We report a novel DNA sequence motif in human and mouse genomes. This motif has several interesting features indicating that it is highly likely to be an unknown functional sequence element. The motif is highly enriched in promoter regions. Locations of the motif sites in the genome have strong tendency to be clustered together. Motif sites are associated with increased phylogenetic conservation as well as elevated DNase I hypersensitivity (DHS) in ENCODE cell lines. Clustered motif sites are found in promoter regions of a substantial fraction of the protein-coding genes in the genome. All together, these indicate that the motif may have important functions associated with a large number of genes.

The Second Heart Field (SHF) has been implicated in several forms of congenital heart disease (CHD), including atrioventricular septal defects (AVSDs). Identifying the SHF gene regulatory networks required for atrioventricular septation is therefore an essential goal for understanding the molecular basis of AVSDs. We defined a SHF Hedgehog-dependent gene regulatory network using whole genome transcriptional profiling and GLI-chromatin interaction studies. The Forkhead box transcription factors Foxf1a and Foxf2 were identified as SHF Hedgehog targets. Compound haploinsufficiency for Foxf1a and Foxf2 caused atrioventricular septal defects, demonstrating the biological relevance of this regulatory network. We identified a Foxf1a cis-regulatory element that bound the Hedgehog transcriptional regulators GLI1 and GLI3 and the T-box transcription factor TBX5 in vivo. GLI1 and TBX5 synergistically activated transcription from this cis-regulatory element in vitro. This enhancer drove reproducible expression in vivo in the posterior SHF, the only region where Gli1 and Tbx5 expression overlaps. Our findings implicate Foxf genes in atrioventricular septation, describe the molecular underpinnings of the genetic interaction between Hedgehog signaling and Tbx5, and establish a molecular model for the selection of the SHF gene regulatory network for cardiac septation.

Codevelopment of the lungs and heart underlies key evolutionary innovations in the transition to terrestrial life. Cardiac specializations that support pulmonary circulation, including the atrial septum, are generated by second heart field (SHF) cardiopulmonary progenitors (CPPs). It has been presumed that transcription factors required in the SHF for cardiac septation, e.g., Tbx5, directly drive a cardiac morphogenesis gene-regulatory network. Here, we report instead that TBX5 directly drives Wnt ligands to initiate a bidirectional signaling loop between cardiopulmonary mesoderm and the foregut endoderm for endodermal pulmonary specification and, subsequently, atrial septation. We show that Tbx5 is required for pulmonary specification in mice and amphibians but not for swim bladder development in zebrafish. TBX5 is non-cell-autonomously required for pulmonary endoderm specification by directly driving Wnt2 and Wnt2b expression in cardiopulmonary mesoderm. TBX5 ChIP-sequencing identified cis-regulatory elements at Wnt2 sufficient for endogenous Wnt2 expression domains in vivo and required for Wnt2 expression in precardiac mesoderm in vitro. Tbx5 cooperated with Shh signaling to drive Wnt2b expression for lung morphogenesis. Tbx5 haploinsufficiency in mice, a model of Holt-Oram syndrome, caused a quantitative decrement of mesodermal-to-endodermal Wnt signaling and subsequent endodermal-to-mesodermal Shh signaling required for cardiac morphogenesis. Thus, Tbx5 initiates a mesoderm-endoderm-mesoderm signaling loop in lunged vertebrates that provides a molecular basis for the coevolution of pulmonary and cardiac structures required for terrestrial life.

Mutations in the Bone Morphogenetic Protein (BMP) pathway are associated with a range of defects in skeletal formation. Genetic analysis of BMP signaling requirements is complicated by the presence of three partially redundant BMPs that are required for multiple stages of limb development. We generated an inducible allele of a BMP inhibitor, Gremlin, which reduces BMP signaling. We show that BMPs act in a dose and time dependent manner in which early reduction of BMPs result in digit loss, while inhibiting overall BMP signaling between E10.5 and E11.5 allows polydactylous digit formation. During this period, inhibiting BMPs extends the duration of FGF signaling. Sox9 is initially expressed in normal digit ray domains but at reduced levels that correlate with the reduction in BMP signaling. The persistence of elevated FGF signaling likely promotes cell proliferation and survival, inhibiting the activation of Sox9 and secondarily, inhibiting the differentiation of Sox9-expressing chondrocytes. Our results provide new insights into the timing and clarify the mechanisms underlying BMP signaling during digit morphogenesis.

The standard methods for detecting differential gene expression are mostly designed for analyzing a single gene expression experiment. When data from multiple related gene expression studies are available, separately analyzing each study is not ideal as it may fail to detect important genes with consistent but relatively weak differential signals in multiple studies. Jointly modeling all data allows one to borrow information across studies to improve the analysis. However, a simple concordance model, in which each gene is assumed to be differential in either all studies or none of the studies, is incapable of handling genes with study-specific differential expression. In contrast, a model that naively enumerates and analyzes all possible differential patterns across studies can deal with study-specificity and allow information pooling, but the complexity of its parameter space grows exponentially as the number of studies increases. Here, we propose a correlation motif approach to address this dilemma. This approach searches for a small number of latent probability vectors called correlation motifs to capture the major correlation patterns among multiple studies. The motifs provide the basis for sharing information among studies and genes. The approach has flexibility to handle all possible study-specific differential patterns. It improves detection of differential expression and overcomes the barrier of exponential model complexity.

We evaluate the feasibility of using a biological sample's transcriptome to predict its genome-wide regulatory element activities measured by DNase I hypersensitivity (DH). We develop BIRD, Big Data Regression for predicting DH, to handle this high-dimensional problem. Applying BIRD to the Encyclopedia of DNA Elements (ENCODE) data, we found that to a large extent gene expression predicts DH, and information useful for prediction is contained in the whole transcriptome rather than limited to a regulatory element's neighboring genes. We show applications of BIRD-predicted DH in predicting transcription factor-binding sites (TFBSs), turning publicly available gene expression samples in Gene Expression Omnibus (GEO) into a regulome database, predicting differential regulatory element activities, and facilitating regulome data analyses by serving as pseudo-replicates. Besides improving our understanding of the regulome-transcriptome relationship, this study suggests that transcriptome-based prediction can provide a useful new approach for regulome mapping.

The rapid development of single-cell RNA-sequencing (scRNA-seq) technologies has led to the emergence of many methods for removing systematic technical noises, including imputation methods, which aim to address the increased sparsity observed in single-cell data. Although many imputation methods have been developed, there is no consensus on how methods compare to each other.

Tumor-initiating cells with reprogramming plasticity or stem-progenitor cell properties (stemness) are thought to be essential for cancer development and metastatic regeneration in many cancers; however, elucidation of the underlying molecular network and pathways remains demanding. Combining machine learning and experimental investigation, here we report CD81, a tetraspanin transmembrane protein known to be enriched in extracellular vesicles (EVs), as a newly identified driver of breast cancer stemness and metastasis. Using protein structure modeling and interface prediction-guided mutagenesis, we demonstrate that membrane CD81 interacts with CD44 through their extracellular regions in promoting tumor cell cluster formation and lung metastasis of triple negative breast cancer (TNBC) in human and mouse models. In-depth global and phosphoproteomic analyses of tumor cells deficient with CD81 or CD44 unveils endocytosis-related pathway alterations, leading to further identification of a quality-keeping role of CD44 and CD81 in EV secretion as well as in EV-associated stemness-promoting function. CD81 is coexpressed along with CD44 in human circulating tumor cells (CTCs) and enriched in clustered CTCs that promote cancer stemness and metastasis, supporting the clinical significance of CD81 in association with patient outcomes. Our study highlights machine learning as a powerful tool in facilitating the molecular understanding of new molecular targets in regulating stemness and metastasis of TNBC.

Pseudotime analysis with single-cell RNA-sequencing (scRNA-seq) data has been widely used to study dynamic gene regulatory programs along continuous biological processes. While many computational methods have been developed to infer the pseudo-temporal trajectories of cells within a biological sample, methods that compare pseudo-temporal patterns with multiple samples (or replicates) across different experimental conditions are lacking. Lamian is a comprehensive and statistically-rigorous computational framework for differential multi-sample pseudotime analysis. It can be used to identify changes in a biological process associated with sample covariates, such as different biological conditions, and also to detect changes in gene expression, cell density, and topology of a pseudotemporal trajectory. Unlike existing methods that ignore sample variability, Lamian draws statistical inference after accounting for cross-sample variability and hence substantially reduces sample-specific false discoveries that are not generalizable to new samples. Using both simulations and real scRNA-seq data, including an analysis of differential immune response programs between COVID-19 patients with different disease severity levels, we demonstrate the advantages of Lamian in decoding cellular gene expression programs in continuous biological processes.

Conventional high-throughput genomic technologies for mapping regulatory element activities in bulk samples such as ChIP-seq, DNase-seq and FAIRE-seq cannot analyze samples with small numbers of cells. The recently developed low-input and single-cell regulome mapping technologies such as ATAC-seq and single-cell ATAC-seq (scATAC-seq) allow analyses of small-cell-number and single-cell samples, but their signals remain highly discrete or noisy. Compared to these regulome mapping technologies, transcriptome profiling by RNA-seq is more widely used. Transcriptome data in single-cell and small-cell-number samples are more continuous and often less noisy. Here, we show that one can globally predict chromatin accessibility and infer regulatory element activities using RNA-seq. Genome-wide chromatin accessibility predicted by RNA-seq from 30 cells can offer better accuracy than ATAC-seq from 500 cells. Predictions based on single-cell RNA-seq (scRNA-seq) can more accurately reconstruct bulk chromatin accessibility than using scATAC-seq. Integrating ATAC-seq with predictions from RNA-seq increases the power and value of both methods. Thus, transcriptome-based prediction provides a new tool for decoding gene regulatory circuitry in samples with limited cell numbers.

Retinitis pigmentosa (RP) and associated inherited retinal diseases (IRDs) are caused by rod photoreceptor degeneration, necessitating therapeutics promoting rod photoreceptor survival. To address this, we tested compounds for neuroprotective effects in multiple zebrafish and mouse RP models, reasoning drugs effective across species and/or independent of disease mutation may translate better clinically. We first performed a large-scale phenotypic drug screen for compounds promoting rod cell survival in a larval zebrafish model of inducible RP. We tested 2934 compounds, mostly human-approved drugs, across six concentrations, resulting in 113 compounds being identified as hits. Secondary tests of 42 high-priority hits confirmed eleven lead candidates. Leads were then evaluated in a series of mouse RP models in an effort to identify compounds effective across species and RP models, that is, potential pan-disease therapeutics. Nine of 11 leads exhibited neuroprotective effects in mouse primary photoreceptor cultures, and three promoted photoreceptor survival in mouse rd1 retinal explants. Both shared and complementary mechanisms of action were implicated across leads. Shared target tests implicated parp1-dependent cell death in our zebrafish RP model. Complementation tests revealed enhanced and additive/synergistic neuroprotective effects of paired drug combinations in mouse photoreceptor cultures and zebrafish, respectively. These results highlight the value of cross-species/multi-model phenotypic drug discovery and suggest combinatorial drug therapies may provide enhanced therapeutic benefits for RP patients.

Most circulating tumor cells (CTC) are detected as single cells, whereas a small proportion of CTCs in multicellular clusters with stemness properties possess 20- to 100-times higher metastatic propensity than the single cells. Here we report that CTC dynamics in both singles and clusters in response to therapies predict overall survival for breast cancer. Chemotherapy-evasive CTC clusters are relatively quiescent with a specific loss of ST6GAL1-catalyzed α2,6-sialylation in glycoproteins. Dynamic hyposialylation in CTCs or deficiency of ST6GAL1 promotes cluster formation for metastatic seeding and enables cellular quiescence to evade paclitaxel treatment in breast cancer. Glycoproteomic analysis reveals newly identified protein substrates of ST6GAL1, such as adhesion or stemness markers PODXL, ICAM1, ECE1, ALCAM1, CD97, and CD44, contributing to CTC clustering (aggregation) and metastatic seeding. As a proof of concept, neutralizing antibodies against one newly identified contributor, PODXL, inhibit CTC cluster formation and lung metastasis associated with paclitaxel treatment for triple-negative breast cancer.

Maternal supplementation with folic acid is known to reduce the incidence of neural tube defects (NTDs) by as much as 70%. Despite the strong clinical link between folate and NTDs, the biochemical mechanisms through which folic acid acts during neural tube development remain undefined. The Mthfd1l gene encodes a mitochondrial monofunctional 10-formyl-tetrahydrofolate synthetase, termed MTHFD1L. This gene is expressed in adults and at all stages of mammalian embryogenesis with localized regions of higher expression along the neural tube, developing brain, craniofacial structures, limb buds, and tail bud. In both embryos and adults, MTHFD1L catalyzes the last step in the flow of one-carbon units from mitochondria to cytoplasm, producing formate from 10-formyl-THF. To investigate the role of mitochondrial formate production during embryonic development, we have analyzed Mthfd1l knockout mice. All embryos lacking Mthfd1l exhibit aberrant neural tube closure including craniorachischisis and exencephaly and/or a wavy neural tube. This fully penetrant folate-pathway mouse model does not require feeding a folate-deficient diet to cause this phenotype. Maternal supplementation with sodium formate decreases the incidence of NTDs and partially rescues the growth defect in embryos lacking Mthfd1l. These results reveal the critical role of mitochondrially derived formate in mammalian development, providing a mechanistic link between folic acid and NTDs. In light of previous studies linking a common splice variant in the human MTHFD1L gene with increased risk for NTDs, this mouse model provides a powerful system to help elucidate the specific metabolic mechanisms that underlie folate-associated birth defects, including NTDs.

We present CisGenome, a software system for analyzing genome-wide chromatin immunoprecipitation (ChIP) data. CisGenome is designed to meet all basic needs of ChIP data analyses, including visualization, data normalization, peak detection, false discovery rate computation, gene-peak association, and sequence and motif analysis. In addition to implementing previously published ChIP-microarray (ChIP-chip) analysis methods, the software contains statistical methods designed specifically for ChlP sequencing (ChIP-seq) data obtained by coupling ChIP with massively parallel sequencing. The modular design of CisGenome enables it to support interactive analyses through a graphic user interface as well as customized batch-mode computation for advanced data mining. A built-in browser allows visualization of array images, signals, gene structure, conservation, and DNA sequence and motif information. We demonstrate the use of these tools by a comparative analysis of ChIP-chip and ChIP-seq data for the transcription factor NRSF/REST, a study of ChIP-seq analysis with or without a negative control sample, and an analysis of a new motif in Nanog- and Sox2-binding regions.

Sonic hedgehog (Shh) signal, mediated by the Gli family of transcription factors, plays an essential role in the growth and patterning of the limb. Through analysis of the early limb bud transcriptome, we identified a posteriorly-enriched gene, Hyaluronic Acid Synthase 2 (Has2), which encodes a key enzyme for the synthesis of hyaluronan (HA), as a direct target of Gli transcriptional regulation during early mouse limb development. Has2 expression in the limb bud is lost in Shh null and expanded anteriorly in Gli3 mutants. We identified an ∼3kb Has2 promoter fragment that contains two strong Gli-binding consensus sequences, and mutation of either site abrogated the ability of Gli1 to activate Has2 promoter in a cell-based assay. Additionally, this promoter fragment is sufficient to direct expression of a reporter gene in the posterior limb mesenchyme. Chromatin immunoprecipitation of DNA-Gli3 protein complexes from limb buds indicated that Gli3 strongly binds to the Has2 promoter region, suggesting that Has2 is a direct transcriptional target of the Shh signaling pathway. We also showed that Has2 conditional mutant (Has2cko) hindlimbs display digit-specific patterning defects with longitudinally shifted phalangeal joints and impaired chondrogenesis. Has2cko limbs show less capacity for mesenchymal condensation with mislocalized distributions of chondroitin sulfate proteoglycans (CSPGs), aggrecan and link protein. Has2cko limb phenotype displays striking resemblance to mutants with defective chondroitin sulfation suggesting tight developmental control of HA on CSPG function. Together, our study identifies Has2 as a novel downstream target of Shh signaling required for joint patterning and chondrogenesis.

During embryonic development, undifferentiated progenitor cells balance the generation of additional progenitor cells with differentiation. Within the developing limb, cartilage cells differentiate from mesodermal progenitors in an ordered process that results in the specification of the correct number of appropriately sized skeletal elements. The internal pathways by which these cells maintain an undifferentiated state while preserving their capacity to differentiate is unknown. Here, we report that the arginine methyltransferase PRMT5 has a crucial role in maintaining progenitor cells. Mouse embryonic buds lacking PRMT5 have severely truncated bones with wispy digits lacking joints. This novel phenotype is caused by widespread cell death that includes mesodermal progenitor cells that have begun to precociously differentiate into cartilage cells. We propose that PRMT5 maintains progenitor cells through its regulation of Bmp4 Intriguingly, adult and embryonic stem cells also require PRMT5 for maintaining pluripotency, suggesting that similar mechanisms might regulate lineage-restricted progenitor cells during organogenesis.

Although previous studies suggest that exposure to traffic-related pollution during childhood increases the risk of childhood overweight or obesity (COWO), the role of early life exposure to fine particulate matter (aerodynamic diameter <2.5 μm; PM2.5) and its joint effect with the mother’s prepregnancy body mass index (MPBMI) on COWO remain unclear.

How distinct transcriptional programs are enacted to generate cellular heterogeneity and plasticity, and enable complex fate decisions are important open questions. One key regulator is the cell's epigenome state that drives distinct transcriptional programs by regulating chromatin accessibility. Genome-wide chromatin accessibility measurements can impart insights into regulatory sequences (in)accessible to DNA-binding proteins at a single-cell resolution. This review outlines molecular methods and bioinformatic tools for capturing cell-to-cell chromatin variation using single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) in a scalable fashion. It also covers joint profiling of chromatin with transcriptome/proteome measurements, computational strategies to integrate multi-omic measurements, and predictive bioinformatic tools to infer chromatin accessibility from single-cell transcriptomic datasets. Methodological refinements that increase power for cell discovery through robust chromatin coverage and integrate measurements from multiple modalities will further expand our understanding of gene regulation during homeostasis and disease.

Nutrient availability and stresses impact a cell's decision to enter a growth state or a quiescent state. Acetyl-CoA stimulates cell growth under nutrient-limiting conditions, but how cells generate acetyl-CoA under starvation stress is less understood. Here, we show that general stress response factors, Msn2 and Msn4, function as master transcriptional regulators of yeast glycolysis via directly binding and activating genes encoding glycolytic enzymes. Yeast cells lacking Msn2 and Msn4 exhibit prevalent repression of glycolytic genes and a significant delay of acetyl-CoA accumulation and reentry into growth from quiescence. Thus Msn2/4 exhibit a dual role in activating carbohydrate metabolism genes and stress response genes. These results suggest a possible mechanism by which starvation-induced stress response factors may prime quiescent cells to reenter growth through glycolysis when nutrients are limited.

COVID-19 mRNA vaccines elicit strong T and B cell responses to the SARS-CoV-2 spike glycoprotein in both SARS-CoV-2 naïve and experienced patients. However, it is unknown whether the post-vaccine CD4+ T cell responses seen in patients with a history of COVID-19 are due to restimulation of T cell clonotypes that were first activated during natural infection or if they are the result of new clones activated by the vaccine.