International Journal of Marine Science, 2025, Vol.15, No.5, 268-276 http://www.aquapublisher.com/index.php/ijms 268 Meta Analysis Open Access Genetic Variation and Genomic Selection Strategies for Growth Rate in Abalone Yanlin Wang1, JinniWu2 1 Tropical Animal Resources Research Center, Hainan Institute of Tropical Agricultural Resources, Sanya, 572025, Hainan, China 2 Aquatic Biology Research Center, Cuixi Academy of Biotechnology, Zhuji, 311800, Zhejiang, China Corresponding author: jinni.wu@cuixi.org International Journal of Marine Science, 2025, Vol.15, No.5, doi: 10.5376/ijms.2025.15.0024 Received: 15 Aug., 2025 Accepted: 28 Sep., 2025 Published: 21 Oct., 2025 Copyright © 2025 Wang and Wu, 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.L., and Wu J.N., 2025, Genetic variation and genomic selection strategies for growth rate in abalone, International Journal of Marine Science, 15(5): 268-276 (doi: 10.5376/ijms.2025.15.0024) Abstract Abalone (Haliotis spp.), as a high-value marine aquaculture species, has growth rate characteristics that are in direct relation to farm productivity and breeding improvement outcome. The biological basis and genetic variation features of abalone growth rate are systematically reviewed in this study, and the uses and limitations of traditional breeding methods in improving growth performance are discussed in detail. The review focuses on the fundamentals, approaches, and recent advances of genomic selection (GS) technology for enhancing abalone growth rate, as well as on practical case studies, and discusses the integration of GS and traditional breeding. It also discusses key challenges in the implementation of genomic selection, including phenotypic data quality, genotyping cost, model predictive ability, and genetic diversity maintenance. By combining high-throughput genotyping and machine learning, this review recapitulates the recent progress of GS strategies and their implications in increasing breeding efficiency. This review provides theoretical foundation and practical reference for building an efficient, precise, and sustainable modern abalone breeding system, promoting the healthy development of the abalone industry. Keywords Abalone; Growth rate; Genetic variation; Genomic selection; Modern breeding 1 Introduction Abalone (Haliotis spp.) is a very valuable sea aquaculture species of great industrial significance and significant economic value worldwide. Because of its superior meat and growing market demand, abalone aquaculture is of vital importance to coastal economies and the international seafood industry. Among various production traits, growth rate is a critical determinant of aquaculture efficiency that has a direct effect on production cycles, yield, and profitability. Quick-growing abalone species can lower the times and cost of cultivation, thus enhancing overall industry competitiveness (Swezey et al., 2020). Identification of the genetic determinants of growth rate is required for the development of effective breeding programs for improving this trait. Gradual improvement has come through traditional selection breeding programs, but the complex genetic architecture of growth traits and environment are the limiting components. With advances in genomic technology, genomic selection (GS) opens new windows for achieving maximum genetic advance using genome-wide marker information for making more accurate and effective selection (Xiao et al., 2025). This review systematically gathers existing information about genetic variation in abalone growth rate and discusses comprehensively genomic selection techniques applied in its improvement. Its objective is to provide theoretical foundation and practical recommendations for the optimization of breeding programs, ultimately contributing to sustainable development and modernization of abalone aquaculture. 2 Biological Basis of Abalone Growth Rate 2.1 Definition and measurement methods of growth rate traits Growth rate parameters in abalone are optimally described by wet body weight, shell length, shell width, shell height, and corresponding tissue weights such as foot muscle and soft tissue weight. These parameters are measured with calipers and electronic balances at several stages of development, often at several time points to capture longitudinal growth patterns. Correlation and path analyses have been used most commonly to assess
RkJQdWJsaXNoZXIy MjQ4ODYzNA==