Status and Potential of Single-cell Transcriptomics for Understanding Plant Development and Functional Biology

Muhammad Munir Iqbal, Bhavna Hurgobin, Andrea Lisa Holme, Rudi Appels, Parwinder Kaur

Research output: Contribution to journalReview article

Abstract

The advent of modern "omics" technologies (genomics, transcriptomics, proteomics, and metabolomics) are attributed to innovative breakthroughs in genome sequencing, bioinformatics, and analytic tools. An organism's biological structure and function is the result of the concerted action of single cells in different tissues. Single cell genomics has emerged as a ground-breaking technology that has greatly enhanced our understanding of the complexity of gene expression at a microscopic resolution and holds the potential to revolutionize the way we characterize complex cell assemblies and study their spatial organization, dynamics, clonal distribution, pathways, function, and networking. Mammalian systems have benefitted immensely from these approaches to dissect complex systems such as cancer, immunological disorders, epigenetic controls of diseases and understanding of developmental biology. However, the applications of single-cell omics in plant research are just starting. The potential to decipher the fundamentals of developmental and functional biology of large and complex plant species at the single-cell resolution are now becoming important drivers of research. In this review, we present the status, challenges and potential of one important and most commonly used single-cell omics technique in plants, namely single cell transcriptomics.

Original languageEnglish
Number of pages32
JournalCytometry Part A : Journal of the International Society for Analytical Cytology
Early online date28 Aug 2020
DOIs
Publication statusE-pub ahead of print - 28 Aug 2020

Keywords

  • single‐cell omics
  • transcriptomics
  • scRNA-seq
  • functional biology
  • development biology
  • plant
  • cytometry
  • VISUALIZATION
  • SUBPOPULATIONS
  • single-cell omics
  • FUTURE
  • GENOME
  • scRNA-Seq
  • TECHNOLOGIES
  • RNA-SEQ
  • PROGRAM

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