International Journal of Marine Science, 2025, Vol.15, No.3, 167-178 http://www.aquapublisher.com/index.php/ijms 169 2.3 Adjustment of behavior and reproductive traits The behavior and reproductive characteristics of abalone also change in artificial environments. Wild abalone often sticks to daytime and comes out to feed at night, and has the habit of getting dark and avoiding light; however, under long-term artificial domestication conditions, abalone's sensitivity to light and disturbance is reduced. It is reported that abalone gradually adapts to daytime feeding and increases daytime feeding in the breeding environment. The clustering and spawning behavior of abalone has changed in the domesticated population. Under wild conditions, abalone often lays eggs simultaneously under specific seasons and environmental stimulation, while artificial breeding groups may be selected and bred, and the breeding season may be extended or advanced. For example, the Nine-hole abalone (Haliotis diversicolor) line raised in indoor constant conditions has an increased number of annual reproduction in the gonad mature period earlier than the wild population. This may be related to artificial high nutritional feed supply and breeding. There are also studies that have observed changes in mate selection and mating behavior of domesticated abalone. In the wild, large male abalone often plays an advantage in reproduction, while in artificial groups, due to high density and controlled environment, small individuals also have the opportunity to reproduce, and the number of effective parents in the group increases. This is beneficial to maintaining genetic diversity to some extent. On the other hand, artificial domestication may have a dual impact on the fertility of abalone: First, good nutrition and environment improve the individual's absolute fertility (the amount of egg laying increases each time); but if the breeding of growth traits is overemphasized, there may be a trade-off effect of reducing reproductive investment, which needs to be avoided through balanced selection (Wang et al., 2019). 3 Genetic Basis Analysis of Trait Variation 3.1 Progress in genetic research on quantitative traits (QTL localization) Important traits such as growth, survival, and stress resistance of abalone are often controlled by multiple genes and are quantitative traits. Through quantitative genetic analysis and QTL (quantitative trait localization) studies, the genetic basis of these traits can be analyzed and used for breeding. In recent years, many scholars have carried out family genetic assessment and linkage mapping research on the quantitative traits of abalone. In South African abalone (H. midae), Tshilate et al. (2024) constructed a high-density genetic linkage map, positioning 5 QTL sites affecting shell length, shell width and body weight, and the contribution rate of each QTL to phenotypic variation is 7.2%~11.4%. These QTLs are co-located on 18 linkage groups, and some sites have a pleiotropy effect on multiple traits. QTL was further localized to the genome, and several candidate genes were identified, such as egf1, notch1, scube2, etc., which were speculated to be related to the growth regulation of abalone. In Japanese Ezo abalone, early family selection experiments estimated that the heritability of growth traits was about 0.2~0.4, suggesting that breeding selection is feasible. Recently, mapping research based on high-throughput classification has been gradually carried out. 3.2 Screening and functional annotation of candidate genes In addition to QTL studies based on linkage mapping, another idea is to screen candidate genes through comparative analysis, that is, to use omics data to find genes significantly related to trait variation and annotate them with functional annotations. Abalone genome and transcriptome data provide the basis for candidate gene screening. In recent years, genome sketches of multiple abalone species have been released one after another, such as Japanese abalone (H. discuss hannai), high-body abalone (H. gigantea), and South African abalone (H. midae), achieving gene prediction and annotation. These genomic data make it possible to screen candidate genes across the genome. For example, in view of the significant growth differentiation of hybrid abalone, Wang et al. (2023) localized GWAS-associated SNPs to genes based on the comparison of the transcriptomes of large and small individuals, and screened out 10 candidate genes closely related to growth differences. These genes include key regulators in pathways such as cell proliferation, development and energy metabolism, and are presumably involved in the differentiation of hybrid abalone growth phenotypes. Studies have shown that screening candidate genes through omics and combining functional analysis is an effective strategy to analyze the quantitative trait mechanism of abalone. In addition to growth, candidate genes for stress resistance traits have also been reported. Some scholars used transcriptome meta analysis of heat stress-responsive transcriptomes to identify 74 core heat
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