SPROUT: spectral sparsification helps restore the spatial structure at single-cell resolution.

Single-cell RNA sequencing thoroughly quantifies the individual cell transcriptomes but renounces the spatial structure. Conversely, recently emerged spatial transcriptomics technologies capture the cellular spatial structure but skimp cell or gene resolutions. Ligand-receptor interactions reveal the potential of cell proximity since they are spatially constrained. Cell-cell affinity values estimated by ligand-receptor interaction can partially represent the structure of cells but falsely include the pseudo affinities between distant or indirectly interacting cells. Here, we develop a software package, SPROUT, to reconstruct the single-cell resolution spatial structure from the transcriptomics data through diminished pseudo ligand-receptor affinities. For spatial data, SPROUT first curates the representative single-cell profiles for each spatial spot from a candidate library, then reduces the pseudo affinities in the intercellular affinity matrix by partial correlation, spectral graph sparsification, and spatial coordinates refinement. SPROUT embeds the estimated interactions into a low-dimensional space with the cross-entropy objective to restore the intercellular structures, which facilitates the discovery of dominant ligand-receptor pairs between neighboring cells at single-cell resolution. SPROUT reconstructed structures achieved shape Pearson correlations ranging from 0.91 to 0.97 on the mouse hippocampus and human organ tumor microenvironment datasets. Furthermore, SPROUT can solely de novo reconstruct the structures at single-cell resolution, i.e., reaching the cell-type proximity correlations of 0.68 and 0.89 between reconstructed and immunohistochemistry-informed spatial structures on a human developing heart dataset and a tumor microenvironment dataset, respectively.

Thin endometrium is associated with the risk of hypertensive disorders of pregnancy in fresh IVF/ICSI embryo transfer cycles: a retrospective cohort study of 9,266 singleton births.

BACKGROUND: Thin endometrial thickness (EMT) has been suggested to be associated with reduced incidence of pregnancy rate after in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) treatment, but the effect of thin endometrium on obstetric outcome is less investigated. This study aims to determine whether EMT affects the incidence of obstetric complications in fresh IVF/ICSI-embryo transfer (ET) cycles. METHODS: We conducted a retrospective cohort study collecting a total of 9266 women who had singleton livebirths after fresh IVF/ICSI-ET treatment cycles at the Center for Reproductive Medicine Affiliated to Shandong University between January 2014 and December 2018. The women were divided into three groups according to the EMT: 544 women with an EMT ≤8 mm, 6234 with an EMT > 8-12 mm, and 2488 with an EMT > 12 mm. The primary outcomes were the incidence of obstetric complications including hypertensive disorders of pregnancy (HDP), gestational diabetes mellitus (GDM), placental abruption, placenta previa, postpartum hemorrhage (PPH) and cesarean section. Multivariable logistic regression analysis was performed to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) for associations between the EMT measured on the day of human chorionic gonadotropin (HCG) trigger and the risk of the outcomes of interest. RESULTS: The HDP incidence rate of pregnant women was highest in EMT ≤ 8 mm group and significantly higher than those in EMT from > 8-12 mm and EMT > 12 mm group, respectively (6.8% versus 3.6 and 3.5%, respectively; P = 0.001). After adjustment for confounding variables by multivariate logistic regression analysis, a thin EMT was still statistically significant associated with an increased risk of HDP. Compared with women with an EMT > 8-12 mm, women with an EMT ≤8 mm had an increased risk of HDP (aOR = 1.853, 95% CI 1.281-2.679, P = 0.001). CONCLUSION: A thin endometrium (≤8 mm) was found to be associated with an increased risk of HDP after adjustment for confounding variables, indicating that the thin endometrium itself is a risk factor for HDP. Obstetricians should remain aware of the possibility of HDP when women with a thin EMT achieve pregnancy through fresh IVF/ICSI-ET treatment cycles.

Single-cell RNA-seq unveils critical regulators of human FOXP3+ regulatory T cell stability.

The heterogeneity and plasticity of T lymphocytes is critical for determining immune response outcomes. Functional regulatory T (Treg) cells are commonly characterized by stable FOXP3 expression and have reported to exhibit heterogeneous phenotypes under inflammatory conditions. However, the interplay between inflammation and Treg cell suppressive activity still remains elusive. Here, we utilized single-cell RNA sequencing to investigate how human Treg cells respond to the pro-inflammatory cytokine interleukin-6 (IL-6). We observed that Treg cells divided into two subpopulations after IL-6 stimulation. TIGIT- unstable Treg cells lost FOXP3 expression and gained an effector-like T cell phenotype, whereas TIGIT+ Treg cells retained robust suppressive function. Single cell transcriptome analysis revealed a spectrum of cellular states of IL-6-stimulated Treg cells and how cytochrome P450 family 1 subfamily A member 1 (CYP1A1) is a crucial regulator of Treg cell suppressive capability and stability. CYP1A1-deficient human Treg cells developed a Th17-like phenotype after IL-6 stimulation. Our findings implicate CYP1A1 as a previously unidentified regulator of Treg cells that may have target potential for clinical application for biotherapies.

Single-cell transcriptomic landscape of nucleated cells in umbilical cord blood.

BACKGROUND: For both pediatric and adult patients, umbilical cord blood (UCB) transplant is a therapeutic option for a variety of hematologic diseases, such as blood cancers, myeloproliferative disorders, genetic diseases, and metabolic disorders. However, the level of cellular heterogeneity and diversity of nucleated cells in UCB has not yet been assessed in an unbiased and systemic fashion. In the present study, nucleated cells from UCB were subjected to single-cell RNA sequencing to simultaneously profile the gene expression signatures of thousands of cells, generating a rich resource for further functional studies. Here, we report the transcriptomes of 17,637 UCB cells, covering 12 major cell types, many of which can be further divided into distinct subpopulations. RESULTS: Pseudotemporal ordering of nucleated red blood cells identifies wave-like activation and suppression of transcription regulators, leading to a polarized cellular state, which may reflect nucleated red blood cell maturation. Progenitor cells in UCB also comprise 2 subpopulations with activation of divergent transcription programs, leading to specific cell fate commitment. Detailed profiling of cytotoxic cell populations unveiled granzymes B and K signatures in natural killer and natural killer T-cell types in UCB. CONCLUSIONS: Taken together, our data form a comprehensive single-cell transcriptomic landscape that reveals previously unrecognized cell types, pathways, and mechanisms of gene expression regulation. These data may contribute to the efficacy and outcome of UCB transplant, broadening the scope of research and clinical innovations.

Efficient and unique cobarcoding of second-generation sequencing reads from long DNA molecules enabling cost-effective and accurate sequencing, haplotyping, and de novo assembly.

Here, we describe single-tube long fragment read (stLFR), a technology that enables sequencing of data from long DNA molecules using economical second-generation sequencing technology. It is based on adding the same barcode sequence to subfragments of the original long DNA molecule (DNA cobarcoding). To achieve this efficiently, stLFR uses the surface of microbeads to create millions of miniaturized barcoding reactions in a single tube. Using a combinatorial process, up to 3.6 billion unique barcode sequences were generated on beads, enabling practically nonredundant cobarcoding with 50 million barcodes per sample. Using stLFR, we demonstrate efficient unique cobarcoding of more than 8 million 20- to 300-kb genomic DNA fragments. Analysis of the human genome NA12878 with stLFR demonstrated high-quality variant calling and phase block lengths up to N50 34 Mb. We also demonstrate detection of complex structural variants and complete diploid de novo assembly of NA12878. These analyses were all performed using single stLFR libraries, and their construction did not significantly add to the time or cost of whole-genome sequencing (WGS) library preparation. stLFR represents an easily automatable solution that enables high-quality sequencing, phasing, SV detection, scaffolding, cost-effective diploid de novo genome assembly, and other long DNA sequencing applications.