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L

Publications and source records attributed to L.

3 recordsLinked to original sources

A Multimodal Single-Cell Epigenomic and 3D Genome Atlas of the Human Basal Ganglia

The basal ganglia (BG) underlie motor control, reward processing, and many neurological and psychiatric disorders, but a comprehensive epigenomic and 3D-genome atlas of the human BG is lacking. Here we present a multimodal single-cell atlas profiling DNA methylation and 3D chromatin conformation in 261,331 nuclei (snm3C-seq) across eight subregions, resolving 12 classes, 31 subclasses, and 59 groups. Harmonized under the HMBA basal-ganglia consensus taxonomy, this atlas integrates with matched RNA, ATAC-seq, and histone-modification data across five regulatory layers. We identify millions of cell-type- and region-specific differentially methylated regions enriched for distinct transcription factor motifs and link them to disease-associated heritability. Neuron-specific loops dominate cell-type-specific 3D contact remodeling, while most non-neuron-specific loops are constitutive. Among spiny projection neurons (SPNs), chromatin loops, rather than TAD boundaries, distinguish D1, D2, and eccentric SPN subclasses, with eccentric SPNs showing the most loop-level reorganization among the three. We characterize STR D2 SMYD2-HTR7 SPN, a newly recognized POU6F2 D2-SPN subtype, and reveal region-specific methylation and contact gradients of disease-associated genes, including CADM1 and PDE8B. Integrative gene-regulatory networks reconstruct cell-type-resolved enhancer-promoter links to interpret Parkinsons disease risk variants at SNCA. Finally, MERFISH spatial profiling combined with cross-species Patch-seq identifies non-SPN neuronal subtypes, including a MOXD1 striosomal STR FS PTHLH-PVALB GABA subtype with distinct electrophysiology, partitioning across the striatal matrix-striosome boundary. HighlightsO_LIA multimodal single-cell atlas maps DNA methylation and 3D genome architecture across human basal ganglia cell types and subregions. C_LIO_LINeuron-specific loops dominate cell-type-specific 3D contact remodeling in the human BG, whereas most non-neuron-specific loops are constitutive. C_LIO_LISpiny Projection Neuron (SPN) subtypes exhibit regionally organized epigenomic and 3D genome signatures that align with dorsal-ventral identities. C_LIO_LIChromatin loops are the primary distinguishing feature among D1, D2, and eccentric SPN subclasses, with eccentric SPNs being the most 3D-reorganized. C_LIO_LIIntegrated regulatory maps link cell-type-specific enhancers to disease-associated genetic risk in the human basal ganglia. C_LIO_LINon-SPN interneurons differ in distribution and in transcriptional and epigenetic identity across the matrix-striosome boundary. C_LI

neuroscience↗

Patterns of within-host genetic diversity in SARS-CoV-2

Monitoring the spread of SARS-CoV-2 and reconstructing transmission chains has become a major public health focus for many governments around the world. The modest mutation rate and rapid transmission of SARS-CoV-2 prevents the reconstruction of transmission chains from consensus genome sequences, but within-host genetic diversity could theoretically help identify close contacts. Here we describe the patterns of within-host diversity in 1,181 SARS-CoV-2 samples sequenced to high depth in duplicate. 95% of samples show within-host mutations at detectable allele frequencies. Analyses of the mutational spectra revealed strong strand asymmetries suggestive of damage or RNA editing of the plus strand, rather than replication errors, dominating the accumulation of mutations during the SARS-CoV-2 pandemic. Within and between host diversity show strong purifying selection, particularly against nonsense mutations. Recurrent within-host mutations, many of which coincide with known phylogenetic homoplasies, display a spectrum and patterns of purifying selection more suggestive of mutational hotspots than recombination or convergent evolution. While allele frequencies suggest that most samples result from infection by a single lineage, we identify multiple putative examples of co-infection. Integrating these results into an epidemiological inference framework, we find that while sharing of within-host variants between samples could help the reconstruction of transmission chains, mutational hotspots and rare cases of superinfection can confound these analyses.

genomics↗

A common haplotype lowers SPI1 (PU.1) expression in myeloid cells and delays age at onset for Alzheimer’s disease

In this study we used age at onset of Alzheimers disease (AD), cerebrospinal fluid (CSF) biomarkers, and cis-expression quantitative trait loci (cis-eQTL) datasets to identify candidate causal genes and mechanisms underlying AD GWAS loci. In a genome-wide survival analysis of 40,255 samples, eight of the previously reported AD risk loci are significantly (P < 5x10-8) or suggestively (P < 1x10-5) associated with age at onset-defined survival (AAOS) and a further fourteen novel loci reached suggestive significance. Using stratified LD score regression we demonstrated a significant enrichment of AD heritability in hematopoietic cells of the myeloid and B-lymphoid lineage. We then investigated the impact of these 22 AAOS-associated variants on CSF biomarkers and gene expression in cells of the myeloid lineage. In particular, the minor allele of rs1057233 (G), within the previously reported CELF1 AD risk locus, shows association with higher age at onset of AD (P=8.40x10-6), higher CSF levels of A{beta}42 (P=1.2x10-4), and lower expression of SPI1 in monocytes (P=1.50x10-105) and macrophages (P=6.41x10-87). SPI1 encodes PU.1, a transcription factor critical for myeloid cell development and function. AD heritability is enriched within the SPI1 cistromes of monocytes and macrophages, implicating a myeloid PU.1 target gene network in the etiology of AD. Finally, experimentally altered PU.1 levels are correlated with phagocytic activity of BV2 mouse microglial cells and specific changes in the expression of multiple myeloid-expressed genes, including the mouse orthologs of AD-associated genes, APOE, CLU/APOJ, CD33, MS4A4A/MS4A6A, and TYROBP. Our results collectively suggest that lower SPI1 expression reduces AD risk by modulating myeloid cell gene expression and function.

neuroscience↗