Zebrafish Chromosome 14 Gene Differential Expression in the fmr1 h u2787 Model of Fragile X Syndrome

Loss of FMRP affects ovarian development and behaviour through multiple pathways in a zebrafish model of fragile X syndrome

Fragile X syndrome (FXS) is an inherited neurodevelopmental disorder and the leading genetic cause of autism spectrum disorders. FXS is caused by loss of function mutations in Fragile X mental retardation protein (FMRP), an RNA binding protein that is known to regulate translation of its target mRNAs, predominantly in the brain and gonads. The molecular mechanisms connecting FMRP function to neurodevelopmental phenotypes are well understood. However, neither the full extent of reproductive phenotypes, nor the underlying molecular mechanisms have been as yet determined. Here, we developed new fmr1 knockout zebrafish lines and show that they mimic key aspects of FXS neuronal phenotypes across both larval and adult stages. Results from the fmr1 knockout females also showed that altered gene expression in the brain, via the neuroendocrine pathway contribute to distinct abnormal phenotypes during ovarian development and oocyte maturation. We identified at least three mechanisms underpinning these defects, including altered neuroendocrine signaling in sexually mature females resulting in accelerated ovarian development, altered expression of germ cell and meiosis promoting genes at various stages during oocyte maturation, and finally a strong mitochondrial impairment in late stage oocytes from knockout females. Our findings have implications beyond FXS in the study of reproductive function and female infertility. Dissection of the translation control pathways during ovarian development using models like the knockout lines reported here may reveal novel approaches and targets for fertility treatments.

Cyfip2 controls the acoustic startle threshold through FMRP, actin polymerization, and GABAB receptor function

Animals process a constant stream of sensory input, and to survive they must detect and respond to dangerous stimuli while ignoring innocuous or irrelevant ones. Behavioral responses are elicited when certain properties of a stimulus such as its intensity or size reach a critical value, and such behavioral thresholds can be a simple and effective mechanism to filter sensory information. For example, the acoustic startle response is a conserved and stereotyped defensive behavior induced by sudden loud sounds, but dysregulation of the threshold to initiate this behavior can result in startle hypersensitivity that is associated with sensory processing disorders including schizophrenia and autism. Through a previous forward genetic screen for regulators of the startle threshold a nonsense mutation in Cytoplasmic Fragile X Messenger Ribonucleoprotein (FMRP)-interacting protein 2 (cyfip2) was found that causes startle hypersensitivity in zebrafish larvae, but the molecular mechanisms by which Cyfip2 establishes the acoustic startle threshold are unknown. Here we used conditional transgenic rescue and CRISPR/Cas9 to determine that Cyfip2 acts though both Rac1 and FMRP pathways, but not the closely related FXR1 or FXR2, to establish the acoustic startle threshold during early neurodevelopment. To identify proteins and pathways that may be downstream effectors of Rac1 and FMRP, we performed a candidate-based drug screen that indicated that Cyfip2 can also act acutely to maintain the startle threshold branched actin polymerization and N-methyl D-aspartate receptors (NMDARs). To complement this approach, we used unbiased discovery proteomics to determine that loss of Cyfip2 alters cytoskeletal and extracellular matrix components while also disrupting oxidative phosphorylation and GABA receptor signaling. Finally, we functionally validated our proteomics findings by showing that activating GABAB receptors, which like NMDARs are also FMRP targets, restores normal startle sensitivity in cyfip2 mutants. Together, these data reveal multiple mechanisms by which Cyfip2 regulates excitatory/inhibitory balance in the startle circuit to control the processing of acoustic information.

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

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.

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

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.