Quantitative investigations of FXN transcription and epigenetic modifications, including histone acetylation and methylation, in FRDA human and mouse tissues

This thesis was submitted for the degree of Master of Philosophy and awarded by Brunel University.Friedreich ataxia (FRDA) is an autosomal recessive neurodegenerative disorder characterized by progressive gait and, limb ataxia, cardiomayopathy, diabetes mellitus, optic atrophy and hearing loss. It is most often caused by homozygous expanded (GAA)∙(TTC)n repeats within intron 1 of the FXN gene, resulting in severely reduced levels of frataxin protein. The exact mechanisms of how the expanded (GAA)∙(TTC)n repeats reduce FXN transcription are not fully understood. However, many studies have suggested that the expanded repeat may induce epigenetic modifications that cause the FXN transcription inhibition to occur. In the past few years, epigenetic modifications have been given considerable attention as an important mechanism that is contributing to the aetiology of FRDA. This thesis investigated histone acetylation and methylation in three different regions of the FXN gene: FXN promoter, upstream GAA and downstream GAA, using chromatin immunoprecipitation (ChIP) and quantitative reverse transcriptase PCR (qRT-PCR) of the human and transgenic mouse brain tissues. Furthermore, the frataxin mRNA levels were investigated in autopsied brain tissues from an FRDA patient and FXN transgenic mouse brain, heart and liver tissues. In addition, a preliminary study that investigated the effect of a histone deacetylase inhibitor (HDACi) on FXN transcription and histone modifications (acetylation) of transgenic mouse brain, heart and liver tissues was conducted. Results showed an overall significant decrease in the acetylation pattern of H3K9ac and H4K16ac residues in all three regions within FXN gene. Moreover, a significant increase in the di- and trimethylation pattern of the H3K9me2 and the H3K9me3 residues was identified in all three regions of the FXN gene. The results were comparable between the FRDA patient and transgenic mouse (YG8, YG22) brain tissues. The FXN mRNA levels showed a significant decrease in all transgenic mouse brain, heart and liver tissues, which is comparable with the FXN mRNA level of the FRDA patient brain and heart tissues.Results for the preliminary HDACi study showed an approximate 20-30 % increase in the FXN mRNA level in different transgenic mouse tissues after 3 days intake at 150mg/kg dose. In addition, there was an increase in the acetylation pattern of the H3K9ac and the H4K12ac in the HDACi treated transgenic mouse brain tissues. These studies will aid the understanding of FXN epigenetic modifications and their contribution to FRDA disease; this is an exciting challenge leading to a new effective FRDA therapeutic pathway

Comparison Between Expression Microarrays and RNA-Sequencing Using UKBEC Dataset Identified a trans-eQTL Associated with MPZ Gene in Substantia Nigra

In recent years, the advantages of RNA-sequencing (RNA-Seq) have made it the platform of choice for measuring gene expression over traditional microarrays. However, RNA-Seq comes with bioinformatical challenges and higher computational costs. Therefore, this study set out to assess whether the increased depth of transcriptomic information facilitated by RNA-Seq is worth the increased computation over microarrays, specifically at three levels: absolute expression levels, differentially expressed genes identification, and expression QTL (eQTL) mapping in regions of the human brain. Using the United Kingdom Brain Expression Consortium (UKBEC) dataset, there is high agreement of gene expression levels measured by microarrays and RNA-seq when quantifying absolute expression levels and when identifying differentially expressed genes. These findings suggest that depending on the aims of a study, the relative ease of working with microarray data may outweigh the computational time and costs of RNA-Seq pipelines. On the other, there was low agreement when mapping eQTLs. However, a number of eQTLs associated with genes that play important roles in the brain were found in both platforms. For example, a trans-eQTL was mapped that is associated with the MPZ gene in the substantia nigra. These eQTLs that we have highlighted are extremely promising candidates that merit further investigation

Quality control parameters on a large dataset of regionally dissected human control brains for whole genome expression studies

We are building an open-access database of regional human brain expression designed to allow the genome-wide assessment of genetic variability on expression. Array and RNA sequencing technologies make assessment of genome-wide expression possible. Human brain tissue is a challenging source for this work because it can only be obtained several and variable hours post-mortem and after varying agonal states. These variables alter RNA integrity in a complex manner. In this report, we assess the effect of post-mortem delay, agonal state and age on gene expression, and the utility of pH and RNA integrity number as predictors of gene expression as measured on 1266 Affymetrix Exon Arrays. We assessed the accuracy of the array data using QuantiGene, as an independent non-PCR-based method. These quality control parameters will allow database users to assess data accuracy. We report that within the parameters of this study post-mortem delay, agonal state and age have little impact on array quality, array data are robust to variable RNA integrity, and brain pH has only a small effect on array performance. QuantiGene gave very similar expression profiles as array data. This study is the first step in our initiative to make human, regional brain expression freely available

Investigating the utility of human embryonic stem cell-derived neurons to model ageing and neurodegenerative disease using whole-genome gene expression and splicing analysis

A major goal in regenerative medicine is the predictable manipulation of human embryonic stem cells (hESCs) to defined cell fates that faithfully represent their somatic counterparts. Directed differentiation of hESCs into neuronal populations has galvanized much interest into their potential application in modelling neurodegenerative disease. However, neurodegenerative diseases are age-related, and therefore establishing the maturational comparability of hESC-derived neural derivatives is critical to generating accurate in vitro model systems. We address this issue by comparing genome-wide, exon-specific expression analyses of pluripotent hESCs, multipotent neural precursor cells and a terminally differentiated enriched neuronal population to expression data from post-mortem foetal and adult human brain samples. We show that hESC-derived neuronal cultures (using a midbrain differentiation protocol as a prototypic example of lineage restriction), while successful in generating physiologically functional neurons, are closer to foetal than adult human brain in terms of molecular maturation. These findings suggest that developmental stage has a more dominant influence on the cellular transcriptome than regional identity. In addition, we demonstrate that developmentally regulated gene splicing is common, and potentially a more sensitive measure of maturational state than gene expression profiling alone. In summary, this study highlights the value of genomic indices in refining and validating optimal cell populations appropriate for modelling ageing and neurodegeneration

Genetic evidence for a pathogenic role for the vitamin D3 metabolizing enzyme CYP24A1 in multiple sclerosis

Background: Multiple sclerosis (MS) is a common disease of the central nervous system and a major cause of disability amongst young adults. Genome-wide association studies have identified many novel susceptibility loci including rs2248359. We hypothesized that genotypes of this locus could increase the risk of MS by regulating expression of neighboring gene, CYP24A1 which encodes the enzyme responsible for initiating degradation of 1,25-dihydroxyvitamin D3. Methods: We investigated this hypothesis using paired gene expression and genotyping data from three independent datasets of neurologically healthy adults of European descent. The UK Brain Expression Consortium (UKBEC) consists of post-mortem samples across 10 brain regions originating from 134 individuals (1231 samples total). The North American Brain Expression Consortium (NABEC) consists of cerebellum and frontal cortex samples from 304 individuals (605 samples total). The brain dataset from Heinzen and colleagues consists of prefrontal cortex samples from 93 individuals. Additionally, we used gene network analysis to analyze UKBEC expression data to understand CYP24A1 function in human brain. Findings: The risk allele, rs2248359-C, is strongly associated with increased expression of CYP24A1 in frontal cortex (p-value=1.45×10−13), but not white matter. This association was replicated using data from NABEC (p-value=7.2×10−6) and Heinzen and colleagues (p-value=1.2×10−4). Network analysis shows a significant enrichment of terms related to immune response in eight out of the 10 brain regions. Interpretation: The known MS risk allele rs2248359-C increases CYP24A1 expression in human brain providing a genetic link between MS and vitamin D metabolism, and predicting that the physiologically active form of vitamin D3 is protective. Vitamin D3's involvement in MS may relate to its immunomodulatory functions in human brain. Finding: Medical Research Council UK; King Faisal Specialist Hospital and Research Centre, Saudi Arabia; Intramural Research Program of the National Institute on Aging, National Institutes of Health, USA

Regulatory sites for splicing in human basal ganglia are enriched for disease-relevant information

International Parkinson’s Disease Genomics Consortium (IPDGC), UK Brain Expression Consortium (UKBEC).Genome-wide association studies have generated an increasing number of common genetic variants associated with neurological and psychiatric disease risk. An improved understanding of the genetic control of gene expression in human brain is vital considering this is the likely modus operandum for many causal variants. However, human brain sampling complexities limit the explanatory power of brain-related expression quantitative trait loci (eQTL) and allele-specific expression (ASE) signals. We address this, using paired genomic and transcriptomic data from putamen and substantia nigra from 117 human brains, interrogating regulation at different RNA processing stages and uncovering novel transcripts. We identify disease-relevant regulatory loci, find that splicing eQTLs are enriched for regulatory information of neuron-specific genes, that ASEs provide cell-specific regulatory information with evidence for cellular specificity, and that incomplete annotation of the brain transcriptome limits interpretation of risk loci for neuropsychiatric disease. This resource of regulatory data is accessible through our web server, http://braineacv2.inf.um.es/.Mina Ryten, David Zhang, and Karishma D’Sa were supported by the UK Medical Research Council (MRC) through the award of Tenure-track Clinician Scientist Fellowship to Mina Ryten (MR/N008324/1). Sebastian Guelfi was supported by Alzheimer’s Research UK through the award of a PhD Fellowship (ARUK-PhD2014-16). Regina Reynolds was supported through the award of a Leonard Wolfson Doctoral Training Fellowship in Neurodegeneration

eQTL Catalogue 2023: New datasets, X chromosome QTLs, and improved detection and visualisation of transcript-level QTLs

The eQTL Catalogue is an open database of uniformly processed human molecular quantitative trait loci (QTLs). We are continuously updating the resource to further increase its utility for interpreting genetic associations with complex traits. Over the past two years, we have increased the number of uniformly processed studies from 21 to 31 and added X chromosome QTLs for 19 compatible studies. We have also implemented Leafcutter to directly identify splice-junction usage QTLs in all RNA sequencing datasets. Finally, to improve the interpretability of transcript-level QTLs, we have developed static QTL coverage plots that visualise the association between the genotype and average RNA sequencing read coverage in the region for all 1.7 million fine mapped associations. To illustrate the utility of these updates to the eQTL Catalogue, we performed colocalisation analysis between vitamin D levels in the UK Biobank and all molecular QTLs in the eQTL Catalogue. Although most GWAS loci colocalised both with eQTLs and transcript-level QTLs, we found that visual inspection could sometimes be used to distinguish primary splicing QTLs from those that appear to be secondary consequences of large-effect gene expression QTLs. While these visually confirmed primary splicing QTLs explain just 6/53 of the colocalising signals, they are significantly less pleiotropic than eQTLs and identify a prioritised causal gene in 4/6 cases

Increased brain expression of GPNMB is associated with genome wide significant risk for Parkinson's disease on chromosome 7p15.3

Genome wide association studies (GWAS) for Parkinson's disease (PD) have previously revealed a significant association with a locus on chromosome 7p15.3, initially designated as the glycoprotein non-metastatic melanoma protein B (GPNMB) locus. In this study, the functional consequences of this association on expression were explored in depth by integrating different expression quantitative trait locus (eQTL) datasets (Braineac, CAGEseq, GTEx, and Phenotype-Genotype Integrator (PheGenI)). Top risk SNP rs199347 eQTLs demonstrated increased expressions of GPNMB, KLHL7, and NUPL2 with the major allele (AA) in brain, with most significant eQTLs in cortical regions, followed by putamen. In addition, decreased expression of the antisense RNA KLHL7-AS1 was observed in GTEx. Furthermore, rs199347 is an eQTL with long non-coding RNA (AC005082.12) in human tissues other than brain. Interestingly, transcript-specific eQTLs in immune-related tissues (spleen and lymphoblastoid cells) for NUPL2 and KLHL7-AS1 were observed, which suggests a complex functional role of this eQTL in specific tissues, cell types at specific time points. Significantly increased expression of GPNMB linked to rs199347 was consistent across all datasets, and taken in combination with the risk SNP being located within the GPNMB gene, these results suggest that increased expression of GPNMB is the causative link explaining the association of this locus with PD. However, other transcript eQTLs and subsequent functional roles cannot be excluded. This highlights the importance of further investigations to understand the functional interactions between the coding genes, antisense, and non-coding RNA species considering the tissue and cell-type specificity to understand the underlying biological mechanisms in PD

Integration of GWAS SNPs and tissue specific expression profiling reveal discrete eQTLs for human traits in blood and brain

Our knowledge of the transcriptome has become much more complex since the days of the central dogma of molecular biology. We now know that splicing takes place to create potentially thousands of isoforms from a single gene, and we know that RNA does not always faithfully recapitulate DNA if RNA editing occurs. Collectively, these observations show that the transcriptome is amazingly rich with intricate regulatory mechanisms for overall gene expression, splicing, and RNA editing. Genetic variability can play a role in controlling gene expression, which can be identified by examining expression quantitative trait loci (eQTLs). eQTLs are genomic regions where genetic variants, including single nucleotide polymorphisms (SNPs) show a statistical association with expression of mRNA transcripts. In humans, many SNPs are also associated with disease, and have been identified using genome wide association studies (GWAS) but the biological effects of those SNPs are usually not known. If SNPs found in GWAS are also found in eQTLs, then one could hypothesize that expression levels may contribute to disease risk. Performing eQTL analysis with GWAS SNPs in both blood and brain, specifically the frontal cortex and the cerebellum, we found both shared and tissue unique eQTLS. The identification of tissue-unique eQTLs supports the argument that choice of tissue type is important in eQTL studies (Paper I). Aging is a complex process with the mechanisms underlying aging still being poorly defined. There is evidence that the transcriptome changes with age, and hence we used the brain dataset from our first paper as a discovery set, with an additional replication dataset, to investigate any aging-gene expression associations. We found evidence that many genes were associated with aging. We further found that there were more statically significant expression changes in the frontal cortex versus the cerebellum, indicating that brain regions may age at different rates. As the brain is a heterogeneous tissue including both neurons and non-neuronal cells, we used LCM to capture Purkinje cells as a representative neuronal type and repeated the age analysis. Looking at the discovery, replication and Purkinje cell datasets we found five genes with strong, replicated evidence of age-expression associations (Paper II). Being able to capture and quantify the depth of the transcriptome has been a lengthy process starting with methods that could only measure a single gene to genome-wide techniques such as microarray. A recently developed technology, RNA-Seq, shows promise in its ability to capture expression, splicing, and editing and with its broad dynamic range quantification is accurate and reliable. RNA-Seq is, however, data intensive and a great deal of computational expertise is required to fully utilize the strengths of this method. We aimed to create a small, well-controlled, experiment in order to test the performance of this relatively new technology in the brain. We chose embryonic versus adult cerebral cortex, as mice are genetically homogenous and there are many known differences in gene expression related to brain development that we could use as benchmarks for analysis testing. We found a large number of differences in total gene expression between embryonic and adult brain. Rigorous technical and biological validation illustrated the accuracy and dynamic range of RNA-Seq. We were also able to interrogate differences in exon usage in the same dataset. Finally we were able to identify and quantify both well-known and novel A-to-I edit sites. Overall this project helped us develop the tools needed to build usable pipelines for RNA-Seq data processing (Paper III). Our studies in the developing brain (Paper III) illustrated that RNA-Seq was a useful unbiased method for investigating RNA editing. To extend this further, we utilized a genetically modified mouse model to study the transcriptomic role of the RNA editing enzyme ADAR2. We found that ADAR2 was important for editing of the coding region of mRNA as a large proportion of RNA editing sites in coding regions had a statistically significant decrease in editing percentages in Adar2 -/-Gria2 R/R mice versus controls. However, despite indications in the literature that ADAR2 may also be involved in splicing and expression regulatory machinery we found no changes in gene expression or exon utilization in Adar2 -/-Gria2 R/R mice as compared to their littermate controls (Paper IV). In our final study, based on the methods developed in Papers III and IV, we revisited the idea of age related gene expression associations from Paper II. We used a subset of human frontal cortices for RNA sequencing. Interestingly we found more gene expression changes with aging compared to the previous data using microarrays in Paper II. When the significant gene lists were analysed for gene ontology enrichment, we found that there was a large number of downregulated genes involved in synaptic function while those that were upregulated had enrichment in immune function. This dataset illustrates that the aging brain may be predisposed to the processes found in neurodegenerative diseases (Paper V)

A comprehensive introduction to the genetic basis of non-syndromic hearing loss in the Saudi Arabian population

<p>Abstract</p> <p>Background</p> <p>Hearing loss is a clinically and genetically heterogeneous disorder. Mutations in the <it>DFNB1 </it>locus have been reported to be the most common cause of autosomal recessive non-syndromic hearing loss worldwide. Apart from <it>DFNB1</it>, many other loci and their underlying genes have also been identified and the basis of our study was to provide a comprehensive introduction to the delineation of the molecular basis of non-syndromic hearing loss in the Saudi Arabian population. This was performed by screening <it>DFNB1 </it>and to initiate prioritized linkage analysis or homozygosity mapping for a pilot number of families in which <it>DFNB1 </it>has been excluded.</p> <p>Methods</p> <p>Individuals from 130 families of Saudi Arabian tribal origin diagnosed with an autosomal recessive non-syndromic sensorineural hearing loss were screened for mutations at the <it>DFNB1 </it>locus by direct sequencing. If negative, genome wide linkage analysis or homozygosity mapping were performed using Affymetrix GeneChip^®Human Mapping 250K/6.0 Arrays to identify regions containing any known-deafness causing genes that were subsequently sequenced.</p> <p>Results</p> <p>Our results strongly indicate that <it>DFNB1 </it>only accounts for 3% of non-syndromic hearing loss in the Saudi Arabian population of ethnic ancestry. Prioritized linkage analysis or homozygosity mapping in five separate families established that their hearing loss was caused by five different known-deafness causing genes thus confirming the genetic heterogeneity of this disorder in the kingdom.</p> <p>Conclusion</p> <p>The overall results of this study are highly suggestive that underlying molecular basis of autosomal recessive non-syndromic deafness in Saudi Arabia is very genetically heterogeneous. In addition, we report that the preliminary results indicate that there does not seem to be any common or more prevalent loci, genes or mutations in patients with autosomal recessive non-syndromic hearing loss in patients of Saudi Arabian tribal origin.</p