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Updated: Jul 13, 2026
13:33
Infinium Assay for Large-scale SNP Genotyping Applications
Published on: November 19, 2013
Indel arrays: an affordable alternative for genotyping
Neeraj Salathia1, Hana N Lee, Todd A Sangster
1FAS Center for Systems Biology, Harvard University, Cambridge, MA 02138, USA.
The Plant Journal : for Cell and Molecular Biology
|July 25, 2007
Summary
We developed a cost-effective microarray for genome-wide genotyping using insertion/deletion polymorphisms. This method enables rapid mapping of mutations and genetic variations in Arabidopsis thaliana and other species.
Area of Science:
- Plant genetics
- Genomics
- Molecular biology
Background:
- Natural variation and induced mutations are crucial for gene discovery and understanding genetic circuits.
- Efficient genome-wide genotyping methods are essential for mapping polymorphisms.
- Existing methods can be costly and time-consuming.
Purpose of the Study:
- To develop a rapid, cost-efficient microarray-based method for genome-wide genotyping.
- To utilize insertion/deletion (indel) polymorphisms for high-precision marker detection.
- To facilitate the mapping of genetic variations in various plant populations.
Main Methods:
- Designed a microarray with 240 unique 70-mer oligonucleotide elements targeting indel polymorphisms between Arabidopsis thaliana accessions Col and Ler.
- Employed comparative genomic hybridization for precise recognition of indel markers.
- Integrated PCR primer information for single-locus analysis and utilized multi-well chips for high-throughput genotyping.
Main Results:
- Achieved genome-wide genotyping at a material cost of less than US$50 per line.
- Demonstrated high precision in detecting indel polymorphisms, eliminating the need for array replicates and complex analysis.
- Successfully mapped recessive mutations, RIL populations, and mixed genetic backgrounds from diverse accessions.
Conclusions:
- The developed microarray offers a rapid, cost-effective, and precise tool for genome-wide genotyping.
- This approach is highly adaptable for non-model organisms, leveraging shotgun sequencing data.
- Facilitates gene discovery and genetic circuit elucidation through efficient polymorphism mapping.
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