Streamlined spatial and environmental expression signatures characterize the minimalist duckweed .

Single-cell genomics permits a new resolution in the examination of molecular and cellular dynamics, allowing global, parallel assessments of cell types and cellular behaviors through development and in response to environmental circumstances, such as interaction with water and the light-dark cycle of the Earth. Here, we leverage the smallest, and possibly most structurally reduced, plant, the semiaquatic , to understand dynamics of cell expression in these contexts at the whole-plant level. We examined single-cell-resolution RNA-sequencing data and found cells divide into four principal clusters representing the above- and below-water-situated parenchyma and epidermis.

BAllC and BAllCools: efficient formatting and operating for single-cell DNA methylation data.

Motivation: With single-cell DNA methylation studies yielding vast datasets, existing data formats struggle with the unique challenges of storage and efficient operations, highlighting a need for improved solutions.

Results: BAllC (Binary All Cytosines) emerges as a tailored format for methylation data, addressing these challenges. BAllCools, its complementary software toolkit, enhances parsing, indexing, and querying capabilities, promising superior operational speeds and reduced storage needs.

transcriptome responses to low water potential using high-throughput plate assays.

Soil-free assays that induce water stress are routinely used to investigate drought responses in the plant . Due to their ease of use, the research community often relies on polyethylene glycol (PEG), mannitol, and salt (NaCl) treatments to reduce the water potential of agar media, and thus induce drought conditions in the laboratory. However, while these types of stress can create phenotypes that resemble those of water deficit experienced by soil-grown plants, it remains unclear how these treatments compare at the transcriptional level.

Cell-type-specific effects of age and sex on human cortical neurons.

Altered transcriptional and epigenetic regulation of brain cell types may contribute to cognitive changes with advanced age. Using single-nucleus multi-omic DNA methylation and transcriptome sequencing (snmCT-seq) in frontal cortex from young adult and aged donors, we found widespread age- and sex-related variation in specific neuron types. The proportion of inhibitory SST- and VIP-expressing neurons was reduced in aged donors.

Deconvolution of polygenic risk score in single cells unravels cellular and molecular heterogeneity of complex human diseases.

Polygenic risk scores (PRSs) are commonly used for predicting an individual's genetic risk of complex diseases. Yet, their implication for disease pathogenesis remains largely limited. Here, we introduce scPRS, a geometric deep learning model that constructs single-cell-resolved PRS leveraging reference single-cell chromatin accessibility profiling data to enhance biological discovery as well as disease prediction.

scMeFormer: a transformer-based deep learning model for imputing DNA methylation states in single cells enhances the detection of epigenetic alterations in schizophrenia.

DNA methylation (DNAm), a crucial epigenetic mark, plays a key role in gene regulation, mammalian development, and various human diseases. Single-cell technologies enable the profiling of DNAm states at cytosines within the DNA sequence of individual cells, but they often suffer from limited coverage of CpG sites. In this study, we introduce scMeFormer, a transformer-based deep learning model designed to impute DNAm states for each CpG site in single cells.

Cell type-specific enrichment of somatic aneuploidy in the mammalian brain.

Somatic mutations alter the genomes of a subset of an individual's brain cells, impacting gene regulation and contributing to disease processes. Mosaic single nucleotide variants have been characterized with single-cell resolution in the brain, but we have limited information about large-scale structural variation, including whole-chromosome duplication or loss. We used a dataset of over 415,000 single-cell DNA methylation and chromatin conformation profiles across the adult mouse brain to identify aneuploid cells comprehensively.

Brain-wide correspondence of neuronal epigenomics and distant projections.

Single-cell analyses parse the brain's billions of neurons into thousands of 'cell-type' clusters residing in different brain structures. Many cell types mediate their functions through targeted long-distance projections allowing interactions between specific cell types. Here we used epi-retro-seq to link single-cell epigenomes and cell types to long-distance projections for 33,034 neurons dissected from 32 different regions projecting to 24 different targets (225 source-to-target combinations) across the whole mouse brain.

Conserved and divergent gene regulatory programs of the mammalian neocortex.

Divergence of cis-regulatory elements drives species-specific traits, but how this manifests in the evolution of the neocortex at the molecular and cellular level remains unclear. Here we investigated the gene regulatory programs in the primary motor cortex of human, macaque, marmoset and mouse using single-cell multiomics assays, generating gene expression, chromatin accessibility, DNA methylome and chromosomal conformation profiles from a total of over 200,000 cells. From these data, we show evidence that divergence of transcription factor expression corresponds to species-specific epigenome landscapes.

Single-cell analysis of chromatin accessibility in the adult mouse brain.

Recent advances in single-cell technologies have led to the discovery of thousands of brain cell types; however, our understanding of the gene regulatory programs in these cell types is far from complete. Here we report a comprehensive atlas of candidate cis-regulatory DNA elements (cCREs) in the adult mouse brain, generated by analysing chromatin accessibility in 2.3 million individual brain cells from 117 anatomical dissections.

Single-cell DNA methylome and 3D multi-omic atlas of the adult mouse brain.

Cytosine DNA methylation is essential in brain development and is implicated in various neurological disorders. Understanding DNA methylation diversity across the entire brain in a spatial context is fundamental for a complete molecular atlas of brain cell types and their gene regulatory landscapes. Here we used single-nucleus methylome sequencing (snmC-seq3) and multi-omic sequencing (snm3C-seq) technologies to generate 301,626 methylomes and 176,003 chromatin conformation-methylome joint profiles from 117 dissected regions throughout the adult mouse brain.

Single-cell DNA methylation and 3D genome architecture in the human brain.

Delineating the gene-regulatory programs underlying complex cell types is fundamental for understanding brain function in health and disease. Here, we comprehensively examined human brain cell epigenomes by probing DNA methylation and chromatin conformation at single-cell resolution in 517 thousand cells (399 thousand neurons and 118 thousand non-neurons) from 46 regions of three adult male brains. We identified 188 cell types and characterized their molecular signatures.

A comparative atlas of single-cell chromatin accessibility in the human brain.

Recent advances in single-cell transcriptomics have illuminated the diverse neuronal and glial cell types within the human brain. However, the regulatory programs governing cell identity and function remain unclear. Using a single-nucleus assay for transposase-accessible chromatin using sequencing (snATAC-seq), we explored open chromatin landscapes across 1.

BAllC and BAllCools: Efficient Formatting and Operating for Single-Cell DNA Methylation Data.

Motivation: With single-cell DNA methylation studies yielding vast datasets, existing data formats struggle with the unique challenges of storage and efficient operations, highlighting a need for improved solutions.

Results: BAllC (Binary All Cytosines) emerges as a tailored binary format for methylation data, addressing these challenges. BAllCools, its complementary software toolkit, enhances parsing, indexing, and querying capabilities, promising superior operational speeds and reduced storage needs.

Yet uninfected? Resolving cell states of plants under pathogen attack.

Although we have made significant strides in unraveling plant responses to pathogen attacks at the tissue or major cell type scale, a comprehensive understanding of individual cell responses still needs to be achieved. Addressing this gap, Zhu et al. employed single-cell transcriptome analysis to unveil the heterogeneous responses of plant cells when confronted with bacterial pathogens.

Robust enhancer-gene regulation identified by single-cell transcriptomes and epigenomes.

Single-cell sequencing could help to solve the fundamental challenge of linking millions of cell-type-specific enhancers with their target genes. However, this task is confounded by patterns of gene co-expression in much the same way that genetic correlation due to linkage disequilibrium confounds fine-mapping in genome-wide association studies (GWAS). We developed a non-parametric permutation-based procedure to establish stringent statistical criteria to control the risk of false-positive associations in enhancer-gene association studies (EGAS).

Human Immune Cell Epigenomic Signatures in Response to Infectious Diseases and Chemical Exposures.

Variations in DNA methylation patterns in human tissues have been linked to various environmental exposures and infections. Here, we identified the DNA methylation signatures associated with multiple exposures in nine major immune cell types derived from peripheral blood mononuclear cells (PBMCs) at single-cell resolution. We performed methylome sequencing on 111,180 immune cells obtained from 112 individuals who were exposed to different viruses, bacteria, or chemicals.

A guide to the BRAIN Initiative Cell Census Network data ecosystem.

Characterizing cellular diversity at different levels of biological organization and across data modalities is a prerequisite to understanding the function of cell types in the brain. Classification of neurons is also essential to manipulate cell types in controlled ways and to understand their variation and vulnerability in brain disorders. The BRAIN Initiative Cell Census Network (BICCN) is an integrated network of data-generating centers, data archives, and data standards developers, with the goal of systematic multimodal brain cell type profiling and characterization.