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Abstract

In the last few decades, conventional breeding, combined with transgenic methods and mutagenesis, has played a crucial role in accelerating the pace of genetic research and the application of genome editing in various fields, including agriculture and medicine. Genome editing technologies have revolutionized the field of genetics, offering precise regulation over the genetic makeup of organisms. A rapid assay for estimating the frequencies of various induced mutations during genome editing is of key importance. Understanding and quantifying the mutations introduced during genome editing processes are crucial for assessing the efficiency and specificity of these technologies. Therefore, many techniques are used to quantify genome editing-derived mutations, depending on their type and the level of sensitivity required. This chapter provides an in-depth exploration of estimation and quantification techniques used to analyze targeted mutations, with a focus on high-resolution melting (HRM) analysis, targeting induced local lesions in genomes (TILLING), CRISPR ribonucleoprotein (RNP) complexes, and mutation tracking tools like tracking of indels by decomposition (TIDE) and tracking of insertion, deletions and recombination events (TIDER). In addition, next-generation sequencing (NGS), including Nanopore, Ion Torrent, Illumina, Pacific Biosciences (PacBio), sequencing by oligonucleotide ligation and detection (SOLiD), BGI sequencer (BGISEQ), and 454 pyrosequencing, is briefly discussed to evaluate the sensitivity of existing bioinformatics tools and proposing strategies to minimize the error to identify unintended mutations.

Keywords

CRISPR ribonucleoprotein (RNP) complexes; High-resolution melting analysis (HRM); Mutation tracking; Next-generation sequencing (NGS); Plant genome editing; Targeted mutations; Targeting Induced Local Lesions in Genomes (TILLING)

Published in

Title: Genome Editing for Crop Improvement : theory and methodology
Publisher: CABI International

SLU Authors

UKÄ Subject classification

Genetics and Genomics
Agricultural Science

Publication identifier

  • DOI: https://doi.org/10.1079/9781800622517.0009
  • ISBN: 9781800622494
  • eISBN: 9781800622500

Permanent link to this page (URI)

https://res.slu.se/id/publ/142909