Related Experiment Video
Updated: Aug 9, 2025
09:19
Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
Published on: July 6, 2022
5.0K
SINFONIA: Scalable Identification of Spatially Variable Genes for Deciphering Spatial Domains
Rui Jiang1, Zhen Li1, Yuhang Jia2
1MOE Key Laboratory of Bioinformatics and Bioinformatics Division, BNRIST/Department of Automation, Tsinghua University, Beijing 100084, China.
Cells
|February 25, 2023
Summary
SINFONIA, a new scalable method, efficiently identifies spatially variable genes (SVGs) in spatial transcriptomics data. It integrates seamlessly into workflows, improving spatial domain characterization and analysis across diverse datasets.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- Spatial transcriptomics advances tissue organization understanding.
- Identifying spatially variable genes (SVGs) is crucial for spatial domain analysis.
- Existing SVG identification methods face challenges in deciphering domains, efficiency, and workflow integration.
Purpose of the Study:
- To introduce SINFONIA, a scalable and efficient method for identifying spatially variable genes (SVGs).
- To enhance the integration of SVG identification into standard spatial transcriptomics analysis workflows.
- To provide a robust tool for accurate spatial domain characterization.
Main Methods:
- SINFONIA utilizes ensemble strategies for scalable SVG identification.
- The method is implemented in Python for seamless integration into existing bioinformatics pipelines.
- Performance was evaluated on 15 diverse spatial transcriptomic datasets using 21 quantitative metrics.
Main Results:
- SINFONIA demonstrated superior performance compared to three baseline methods and two variants.
- Evaluations covered spatial clustering, domain resolution, latent representation, spatial visualization, and computational efficiency.
- The method showed robustness concerning the number of SVGs selected.
Conclusions:
- SINFONIA offers a scalable and efficient solution for identifying spatially variable genes.
- The method facilitates improved spatial domain characterization in spatial transcriptomics.
- SINFONIA is expected to significantly aid the analysis of spatial transcriptomics data.
More Related Videos
Related Concept Videos
02:32Position-effect Variegation
6.4K
In 1928, a German botanist Emil Heitz observed the moss nuclei with a DNA binding dye. He observed that while some chromatin regions decondense and spread out in the interphase nucleus, others do not. He termed them euchromatin and heterochromatin, respectively. He proposed that the heterochromatin regions reflect a functionally inactive state of the genome. It was later confirmed that heterochromatin is transcriptionally repressed, and euchromatin is transcriptionally active chromatin.
6.4K
02:11Reporter Genes
11.7K
Reporter genes are a type of protein-coding gene that are often tagged to a gene of interest. Once inside a target cell, reporter genes usually produce visually identifiable characteristics like fluorescence and luminescence when expressed along with the gene of interest. Thus, reporter genes “report” the presence or absence of genes of interest in an organism, determine the gene expression pattern, or track the physical location of a DNA segment or protein in the cell.
11.7K
02:34DNA Microarrays
17.9K
Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
17.9K
02:24Ribosome Profiling
3.6K
Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
3.6K
02:05Gene Evolution - Fast or Slow?
7.2K
The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...
In contrast, regions which code...
7.2K
02:22Regulated mRNA Transport
6.3K
In eukaryotes, transcription and translation are compartmentalized; an mRNA is first synthesized in the nucleus and then selectively transported to the cytoplasm for protein synthesis. Before transport, a pre-mRNA undergoes several steps of post-transcriptional modifications including splicing, 5' capping, and the addition of a poly-adenine tail. Various proteins bind to the pre-mRNA during these modifications. The mRNA transport takes place with the help of multiple proteins playing...
6.3K