Article
Biochemical Research Methods
Hongcang Gu, Ayush T. Raman, Xiaoxue Wang, Federico Gaiti, Ronan Chaligne, Arman W. Mohammad, Aleksandra Arczewska, Zachary D. Smith, Dan A. Landau, Martin J. Aryee, Alexander Meissner, Andreas Gnirke
Summary: The integration of DNA methylation and transcriptional state within single cells is of broad interest for studying cellular heterogeneity and rare cell populations. The Smart-RRBS protocol combines Smart-seq2 and RRBS to generate paired epigenetic promoter and RNA-expression measurements for approximately 24% of protein-coding genes in typical single cells, and can also be applied to tissue samples comprising hundreds of cells. The protocol, excluding flow sorting of cells and sequencing, takes around 3 days to process up to 192 samples manually and requires basic molecular biology expertise and laboratory equipment.
Article
Biochemistry & Molecular Biology
Artem Nurislamov, Timofey Lagunov, Maria Gridina, Alla Krasikova, Veniamin Fishman
Summary: DNA methylation is an important epigenetic mechanism involved in various genomic processes. This study investigated DNA methylation patterns in chicken diplotene oocytes and found that they closely resemble the genomic distribution observed in somatic tissues.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Biology
Diogo M. Ribeiro, Chaymae Ziyani, Olivier Delaneau
Summary: This study utilizes single-cell datasets to identify gene co-expression in different human cell types. The results show that many co-expressed genes are functionally related and their co-expression is maintained at the protein level. Additionally, the study reveals that co-expressed gene pairs share regulatory elements, suggesting the importance of studying shared regulatory architecture between genes in understanding disease comorbidity.
COMMUNICATIONS BIOLOGY
(2022)
Article
Biotechnology & Applied Microbiology
Simon Mages, Noa Moriel, Inbal Avraham-Davidi, Evan Murray, Jan Watter, Fei Chen, Orit Rozenblatt-Rosen, Johanna Klughammer, Aviv Regev, Mor Nitzan
Summary: Transferring annotations of single-cell-, spatial- and multi-omics data is challenging due to technical limitations and biological variations. We present TACCO, a computational framework for annotation transfer, which utilizes continuous mixtures of cells or molecules to annotate a wide variety of data. TACCO achieves high accuracy while reducing computational requirements and scales to larger datasets.
NATURE BIOTECHNOLOGY
(2023)
Review
Neurosciences
Ethan J. Armand, Junhao Li, Fangming Xie, Chongyuan Luo, Eran A. Mukamel
Summary: Single-cell sequencing technologies provide insights into the diversity and developmental relationships of brain cell types, aiding in the design of tools for targeted functional studies of brain circuit components.
Article
Multidisciplinary Sciences
Euxhen Hasanaj, Jingtao Wang, Arjun Sarathi, Jun Ding, Ziv Bar-Joseph
Summary: Cell type assignment is a major challenge in high throughput single cell data analysis. To address this issue, researchers have developed Cellar, a software tool that provides interactive support for cell type assignment and dataset comparison.
NATURE COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
Hanqing Liu, Jingtian Zhou, Wei Tian, Chongyuan Luo, Anna Bartlett, Andrew Aldridge, Jacinta Lucero, Julia K. Osteen, Joseph R. Nery, Huaming Chen, Angeline Rivkin, Rosa G. Castanon, Ben Clock, Yang Eric Li, Xiaomeng Hou, Olivier B. Poirion, Sebastian Preissl, Antonio Pinto-Duarte, Carolyn O'Connor, Lara Boggeman, Conor Fitzpatrick, Michael Nunn, Eran A. Mukamel, Zhuzhu Zhang, Edward M. Callaway, Bing Ren, Jesse R. Dixon, M. Margarita Behrens, Joseph R. Ecker
Summary: The study comprehensively assessed the epigenomes of different cell types in the mouse brain, revealing the diversity and spatial organization of cell types, as well as the repetitive usage of regulators for distinguishing cell subtypes. By constructing an artificial neural network model, it is possible to accurately predict the cell type and spatial location of individual neurons in the brain.
Article
Biochemical Research Methods
Tim Stuart, Avi Srivastava, Shaista Madad, Caleb A. Lareau, Rahul Satija
Summary: Signac is a comprehensive toolkit for the analysis of single-cell chromatin data, enabling end-to-end analysis and interoperability with the Seurat package for multimodal analysis.
Article
Multidisciplinary Sciences
Javier Rodriguez-Ubreva, Anna Arutyunyan, Marc Jan Bonder, Lucia Del Pino-Molina, Stephen J. Clark, Carlos de la Calle-Fabregat, Luz Garcia-Alonso, Louis-Francois Handfield, Laura Ciudad, Eduardo Andres-Leon, Felix Krueger, Francesc Catala-Moll, Virginia C. Rodriguez-Cortez, Krzysztof Polanski, Lira Mamanova, Stijn van Dongen, Vladimir Yu Kiselev, Maria T. Martinez-Saavedra, Holger Heyn, Javier Martin, Klaus Warnatz, Eduardo Lopez-Granados, Carlos Rodriguez-Gallego, Oliver Stegle, Gavin Kelsey, Roser Vento-Tormo, Esteban Ballestar
Summary: In this study, single-cell omics analyses were performed in CVID-discordant monozygotic twins, revealing epigenetic and transcriptional alterations associated with activation in memory B cells. These findings provide valuable insights into the diagnosis and treatment of CVID patients.
NATURE COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
Yodai Takei, Shiwei Zheng, Jina Yun, Sheel Shah, Nico Pierson, Jonathan White, Simone Schindler, Carsten H. Tischbirek, Guo-Cheng Yuan, Long Cai
Summary: By utilizing integrated spatial genomics, this study identified cell type-specific nuclear architecture and gene expression levels in mouse brain tissue sections, while also revealing that active and inactive X chromosomes access similar domain structures in single cells. This work represents a significant advancement in linking single-cell three-dimensional nuclear architecture, gene expression, and epigenetic modifications in a native tissue context.
Review
Biochemistry & Molecular Biology
Mojca Mattiazzi Usaj, Clarence Hue Lok Yeung, Helena Friesen, Charles Boone, Brenda J. Andrews
Summary: Single-cell image analysis is a powerful tool for studying cell-to-cell heterogeneity and provides a higher resolution view of cellular function, which is crucial for understanding the genotype-to-phenotype relationship.
Article
Biotechnology & Applied Microbiology
Francesc Muyas, Carolin M. Sauer, Jose Espejo Valle-Inclan, Ruoyan Li, Raheleh Rahbari, Thomas J. Mitchell, Sahand Hormoz, Isidro Cortes-Ciriano
Summary: SComatic is an algorithm that identifies somatic mutations from scRNA-seq and scATAC data without a matched reference sample. It distinguishes somatic mutations from other events and artefacts using filters and statistical tests. Validated against matched genome sequencing and scRNA-seq data, SComatic shows high accuracy in detecting mutations in single cells. It allows for de novo mutational signature analysis and the study of clonal heterogeneity and mutational burdens at a single-cell resolution.
NATURE BIOTECHNOLOGY
(2023)
Article
Genetics & Heredity
Jiaqi Li, Jingjing Wang, Peijing Zhang, Renying Wang, Yuqing Mei, Zhongyi Sun, Lijiang Fei, Mengmeng Jiang, Lifeng Ma, E. Weigao, Haide Chen, Xinru Wang, Yuting Fu, Hanyu Wu, Daiyuan Liu, Xueyi Wang, Jingyu Li, Qile Guo, Yuan Liao, Chengxuan Yu, Danmei Jia, Jian Wu, Shibo He, Huanju Liu, Jun Ma, Kai Lei, Jiming Chen, Xiaoping Han, Guoji Guo
Summary: This study generated single-cell whole-body expression landscapes of zebrafish, Drosophila, and earthworm using Microwell-seq. By integrating cell landscapes from eight representative species, the researchers developed a deep-learning-based strategy, Nvwa, to predict gene expression and identify regulatory programs. Conserved genetic regulation in vertebrates and invertebrates were revealed through comparison of cell-type-specific transcription factors. This work provides a valuable resource and a new strategy for studying regulatory grammar in diverse biological systems.
Article
Gastroenterology & Hepatology
Angela L. Chu, Joel D. Schilling, Kevin R. King, Ariel E. Feldstein
Summary: Single cell transcriptomics is a powerful tool for studying molecular diversity in tissues such as the liver during health and disease. By developing cell isolation and sorting protocols, researchers can more accurately analyze cell-type-specific expression and uncover the mysteries of cellular heterogeneity. Profiling transcriptomes at the single-cell level has opened up new research opportunities that were previously impossible.
Article
Chemistry, Analytical
Kevin D. Clark, Stanislav S. Rubakhin, Jonathan Sweedler
Summary: SNRMA-MS is the first analytical approach capable of simultaneously quantifying numerous RNA modifications in single neurons and revealing cell-specific modification profiles.
ANALYTICAL CHEMISTRY
(2021)
