Niche Clustering Research Articles

Gene Regulatory Networks Controlling Sinusoidal Hematopoietic Niche Function

The bone marrow sinusoidal vascular niche is important for HSC engraftment and regeneration of hematopoiesis after transplantation, but the epigenetic factors that control these biological functions are undefined. Here, we show that sinusoidal hematopoietic niche functions are controlled by gene regulatory networks (GRNs), involving transcription factors (TFs) that bind to enhancers to regulate corresponding target genes. To characterize sinusoidal niche specific transcriptional and chromatin accessibility states, we performed multimodal single nuclei RNA and ATAC-seq analysis on unsorted zebrafish embryos. We identified 4 niche clusters, including mesenchymal stem cells, fibroblasts, osteoblasts and sinusoidal endothelial cells. Differential RNA transcriptome analysis confirmed the identity of each niche cluster with canonical gene markers for each niche cluster. To examine differential transcriptional accessibility in zebrafish niche clusters, we aggregated co-accessible regions in cells from these clusters. Each cluster demonstrated a unique chromatin accessibility profile with differentially accessible regions. Differential motif activity based on chromatin accessibility analysis further exhibited unique TF motifs activity in sinusoidal endothelial cells. To identify potential regulatory TFs in sinusoidal vascular niche, we predicted TFs based on the TF binding sites accessibility and TF expression. Thus, we identified 3 specific expressed and enriched TFs for sinusoidal vascular niche, including Fli1 (Friend leukemia integration 1), Mef2a (Myocyte enhancer factor 2A) and Mef2c. Next, to investigate genomic regulatory regions that interact with TFs, in which control the transcription of their target genes, we performed random forests and regression trees machine learning methods to infer GRNs. We observed multiple active GRNs in sinusoidal vascular niche, which were predicted to essential for regulating hematopoietic niche development and HSC maintenance, including klf12, egfl7, ebf3 and ldb2. Finally, we examined whether these putative gene regulatory networks were conserved across species and tissue types. We used same approach (single-cell multiome sequencing) on E4-HUVEC cells, a transduced human umbilical vein endothelial cells (HUVEC) with the adenovirus E4ORF1 gene, which was a well-defined model of the human sinusoidal vascular niche. We likewise observed regulatory networks in HUVEC cells. As in zebrafish, GRNs in human sinusoidal cluster consisted of FLI1 and MEF2 family, regulatory regions and their target genes. Our findings reveal that unique sinusoidal vascular niche specific gene regulatory networks, including TFs, regulatory regions and target genes indicate the treatments targeting GRNs may help to facilitate reprogramming of sinusoidal endothelial niche to support HSC homing and regeneration after transplantation.

Emerging niche clustering results from both competition and predation.

Understanding species coexistence has been a central question in ecology for decades, and the notion that competing species need to differ in their ecological niche for stable coexistence has dominated. Recent theoretical and empirical work suggests differently. Species can also escape competitive exclusion by being similar, leading to clusters of species with similar traits. This theory has so far only been explored under competition. By combining mathematical and numerical analyses, we reveal that competition and predation are equally capable to promote clusters of similar species in prey-predator communities, their relative importance being modulated by resource availability. We further show that predation has a stabilizing effect on clustering patterns, making the clusters more diverse. Our results merge different ecological theories and bring new light to the emergent neutrality theory by adding the perspective of trophic interactions. These results open new perspectives to the study of trait distributions in ecological interaction networks.

Phylogenetic and functional trait-based community assembly within Pacific Cyrtandra (Gesneriaceae): Evidence for clustering at multiple spatial scales.

Tropical rainforest communities are often characterized by a small number of species-rich genera that contribute disproportionately to the alpha diversity in these habitats. In the Pacific Basin, there are nearly 200 species of Cyrtandra, most of which are white-flowered woody shrubs that are single-island endemics. Within these island communities, multiple Cyrtandra species are commonly observed to occur sympatrically in wet forest understories, forming swarms of what appear to be ecologically similar taxa. The aim of this study was to determine whether species of these plants are randomly assembled with respect to phylogenetic relatedness and traits that are ecologically relevant. I examined assembly patterns across three Pacific archipelagoes using a combination of 10 functional traits and a well-resolved phylogeny comprising 34 species of Cyrtandra. Coexisting species were found to be more closely related and more phenotypically similar than would be expected by chance. This pattern was observed at both regional (island) and local (site) spatial scales. The retention of phylogenetic signal in floral traits and the strong influence of these traits on the observed degree of phylogenetic clustering may indicate that generalist insect pollinators act as a biotic filter on oceanic islands, driving selection for similar floral morphology among closely related species of Pacific Cyrtandra. Phylogenetic signal was also detected in leaf size, which contributed to niche clustering at both spatial scales. Coupled with a propensity for long-distance dispersal, and the restricted distribution of Cyrtandra to rainforest understories, this finding suggests that environmental filtering along this trait axis may be more important than dispersal limitation in determining species assemblages. This study supports the theory that plant species are not randomly assembled, and instead, that niche-based processes structure biodiversity at regional and local spatial scales in diverse congeneric species assemblages.

Generation of raptor diversity in Europe: linking speciation with climate changes and the ability to migrate.

Europe holds a rich community of diurnal birds of prey, and the highest proportion of transcontinental migratory raptorial species of any landmass. This study will test the hypotheses that the high diversification of the raptor assemblage in Europe is a recent event, that closely related species sharing the same trophic niches can only coexist in sympatry during the breeding period, when food availability is higher, and finally that migration is a function of size, with the smaller species in every trophic group moving further. A consensus molecular phylogeny for the 38 regular breeding species of raptors in Europe was obtained from BirdTree (www.birdtree.org). For the same species, a trophic niche cluster dendrogram was constructed. Size and migratory strategy were introduced in the resulting phylogeny, where trophic groups were also identified. Multispecific trophic groups tended to be composed of reciprocal sister species of different sizes, while monospecific groups (n = 3) were composed of highly specialized species. Many speciation events took place recently, during the glacial cycles of the Quaternary, and size divergence among competing species may be due to character displacement. Nowadays, the smaller species in every trophic group migrate to sub-Saharan Africa. This investigation illustrates how the rich assemblage of diurnal birds of prey in Europe, more diverse and more migratory than, for instance, the North American assemblage at equivalent latitudes, has emerged recently due to the multiplication of look-alike species with similar trophic ecologies, possibly in climate refugia during cold periods.

Identifying COVID-19 Instagram behaviour patterns via a novel network analysis pipeline

Instagram has become one of the most widely used social media platforms globally. As such, the volume of information generated by Instagram users makes it an excellent data mine to study human behaviour. Although researchers have turned to Twitter data to observe the flow of misinformation surrounding the COVID-19 pandemic, there is little to no publication on COVID-19 behaviours on Instagram. To address this knowledge gap, an extensive analysis was conducted on COVID-19-related big data from Instagram. 5,300 global Instagram posts were collected between January 5 and March 20 of 2020, and the associated hashtags were processed using a novel, highly extensible Social Network Analysis pipeline. Eigenvector centrality and weight cluster indexing partitioned the hashtag data into eleven clusters, three of which were studied to reflect public behaviour. The data revealed that the mental health cluster consisted mainly of Instagram business profiles and that these were associated with positive sentiments on COVID-19. It was found that a niche cluster containing conspiracy-related content was primarily created by real Instagram users and was associated with very negative sentiments. A supervised machine learning approach was also used to classify hashtags related to comedy and memes as bot-generated content. For future investigations, it is recommended that a large-scale behavioural analysis of bots and their effects on pandemic information be performed.

Quasi-neutral community assembly: Evidence from niche overlap, phylogenetic, and trait distribution analyses of a subtropical forest in South America

In spite of recent advances, the relative roles of deterministic and stochastic processes in community assembly remains disputed. We tested community assembly hypotheses in a disturbance gradient in a logged mixed conifer-hardwood forest complex in southern Brazil. If abiotic heterogeneity was strong enough (Selection hypothesis), we expected niche clustering and reduced niche overlap between species and between ecological groups, phylogenetic clustering, significant β-diversity departure from a random expectation after controlling for α-diversity variation, and non-random trait distribution due to abiotic filtering and limiting similarity. Null expectations were predicted under the Neutral hypothesis. Under the Quasi-Neutral hypothesis, we expected niche clustering and reduced niche overlap as in the Selection hypothesis, but random phylogenetic distribution, random β-diversity variation, and random trait distribution due to niche-based specialization but weak habitat matching resulting from dispersal limitation and drift. We used a series of null models to provide an integrative evaluation of community assembly including species abundances, environmental preferences, phylogenetic relatedness, and trait distribution. Results supported the Quasi-Neutral hypothesis due to a combination of reduced niche overlap, niche clustering along soil and disturbance gradients, evidence for abiotic filtering of functional traits but absent phylogenetic structure and random β-diversity variation. Support to the Quasi-Neutral hypothesis provides evidence for niche-based species selection along environmental gradients, coupled with poor matches between species distributions and environmental factors due to stochastic processes. It also highlights the importance of an integrative approach to the evaluation of community patterns indicative of assembly processes. Had only a subset of the approaches used been employed and different conclusions would have been reached: niche overlap and trait distribution analyses would have indicated a stronger role for selection, while phylogenetic and abundance analyses would have indicated stochastic community assembly. Future research should include different disturbance regimes along with environmental variation in order to assess the interplay of the different drivers that shape the community assembly process, as well as the potential of the Quasi-Neutral hypothesis as an explanation for the assembly process of complex and species-rich subtropical forests.

Analysis of regional zoobenthos status in the Huai River Basin, China, using two new ecological niche clustering approaches

ABSTRACTTwo new ecological niche clustering approaches are presented in this paper: first, an importance/dominance evaluation model, based on both density and biomass, is devised to evaluate the importance (contribution) of a specific species in its community; second, an integrated index encoding approach is constructed to spatially cluster all dominant species at a sampling site. Two approaches are employed to study ecological niche clustering of the Huai River Basin zoobenthos in order to identify key regions for ecosystem restoration. Results show that habitat changes will significantly impact Corbicula fluminea (Müller), whereas influences on Corbicula nitens (Philippi) will be the least significant. Total phosphorus has the greatest impact on zoobenthos, and high‐concentrated ammonia nitrogen is also detrimental. Decreasing the discharge of both phosphorus and ammonia nitrogen in the Huai River Basin is therefore required to facilitate restoration. Changing habitat parameters has only a limited effect on alteration of zoobenthos structure. The application of these niche clustering approaches has identified priority locations for ecological restoration in the Huai River Basin. Copyright © 2012 John Wiley & Sons, Ltd.

Mining and tracking evolving web user trends from large web server logs

AbstractRecently, online organizations became interested in tracking users' behavior on their websites to better understand and satisfy their needs. In response to this need, web usage mining tools were developed to help them use web logs to discover usage patterns or profiles. However, since website usage logs are being continuously generated, in some cases, amounting to a dynamic data stream, most existing tools are still not able to handle their changing nature or growing size. This paper proposes a scalable framework that is capable of tracking the changing nature of user behavior on a website, and represent it in a set of evolving usage profiles. These profiles can offer the best usage representation of user activity at any given time, and they can be used as an input to higher‐level applications such as a web recommendation system. Our specific aim is to make the hierarchical unsupervised niche clustering (HUNC) algorithm more scalable, and to add integrated profile tracking and cluster‐based validation to it. Our experiments on real web log data confirm the validity of our approach for large data sets that previously could not be handled in one shot. Copyright © 2010 Wiley Periodicals, Inc. Statistical Analysis and Data Mining 3: 106‐125, 2010

AN EVOLUTIONARY APPROACH TO MINING ROBUST MULTI-RESOLUTION WEB PROFILES AND CONTEXT SENSITIVE URL ASSOCIATIONS

We present a technique for simultaneously mining Web navigation patterns and maximally frequent context-sensitive itemsets (URL associations) from the historic user access data stored in Web server logs. A new hierarchical clustering technique that exploits the symbiosis between clusters in feature space and genetic biological niches in nature, called Hierarchical Unsupervised Niche Clustering (H-UNC) is presented. We use H-UNC as part of a complete system of knowledge discovery in Web usage data. Our approach does not necessitate fixing the number of clusters in advance, is insensitive to initialization, can handle noisy data, general non-differentiable similarity measures, and automatically provides profiles at multiple resolution levels. Our experiments show that our algorithm is not only capable of extracting meaningful user profiles on real Web sites, but also discovers associations between distinct URL pages on a site, with no additional cost. Unlike content based association methods, our approach discovers associations between different Web pages based only on the user access patterns and not on the page content. Also, unlike traditional context-blind association discovery methods, H-UNC discovers context-sensitive associations which are only meaningful within a limited context/user profile.

The effects of selected physical and chemical factors on attached diatoms in the Uintah Basin of Utah, U.S.A.

The relationships of diatom species to selected physical and chemical parameters in the streams of the Uintah Basin of Utah were studied through four seasons of 1977–1978. Niche center gradient analysis, cluster analysis and correlation analysis were performed.Achnanthes minutissima, Cyclotella meneghiniana, Cymbella minuta var.latens, Fragilaria capucina, andNavicula secreta var.apiculata appear to be indicator species of high or low levels of certain water quality parameters. Several other species also showed meaningful relationships to selected physical and chemical parameters.