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Whitaker, D. T.

Publications and source records attributed to Whitaker, D. T..

5 recordsLinked to original sources

Integration of cell-specific gene expression and chromatin accessibility facilitates localization of neurodegenerative risk in microglia

Genome-wide association studies (GWAS) have identified many loci that contribute to the risk of neurodegenerative diseases. However, a persistent challenge in interpretation of GWAS is to break loci down to specific genes, variants, and cell types, and thus nominate disease mechanisms. Here, we used iPSC-derived cells containing population-level variation to examine GWAS loci across NDDs including Alzheimer's disease, Parkinson's disease and Lewy body dementia. We differentiated a set of 135 iPSC donor lines into two cell types relevant to neurodegeneration, neurons and microglia, and completed single cell gene expression and chromatin accessibility profiling. Meta-analysis of these data with published human brain snRNAseq for QTL mapping identified multiple loci associated with NDDs that are restricted to either neurons or microglia. Colocalization of GWAS and these QTL supports microglia as having a strong contribution to disease risk. We tested peaks nominated at the BIN1 locus for enhancer activity using a perturb-seq-based method in microglia. Our results show one of the nominated peaks controls BIN1 expression in microglia but also modifies expression of other genes at the locus. These results support the hypothesis that common variants affecting gene expression specifically in microglia can contribute directly to NDD risk rather than functioning solely as a secondary response to neurodegeneration. These data also show that iPSC-derived cells are a useful model to experimentally dissect GWAS loci that colocalize with QTL.

genomics↗

Characterization of DNA methylation in PBMCs and donor-matched iPSCs shows methylation is reset during stem cell reprogramming

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC="FIGDIR/small/627515v2_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@18cda69org.highwire.dtl.DTLVardef@574c4corg.highwire.dtl.DTLVardef@1522644org.highwire.dtl.DTLVardef@4e799c_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO C_FIG HighlightsO_LIGeneration of a population-level set of iPSC lines from healthy individuals across the lifespan C_LIO_LIAging-related features were reset based on epigenetic markers of cytosine methylation and telomere length C_LIO_LIBy comparing methQTLs in iPSC vs. their donor PBMCs, we find that detection of methQTLs reflect biological functions of different cell types C_LI DNA methylation is an important epigenetic mechanism that helps define and maintain cellular functions. It is influenced by many factors, including environmental exposures, genotype, cell type, sex, and aging. Since age is the primary risk factor for developing neurodegenerative diseases, it is important to determine if aging-related DNA methylation is retained when cells are reprogrammed to an induced Pluripotent Stem Cell (iPSC) state. Here, we selected peripheral blood mononuclear cells (PBMCs; n = 99) from a cohort of diverse and healthy individuals enrolled in the Genetic and Epigenetic Signatures of Translational Aging Laboratory Testing (GESTALT) study to convert to iPSCs. After reprogramming we evaluated the resulting iPSCs for DNA methylation signatures to determine if they reflect the confounding factors of age and environmental factors. We used genome-wide DNA methylation arrays in both cell types to show that the epigenetic clock is largely reset to an early methylation age after conversion of PBMCs to iPSCs. We further examined the epigenetic age of each cell type using an Epigenome-wide Association Study (EWAS). Finally, we identified a set of methylation Quantitative Trait Loci (methQTL) in each cell type. Our results show that age-related DNA methylation is largely reset in iPSCs, and each cell type has a unique set of methylation sites that are genetically influenced.

molecular biology↗

Divergent patterns of healthy aging across human brain regions at single-cell resolution reveal links to neurodegenerative disease

Given that age is a significant risk factor for multiple neurodegenerative diseases, investigating normal brain aging may help identify molecular events that may contribute to increased disease risk over time. Single-nucleus RNA sequencing (snRNA-seq) enables analysis of gene expression changes within specific cell-types, potentially offering insights into the molecular mechanisms underlying aging. However, most brain snRNA-Seq datasets used age-matched controls from studies focused on pathological processes and have largely been limited to cortical regions. Therefore, there is a need to investigate the non-pathological aging process in brain regions that are vulnerable to age-related diseases. Here, we report a snRNA-seq study of 6 young (20-30 years) and 7 aged (60-85 years) encompassing four different brain regions: the entorhinal cortex, middle temporal gyrus, subventricular zone, and putamen. We captured over 150,000 nuclei that represented 10 broad cell-types. While we did not find statistically significant differences in cell-type proportions with age, region- and cell-type-specific differential expression analyses identified over 8,000 age-associated genes. Notably, within a given cell-type, most of these associations were region-specific. Functional enrichment analyses of the gene sets for each cell-type-region combination revealed diverse biological processes, including multiple hallmarks of aging, such as proteostasis, interactions with cytokines, vesicular trafficking, metabolism, inflammation, and metal ion homeostasis. Overall, our findings suggest that unique cell-types exhibit distinct transcriptional aging profiles both at the cell-type level and across different brain regions.

neuroscience↗

Best practices for analyzing imputed genotypes from low-pass sequencing in dogs

Although DNA array-based approaches for genome wide association studies (GWAS) permit the collection of thousands of low-cost genotypes, it is often at the expense of resolution and completeness, as SNP chip technologies are ultimately limited by SNPs chosen during array development. An alternative low-cost approach is low-pass whole genome sequencing (WGS) followed by imputation. Rather than relying on high levels of genotype confidence at a set of select loci, low-pass WGS and imputation relies on the combined information from millions of randomly sampled low confidence genotypes. To investigate low-pass WGS and imputation in the dog, we assessed accuracy and performance by downsampling 97 high-coverage (>15x) WGS datasets from 51 different breeds to approximately 1x coverage, simulating low-pass WGS. Using a reference panel of 676 dogs from 91 breeds, genotypes were imputed from the downsampled data and compared to a truth set of genotypes generated from high coverage WGS. Using our truth set, we optimized a variant quality filtering strategy that retained approximately 80% of 14M imputed sites and lowered the imputation error rate from 3.0% to 1.5%. Seven million sites remained with a MAF > 5% and an average imputation quality score of 0.95. Finally, we simulated the impact of imputation errors on outcomes for case-control GWAS, where small effect sizes were most impacted and medium to large effect sizes were minorly impacted. These analyses provide best practice guidelines for study design and data post-processing of low-pass WGS imputed genotypes in dogs.

genomics↗

NRL- and CRX-guided gene network modulates photoreceptor presynapse size and positioning during retinal development

Unique morphologies of rod and cone photoreceptor presynaptic terminals permit the formation of synapses onto interneurons during retina development. We integrated multiple \"omics\" datasets of developing rod and S-cone-like photoreceptors and identified 719 genes that are regulated by NRL and CRX, critical transcriptional regulators of rod differentiation, as candidates for controlling presynapse morphology. In vivo knockdown of 72 candidate genes in the developing retina uncovered 26 genes that alter size and/or positioning of rod spherules in the outer plexiform layer. Co-expression of seven cDNAs with their cognate shRNAs rescued the rod presynapse phenotype. Loss of function of four genes in germline or by an AAV-mediated CRISPR/Cas9 strategy validated RNAi screen findings. A protein interaction network analysis of the 26 positive effectors revealed additional candidates in the NRL/CRX-regulated presynapse morphology-associated gene network. Follow-up knockdowns of two novel candidates support the proposed network. Our studies demonstrate a requirement of multiple components in a modular network for rod presynapse morphogenesis and provide a functional genomic framework for deciphering genetic determinants of morphological specification during development.\n\nAuthor SummaryThe relationship between neuronal morphology and function has been recognized for over 100 years. However, we still have poor understanding of genes and proteins that control morphogenesis of a specific neuron. In the current study, we address this connection between gene expression and neural morphology by identifying and knocking down a subset of expressed genes in rod photoreceptors. We ascertained a number of candidate genes controlling photoreceptor pre-synaptic terminal morphology, which is necessary for its connection with second-order neurons in the retinal circuit. Furthermore, we have curated a more plausible network of genes, either identified in our study or predicted, that are enriched for processes underlying photoreceptor morphogenesis. We suggest that our work will provide a framework for dissecting genetic basis of neuronal architecture and assist in better design of cell replacement therapies for retinal degeneration.

neuroscience↗