In Silico Identification of Stress-Associated Transposable Elements in Arabidopsis thaliana Using Public Transcriptome Data

Methods Mol Biol. 2021:2250:15-30. doi: 10.1007/978-1-0716-1134-0_2.

Abstract

Transposable elements (TEs) have been associated with stress response in many plants, making them a key target of study. However, the high variability, genomic repeat-heavy nature, and widely noncoding character of TEs have made them difficult to study using non-specialized methods, whether experimental or computational. In this chapter, we introduce two computational workflows to analyze transposable elements using publicly available transcriptome data. In the first of these methods, we identify TEs, which show differential expression under salt stress using sample transcriptome libraries that includes noncoding transcripts. In the second, we identify protein-coding genes with differential expression under the same conditions, and determine which TEs are enriched in the promoter regions of these stress-related genes.

Keywords: Bioinformatics; Plant genome; Public databases; RNA-seq; Stress response; Transcriptomics; Transposable elements.

MeSH terms

  • Arabidopsis / genetics*
  • Computational Biology / methods*
  • Computer Simulation
  • DNA Transposable Elements*
  • Databases, Genetic
  • Gene Expression Profiling / methods*
  • Gene Expression Regulation, Plant
  • Molecular Sequence Annotation
  • Salt Stress
  • Sequence Analysis, RNA
  • Transcriptome

Substances

  • DNA Transposable Elements