Estimation of genetic parameters for the implementation of selective breeding in commercial insect production

IF 3.6 1区 农林科学 Q1 AGRICULTURE, DAIRY & ANIMAL SCIENCE Genetics Selection Evolution Pub Date : 2024-03-25 DOI:10.1186/s12711-024-00894-7
Laura Skrubbeltrang Hansen, Stine Frey Laursen, Simon Bahrndorff, Morten Kargo, Jesper Givskov Sørensen, Goutam Sahana, Hanne Marie Nielsen, Torsten Nygaard Kristensen
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Abstract

There is a burgeoning interest in using insects as a sustainable source of food and feed, particularly by capitalising on various waste materials and by-products that are typically considered of low value. Enhancing the commercial production of insects can be achieved through two main approaches: optimising environmental conditions and implementing selective breeding strategies. In order to successfully target desirable traits through selective breeding, having a thorough understanding of the genetic parameters pertaining to those traits is essential. In this study, a full-sib half-sib mating design was used to estimate variance components and heritabilities for larval size and survival at day seven of development, development time and survival from egg to adult, and to estimate correlations between these traits, within an outbred population of house flies (Musca domestica), using high-throughput phenotyping for data collection. The results revealed low to intermediate heritabilities and positive genetic correlations between all traits except development time and survival to day seven of development and from egg to adulthood. Surprisingly, larval size at day seven exhibited a comparatively low heritability (0.10) in contrast to development time (0.25), a trait that is believed to have a stronger association with overall fitness. A decline in family numbers resulting from low mating success and high overall mortality reduced the amount of available data which resulted in large standard errors for the estimated parameters. Environmental factors made a substantial contribution to the phenotypic variation, which was overall high for all traits. There is potential for genetic improvement in all studied traits and estimates of genetic correlations indicate a partly shared genetic architecture among the traits. All estimates have large standard errors. Implementing high-throughput phenotyping is imperative for the estimation of genetic parameters in fast developing insects, and facilitates age synchronisation, which is vital in a breeding population. In spite of endeavours to minimise non-genetic sources of variation, all traits demonstrated substantial influences from environmental components. This emphasises the necessity of thorough attention to the experimental design before breeding is initiated in insect populations.
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在商业昆虫生产中实施选择性育种的遗传参数估计
人们对利用昆虫作为可持续食品和饲料来源的兴趣日益浓厚,特别是通过利用各种通常被认为价值较低的废料和副产品。提高昆虫的商业产量可通过两种主要方法实现:优化环境条件和实施选择性育种战略。为了通过选择性育种成功锁定理想性状,全面了解与这些性状相关的遗传参数至关重要。本研究采用全同父异母半同母交配设计,在家蝇(Musca domestica)的近交种群中,利用高通量表型数据收集技术估算了幼虫大小、发育第七天的存活率、发育时间和从卵到成虫的存活率的方差成分和遗传力,并估算了这些性状之间的相关性。结果表明,除了发育时间和发育至第七天的存活率以及从卵到成虫的存活率外,所有性状之间的遗传率均为中低水平,遗传相关性为正。令人惊讶的是,第七天的幼虫体型与发育时间(0.25)相比,遗传率相对较低(0.10)。由于交配成功率低和总死亡率高导致家庭数量减少,从而减少了可用数据量,导致估计参数的标准误差较大。环境因素对表型变异有很大影响,所有性状的表型变异都很高。所有研究的性状都有遗传改良的潜力,遗传相关性估计表明性状之间存在部分共享的遗传结构。所有估计值的标准误差都很大。对快速发育昆虫的遗传参数估计而言,实施高通量表型分析势在必行,而且有助于年龄同步,这在育种群体中至关重要。尽管努力将非遗传变异源降到最低,但所有性状都显示出环境因素的巨大影响。这强调了在昆虫种群中开始育种之前对实验设计进行全面关注的必要性。
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来源期刊
Genetics Selection Evolution
Genetics Selection Evolution 生物-奶制品与动物科学
CiteScore
6.50
自引率
9.80%
发文量
74
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.
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