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Amaral, M. L.

Publications and source records attributed to Amaral, M. L..

3 recordsLinked to original sources

Single-Cell Epigenomics Uncovers Heterochromatin Instability and Transcription Factor Dysfunction during Mouse Brain Aging

The mechanisms regulating transcriptional changes in brain aging remain poorly understood. Here, we use single-cell epigenomics to profile chromatin accessibility and gene expression across eight brain regions in the mouse brain at 2, 9, and 18 months of age. In addition to a significant decline in progenitor cell populations involved in neurogenesis and myelination, we observed widespread and concordant changes of transcription and chromatin accessibility during aging in glial and neuronal cell types. These alterations are accompanied by dysregulation of master transcription factors and a shift toward stress-responsive programs driven by AP-1, indicating a progressive loss of cell identity with aging. We also identify region- and cell-type-specific heterochromatin decay, characterized by increased accessibility at H3K9me3-marked domains, activation of transposable elements, and upregulation of long non-coding RNAs, particularly in glutamatergic neurons. Together, these results reveal age-related disruption of heterochromatin maintenance and transcriptional programs, identify vulnerable brain regions and cell types, and pinpoint key molecular pathways altered in brain aging. HighlightsO_LISingle-cell multimodal profiling across eight brain regions reveals coordinated chromatin and transcriptional shifts during aging C_LIO_LIAge-related depletion of progenitor cells coincides with dysregulation of key developmental transcription factors C_LIO_LICell identity maintenance is compromised with the decline of master transcription factors C_LIO_LIHeterochromatin destabilization accompanied by activation of AP-1, transposable elements, pseudogene families, and long non-coding RNAs C_LI

genomics↗

Cell-type-specific transposable element demethylation and TAD remodeling in the aging mouse brain

Aging is a major risk factor for neurodegenerative diseases, yet underlying epigenetic mechanisms remain unclear. Here, we generated a comprehensive single-nucleus cell atlas of brain aging across multiple brain regions, comprising 132,551 single-cell methylomes and 72,666 joint chromatin conformation-methylome nuclei. Integration with companion transcriptomic and chromatin accessibility data yielded a cross-modality taxonomy of 36 major cell types. We observed that age-related methylation changes were more pronounced in non-neuronal cells. Transposable element methylation alone distinguished age groups, showing cell-type-specific genome-wide demethylation. Chromatin conformation analysis demonstrated age-related increases in TAD boundary strength with enhanced accessibility at CTCF binding sites. Spatial transcriptomics across 895,296 cells revealed regional heterogeneity during aging within identical cell types. Finally, we developed novel deep-learning models that accurately predict age-related gene expression changes using multi-modal epigenetic features, providing mechanistic insights into gene regulation. This dataset advances our understanding of brain aging and offers potential translational applications. HighlightsO_LISingle-cell multi-omic profiling maps the epigenetic and spatial transcriptomic landscape of brain aging across multiple regions. C_LIO_LICell-type-specific genome-wide demethylation of retrotransposable elements correlates with increased chromatin accessibility and expression. C_LIO_LIElevated TAD boundary strength emerges as a unique marker of brain aging associated with CTCF gaining accessibility. C_LIO_LIA novel deep-learning model reveals the significance of epigenetic features on age-related transcriptomic changes across genes. C_LI

genomics↗

Cell Type- and Tissue-specific Enhancers in Craniofacial Development

The genetic basis of craniofacial birth defects and general variation in human facial shape remains poorly understood. Distant-acting transcriptional enhancers are a major category of non-coding genome function and have been shown to control the fine-tuned spatiotemporal expression of genes during critical stages of craniofacial development1-3. However, a lack of accurate maps of the genomic location and cell type-specific in vivo activities of all craniofacial enhancers prevents their systematic exploration in human genetics studies. Here, we combined histone modification and chromatin accessibility profiling from different stages of human craniofacial development with single-cell analyses of the developing mouse face to create a comprehensive catalogue of the regulatory landscape of facial development at tissue- and single cell-resolution. In total, we identified approximately 14,000 enhancers across seven developmental stages from weeks 4 through 8 of human embryonic face development. We used transgenic mouse reporter assays to determine the in vivo activity patterns of human face enhancers predicted from these data. Across 16 in vivo validated human enhancers, we observed a rich diversity of craniofacial subregions in which these enhancers are active in vivo. To annotate the cell type specificities of human-mouse conserved enhancers, we performed single-cell RNA-seq and single-nucleus ATAC-seq of mouse craniofacial tissues from embryonic days e11.5 to e15.5. By integrating these data across species, we find that the majority (56%) of human craniofacial enhancers are functionally conserved in mice, providing cell type- and embryonic stage-resolved predictions of their in vivo activity profiles. Using retrospective analysis of known craniofacial enhancers in combination with single cell-resolved transgenic reporter assays, we demonstrate the utility of these data for predicting the in vivo cell type specificity of enhancers. Taken together, our data provide an expansive resource for genetic and developmental studies of human craniofacial development. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=138 HEIGHT=200 SRC="FIGDIR/small/546603v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@7595a9org.highwire.dtl.DTLVardef@1b48b81org.highwire.dtl.DTLVardef@32fe86org.highwire.dtl.DTLVardef@1e41fed_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗