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Related Experiment Video

Updated: Jul 17, 2025

Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics
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Gene Regulatory Network Modeling Using Single-Cell Multi-Omics in Plants.

Tran Chau1, Prakash Timilsena2, Song Li3,4

  • 1Graduate Program in Genetics, Bioinformatics and Computational Biology (GBCB), Blacksburg, VA, USA.

Methods in Molecular Biology (Clifton, N.J.)
|September 8, 2023
PubMed
Summary
This summary is machine-generated.

This study presents a computational pipeline for analyzing single-cell multi-omics data to build gene regulatory networks in plants. This method aids in understanding gene expression and chromatin accessibility at a single-cell level.

Keywords:
Gene regulatory networkMachine learningMotif analysisMulti-omicsRootSingle-cell sequencingscATAC-seqscRNA-seq

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Area of Science:

  • Plant biology
  • Genomics
  • Computational biology

Background:

  • Single-cell multi-omics technologies offer high-resolution insights into cellular heterogeneity.
  • Understanding gene regulation is crucial for deciphering complex biological processes.

Purpose of the Study:

  • To describe a computational pipeline for analyzing single-cell RNA sequencing (scRNA-seq) and single-cell Assay for Transposase-Accessible Chromatin sequencing (scATAC-seq) data.
  • To construct gene regulatory networks from single-cell multi-omics data.

Main Methods:

  • Data normalization and integration of scRNA-seq and scATAC-seq datasets.
  • Identification of cluster marker genes.
  • Motif finding for selected marker genes.
  • Machine learning application for regulatory network identification.

Main Results:

  • The pipeline was successfully validated using data from the model plant species Arabidopsis.
  • The developed pipeline is adaptable for analyzing single-cell multi-omics data in various plant and animal species.

Conclusions:

  • The computational pipeline provides a robust framework for characterizing gene regulatory networks using single-cell multi-omics data.
  • This approach facilitates a deeper understanding of gene regulation at the cellular level across different species.