Sexual maturation in boars impacts reproductive efficiency in swine production, yet the molecular mechanisms underlying this developmental transition remain poorly understood. This study aimed to investigate the transcriptomic changes in sperm from Duroc boars during sexual maturation, conducting a longitudinal analysis. The total RNA and miRNA profiles from the same individuals (n = 6) at puberty (7.24 ± 0.39 months) and sexual maturity (10 ± 0.40 months) were compared, identifying molecular signatures associated with reproductive development. Total RNA sequencing (Illumina NovaSeq-6000) and miRNA sequencing (Illumina NextSeq-500) were performed on all 12 paired samples (6 boars at 2 time points), followed by differential expression analysis using a paired statistical model in DESeq2 to account for repeated measures. Differential expression analysis identified 60 differentially expressed genes using stringent criteria (adj P < 0.05, |log2FC| ≥ 0.5), with 65

Abstract Bovine viral diarrhea virus (BVDV, genus Pestivirus , family Flaviviridae ) is a notifiable pathogen of cattle which significantly impacts animal health, welfare, and the economy. Several cellular factors important for BVDV infection, such as Jiv, CD46 and ADAM17, have already been identified providing new targets development of effective defense strategies. However, our knowledge about BVDV host factor requirements remains limited, as no genome-wide studies of BVDV host resistance factors were performed to date, in part due to lack of accessible whole genome libraries. To close this gap, we have designed a novel bovine whole genome knockout library and successfully used it to identify a set of BVDV host resistance factors. The validity of our approach is highlighted by the strong selection of cells with inactivated ADAM17 and TMEM41B, which have both been described to be of pivotal importance for BVDV infection. In addition, guides targeting VMP1, recently identified as an important factor for flavivirus infection, were also significantly enriched in our screen. Furthermore, we found differential selection of several proteins essential for triggering autophagy, providing additional strong evidence of this process underlying key cellular functions involved in resistance to BVDV.

Abstract The Duroc-derived reference genome Sscrofa11.1 has provided a critical foundation for pig genomics, providing a high-quality reference genome for accurate variant detection and comparative genomics but does not capture breed-specific variation. Here, we present a near-complete, gap-free genome assembly for the Landrace pig (Landrace_v1, GCA_963921485.1), spanning all 20 chromosomes and totaling 2.6 Gb, including 176 Mb of sequence absent from Sscrofa11.1. Comparative analyses with recently published high-quality pig genomes reveal a conserved centromere organization across breeds, accompanied by substantial variation in repeat composition and length, and identify a pig specific pattern of telomere variant repeats across eight pig breeds. The improved resolution of repetitive regions in Landrace_v1 enables more complete reconstruction of complex gene families, including olfactory receptors, and uncovers structural variation at the KIT proto-oncogene receptor tyrosine kinase locus not represented in the Duroc reference. Together, these findings highlight the limitations of single-reference genomes and demonstrate the value of breed-specific assemblies for capturing genomic diversity and improving downstream analyses.

Pork is the most widely consumed meat globally, and the industry has achieved substantial genetic advancements for several traits using genomic selection. However, traditional linear genomic prediction models may be inadequate for predicting complex traits, such as feed efficiency, as they primarily capture additive genetic effects and overlook nonadditive effects, including dominance and epistasis. Deep learning (DL) has the potential to address this limitation due to its ability to model nonlinear patterns inherent in genomic data. The objectives of this study were to compare the predictive ability of DL models to the linear models for predicting feed efficiency (FE) trait in 2 boar populations, estimate the nonadditive genetic variance captured by DL, and assess its effect on predictive ability. Our results showed that the DL models using the averaged-prediction method had the highest predictive ability in the sire line test population (0.381 for multilayer perceptron [MLP] and 0.377 for convolutional neural network [CNN]), compared to 0.366 for linear models. DL models also showed higher abilities in the dam line test population, with MLP achieving a predictive ability of 0.364. Additionally, we showed that DL models captured nonadditive variance; however, this did not significantly improve predictive ability. In conclusion, DL models, particularly MLP, demonstrated the highest predictive ability for FE, improving performance by approximately 4.1% for the sire line and 2.8% for the dam line compared to the traditional linear models. Therefore, DL models are recommended for predicting phenotypes and for estimating total genetic effects, including nonadditive components. However, this comes at a significant increase of computational cost.

Metabolomic analysis of boar semen associated with sexual maturation is essential for improving fertility management and breeding, with amino acids and amines playing key roles in the reproductive process. This study aimed to explore changes in amino acids and amines in boar spermatozoa and seminal plasma during puberty to sexual maturity and identify potential biomarkers of sexual maturity. Semen was collected from the same 15 Duroc boars over time at approximately 7 months (Age 1), 8.5 months (Age 2), and 10 months (Age 3). Liquid chromatography-mass spectrometry was used to analyse amino acids and amines in spermatozoa and seminal plasma separately. Multivariate analysis (PLS-DA) revealed pronounced age-dependent changes in amino acids and amines in spermatozoa between Age 1 and Age 3, and more subtle shifts in seminal plasma. Univariate analysis (Repeated measure ANOVA/Friedman) revealed that glutamate and taurine had significant pairwise differences in seminal plasma (P < 0.05). In sperm, 15 amino acids (glutamate, alanine, aspartate, choline, taurine, histidine, methionine, tryptophan, leucine, cystine, tyrosine, arginine, lysine, valine and glycine) exhibited significant pairwise differences (P < 0.05). VIP scoring (>1.5) prioritised glutamate, alanine, aspartate, and choline as key contributors to the variations and pathway analysis implicated alanine, aspartate and glutamate metabolism, and histidine metabolism linked to sexual maturity. Our study highlights metabolic changes during sexual maturation, identifying potential biomarkers for assessing reproductive maturity. These findings are initial steps toward optimising younger boars' usage in breeding, enhancing genetic gain, and reducing costs associated with their non-productive days at AI centres.

Boars undergo physiological and biochemical changes in semen composition as they grow from puberty to sexual maturity. However, comprehensive metabolomic profiles of boar semen remain uncharacterised. Understanding metabolic alterations in semen during this period is important for optimising reproductive performance in breeding programs. The aim of this study was to characterise the semen metabolome as boars mature, utilising an untargeted metabolomic approach. Semen samples were collected from 15 Duroc boars at three developmental ages: 7 months, 8.5 months, and 10 months. Sperm and seminal plasma were separated and analysed by hydrophilic interaction and reversed-phase liquid chromatography coupled with mass spectrometry to capture a wide range of metabolites. We identified a total of 4,491 features in boar semen, annotating 92 distinct metabolites. Amino acids, peptides and analogues constituted the most abundant components, followed by fatty acid esters. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) showed a clear separation between metabolomic profiles by age groups. PERMANOVA analysis of PCA scores confirmed statistically significant differences (P < 0.05) between younger (7 months) and more mature boars (8.5 months and 10 months). Pathway analysis identified porphyrin metabolism, taurine and hypotaurine metabolism, and glycerolipid metabolism as significantly enriched pathways in sperm, while glutathione and nitrogen metabolism were prominently enriched in seminal plasma. Using linear modelling, partial Spearman correlation and random forest analyses, we identified homoisovanillic acid as a key metabolite discriminating age groups in both sperm and seminal plasma. Additionally, L-glutamic acid, decanoyl-L-carnitine and N-(1,3-Thiazol-2-yl)benzenesulfonamide emerged as important sperm metabolites, while glyceric acid, myo-inositol, glycerophosphocholine, and several other compounds were identified as critical seminal plasma metabolites. This study provides a detailed characterisation of metabolic changes in Duroc boar semen during the transition from puberty to sexual maturity. Our findings enhance the understanding of reproductive development and could inform strategies to assess sexual maturity in breeding programs.

Characterization of essential genes across the genome is fundamental to understanding cellular functions at a molecular level. While significant progress has been made in characterizing essential genes in human and mouse models, relatively little is known about essential genes in the porcine genome. Pigs are an important production species and are now emerging as valuable models for studying human diseases due to their physiological similarities to humans. To map essential genes across the porcine genome, we have developed a novel porcine genome-wide CRISPR knockout screening library (pGeCKO) and applied it to two porcine cell lines, PK15 and IPEC-J2. We identified 2,245 essential genes in PK15 cells and 919 essential genes in IPEC-J2 cells, with 683 of these shared between both cell lines. Functional analyses revealed that most essential genes are involved in core cellular processes such as cell cycle regulation, DNA replication, transcription, and translation. Comparative analysis with human essential genes from the DepMap project revealed that over half of the genes are shared with humans and the rest are porcine-specific. These porcine-specific essential genes included genes in core functional pathways related to protein and RNA processing as well as many related to N-glycan biosynthesis, signal transduction, and several long-noncoding RNAs. This work provides a new resource for leveraging porcine models in disease research, enhancing our understanding of porcine genetics and its implications for human health. ### Competing Interest Statement The authors have declared no competing interest.

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.

With heritable PSE (hal+) being largely eradicated in many countries, pork quality defects and their linkage to known mutations have received less attention in the last decade. We address this by mapping the frequency of four known mutations (200Q, 199 V, hal+, PHKG1) in heterogenous Norwegian and German pig populations (n = 136/61). Genotyping for mutations was done by PCR-RFLP analyses and Illumina chip genotyping. We found a high prevalence of pigs with at least one of the four tested mutations for Norwegian and German samples (60%, 77%). For Norwegian samples, we confirm known links of 200Q and PHKG1 with Hampshire and Duroc genetics, respectively. For Germany, we show that Pi & eacute;train pigs can still be heterozygous carriers of hal + . In all, our data points to a relatively high abundance of mutations that affect pork quality in both countries. The high prevalence of individual mutations may contribute to recent ham quality defects.

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.

Hyperactive sperm motility is important for successful fertilization. In the present study, a proteome profiling approach was performed to identify the differences between Landrace boars with different levels of hyperactive sperm motility in liquid extended semen. Two contrasts were studied: (i) high versus low levels of sperm hyperactivity at semen collection day and (ii) high versus low change in levels of sperm hyperactivity after 96 h semen storage. Testicular samples were analyzed on a Q Exactive mass spectrometer and more than 6000 proteins were identified in the 13 samples. The most significant differentially expressed proteins were mediator complex subunit 28 (MED28), cell division cycle 37 like 1 (CDC37L1), ubiquitin specific peptidase 10 (USP10), zinc finger FYVE-type containing 26 (ZFYVE26), protein kinase C delta (PRKCD), actinin alpha 4 (ACTN4), N(alpha)-acetyltransferase 30 (NAA30), C1q domain-containing (LOC110258309) and uncharacterized LOC100512926. Of the differentially expressed proteins, 11 have previously been identified as differentially expressed at the corresponding mRNA transcript level using the same samples and contrasts. These include sphingosine kinase 1 isoform 2 (SPHK1), serine and arginine rich splicing factor 1 (SRSF1), and tubulin gamma-1 (TUBG1) which are involved in the acrosome reaction and sperm motility. A mass spectrometry approach was applied to investigate the protein profiles of boars with different levels of hyperactive sperm motility. This study identified several proteins previously shown to be involved in sperm motility and quality, but also proteins with no known function for sperm motility. Candidates that are differentially expressed on both mRNA and protein levels are especially relevant as biological markers of semen quality.

The aim of this study was to develop a strategy for selecting SNPs that could receive higher weight than other SNPs in a GBLUP approach due to their expected association with important pig phenotypes. In addition, we aimed to investigate if such a strategy yields improved prediction accuracy compared to a traditional GBLUP approach. Four prediction accuracy scenarios were evaluated using three production traits in two pig populations. Our results show that adding extra weight to SNPs that are expected to be (close to) causal variants in the G matrix increases the prediction accuracy of genomic prediction. The advantage of weighted G matrix compared to a traditional one is not very large, but the added value is consistent.

Several QTL regions affecting number of teats have been detected in commercial pig lines. In this study we follow the indirect effects of index selection on different QTL regions for number of teats in two maternal lines in 40K animals with imputed 555K SNP. In total, 3 QTL regions overlap between the two populations. For a QTL on Sus scrofa chromosome 7 (SSC7), the underlying functional variation affecting number of thoracic vertebrae located in the vertnin gene has also been genotyped showing an allelic substitution effect of nearly 0.4 teats in both lines. However, allele frequencies show an opposite trend at the vertnin gene locus in the two lines. Moreover, epistatic effects between two QTL regions on SSC7 and SSC12 are investigated at the molecular and phenotypic level.

The aim of this study was to perform genome-wide association analyses for backfat thickness and osteochondrosis in Landrace pigs and to fine map pleiotropic genomic regions. In order to characterise genomic regions, phenotypic information of 5,000 animals with osteochondrosis scored from CT images and 40,000 animals with backfat thickness scored from CT or ultrasound images were analysed. All animals were genotyped with a medium density SNP chip and a subset of them were genotyped with a high-density SNP chip as well, allowing for imputation. Two genomic loci were found in common for osteochondrosis and backfat thickness, one on chromosome 5 and one on chromosome 14. For both regions, an antagonistic relationship was found. Fine mapping using an impact score approach identified the CCND2 gene as the most likely causal gene on chromosome 5, whereas a mutation in CRTAC1 had the highest impact score in the chromosome 14 region.

Backfat is an important trait in pork production, and it has been included in the breeding objectives of genetic companies for decades. Although adipose tissue is a good energy storage, excessive fat results in reduced efficiency and economical losses. A large QTL for backfat thickness on chromosome 5 is still segregating in different commercial pig breeds. We fine mapped this QTL region using a genome-wide association analysis (GWAS) with 133,358 genotyped animals from five commercial populations (Landrace, Pietrain, Large White, Synthetic, and Duroc) imputed to the porcine 660K SNP chip. The lead SNP was located at 5:66103958 (G/A) within the third intron of the CCND2 gene, with the G allele associated with more backfat, while the A allele is associated with less backfat. We further phased the QTL region to discover a core haplotype of five SNPs associated with low backfat across three breeds. Linkage disequilibrium analysis using whole-genome sequence data revealed three candidate causal variants within intronic regions and downstream of the CCND2 gene, including the lead SNP. We evaluated the association of the lead SNP with the expression of the genes in the QTL region (including CCND2) in a large cohort of 100 crossbred samples, sequenced in four different tissues (lung, spleen, liver, muscle). Results show that the A allele increases the expression of CCND2 in an additive way in three out of four tissues. Our findings indicate that the causal variant for this QTL region is a regulatory variant within the third intron of the CCND2 gene affecting the expression of CCND2.

Background Sperm hyperactive motility has previously been shown to influence litter size in pigs, but little is known about the underlying biological mechanisms. The aim of this study was to use RNA sequencing to investigate gene expression differences in testis tissue from Landrace and Duroc boars with high and low levels of sperm hyperactive motility. Boars with divergent phenotypes were selected based on their sperm hyperactivity values at the day of ejaculation (day 0) (contrasts (i) and (ii) for Landrace and Duroc, respectively) and on their change in hyperactivity between day 0 and after 96 h liquid storage at 18 °C (contrast (iii)). Results RNA sequencing was used to measure gene expression in testis. In Landrace boars, 3219 genes were differentially expressed for contrast (i), whereas 102 genes were differentially expressed for contrast (iii). Forty-one differentially expressed genes were identified in both contrasts, suggesting a functional role of these genes in hyperactivity regardless of storage. Zinc finger DNLZ was the most up-regulated gene in contrasts (i) and (iii), whereas the most significant differentially expressed gene for the two contrasts were ADP ribosylation factor ARFGAP1 and solute carrier SLC40A1 , respectively. For Duroc (contrast (ii)), the clustering of boars based on their gene expression data did not reflect their difference in sperm hyperactivity phenotypes. No results were therefore obtained for this breed. A case-control analysis of variants identified in the Landrace RNA sequencing data showed that SNPs in NEU3 , CHRDL2 and HMCN1 might be important for sperm hyperactivity. Conclusions Differentially expressed genes were identified in Landrace boars with high and low levels of sperm hyperactivity at the day of ejaculate collection and high and low change in hyperactivity after 96 h of sperm storage. The results point towards important candidate genes, biochemical pathways and sequence variants underlying sperm hyperactivity in pigs.

The authors wish to make the following corrections to this paper [...]

Surgical castration of piglets without pain relief is still common practice in many countries. Possible alternatives for surgical castration are application of pain relief or anaesthesia or production of boars (entire males) and immunocastrates. Each of these alternatives faces advantages and disadvantages which may result in different citizen attitudes and consumers acceptability. Understanding which practice is acceptable to whom and why may further stimulate implementation. Consumer (n = 3251) and stakeholder (n = 1027) attitudes towards surgical castration without pain relief, surgical castration with anaesthesia, immunocastration, and production of boars were surveyed from April to June 2020 via an online questionnaire in 16 countries (>175 respondents per country). Surgical castration without pain relief was separated from each of the alternatives due to animal welfare and showed the lowest acceptability (32%). Within the alternatives, a further partitioning between the alternatives was based on perceived quality and food safety, with an acceptance of 85% for applying anaesthesia, 71% for immunocastration, and 49% for boar production. Differences depending on professional involvement and familiarity with agriculture could be observed, mainly for the acceptance of surgical castration without anaesthesia, immunocastration, and boars. Castration with anaesthesia was highly accepted by all types of respondents.

Finding effective predictors of traits related to boar fertility is essential for increasing the efficiency of artificial insemination systems in pig breeding. The objective of this study was to find associations between single-nucleotide polymorphisms (SNPs) within candidate genes and fertility in the breeds Landrace and Duroc. Animals with breeding values for total number of piglets born, were re-sequenced for exonic regions of 14 candidate genes related to male and female fertility using samples from 16 Landrace boars and 16 Duroc boars (four with high and four with low breeding value of total number of piglets born for each breed for male fertility, and the same for female fertility) to detect genetic variants. Genotyping for the detected SNPs was done in 619 Landrace boars and 513 Duroc boars. Two SNPs in BMPR1 and one SNP in COX-2 were found significantly associated with the total number of piglets born in Landrace. In Duroc, two SNPs in PLCz, one SNP in VWF and one SNP in ZP3 were found significantly associated with total number of piglets born. These SNPs explained between 0.27% and 1.18% of the genetic variance. These effects are too low for being used directly for selection purposes but can be of interest in SNP-panels used for genomic selection.

Modern breeding schemes for livestock species accumulate a large amount of genotype and phenotype data which can be used for genome-wide association studies (GWAS). Many chromosomal regions harboring effects on quantitative traits have been reported from these studies, but the underlying causative mutations remain mostly undetected. In this study, we combine large genotype and phenotype data available from a commercial pig breeding scheme for three different breeds (Duroc, Landrace, and Large White) to pinpoint functional variation for a region on porcine chromosome 7 affecting number of teats (NTE). Our results show that refining trait definition by counting number of vertebrae (NVE) and ribs (RIB) helps to reduce noise from other genetic variation and increases heritability from 0.28 up to 0.62 NVE and 0.78 RIB in Duroc. However, in Landrace, the effect of the same QTL on NTE mainly affects NVE and not RIB, which is reflected in reduced heritability for RIB (0.24) compared to NVE (0.59). Further, differences in allele frequencies and accuracy of rib counting influence genetic parameters. Correction for the top SNP does not detect any other QTL effect on NTE, NVE, or RIB in Landrace or Duroc. At the molecular level, haplotypes derived from 660K SNP data detects a core haplotype of seven SNPs in Duroc. Sequence analysis of 16 Duroc animals shows that two functional mutations of the Vertnin (VRTN) gene known to increase number of thoracic vertebrae (ribs) reside on this haplotype. In Landrace, the linkage disequilibrium (LD) extends over a region of more than 3 Mb also containing both VRTN mutations. Here, other modifying loci are expected to cause the breed-specific effect. Additional variants found on the wildtype haplotype surrounding the VRTN region in all sequenced Landrace animals point toward breed specific differences which are expected to be present also across the whole genome. This Landrace specific haplotype contains two missense mutations in the ABCD4 gene, one of which is expected to have a negative effect on the protein function. Together, the integration of largescale genotype, phenotype and sequence data shows exemplarily how population parameters are influenced by underlying variation at the molecular level.