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Updated: Nov 16, 2025

Development of Targeting Induced Local Lesions IN Genomes TILLING Populations in Small Grain Crops by Ethyl Methanesulfonate Mutagenesis
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Accurate, Efficient and User-Friendly Mutation Calling and Sample Identification for TILLING Experiments.

Juanita Gil1, Juan Sebastian Andrade-Martínez2,3, Jorge Duitama1

  • 1Systems and Computing Engineering Department, Universidad de Los Andes, Bogotá, Colombia.

Frontiers in Genetics
|February 22, 2021
PubMed
Summary
This summary is machine-generated.

Targeting Induced Local Lesions IN Genomes (TILLING) is a reverse genetics method. New NGSEP components accurately detect low-frequency mutations in pooled samples and identify individual mutations, improving plant breeding and genomics research.

Keywords:
TILLINGfunctional genomicsmutagenesissoftwarevariants detection

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Area of Science:

  • Plant genomics
  • Reverse genetics
  • Bioinformatics

Background:

  • Targeting Induced Local Lesions IN Genomes (TILLING) is crucial for plant functional genomics and breeding.
  • Current bioinformatics tools struggle with low-frequency mutation detection in pooled samples and individual sample identification.

Purpose of the Study:

  • To introduce novel components within the Next Generation Sequencing Experience Platform (NGSEP) for enhanced TILLING experiment design and analysis.
  • To address limitations in detecting low-frequency mutations and assigning them to individuals in pooled sequencing data.

Main Methods:

  • Development of a pooled variant detector with an improved calling model for low-frequency mutations.
  • Implementation of a sample identifier using triangulation across overlapping pools for mutation assignment.
  • Creation of a TILLING experiment simulator for tool benchmarking and experimental design.

Main Results:

  • NGSEP demonstrates comparable accuracy and superior efficiency in pooled variant detection compared to existing tools.
  • The NGSEP sample identifier successfully assigns discovered mutations to individual plants from pooled data.
  • Simulation experiments validate the effectiveness of the new NGSEP components.

Conclusions:

  • NGSEP offers a comprehensive solution for TILLING experiments, enhancing mutation detection and individual assignment.
  • This advancement is expected to benefit plant breeding programs and researchers utilizing pooled sequencing for various applications.
  • NGSEP is currently the only tool providing individual mutation assignments from pooled sequencing data.