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Most deleterious variants are recessive and segregate at relatively low frequency. Therefore, high sample sizes are required to identify these variants. In this study we report a large-scale sequence based genome-wide association study (GWAS) in pigs, with a total of 120,000 Large White and 80,000 Synthetic breed animals imputed to sequence using a reference population of approximately 1,100 whole genome sequenced pigs. We imputed over 20 million variants with high accuracies (R2>0.9) even for low frequency variants (1-5% minor allele frequency). This sequence-based analysis revealed a total of 14 additive and 9 non-additive significant quantitative trait loci (QTLs) for growth rate and backfat thickness. With the non-additive (recessive) model, we identified a deleterious missense SNP in the CDHR2 gene reducing growth rate and backfat in homozygous Large White animals. For the Synthetic breed, we revealed a QTL on chromosome 15 with a frameshift variant in the OBSL1 gene. This QTL has a major impact on both growth rate and backfat, resembling human 3M-syndrome 2 which is related to the same gene. With the additive model, we confirmed known QTLs on chromosomes 1 and 5 for both breeds, including variants in the MC4R and CCND2 genes. On chromosome 1, we disentangled a complex QTL region with multiple variants affecting both traits, harboring 4 independent QTLs in the span of 5 Mb. Together we present a large scale sequence-based association study that provides a key resource to scan for novel variants at high resolution for breeding and to further reduce the frequency of deleterious alleles at an early stage in the breeding program., Competing Interests: All authors declare that the results are presented in full and present no conflict of interest., (Copyright: © 2024 Boshove et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

In pig production, the production animals are generally three- or four-way crossbreeds. Reliable information regarding the breed of origin of slaughtered pigs is useful, even a prerequisite, for a number of purposes, e.g., evaluating potential breed effects on carcass grading. Genetic data from slaughtered pigs can easily be extracted and used for crossbreed classification. In the current study, four classification methods, namely, random forest (RF), ADMIXTURE, partial least squares regression (PLSR), and partial least squares together with quadratic discriminant analysis (PLS-QDA) were evaluated on simulated ( n = 7,500) genomic data of crossbreeds. The derivation of the theory behind PLS-QDA is a major part of the current study, whereas RF and ADMIXTURE are known and well-described in the literature. Classification success (CS) rate, square loss (SL), and Kullback-Leibler (KL) divergence loss for the simulated data were used to compare methods. Overall, PLS-QDA performed best with 99%/0.0018/0.002 (CS/SL/KL) vs. 97%/0.0084/0.051, 97%/0.0087/0.0623, and 17%/0.068/0.39 for PLSR, ADMIXTURE, and RF, respectively. PLS-QDA and ADMIXTURE, as the most relevant methods, were used on a real dataset ( n = 1,013) from Norway where the two largest classes contained 532 and 192 (PLS-QDA), and 531 and 193 (ADMIXTURE) individuals, respectively. These two classes were expected to be dominating a priori . The Bayesian nature of PLS-QDA enables inclusion of desirable features such as a separate class "unknown breed combination" and informative priors for crossbreeds, making this a preferable method for the classification of breed combination in the industry., Competing Interests: Authors AH and LG were employed by the company Animalia AS. Author MS was employed by the company Norsvin SA. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Vinje, Brustad, Heggli, Sevillano, Van Son and Gangsei.)

Anaerobic digestion is a well-known technology with wide application in the treatment of high-strength organic wastes. The economic feasibility of this type of installation is usually attained thanks to the availability of fiscal incentives. In this review, an analysis of the different factors associated with this biological treatment and a description of alternatives available in literature for increasing performance of the process were provided. The possible integration of this process into a biorefinery as a way for producing energy and chemical products from the conversion of wastes and biomass also analyzed. The future outlook of anaerobic digestion will be closely linked to circular economy principles. Therefore, this technology should be properly integrated into any production system where energy can be recovered from organics. Digestion can play a major role in any transformation process where by-products need further stabilization or it can be the central core of any waste treatment process, modifying the current scheme by a concatenation of several activities with the aim of increasing the efficiency of the conversion. Thus, current plants dedicated to the treatment of wastewaters, animal manures, or food wastes can become specialized centers for producing bio-energy and green chemicals. However, high installation costs, feedstock dispersion and market distortions were recognized as the main parameters negatively affecting these alternatives.

In pig breeding, selection commonly takes place in purebred (PB) pigs raised mainly in temperate climates (TEMP) under optimal environmental conditions in nucleus farms. However, pork production typically makes use of crossbred (CB) animals raised in nonstandardized commercial farms, which are located not only in TEMP regions but also in tropical and subtropical regions (TROP). Besides the differences in the genetic background of PB and CB, differences in climate conditions, and differences between nucleus and commercial farms can lower the genetic correlation between the performance of PB in the TEMP (PBTEMP) and CB in the TROP (CBTROP). Genetic correlations (rg) between the performance of PB and CB growing-finishing pigs in TROP and TEMP environments have not been reported yet, due to the scarcity of data in both CB and TROP. Therefore, the present study aimed 1) to verify the presence of genotype × environment interaction (G × E) and 2) to estimate the rg for carcass and growth performance traits when PB and 3-way CB pigs are raised in 2 different climatic environments (TROP and TEMP). Phenotypic records of 217,332 PB and 195,978 CB, representing 2 climatic environments: TROP (Brazil) and TEMP (Canada, France, and the Netherlands) were available for this study. The PB population consisted of 2 sire lines, and the CB population consisted of terminal 3-way cross progeny generated by crossing sires from one of the PB sire lines with commercially available 2-way maternal sow crosses. G × E appears to be present for average daily gain, protein deposition, and muscle depth given the rg estimates between PB in both environments (0.64 to 0.79). With the presence of G × E, phenotypes should be collected in TROP when the objective is to improve the performance of CB in the TROP. Also, based on the rg estimates between PBTEMP and CBTROP (0.22 to 0.25), and on the expected responses to selection, selecting based only on the performance of PBTEMP would give limited genetic progress in the CBTROP. The rg estimates between PBTROP and CBTROP are high (0.80 to 0.99), suggesting that combined crossbred-purebred selection schemes would probably not be necessary to increase genetic progress in CBTROP. However, the calculated responses to selection show that when the objective is the improvement of CBTROP, direct selection based on the performance of CBTROP has the potential to lead to the higher genetic progress compared with indirect selection on the performance of PBTROP., (© The Author(s) 2019. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Heat stress is an important issue in the global dairy industry. In tropical areas, an alternative to overcome heat stress is the use of crossbred animals or synthetic breeds, such as the Girolando. In this study, we performed a genome-wide association study (GWAS) and post-GWAS analyses for heat stress in an experimental Gir × Holstein F 2 population. Rectal temperature (RT) was measured in heat-stressed F 2 animals, and the variation between 2 consecutive RT measurements (ΔRT) was used as the dependent variable. Illumina BovineSNP50v1 BeadChip (Illumina Inc., San Diego, CA) and single-SNP approach were used for GWAS. Post-GWAS analyses were performed by gene ontology terms enrichment and gene-transcription factor (TF) networks, generated from enriched TF. The breed origin of marker alleles in the F 2 population was assigned using the breed of origin of alleles (BOA) approach. Heritability and repeatability estimates (± standard error) for ΔRT were 0.13 ± 0.08 and 0.29 ± 0.06, respectively. Association analysis revealed 6 SNP significantly associated with ΔRT. Genes involved with biological processes in response to heat stress effects (LIF, OSM, TXNRD2, and DGCR8) were identified as putative candidate genes. After performing the BOA approach, the 10% of F 2 animals with the lowest breeding values for ΔRT were classified as low-ΔRT, and the 10% with the highest breeding values for ΔRT were classified as high-ΔRT. On average, 49.4% of low-ΔRT animals had 2 alleles from the Holstein breed (HH), and 39% had both alleles from the Gir breed (GG). In high-ΔRT animals, the average proportion of animals for HH and GG were 1.4 and 50.2%, respectively. This study allowed the identification of candidate genes for ΔRT in Gir × Holstein crossbred animals. According to the BOA approach, Holstein breed alleles could be associated with better response to heat stress effects, which could be explained by the fact that Holstein animals are more affected by heat stress than Gir animals and thus require a genetic architecture to defend the body from the deleterious effects of heat stress. Future studies can provide further knowledge to uncover the genetic architecture underlying heat stress in crossbred cattle., (Copyright © 2019 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

The genome in crossbred animals is a mosaic of genomic regions inherited from the different parental breeds. We previously showed that effects of haplotypes strongly associated with crossbred performance are different depending upon from which parental breed they are inherited, however, the majority of the genomic regions are not or only weakly associated with crossbred performance. Therefore, our objective was to develop a model that distinguishes between selected single nucleotide polymorphisms (SNP) strongly associated with crossbred performance and all remaining SNP. For the selected SNP, breed-specific allele effects were fitted whereas for the remaining SNP it was assumed that effects are the same across breeds (SEL-BOA model). We used data from three purebred populations; S, LR, and LW, and the corresponding crossbred population. We selected SNP that explained together either 5 or 10% of the total crossbred genetic variance for average daily gain in each breed of origin. The model was compared to a model where all SNP-alleles were allowed to have different effects for crossbred performance depending upon the breed of origin (BOA model) and to a model where all SNP-alleles had the same effect for crossbred performance across breeds (G model). Across the models, the heritability for crossbred performance was very similar with values of 0.29-0.30. With the SEL-BOA models, in general, the purebred-crossbred genetic correlation (r pc ) for the selected SNP was larger than for the non-selected SNP. For breed LR, the r pc for selected SNP and non-selected SNP estimated with the SEL-BOA 5% and SEL-BOA 10% were very different compared to the r pc estimated with the G or BOA model. For breeds S and LW, there was not a big discrepancy for the r pc estimated with the SEL-BOA models and with the G or BOA model. The BOA model calculates more accurate breeding values of purebred animals for crossbred performance than the G model when r pc differs (≈10%) between the G and the BOA model. Superiority of the SEL-BOA model compared to the BOA model was only observed for SEL-BOA 10% and when r pc for the selected and non-selected SNP differed both (≈20%) from the r pc estimated by the G or BOA model.

Rhipicephalus (Boophilus) microplus is the main cattle ectoparasite in tropical areas. Gir × Holstein crossbred cows are well adapted to different production systems in Brazil. In this context, we performed genome-wide association study (GWAS) and post-GWAS analyses for R. microplus resistance in an experimental Gir × Holstein F 2 population. Single nucleotide polymorphisms (SNP) identified in GWAS were used to build gene networks and to investigate the breed of origin for its alleles. Tick artificial infestations were performed during the dry and rainy seasons. Illumina BovineSNP50 BeadChip (Illumina Inc., San Diego, CA) and single-step BLUP procedure was used for GWAS. Post-GWAS analyses were performed by gene ontology terms enrichment and gene transcription factors networks, generated from enriched transcription factors, identified from the promoter sequences of selected gene sets. The genetic origin of marker alleles in the F 2 population was assigned using the breed of origin of alleles approach. Heritability estimates for tick counts were 0.40 ± 0.11 in the rainy season and 0.54 ± 0.11 in the dry season. The top ten 0.5-Mbp windows with the highest percentage of genetic variance explained by SNP markers were found in chromosomes 10 and 23 for both the dry and rainy seasons. Gene network analyses allowed the identification of genes involved with biological processes relevant to immune system functions (TREM1, TREM2, and CD83). Gene-transcription factors network allowed the identification of genes involved with immune functions (MYO5A, TREML1, and PRSS16). In resistant animals, the average proportion of animals showing significant SNPs with paternal and maternal alleles originated from Gir breed was 44.8% whereas the proportion of animals with both paternal and maternal alleles originated from Holstein breed was 11.3%. Susceptible animals showing both paternal and maternal alleles originated from Holstein breed represented 44.6% on average, whereas both paternal and maternal alleles originated from Gir breed animals represented 9.3%. This study allowed us to identify candidate genes for tick resistance in Gir × Holstein crossbreds in both rainy and dry seasons. According to the origin of alleles analysis, we found that most animals classified as resistant showed 2 alleles from Gir breed, while the susceptible ones showed alleles from Holstein. Based on these results, the identified genes may be thoroughly investigated in additional experiments aiming to validate their effects on tick resistance phenotype in cattle., (Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Pig-breeding businesses have resulted in global breeding programs that select pigs to perform well on high-energy high-protein diets, which are traditionally based on corn and soybean meal. Nowadays, there is a shift toward diets based on cereals and co-products, therefore, high dietary inclusion of co-products can modify the expected performance of these pigs. The objective of this study was to evaluate the effect of feeding a cereals-alternative ingredients diet (CA-diet) compared to a corn-soybean meal diet (CS-diet) on the growth performance, feed efficiency, and carcass characteristics of genetically similar growing-finishing gilts and boars. In total, 160 pigs, 80 gilts and 80 boars, coming from 18 litters were used. The pigs were blocked based on litter, to ensure no genetic differences between the 2 treatments. For the starter phase, pigs fed the CA-diet performed in terms of growth, and feed efficiency, as good as the pigs fed CS-diet (P > 0.05). For the grower phase, pigs fed the CA-diet had the same ADFI (P > 0.05), but a lower daily energy intake (ADEI) (P < 0.001), and same growth performance (P > 0.05) than pig fed the CS-diet, therefore pigs fed the CA-diet were more efficient in terms of residual energy intake (REI) (P < 0.001). For the finisher phase, interaction between diet and sex had an effect on ADFI (P < 0.001), ADEI (P < 0.001), ADG (P = 0.010), and lipid deposition (Ld) (P = 0.016). Pigs fed the CA-diet were less efficient than pigs fed the CS-diet, i.e., G:F (P < 0.001), RFI (P < 0.001), and REI (P = 0.007). In general, feeding a CA-diet to pigs showed to improve the ratio between Pd and Ld, especially for boars. Also, pigs fed the CA-diet showed thinner back fat thickness (P < 0.001), same loin depth thickness (P > 0.05), but lower dressing percentage (P < 0.001), than pigs fed the CS-diet.

Background: This study investigated if the allele effect of a given single nucleotide polymorphism (SNP) for crossbred performance in pigs estimated in a genomic prediction model differs depending on its breed-of-origin, and how these are related to estimated effects for purebred performance., Results: SNP-allele substitution effects were estimated for a commonly used SNP panel using a genomic best linear unbiased prediction model with breed-specific partial relationship matrices. Estimated breeding values for purebred and crossbred performance were converted to SNP-allele effects by breed-of-origin. Differences between purebred and crossbred, and between breeds-of-origin were evaluated by comparing percentage of variance explained by genomic regions for back fat thickness (BF), average daily gain (ADG), and residual feed intake (RFI). From ten regions explaining most additive genetic variance for crossbred performance, 1 to 5 regions also appeared in the top ten for purebred performance. The proportion of genetic variance explained by a genomic region and the estimated effect of a haplotype in such a region were different depending upon the breed-of-origin. To illustrate underlying mechanisms, we evaluated the estimated effects across breeds-of-origin for haplotypes associated to the melanocortin 4 receptor (MC4R) gene, and for the MC4Rsnp itself which is a missense mutation with a known effect on BF and ADG. Although estimated allele substitution effects of the MC4Rsnp mutation were very similar across breeds, explained genetic variance of haplotypes associated to the MC4R gene using a SNP panel that does not include the mutation, was considerably lower in one of the breeds where the allele frequency of the mutation was the lowest., Conclusions: Similar regions explaining similar additive genetic variance were observed across purebred and crossbred performance. Moreover, there was some overlap across breeds-of-origin between regions that explained relatively large proportions of genetic variance for crossbred performance; albeit that the actual proportion of variance deviated across breeds-of-origin. Results based on a missense mutation in MC4R confirmed that even if a causal locus has similar effects across breeds-of-origin, estimated effects and explained variance in its region using a commonly used SNP panel can strongly depend on the allele frequency of the underlying causal mutation.

A major objective of pork producers is to reduce production cost. Feeding may account for over 75% of pork production costs. Thus, selecting pigs for feed efficiency (FE) traits is a priority in pig breeding programs. While in the Americas, pigs are typically fed high-input diets, based on corn and soybean meal (CS); in Western Europe, pigs are commonly fed diets based on wheat and barley with high amounts of added protein-rich coproducts (WB), e.g., from milling and seed-oil industries. These two feeding scenarios provided a realistic setting for investigating a specific type of genotype by environment interaction; thus, we investigated the genotype by feed interaction (GxF). In the presence of a GxF, different feed compositions should be considered when selecting for FE. This study aimed to 1) verify the presence of a GxF for FE and growth performance traits in different growth phases (starter, grower, and finisher) of 3-way crossbred growing-finishing pigs fed either a CS (547 boars and 558 gilts) or WB (567 boars and 558 gilts) diet; and 2) to assess and compare the expected responses to direct selection under the 2 diets and the expected correlated responses for one diet to indirect selection under the other diet. We found that GxF did not interfere in the ranking of genotypes under both diets for growth, protein deposition, feed intake, energy intake, or feed conversion rate. Therefore, for these traits, we recommend changing the diet of growing-finishing pigs from high-input feed (i.e., CS) to feed with less valuable ingredients, as WB, to reduce production costs and the environmental impact, regardless of which diet is used in selection. We found that GxF interfered in the ranking of genotypes and caused heterogeneity of genetic variance under both diets for lipid deposition (LD), residual energy intake (REI), and residual feed intake (RFI). Thus, selecting pigs under a diet different from the diet used for growing-finishing performance could compromise the LD in all growth phases, compromise the REI and RFI during the starter phase, and severely compromise the REI during the grower phase. In particular, when pigs are required to consume a WB diet for growing-finishing performance, pigs should be selected for FE under the same diet. Breeding pigs for FE under lower-input diets should be considered, because FE traits will become more important and lower-input diets will become more widespread in the near future.

Selection for feed efficiency (FE) is a strategy to reduce the production costs per unit of animal product, which is one of the major objectives of current animal breeding programs. In pig breeding, selection for FE and other traits traditionally takes place based on purebred pig (PB) performance at the nucleus level, while pork production typically makes use of crossbred animals (CB). The success of this selection, therefore, depends on the genetic correlation between the performance of PB and CB (rpc) and on the genetic correlation (rg) between FE and the other traits that are currently under selection. Different traits are being used to account for FE, but the rpc has been reported only for feed conversion rate. Therefore, this study aimed 1) to estimate the rpc for growth performance, carcass, and FE traits; 2) to estimate rg between traits within PB and CB populations; and 3) to compare three different traits representing FE: feed conversion rate, residual energy intake (REI), and residual feed intake (RFI). Phenotypes of 194,445 PB animals from 23 nucleus farms, and 46,328 CB animals from three farms where research is conducted under near commercial production conditions were available for this study. From these, 22,984 PB and 8,657 CB presented records for feed intake. The PB population consisted of five sire and four dam lines, and the CB population consisted of terminal cross-progeny generated by crossing sires from one of the five PB sire lines with commercially available two-way maternal sow crosses. Estimates of rpc ranged from 0.61 to 0.71 for growth performance traits, from 0.75 to 0.82 for carcass traits, and from 0.62 to 0.67 for FE traits. Estimates of rg between growth performance, carcass, and FE traits differed within PB and CB. REI and RFI showed substantial positive rg estimates in PB (0.84) and CB (0.90) populations. The magnitudes of rpc estimates indicate that genetic progress is being realized in CB at the production level from selection on PB performance at nucleus level. However, including CB phenotypes recorded on production farms, when predicting breeding values, has the potential to increase genetic progress for these traits in CB. Given the genetic correlations with growth performance traits and the genetic correlation between the performance of PB and CB, REI is an attractive FE parameter for a breeding program.

After publication of our article [1], we found a typo in the formula to build the genomic relationship matrix using allele frequencies across all genotyped pigs (matrix) and the genomic relationship matrix using breed-specific allele frequencies (matrix), and we noted that the description to this formula is not very clear.

Background: Genomic prediction of purebred animals for crossbred performance can be based on a model that estimates effects of single nucleotide polymorphisms (SNPs) in purebreds on crossbred performance. For crossbred performance, SNP effects might be breed-specific due to differences between breeds in allele frequencies and linkage disequilibrium patterns between SNPs and quantitative trait loci. Accurately tracing the breed-of-origin of alleles (BOA) in three-way crosses is possible with a recently developed procedure called BOA. A model that accounts for breed-specific SNP effects (BOA model), has never been tested empirically on a three-way crossbreeding scheme. Therefore, the objectives of this study were to evaluate the estimates of variance components and the predictive accuracy of the BOA model compared to models in which SNP effects for crossbred performance were assumed to be the same across breeds, using either breed-specific allele frequencies ([Formula: see text] model) or allele frequencies averaged across breeds ([Formula: see text] model). In this study, we used data from purebred and three-way crossbred pigs on average daily gain (ADG), back fat thickness (BF), and loin depth (LD)., Results: Estimates of variance components for crossbred performance from the BOA model were mostly similar to estimates from models [Formula: see text] and [Formula: see text]. Heritabilities for crossbred performance ranged from 0.24 to 0.46 between traits. Genetic correlations between purebred and crossbred performance ([Formula: see text]) across breeds ranged from 0.30 to 0.62 for ADG and from 0.53 to 0.74 for BF and LD. For ADG, prediction accuracies of the BOA model were higher than those of the [Formula: see text] and [Formula: see text] models, with significantly higher accuracies only for one maternal breed. For BF and LD, prediction accuracies of models [Formula: see text] and [Formula: see text] were higher than those of the BOA model, with no significant differences. Across all traits, models [Formula: see text] and [Formula: see text] yielded similar predictions., Conclusions: The BOA model yielded a higher prediction accuracy for ADG in one maternal breed, which had the lowest [Formula: see text] (0.30). Using the BOA model was especially relevant for traits with a low [Formula: see text]. In all other cases, the use of crossbred information in models [Formula: see text] and [Formula: see text], does not jeopardize predictions and these models are more easily implemented than the BOA model.

Background: For some species, animal production systems are based on the use of crossbreeding to take advantage of the increased performance of crossbred compared to purebred animals. Effects of single nucleotide polymorphisms (SNPs) may differ between purebred and crossbred animals for several reasons: (1) differences in linkage disequilibrium between SNP alleles and a quantitative trait locus; (2) differences in genetic backgrounds (e.g., dominance and epistatic interactions); and (3) differences in environmental conditions, which result in genotype-by-environment interactions. Thus, SNP effects may be breed-specific, which has led to the development of genomic evaluations for crossbred performance that take such effects into account. However, to estimate breed-specific effects, it is necessary to know breed origin of alleles in crossbred animals. Therefore, our aim was to develop an approach for assigning breed origin to alleles of crossbred animals (termed BOA) without information on pedigree and to study its accuracy by considering various factors, including distance between breeds., Results: The BOA approach consists of: (1) phasing genotypes of purebred and crossbred animals; (2) assigning breed origin to phased haplotypes; and (3) assigning breed origin to alleles of crossbred animals based on a library of assigned haplotypes, the breed composition of crossbred animals, and their SNP genotypes. The accuracy of allele assignments was determined for simulated datasets that include crosses between closely-related, distantly-related and unrelated breeds. Across these scenarios, the percentage of alleles of a crossbred animal that were correctly assigned to their breed origin was greater than 90 %, and increased with increasing distance between breeds, while the percentage of incorrectly assigned alleles was always less than 2 %. For the remaining alleles, i.e. 0 to 10 % of all alleles of a crossbred animal, breed origin could not be assigned., Conclusions: The BOA approach accurately assigns breed origin to alleles of crossbred animals, even if their pedigree is not recorded.

Background: Although breeding programs for pigs and poultry aim at improving crossbred performance, they mainly use training populations that consist of purebred animals. For some traits, e.g. residual feed intake, the genetic correlation between purebred and crossbred performance is low and thus including crossbred animals in the training population is required. With crossbred animals, the effects of single nucleotide polymorphisms (SNPs) may be breed-specific because linkage disequilibrium patterns between a SNP and a quantitative trait locus (QTL), and allele frequencies and allele substitution effects of a QTL may differ between breeds. To estimate the breed-specific effects of alleles in a crossbred population, the breed-of-origin of alleles in crossbred animals must be known. This study was aimed at investigating the performance of an approach that assigns breed-of-origin of alleles in real data of three-breed cross pigs. Genotypic data were available for 14,187 purebred, 1354 F1, and 1723 three-breed cross pigs., Results: On average, 93.0 % of the alleles of three-breed cross pigs were assigned a breed-of-origin without using pedigree information and 94.6 % with using pedigree information. The assignment percentage could be improved by allowing a percentage (fr) of the copies of a haplotype to be observed in a purebred population different from the assigned breed-of-origin. Changing fr from 0 to 20 %, increased assignment of breed-of-origin by 0.6 and 0.7 % when pedigree information was and was not used, respectively, which indicates the benefit of setting fr to 20 %., Conclusions: Breed-of-origin of alleles of three-breed cross pigs can be derived empirically without the need for pedigree information, with 93.7 % of the alleles assigned a breed-of-origin. Pedigree information is useful to reduce computation time and can slightly increase the percentage of assignments. Knowledge on the breed-of-origin of alleles allows the use of models that implement breed-specific effects of SNP alleles in genomic prediction, with the aim of improving selection of purebred animals for crossbred offspring performance.

Seasonal infertility is often observed as anestrus and a lower conception rate resulting in a reduced farrowing rate (FR) during late summer and early autumn. This is often regarded as an effect of heat stress; however, we observed a reduction in the FR of sows even after correcting for ambient temperature in our data. Therefore, we added change in photoperiod in the analysis of FR considering its effect on sow fertility. Change in photoperiod was modeled using the cosine of the day of first insemination within a year. On an average, the FR decreased by 2% during early autumn with decreasing daily photoperiod compared with early summer with almost no change in daily photoperiod. It declined 0.2% per degree Celsius of ambient temperature above 19.2°C. This result is a step forward in disentangling the 2 environmental components responsible for seasonal infertility. Our next aim was to estimate the magnitude of genetic variation in FR in response to change in photoperiod and ambient temperature to explore opportunities for selecting pigs to have a constant FR throughout the year. We used reaction norm models to estimate additive genetic variation in response to change in photoperiod and ambient temperature. The results revealed a larger genetic variation at stressful environments when daily photoperiod decreased and ambient temperatures increased above 19.2°C compared with neutral environments. Genetic correlations between stressful environments and nonstressful environments ranged from 0.90 (±0.03) to 0.46 (±0.13) depending on the severity of the stress, indicating changes in expression of FR depending on the environment. The genetic correlation between responses of pigs to changes in photoperiod and to those in ambient temperature were positive, indicating that pigs tolerant to decreasing daily photoperiod are also tolerant to high ambient temperatures. Therefore, selection for tolerance to decreasing daily photoperiod should also increase tolerance to high ambient temperatures or vice versa.

Background: Cryptorchidism and scrotal/inguinal hernia are the most frequent congenital defects in pigs. Identification of genomic regions that control these congenital defects is of great interest to breeding programs, both from an animal welfare point of view as well as for economic reasons. The aim of this genome-wide association study (GWAS) was to identify single nucleotide polymorphisms (SNPs) that are strongly associated with these congenital defects. Genotypes were available for 2570 Large White (LW) and 2272 Landrace (LR) pigs. Breeding values were estimated based on 1 359 765 purebred and crossbred male offspring, using a binary trait animal model. Estimated breeding values were deregressed (DEBV) and taken as the response variable in the GWAS., Results: Heritability estimates were equal to 0.26 ± 0.02 for cryptorchidism and to 0.31 ± 0.01 for scrotal/inguinal hernia. Seven and 31 distinct QTL regions were associated with cryptorchidism in the LW and LR datasets, respectively. The top SNP per region explained between 0.96% and 1.10% and between 0.48% and 2.77% of the total variance of cryptorchidism incidence in the LW and LR populations, respectively. Five distinct QTL regions associated with scrotal/inguinal hernia were detected in both LW and LR datasets. The top SNP per region explained between 1.22% and 1.60% and between 1.15% and 1.46% of the total variance of scrotal/inguinal hernia incidence in the LW and LR populations, respectively. For each trait, we identified one overlapping region between the LW and LR datasets, i.e. a region on SSC8 (Sus scrofa chromosome) between 65 and 73 Mb for cryptorchidism and a region on SSC13 between 34 and 37 Mb for scrotal/inguinal hernia., Conclusions: The use of DEBV in combination with a binary trait model was a powerful approach to detect regions associated with difficult traits such as cryptorchidism and scrotal/inguinal hernia that have a low incidence and for which affected animals are generally not available for genotyping. Several novel QTL regions were detected for cryptorchidism and scrotal/inguinal hernia, and for several previously known QTL regions, the confidence interval was narrowed down.