Molecular Markers and Selection for Complex Traits in Plants: Learning from the Last 20 Years

TLDR

In the mid‑1980s, the development of abundant molecular markers, appropriate statistical procedures, and user‑friendly software enabled detection of markers linked to QTL for complex traits, yet despite thousands of reported marker‑trait associations, few examples of successfully exploiting mapped QTL have been reported. Marker‑assisted selection was proposed to exploit QTL‑linked markers for improved cultivars, and future applications will focus on predictive marker‑based selection before phenotyping or without QTL mapping. These applications will take advantage of cheaper genotyping costs compared to phenotyping. Key lessons include defining the purpose of QTL detection, tailoring marker‑based selection to the number of QTL, recognizing inconsistent QTL effect estimates, and prioritizing gain per unit cost and time over gain per cycle.

Abstract

In the mid‐1980s, the development of abundant molecular markers, appropriate statistical procedures, and user‐friendly computer software that implemented these statistical procedures permitted the detection of molecular markers associated with quantitative trait loci (QTL) for complex traits. Marker‐assisted selection was then proposed as a means of exploiting markers linked to QTL to develop improved cultivars. But while thousands of marker‐trait associations have been reported for many traits in different plant species, far fewer examples of successfully exploiting mapped QTL have been reported in the literature. Key lessons learned from applying markers in plant breeding include the following: (i) the purpose of detecting QTL should be clearly defined before embarking on QTL mapping; (ii) procedures for marker‐based selection depend on the number of QTL; (iii) estimates of QTL effects for complex traits are often inconsistent; and (iv) gain per unit cost and time rather than gain per cycle should be considered. Future applications for complex traits will likely focus on predictive methodologies for marker‐based selection before phenotyping and for marker‐based selection without QTL mapping. These applications will take advantage of cheaper costs of genotyping than of phenotyping.