Spatial Transcriptomics: Emerging Technologies in Tissue Gene Expression Profiling

Robles-Remacho, Agustín; Sanchez-Martin, Rosario M.; Diaz-Mochon, Juan J.

doi:10.1021/acs.analchem.3c02029

Cited by 16 publications

(2 citation statements)

References 74 publications

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“…Sequencing results of RNA-seq were used to further validate the effect of different staining methods on RNA quality and sequencing results. RNA-seq is not only widely used in the field of multiomics but also crucial for single-cell spatial transcriptomic studies . It is difficult to determine which cellular stress mechanisms other than reduced RNA integrity may drive changes in gene transcription levels.…”

Section: Discussionmentioning

confidence: 99%

Effect of Different Staining Methods on Brain Cryosections

Zhou,

Qi,

Yang

et al. 2024

ACS Chem. Neurosci.

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Staining frozen sections is often required to distinguish cell types for spatial transcriptomic studies of the brain. The impact of the staining methods on the RNA integrity of the cells becomes one of the limitations of spatial transcriptome technology with microdissection. However, there is a lack of systematic comparisons of different staining modalities for the pretreatment of frozen sections of brain tissue as well as their effects on transcriptome sequencing results. In this study, four different staining methods were analyzed for their effect on RNA integrity in frozen sections of brain tissue. Subsequently, differences in RNA quality in frozen sections under different staining conditions and their impact on transcriptome sequencing results were assessed by RNA-seq. As one of the most commonly used methods for staining pathological sections, HE staining seriously affects the RNA quality of frozen sections of brain tissue. In contrast, the homemade cresyl violet staining method developed in this study has the advantages of short staining time, low cost, and less RNA degradation. The homemade cresyl violet staining proposed in this study can be applied instead of HE staining as an advance staining step for transcriptome studies in frozen sections of brain tissue. In the future, this staining method may be suitable for wide application in brain-related studies of frozen tissue sections. Moreover, it is expected to become a routine step for staining cells before sampling in brain science.

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Section: Discussionmentioning

confidence: 99%

Effect of Different Staining Methods on Brain Cryosections

Zhou,

Qi,

Yang

et al. 2024

ACS Chem. Neurosci.

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show abstract

“…On the other hand, the importance of our work is highlighted by the fact that transcriptomes describe biological functional states in a transient manner, necessitating verification of the same biological phenomena across multiple instances [ 46 ]. Compared with the latest spatial transcriptome technology, although it has the advantages of high throughput and single cell resolution, which can achieve the whole transcriptome analysis of a single mouse brain [ 47 , 48 ], it has the disadvantage that all genes are expressed from the same organism at the same moment. Therefore, it is not possible to achieve single-gene ISH validation equivalent to AMBA ISH data in terms of biological replication.…”

Section: Discussionmentioning

confidence: 99%

Repairing the in situ hybridization missing data in the hippocampus region by using a 3D residual U-Net model

Wan,

Fu,

Peng

et al. 2024

Biomed. Opt. Express

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The hippocampus is a critical brain region. Transcriptome data provides valuable insights into the structure and function of the hippocampus at the gene level. However, transcriptome data is often incomplete. To address this issue, we use the convolutional neural network model to repair the missing voxels in the hippocampus region, based on Allen institute coronal slices in situ hybridization (ISH) dataset. Moreover, we analyze the gene expression correlation between coronal and sagittal dataset in the hippocampus region. The results demonstrated that the trend of gene expression correlation between the coronal and sagittal datasets remained consistent following the repair of missing data in the coronal ISH dataset. In the last, we use repaired ISH dataset to identify novel genes specific to hippocampal subregions. Our findings demonstrate the accuracy and effectiveness of using deep learning method to repair ISH missing data. After being repaired, ISH has the potential to improve our comprehension of the hippocampus's structure and function.

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Next‐generation spatial transcriptomics: unleashing the power to gear up translational oncology

Wang,

Hong,

et al. 2024

MedComm

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The growing advances in spatial transcriptomics (ST) stand as the new frontier bringing unprecedented influences in the realm of translational oncology. This has triggered systemic experimental design, analytical scope, and depth alongside with thorough bioinformatics approaches being constantly developed in the last few years. However, harnessing the power of spatial biology and streamlining an array of ST tools to achieve designated research goals are fundamental and require real‐world experiences. We present a systemic review by updating the technical scope of ST across different principal basis in a timeline manner hinting on the generally adopted ST techniques used within the community. We also review the current progress of bioinformatic tools and propose in a pipelined workflow with a toolbox available for ST data exploration. With particular interests in tumor microenvironment where ST is being broadly utilized, we summarize the up‐to‐date progress made via ST‐based technologies by narrating studies categorized into either mechanistic elucidation or biomarker profiling (translational oncology) across multiple cancer types and their ways of deploying the research through ST. This updated review offers as a guidance with forward‐looking viewpoints endorsed by many high‐resolution ST tools being utilized to disentangle biological questions that may lead to clinical significance in the future.

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Spatial Transcriptomics: Emerging Technologies in Tissue Gene Expression Profiling

Cited by 16 publications

References 74 publications

Effect of Different Staining Methods on Brain Cryosections

Effect of Different Staining Methods on Brain Cryosections

Repairing the in situ hybridization missing data in the hippocampus region by using a 3D residual U-Net model

Next‐generation spatial transcriptomics: unleashing the power to gear up translational oncology

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