Lost in space: what single-cell RNA sequencing cannot tell you

Adema, Kelvin; Schon, Michael A.; Nodine, Michael D.; Kohlen, Wouter

doi:10.1016/j.tplants.2024.03.010

Cited by 4 publications

(3 citation statements)

References 71 publications

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“…Another limitation of sc/snRNA-seq and sc/snATAC-seq is the lack of spatial resolution, which impedes the precise characterization of cell–cell interactions in spatial context and organization within tissues and organs [ 91 ]. Cell populations identified from single-cell sequencing have been localized in a spatial context using techniques such as RNA in-situ hybridization and immunofluorescence [ 19 , 92 ].…”

Section: Challenges and Limitations Of Single-cell Technologies In Ru...mentioning

confidence: 99%

“…In livestock species, where tissue architecture and cellular microenvironments play crucial roles in development, growth, and disease resistance, the inability to capture spatial information can limit the biological insights gained from single-cell sequencing data. Emerging spatial transcriptomics and spatial genomics technologies offer promising solutions to this challenge by enabling the profiling of gene expression within intact tissue sections [ 91 ]. These technologies are rapidly improving in robustness and resolution and are becoming more widely utilized in non-model organisms [ 93 , 94 ].…”

Section: Challenges and Limitations Of Single-cell Technologies In Ru...mentioning

confidence: 99%

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Single-Cell Sequencing Technology in Ruminant Livestock: Challenges and Opportunities

Lyons,

Brown,

Davenport

2024

CIMB

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Advancements in single-cell sequencing have transformed the genomics field by allowing researchers to delve into the intricate cellular heterogeneity within tissues at greater resolution. While single-cell omics are more widely applied in model organisms and humans, their use in livestock species is just beginning. Studies in cattle, sheep, and goats have already leveraged single-cell and single-nuclei RNA-seq as well as single-cell and single-nuclei ATAC-seq to delineate cellular diversity in tissues, track changes in cell populations and gene expression over developmental stages, and characterize immune cell populations important for disease resistance and resilience. Although challenges exist for the use of this technology in ruminant livestock, such as the precise annotation of unique cell populations and spatial resolution of cells within a tissue, there is vast potential to enhance our understanding of the cellular and molecular mechanisms underpinning traits essential for healthy and productive livestock. This review intends to highlight the insights gained from published single-cell omics studies in cattle, sheep, and goats, particularly those with publicly accessible data. Further, this manuscript will discuss the challenges and opportunities of this technology in ruminant livestock and how it may contribute to enhanced profitability and sustainability of animal agriculture in the future.

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Section: Challenges and Limitations Of Single-cell Technologies In Ru...mentioning

confidence: 99%

Section: Challenges and Limitations Of Single-cell Technologies In Ru...mentioning

confidence: 99%

Single-Cell Sequencing Technology in Ruminant Livestock: Challenges and Opportunities

Lyons,

Brown,

Davenport

2024

CIMB

View full text Add to dashboard Cite

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“…Moreover, generating multiple single-cell data has allowed scientists to produce reference single-cell atlases to compare cellular conditions across various research investigations [ 42 ]. Although scRNA-seq has significantly increased our understanding of the complex cellular heterogeneity of tissues and organs, it has some disadvantages, such as the effect of cell dissociation and the loss of positional information [ 43 ]. The spatial context of the cells has a significant role in developmental biology, cellular communication, and disease study, among others.…”

Section: Genomics and Transcriptomicsmentioning

confidence: 99%

Multi Omics Applications in Biological Systems

Gutierrez Reyes,

Alejo-Jacuinde,

Perez Sanchez

et al. 2024

CIMB

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Traditional methodologies often fall short in addressing the complexity of biological systems. In this regard, system biology omics have brought invaluable tools for conducting comprehensive analysis. Current sequencing capabilities have revolutionized genetics and genomics studies, as well as the characterization of transcriptional profiling and dynamics of several species and sample types. Biological systems experience complex biochemical processes involving thousands of molecules. These processes occur at different levels that can be studied using mass spectrometry-based (MS-based) analysis, enabling high-throughput proteomics, glycoproteomics, glycomics, metabolomics, and lipidomics analysis. Here, we present the most up-to-date techniques utilized in the completion of omics analysis. Additionally, we include some interesting examples of the applicability of multi omics to a variety of biological systems.

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Cross-modality representation and multi-sample integration of spatially resolved omics data

Li,

Cui,

Chen

et al. 2024

Preprint

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Spatially resolved sequencing technologies have revolutionized the characterization of biological regulatory processes within microenvironment by simultaneously accessing the states of genomic regions, genes and proteins, along with the spatial coordinates of cells, necessitating advanced computational methods for the cross-modality and multi-sample integrated analysis of spatial omics datasets. To address this gap, we propose PRESENT, an effective and scalable contrastive learning framework, for the cross-modality representation of spatially resolved omics data. Through comprehensive experiments on massive spatially resolved datasets, PRESENT achieves superior performance across various species, tissues, and sequencing technologies, including spatial epigenomics, transcriptomics, and multi-omics. Specifically, PRESENT empowers the incorporation of spatial dependency and complementary omics information simultaneously, facilitating the detection of spatial domains and uncovering biological regulatory mechanisms within microenvironment. Furthermore, PRESENT can be extended to the integrative analysis of horizontal and vertical samples across different dissected regions or developmental stages, thereby promoting the identification of hierarchical structures from a spatiotemporal perspective.

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Lost in space: what single-cell RNA sequencing cannot tell you

Cited by 4 publications

References 71 publications

Single-Cell Sequencing Technology in Ruminant Livestock: Challenges and Opportunities

Single-Cell Sequencing Technology in Ruminant Livestock: Challenges and Opportunities

Multi Omics Applications in Biological Systems

Cross-modality representation and multi-sample integration of spatially resolved omics data

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