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The gut microbiome plays an important role in the performance and health of swine by providing essential nutrients and supporting the immune system. Recent studies have demonstrated that the gut microbiome can explain part of the variation observed in growth, health, and meat quality. Feed efficiency is crucial in swine production, as feed cost account for more than 60% of total production costs. This study aimed to assess the relationships between the host genome, gut microbiome, and feed efficiency in Iberian pigs raised under intensive conditions. The specific objectives were to assess the mediating effects of the gut microbiome on feed efficiency and to estimate the direct and total heritability of feed efficiency. The data set included the feed conversion ratio (FCR) and residual feed intake (RFI) from 587 Iberian pigs, as well as the 16S rRNA gut microbial abundance from 151 of those pigs raised in a nucleus of selection. We reparametrised variance components from standard bivariate mixed models into recursive models to disentangle the microbiome’s mediating effect on feed efficiency. In our models, the host genome has direct effects on both the phenotype (G→P) and the gut microbiome (G→M). Additionally, there is an indirect effect of the host genome on the phenotype mediated by the microbiome (G→M→P). We identified a total of 14 taxa with relevant effects on FCR and 16 taxa with relevant effects on RFI. We categorised the gut microbiome into groups for potential practical application in pig farming. The gut microbes with relevant causal effects and low heritability can be manipulated through management interventions, while those microbes with relevant causal effects and moderate heritability can be targeted through selective breeding. Our findings indicate that incorporating microbiome data leads to a reduction in total heritability for both FCR and RFI. This study provides new insights into the link between the gut microbiome and feed efficiency, presenting practical methods to target microbes that can be influenced through selective breeding or management interventions.

There is a growing need to produce more resilient livestock that can cope with extreme environments and their associated impacts. Daily feed intake (DFI) is a promising metric for the development of resilience indicators (RIs), as reduced feed consumption is widely recognised as a clinical sign of disease. However, there is no consensus on which DFI-based RIs are the most informative. The objectives of this study were: (i) to evaluate the most common DFI-based RIs and their relationships with feed efficiency traits (FETs), (ii) to investigate the relationship between these indicators and progeny mortality rates on commercial farms, and (iii) to gain insight into their biological mechanisms. A total of 111 121 DFI records of 1 634 healthy purebred Pietrain boars were used, ranging from 47 to 90 days, with an average of 69 DFI records per boar. Three RIs were calculated: residual variance, RMSE and logarithm of the variance of the deviations from an expected pattern (LnVar). A classical animal model was used to estimate the variance components of each RI, and a bivariate model was implemented to estimate the genetic correlation between RIs and the FET. Furthermore, a preliminary mortality study was carried out using data from 6 889 progeny of 55 boars on farms catalogued as virulent for porcine reproductive and respiratory syndrome. Progeny mortality was calculated for each contemporary group (farm and batch) of the offspring, and sires were classified into three levels of resilience. A Bayesian linear model was used to determine whether the differences in progeny mortality rate between the levels of resilience were relevant. On the other hand, a weighted single-step genome-wide association study was performed for each RI and the FET, using a total of 1 216 genotypes. RIs showed moderate heritability (h2 = 0.27–0.49) and moderate to strong genetic correlation with FET. Progeny of resilient sires had an 80% probability of at least a 2.5% higher survival rate. Overlapping genomic regions were found for RIs and feed conversion ratio, highlighting DOCK1, SYK and SPTLC1 genes for their potential roles in modulating immune responses and/or metabolism. The LnVar of deviations from the population mean was the most promising indicators (LnVar-Pop) for disease resilience, as it was the RI that better captured differences in progeny mortality. Furthermore, these results suggest a common biological basis for RIs and FET of interest to breeding programmes. Further studies are needed to validate them.

Background: There is a growing interest in uncovering the factors that shape microbiome composition due to its association with complex phenotypic traits in livestock. Host genetic variation is increasingly recognized as a major factor influencing the microbiome. The Iberian pig breed, known for its high-quality meat products, includes various strains with recognized genetic and phenotypic variability. However, despite the microbiome's known impact on pigs' productive phenotypes such as meat quality traits, comparative analyses of gut microbial composition across Iberian pig strains are lacking. This study aims to explore the gut microbiota of two Iberian pig strains, Entrepelado (n = 74) and Retinto (n = 63), and their reciprocal crosses (n = 100), using machine learning (ML) models to identify key microbial taxa relevant for distinguishing their genetic backgrounds, which holds potential application in the pig industry. Nine ML algorithms, including tree-based, kernel-based, probabilistic, and linear algorithms, were used., Results: Beta diversity analysis on 16 S rRNA microbiome data revealed compositional divergence among genetic, age and batch groups. ML models exploring maternal, paternal and heterosis effects showed varying levels of classification performance, with the paternal effect scenario being the best, achieving a mean Area Under the ROC curve (AUROC) of 0.74 using the Catboost (CB) algorithm. However, the most genetically distant animals, the purebreds, were more easily discriminated using the ML models. The classification of the two Iberian strains reached the highest mean AUROC of 0.83 using Support Vector Machine (SVM) model. The most relevant genera in this classification performance were Acetitomaculum, Butyricicoccus and Limosilactobacillus. All of which exhibited a relevant differential abundance between purebred animals using a Bayesian linear model., Conclusions: The study confirms variations in gut microbiota among Iberian pig strains and their crosses, influenced by genetic and non-genetic factors. ML models, particularly CB and RF, as well as SVM in certain scenarios, combined with a feature selection process, effectively classified genetic groups based on microbiome data and identified key microbial taxa. These taxa were linked to short-chain fatty acids production and lipid metabolism, suggesting microbial composition differences may contribute to variations in fat-related traits among Iberian genetic groups., Competing Interests: Declarations. Ethics approval and consent to participate: All the experimental procedures were approved by the Committee of Ethics and Animal Welfare of the Miguel Hernández University, according to Council Directives 98/58/EC and 2010/63/EU. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

Social behaviour traits and their impact on feed efficiency are of particular interest in pig farming. The integration of automatic feeders enables the collection of multiple phenotypes for breeding purposes. The additive genetic and social genetic effect can be estimated considering all the visits to the feeder by modelling each visit independently in a 'visit-based approach'. This study aimed to determine the impact of the social genetic effect on individual feed intake and duration per visit in Pietrain pigs and Iberian pigs separately. The dataset comprised 883,906 visits from 1608 Pietrain pigs and 775,054 visits from 856 Iberian pigs. In the Pietrain population, the social genetic effects did not explain a substantial percentage of the phenotypic variance (~1%). In contrast, the Iberian population exhibited more substantial contributions, with social genetic effects accounting for 6.2% of the variance in duration per visit and 5.5% in feed intake per visit. The correlations between additive direct genetic and additive social genetic effects were slightly positive for feed intake across all analyses, and around zero for duration per visit with most of them including the zero in the highest posterior density interval (HPD95%). These weak correlations suggest that both effects could be selected independently. The visit-based approach successfully identified social genetic effects in the studied populations. Models incorporating social genetic effects demonstrated lower residual variance, enhancing the accuracy of additive values and, consequently, the potential for an improved response to selection., (© 2025 Wiley‐VCH GmbH. Published by John Wiley & Sons Ltd.)

Background: Substance use among adolescents is strongly associated with adverse physical, mental health, and social outcomes. Prevention and early intervention can reduce the likelihood of future problems, but requires valid and reliable screening tools capable of assessing risk across a range of substances. This study assessed the validity, reliability, and clinical utility of the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST-Y) for adolescents aged 15-17 years., Methods: A sample of adolescent males (N = 101), aged 15-17 years, held in a juvenile detention facility on substance-related offences in Barcelona, Spain were eligible. Participants were administered a battery of standardized substance-use screening tools by a clinical psychologist, and underwent a diagnostic interview assessing DSM-IV-TR substance abuse and dependence by an addiction medicine specialist. Scores on the various assessments were compared to establish validity (concurrent with interview, convergent with other measures), reliability, and clinical utility of ASSIST-Y., Results: Majority of participants (n = 77) completed assessments. While tobacco was not assessed as part of the interview, concurrent validity in detecting substance abuse was established for all remaining substances. Concurrent validity for detecting dependence was established for alcohol, cannabis, cocaine, stimulants and sedatives. Fewer numbers in higher-risk groups for inhalants, opioids and hallucinogen use limited confirmation of validity for those substances. ASSIST-Y also demonstrated good convergent validity with the other screening tools for all substances, except hallucinogens. Reliability for each subscale was established, except for tobacco (too few items), sedatives, and hallucinogens. Finally, clinical utility indices were significant for most substances (except sedatives and opioids); whilst clinical utility indices were significant for ruling out cases of non-dependence (all substances)., Conclusions: As a screening tool, the purpose of ASSIST-Y is designed to help identify adolescents who may be at-risk of substance-related harm. While the instrument was found to be valid and reliable in identifying risky use across a variety of substances, further research is needed to validate the instrument in other population groups, and for other substances. Future research should investigate the effect of the linked brief intervention to reduce risk of harm, especially for non-specialist clinicians., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

Scientists and coaches seek effective ergogenic aids for performance improvement. Cyclists commonly use β-Alanine, which may enhance post-exercise recovery and physical performance. High-dose β-Alanine supplementation's impact on World Tour cyclists during a 7-day camp remains unstudied. This study aimed to analyse the effect of a high dose of β-alanine in World Tour cyclist during a 7-day camp. A double-blinded, randomised controlled trial was conducted. 11 cyclists were included in the final analysis: β-alanine supplementation (n = 5; VO2max: 67.6±1.6 ml/kg/min) and a placebo group (n = 6; VO2max: 68.0±2.4 ml/kg/min). The duration of the supplementation protocol was seven days with four daily intakes. The subjects commenced supplementation after the physical tests (immediately following the snack) and consumed the final intake after breakfast on the day of the final test (a total of 7 days and 3 additional doses, 31 servings in total; 5g per dosage; 155g the total cumulative amount). Before and after seven days of supplementation, the cyclists performed an uphill time trial. Blood lactate, heart rate and rating of perceived exertion were measured during test. β-alanine supplementation improved the relative mean power attained during the time-trial compared with the control group (Z = -2.008; p = 0.045; Δ = 0.060), as well as the time needed to complete this trial (Z = -2.373; p = 0.018). As for physiological and metabolic variables, no significant change was found. In conclusion, the present study supports the effectiveness of one-week high dose of β-alanine during a cycling training in World Tour cyclists to improve their uphill time-trial performance. In addition, it is important to highlight the potential role of β-alanine in improving recovery power. This aspect is particularly relevant in the context of a training camp, where fatigue levels can increase alongside training intensity. Trial registration: This study was registered in ClinicalTrials.gov: (identifier: NCT04427319)., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Pérez-Piñero 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.)

Intramuscular fat (IMF) content is important for meat production and human health, where the host genetics and its microbiome greatly contribute to its variation. The aim of this study is to describe the consequences of the genetic modification of IMF by selecting the taxonomic composition of the microbiome, using rabbits from the 10th generation of a divergent selection experiment for IMF (high (H) and low (L) lines differ by 3.8 standard deviations). The selection altered the composition of the gut microbiota. Correlated responses were better distinguished at the genus level (51 genera) than at the phylum level (10 phyla). The H-line was enriched in Hungateiclostridium , Limosilactobacillus , Legionella , Lysinibacillus , Phorphyromonas , Methanosphaera , Desulfovibrio , and Akkermansia , while the L-line was enriched in Escherichia , Methanobrevibacter , Fonticella , Candidatus Amulumruptor , Methanobrevibacter , Exiguobacterium , Flintibacter , and Coprococcus , among other genera with smaller line differences. A microbial biomarker generated from the abundance of four of these genera classified the lines with 78% accuracy in a logit regression. Our results demonstrate different gut microbiome compositions in hosts with divergent IMF genotypes. Furthermore, we provide a microbial biomarker to be used as an indicator of hosts genetically predisposed to accumulate muscle lipids, which opens up the opportunity for research to develop probiotics or microbiome-based breeding strategies targeting IMF.

Background: Longevity and resilience are two fundamental traits for more sustainable livestock production. These traits are closely related, as resilient animals tend to have longer lifespans. An interesting criterion for increasing longevity in rabbit could be based on the information provided by its gut microbiome. The gut microbiome is essential for regulating health and plays crucial roles in the development of the immune system. The aim of this research was to investigate if animals with different longevities have different microbial profiles. We sequenced the 16S rRNA gene from soft faeces from 95 does. First, we compared two maternal rabbit lines with different longevities; a standard longevity maternal line (A) and a maternal line (LP) that was founded based on longevity criteria: females with a minimum of 25 parities with an average prolificacy per parity of 9 or more. Second, we compared the gut microbiota of two groups of animals from line LP with different longevities: females that died/were culled with two parities or less (LLP) and females with more than 15 parities (HLP)., Results: Differences in alpha and beta diversity were observed between lines A and LP, and a partial least square discriminant analysis (PLS-DA) showed a high prediction accuracy (> 91%) of classification of animals to line A versus LP (146 amplicon sequence variants (ASV)). The PLS-DA also showed a high prediction accuracy (> 94%) to classify animals to the LLP and HLP groups (53 ASV). Interestingly, some of the most important taxa identified in the PLS-DA were common to both comparisons (Akkermansia, Christensenellaceae R-7, Uncultured Eubacteriaceae, among others) and have been reported to be related to resilience and longevity., Conclusions: Our results indicate that the first parity gut microbiome profile differs between the two rabbit maternal lines (A and LP) and, to a lesser extent, between animals of line LP with different longevities (LLP and HLP). Several genera were able to discriminate animals from the two lines and animals with different longevities, which shows that the gut microbiome could be used as a predictive factor for longevity, or as a selection criterion for these traits., (© 2024. The Author(s).)

Crossbreeding plays a pivotal role within pig breeding programmes, aiming to maximize heterosis and improve reproductive traits in crossbred maternal lines. Nevertheless, there is evidence indicating that the performance of reciprocal crosses between two genetic lines might exhibit variability. These variations in performance can be attributed to differences in the correlations between gametic effects, acting as either sire or dam, within purebred and crossbred populations. To address this issue, we propose a multivariate gametic model that incorporates up to four correlated gametic effects for each parental population. The model is employed on a data set comprising litter size data (total number of piglets born-TNB- and number of piglets born alive-NBA-) derived from a reciprocal cross involving two Iberian pig populations: Entrepelado and Retinto. The data set comprises 6933 records from 1564 purebred Entrepelado (EE) sows, 4995 records from 1015 Entrepelado × Retinto (ER) crosses, 2977 records from 756 Retinto × Entrepelado (RE) crosses and 7497 records from 1577 purebred Retinto (RR) sows. The data set is further supplemented by a pedigree encompassing 6007 individual-sire-dam entries. The statistical model also included the order of parity (with six levels), the breed of the service sire (five levels) and the herd-year-season effects (141 levels). Additionally, the model integrates random dominant and permanent environmental sow effects. The analysis employed a Bayesian approach, and the results revealed all the posterior estimates of the gametic correlations to be positive. The range of the posterior mean estimates of the correlations varied across different gametic effects and traits, with a range between 0.04 (gametic correlation between the paternal effects for purebred and the maternal for crossbred in Retinto) and 0.53 (gametic correlation between the paternal effects for purebred and the paternal for crossbred in Entrepelado). Furthermore, the posterior mean variance estimates of the maternal gametic effects were consistently surpassed those for paternal effects within all four populations. The results suggest the possible influence of imprinting effects on the genetic control of litter size, and underscore the importance of incorporating crossbred data into the breeding value predictions for purebred individuals., (© 2023 The Authors. Journal of Animal Breeding and Genetics published by John Wiley & Sons Ltd.)

Purpose: To describe a rare case of acquired enophthalmos in a patient with idiopathic orbital inflammatory disease after treatment with systemic corticosteroids., Observations: Orbital socket contracture produces a non-traumatic enophthalmos and is most frequently reported as a consequence of orbital trauma or metastatic fibrosis. A previously healthy 64-year-old male presented with 3-month history of binocular diplopia and left proptosis, hypoglobus, supraduction deficit, and compressive neuropathy. Imaging techniques showed a left orbital mass; laboratory tests and biopsy of the mass lead to the diagnosis of idiopathic orbital inflammatory disease. Systemic corticosteroids were administered and, surprisingly, the patient developed left enophthalmos with eyelid retraction., Conclusions and Importance: Although extremely unusual, orbital socket contracture can cause enophthalmos and visual morbidity in patients with idiopathic orbital inflammatory disease treated with corticosteroids., Competing Interests: The following authors have no financial disclosures: SPO, MBM, MPL, NIF. Authorship: All authors attest that they meet the current ICMJE criteria for Authorship., (© 2024 The Authors. Published by Elsevier Inc.)

Monitoring the genetic variance of traits is a key priority to ensure the sustainability of breeding programmes in populations under directional selection, since directional selection can decrease genetic variation over time. Studies monitoring changes in genetic variation have typically used long-term data from small experimental populations selected for a handful of traits. Here, we used a large dataset from a commercial breeding line spread over a period of twenty-three years. A total of 2,059,869 records and 2,062,112 animals in the pedigree were used for the estimations of variance components for the traits: body weight (BWT; 2,059,869 records) and hen-housed egg production (HHP; 45,939 records). Data were analysed with three estimation approaches: sliding overlapping windows, under frequentist (restricted maximum likelihood (REML)) and Bayesian (Gibbs sampling) methods; expected variances using coefficients of the full relationship matrix; and a "double trait covariances" analysis by computing correlations and covariances between the same trait in two distinct consecutive windows. The genetic variance showed marginal fluctuations in its estimation over time. Whereas genetic, maternal permanent environmental, and residual variances were similar for BWT in both the REML and Gibbs methods, variance components when using the Gibbs method for HHP were smaller than the variances estimated when using REML. Large data amounts were needed to estimate variance components and detect their changes. For Gibbs (REML), the changes in genetic variance from 1999-2001 to 2020-2022 were 82.29 to 93.75 (82.84 to 93.68) for BWT and 76.68 to 95.67 (98.42 to 109.04) for HHP. Heritability presented a similar pattern as the genetic variance estimation, changing from 0.32 to 0.36 (0.32 to 0.36) for BWT and 0.16 to 0.15 (0.21 to 0.18) for HHP. On the whole, genetic parameters tended slightly to increase over time. The expected variance estimates were lower than the estimates when using overlapping windows. That indicates the low effect of the drift-selection process on the genetic variance, or likely, the presence of genetic variation sources compensating for the loss. Double trait covariance analysis confirmed the maintenance of variances over time, presenting genetic correlations >0.86 for BWT and >0.82 for HHP. Monitoring genetic variance in broiler breeding programmes is important to sustain genetic progress. Although the genetic variances of both traits fluctuated over time, in some windows, particularly between 2003 and 2020, increasing trends were observed, which warrants further research on the impact of other factors, such as novel mutations, operating on the dynamics of genetic variance.

Inbreeding depression is expected to be more pronounced in fitness-related traits, such as pig litter size. Recent studies have suggested that the genetic determinism of inbreeding depression may be heterogeneous across the genome. Therefore, the objective of this study was to conduct a genomic scan of the whole pig autosomal genome to detect the genomic regions that control inbreeding depression for litter size in two varieties of Iberian pigs (Entrepelado and Retinto). The datasets consisted of 2069 (338 sows) and 2028 (327 sows) records of litter size (Total Number Born and Number Born Alive) for the Entrepelado and Retinto varieties. All sows were genotyped using the Geneseek GGP PorcineHD 70 K chip. We employed the Unfavorable Haplotype Finder software to extract runs of homozygosity (ROHs) and conducted a mixed-model analysis to identify highly significant differences between homozygous and heterozygous sows for each specific ROH. A total of eight genomic regions located on SSC2, SSC5, SSC7, SSC8, and SSC13 were significantly associated with inbreeding depression, housing some relevant genes such as FSHR, LHCGR, CORIN, AQP6, and CEP120.

Maternal genetic effects (MGE) could affect meat quality traits such as intramuscular fat (IMF) and its fatty acid composition. However, it has been scarcely studied, especially in rabbits. The objectives of the present study were, first, to assess the importance of MGE on intramuscular fat and fatty acid composition by applying a Bayesian maternal animal model in two rabbit lines divergently selected for IMF. The second objective was to identify genomic regions and candidate genes of MGE that are associated with the traits of these offspring, using Bayesian methods in a Genome Wide Association Study (GWAS). Quantitative analyses were performed using data from 1982 rabbits, and 349 animals from the 9th generation and 76 dams of the 8th generation with 88,512 SNPs were used for the GWAS. The studied traits were IMF, saturated fatty acids (total SFA, C14:0; myristic acid, C16:0; palmitic acid and C18:0; stearic acid), monounsaturated fatty acids (total MUFA, C16:1n-7; palmitoleic acid and C18:1n-9; oleic acid), polyunsaturated fatty acids (total PUFA, C18:2n-6; linoleic acid, C18:3n-3; α-linolenic acid and C20:4n-6; arachidonic acid), MUFA/SFA and PUFA/SFA. The proportion of phenotypic variance explained by the maternal genetic effect ranged from 8 to 22% for IMF, depending on the model. For fatty acid composition, the proportion of phenotypic variance explained by maternal genetic effects varied from 10% (C18:0) to 46% (MUFA) in a model including both direct and additive maternal genetic effects, together with the common litter effect as a random variable. In particular, there were significant direct maternal genetic correlations for C16:0, C18:1n9, C18:2n6, SFA, MUFA, and PUFA with values ranging from -0.53 to -0.89. Relevant associated genomic regions were located on the rabbit chromosomes (OCU) OCU1, OCU5 and OCU19 containing some relevant candidates ( TANC2 , ACE , MAP3K3 , TEX2 , PRKCA , SH3GL2 , CNTLN , RPGRIP1L and FTO ) related to lipid metabolism, binding, and obesity. These regions explained about 1.2 to 13.9% of the total genomic variance of the traits studied. Our results showed an important maternal genetic effect on IMF and its fatty acid composition in rabbits and identified promising candidate genes associated with these traits.

Improved feed efficiency is an essential goal for the sustainability of pig production in economic and environmental terms. Traits such as feed conversion rate (FCR), residual feed intake (RFI), residual body weight gain (RG) and feeding behaviour, such as duration (TPV) and feeding rate per visit (FR) can now be measured by automatic feeding systems. The aim of this study was to evaluate the benefits of incorporating feeding behaviour traits into a selection index to improve feed efficiency in a nucleus of purebred Pietrain pigs. Data on body weight, feed intake and duration were recorded at each visit in 1608 animals. The information contained in 843,605 visits was grouped by animal ID to obtain a set of feed efficiency and feeding behaviour traits. These traits were obtained in three periods (first, second and total period). Bayesian models were built to estimate the posterior marginal distribution of the variance components. The heritabilities were between 0.44 and 0.59 for feeding behaviour traits and between 0.31 and 0.49 for feed efficiency traits. The FCR and RFI showed a considerable genetic correlation with daily feed intake (~0.65). FCR showed a genetic correlation with feeding behaviour traits, such as feed intake per visit (FPV) (0.44) and FR (0.33). Furthermore, the fast-eating pigs were less efficient. This was due to the positive genetic correlation found between the FR and the FCR (0.33) and the RFI (0.23), and the negative correlation found with the RG (-0.28). On the other hand, the inclusion of the feeding behaviour traits into a selection index slightly increased the selection response for FCR (4%) and RFI (1.8%). However, there was an increase of up to 19% in the selection response for RG and an improvement in accuracy from 0.59 to 0.70. Therefore, we concluded that it would be interesting to include feeding behaviour traits in a selection index to improve the selection response and accuracy of feed efficiency traits., (© 2023 The Authors. Journal of Animal Breeding and Genetics published by John Wiley & Sons Ltd.)

Cities are often hotspots for biological invasions, showing much higher percentages of alien species than non-urbanized settings. The reasons are multiple and are mostly related to two main factors: their heterogeneous, highly disturbed habitats and their many gateways that allow alien species introduction (e.g., airports, roads, train stations, or gardens). In addition to being a sink of biological invasions, cities can also be a source of the spread of alien species into surrounding landscapes, which adds further complexity to this issue. Herein, we are presenting the results of a five-year survey of the alien flora of Montjuïc, the largest urban hill in Barcelona (Spain). In just about 3.4 km 2 , we recorded up to 247 alien plant taxa, a figure much higher than those of many other Mediterranean cities and which clearly points to the role of Montjuïc as a hotspot for alien plants. The comparison with the alien flora of its surrounding region (coastal Catalonia) suggests that the alien flora of Montjuïc would have become enriched through many immigration episodes from close geographic areas. The hill, however, would have also acted as a source of the spread of alien plants, and indeed, some species have not been detected yet beyond the confines of Montjuïc. This study aims to be a key tool to ensure early detection and also to develop appropriate management and/or eradication actions.

Background: Understanding how the host's microbiome shapes phenotypes and participates in the host response to selection is fundamental for evolutionists and animal and plant breeders. Currently, selection for resilience is considered a critical step in improving the sustainability of livestock systems. Environmental variance (V E ), the within-individual variance of a trait, has been successfully used as a proxy for animal resilience. Selection for reduced V E could effectively shift gut microbiome composition; reshape the inflammatory response, triglyceride, and cholesterol levels; and drive animal resilience. This study aimed to determine the gut microbiome composition underlying the V E of litter size (LS), for which we performed a metagenomic analysis in two rabbit populations divergently selected for low (n = 36) and high (n = 34) V E of LS. Partial least square-discriminant analysis and alpha- and beta-diversity were computed to determine the differences in gut microbiome composition among the rabbit populations., Results: We identified 116 KEGG IDs, 164 COG IDs, and 32 species with differences in abundance between the two rabbit populations studied. These variables achieved a classification performance of the V E rabbit populations of over than 80%. Compared to the high V E population, the low V E (resilient) population was characterized by an underrepresentation of Megasphaera sp., Acetatifactor muris, Bacteroidetes rodentium, Ruminococcus bromii, Bacteroidetes togonis, and Eggerthella sp. and greater abundances of Alistipes shahii, Alistipes putredinis, Odoribacter splanchnicus, Limosilactobacillus fermentum, and Sutterella, among others. Differences in abundance were also found in pathways related to biofilm formation, quorum sensing, glutamate, and amino acid aromatic metabolism. All these results suggest differences in gut immunity modulation, closely related to resilience., Conclusions: This is the first study to show that selection for V E of LS can shift the gut microbiome composition. The results revealed differences in microbiome composition related to gut immunity modulation, which could contribute to the differences in resilience among rabbit populations. The selection-driven shifts in gut microbiome composition should make a substantial contribution to the remarkable genetic response observed in the V E rabbit populations. Video Abstract., (© 2023. The Author(s).)

INGA FOOD, S.A. initiated a crossbreeding program between two Iberian pig varieties, Retinto (R) and Entrepelado (E), with the goal of producing a hybrid sow (F1). Several studies have been conducted to evaluate its productive performance, and these studies have revealed differences in litter size between the two reciprocal crosses, suggesting the presence of genomic imprinting effects. To further investigate these effects, this study introduces a multivariate gametic model designed to estimate gametic correlations between paternal and maternal effects originating from both genetic backgrounds involved in the reciprocal crosses. The dataset consisted of 1258 records (the total number born-TNB and the number born alive-NBA) from 203 crossbred dams for the Entrepelado (sire) × Retinto (dam) cross and 700 records from 125 crossbred dams for the Retinto (sire) × Entrepelado (dam) cross. All animals were genotyped using the GeneSeek ® GPP Porcine 70 K HDchip (Illumina Inc., San Diego, CA, USA). The results indicated that the posterior distribution of the gametic correlation between paternal and maternal effects was distinctly different between the two populations. Specifically, in the Retinto population, the gametic correlation showed a positive skew with posterior probabilities of 0.78 for the TNB and 0.80 for the NBA. On the other hand, the Entrepelado population showed a posterior probability of a positive gametic correlation between paternal and maternal effects of approximately 0.50. The differences in the shape of the posterior distribution of the gametic correlations between paternal and maternal effects observed in the two varieties may account for the distinct performance outcomes observed in the reciprocal crosses.

Background: Gut metabolites are key actors in host-microbiota crosstalk with effect on health. The study of the gut metabolome is an emerging topic in livestock, which can help understand its effect on key traits such as animal resilience and welfare. Animal resilience has now become a major trait of interest because of the high demand for more sustainable production. Composition of the gut microbiome can reveal mechanisms that underlie animal resilience because of its influence on host immunity. Environmental variance (V E ), specifically the residual variance, is one measure of resilience. The aim of this study was to identify gut metabolites that underlie differences in the resilience potential of animals originating from a divergent selection for V E of litter size (LS). We performed an untargeted gut metabolome analysis in two divergent rabbit populations for low (n = 13) and high (n = 13) V E of LS. Partial least square-discriminant analysis was undertaken, and Bayesian statistics were computed to determine dissimilarities in the gut metabolites between these two rabbit populations., Results: We identified 15 metabolites that discriminate rabbits from the divergent populations with a prediction performance of 99.2% and 90.4% for the resilient and non-resilient populations, respectively. These metabolites were suggested to be biomarkers of animal resilience as they were the most reliable. Among these, five that derived from the microbiota metabolism (3-(4-hydroxyphenyl)lactate, 5-aminovalerate, and equol, N6-acetyllysine, and serine), were suggested to be indicators of dissimilarities in the microbiome composition between the rabbit populations. The abundances of acylcarnitines and metabolites derived from the phenylalanine, tyrosine, and tryptophan metabolism were low in the resilient population and these pathways can, therefore impact the inflammatory response and health status of animals., Conclusions: This is the first study to identify gut metabolites that could act as potential resilience biomarkers. The results support differences in resilience between the two studied rabbit populations that were generated by selection for V E of LS. Furthermore, selection for V E of LS modified the gut metabolome, which could be another factor that modulates animal resilience. Further studies are needed to determine the causal role of these metabolites in health and disease., (© 2023. The Author(s).)