High-throughput marker discovery in melon using a self-designed oligo microarray

• Main Authors: Uliel Shai, Burger Yoseph, Portnoy Vitaly, Tzuri Galil, Harel-Beja Rotem, Eshed Ravit, Ophir Ron, Katzir Nurit, Sherman Amir
• Format: Article
• Language: English
• Published: BMC 2010-04-01
• Series: BMC Genomics
• Online Access: http://www.biomedcentral.com/1471-2164/11/269

<p>Abstract</p> <p>Background</p> <p>Genetic maps constitute the basis of breeding programs for many agricultural organisms. The creation of these maps is dependent on marker discovery. Melon, among other crops, is still lagging in genomic resources, limiting the ability to discover new markers in a high-throughput fashion. One of the methods used to search for molecular markers is DNA hybridization to microarrays. Microarray hybridization of DNA from different accessions can reveal differences between them--single-feature polymorphisms (SFPs). These SFPs can be used as markers for breeding purposes, or they can be converted to conventional markers by sequencing. This method has been utilized in a few different plants to discover genetic variation, using Affymetrix arrays that exist for only a few organisms. We applied this approach with some modifications for marker discovery in melon.</p> <p>Results</p> <p>Using a custom-designed oligonucleotide microarray based on a partial EST collection of melon, we discovered 6184 putative SFPs between the parents of our mapping population. Validation by sequencing of 245 SFPs from the two parents showed a sensitivity of around 79%. Most SFPs (81%) contained single-nucleotide polymorphisms. Testing the SFPs on another mapping population of melon confirmed that many of them are conserved.</p> <p>Conclusion</p> <p>Thousands of new SFPs that can be used for genetic mapping and molecular-assisted breeding in melon were discovered using a custom-designed oligo microarray. A portion of these SFPs are conserved and can be used in different breeding populations. Although improvement of the discovery rate is still needed, this approach is applicable to many agricultural systems with limited genomic resources.</p>