scholarly journals Alignment and Integration of Spatial Transcriptomics Data

2021 ◽  
Author(s):  
Ron Zeira ◽  
Max Land ◽  
Benjamin J. Raphael
Keyword(s):  
Gene Expression ◽  
Spatial Organization ◽  
Optimal Transport ◽  
Single Layer ◽  
Pairwise Alignment ◽  
Spatial Location ◽  
Low Rank ◽  
Tissue Slices ◽  
Adjacent Tissue ◽  
Expression Matrix

AbstractSpatial transcriptomics (ST) is a new technology that measures mRNA expression across thousands of spots on a tissue slice, while preserving information about the spatial location of spots. ST is typically applied to several replicates from adjacent slices of a tissue. However, existing methods to analyze ST data do not take full advantage of the similarity in both gene expression and spatial organization across these replicates. We introduce a new method PASTE (Probabilistic Alignment of ST Experiments) to align and integrate ST data across adjacent tissue slices leveraging both transcriptional similarity and spatial distances between spots. First, we formalize and solve the problem of pairwise alignment of ST data from adjacent tissue slices, or layers, using Fused Gromov-Wasserstein Optimal Transport (FGW-OT), which accounts for variability in the composition and spatial location of the spots on each layer. From these pairwise alignments, we construct a 3D representation of the tissue. Next, we introduce the problem of simultaneous alignment and integration of multiple ST layers into a single layer with a low rank gene expression matrix. We derive an algorithm to solve the problem by alternating between solving FGW-OT instances and solving a Non-negative Matrix Factorization (NMF) of a weighted expression matrix. We show on both simulated and real ST datasets that PASTE accurately aligns spots across adjacent layers and accurately estimates a consensus expression matrix from multiple ST layers. PASTE outperforms integration methods that rely solely on either transcriptional similarity or spatial similarity, demonstrating the advantages of combining both types of information.Code availabilitySoftware is available at https://github.com/raphael-group/paste

scholarly journals Multi-resolution deconvolution of spatial transcriptomics data reveals continuous patterns of inflammation

2021 ◽  
Author(s):  
Romain Lopez ◽  
Baoguo Li ◽  
Hadas Keren-Shaul ◽  
Pierre Boyeau ◽  
Merav Kedmi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Mammalian Cells ◽  
Spatial Organization ◽  
Probabilistic Method ◽  
Joint Analysis ◽  
Mouse Tumor ◽  
Cell Type ◽  
Tissue Slices ◽  
The Way

The function of mammalian cells is largely influenced by their tissue microenvironment. Advances in spatial transcriptomics open the way for studying these important determinants of cellular function by enabling a transcriptome-wide evaluation of gene expression in situ. A critical limitation of the current technologies, however, is that their resolution is limited to niches (spots) of sizes well beyond that of a single cell, thus providing measurements for cell aggregates which may mask critical interactions between neighboring cells of different types. While joint analysis with single-cell RNA-sequencing (scRNA-seq) can be leveraged to alleviate this problem, current analyses are limited to a discrete view of cell type proportion inside every spot. This limitation becomes critical in the common case where, even within a cell type, there is a continuum of cell states that cannot be clearly demarcated but reflects important differences in the way cells function and interact with their surroundings. To address this, we developed Deconvolution of Spatial Transcriptomics profiles using Variational Inference (DestVI), a probabilistic method for multi-resolution analysis for spatial transcriptomics that explicitly models continuous variation within cell types. Using simulations, we demonstrate that DestVI is capable of providing higher resolution compared to the existing methods and that it can estimate gene expression by every cell type inside every spot. We then introduce an automated pipeline that uses DestVI for analysis of single tissue slices and comparison between tissues. We apply this pipeline to study the immune crosstalk within lymph nodes to infection and explore the spatial organization of a mouse tumor model. In both cases, we demonstrate that DestVI can provide a high resolution and accurate spatial characterization of the cellular organization of these tissues, and that it is capable of identifying important cell-type-specific changes in gene expression - between different tissue regions or between conditions. DestVI is available as an open-source software package in the scvi-tools codebase (https://scvi-tools.org).

scholarly journals A Sparse and Low-Rank Regression Model for Identifying the Relationships Between DNA Methylation and Gene Expression Levels in Gastric Cancer and the Prediction of Prognosis

Genes ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 854
Author(s):  
Yishu Wang ◽  
Lingyun Xu ◽  
Dongmei Ai
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Dna Methylation ◽  
Regression Model ◽  
The Cancer Genome Atlas ◽  
Low Rank ◽  
Expression Levels ◽  
Rank Regression ◽  
Prediction Of Prognosis ◽  
Gene Expression Levels

DNA methylation is an important regulator of gene expression that can influence tumor heterogeneity and shows weak and varying expression levels among different genes. Gastric cancer (GC) is a highly heterogeneous cancer of the digestive system with a high mortality rate worldwide. The heterogeneous subtypes of GC lead to different prognoses. In this study, we explored the relationships between DNA methylation and gene expression levels by introducing a sparse low-rank regression model based on a GC dataset with 375 tumor samples and 32 normal samples from The Cancer Genome Atlas database. Differences in the DNA methylation levels and sites were found to be associated with differences in the expressed genes related to GC development. Overall, 29 methylation-driven genes were found to be related to the GC subtypes, and in the prognostic model, we explored five prognoses related to the methylation sites. Finally, based on a low-rank matrix, seven subgroups were identified with different methylation statuses. These specific classifications based on DNA methylation levels may help to account for heterogeneity and aid in personalized treatments.

scholarly journals Chromatin loop anchors contain core structural components of the gene expression machinery in maize

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Stéphane Deschamps ◽  
John A. Crow ◽  
Nadia Chaidir ◽  
Brooke Peterson-Burch ◽  
Sunil Kumar ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Resolution ◽  
Transcriptional Activity ◽  
Spatial Organization ◽  
Regulatory Elements ◽  
Open Chromatin ◽  
Maize Genome ◽  
Chromatin Loop ◽  
Structural Components ◽  
Chromatin Loops

Abstract Background Three-dimensional chromatin loop structures connect regulatory elements to their target genes in regions known as anchors. In complex plant genomes, such as maize, it has been proposed that loops span heterochromatic regions marked by higher repeat content, but little is known on their spatial organization and genome-wide occurrence in relation to transcriptional activity. Results Here, ultra-deep Hi-C sequencing of maize B73 leaf tissue was combined with gene expression and open chromatin sequencing for chromatin loop discovery and correlation with hierarchical topologically-associating domains (TADs) and transcriptional activity. A majority of all anchors are shared between multiple loops from previous public maize high-resolution interactome datasets, suggesting a highly dynamic environment, with a conserved set of anchors involved in multiple interaction networks. Chromatin loop interiors are marked by higher repeat contents than the anchors flanking them. A small fraction of high-resolution interaction anchors, fully embedded in larger chromatin loops, co-locate with active genes and putative protein-binding sites. Combinatorial analyses indicate that all anchors studied here co-locate with at least 81.5% of expressed genes and 74% of open chromatin regions. Approximately 38% of all Hi-C chromatin loops are fully embedded within hierarchical TAD-like domains, while the remaining ones share anchors with domain boundaries or with distinct domains. Those various loop types exhibit specific patterns of overlap for open chromatin regions and expressed genes, but no apparent pattern of gene expression. In addition, up to 63% of all unique variants derived from a prior public maize eQTL dataset overlap with Hi-C loop anchors. Anchor annotation suggests that < 7% of all loops detected here are potentially devoid of any genes or regulatory elements. The overall organization of chromatin loop anchors in the maize genome suggest a loop modeling system hypothesized to resemble phase separation of repeat-rich regions. Conclusions Sets of conserved chromatin loop anchors mapping to hierarchical domains contains core structural components of the gene expression machinery in maize. The data presented here will be a useful reference to further investigate their function in regard to the formation of transcriptional complexes and the regulation of transcriptional activity in the maize genome.

scholarly journals EPCO-31. EPIGENOMIC INTRATUMORAL HETEROGENEITY OF GLIOBLASTOMA IN THREE-DIMENSIONAL SPACE

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii76-ii76
Author(s):  
Radhika Mathur ◽  
Sriranga Iyyanki ◽  
Stephanie Hilz ◽  
Chibo Hong ◽  
Joanna Phillips ◽  
...  
Keyword(s):  
Spatial Organization ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Spatial Location ◽  
Therapy Resistance ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Intratumoral Heterogeneity ◽  
Tumor Evolution ◽  
Open Chromatin

Abstract Treatment failure in glioblastoma is often attributed to intratumoral heterogeneity (ITH), which fosters tumor evolution and generation of therapy-resistant clones. While ITH in glioblastoma has been well-characterized at the genomic and transcriptomic levels, the extent of ITH at the epigenomic level and its biological and clinical significance are not well understood. In collaboration with neurosurgeons, neuropathologists, and biomedical imaging experts, we have established a novel topographical approach towards characterizing epigenomic ITH in three-dimensional (3-D) space. We utilize pre-operative MRI scans to define tumor volume and then utilize 3-D surgical neuro-navigation to intra-operatively acquire 10+ samples representing maximal anatomical diversity. The precise spatial location of each sample is mapped by 3-D coordinates, enabling tumors to be visualized in 360-degrees and providing unprecedented insight into their spatial organization and patterning. For each sample, we conduct assay for transposase-accessible chromatin using sequencing (ATAC-Seq), which provides information on the genomic locations of open chromatin, DNA-binding proteins, and individual nucleosomes at nucleotide resolution. We additionally conduct whole-exome sequencing and RNA sequencing for each spatially mapped sample. Integrative analysis of these datasets reveals distinct patterns of chromatin accessibility within glioblastoma tumors, as well as their associations with genetically defined clonal expansions. Our analysis further reveals how differences in chromatin accessibility within tumors reflect underlying transcription factor activity at gene regulatory elements, including both promoters and enhancers, and drive expression of particular gene expression sets, including neuronal and immune programs. Collectively, this work provides the most comprehensive characterization of epigenomic ITH to date, establishing its importance for driving tumor evolution and therapy resistance in glioblastoma. As a resource for further investigation, we have provided our datasets on an interactive data sharing platform – The 3D Glioma Atlas – that enables 360-degree visualization of both genomic and epigenomic ITH.

The gene expression matrix: Towards the extraction of genetic network architectures

1997 ◽  
Vol 30 (3) ◽  
pp. 1815-1824 ◽  
Author(s):  
Roland Somogyi ◽  
Stefanie Fuhrman ◽  
Manor Askenazi ◽  
Andy Wuensche
Keyword(s):  
Gene Expression ◽  
Genetic Network ◽  
Network Architectures ◽  
Gene Expression Matrix ◽  
Expression Matrix

Combinatorial control of the bradykinin B2 receptor promoter by p53, CREB, KLF-4, and CBP: implications for terminal nephron differentiation

2005 ◽  
Vol 288 (5) ◽  
pp. F899-F909 ◽  
Author(s):  
Zubaida Saifudeen ◽  
Susana Dipp ◽  
Hao Fan ◽  
Samir S. El-Dahr
Keyword(s):  
Gene Expression ◽  
Transcription Factors ◽  
Dna Binding ◽  
Spatial Organization ◽  
Kidney Development ◽  
Collecting Duct ◽  
Proximal Promoter ◽  
Bradykinin B2 Receptor ◽  
Nephron Differentiation ◽  
Terminal Nephron

Despite a wealth of knowledge regarding the early steps of epithelial differentiation, little is known about the mechanisms responsible for terminal nephron differentiation. The bradykinin B2 receptor (B2R) regulates renal function and integrity, and its expression is induced during terminal nephron differentiation. This study investigates the transcriptional regulation of the B2R during kidney development. The rat B2R 5′-flanking region has a highly conserved cis-acting enhancer in the proximal promoter consisting of contiguous binding sites for the transcription factors cAMP response element binding protein (CREB), p53, and Krüppel-like factor (KLF-4). The B2R enhancer drives reporter gene expression in inner medullary collecting duct-3 cells but is considerably weaker in other cell types. Site-directed mutagenesis and expression of dominant negative mutants demonstrated the requirement of CREB DNA binding and Ser-133 phosphorylation for optimal enhancer function. Moreover, helical phasing experiments showed that disruption of the spatial organization of the enhancer inhibits B2R promoter activity. Several lines of evidence indicate that cooperative interactions among the three transcription factors occur in vivo during terminal nephron differentiation: 1) CREB, p53, and KLF-4 are coexpressed in B2R-positive differentiating cells; 2) the maturational expression of B2R correlates with CREB/p53/KLF-4 DNA-binding activity; 3) assembly of CREB, p53, and KLF-4 on chromatin at the endogenous B2R promoter is developmentally regulated and is accompanied by CBP recruitment and histone hyperacetylation; and 4) CREB and p53 occupancy of the B2R enhancer is cooperative. These results demonstrate that combinatorial interactions among the transcription factors, CREB, p53, and KLF-4, and the coactivator CBP, may be critical for the regulation of B2R gene expression during terminal nephron differentiation.

scholarly journals A loop-counting method for covariate-corrected low-rank biclustering of gene-expression and genome-wide association study data

2018 ◽  
Vol 14 (5) ◽  
pp. e1006105 ◽  
Author(s):  
Aaditya V. Rangan ◽  
Caroline C. McGrouther ◽  
John Kelsoe ◽  
Nicholas Schork ◽  
Eli Stahl ◽  
...  
Keyword(s):  
Gene Expression ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Study Data ◽  
Genome Wide Association ◽  
Low Rank ◽  
Counting Method ◽  
Genome Wide

scholarly journals The Toolbox for Untangling Chromosome Architecture in Immune Cells

2021 ◽  
Vol 12 ◽  
Author(s):  
Shuai Liu ◽  
Keji Zhao
Keyword(s):  
Gene Expression ◽  
Immune Cells ◽  
Spatial Organization ◽  
Chromosome Structure ◽  
Immune Cell ◽  
Genome Structure ◽  
Chromosome Architecture ◽  
The Past ◽  
Important Player ◽  
The Way

The code of life is not only encrypted in the sequence of DNA but also in the way it is organized into chromosomes. Chromosome architecture is gradually being recognized as an important player in regulating cell activities (e.g., controlling spatiotemporal gene expression). In the past decade, the toolbox for elucidating genome structure has been expanding, providing an opportunity to explore this under charted territory. In this review, we will introduce the recent advancements in approaches for mapping spatial organization of the genome, emphasizing applications of these techniques to immune cells, and trying to bridge chromosome structure with immune cell activities.

scholarly journals Phosphorylation-dependent mitotic SUMOylation drives nuclear envelope–chromatin interactions

2021 ◽  
Vol 220 (12) ◽  
Author(s):  
Christopher Ptak ◽  
Natasha O. Saik ◽  
Ashwini Premashankar ◽  
Diego L. Lapetina ◽  
John D. Aitchison ◽  
...  
Keyword(s):  
Gene Expression ◽  
Nuclear Envelope ◽  
Spatial Organization ◽  
G1 Phase ◽  
Nuclear Pore ◽  
Nuclear Pore Complexes ◽  
Chromatin Binding ◽  
Chromatin Interactions ◽  
Sumo Ligase ◽  
Pore Complexes

In eukaryotes, chromatin binding to the inner nuclear membrane (INM) and nuclear pore complexes (NPCs) contributes to spatial organization of the genome and epigenetic programs important for gene expression. In mitosis, chromatin–nuclear envelope (NE) interactions are lost and then formed again as sister chromosomes segregate to postmitotic nuclei. Investigating these processes in S. cerevisiae, we identified temporally and spatially controlled phosphorylation-dependent SUMOylation events that positively regulate postmetaphase chromatin association with the NE. Our work establishes a phosphorylation-mediated targeting mechanism of the SUMO ligase Siz2 to the INM during mitosis, where Siz2 binds to and SUMOylates the VAP protein Scs2. The recruitment of Siz2 through Scs2 is further responsible for a wave of SUMOylation along the INM that supports the assembly and anchorage of subtelomeric chromatin at the INM and localization of an active gene (INO1) to NPCs during the later stages of mitosis and into G1-phase.

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