzheimer's Disease Genetics Laboratory, School of Biological Sciences, University of Adelaide, North Terrace, Adelaide, SA, Australia
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Barthelson K, Pederson SM, Newman M, Jiang H, Lardelli M. In-Frame and Frameshift Mutations in Zebrafish Presenilin 2 Affect Different Cellular Functions in Young Adult Brains. J Alzheimers Dis Rep 2021; 5:395-404. [PMID: 34189411 PMCID: PMC8203281 DOI: 10.3233/adr-200279] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/30/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Mutations in PRESENILIN 2 (PSEN2) cause early onset familial Alzheimer's disease (EOfAD) but their mode of action remains elusive. One consistent observation for all PRESENILIN gene mutations causing EOfAD is that a transcript is produced with a reading frame terminated by the normal stop codon-the "reading frame preservation rule". Mutations that do not obey this rule do not cause the disease. The reasons for this are debated. OBJECTIVE To predict cellular functions affected by heterozygosity for a frameshift, or a reading frame-preserving mutation in zebrafish psen2 using bioinformatic techniques. METHODS A frameshift mutation (psen2 N140fs ) and a reading frame-preserving (in-frame) mutation (psen2 T141 _ L142delinsMISLISV ) were previously isolated during genome editing directed at the N140 codon of zebrafish psen2 (equivalent to N141 of human PSEN2). We mated a pair of fish heterozygous for each mutation to generate a family of siblings including wild type and heterozygous mutant genotypes. Transcriptomes from young adult (6 months) brains of these genotypes were analyzed. RESULTS The in-frame mutation uniquely caused subtle, but statistically significant, changes to expression of genes involved in oxidative phosphorylation, long-term potentiation and the cell cycle. The frameshift mutation uniquely affected genes involved in Notch and MAPK signaling, extracellular matrix receptor interactions and focal adhesion. Both mutations affected ribosomal protein gene expression but in opposite directions. CONCLUSION A frameshift and an in-frame mutation at the same position in zebrafish psen2 cause discrete effects. Changes in oxidative phosphorylation, long-term potentiation and the cell cycle may promote EOfAD pathogenesis in humans.
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Affiliation(s)
- Karissa Barthelson
- Alzheimer’s Disease Genetics Laboratory, School of Biological Sciences, University of Adelaide, North Terrace, Adelaide, SA, Australia
| | - Stephen Martin Pederson
- Bioinformatics Hub, School of Biological Sciences, University of Adelaide, North Terrace, Adelaide, SA, Australia
| | - Morgan Newman
- Alzheimer’s Disease Genetics Laboratory, School of Biological Sciences, University of Adelaide, North Terrace, Adelaide, SA, Australia
| | - Haowei Jiang
- School of Pharmacy, Shanghai Jiao Tong University, Shanghai, China
| | - Michael Lardelli
- Alzheimer’s Disease Genetics Laboratory, School of Biological Sciences, University of Adelaide, North Terrace, Adelaide, SA, Australia
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