Phenotypic and genetic analysis of energy partitioning and feed efficiency in Atlantic salmon.

IF 3.1 1区农林科学 Q1 AGRICULTURE, DAIRY & ANIMAL SCIENCE

Genetics Selection Evolution Pub Date : 2026-05-08 DOI:10.1186/s12711-026-01045-w

Anna Kristina Sonesson, Gareth Frank Difford, Ashie Norris, Bjarne Hatlen

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引用次数: 0

Abstract

Background: There are both economic and environmental motivations to improve feed efficiency. However, direct genetic improvement of feed efficiency ratio (FER; weight gain/feed intake) is difficult. Alternatively, improved FER might be achieved indirectly by selection for increased growth rate and reduced body fat. The aims of this study were (i) to perform a phenotypic analysis of energy partitioning traits among Atlantic salmon families; (ii) to estimate heritability and genetic relationships among feed efficiency and underlying traits; (iii) to determine an optimal breeding strategy to improve feed efficiency in Atlantic salmon.

Results: Moderate genomic heritability estimates were obtained for most traits, e.g. feed intake (0.35), weight gain (0.42), feed efficiency ratio (0.19) and energy density of the gained weight (0.26). Heritability for residual feed intake was 0.04. Genetic correlation between feed efficiency and growth or energy density of the gained weight was 0.68 and -0.64, respectively. A selection index including weight gain and energy density of the gained weight was most beneficial to increase FER. The effect of body energy (reflecting fat deposition) was half of what could be predicted if energy efficiency (EE; energy gain/energy intake) was constant. The fish retained 50 and 49% of the energy and protein intake, respectively. Energy loss was due to heat (29% of intake), faecal loss (18%) and nitrogen excretion (3%). The derived energy and protein budget traits displayed low to moderate genomic heritability (h2 = 0.01-0.31). Protein efficiency reflected FER.

Conclusions: Genetic selection for weight gain and against energy density of the gained weight will improve feed efficiency ratio in Atlantic salmon without the need for individual feed intake records. The results suggest that by selection against body energy, and given the same weight gain, 50% of the reduction in body energy can be realised as reduced feed intake and thus improved FER.

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大西洋鲑鱼能量分配和饲料效率的表型和遗传分析。

背景：提高饲料效率既有经济动机，也有环境动机。然而，饲料效率比（FER；增重/采食量）的直接遗传改良是困难的。另一种可能是通过选择提高生长速率和降低体脂来间接提高饲料质量。本研究的目的是：(i)对大西洋鲑鱼家族之间的能量分配特征进行表型分析；（ii）估计饲料效率和基本性状之间的遗传能力和遗传关系；（iii）确定提高大西洋鲑鱼饲料效率的最佳育种策略。结果：采食量（0.35）、增重（0.42）、饲料效率（0.19）和增重能量密度（0.26）等性状的基因组遗传率均达到中等水平。剩余采食量遗传率为0.04。饲料效率与生长和增重能量密度的遗传相关分别为0.68和-0.64。以增重和增重能量密度为选择指标最有利于提高肥效系数。如果能量效率（EE；能量增益/能量摄入）不变，身体能量（反映脂肪沉积）的影响是可以预测的一半。鱼分别保留了摄入的50%和49%的能量和蛋白质。能量损失是由于热量（摄入的29%）、粪便损失（18%）和氮排泄（3%）。衍生的能量和蛋白质平衡性状具有低至中等的基因组遗传力（h2 = 0.01 ~ 0.31）。蛋白质效率反映FER。结论：以增重和增重能量密度为目标的遗传选择可以提高大西洋鲑鱼的饲料效率，而无需进行个体采食量记录。由此可见，在相同增重条件下，通过对体能的选择，体能减少的50%可以通过减少采食量来实现，从而提高饲料利用率。

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来源期刊

Genetics Selection Evolution 生物-奶制品与动物科学

CiteScore

6.50

自引率

9.80%

发文量

审稿时长

1 months

期刊介绍： Genetics Selection Evolution invites basic, applied and methodological content that will aid the current understanding and the utilization of genetic variability in domestic animal species. Although the focus is on domestic animal species, research on other species is invited if it contributes to the understanding of the use of genetic variability in domestic animals. Genetics Selection Evolution publishes results from all levels of study, from the gene to the quantitative trait, from the individual to the population, the breed or the species. Contributions concerning both the biological approach, from molecular genetics to quantitative genetics, as well as the mathematical approach, from population genetics to statistics, are welcome. Specific areas of interest include but are not limited to: gene and QTL identification, mapping and characterization, analysis of new phenotypes, high-throughput SNP data analysis, functional genomics, cytogenetics, genetic diversity of populations and breeds, genetic evaluation, applied and experimental selection, genomic selection, selection efficiency, and statistical methodology for the genetic analysis of phenotypes with quantitative and mixed inheritance.