Germplasm-regression-combined (GRC) marker-trait association identification in plant breeding: a challenge for plant biotechnological breeding under soil water deficit conditions.
In the past 20 years, the major effort in plant breeding has changed from quantitative to molecular genetics with emphasis on quantitative trait loci (QTL) identification and marker assisted selection (MAS). However, results have been modest. This has been due to several factors including absence of tight linkage QTL, non-availability of mapping populations, and substantial time needed to develop such populations. To overcome these limitations, and as an alternative to planned populations, molecular marker-trait associations have been identified by the combination between germplasm and the regression technique. In the present preview, the authors (1) survey the successful applications of germplasm-regression-combined (GRC) molecular marker-trait association identification in plants; (2) describe how to do the GRC analysis and its differences from mapping QTL based on a linkage map reconstructed from the planned populations; (3) consider the factors that affect the GRC association identification, including selections of optimal germplasm and molecular markers and testing of identification efficiency of markers associated with traits; and (4) finally discuss the future prospects of GRC marker-trait association analysis used in plant MAS/QTL breeding programs, especially in long-juvenile woody plants when no other genetic information such as linkage maps and QTL are available.
Ruan
Cheng-Jiang
CJ
Yantai Institute of Costal Zone Research, Chinese Academy of Sciences, Yantai, China.
Xu
Xue-Xuan
XX
Shao
Hong-Bo
HB
Jaleel
Cheruth Abdul
CA
D001709:Biotechnology; D001947:Breeding; D055864:Droughts; D056726:Genetic Association Studies; D005819:Genetic Markers / Q000235:genetics*; D010944:Plants / Q000235:genetics*; D040641:Quantitative Trait Loci / Q000235:genetics*; D012044:Regression Analysis; D013312:Stress, Physiological / Q000235:genetics*
D005819:Genetic Markers