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Updated: Apr 26, 2026

Fluorescence-microscopy Screening and Next-generation Sequencing: Useful Tools for the Identification of Genes Involved in Organelle Integrity

Fluorescence-microscopy Screening and Next-generation Sequencing: Useful Tools for the Identification of Genes Involved in Organelle Integrity

Published on: April 13, 2012

Fast and cost-effective genetic mapping in apple using next-generation sequencing.

Kyle M Gardner¹, Patrick Brown², Thomas F Cooke³

¹Department of Plant and Animal Sciences, Faculty of Agriculture, Dalhousie University, Nova Scotia, Canada.

G3 (Bethesda, Md.)

|July 18, 2014

Summary

Genotyping-by-sequencing (GBS) enables genome-wide genetic mapping in apples using next-generation sequencing. This cost-effective method generates genotype data for linkage mapping and quantitative trait locus (QTL) identification, even with sparse data.

Keywords:

Malus QTL SNP apple genotyping-by-sequencing next-generation DNA sequencing

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Last Updated: Apr 26, 2026

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G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome

Published on: March 22, 2018

Area of Science:

Genomics
Plant Breeding
Bioinformatics

Background:

Next-generation sequencing (NGS) generates large datasets but is not optimized for genetic mapping.
Reduced representation libraries and DNA sample barcoding improve NGS for genome-wide genotype data generation.
Genotyping-by-sequencing (GBS) combines these techniques for genetic marker analysis across many samples.

Purpose of the Study:

To assess the utility of GBS for genetic mapping in apples (Malus × domestica).
To generate a genome-wide genotype dataset for an F1 apple population segregating for skin color.
To construct a saturated genetic linkage map and identify a known QTL for apple skin color.

Main Methods:

Applied GBS to an F1 apple population.
Discovered over 270,000 single nucleotide polymorphisms (SNPs).
Filtered data for genotype quality and missing data, retaining 3967 SNPs from 89 samples.

Main Results:

GBS produced a sparse genotype matrix, with only 6% of reads yielding useful genotype calls after filtering.
A saturated genetic linkage map was constructed using the filtered SNP data.
A known QTL for apple skin color was successfully identified.

Conclusions:

GBS is a cost-effective method for generating genome-wide SNP data for genetic mapping in diverse, heterozygous species like apples.
Despite data sparsity, GBS is suitable for genetic mapping with appropriate filtering and analysis.
Future improvements in GBS analysis pipelines will further enhance its utility for genetic mapping across various species.