Research Review

Analyzing the Impact of Marker-Assisted Selection on Livestock Productivity and Genetic Diversity  

Jiong Li , Xiaofang Lin
1 Biotechnology Research Center, Cuixi Academy of Biotechnology , Zhuji, 311800, Zhejiang, China
2 Tropical Animal Medical Center, Hainan Institute of Tropical Agricultural Resources, Sanya, 572025, Hainan, China
Author    Correspondence author
Animal Molecular Breeding, 2024, Vol. 14, No. 1   doi: 10.5376/amb.2024.14.0014
Received: 07 Jan., 2024    Accepted: 18 Feb., 2024    Published: 28 Feb., 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:

Li J., and Lin X.F., 2024, Analyzing the impact of marker-assisted selection on livestock productivity and genetic diversity, Animal Molecular Breeding, 14(1): 119-129 (doi: 10.5376/amb.2024.14.0014)

Abstract

Marker-assisted selection (MAS) has emerged as a pivotal tool in enhancing livestock productivity and maintaining genetic diversity. This study analyzes the impact of MAS on livestock by integrating molecular markers with traditional breeding methods. This study highlights the efficiency of MAS in improving quantitative traits, disease resistance, and overall genetic diversity in livestock populations. The integration of genomic selection (GS) with MAS has further revolutionized animal breeding by enabling the identification and selection of superior traits with higher precision. Despite the challenges associated with complex traits and the need for large reference populations, MAS has shown significant promise in accelerating genetic gains and improving livestock productivity. Future directions include the adoption of high-throughput genotyping technologies and the development of more robust selection indices to enhance the efficiency of MAS in livestock breeding programs.

Keywords
Marker-assisted selection; Livestock productivity; Genetic diversity; Genomic selection; Quantitative traits
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