We tested the premise that optimum-contribution selection with pedigree relationships to control inbreeding (POCS) realises at least as much true genetic gain as optimum-contribution selection with genomic relationships (GOCS) at the same rate of true inbreeding. We used stochastic simulation to estimate rates of true genetic gain realised by POCS and GOCS at a 0.01 rate of true inbreeding in three breeding schemes with best linear unbiased predictions of breeding values based on pedigree (PBLUP) and genomic (GBLUP) information. The three breeding schemes differed in number of matings and litter size. Selection was for a single trait with a heritability of 0.2. The trait was controlled by 7702 biallelic quantitative-trait loci (QTL) that were distributed across a 30-M genome. The genome contained 54,218 biallelic markers that were used in GOCS and GBLUP. A total of 6012 identity-by-descent loci were placed across the genome in base populations. Unique alleles at these loci were used to calculate rates of true inbreeding. Breeding schemes were run for 10 discrete generations. Selection candidates were genotyped and phenotyped before selection. POCS realised more true genetic gain than GOCS at a 0.01 rate of true inbreeding in all combinations of breeding scheme and prediction method. POCS realised 14 to 33% more true genetic gain than GOCS with PBLUP in the three breeding schemes. It realised 1.5 to 5.7% more true genetic gain than GOCS with GBLUP. POCS realised more true genetic gain than GOCS because it managed expected genetic drift without restricting selection at QTL. By contrast, GOCS penalised changes in allele frequencies at markers that were generated by genetic drift and selection. Because these marker alleles were in linkage disequilibrium with QTL alleles, GOCS restricted changes in allele frequencies at QTL. This provides little incentive to use GOCS and highlights that we have more to learn before we can control inbreeding using genomic relationships in selective-breeding schemes. Until we can do so, POCS remains a worthy method of optimum-contribution selection because it realises more true genetic gain than GOCS at the same rate of true inbreeding.

Within ecophysiological and genetic studies on insects, morphological and physiological traits are commonly assessed and phenotypes are typically obtained from manual measurements on numerous individuals. Manual observations are, however, time consuming, can introduce observer bias and are prone to human error. Here, we contrast results obtained from manual assessment of larval size and thermal tolerance traits in black soldier flies (Hermetia illucens) and houseflies (Musca domestica) that have been acclimated under three different temperature regimes with those obtained automatically using an image analysis software (Noldus EthoVision XT). We found that (i) larval size estimates of both species, obtained by manual weighing or by using the software, were highly correlated, (ii) measures of heat and cold tolerance using manual and automated approaches provided qualitatively similar results, and (iii) by using the software we obtained quantifiable information on stress responses and acclimation effects of potentially higher ecological relevance than the endpoint traits that are typically assessed when manual assessments are used. Based on these findings, we argue that automated assessment of insect stress responses and largescale phenotyping of morphological traits such as size will provide new opportunities within many disciplines where accurate and largescale phenotyping of insects is required.

Background: 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. Results: 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. Conclusions: 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.

Black soldier fly (BSF) larvae are exceptionally efficient at converting otherwise unusable waste products, while having a minimal impact on the environment. To optimise the production of BSF larvae, selective breeding could be used. With selective breeding, the best individuals to breed the next generation are selected, for example, with a breeding goal. This study aimed to make the first step towards defining such a breeding goal, by estimating the economic values (EV) of traits that are important for the production of BSF larvae. EV were estimated for larval mass on day 15, feed intake, feed conversion ratio, growth rate, dry mass-, protein- and fat content, development time, eggs per fly, egg hatching rate, and larval mortality. A bio-economic model was used to estimate the profit of a BSF production system that produces 1000 kg of wet larvae at harvesting. The EV of a trait was estimated as the increase in profit when the trait value was increased by 10%, whilst the other traits remained unchanged. EV were expressed per 10% increase, and changes in revenues and costs were specified. The results showed traits with the highest EV were related to composition (dry mass-, and protein-content) and growth (larval mass, development time, growth rate). Traits related to reproduction and flies (development from pupa to fly, number of eggs) had the lowest EV. Due to the lack of information on genetic parameters, the EV are expressed per +10% of the mean value of a trait. In the future, when more information is available, the EV should be expressed per genetic standard deviation. In conclusion, this is the first study that estimated EV for an insect species. The results are a first step towards developing a more sophisticated breeding program for optimizing BSF production.

Black soldier fly (BSF; Hermetia illucens) is a promising insect species for food and feed production as its larvae can convert different organic waste to high-value protein. Selective breeding is one way to optimize production, but the potential of breeding is only starting to be explored and not yet utilized for BSF. To assist in monitoring a captive population and implementing a breeding program, genomics tools are imperative. We conducted whole genome sequencing of two captive populations separated by geographical distance - Denmark (DK) and Texas, USA (TX). Various population genetics analyses revealed a moderate genetic differentiation between two populations. Moreover, we observed higher inbreeding in the DK population, and the detection of a subpopulation within DK population aligned well with the recent foundation of the DK population from two captive populations. Additionally, we generated gene ontology annotation and variants annotation for wider potential applications. Our findings establish a robust marker set for research in population genetics, facilitating the monitoring of inbreeding and laying the groundwork for practical breeding programs for BSF.