Tree-Based Co-Clustering Identifies Chromatin Accessibility Patterns Associated With Hematopoietic Lineage Structure

Chromatin accessibility, as measured by ATACseq, varies between hematopoietic cell types in different lineages of the hematopoietic differentiation tree, e.g. T cells vs. B cells, but methods that associate variation in chromatin accessibility to the lineage structure of the differentiation tree are lacking. Using an ATACseq dataset recently published by the ImmGen consortium, we construct associations between chromatin accessibility and hematopoietic cell types using a novel co-clustering approach that accounts for the structure of the hematopoietic, differentiation tree. Under a model in which all loci and cell types within a co-cluster have a shared accessibility state, we show that roughly 80% of cell type associated accessibility variation can be captured through 12 cell type clusters and 20 genomic locus clusters, with the cell type clusters reflecting coherent components of the differentiation tree. Using publicly available ChIPseq datasets, we show that our clustering reflects transcription factor binding patterns with implications for regulation across cell types. We show that traditional methods such as hierarchical and kmeans clusterings lead to cell type clusters that are more dispersed on the tree than our tree-based algorithm. We provide a python package, chromcocluster, that implements the algorithms presented.

Cross-tissue single-cell transcriptomics reveals organizing principles of fibroblasts in health and disease

Fibroblasts are non-hematopoietic structural cells that define the architecture of organs, support the homeostasis of tissue-resident cells and play key roles in fibrosis, cancer, autoimmunity and wound healing. Recent studies have described fibroblast heterogeneity within individual tissues. However, the field lacks a definition of fibroblasts at single-cell resolution across tissues in healthy and diseased organs. Here, we integrated single-cell RNA transcriptomic data from ~150,000 fibroblast cells derived from 16 steady- and 11 perturbed-state mouse organs into fibroblast atlases. These data revealed two universal fibroblast cell subtypes, marked by expression of Pi16 or Col15a1, in all tissues; it also revealed discrete subsets of five specialized fibroblast subtypes in steady-state tissues and three activated fibroblast subtypes in perturbed or diseased tissues. These subsets were transcriptionally shaped by microenvironmental context rather than tissue-type alone. Inference of fibroblast lineage structure from the murine steady-state and perturbed-state fibroblast atlases suggested that specialized and activated subtypes are developmentally related to universal tissue-resident fibroblasts. Analysis of human samples revealed that fibroblast subtypes found in mice are conserved between species, including universal fibroblasts and activated phenotypes associated with pathogenicity in human cancer, fibrosis, arthritis and inflammation. In sum, a cross-species and pan-tissue approach to transcriptomics at single-cell resolution enabled us to define the organizing principles of the fibroblast lineage in health and disease.

Establishment and lineage dynamics of the SARS-CoV-2 epidemic in the UK

The UK’s COVID-19 epidemic during early 2020 was one of world’s largest and unusually well represented by virus genomic sampling. Here we reveal the fine-scale genetic lineage structure of this epidemic through analysis of 50,887 SARS-CoV-2 genomes, including 26,181 from the UK sampled throughout the country’s first wave of infection. Using large-scale phylogenetic analyses, combined with epidemiological and travel data, we quantify the size, spatio-temporal origins and persistence of genetically-distinct UK transmission lineages. Rapid fluctuations in virus importation rates resulted in >1000 lineages; those introduced prior to national lockdown tended to be larger and more dispersed. Lineage importation and regional lineage diversity declined after lockdown, while lineage elimination was size-dependent. We discuss the implications of our genetic perspective on transmission dynamics for COVID-19 epidemiology and control.

Establishment & lineage dynamics of the SARS-CoV-2 epidemic in the UK

The UK’s COVID-19 epidemic during early 2020 was one of world’s largest and unusually well represented by virus genomic sampling. Here we reveal the fine-scale genetic lineage structure of this epidemic through analysis of 50,887 SARS-CoV-2 genomes, including 26,181 from the UK sampled throughout the country’s first wave of infection. Using large-scale phylogenetic analyses, combined with epidemiological and travel data, we quantify the size, spatio-temporal origins and persistence of genetically-distinct UK transmission lineages. Rapid fluctuations in virus importation rates resulted in >1000 lineages; those introduced prior to national lockdown were larger and more dispersed. Lineage importation and regional lineage diversity declined after lockdown, whilst lineage elimination was size-dependent. We discuss the implications of our genetic perspective on transmission dynamics for COVID-19 epidemiology and control.

Data Extraction in Malignant Environments

Deliberate or inadvertent escape of classified data is undoubtedly one among the premier extreme security dangers that associations look inside the advanced period. The risk right now stretches out to the private lives: an abundance of private information is out there to interpersonal organizations and great telephone providers and is in a roundabout way exchanged to undependable outsider and fourth gathering applications. amid this work, a bland data genealogy structure LIME (Data Lineage in the Malicious Environment), is utilized for data stream over different elements that take two trademark, guideline parts (i.e., proprietor and buyer). It characterizes the exact security ensures required by such a data heredity component toward recognizable proof of a blameworthy substance, and decide the disentangling non-denial and trustworthiness suspicions. At that point create and break down a totally special dependable data exchange convention between two substances among noxious surroundings by expanding upon unmindful exchange, solid watermarking, and mark natives. At long last, an exploratory investigation to exhibit the helpfulness of convention what's more, apply structure to the important data run projections of learning outsourcing and the informal organizations. In general, LIME(Data Lineage in the Malicious Environment),lineage structure for information exchange, to be a key advance towards accomplishing responsibility by plan.

Strain-level diversity drives alternative community types in millimeter scale granular biofilms

Microbial communities are often highly diverse in their composition, both at the level of coarse-grained taxa such as genera as well as at the level of strains within species. This variability can be driven by both extrinsic factors like temperature, pH, etc., as well as by intrinsic ones, such as demographic fluctuations or ecological interactions. The relative contributions of these factors and the taxonomic level at which they influence community structure remain poorly understood, in part because of the difficulty of identifying true community replicates assembled under the same environmental parameters. Here, we address this problem using an activated granular sludge reactor in which millimeter scale biofilm granules represent true community replicates whose differences in composition are expected to be driven primarily by biotic factors. Using 142 shotgun metagenomes of single biofilm granules we found that, at the commonly used genuslevel resolution, community replicates varied much more in their composition than would be expected from neutral assembly processes. This variation, however, did not translate into any clear partitioning into discrete community types, i.e. the equivalent of enterotypes in the human gut. However, a strong partition into community types did emerge at the strain level for the most abundant organism: strains of Candidatus Accumulibacter that coexisted in the metacommunity--i.e. the reactor--excluded each other within community replicates. Single-granule communities maintained a significant lineage structure, whereby the strain phylogeny of Accumulibacter correlated with the overall species composition of the community, indicating high potential for co-diversification among species and communities. Our results suggest that due to the high functional redundancy and competition between close relatives, alternative community types are most likely observed at the level of recently differentiated genotypes but not higher orders of genetic resolution.

Social Structures in Transition: Applications of Two Theories to Chiefdoms

Status characteristics theory and elementary theory are applied to explain developments through three structural forms that chiefdoms are known to take. Theoretic models find that downward mobility inherent in the first form, the status-lineage structure, destabilizes its system of privilege. As a consequence, high-status actors are motivated to find mechanisms to preserve and enhance privilege. By engaging in hostile relations with other chiefdoms, high-status actors offer protection to low-status others from real or imagined threats. Through that protection, they gain tribute and support. The result is structural change from influence based on status to power exercised through indirect coercion, the second structural form. In settled societies, accumulation through war and selective redistribution contribute to separation of warrior and commoner rankings. That separation leads to the third structural form, direct coercive chiefdom.