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An Array-based Comparative Genomic Hybridization Platform for Efficient Detection of Copy Number Variations in Fast Neutron-induced Medicago truncatula Mutants

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Mapping Maize Mutants Using Bulked-Segregant Analysis and Next-Generation Sequencing.

Norman B Best¹, Paula McSteen²

¹USDA-ARS, Plant Genetics Research Unit, Columbia, Missouri.

Current Protocols

|November 9, 2022

Summary

This summary is machine-generated.

This study presents a streamlined protocol for mapping maize mutations using bulked-segregant analysis (BSA) and high-throughput sequencing. It simplifies identifying the genetic basis of mutant phenotypes in Zea mays.

Keywords:

bulked-segregant analysis forward genetics maize mutant genes next-generation sequencing

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Experimental Design for Laser Microdissection RNA-Seq: Lessons from an Analysis of Maize Leaf Development

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Area of Science:

Plant genetics
Genomics
Bioinformatics

Background:

Forward genetics identifies genes underlying specific traits by analyzing mutants.
Traditional mapping methods are time-consuming and complex.
Advancements in high-throughput sequencing have enabled more efficient genetic mapping.

Purpose of the Study:

To provide a straightforward protocol for mapping mutations in maize using BSA and high-throughput sequencing.
To detail the experimental design, bioinformatic analysis, and interpretation of results for identifying causative mutations.
To offer adaptable methods for forward genetics experiments in Zea mays.

Main Methods:

Development of a mutant mapping population in maize.
DNA preparation and high-throughput sequencing of pooled DNA from mutant and wild-type individuals.
Bioinformatic analysis of short-read sequences using provided scripts for mutation mapping.

Main Results:

Successful application of BSA combined with high-throughput sequencing to map mutations in maize.
Identification of candidate causative mutations responsible for observed phenotypes.
Demonstration of an effective and timely approach to genetic mapping in Zea mays.

Conclusions:

The described protocol offers an effective and adaptable method for identifying the genetic basis of maize mutant phenotypes.
Careful experimental design and bioinformatic analysis are crucial for successful mutation mapping.
This approach significantly improves upon traditional, labor-intensive mapping techniques.