Climate change threatens global agriculture, impacting plant health and crop yield, while plant microbiomes offer potential solutions to enhance resilience. In this forum, we discuss the prospects of single cell multiome and network science in understanding intricate plant-microbe interactions, providing insights for sustainable agriculture and improved crop productivity for global food security.

Leukemia can arise at various stages of the hematopoietic differentiation hierarchy, but the impact of developmental arrest on drug sensitivity is unclear. Applying network-based analyses to single-cell transcriptomes of human B cells, we define genome-wide signaling circuitry for each B cell differentiation stage. Using this reference, we comprehensively map the developmental states of B cell acute lymphoblastic leukemia (B-ALL), revealing its strong correlation with sensitivity to asparaginase, a commonly used chemotherapeutic agent. Single-cell multi-omics analyses of primary B-ALL blasts reveal marked intra-leukemia heterogeneity in asparaginase response: resistance is linked to pre-pro-B-like cells, with sensitivity associated with the pro-B-like population. By targeting BCL2, a driver within the pre-pro-B-like cell signaling network, we find that venetoclax significantly potentiates asparaginase efficacy in vitro and in vivo. These findings demonstrate a single-cell systems pharmacology framework to predict effective combination therapies based on intra-leukemia heterogeneity in developmental state, with potentially broad applications beyond B-ALL.

Cell plasticity theoretically extends to all possible cell types, but naturally decreases as cells differentiate, whereas injury-repair re-engages the developmental plasticity. Here we show that the lung alveolar type 2 (AT2)-specific transcription factor (TF), CEBPA, restricts AT2 cell plasticity in the mouse lung. AT2 cells undergo transcriptional and epigenetic maturation postnatally. Without CEBPA, both neonatal and mature AT2 cells reduce the AT2 program, but only the former reactivate the SOX9 progenitor program. Sendai virus infection bestows mature AT2 cells with neonatal plasticity where Cebpa mutant, but not wild type, AT2 cells express SOX9, as well as more readily proliferate and form KRT8/CLDN4+ transitional cells. CEBPA promotes the AT2 program by recruiting the lung lineage TF NKX2-1. The temporal change in CEBPA-dependent plasticity reflects AT2 cell developmental history. The ontogeny of AT2 cell plasticity and its transcriptional and epigenetic mechanisms have implications in lung regeneration and cancer.

Mesenchymal stem cells (MSC) are multipotent stem cells that can differentiate into multiple cell types, including osteoblasts, chondrocytes, and adipocytes. Osteoblast differentiation is reduced during osteoporosis development, resulting in reduced bone formation. Further, MSC isolated from different donors possess distinct osteogenic capacity. In this study, we used single-cell multiomic analysis to profile the transcriptome and epigenome of MSC from four healthy donors. Data were obtained from ~1300 to 1600 cells for each donor. These cells were clustered into four groups, indicating that MSC from different donors have distinct chromatin accessible regulatory elements for regulating gene expression. To investigate the mechanism by which MSC undergo osteogenic differentiation, we used the chromatin accessibility data from the single-cell multiome data to identify individual-specific enhancer-promoter pairs and evaluated the expression levels and activities of the transcriptional regulators. The MSC from four donors showed distinct differentiation potential into osteoblasts. MSC of donor 1 showed the largest average motif activities, indicating that MSC from donor 1 was most likely to differentiate into osteoblasts. The results of our validation experiments were consistent with the bioinformatics prediction. We also tested the enrichment of genome-wide association study (GWAS) signals of several musculoskeletal disease traits in the patient-specific chromatin accessible regions identified in the single-cell multiome data, including osteoporosis, osteopenia, and osteoarthritis. We found that osteoarthritis-associated variants were only enriched in the regions identified from donor 4. In contrast, osteoporosis and osteopenia variants were enriched in regions from donor 1 and least enriched in donor 4. Since osteoporosis and osteopenia are related to the density of bone cells, the enrichment of variants from these traits should be correlated with the osteogenic potential of MSC. In summary, this study provides large-scale data to link regulatory elements with their target genes to study the regulatory relationships during the differentiation of mesenchymal stem cells and provide a deeper insight into the gene regulatory mechanism.

We propose Destin2, a novel statistical and computational method for cross-modality dimension reduction, clustering, and trajectory reconstruction for single-cell ATAC-seq data. The framework integrates cellular-level epigenomic profiles from peak accessibility, motif deviation score, and pseudo-gene activity and learns a shared manifold using the multimodal input, followed by clustering and/or trajectory inference. We apply Destin2 to real scATAC-seq datasets with both discretized cell types and transient cell states and carry out benchmarking studies against existing methods based on unimodal analyses. Using cell-type labels transferred with high confidence from unmatched single-cell RNA sequencing data, we adopt four performance assessment metrics and demonstrate how Destin2 corroborates and improves upon existing methods. Using single-cell RNA and ATAC multiomic data, we further exemplify how Destin2\'s cross-modality integrative analyses preserve true cell-cell similarities using the matched cell pairs as ground truths. Destin2 is compiled as a freely available R package available at https://github.com/yuchaojiang/Destin2.

The method of single-cell RNA sequencing has been rapidly developed, and numerous experiments have been conducted over the past decade. Their results allow us to recognize various subpopulations and rare cell states in tissues, tumors, and immune systems that are previously unidentified, and guide us to understand fundamental biological processes that determine cell identity based on single-cell gene expression profiles. However, it is still challenging to understand the principle of comprehensive gene regulation that determines the cell fate only with transcriptome, a consequential output of the gene expression program. To elucidate the mechanisms related to the origin and maintenance of comprehensive single-cell transcriptome, we require a corresponding single-cell epigenome, which is a differentiated information of each cell with an identical genome. This review deals with the current development of single-cell epigenomic library construction methods, including multi-omics tools with crucial factors and additional requirements in the future focusing on DNA methylation, chromatin accessibility, and histone post-translational modifications. The study of cellular differentiation and the disease occurrence at a single-cell level has taken the first step with single-cell transcriptome and is now taking the next step with single-cell epigenome.