Feature Review

Gene-Driven Future: Breakthroughs and Applications of Marker-Assisted Selection in Tree Breeding  

Yufen Wang , Lianming Zhang
Traditional Chinese Medicine Research Center, Cuixi Academy of Biotechnology, Zhuji, 311800, Zhejiang, China
Author    Correspondence author
Molecular Plant Breeding, 2024, Vol. 15, No. 3   doi: 10.5376/mpb.2024.15.0014
Received: 18 Apr., 2024    Accepted: 27 May, 2024    Published: 28 Jun., 2024
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This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Preferred citation for this article:

Wang Y.F., and Zhang L.M., 2024, Gene-driven future: breakthroughs and applications of marker-assisted selection in tree breeding, Molecular Plant Breeding, 15(3): 132-143 (doi: 10.5376/mpb.2024.15.0014)

Abstract

Marker-assisted selection (MAS) is a transformative method in tree breeding, combining traditional breeding techniques with modern genetic tools to enhance desirable traits such as growth rate, wood quality, and disease resistance. This study systematically examines the progress, applications, challenges, and future prospects of MAS in tree breeding. Technological advancements, including high-throughput sequencing and genomic selection, have significantly improved the precision and efficiency of MAS. Key achievements include the development of tree varieties that are disease-resistant, fast-growing, and produce high-quality wood. However, MAS still faces technical, biological, and socioeconomic challenges that must be addressed. Integrating emerging technologies such as CRISPR gene editing, synthetic biology, big data analysis, and remote sensing holds promise for further advancements. By leveraging these advancements, MAS can make significant contributions to developing high-quality tree varieties, promoting environmental conservation, and improving resource management.

Keywords
Marker-assisted selection; Genomic selection; Tree breeding; Genomics; Disease resistance; Genetic gain
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