TY - JOUR
T1 - Germplasm-regression-combined (GRC) marker-trait association identification in plant breeding
T2 - A challenge for plant biotechnological breeding under soil water deficit conditions
AU - Ruan, Cheng Jiang
AU - Xu, Xue Xuan
AU - Shao, Hong Bo
AU - Jaleel, Cheruth Abdul
N1 - Funding Information:
This work was jointly funded by the Keystone Project of the Agriculture Science and Technology Research Item of the Liaoning Scientific and Technological Committee (No. 2007207005), One hundred-Talent Plan of Chinese Academy of Sciences, The Awarding Foundation of the State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau (10501-JL), the CAS/SAFEA International Partnership Program for Creative Research Teams, the Important Direction Project of CAS (KZCX2-YW-JC203, KZCX2-XB2-05, kzcx2-yw-BR-02), and CAS Young Scientists Fellowship (2009Y2B211).
PY - 2010/9
Y1 - 2010/9
N2 - 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 markertrait 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 germplasmregressioncombined (GRC) molecular markertrait 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 markertrait 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.
AB - 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 markertrait 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 germplasmregressioncombined (GRC) molecular markertrait 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 markertrait 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.
KW - Abiotic stress
KW - Association analysis
KW - Biotechnological breeding
KW - Germplasm-regression
KW - MAS
KW - Molecular marker
KW - Quantitative trait
KW - Sea buckthorn
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U2 - 10.3109/07388551003649062
DO - 10.3109/07388551003649062
M3 - Review article
C2 - 20210691
AN - SCOPUS:77956074813
SN - 0738-8551
VL - 30
SP - 192
EP - 199
JO - Critical Reviews in Biotechnology
JF - Critical Reviews in Biotechnology
IS - 3
ER -