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Cell Specific Gene Expression01:58

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Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...
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Combinatorial gene control is the synergistic action of several transcriptional factors to regulate the expression of a single gene. The absence of one or more of these factors may lead to a significant difference in the level of gene expression or repression.
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A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is comprised  of nucleotides and proteins are comprised of amino acids, a mediator is required to convert the information encoded in DNA into proteins. This mediator is the messenger RNA (mRNA). mRNA copies the blueprint from DNA by a process called transcription. In eukaryotes, transcription occurs in the nucleus by complementary base-pairing with the DNA template. The mRNA is then...
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Overview
Gene expression is the process in which DNA directs the synthesis of functional products, that is, proteins. Cells can regulate gene expression at various stages. It allows organisms to generate different cell types and enables cells to adapt to internal and external factors.
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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...
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scLink: Inferring Sparse Gene Co-expression Networks from Single-cell Expression Data.

Wei Vivian Li1, Yanzeng Li1

  • 1Department of Biostatistics and Epidemiology, Rutgers School of Public Health, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.

Genomics, Proteomics & Bioinformatics
|July 12, 2021
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Summary

We developed scLink, a new method using statistical network modeling to analyze gene co-expression networks from single-cell gene expression data. scLink enhances the understanding of gene interactions in specific cell types for biological research.

Keywords:
Gene co-expression networkNetwork modelingRobust correlationSingle-cell RNA sequencing

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Area of Science:

  • Genomics
  • Computational Biology
  • Systems Biology

Background:

  • Understanding gene expression regulation is crucial for studying biological complexity in health and disease.
  • Single-cell RNA sequencing (scRNA-seq) enables cell type-specific investigation of gene interactions.
  • Existing methods may not fully capture the nuances of gene networks at the single-cell level.

Purpose of the Study:

  • To introduce scLink, a novel method for constructing gene co-expression networks from scRNA-seq data.
  • To leverage statistical network modeling for cell type-specific gene interaction analysis.
  • To demonstrate the utility and advantages of scLink in analyzing single-cell gene expression data.

Main Methods:

  • Development of the scLink method utilizing statistical network modeling.
  • Application of scLink to construct sparse gene co-expression networks.
  • Validation using both simulated and real single-cell gene expression datasets.

Main Results:

  • scLink effectively models co-expression relationships among genes.
  • The method successfully constructs sparse gene co-expression networks from scRNA-seq data.
  • Performance evaluations show scLink's advantages in single-cell gene network analysis.

Conclusions:

  • scLink provides a powerful tool for dissecting cell type-specific gene regulatory mechanisms.
  • The method improves the analysis of gene networks derived from single-cell expression data.
  • The scLink R package is publicly available to facilitate research in this area.