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

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.

Application of a Bio-Economic Model to Demonstrate the Importance of Health Traits in Herd Management of Lithuanian Dairy Breeds.

Assessing the economic importance of traits is crucial for delivering appropriate breeding goals in dairy cattle breeding. The aim of the present study was to calculate economic values (EV) and assign the importance of health traits for three dairy cattle breeds: Lithuanian Black-and-White open population (LBW), Lithuanian Red open population (LR) and Lithuanian Red old genotype (LROG). The EV estimation was carried out using a stochastic bio-economic model SimHerd, which allows the simulation of the expected monetary gain of dairy herds. The simulation model was calibrated for LBW, LR and LROG breeds, taking into account breed-specific phenotypic and economic data. For each trait, two scenarios were simulated with a respective trait at different phenotypic levels. To obtain the EVs, the scenarios were compared with each other in terms of their economic outcomes. In order to avoid the double counting of the effects, the output results were corrected using a multiple regression analysis with mediator variables. The EVs were derived for the traits related to production ECM (energy-corrected milk), fertility, calving traits, calf survival, cow survival and direct health. To demonstrate the importance of health traits in herd management, we provided reliable EVs estimates for functional traits related to herd health. The highest EV for direct health traits, caused by an increase in of 1 percentage point, were those found for mastitis (EUR 1.73 to EUR 1.82 per cow-year) and lameness (EUR 1.07 to EUR 1.27 per cow-year). The total costs per case of ketosis, milk fever and metritis ranged from EUR 1.01 to EUR 1.30, EUR 1.14 to EUR 1.26 and EUR 0.95 to EUR 1.0, respectively. The highest economic values of dystocia were estimated for LROG (EUR -1.32), slightly lower for LBW (EUR -1.31) and LR (EUR -1.23). The results of this study show the importance of health traits to the economic features of cattle herd selection of new breeding goal and this would improve the herd health. The economic evaluation of the functional traits analyzed in this study indicated the significant economic importance of the functional traits in Lithuanian dairy cattle breeds.

Breeding schemes with optimum-contribution selection or truncation selection for beef cattle destined for use on dairy females.

We tested the hypothesis that the size of a beef cattle population destined for use on dairy females is smaller under optimum-contribution selection (OCS) than under truncation selection (TRS) at the same genetic gain (ΔG) and the same rate of inbreeding (ΔF). We used stochastic simulation to estimate true ΔG realized at a 0.005 ΔF in breeding schemes with OCS or TRS. The schemes for the beef cattle population also differed in the number of purebred offspring per dam and the total number of purebred offspring per generation. Dams of the next generation were exclusively selected among the one-year-old heifers. All dams were donors for embryo transfer and produced a maximum of 5 or 10 offspring. The total number of purebred offspring per generation was: 400, 800, 1,600 or 4,000 calves, and it was used as a measure of population size. Rate of inbreeding was predicted and controlled using pedigree relationships. Each OCS (TRS) scheme was simulated for 10 discrete generations and replicated 100 (200) times. The OCS scheme and the TRS scheme with a maximum of 10 offspring per dam required approximately 783 and 1,257 purebred offspring per generation to realize a true ΔG of €14 and a ΔF of 0.005 per generation. Schemes with a maximum of 5 offspring per dam required more purebred offspring per generation to realize a similar true ΔG and a similar ΔF. Our results show that OCS and multiple ovulation and embryo transfer act on selection intensity through different mechanisms to achieve fewer selection candidates and fewer selected sires and dams than under TRS at the same ΔG and a fixed ΔF. Therefore, we advocate the use of a breeding scheme with OCS and multiple ovulation and embryo transfer for beef cattle destined for use on dairy females because it is favorable both from an economic perspective and a carbon footprint perspective.

Short- and long-term consequences of collaboration between Northern European Red dairy and dual-purpose cattle.

In Northern European countries, a great variety of Red cattle populations exists which can be broadly categorized in two groups: specialized dairy and dual-purpose breeds. Collaboration between these breeds (i.e. the exchange of sires across breeds) can be beneficial but is limited so far. The aim of this study was to demonstrate and evaluate consequences of collaboration between Red breeds using stochastic simulations. Two breeding lines (dairy type and dual purpose) were simulated. As a special aspect of this study, differences in genetic levels of breeding traits (milk production, beef production, mastitis resistance, fertility, feed efficiency) have been taken into account. Various scenarios were investigated where across-breed selection was either restricted or allowed and with different correlations between breeding goals in the two lines. The results of this study were influenced by the different genetic levels in breeding traits only in the first years of simulation. In the long run, the breed differences did not affect the degree of collaboration between lines. When the correlation between breeding goals was close to unity, the selection of external bulls was highly beneficial in terms of genetic gain and total monetary gain. Additionally, the lowest rate of inbreeding was found in that case. With decreasing correlations between environments, degree of cooperation between lines rapidly terminated and lines operated individually. In last years of simulation, cooperation was only found when the correlation between breeding goals was close to unity. From a long-term perspective, the exchange of breeding sires across lines also caused negative effects. In the dual-purpose line, deterioration of genetic gain in mastitis resistance and fertility was observed. Additionally, breeding lines genetically converged, which decreased genetic diversity. Collectively, short-term benefits and long-term negative effects have to be reconciled if collaboration between Red breeds in Northern Europe is to be pursued.

Ignoring genotype by environment interaction in the genetic evaluation of dairy cattle reduces accuracy but may increase selection intensity.

Genotype by environment interaction (G×E) may exist for traits that are expressed in different environments. The G×E is often ignored in the genetic evaluation of selection candidates. We hypothesized that genetic gain in 2 environments is always higher when the true value of the genetic correlation (rg) between traits expressed in different environments is considered in the genetic evaluation. We tested this hypothesis by stochastic simulation of dairy cattle breeding programs in a mainstream and a niche environment. The rg was varied from 0 to 1 in steps of 0.1. We simulated the following 3 scenarios: 1Trait_1Index, 2Traits_1Index, and 2Traits_2Indices. The G×E was ignored in the genetic evaluation in the scenario with 1Trait and included in scenarios with 2Traits. Selection was based on the mainstream selection index in both environments in scenarios with 1Index. Selection in the mainstream environment was based on the mainstream selection index and selection in the niche environment was based on the niche selection index in the scenario with 2Indices. With moderate G×E (rg between 0.6 and 0.9), the highest genetic gain was achieved in the niche environment by selecting for the mainstream selection index and ignoring G×E. At lower rg, the highest genetic gain was achieved when considering G×E and selecting for the niche selection index. For the mainstream environment, it was never an advantage to ignore G×E. Therefore, although our hypothesis was confirmed in most cases, there were cases where ignoring G×E was the better option, and using the correct evaluation led to inferior genetic gain. The results of the current study can be used in animal breeding programs that encompass multiple environments.

Effects of Incorporating Dry Matter Intake and Residual Feed Intake into a Selection Index for Dairy Cattle Using Deterministic Modeling.

The inclusion of feed efficiency in the breeding goal for dairy cattle has been discussed for many years. The effects of incorporating feed efficiency into a selection index were assessed by indirect selection (dry matter intake) and direct selection (residual feed intake) using deterministic modeling. Both traits were investigated in three ways: (1) restricting the trait genetic gain to zero, (2) applying negative selection pressure, and (3) applying positive selection pressure. Changes in response to selection from economic and genetic gain perspectives were used to evaluate the impact of including feed efficiency with direct or indirect selection in an index. Improving feed efficiency through direct selection on residual feed intake was the best scenario analyzed, with the highest overall economic response including favorable responses to selection for production and feed efficiency. Over time, the response to selection is cumulative, with the potential for animals to reduce consumption by 0.16 kg to 2.7 kg of dry matter per day while maintaining production. As the selection pressure increased on residual feed intake, the response to selection for production, health, and fertility traits and body condition score became increasingly less favorable. This work provides insight into the potential long-term effects of selecting for feed efficiency as residual feed intake.

Fatty Acid Profiles from Routine Milk Recording as a Decision Tool for Body Weight Change of Dairy Cows after Calving.

Cows mobilize body reserves during early lactation, which is reflected in the milk fatty acid (FA) profile. Milk FA can be routinely predicted by Fourier-transform infrared (FTIR) spectroscopy, and be, thus, used to develop an early indicator for bodyweight change (BWC) in early lactating cows in commercial dairy farms. Cow records from 165 herds in Denmark between 2015 and 2017 were used with bodyweight (BW) records at each milking from floor scales in automatic milking systems. Milk FA in monthly test-day samples was predicted by FTIR. Predictions of BWC were based on a random forest model and included parity, stage of lactation, and test day milk production and components (fat, protein, and FA). Bodyweight loss was mainly explained by decreased short-chain FA (C4:0-C10:0) and increased C18:0 FA. The root mean square error (RMSE) of prediction after cross-validation was 1.79 g/kg of BW (R2 of 0.94). Model evaluation with previously unseen BWC records resulted in reduced prediction performance (RMSE of 2.33 g/kg of BW; R2 of 0.31). An early warning system may be implemented for cows with a large BW loss during early lactation based on milk FA profiles, but model performance should be improved, ideally by using the full FTIR milk spectra.

Genomic Breeding Programs Realize Larger Benefits by Cooperation in the Presence of Genotype × Environment Interaction Than Conventional Breeding Programs.

Genotype × environment interaction (G × E) is of increasing importance for dairy cattle breeders due to international multiple-environment selection of animals as well as the differentiation of production environments within countries. This theoretical simulation study tested the hypothesis that genomic selection (GS) breeding programs realize larger genetic benefits by cooperation in the presence of G × E than conventional pedigree-based selection (PS) breeding programs. We simulated two breeding programs each with their own cattle population and environment. Two populations had either equal or unequal population sizes. Selection of sires was done either across environments (cooperative) or within their own environment (independent). Four scenarios, (GS/PS) × (cooperative/independent), were performed. The genetic correlation (r g ) between the single breeding goal trait expressed in two environments was varied between 0.5 and 0.9. We compared scenarios for genetic gain, rate of inbreeding, proportion of selected external sires, and the split-point r g that is the lowest value of r g for long-term cooperation. Between two equal-sized populations, cooperative GS breeding programs achieved a maximum increase of 19.3% in genetic gain and a maximum reduction of 24.4% in rate of inbreeding compared to independent GS breeding programs. The increase in genetic gain and the reduction in rate of inbreeding realized by GS breeding programs with cooperation were respectively at maximum 9.7% and 24.7% higher than those realized by PS breeding programs with cooperation. Secondly, cooperative GS breeding programs allowed a slightly lower split-point r g than cooperative PS breeding programs (0.85∼0.875 vs ≥ 0.9). Between two unequal-sized populations, cooperative GS breeding programs realized higher increase in genetic gain and showed greater probability for long-term cooperation than cooperative PS breeding programs. Secondly, cooperation using GS were more beneficial to the small population while also beneficial but much less to the large population. In summary, by cooperation in the presence of G × E, GS breeding programs realize larger improvements in terms of the genetic gain and rate of inbreeding, and have greater possibility of long-term cooperation than conventional PS breeding programs. Therefore, we recommend cooperative GS breeding programs in situations with mild to moderate G × E, depending on the sizes of two populations.

Realization of breeding values for milk fatty acids in relation to seasonal variation in organic milk.

Prediction of detailed milk fatty acid (FA) composition by mid-infrared spectroscopy (MIRS) offers possibilities for high-throughput indirect measurements of detailed milk compositional parameters through the milk testing system, which can be used to differentiate the FA profile by genetics or specific management or on dairies for milk quality evaluation. Since 2015, milk samples from all Danish dairy cows under milk testing have been recorded using MIRS. The MIRS software from the FOSS Application Note 64 was used to predict contents of 7 FA groups and 4 individual FA. Data generated from the application note have been used to estimate breeding values for sires for percentage of saturated fat (SFA%) in milk. To investigate whether extreme SFA% breeding values of sires were reflected in the detailed milk FA profile from their daughters, milk samples from 194 cows in 7 organic herds were collected and the detailed FA composition measured by gas chromatography. From each cow, milk samples were collected twice to explore specific seasonal effects of pasture-based diets in relation to sires' estimated breeding value (EBV) for MIRS-predicted SFA% (MIRS-SFA%). The results showed a significant difference in SFA% measured from GC (GC-SFA%) in milk from daughters of sires having high SFA% EBV compared with daughters of sires having low SFA% EBV. The EBV group (low or high) also significantly affected most FA except C13:0, C15:0, C17:0, and C18:1 trans-11. Contents of SFA with even chain-lengths were all higher in the high EBV group, whereas C14:1, C16:1, and the other unsaturated C18 FA had a higher content in the low EBV group. All FA were significantly affected by season. The SFA% decreased from indoor spring feeding to summer pasture, as did FA with chain length ≤16 carbons, whereas long-chain FA (>C17) all increased during summer pasture. The results show that use of MIRS-predicted EBV for SFA% will most likely display a correlated response on the detailed FA composition in milk. In the current study, the combined action of feeding and genetics resulted in a 10 percentage-point difference on average when comparing milk SFA% from daughters of high SFA% EBV sires during indoor spring feeding from one farm to milk SFA% from daughters of low SFA% EBV sires during summer from another farm.

Genotype-by-environment interaction of fertility traits in Danish Holstein cattle using a single-step genomic reaction norm model.

Genotype-by-environment (G × E) interactions could play an important role in cattle populations, and it should be considered in breeding programmes to select the best sires for different environments. The objectives of this study were to study G × E interactions for female fertility traits in the Danish Holstein dairy cattle population using a reaction norm model (RNM), and to detect the particular genomic regions contributing to the performance of these traits and the G × E interactions. In total 4534 bulls were genotyped by an Illumina BovineSNP50 BeadChip. An RNM with a pedigree-based relationship matrix and a pedigree-genomic combined relationship matrix was used to explore the existence of G × E interactions. In the RNM, the environmental gradient (EG) was defined as herd effect. Further, the genomic regions affecting interval from calving to first insemination (ICF) and interval from first to last insemination (IFL) were detected using single-step genome-wide association study (ssGWAS). The genetic correlations between extreme EGs indicated that G × E interactions were sizable for ICF and IFL. The genomic RNM (pedigree-genomic combined relationship matrix) had higher prediction accuracy than the conventional RNM (pedigree-based relationship matrix). The top genomic regions affecting the slope of the reaction norm included immunity-related genes (IL17, IL17F and LIF), and growth-related genes (MC4R and LEP), while the top regions influencing the intercept of the reaction norm included fertility-related genes such as EREG, AREG and SMAD4. In conclusion, our findings validated the G × E interactions for fertility traits across different herds and were helpful in understanding the genetic background of G × E interactions for these traits.

Genotype by environment interaction for activity-based estrus traits in relation to production level for Danish Holstein.

The objective of this study was to investigate whether genotype by environment interaction exists for female fertility traits and production of energy-corrected milk at 70d in milk (ECM70). Fertility traits considered were the activity-based estrus traits interval from calving to first high activity (CFHA), duration of high activity episode (DHA), as an indicator for first estrus duration, and strength of high activity episode (SHA), as an indicator for first estrus strength. The physical activity traits were derived from electronic activity tags for 11,522 first-parity cows housed in 125 commercial dairy herds. Data were analyzed using a univariate random regression animal model (URRM), by regressing the phenotypic performance on the average herd ECM70 as an environmental gradient. Furthermore, the genetic correlations between CFHA and ECM70 as a function of production level were estimated using a bivariate random regression animal model (BRRM). For all traits, heterogeneity of additive genetic variances and heritability estimates was observed. The heritability estimate for CFHA decreased from 0.25 to 0.10 with increasing production level and the heritability estimate for ECM70 decreased from 0.35 to 0.15 with increasing production level using URRM. The genetic correlation of the same trait in low and high production levels was around 0.74 for CFHA and 0.80 for ECM70 using URRM, but when data were analyzed using the multiple-trait analysis (MT), genetic correlation estimates between low and high production levels were not significantly different from unity. Furthermore, the genetic correlation of SHA between low and high production level was 0.22 using URRM, but the corresponding correlation estimate had large standard error when data were analyzed using MT. The genetic correlation between CFHA and ECM70 as a function of production environment was weak but unfavorable and decreased slightly from 0.09 to 0.04 with increasing production level using BRRM. Moreover, the same trend was observed when the data were analyzed using MT where the genetic correlation between CFHA and ECM70 in the low production environment was 0.29 compared with -0.13 in the high production environment, but these estimates had large standard errors. In conclusion, regardless of the trait used, in relation to average herd ECM70 production, the results indicated no clear evidence of strong genotype by environment interaction that would cause significant re-ranking of sires between low and high production environments.

Genotype by environment interaction for the interval from calving to first insemination with regard to calving month and geographic location in Holstein cows in Denmark and Sweden.

The objectives of this study were to investigate genotype by environment interaction effects, with environments defined as calving month and geographic location, on the interval from calving to first insemination (CFI) of Holstein cows in Denmark and Sweden. The data set included 811,285 records on CFI for first-parity cows from January 2010 to January 2014 housed in 7,458 herds. The longest mean CFI was 84.7 d for cows calving in April and the shortest was 76.3 d for cows calving in September. The longest mean CFI of 87.1 d was recorded at the northernmost location (LOC-8), whereas the shortest mean CFI of 73.5 d was recorded at the southernmost location (LOC-1). The multiple trait approach, in which CFI values in different calving months and different geographic locations were treated as different traits, was used to estimate the variance components and genetic correlations for CFI by using the average information (AI)-REML procedure in a bivariate sire model. Estimates of genetic variance and heritability were highest for January calvings and 3 times smaller for June calvings. Location 2 had the highest heritability and LOC-8 the lowest, with heritability estimates decreasing from LOC-2 to LOC-8. Genetic correlations of CFI between calving months were weakest between cold months (December and January) and warm months (June, August, and September); the lowest estimate was found between January and September calvings. Genetic correlations of CFI between the different geographic locations were generally strong, and the weakest correlation was between LOC-3 and LOC-8. These results indicate a genotype by environment interaction for CFI primarily regarding seasons described by calving months. The effect of geographic location was less important, mostly producing a scaling effect of CFI in different locations. We concluded that CFI is more sensitive to seasonal effects than geographic locations in Denmark and Sweden.

Estrus traits derived from activity measurements are heritable and closely related to the time from calving to first insemination.

The aim of this study was to estimate genetic parameters for estrus-related traits that could improve selection for increased fertility due to improved ability of the cow to return to cycling and go into heat after calving. We compared the time from calving to first insemination (CFI) to 3 physical activity traits: the interval from calving to first high activity (CFHA), estrus duration (ED), and estrus strength (ES). We calculated CFI based on data from commercial Holstein herds that included the insemination dates for 11,363 cows. The CFHA, ED, and ES traits were derived from electronic activity tags for 3,533 Holstein cows. Estimates of heritability were 0.07 for CFI, 0.16 for CFHA, 0.02 for ED, and 0.05 for ES. We found a strong genetic correlation between CFI and CFHA (0.96). Genetic correlations between ED and CFI and CFHA were -0.37 and -0.68, respectively. Genetic correlations between ES and CFI and CFHA were -0.50 and -0.58, respectively. The heritability of CFHA and its strong genetic correlation with CFI suggest that including CFHA in the genetic evaluation of female cow fertility could improve the effectiveness of selection, because CFHA reflects the ability to return to cyclicity and go into heat after calving.