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JOURNAL ARTICLE
Paolo Cadinu, Kisha N Sivanathan, Aditya Misra, Rosalind J Xu, Davide Mangani, Evan Yang, Joseph M Rone, Katherine Tooley, Yoon-Chul Kye, Lloyd Bod, Ludwig Geistlinger, Tyrone Lee, Randall T Mertens, Noriaki Ono, Gang Wang, Liliana Sanmarco, Francisco J Quintana, Ana C Anderson, Vijay K Kuchroo, Jeffrey R Moffitt, Roni Nowarski
Gut inflammation involves contributions from immune and non-immune cells, whose interactions are shaped by the spatial organization of the healthy gut and its remodeling during inflammation. The crosstalk between fibroblasts and immune cells is an important axis in this process, but our understanding has been challenged by incomplete cell-type definition and biogeography. To address this challenge, we used multiplexed error-robust fluorescence in situ hybridization (MERFISH) to profile the expression of 940 genes in 1...
April 1, 2024: Cell
#2
JOURNAL ARTICLE
Clarence K Mah, Noorsher Ahmed, Nicole A Lopez, Dylan C Lam, Avery Pong, Alexander Monell, Colin Kern, Yuanyuan Han, Gino Prasad, Anthony J Cesnik, Emma Lundberg, Quan Zhu, Hannah Carter, Gene W Yeo
The spatial organization of molecules in a cell is essential for their functions. While current methods focus on discerning tissue architecture, cell-cell interactions, and spatial expression patterns, they are limited to the multicellular scale. We present Bento, a Python toolkit that takes advantage of single-molecule information to enable spatial analysis at the subcellular scale. Bento ingests molecular coordinates and segmentation boundaries to perform three analyses: defining subcellular domains, annotating localization patterns, and quantifying gene-gene colocalization...
April 2, 2024: Genome Biology
#3
JOURNAL ARTICLE
Stefano Nardone, Roberto De Luca, Antonino Zito, Nataliya Klymko, Dimitris Nicoloutsopoulos, Oren Amsalem, Cory Brannigan, Jon M Resch, Christopher L Jacobs, Deepti Pant, Molly Veregge, Harini Srinivasan, Ryan M Grippo, Zongfang Yang, Mark L Zeidel, Mark L Andermann, Kenneth D Harris, Linus T Tsai, Elda Arrigoni, Anne M J Verstegen, Clifford B Saper, Bradford B Lowell
The "dorsal pons", or "dorsal pontine tegmentum" (dPnTg), is part of the brainstem. It is a complex, densely packed region whose nuclei are involved in regulating many vital functions. Notable among them are the parabrachial nucleus, the Kölliker Fuse, the Barrington nucleus, the locus coeruleus, and the dorsal, laterodorsal, and ventral tegmental nuclei. In this study, we applied single-nucleus RNA-seq (snRNA-seq) to resolve neuronal subtypes based on their unique transcriptional profiles and then used multiplexed error robust fluorescence in situ hybridization (MERFISH) to map them spatially...
March 4, 2024: Nature Communications
#4
JOURNAL ARTICLE
Eric D Sun, Rong Ma, Paloma Navarro Negredo, Anne Brunet, James Zou
Whole-transcriptome spatial profiling of genes at single-cell resolution remains a challenge. To address this limitation, spatial gene expression prediction methods have been developed to infer the spatial expression of unmeasured transcripts, but the quality of these predictions can vary greatly. Here we present Transcript Imputation with Spatial Single-cell Uncertainty Estimation (TISSUE) as a general framework for estimating uncertainty for spatial gene expression predictions and providing uncertainty-aware methods for downstream inference...
February 12, 2024: Nature Methods
#5
JOURNAL ARTICLE
Zhen-Hao Guo, Yan-Bin Wang, Siguo Wang, Qinhu Zhang, De-Shuang Huang
The advent of single-cell sequencing technologies has revolutionized cell biology studies. However, integrative analyses of diverse single-cell data face serious challenges, including technological noise, sample heterogeneity, and different modalities and species. To address these problems, we propose scCorrector, a variational autoencoder-based model that can integrate single-cell data from different studies and map them into a common space. Specifically, we designed a Study Specific Adaptive Normalization for each study in decoder to implement these features...
January 22, 2024: Briefings in Bioinformatics
#6
JOURNAL ARTICLE
Lifei Wang, Rui Nie, Xuexia Miao, Yankai Cai, Anqi Wang, Hanwen Zhang, Jiang Zhang, Jun Cai
BACKGROUND: With the development of single-cell technology, many cell traits can be measured. Furthermore, the multi-omics profiling technology could jointly measure two or more traits in a single cell simultaneously. In order to process the various data accumulated rapidly, computational methods for multimodal data integration are needed. RESULTS: Here, we present inClust+, a deep generative framework for the multi-omics. It's built on previous inClust that is specific for transcriptome data, and augmented with two mask modules designed for multimodal data processing: an input-mask module in front of the encoder and an output-mask module behind the decoder...
January 24, 2024: BMC Bioinformatics
#7
JOURNAL ARTICLE
Michael I Miller, Alain Trouvé, Laurent Younes
Advances in the development of largely automated microscopy methods such as MERFISH for imaging cellular structures in mouse brains are providing spatial detection of micron resolution gene expression. While there has been tremendous progress made in the field of Computational Anatomy (CA) to perform diffeomorphic mapping technologies at the tissue scales for advanced neuroinformatic studies in common coordinates, integration of molecular- and cellular-scale populations through statistical averaging via common coordinates remains yet unattained...
December 23, 2023: Medical Image Analysis
#8
JOURNAL ARTICLE
Huiping Shi, Liang Gao, Nicole Kirby, Bojing Shao, Xindi Shan, Mariko Kudo, Robert Silasi, Michael J McDaniel, Meixiang Zhou, Samuel McGee, Wei Jing, Florea Lupu, Audrey Cleuren, James N George, Lijun Xia
Although it is caused by a single nucleotide mutation in the -globin gene, sickle cell anemia (SCA) is a systemic disease with complex, incompletely elucidated pathologies. The mononuclear phagocyte system plays critical roles in SCA pathophysiology. However, how heterogeneous populations of hepatic macrophages contribute to SCA remains unclear. Using a combination of single-cell RNA sequencing and spatial transcriptomics via multiplexed error-robust fluorescence in situ hybridization (MERFISH), we identified distinct macrophage populations with diversified origins and biological functions in SCA mouse liver...
December 24, 2023: Blood
#9
Kevin Johnston, Bereket B Berackey, Kristine Minh Tran, Alon Gelber, Zhaoxia Yu, Grant MacGregor, Eran A Mukamel, Zhiqun Tan, Kim Green, Xiangmin Xu
INTRODUCTION The R47H missense mutation of the TREM2 gene is a strong risk factor for development of Alzheimer's Disease. We investigate cell-type-specific spatial transcriptomic changes induced by the Trem2 R47H mutation to determine the impacts of this mutation on transcriptional dysregulation. METHODS We profiled 15 mouse brain sections consisting of wild-type, Trem2 R47H , 5xFAD and Trem2 R47H ; 5xFAD genotypes using MERFISH spatial transcriptomics. Single-cell spatial transcriptomics and neuropathology data were analyzed using our custom pipeline to identify plaque and Trem2 R47H induced transcriptomic dysregulation...
December 7, 2023: Research Square
#10
JOURNAL ARTICLE
Ely Cheikh Boussaty, Neil Tedeschi, Mark Novotny, Yuzuru Ninoyu, Eric Du, Clara Draf, Yun Zhang, Uri Manor, Richard H Scheuermann, Rick Friedman
Age-related hearing loss (ARHL) is the most common cause of hearing loss and one of the most prevalent conditions affecting the elderly worldwide. Despite evidence from our lab and others about its polygenic nature, little is known about the specific genes, cell types, and pathways involved in ARHL, impeding the development of therapeutic interventions. In this manuscript, we describe, for the first time, the complete cell-type specific transcriptome of the aging mouse cochlea using snRNA-seq in an outbred mouse model in relation to auditory threshold variation...
2023: Frontiers in Cellular Neuroscience
#11
JOURNAL ARTICLE
Zizhen Yao, Cindy T J van Velthoven, Michael Kunst, Meng Zhang, Delissa McMillen, Changkyu Lee, Won Jung, Jeff Goldy, Aliya Abdelhak, Matthew Aitken, Katherine Baker, Pamela Baker, Eliza Barkan, Darren Bertagnolli, Ashwin Bhandiwad, Cameron Bielstein, Prajal Bishwakarma, Jazmin Campos, Daniel Carey, Tamara Casper, Anish Bhaswanth Chakka, Rushil Chakrabarty, Sakshi Chavan, Min Chen, Michael Clark, Jennie Close, Kirsten Crichton, Scott Daniel, Peter DiValentin, Tim Dolbeare, Lauren Ellingwood, Elysha Fiabane, Timothy Fliss, James Gee, James Gerstenberger, Alexandra Glandon, Jessica Gloe, Joshua Gould, James Gray, Nathan Guilford, Junitta Guzman, Daniel Hirschstein, Windy Ho, Marcus Hooper, Mike Huang, Madie Hupp, Kelly Jin, Matthew Kroll, Kanan Lathia, Arielle Leon, Su Li, Brian Long, Zach Madigan, Jessica Malloy, Jocelin Malone, Zoe Maltzer, Naomi Martin, Rachel McCue, Ryan McGinty, Nicholas Mei, Jose Melchor, Emma Meyerdierks, Tyler Mollenkopf, Skyler Moonsman, Thuc Nghi Nguyen, Sven Otto, Trangthanh Pham, Christine Rimorin, Augustin Ruiz, Raymond Sanchez, Lane Sawyer, Nadiya Shapovalova, Noah Shepard, Cliff Slaughterbeck, Josef Sulc, Michael Tieu, Amy Torkelson, Herman Tung, Nasmil Valera Cuevas, Shane Vance, Katherine Wadhwani, Katelyn Ward, Boaz Levi, Colin Farrell, Rob Young, Brian Staats, Ming-Qiang Michael Wang, Carol L Thompson, Shoaib Mufti, Chelsea M Pagan, Lauren Kruse, Nick Dee, Susan M Sunkin, Luke Esposito, Michael J Hawrylycz, Jack Waters, Lydia Ng, Kimberly Smith, Bosiljka Tasic, Xiaowei Zhuang, Hongkui Zeng
The mammalian brain consists of millions to billions of cells that are organized into many cell types with specific spatial distribution patterns and structural and functional properties1-3 . Here we report a comprehensive and high-resolution transcriptomic and spatial cell-type atlas for the whole adult mouse brain. The cell-type atlas was created by combining a single-cell RNA-sequencing (scRNA-seq) dataset of around 7 million cells profiled (approximately 4.0 million cells passing quality control), and a spatial transcriptomic dataset of approximately 4...
December 2023: Nature
#12
Stefano Nardone, Roberto De Luca, Antonino Zito, Nataliya Klymko, Dimitris Nicoloutsopoulos, Oren Amsalem, Cory Brannigan, Jon M Resch, Christopher L Jacobs, Deepti Pant, Molly Veregge, Harini Srinivasan, Ryan M Grippo, Zongfang Yang, Mark L Zeidel, Mark L Andermann, Kenneth D Harris, Linus T Tsai, Elda Arrigoni, Anne M J Verstegen, Clifford B Saper, Bradford B Lowell
The "dorsal pons", or "dorsal pontine tegmentum" (dPnTg), is part of the brainstem. It is a complex, densely packed region whose nuclei are involved in regulating many vital functions. Notable among them are the parabrachial nucleus, the Kölliker Fuse, the Barrington nucleus, the locus coeruleus, and the dorsal, laterodorsal, and ventral tegmental nuclei. In this study, we applied single-nucleus RNA-seq (snRNA-seq) to resolve neuronal subtypes based on their unique transcriptional profiles and then used multiplexed error robust fluorescence in situ hybridization (MERFISH) to map them spatially...
November 17, 2023: bioRxiv
#13
JOURNAL ARTICLE
Chanyoung Park, Kwadwo E Owusu-Boaitey, Giselle M Valdes, Peter W Reddien
Regeneration requires mechanisms for producing a wide array of cell types. Neoblasts are stem cells in the planarian Schmidtea mediterranea that undergo fate specification to produce over 125 adult cell types. Fate specification in neoblasts can be regulated through expression of fate-specific transcription factors. We utilize multiplexed error-robust fluorescence in situ hybridization (MERFISH) and whole-mount FISH to characterize fate choice distribution of stem cells within planarians. Fate choices are often made distant from target tissues and in a highly intermingled manner, with neighboring neoblasts frequently making divergent fate choices for tissues of different location and function...
November 16, 2023: Nature Communications
#14
Jongsu Choi, Jin Li, Salma Ferdous, Qingnan Liang, Jeffrey R Moffitt, Rui Chen
No abstract text is available yet for this article.
September 28, 2023: Nature Communications
#15
JOURNAL ARTICLE
Cecilia Cisar, Nicholas Keener, Mathew Ruffalo, Benedict Paten
High-throughput spatial transcriptomics has emerged as a powerful tool for investigating the spatial distribution of mRNA expression and its effects on cellular function. There is a lack of standardized tools for analyzing spatial transcriptomics data, leading many groups to write their own in-house tools that are often poorly documented and not generalizable. To address this, we have expanded and improved the starfish library and used those tools to create PIPEFISH, a semi-automated and generalizable pipeline that performs transcript annotation for fluorescence in situ hybridization (FISH)-based spatial transcriptomics...
September 13, 2023: Cell Genom
#16
Mingze Dong, Harriet Kluger, Rong Fan, Yuval Kluger
Spatial omics analyze gene expression and interaction dynamics in relation to tissue structure and function. However, existing methods cannot model the intrinsic and spatial-induced variation in spatial omics data, thus failing to identify true spatial interaction effects. Here, we present Spatial Interaction Modeling using Variational Inference (SIMVI), an annotation-free framework that disentangles cell intrinsic and spatial-induced latent variables for modeling gene expression in spatial omics data. SIMVI enables novel downstream analyses, such as clustering and differential expression analysis based on disentangled representations, spatial effect (SE) identification, SE interpretation, and transfer learning on new measurements / modalities...
August 30, 2023: bioRxiv
#17
JOURNAL ARTICLE
Jongsu Choi, Jin Li, Salma Ferdous, Qingnan Liang, Jeffrey R Moffitt, Rui Chen
The visual signal processing in the retina requires the precise organization of diverse neuronal types working in concert. While single-cell omics studies have identified more than 120 different neuronal subtypes in the mouse retina, little is known about their spatial organization. Here, we generated the single-cell spatial atlas of the mouse retina using multiplexed error-robust fluorescence in situ hybridization (MERFISH). We profiled over 390,000 cells and identified all major cell types and nearly all subtypes through the integration with reference single-cell RNA sequencing (scRNA-seq) data...
August 15, 2023: Nature Communications
#18
JOURNAL ARTICLE
Peter Androvic, Martina Schifferer, Katrin Perez Anderson, Ludovico Cantuti-Castelvetri, Hanyi Jiang, Hao Ji, Lu Liu, Garyfallia Gouna, Stefan A Berghoff, Simon Besson-Girard, Johanna Knoferle, Mikael Simons, Ozgun Gokce
Understanding the complexity of cellular function within a tissue necessitates the combination of multiple phenotypic readouts. Here, we developed a method that links spatially-resolved gene expression of single cells with their ultrastructural morphology by integrating multiplexed error-robust fluorescence in situ hybridization (MERFISH) and large area volume electron microscopy (EM) on adjacent tissue sections. Using this method, we characterized in situ ultrastructural and transcriptional responses of glial cells and infiltrating T-cells after demyelinating brain injury in male mice...
July 11, 2023: Nature Communications
#19
JOURNAL ARTICLE
Qihuang Zhang, Shunzhou Jiang, Amelia Schroeder, Jian Hu, Kejie Li, Baohong Zhang, David Dai, Edward B Lee, Rui Xiao, Mingyao Li
Single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of cellular heterogeneity in health and disease. However, the lack of physical relationships among dissociated cells has limited its applications. To address this issue, we present CeLEry (Cell Location recovEry), a supervised deep learning algorithm that leverages gene expression and spatial location relationships learned from spatial transcriptomics to recover the spatial origins of cells in scRNA-seq. CeLEry has an optional data augmentation procedure via a variational autoencoder, which improves the method's robustness and allows it to overcome noise in scRNA-seq data...
July 8, 2023: Nature Communications
#20
JOURNAL ARTICLE
Mihir Bafna, Hechen Li, Xiuwei Zhang
MOTIVATION: Gene regulatory networks (GRNs) in a cell provide the tight feedback needed to synchronize cell actions. However, genes in a cell also take input from, and provide signals to other neighboring cells. These cell-cell interactions (CCIs) and the GRNs deeply influence each other. Many computational methods have been developed for GRN inference in cells. More recently, methods were proposed to infer CCIs using single cell gene expression data with or without cell spatial location information...
June 30, 2023: Bioinformatics
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