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Criteria for evaluating molecular markers: Comprehensive quality metrics to improve marker-assisted selection

PLoS ONE, ISSN: 1932-6203, Vol: 14, Issue: 1, Page: e0210529
2019
  • 61
    Citations
  • 0
    Usage
  • 102
    Captures
  • 2
    Mentions
  • 29
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    61
  • Captures
    102
  • Mentions
    2
    • News Mentions
      2
      • News
        2
  • Social Media
    29
    • Shares, Likes & Comments
      29
      • Facebook
        29

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Article Description

Despite strong interest over many years, the usage of quantitative trait loci in plant breeding has often failed to live up to expectations. A key weak point in the utilisation of QTLs is the “quality” of markers used during marker-assisted selection (MAS): unreliable markers result in variable outcomes, leading to a perception that MAS products fail to achieve reliable improvement. Most reports of markers used for MAS focus on markers derived from the mapping population. There are very few studies that examine the reliability of these markers in other genetic backgrounds, and critically, no metrics exist to describe and quantify this reliability. To improve the MAS process, this work proposes five core metrics that fully describe the reliability of a marker. These metrics give a comprehensive and quantitative measure of the ability of a marker to correctly classify germplasm as QTL[+]/[–], particularly against a background of high allelic diversity. Markers that score well on these metrics will have far higher reliability in breeding, and deficiencies in specific metrics give information on circumstances under which a marker may not be reliable. The metrics are applicable across different marker types and platforms, allowing an objective comparison of the performance of different markers irrespective of the platform. Evaluating markers using these metrics demonstrates that trait-specific markers consistently out-perform markers designed for other purposes. These metrics also provide a superb set of criteria for designing superior marker systems for a target QTL, enabling the selection of an optimal marker set before committing to design.

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