Gut microbiome and resistome characterization of pigs treated with commonly used post-weaning diarrhea treatments

BACKGROUND

The global burden of antimicrobial resistance demands additional measures to ensure the sustainable and conscious use of antimicrobials. For the swine industry, the post-weaning period is critical and for many years, antimicrobials have been the most effective strategy to control and treat post-weaning related infections. Among them, post-weaning diarrhea causes vast economic losses, as it severely compromises piglets' health and growth performance. In this study, 210 piglets were transferred from a farm with recurrent cases of post-weaning diarrhea to an experimental farm and divided into six different treatment groups to determine the effect of the different treatments on the growth performance and survival, the microbiome, and the resistome in a cross-sectional and longitudinal study. The different treatments included antimicrobials trimethoprim/sulfamethoxazole, colistin, and gentamicin, an oral commercial vaccine, a control with water acidification, and an untreated control. An extra group remained at the farm of origin following the implemented amoxicillin routine treatment. A total of 280 fecal samples from pigs at four different sampling times were selected for metagenomics: before weaning-treatment at the farm of origin, and three days, two weeks, and four weeks post-treatment.

RESULTS

The control group with water acidification showed a reduced death risk in the survival analyses and non-significant differences in average daily weight gain in comparison to the antibiotic-treated groups. However, the growth-promoting effect among antibiotic-treated groups was demonstrated when comparing against the untreated control group at the experimental farm. After four weeks of treatment, diversity indexes revealed significantly decreased diversity for the untreated control and the group that remained at the farm of origin treated with amoxicillin. For this last group, impaired microbial diversity could be related to the continuous amoxicillin treatment carried out at the farm. Analysis of the resistome showed that both gentamicin and amoxicillin treatments significantly contributed to the emergence of resistance, while trimethoprim/sulphonamide and colistin did not, suggesting that different treatments contribute differently to the emergence of resistance.

CONCLUSIONS

Overall, this shotgun longitudinal metagenomics analysis demonstrates that non-antibiotic alternatives, such as water acidification, can contribute to reducing the emergence of antimicrobial resistance without compromising pig growth performance and gut microbiome.

Recent Advances in Enteric Methane Mitigation and the Long Road to Sustainable Ruminant Production

Mitigation of methane emission, a potent greenhouse gas, is a worldwide priority to limit global warming. A substantial part of anthropogenic methane is emitted by the livestock sector, as methane is a normal product of ruminant digestion. We present the latest developments and challenges ahead of the main efficient mitigation strategies of enteric methane production in ruminants. Numerous mitigation strategies have been developed in the last decades, from dietary manipulation and breeding to targeting of methanogens, the microbes that produce methane. The most recent advances focus on specific inhibition of key enzymes involved in methanogenesis. But these inhibitors, although efficient, are not affordable and not adapted to the extensive farming systems prevalent in low- and middle-income countries. Effective global mitigation of methane emissions from livestock should be based not only on scientific progress but also on the feasibility and accessibility of mitigation strategies.

Identification of candidate regulatory genes for intramuscular fatty acid composition in pigs by transcriptome analysis

BACKGROUND

Intramuscular fat (IMF) content and its fatty acid (FA) composition are typically controlled by several genes, each with a small effect. In the current study, to pinpoint candidate genes and putative regulators involved in FA composition, we performed a multivariate integrative analysis between intramuscular FA and transcriptome profiles of porcine longissimus dorsi (LD) muscle. We also carried out a combination of network, regulatory impact factor (RIF), in silico prediction of putative target genes, and functional analyses to better support the biological relevance of our findings.

RESULTS

For this purpose, we used LD RNA-Seq and intramuscular FA composition profiles of 129 Iberian × Duroc backcrossed pigs. We identified 378 correlated variables (13 FA and 365 genes), including six FA (C20:4n-6, C18:2n-6, C20:3n-6, C18:1n-9, C18:0, and C16:1n-7) that were among the most interconnected variables in the predicted network. The detected FA-correlated genes include genes involved in lipid and/or carbohydrate metabolism or in regulation of IMF deposition (e.g., ADIPOQ, CHUK, CYCS, CYP4B1, DLD, ELOVL6, FBP1, G0S2, GCLC, HMGCR, IDH3A, LEP, LGALS12, LPIN1, PLIN1, PNPLA8, PPP1R1B, SDR16C5, SFRP5, SOD3, SNW1, and TFRC), meat quality (GALNT15, GOT1, MDH1, NEU3, PDHA1, SDHD, and UNC93A), and transport (e.g., EXOC7 and SLC44A2). Functional analysis highlighted 54 over-represented gene ontology terms, including well-known biological processes and pathways that regulate lipid and carbohydrate metabolism. RIF analysis suggested a pivotal role for six transcription factors (CARHSP1, LBX1, MAFA, PAX7, SIX5, and TADA2A) as putative regulators of gene expression and intramuscular FA composition. Based on in silico prediction, we identified putative target genes for these six regulators. Among these, TADA2A and CARHSP1 had extreme RIF scores and present novel regulators in pigs. In addition, the expression of TADA2A correlated (either positively or negatively) with C20:4n-6, C18:2n-6, C20:3n-6, C18:1n-9, and that of CARHSP1 correlated (positively) with the C16:1n-7 lipokine. We also found that these two transcription factors share target genes that are involved in lipid metabolism (e.g., GOT1, PLIN1, and TFRC).

CONCLUSIONS

This integrative analysis of muscle transcriptome and intramuscular FA profile revealed valuable information about key candidate genes and potential regulators for FA and lipid metabolism in pigs, among which some transcription factors are proposed to control gene expression and modulate FA composition differences.

Correction: Mixed management in growing and finishing pigs: Differences between gender and their impacts on behavior, growth performance, and physiological parameters

[This corrects the article DOI: 10.1371/journal.pone.0284481.].

Mutations on a conserved distal enhancer in the porcine C-reactive protein gene impair its expression in liver

C-reactive protein (CRP) is an evolutionary highly conserved protein. Like humans, CRP acts as a major acute phase protein in pigs. While CRP regulatory mechanisms have been extensively studied in humans, little is known about the molecular mechanisms that control pig CRP gene expression. The main goal of the present work was to study the regulatory mechanisms and identify functional genetic variants regulating CRP gene expression and CRP blood levels in pigs. The characterization of the porcine CRP proximal promoter region revealed a high level of conservation with both cow and human promoters, sharing binding sites for transcription factors required for CRP expression. Through genome-wide association studies and fine mapping, the most associated variants with both mRNA and protein CRP levels were localized in a genomic region 39.3 kb upstream of CRP. Further study of the region revealed a highly conserved putative enhancer that contains binding sites for several transcriptional regulators such as STAT3, NF-kB or C/EBP-β. Luciferase reporter assays showed the necessity of this enhancer-promoter interaction for the acute phase induction of CRP expression in liver, where differences in the enhancer sequences significantly modified CRP activity. The associated polymorphisms disrupted the putative binding sites for HNF4α and FOXA2 transcription factors. The high correlation between HNF4α and CRP expression levels suggest the participation of HNF4α in the regulatory mechanism of porcine CRP expression through the modification of its binding site in liver. Our findings determine, for the first time, the relevance of a distal regulatory element essential for the acute phase induction of porcine CRP in liver and identify functional polymorphisms that can be included in pig breeding programs to improve immunocompetence.

Copy Number Variation on ABCC2-DNMBP Loci Affects the Diversity and Composition of the Fecal Microbiota in Pigs

Genetic variation in the pig genome partially modulates the composition of porcine gut microbial communities. Previous studies have been focused on the association between single nucleotide polymorphisms (SNPs) and the gut microbiota, but little is known about the relationship between structural variants and fecal microbial traits. The main goal of this study was to explore the association between porcine genome copy number variants (CNVs) and the diversity and composition of pig fecal microbiota. For this purpose, we used whole-genome sequencing data to undertake a comprehensive identification of CNVs followed by a genome-wide association analysis between the estimated CNV status and the fecal bacterial diversity in a commercial Duroc pig population. A CNV predicted as gain (DUP) partially harboring ABCC2-DNMBP loci was associated with richness (P = 5.41 × 10-5, false discovery rate [FDR] = 0.022) and Shannon α-diversity (P = 1.42 × 10-4, FDR = 0.057). The in silico predicted gain of copies was validated by real-time quantitative PCR (qPCR), and its segregation, and positive association with the richness and Shannon α-diversity of the porcine fecal bacterial ecosystem was confirmed in an unrelated F1 (Duroc × Iberian) cross. Our results advise the relevance of considering the role of host-genome structural variants as potential modulators of microbial ecosystems and suggest the ABCC2-DNMBP CNV as a host-genetic factor for the modulation of the diversity and composition of the fecal microbiota in pigs. IMPORTANCE A better understanding of the environmental and host factors modulating gut microbiomes is a topic of greatest interest. Recent evidence suggests that genetic variation in the pig genome partially controls the composition of porcine gut microbiota. However, since previous studies have been focused on the association between single nucleotide polymorphisms and the fecal microbiota, little is known about the relationship between other sources of genetic variation, like the structural variants and microbial traits. Here, we identified, experimentally validated, and replicated in an independent population a positive link between the gain of copies of ABCC2-DNMBP loci and the diversity and composition of pig fecal microbiota. Our results advise the relevance of considering the role of host-genome structural variants as putative modulators of microbial ecosystems and open the possibility of implementing novel holobiont-based management strategies in breeding programs for the simultaneous improvement of microbial traits and host performance.

Gut barrier-microbiota imbalances in early life lead to higher sensitivity to inflammation in a murine model of C-section delivery

BACKGROUND

Most interactions between the host and its microbiota occur at the gut barrier, and primary colonizers are essential in the gut barrier maturation in the early life. The mother-offspring transmission of microorganisms is the most important factor influencing microbial colonization in mammals, and C-section delivery (CSD) is an important disruptive factor of this transfer. Recently, the deregulation of symbiotic host-microbe interactions in early life has been shown to alter the maturation of the immune system, predisposing the host to gut barrier dysfunction and inflammation. The main goal of this study is to decipher the role of the early-life gut microbiota-barrier alterations and its links with later-life risks of intestinal inflammation in a murine model of CSD.

RESULTS

The higher sensitivity to chemically induced inflammation in CSD mice is related to excessive exposure to a too diverse microbiota too early in life. This early microbial stimulus has short-term consequences on the host homeostasis. It switches the pup's immune response to an inflammatory context and alters the epithelium structure and the mucus-producing cells, disrupting gut homeostasis. This presence of a too diverse microbiota in the very early life involves a disproportionate short-chain fatty acids ratio and an excessive antigen exposure across the vulnerable gut barrier in the first days of life, before the gut closure. Besides, as shown by microbiota transfer experiments, the microbiota is causal in the high sensitivity of CSD mice to chemical-induced colitis and in most of the phenotypical parameters found altered in early life. Finally, supplementation with lactobacilli, the main bacterial group impacted by CSD in mice, reverts the higher sensitivity to inflammation in ex-germ-free mice colonized by CSD pups' microbiota.

CONCLUSIONS

Early-life gut microbiota-host crosstalk alterations related to CSD could be the linchpin behind the phenotypic effects that lead to increased susceptibility to an induced inflammation later in life in mice. Video Abstract.

On the holobiont 'predictome' of immunocompetence in pigs

BACKGROUND

Gut microbial composition plays an important role in numerous traits, including immune response. Integration of host genomic information with microbiome data is a natural step in the prediction of complex traits, although methods to optimize this are still largely unexplored. In this paper, we assess the impact of different modelling strategies on the predictive capacity for six porcine immunocompetence traits when both genotype and microbiota data are available.

METHODS

We used phenotypic data on six immunity traits and the relative abundance of gut bacterial communities on 400 Duroc pigs that were genotyped for 70 k SNPs. We compared the predictive accuracy, defined as the correlation between predicted and observed phenotypes, of a wide catalogue of models: reproducing kernel Hilbert space (RKHS), Bayes C, and an ensemble method, using a range of priors and microbial clustering strategies. Combined (holobiont) models that include both genotype and microbiome data were compared with partial models that use one source of variation only.

RESULTS

Overall, holobiont models performed better than partial models. Host genotype was especially relevant for predicting adaptive immunity traits (i.e., concentration of immunoglobulins M and G), whereas microbial composition was important for predicting innate immunity traits (i.e., concentration of haptoglobin and C-reactive protein and lymphocyte phagocytic capacity). None of the models was uniformly best across all traits. We observed a greater variability in predictive accuracies across models when microbiability (the variance explained by the microbiome) was high. Clustering microbial abundances did not necessarily increase predictive accuracy.

CONCLUSIONS

Gut microbiota information is useful for predicting immunocompetence traits, especially those related to innate immunity. Modelling microbiome abundances deserves special attention when microbiability is high. Clustering microbial data for prediction is not recommended by default.

Mixed management in growing and finishing pigs: Differences between gender and their impacts on behavior, growth performance, and physiological parameters

Mixing, a common management strategy used to regroup pigs, has been reported to impair individual performance and affect pig welfare because of the establishment of a new social hierarchy after regrouping. In this study we aimed to determine whether mixing management (non-mixed vs. mixed) and gender (gilts vs. barrows) affect the social and non-social behavior, performance, and physiological parameters of pigs. A total of 96 growing pigs (48 barrows and 48 females) were separated into two treatments: control (CT)-pigs that were mixed once during the growing-finishing period; and social stress (SS)-pigs that were mixed thrice during the growing-finishing period. We recorded social and non-social behaviors, injury score, performance, and physiological parameters during the experimental period. Data were grouped by the period, based on each mix performed, and overall values. The statistical analysis performed considered gender and treatment. For treatment, during period-II and III, the SS group presented the highest frequency of agonistic interactions (AI), stayed longer lying laterally (LL) and sternly (LS), and explored more enrichment material (ER) than the CT group. Furthermore, SS pigs presented the highest injury score in the ear, head, and middle and posterior regions. Compared to the females, the barrows spent more time at the electronic feed station and initiated most of the agonistic interactions during period-II, and they presented a higher injury score for the ear and head regions during period-III. In conclusion, repeated regrouping significantly affected social and feeding behavior without severely altering performance and physiological parameters. Furthermore, different patterns of social and feeding behavior, agonistic interactions, and injury scores between barrows and females were observed. This study provides an understanding of the impact of mixing management and gender differences on pigs, and this knowledge can be used to improve swine productivity and welfare.

Hierarchy Establishment in Growing Finishing Pigs: Impacts on Behavior, Growth Performance, and Physiological Parameters

In recent years, an increased number of studies have dealt with the analysis of social dominance related to animal behavior, physiology, and performance. This study aimed to investigate whether hierarchical ranking affects the coping style, non-social behavior during open field and novel object tests, performance, and physiological parameters of pigs. A total of 48 growing pigs (24 barrows and 24 females) were mixed three times during the growing-finishing period. The social and non-social behaviors of pigs were directly noted, and three behavioral tests were performed during the experimental period. Performance and physiological parameters were also recorded. Statistical analysis considered hierarchical classification (dominant vs. intermediary vs. subordinate) and p-values ≤ 0.05 were considered significant. After three regroupings, the pigs in different hierarchical classifications showed no change in hair cortisol values and open-field and novel object tests. Mean corpuscular hemoglobin concentration and leukocyte values increased in intermediary pigs, and the lowest counts were found in pigs classified as dominants. Furthermore, dominant pigs visited the feeder more but spent shorter time there compared to subordinate and intermediary pigs. Our results suggest that hierarchical classification influenced feeding behavior and physiological parameters without affecting cortisol values and growth performance, demonstrating a possible compensation skill.

Genetic architecture of innate and adaptive immune cells in pigs

Pig industry is facing new challenges that make necessary to reorient breeding programs to produce more robust and resilient pig populations. The aim of the present work was to study the genetic determinism of lymphocyte subpopulations in the peripheral blood of pigs and identify genomic regions and biomarkers associated to them. For this purpose, we stained peripheral blood mononuclear cells to measure ten immune-cell-related traits including the relative abundance of different populations of lymphocytes, the proportions of CD4⁺ T cells and CD8⁺ T cells, and the ratio of CD4⁺/CD8⁺ T cells from 391 healthy Duroc piglets aged 8 weeks. Medium to high heritabilities were observed for the ten immune-cell-related traits and significant genetic correlations were obtained between the proportion of some lymphocytes populations. A genome-wide association study pointed out 32 SNPs located at four chromosomal regions on pig chromosomes SSC3, SSC5, SSC8, and SSCX as significantly associated to T-helper cells, memory T-helper cells and γδ T cells. Several genes previously identified in human association studies for the same or related traits were located in the associated regions, and were proposed as candidate genes to explain the variation of T cell populations such as CD4, CD8A, CD8B, KLRC2, RMND5A and VPS24. The transcriptome analysis of whole blood samples from animals with extreme proportions of γδ T, T-helper and memory T-helper cells identified differentially expressed genes (CAPG, TCF7L1, KLRD1 and CD4) located into the associated regions. In addition, differentially expressed genes specific of different T cells subpopulations were identified such as SOX13 and WC1 genes for γδ T cells. Our results enhance the knowledge about the genetic control of lymphocyte traits that could be considered to optimize the induction of immune responses to vaccines against pathogens. Furthermore, they open the possibility of applying effective selection programs for improving immunocompetence in pigs and support the use of the pig as a very reliable human biomedical model.

Identification of transcriptional regulatory variants in pig duodenum, liver, and muscle tissues

BACKGROUND

In humans and livestock species, genome-wide association studies (GWAS) have been applied to study the association between variants distributed across the genome and a phenotype of interest. To discover genetic polymorphisms affecting the duodenum, liver, and muscle transcriptomes of 300 pigs from 3 different breeds (Duroc, Landrace, and Large White), we performed expression GWAS between 25,315,878 polymorphisms and the expression of 13,891 genes in duodenum, 12,748 genes in liver, and 11,617 genes in muscle.

RESULTS

More than 9.68 × 1011 association tests were performed, yielding 14,096,080 significantly associated variants, which were grouped in 26,414 expression quantitative trait locus (eQTL) regions. Over 56% of the variants were within 1 Mb of their associated gene. In addition to the 100-kb region upstream of the transcription start site, we identified the importance of the 100-kb region downstream of the 3'UTR for gene regulation, as most of the cis-regulatory variants were located within these 2 regions. We also observed 39,874 hotspot regulatory polymorphisms associated with the expression of 10 or more genes that could modify the protein structure or the expression of a regulator gene. In addition, 2 motifs (5'-GATCCNGYGTTGCYG-3' and a poly(A) sequence) were enriched across the 3 tissues within the neighboring sequences of the most significant single-nucleotide polymorphisms in each cis-eQTL region.

CONCLUSIONS

The 14 million significant associations obtained in this study are publicly available and have enabled the identification of expression-associated cis-, trans-, and hotspot regulatory variants within and across tissues, thus shedding light on the molecular mechanisms of regulatory variations that shape end-trait phenotypes.

Disentangling the causal relationship between rabbit growth and cecal microbiota through structural equation models

BACKGROUND

The effect of the cecal microbiome on growth of rabbits that were fed under different regimes has been studied previously. However, the term "effect" carries a causal meaning that can be confounded because of potential genetic associations between the microbiome and production traits. Structural equation models (SEM) can help disentangle such a complex interplay by decomposing the effect on a production trait into direct host genetics effects and indirect host genetic effects that are exerted through microbiota effects. These indirect effects can be estimated via structural coefficients that measure the effect of the microbiota on growth while the effects of the host genetics are kept constant. In this study, we applied the SEM approach to infer causal relationships between the cecal microbiota and growth of rabbits fed under ad libitum (ADG_AL) or restricted feeding (ADG_R).

RESULTS

We identified structural coefficients that are statistically different from 0 for 138 of the 946 operational taxonomic units (OTU) analyzed. However, only 15 and 38 of these 138 OTU had an effect greater than 0.2 phenotypic standard deviations (SD) on ADG_AL and ADG_R, respectively. Many of these OTU had a negative effect on both traits. The largest effects on ADG_R were exerted by an OTU that is taxonomically assigned to the Desulfovibrio genus (- 1.929 g/d, CSS-normalized OTU units) and by an OTU that belongs to the Ruminococcaceae family (1.859 g/d, CSS-normalized OTU units). For ADG_AL, the largest effect was from OTU that belong to the S24-7 family (- 1.907 g/d, CSS-normalized OTU units). In general, OTU that had a substantial effect had low to moderate estimates of heritability.

CONCLUSIONS

Disentangling how direct and indirect effects act on production traits is relevant to fully describe the processes of mediation but also to understand how these traits change before considering the application of an external intervention aimed at changing a given microbial composition by blocking/promoting the presence of a particular microorganism.

Modeling microRNA-driven post-transcriptional regulation using exon-intron split analysis in pigs

The contribution of microRNAs (miRNAs) to mRNA post-transcriptional regulation has often been explored by the post hoc selection of downregulated genes and determining whether they harbor binding sites for miRNAs of interest. This approach, however, does not discriminate whether these mRNAs are also downregulated at the transcriptional level. Here, we have characterized the transcriptional and post-transcriptional changes in mRNA expression in two porcine tissues: gluteus medius muscle of fasted and fed Duroc gilts and adipose tissue of lean and obese Duroc-Göttingen minipigs. Exon-intron split analysis of RNA-seq data allowed us to identify downregulated mRNAs with high post-transcriptional signals in fed or obese states, and we assessed whether they harbor binding sites for upregulated miRNAs in any of these two physiological states. We found 26 downregulated mRNAs with high post-transcriptional signals in the muscle of fed gilts and 21 of these were predicted targets of miRNAs upregulated in fed pigs. For adipose tissue, 44 downregulated mRNAs in obese minipigs displayed high post-transcriptional signals, and 25 of these were predicted targets of miRNAs upregulated in the obese state. These results suggest that the contribution of miRNAs to mRNA repression is more prominent in the skeletal muscle system. Finally, we identified several genes that may play relevant roles in the energy homeostasis of the pig skeletal muscle (DKK2 and PDK4) and adipose (SESN3 and ESRRG) tissues. By differentiating transcriptional from post-transcriptional changes in mRNA expression, exon-intron split analysis provides a valuable view of the regulation of gene expression, complementary to canonical differential expression analyses.

Use of Bayes factors to evaluate the effects of host genetics, litter and cage on the rabbit cecal microbiota

Background

The rabbit cecum hosts and interacts with a complex microbial ecosystem that contributes to the variation of traits of economic interest. Although the influence of host genetics on microbial diversity and specific microbial taxa has been studied in several species (e.g., humans, pigs, or cattle), it has not been investigated in rabbits. Using a Bayes factor approach, the aim of this study was to dissect the effects of host genetics, litter and cage on 984 microbial traits that are representative of the rabbit microbiota.

Results

Analysis of 16S rDNA sequences of cecal microbiota from 425 rabbits resulted in the relative abundances of 29 genera, 951 operational taxonomic units (OTU), and four microbial alpha-diversity indices. Each of these microbial traits was adjusted with mixed linear and zero-inflated Poisson (ZIP) models, which all included additive genetic, litter and cage effects, and body weight at weaning and batch as systematic factors. The marginal posterior distributions of the model parameters were estimated using MCMC Bayesian procedures. The deviance information criterion (DIC) was used for model comparison regarding the statistical distribution of the data (normal or ZIP), and the Bayes factor was computed as a measure of the strength of evidence in favor of the host genetics, litter, and cage effects on microbial traits. According to DIC, all microbial traits were better adjusted with the linear model except for the OTU present in less than 10% of the animals, and for 25 of the 43 OTU with a frequency between 10 and 25%. On a global scale, the Bayes factor revealed substantial evidence in favor of the genetic control of the number of observed OTU and Shannon indices. At the taxon-specific level, significant proportions of the OTU and relative abundances of genera were influenced by additive genetic, litter, and cage effects. Several members of the genera Bacteroides and Parabacteroides were strongly influenced by the host genetics and nursing environment, whereas the family S24-7 and the genus Ruminococcus were strongly influenced by cage effects.

Conclusions

This study demonstrates that host genetics shapes the overall rabbit cecal microbial diversity and that a significant proportion of the taxa is influenced either by host genetics or environmental factors, such as litter and/or cage.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-022-00738-2.

A Co-Association Network Analysis Reveals Putative Regulators for Health-Related Traits in Pigs

In recent years, the increase in awareness of antimicrobial resistance together with the societal demand of healthier meat products have driven attention to health-related traits in livestock production. Previous studies have reported medium to high heritabilities for these traits and described genomic regions associated with them. Despite its genetic component, health- and immunity-related traits are complex and its study by association analysis with genomic markers may be missing some information. To analyse multiple phenotypes and gene-by-gene interactions, systems biology approaches, such as the association weight matrix (AWM), allows combining genome wide association study results with network inference algorithms. The present study aimed to identify gene networks, key regulators and candidate genes associated to immunocompetence in pigs by integrating multiple health-related traits, enriched for innate immune phenotypes, using the AWM approach. The co-association network analysis unveiled a network comprised of 3,636 nodes (genes) and 451,407 edges (interactions), including a total of 246 regulators. From these, five genes (ARNT2, BRMS1L, MED12L, SUPT3H and TRIM25) were selected as key regulators as they were associated with the maximum number of genes with the minimum overlapping (1,827 genes in total). The five regulators were involved in pathways related to immunity such as lymphocyte differentiation and activation, platelet activation and degranulation, megakaryocyte differentiation, FcγR-mediated phagocytosis and response to nitric oxide, among others, but also in immunometabolism. Furthermore, we identified genes co-associated with the key regulators previously reported as candidate genes (e.g., ANGPT1, CD4, CD36, DOCK1, PDE4B, PRKCE, PTPRC and SH2B3) for immunity traits in humans and pigs, but also new candidate ones (e.g., ACSL3, CXADR, HBB, MMP12, PTPN6, WLS) that were not previously described. The co-association analysis revealed new regulators associated with health-related traits in pigs. This approach also identified gene-by-gene interactions and candidate genes involved in pathways related to cell fate and metabolic and immune functions. Our results shed new light in the regulatory mechanisms involved in pig immunity and reinforce the use of the pig as biomedical model.

Leveraging host-genetics and gut microbiota to determine immunocompetence in pigs

Background

The gut microbiota influences host performance playing a relevant role in homeostasis and function of the immune system. The aim of the present work was to identify microbial signatures linked to immunity traits and to characterize the contribution of host-genome and gut microbiota to the immunocompetence in healthy pigs.

Results

To achieve this goal, we undertook a combination of network, mixed model and microbial-wide association studies (MWAS) for 21 immunity traits and the relative abundance of gut bacterial communities in 389 pigs genotyped for 70K SNPs. The heritability (h²; proportion of phenotypic variance explained by the host genetics) and microbiability (m²; proportion of variance explained by the microbial composition) showed similar values for most of the analyzed immunity traits, except for both IgM and IgG in plasma that was dominated by the host genetics, and the haptoglobin in serum which was the trait with larger m² (0.275) compared to h² (0.138). Results from the MWAS suggested a polymicrobial nature of the immunocompetence in pigs and revealed associations between pigs gut microbiota composition and 15 of the analyzed traits. The lymphocytes phagocytic capacity (quantified as mean fluorescence) and the total number of monocytes in blood were the traits associated with the largest number of taxa (6 taxa). Among the associations identified by MWAS, 30% were confirmed by an information theory network approach. The strongest confirmed associations were between Fibrobacter and phagocytic capacity of lymphocytes (r = 0.37), followed by correlations between Streptococcus and the percentage of phagocytic lymphocytes (r = -0.34) and between Megasphaera and serum concentration of haptoglobin (r = 0.26). In the interaction network, Streptococcus and percentage of phagocytic lymphocytes were the keystone bacterial and immune-trait, respectively.

Conclusions

Overall, our findings reveal an important connection between gut microbiota composition and immunity traits in pigs, and highlight the need to consider both sources of information, host genome and microbial levels, to accurately characterize immunocompetence in pigs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s42523-021-00138-9.

The value of gut microbiota to predict feed efficiency and growth of rabbits under different feeding regimes

Gut microbiota plays an important role in nutrient absorption and could impact rabbit feed efficiency. This study aims at investigating such impact by evaluating the value added by microbial information for predicting individual growth and cage phenotypes related to feed efficiency. The dataset comprised individual average daily gain and cage-average daily feed intake from 425 meat rabbits, in which cecal microbiota was assessed, and their cage mates. Despite microbiota was not measured in all animals, consideration of pedigree relationships with mixed models allowed the study of cage-average traits. The inclusion of microbial information into certain mixed models increased their predictive ability up to 20% and 46% for cage-average feed efficiency and individual growth traits, respectively. These gains were associated with large microbiability estimates and with reductions in the heritability estimates. However, large microbiabililty estimates were also obtained with certain models but without any improvement in their predictive ability. A large proportion of OTUs seems to be responsible for the prediction improvement in growth and feed efficiency traits, although specific OTUs taxonomically assigned to 5 different phyla have a higher weight. Rabbit growth and feed efficiency are influenced by host cecal microbiota, thus considering microbial information in models improves the prediction of these complex phenotypes.

Opportunities and limits of combining microbiome and genome data for complex trait prediction

Background

Analysis and prediction of complex traits using microbiome data combined with host genomic information is a topic of utmost interest. However, numerous questions remain to be answered: how useful can the microbiome be for complex trait prediction? Are estimates of microbiability reliable? Can the underlying biological links between the host’s genome, microbiome, and phenome be recovered?

Methods

Here, we address these issues by (i) developing a novel simulation strategy that uses real microbiome and genotype data as inputs, and (ii) using variance-component approaches (Bayesian Reproducing Kernel Hilbert Space (RKHS) and Bayesian variable selection methods (Bayes C)) to quantify the proportion of phenotypic variance explained by the genome and the microbiome. The proposed simulation approach can mimic genetic links between the microbiome and genotype data by a permutation procedure that retains the distributional properties of the data.

Results

Using real genotype and rumen microbiota abundances from dairy cattle, simulation results suggest that microbiome data can significantly improve the accuracy of phenotype predictions, regardless of whether some microbiota abundances are under direct genetic control by the host or not. This improvement depends logically on the microbiome being stable over time. Overall, random-effects linear methods appear robust for variance components estimation, in spite of the typically highly leptokurtic distribution of microbiota abundances. The predictive performance of Bayes C was higher but more sensitive to the number of causative effects than RKHS. Accuracy with Bayes C depended, in part, on the number of microorganisms’ taxa that influence the phenotype.

Conclusions

While we conclude that, overall, genome-microbiome-links can be characterized using variance component estimates, we are less optimistic about the possibility of identifying the causative host genetic effects that affect microbiota abundances, which would require much larger sample sizes than are typically available for genome-microbiome-phenome studies. The R code to replicate the analyses is in https://github.com/miguelperezenciso/simubiome.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00658-7.

Diet, Immunity, and Microbiota Interactions: An Integrative Analysis of the Intestine Transcriptional Response and Microbiota Modulation in Gilthead Seabream (Sparus aurata) Fed an Essential Oils-Based Functional Diet

Essential oils (EOs) are promising alternatives to chemotherapeutics in animal production due to their immunostimulant, antimicrobial, and antioxidant properties, without associated environmental or hazardous side effects. In the present study, the modulation of the transcriptional immune response (microarray analysis) and microbiota [16S Ribosomal RNA (rRNA) sequencing] in the intestine of the euryhaline fish gilthead seabream (Sparus aurata) fed a dietary supplementation of garlic, carvacrol, and thymol EOs was evaluated. The transcriptomic functional analysis showed the regulation of genes related to processes of proteolysis and inflammatory modulation, immunity, transport and secretion, response to cyclic compounds, symbiosis, and RNA metabolism in fish fed the EOs-supplemented diet. Particularly, the activation of leukocytes, such as acidophilic granulocytes, was suggested to be the primary actors of the innate immune response promoted by the tested functional feed additive in the gut. Fish growth performance and gut microbiota alpha diversity indices were not affected, while dietary EOs promoted alterations in bacterial abundances in terms of phylum, class, and genus. Subtle, but significant alterations in microbiota composition, such as the decrease in Bacteroidia and Clostridia classes, were suggested to participate in the modulation of the intestine transcriptional immune profile observed in fish fed the EOs diet. Moreover, regarding microbiota functionality, increased bacterial sequences associated with glutathione and lipid metabolisms, among others, detected in fish fed the EOs supported the metabolic alterations suggested to potentially affect the observed immune-related transcriptional response. The overall results indicated that the tested dietary EOs may promote intestinal local immunity through the impact of the EOs on the host-microbial co-metabolism and consequent regulation of significant biological processes, evidencing the crosstalk between gut and microbiota in the inflammatory regulation upon administration of immunostimulant feed additives.

A gene co-association network regulating gut microbial communities in a Duroc pig population

BACKGROUND

Analyses of gut microbiome composition in livestock species have shown its potential to contribute to the regulation of complex phenotypes. However, little is known about the host genetic control over the gut microbial communities. In pigs, previous studies are based on classical "single-gene-single-trait" approaches and have evaluated the role of host genome controlling gut prokaryote and eukaryote communities separately.

RESULTS

In order to determine the ability of the host genome to control the diversity and composition of microbial communities in healthy pigs, we undertook genome-wide association studies (GWAS) for 39 microbial phenotypes that included 2 diversity indexes, and the relative abundance of 31 bacterial and six commensal protist genera in 390 pigs genotyped for 70 K SNPs. The GWAS results were processed through a 3-step analytical pipeline comprised of (1) association weight matrix; (2) regulatory impact factor; and (3) partial correlation and information theory. The inferred gene regulatory network comprised 3561 genes (within a 5 kb distance from a relevant SNP-P < 0.05) and 738,913 connections (SNP-to-SNP co-associations). Our findings highlight the complexity and polygenic nature of the pig gut microbial ecosystem. Prominent within the network were 5 regulators, PRDM15, STAT1, ssc-mir-371, SOX9 and RUNX2 which gathered 942, 607, 588, 284 and 273 connections, respectively. PRDM15 modulates the transcription of upstream regulators of WNT and MAPK-ERK signaling to safeguard naive pluripotency and regulates the production of Th1- and Th2-type immune response. The signal transducer STAT1 has long been associated with immune processes and was recently identified as a potential regulator of vaccine response to porcine reproductive and respiratory syndrome. The list of regulators was enriched for immune-related pathways, and the list of predicted targets includes candidate genes previously reported as associated with microbiota profile in pigs, mice and human, such as SLIT3, SLC39A8, NOS1, IL1R2, DAB1, TOX3, SPP1, THSD7B, ELF2, PIANP, A2ML1, and IFNAR1. Moreover, we show the existence of host-genetic variants jointly associated with the relative abundance of butyrate producer bacteria and host performance.

CONCLUSIONS

Taken together, our results identified regulators, candidate genes, and mechanisms linked with microbiome modulation by the host. They further highlight the value of the proposed analytical pipeline to exploit pleiotropy and the crosstalk between bacteria and protists as significant contributors to host-microbiome interactions and identify genetic markers and candidate genes that can be incorporated in breeding program to improve host-performance and microbial traits. Video Abstract.

kernInt: A Kernel Framework for Integrating Supervised and Unsupervised Analyses in Spatio-Temporal Metagenomic Datasets

The advent of next-generation sequencing technologies allowed relative quantification of microbiome communities and their spatial and temporal variation. In recent years, supervised learning (i.e., prediction of a phenotype of interest) from taxonomic abundances has become increasingly common in the microbiome field. However, a gap exists between supervised and classical unsupervised analyses, based on computing ecological dissimilarities for visualization or clustering. Despite this, both approaches face common challenges, like the compositional nature of next-generation sequencing data or the integration of the spatial and temporal dimensions. Here we propose a kernel framework to place on a common ground the unsupervised and supervised microbiome analyses, including the retrieval of microbial signatures (taxa importances). We define two compositional kernels (Aitchison-RBF and compositional linear) and discuss how to transform non-compositional beta-dissimilarity measures into kernels. Spatial data is integrated with multiple kernel learning, while longitudinal data is evaluated by specific kernels. We illustrate our framework through a single point soil dataset, a human dataset with a spatial component, and a previously unpublished longitudinal dataset concerning pig production. The proposed framework and the case studies are freely available in the kernInt package at https://github.com/elies-ramon/kernInt.

Whole-genome sequencing reveals insights into the adaptation of French Charolais cattle to Cuban tropical conditions

Background

In the early 20th century, Cuban farmers imported Charolais cattle (CHFR) directly from France. These animals are now known as Chacuba (CHCU) and have become adapted to the rough environmental tropical conditions in Cuba. These conditions include long periods of drought and food shortage with extreme temperatures that European taurine cattle have difficulty coping with.

Results

In this study, we used whole-genome sequence data from 12 CHCU individuals together with 60 whole-genome sequences from six additional taurine, indicus and crossed breeds to estimate the genetic diversity, structure and accurate ancestral origin of the CHCU animals. Although CHCU animals are assumed to form a closed population, the results of our admixture analysis indicate a limited introgression of Bos indicus. We used the extended haplotype homozygosity (EHH) approach to identify regions in the genome that may have had an important role in the adaptation of CHCU to tropical conditions. Putative selection events occurred in genomic regions with a high proportion of Bos indicus, but they were not sufficient to explain adaptation of CHCU to tropical conditions by Bos indicus introgression only. EHH suggested signals of potential adaptation in genomic windows that include genes of taurine origin involved in thermogenesis (ATP9A, GABBR1, PGR, PTPN1 and UCP1) and hair development (CCHCR1 and CDSN). Within these genes, we identified single nucleotide polymorphisms (SNPs) that may have a functional impact and contribute to some of the observed phenotypic differences between CHCU and CHFR animals.

Conclusions

Whole-genome data confirm that CHCU cattle are closely related to Charolais from France (CHFR) and Canada, but also reveal a limited introgression of Bos indicus genes in CHCU. We observed possible signals of recent adaptation to tropical conditions between CHCU and CHFR founder populations, which were largely independent of the Bos indicus introgression. Finally, we report candidate genes and variants that may have a functional impact and explain some of the phenotypic differences observed between CHCU and CHFR cattle.

A systems biology framework integrating GWAS and RNA-seq to shed light on the molecular basis of sperm quality in swine

BACKGROUND

Genetic pressure in animal breeding is sparking the interest of breeders for selecting elite boars with higher sperm quality to optimize ejaculate doses and fertility rates. However, the molecular basis of sperm quality is not yet fully understood. Our aim was to identify candidate genes, pathways and DNA variants associated to sperm quality in swine by analysing 25 sperm-related phenotypes and integrating genome-wide association studies (GWAS) and RNA-seq under a systems biology framework.

RESULTS

By GWAS, we identified 12 quantitative trait loci (QTL) associated to the percentage of head and neck abnormalities, abnormal acrosomes and motile spermatozoa. Candidate genes included CHD2, KATNAL2, SLC14A2 and ABCA1. By RNA-seq, we identified a wide repertoire of mRNAs (e.g. PRM1, OAZ3, DNAJB8, TPPP2 and TNP1) and miRNAs (e.g. ssc-miR-30d, ssc-miR-34c, ssc-miR-30c-5p, ssc-miR-191, members of the let-7 family and ssc-miR-425-5p) with functions related to sperm biology. We detected 6128 significant correlations (P-value ≤ 0.05) between sperm traits and mRNA abundances. By expression (e)GWAS, we identified three trans-expression QTL involving the genes IQCJ, ACTR2 and HARS. Using the GWAS and RNA-seq data, we built a gene interaction network. We considered that the genes and interactions that were present in both the GWAS and RNA-seq networks had a higher probability of being actually involved in sperm quality and used them to build a robust gene interaction network. In addition, in the final network we included genes with RNA abundances correlated with more than four semen traits and miRNAs interacting with the genes on the network. The final network was enriched for genes involved in gamete generation and development, meiotic cell cycle, DNA repair or embryo implantation. Finally, we designed a panel of 73 SNPs based on the GWAS, eGWAS and final network data, that explains between 5% (for sperm cell concentration) and 36% (for percentage of neck abnormalities) of the phenotypic variance of the sperm traits.

CONCLUSIONS

By applying a systems biology approach, we identified genes that potentially affect sperm quality and constructed a SNP panel that explains a substantial part of the phenotypic variance for semen quality in our study and that should be tested in other swine populations to evaluate its relevance for the pig breeding sector.

The Identification of Runs of Homozygosity Gives a Focus on the Genetic Diversity and Adaptation of the "Charolais de Cuba" Cattle

Simple Summary

The Charolais de Cuba cattle is a tropical adapted breed founded in Cuba around 120 years ago from Charolais French specimens. Nowadays, it is still a closed breed and remains as a small population. In this work, we analyzed the inbreeding and diversity patterns, as well as the population size, of this recent adapted breed via a run of homozygosity (ROH) analysis. We found that the genomic inbreeding levels are higher in the Charolais de Cuba breed compared to French and British Charolais populations. Nevertheless, we detected that the effective population size experienced a very similar decline during the last century in the three Charolais populations studied. Finally, a number of regions with exceptional patterns of long homozygosity were identified in this breed, and these could be related to processes of adaptation to tropical conditions.

Abstract

Inbreeding and effective population size (Ne) are fundamental indicators for the management and conservation of genetic diversity in populations. Genomic inbreeding gives accurate estimates of inbreeding, and the Ne determines the rate of the loss of genetic variation. The objective of this work was to study the distribution of runs of homozygosity (ROHs) in order to estimate genomic inbreeding (F_ROH) and an effective population size using 38,789 Single Nucleotide Polymorphisms (SNPs) from the Illumina Bovine 50K BeadChip in 86 samples from populations of Charolais de Cuba (n = 40) cattle and to compare this information with French (n = 20) and British Charolais (n = 26) populations. In the Cuban, French, and British Charolais populations, the average estimated genomic inbreeding values using the F_ROH statistics were 5.7%, 3.4%, and 4%, respectively. The dispersion measured by variation coefficient was high at 43.9%, 37.0%, and 54.2%, respectively. The effective population size experienced a very similar decline during the last century in Charolais de Cuba (from 139 to 23 individuals), in French Charolais (from 142 to 12), and in British Charolais (from 145 to 14) for the ~20 last generations. However, the high variability found in the ROH indicators and F_ROH reveals an opportunity for maintaining the genetic diversity of this breed with an adequate mating strategy, which can be favored with the use of molecular markers. Moreover, the detected ROH were compared to previous results obtained on the detection of signatures of selection in the same breed. Some of the observed signatures were confirmed by the ROHs, emphasizing the process of adaptation to tropical climate experienced by the Charolais de Cuba population.

Gene networks for three feed efficiency criteria reveal shared and specific biological processes

Background

French beef producers suffer from the decrease in profitability of their farms mainly because of the continuous increase in feed costs. Selection for feed efficiency in beef cattle represents a relevant solution to face this problem. However, feed efficiency is a complex trait that can be assessed by three major criteria: residual feed intake (RFI), residual gain (RG) and feed efficiency ratio (FE), which involve different genetic determinisms. An analysis that combines phenotype and whole-genome sequence data provides a unique framework for genomic studies. The aim of our study was to identify the gene networks and the biological processes that are responsible for the genetic determinism that is shared between these three feed efficiency criteria.

Results

A population of 1477 French Charolais young bulls was phenotyped for feed intake (FI), average daily gain (ADG) and final weight (FW) to estimate RFI, RG and FE. A subset of 789 young bulls was genotyped on the BovineSNP50 single nucleotide polymorphism (SNP) array and imputed at the sequence level using RUN6 of the 1000 Bull Genomes Project. We conducted a genome-wide association study (GWAS) to estimate the individual effect of 8.5 million SNPs and applied an association weight matrix (AWM) approach to analyse the results, one for each feed efficiency criterion. The results highlighted co-association networks including 626 genes for RFI, 426 for RG and 564 for FE. Enrichment assessment revealed the biological processes that show the strongest association with RFI, RG and FE, i.e. digestive tract (salivary, gastric and mucin secretion) and metabolic processes (cellular and cardiovascular). Energetic functions were more associated with RFI and FE and cardio-vascular and cellular processes with RG. Several hormones such as apelin, glucagon, insulin, aldosterone, the gonadotrophin releasing hormone and the thyroid hormone were also identified, and these should be tested in future studies as candidate biomarkers for feed efficiency.

Conclusions

The combination of network and pathway analyses at the sequence level led to the identification of both common and specific mechanisms that are involved in RFI, RG and FE, and to a better understanding of the genetic determinism underlying these three criteria. The effects of the genes involved in each of the identified processes need to be tested in genomic evaluations to confirm the potential gain in reliability of using functional variants to select animals for feed efficiency.

Breeding farm, level of feeding and presence of antibiotics in the feed influence rabbit cecal microbiota

Background

The effect of the production environment and different management practices in rabbit cecal microbiota remains poorly understood. While previous studies have proved the impact of the age or the feed composition, research in the breeding farm and other animal management aspects, such as the presence of antibiotics in the feed or the level of feeding, is still needed. Characterization of microbial diversity and composition of growing rabbits raised under different conditions could help better understand the role these practices play in cecal microbial communities and how it may result in different animal performance.

Results

Four hundred twenty-five meat rabbits raised in two different facilities, fed under two feeding regimes (ad libitum or restricted) with feed supplemented or free of antibiotics, were selected for this study. A 16S rRNA gene-based assessment through the MiSeq Illumina sequencing platform was performed on cecal samples collected from these individuals at slaughter. Different univariate and multivariate approaches were conducted to unravel the influence of the different factors on microbial alpha diversity and composition at phylum, genus and OTU taxonomic levels. The animals raised in the facility harboring the most stable environmental conditions had greater, and less variable, microbial richness and diversity. Bootstrap univariate analyses of variance and sparse partial least squares-discriminant analyses endorsed that farm conditions exerted an important influence on rabbit microbiota since the relative abundances of many taxa were found differentially represented between both facilities at all taxonomic levels characterized. Furthermore, only five OTUs were needed to achieve a perfect classification of samples according to the facility where animals were raised. The level of feeding and the presence of antibiotics did not modify the global alpha diversity but had an impact on some bacteria relative abundances, albeit in a small number of taxa compared with farm, which is consistent with the lower sample classification power according to these factors achieved using microbial information.

Conclusions

This study reveals that factors associated with the farm effect and other management factors, such as the presence of antibiotics in the diet or the feeding level, modify cecal microbial communities. It highlights the importance of offering a controlled breeding environment that reduces differences in microbial cecal composition that could be responsible for different animal performance.

Link-HD: a versatile framework to explore and integrate heterogeneous microbial communities

MOTIVATION

We present Link-HD, an approach to integrate multiple datasets. Link-HD is a generalization of 'Structuration des Tableaux A Trois Indices de la Statistique-Analyse Conjointe de Tableaux', a family of methods designed to integrate information from heterogeneous data. Here, we extend the classical approach to deal with broader datasets (e.g. compositional data), methods for variable selection and taxon-set enrichment analysis.

RESULTS

The methodology is demonstrated by integrating rumen microbial communities from cows for which methane yield (CH4y) was individually measured. Our approach reproduces the significant link between rumen microbiota structure and CH4 emission. When analyzing the TARA's ocean data, Link-HD replicates published results, highlighting the relevance of temperature with members of phyla Proteobacteria on the structure and functionality of this ecosystem.

AVAILABILITY AND IMPLEMENTATION

The source code, examples and a complete manual are freely available in GitHub https://github.com/lauzingaretti/LinkHD and in Bioconductor https://bioconductor.org/packages/release/bioc/html/LinkHD.html.

Single-step genome-wide association study for social genetic effects and direct genetic effects on growth in Landrace pigs

In livestock social interactions, social genetic effects (SGE) represent associations between phenotype of one individual and genotype of another. Such associations occur when the trait of interest is affected by transmissible phenotypes of social partners. The aim of this study was to estimate SGE and direct genetic effects (DGE, genetic effects of an individual on its own phenotype) on average daily gain (ADG) in Landrace pigs, and to conduct single-step genome-wide association study using SGE and DGE as dependent variables to identify quantitative trait loci (QTLs) and their positional candidate genes. A total of 1,041 Landrace pigs were genotyped using the Porcine SNP 60K BeadChip. Estimates of the two effects were obtained using an extended animal model. The SGE contributed 16% of the total heritable variation of ADG. The total heritability estimated by the extended animal model including both SGE and DGE was 0.52. The single-step genome-wide association study identified a total of 23 QTL windows for the SGE on ADG distributed across three chromosomes (i.e., SSC1, SSC2, and SSC6). Positional candidate genes within these QTL regions included PRDM13, MAP3K7, CNR1, HTR1E, IL4, IL5, IL13, KIF3A, EFHD2, SLC38A7, mTOR, CNOT1, PLCB2, GABRR1, and GABRR2, which have biological roles in neuropsychiatric processes. The results of biological pathway and gene network analyses also support the association of the neuropsychiatric processes with SGE on ADG in pigs. Additionally, a total of 11 QTL windows for DGE on ADG in SSC2, 3, 6, 9, 10, 12, 14, 16, and 17 were detected with positional candidate genes such as ARL15. We found a putative pleotropic QTL for both SGE and DGE on ADG on SSC6. Our results in this study provide important insights that can help facilitate a better understanding of the molecular basis of SGE for socially affected traits.

Detection of selection signatures in Limousin cattle using whole-genome resequencing

Limousin, a renowned beef breed originating from central France, has been selectively bred over the last 100 years to improve economically important traits. We used whole-genome sequencing data from 10 unrelated Limousin bull calves to detect polymorphisms and identify regions under selection. A total of 13 943 766 variants were identified. Moreover, 311 852 bi-allelic SNPs and 92 229 indels located on autosomes were fixed for the alternative allele in all sequenced animals, including the previously reported missense deleterious F94L mutation in MSTN. We performed a whole-genome screen to discover genomic regions with excess homozygosity, using the pooled heterozygosity score and identified 171 different candidate selective sweeps. In total, 68 candidate genes were found in only 57 of these regions, indicating that a large fraction of the genome under selection might lie in non-coding regions and suggesting that a majority of adaptive mutations might be regulatory in nature. Many QTL were found within candidate selective sweep regions, including QTL associated with shear force or carcass weight. Among the putative selective sweeps, we located genes (MSTN, NCKAP5, RUNX2) that potentially contribute to important phenotypes in Limousin. Several candidate regions and genes under selection were also found in previous genome-wide selection scans performed in Limousin. In addition, we were able to pinpoint candidate causative regulatory polymorphisms in GRIK3 and RUNX2 that might have been under selection. Our results will contribute to improved understanding of the mechanisms and targets of artificial selection and will facilitate the interpretation of GWASs performed in Limousin.

A catalog of microbial genes from the bovine rumen unveils a specialized and diverse biomass-degrading environment

Background

The rumen microbiota provides essential services to its host and, through its role in ruminant production, contributes to human nutrition and food security. A thorough knowledge of the genetic potential of rumen microbes will provide opportunities for improving the sustainability of ruminant production systems. The availability of gene reference catalogs from gut microbiomes has advanced the understanding of the role of the microbiota in health and disease in humans and other mammals. In this work, we established a catalog of reference prokaryote genes from the bovine rumen.

Results

Using deep metagenome sequencing we identified 13,825,880 non-redundant prokaryote genes from the bovine rumen. Compared to human, pig, and mouse gut metagenome catalogs, the rumen is larger and richer in functions and microbial species associated with the degradation of plant cell wall material and production of methane. Genes encoding enzymes catalyzing the breakdown of plant polysaccharides showed a particularly high richness that is otherwise impossible to infer from available genomes or shallow metagenomics sequencing. The catalog expands the dataset of carbohydrate-degrading enzymes described in the rumen. Using an independent dataset from a group of 77 cattle fed 4 common dietary regimes, we found that only <0.1% of genes were shared by all animals, which contrast with a large overlap for functions, i.e., 63% for KEGG functions. Different diets induced differences in the relative abundance rather than the presence or absence of genes, which explains the great adaptability of cattle to rapidly adjust to dietary changes.

Conclusions

These data bring new insights into functions, carbohydrate-degrading enzymes, and microbes of the rumen to complement the available information on microbial genomes. The catalog is a significant biological resource enabling deeper understanding of phenotypes and biological processes and will be expanded as new data are made available.

Priming for welfare: gut microbiota is associated with equitation conditions and behavior in horse athletes

We simultaneously measured the fecal microbiota and multiple environmental and host-related variables in a cohort of 185 healthy horses reared in similar conditions during a period of eight months. The pattern of rare bacteria varied from host to host and was largely different between two time points. Among a suite of variables examined, equitation factors were highly associated with the gut microbiota variability, evoking a relationship between gut microbiota and high levels of physical and mental stressors. Behavioral indicators that pointed toward a compromised welfare state (e.g. stereotypies, hypervigilance and aggressiveness) were also associated with the gut microbiota, reinforcing the notion for the existence of the microbiota-gut-brain axis. These observations were consistent with the microbiability of behaviour traits (> 15%), illustrating the importance of gut microbial composition to animal behaviour. As more elite athletes suffer from stress, targeting the microbiota offers a new opportunity to investigate the bidirectional interactions within the brain gut microbiota axis.

Gut eukaryotic communities in pigs: diversity, composition and host genetics contribution

BACKGROUND

The pig gut microbiome harbors thousands of species of archaea, bacteria, viruses and eukaryotes such as protists and fungi. However, since the majority of published studies have been focused on prokaryotes, little is known about the diversity, host-genetic control, and contributions to host performance of the gut eukaryotic counterparts. Here we report the first study that aims at characterizing the diversity and composition of gut commensal eukaryotes in pigs, exploring their putative control by host genetics, and analyzing their association with piglets body weight.

RESULTS

Fungi and protists from the faeces of 514 healthy Duroc pigs of two sexes and two different ages were characterized by 18S and ITS ribosomal RNA gene sequencing. The pig gut mycobiota was dominated by yeasts, with a high prevalence and abundance of Kazachstania spp. Regarding protists, representatives of four genera (Blastocystis, Neobalantidium, Tetratrichomonas and Trichomitus) were predominant in more than the 80% of the pigs. Heritabilities for the diversity and abundance of gut eukaryotic communities were estimated with the subset of 60d aged piglets (N = 390). The heritabilities of α-diversity and of the abundance of fungal and protists genera were low, ranging from 0.15 to 0.28. A genome wide association study reported genetic variants related to the fungal α-diversity and to the abundance of Blastocystis spp. Annotated candidate genes were mainly associated with immunity, gut homeostasis and metabolic processes. Additionally, we explored the association of gut commensal eukaryotes with piglet body weight. Our results pointed to a positive contribution of fungi from the Kazachstania genus, while protists displayed both positive (Blastocystis and Entamoeba) and negative (Trichomitus) associations with piglet body weight.

CONCLUSIONS

Our results point towards a minor and taxa specific genetic control over the diversity and composition of the pig gut eukaryotic communities. Moreover, we provide evidences of the associations between piglets' body weight after weaning and members from the gut fungal and protist eukaryote community. Overall, this study highlights the relevance of considering, along with that of bacteria, the contribution of the gut eukaryote communities to better understand host-microbiome association and their role on pig performance, welfare and health.

Co-expression network analysis predicts a key role of microRNAs in the adaptation of the porcine skeletal muscle to nutrient supply

BACKGROUND

The role of non-coding RNAs in the porcine muscle metabolism is poorly understood, with few studies investigating their expression patterns in response to nutrient supply. Therefore, we aimed to investigate the changes in microRNAs (miRNAs), long intergenic non-coding RNAs (lincRNAs) and mRNAs muscle expression before and after food intake.

RESULTS

We measured the miRNA, lincRNA and mRNA expression levels in the gluteus medius muscle of 12 gilts in a fasting condition (AL-T0) and 24 gilts fed ad libitum during either 5 h. (AL-T1, N = 12) or 7 h. (AL-T2, N = 12) prior to slaughter. The small RNA fraction was extracted from muscle samples retrieved from the 36 gilts and sequenced, whereas lincRNA and mRNA expression data were already available. In terms of mean and variance, the expression profiles of miRNAs and lincRNAs in the porcine muscle were quite different than those of mRNAs. Food intake induced the differential expression of 149 (AL-T0/AL-T1) and 435 (AL-T0/AL-T2) mRNAs, 6 (AL-T0/AL-T1) and 28 (AL-T0/AL-T2) miRNAs and none lincRNAs, while the number of differentially dispersed genes was much lower. Among the set of differentially expressed miRNAs, we identified ssc-miR-148a-3p, ssc-miR-22-3p and ssc-miR-1, which play key roles in the regulation of glucose and lipid metabolism. Besides, co-expression network analyses revealed several miRNAs that putatively interact with mRNAs playing key metabolic roles and that also showed differential expression before and after feeding. One case example was represented by seven miRNAs (ssc-miR-148a-3p, ssc-miR-151-3p, ssc-miR-30a-3p, ssc-miR-30e-3p, ssc-miR-421-5p, ssc-miR-493-5p and ssc-miR-503) which putatively interact with the PDK4 mRNA, one of the master regulators of glucose utilization and fatty acid oxidation.

CONCLUSIONS

As a whole, our results evidence that microRNAs are likely to play an important role in the porcine skeletal muscle metabolic adaptation to nutrient availability.

A functional regulatory variant of MYH3 influences muscle fiber-type composition and intramuscular fat content in pigs

Muscle development and lipid accumulation in muscle critically affect meat quality of livestock. However, the genetic factors underlying myofiber-type specification and intramuscular fat (IMF) accumulation remain to be elucidated. Using two independent intercrosses between Western commercial breeds and Korean native pigs (KNPs) and a joint linkage-linkage disequilibrium analysis, we identified a 488.1-kb region on porcine chromosome 12 that affects both reddish meat color (a*) and IMF. In this critical region, only the MYH3 gene, encoding myosin heavy chain 3, was found to be preferentially overexpressed in the skeletal muscle of KNPs. Subsequently, MYH3-transgenic mice demonstrated that this gene controls both myofiber-type specification and adipogenesis in skeletal muscle. We discovered a structural variant in the promotor/regulatory region of MYH3 for which Q allele carriers exhibited significantly higher values of a* and IMF than q allele carriers. Furthermore, chromatin immunoprecipitation and cotransfection assays showed that the structural variant in the 5'-flanking region of MYH3 abrogated the binding of the myogenic regulatory factors (MYF5, MYOD, MYOG, and MRF4). The allele distribution of MYH3 among pig populations worldwide indicated that the MYH3 Q allele is of Asian origin and likely predates domestication. In conclusion, we identified a functional regulatory sequence variant in porcine MYH3 that provides novel insights into the genetic basis of the regulation of myofiber type ratios and associated changes in IMF in pigs. The MYH3 variant can play an important role in improving pork quality in current breeding programs.

Modulatory Effect of Protein and Carotene Dietary Levels on Pig gut Microbiota

In this study we investigated the impact of dietary protein and carotene levels on microbial functions and composition during the last month of purebred fattening Duroc pigs. Fecal microbiota was characterized using 16S ribosomal RNA sequencing at two points of live, 165 (T1) and 195 (T2) days. From 70 to 165 days of age, 32 pigs were divided into two groups fed either a standard-protein (SP) or a low-protein (LP) diet. In the last month (165-195 days), all pigs received a LP diet, either carotene-enriched (CE) or not (NC). Significant differences were observed between T1 and T2 at Amplicon Sequences Variants (ASVs), phylum and genus levels. In T1 group, Prevotella, Faecalibacterium and Treponema were the genera most influenced by dietary protein, together with predicted functions related with the degradation of protein. In contrast, the CE diet did not impact the microbiome diversity, although 160 ASVs were differentially abundant between CE and NC groups at T2. Weak stability of enterotype clusters across time-points was observed as consequence of medium-term dietary interventions. Our results suggest that during the last month of fattening, dietary protein have a stronger effect than carotenes on the modulation of the compositional and functional structure of the pig microbiota.

Integrating genome-wide co-association and gene expression to identify putative regulators and predictors of feed efficiency in pigs

BACKGROUND

Feed efficiency (FE) has a major impact on the economic sustainability of pig production. We used a systems-based approach that integrates single nucleotide polymorphism (SNP) co-association and gene-expression data to identify candidate genes, biological pathways, and potential predictors of FE in a Duroc pig population.

RESULTS

We applied an association weight matrix (AWM) approach to analyse the results from genome-wide association studies (GWAS) for nine FE associated and production traits using 31K SNPs by defining residual feed intake (RFI) as the target phenotype. The resulting co-association network was formed by 829 SNPs. Additive effects of this SNP panel explained 61% of the phenotypic variance of RFI, and the resulting phenotype prediction accuracy estimated by cross-validation was 0.65 (vs. 0.20 using pedigree-based best linear unbiased prediction and 0.12 using the 31K SNPs). Sixty-eight transcription factor (TF) genes were identified in the co-association network; based on the lossless approach, the putative main regulators were COPS5, GTF2H5, RUNX1, HDAC4, ESR1, USP16, SMARCA2 and GTF2F2. Furthermore, gene expression data of the gluteus medius muscle was explored through differential expression and multivariate analyses. A list of candidate genes showing functional and/or structural associations with FE was elaborated based on results from both AWM and gene expression analyses, and included the aforementioned TF genes and other ones that have key roles in metabolism, e.g. ESRRG, RXRG, PPARGC1A, TCF7L2, LHX4, MAML2, NFATC3, NFKBIZ, TCEA1, CDCA7L, LZTFL1 or CBFB. The most enriched biological pathways in this list were associated with behaviour, immunity, nervous system, and neurotransmitters, including melatonin, glutamate receptor, and gustation pathways. Finally, an expression GWAS allowed identifying 269 SNPs associated with the candidate genes' expression (eSNPs). Addition of these eSNPs to the AWM panel of 829 SNPs did not improve the accuracy of genomic predictions.

CONCLUSIONS

Candidate genes that have a direct or indirect effect on FE-related traits belong to various biological processes that are mainly related to immunity, behaviour, energy metabolism, and the nervous system. The pituitary gland, hypothalamus and thyroid axis, and estrogen signalling play fundamental roles in the regulation of FE in pigs. The 829 selected SNPs explained 61% of the phenotypic variance of RFI, which constitutes a promising perspective for applying genetic selection on FE relying on molecular-based prediction.

About the existence of common determinants of gene expression in the porcine liver and skeletal muscle

BACKGROUND

The comparison of expression QTL (eQTL) maps obtained in different tissues is an essential step to understand how gene expression is genetically regulated in a context-dependent manner. In the current work, we have compared the transcriptomic and eQTL profiles of two porcine tissues (skeletal muscle and liver) which typically show highly divergent expression profiles, in 103 Duroc pigs genotyped with the Porcine SNP60 BeadChip (Illumina) and with available microarray-based measurements of hepatic and muscle mRNA levels. Since structural variation could have effects on gene expression, we have also investigated the co-localization of cis-eQTLs with copy number variant regions (CNVR) segregating in this Duroc population.

RESULTS

The analysis of differential expresssion revealed the existence of 1204 and 1490 probes that were overexpressed and underexpressed in the gluteus medius muscle when compared to liver, respectively (|fold-change| > 1.5, q-value < 0.05). By performing genome scans in 103 Duroc pigs with available expression and genotypic data, we identified 76 and 28 genome-wide significant cis-eQTLs regulating gene expression in the gluteus medius muscle and liver, respectively. Twelve of these cis-eQTLs were shared by both tissues (i.e. 42.8% of the cis-eQTLs identified in the liver were replicated in the gluteus medius muscle). These results are consistent with previous studies performed in humans, where 50% of eQTLs were shared across tissues. Moreover, we have identified 41 CNVRs in a set of 350 pigs from the same Duroc population, which had been genotyped with the Porcine SNP60 BeadChip by using the PennCNV and GADA softwares, but only a small proportion of these CNVRs co-localized with the cis-eQTL signals.

CONCLUSION

Despite the fact that there are considerable differences in the gene expression patterns of the porcine liver and skeletal muscle, we have identified a substantial proportion of common cis-eQTLs regulating gene expression in both tissues. Several of these cis-eQTLs influence the mRNA levels of genes with important roles in meat (CTSF) and carcass quality (TAPT1), lipid metabolism (TMEM97) and obesity (MARC2), thus evidencing the practical importance of dissecting the genetic mechanisms involved in their expression.

Genetic diversity and selection signatures of the beef 'Charolais de Cuba' breed

In this study, we used BovineSNP50 Genotyping BeadChip data to estimate the structure, putative ancestral origin as well as to identify regions with selective sweeps that may have had an important role in the adaptation to tropical conditions of the 'Charolais de Cuba' (CHCU) breed. According to a principal component analysis, CHCU samples cluster together with taurine breeds with an estimated 93% of taurus ancestral alleles. Despite the short period since importation, we detected differentiation (Fst = 0.049) between the French Charolaise (CHA) and CHCU. However, CHA breed was the closest breed to CHCU followed by other hybrids breed with a clear CHA origin. Linkage disequilibrium (r²) decay tends to be lower in CHCU compared to CHA probably due to a less intense artificial selection programs of CHCU. Signals of recent adaptation to tropical conditions between CHCU and CHA were identified. Genes mapping within those regions reflect different functions related to immunity, metabolic changes and heat tolerance (CHCU) and muscle development and meat quality (CHA) that may have had an important role in the phenotypic differentiation of these breeds. Further studies will expand our knowledge on the molecular basis of adaptation of cattle to tropical conditions and molecular process associated with meat quality traits.

A system-based analysis of the genetic determinism of udder conformation and health phenotypes across three French dairy cattle breeds

Using GWAS to identify candidate genes associated with cattle morphology traits at a functional level is challenging. The main difficulty of identifying candidate genes and gene interactions associated with such complex traits is the long-range linkage disequilibrium (LD) phenomenon reported widely in dairy cattle. Systems biology approaches, such as combining the Association Weight Matrix (AWM) with a Partial Correlation in an Information Theory (PCIT) algorithm, can assist in overcoming this LD. Used in a multi-breed and multi-phenotype context, the AWM-PCIT could aid in identifying udder traits candidate genes and gene networks with regulatory and functional significance. This study aims to use the AWM-PCIT algorithm as a post-GWAS analysis tool with the goal of identifying candidate genes underlying udder morphology. We used data from 78,440 dairy cows from three breeds and with own phenotypes for five udder morphology traits, five production traits, somatic cell score and clinical mastitis. Cows were genotyped with medium (50k) or low-density (7 to 10k) chips and imputed to 50k. We performed a within breed and trait GWAS. The GWAS showed 9,830 significant SNP across the genome (p < 0.05). Five thousand and ten SNP did not map a gene, and 4,820 SNP were within 10-kb of a gene. After accounting for 1SNP:1gene, 3,651 SNP were within 10-kb of a gene (set1), and 2,673 significant SNP were further than 10-kb of a gene (set2). The two SNP sets formed 6,324 SNP matrix, which was fitted in an AWM-PCIT considering udder depth/ development as the key trait resulting in 1,013 genes associated with udder morphology, mastitis and production phenotypes. The AWM-PCIT detected ten potential candidate genes for udder related traits: ESR1, FGF2, FGFR2, GLI2, IQGAP3, PGR, PRLR, RREB1, BTRC, and TGFBR2.

Deciphering the genetic regulation of peripheral blood transcriptome in pigs through expression genome-wide association study and allele-specific expression analysis

BACKGROUND

Efforts to improve sustainability in livestock production systems have focused on two objectives: investigating the genetic control of immune function as it pertains to robustness and disease resistance, and finding predictive markers for use in breeding programs. In this context, the peripheral blood transcriptome represents an important source of biological information about an individual's health and immunological status, and has been proposed for use as an intermediate phenotype to measure immune capacity. The objective of this work was to study the genetic architecture of variation in gene expression in the blood of healthy young pigs using two approaches: an expression genome-wide association study (eGWAS) and allele-specific expression (ASE) analysis.

RESULTS

The blood transcriptomes of 60-day-old Large White pigs were analyzed by expression microarrays for eGWAS (242 animals) and by RNA-Seq for ASE analysis (38 animals). Using eGWAS, the expression levels of 1901 genes were found to be associated with expression quantitative trait loci (eQTLs). We recovered 2839 local and 1752 distant associations (Single Nucleotide Polymorphism or SNP located less or more than 1 Mb from expression probe, respectively). ASE analyses confirmed the extensive cis-regulation of gene transcription in blood, and revealed allelic imbalance in 2286 SNPs, which affected 763 genes. eQTLs and ASE-genes were widely distributed on all chromosomes. By analyzing mutually overlapping eGWAS results, we were able to describe putative regulatory networks, which were further refined using ASE data. At the functional level, genes with genetically controlled expression that were detected by eGWAS and/or ASE analyses were significantly enriched in biological processes related to RNA processing and immune function. Indeed, numerous distant and local regulatory relationships were detected within the major histocompatibility complex region on chromosome 7, revealing ASE for most class I and II genes.

CONCLUSIONS

This study represents, to the best of our knowledge, the first genome-wide map of the genetic control of gene expression in porcine peripheral blood. These results represent an interesting resource for the identification of genetic markers and blood biomarkers associated with variations in immunity traits in pigs, as well as any other complex traits for which blood is an appropriate surrogate tissue.

Integration of liver gene co-expression networks and eGWAs analyses highlighted candidate regulators implicated in lipid metabolism in pigs

In the present study, liver co-expression networks and expression Genome Wide Association Study (eGWAS) were performed to identify DNA variants and molecular pathways implicated in the functional regulatory mechanisms of meat quality traits in pigs. With this purpose, the liver mRNA expression of 44 candidates genes related with lipid metabolism was analysed in 111 Iberian x Landrace backcross animals. The eGWAS identified 92 eSNPs located in seven chromosomal regions and associated with eight genes: CROT, CYP2U1, DGAT1, EGF, FABP1, FABP5, PLA2G12A, and PPARA. Remarkably, cis-eSNPs associated with FABP1 gene expression which may be determining the C18:2(n-6)/C18:3(n-3) ratio in backfat through the multiple interaction of DNA variants and genes were identified. Furthermore, a hotspot on SSC8 associated with the gene expression of eight genes was identified and the TBCK gene was pointed out as candidate gene regulating it. Our results also suggested that the PI3K-Akt-mTOR pathway plays an important role in the control of the analysed genes highlighting nuclear receptors as the NR3C1 or PPARA. Finally, sex-dimorphism associated with hepatic lipid metabolism was identified with over-representation of female-biased genes. These results increase our knowledge of the genetic architecture underlying fat composition traits.

Understanding the response to endurance exercise using a systems biology approach: combining blood metabolomics, transcriptomics and miRNomics in horses

Background

Endurance exercise in horses requires adaptive processes involving physiological, biochemical, and cognitive-behavioral responses in an attempt to regain homeostasis. We hypothesized that the identification of the relationships between blood metabolome, transcriptome, and miRNome during endurance exercise in horses could provide significant insights into the molecular response to endurance exercise.

For this reason, the serum metabolome and whole-blood transcriptome and miRNome data were obtained from ten horses before and after a 160 km endurance competition.

Results

We obtained a global regulatory network based on 11 unique metabolites, 263 metabolic genes and 5 miRNAs whose expression was significantly altered at T1 (post- endurance competition) relative to T0 (baseline, pre-endurance competition). This network provided new insights into the cross talk between the distinct molecular pathways (e.g. energy and oxygen sensing, oxidative stress, and inflammation) that were not detectable when analyzing single metabolites or transcripts alone. Single metabolites and transcripts were carrying out multiple roles and thus sharing several biochemical pathways.

Using a regulatory impact factor metric analysis, this regulatory network was further confirmed at the transcription factor and miRNA levels.

In an extended cohort of 31 independent animals, multiple factor analysis confirmed the strong associations between lactate, methylene derivatives, miR-21-5p, miR-16-5p, let-7 family and genes that coded proteins involved in metabolic reactions primarily related to energy, ubiquitin proteasome and lipopolysaccharide immune responses after the endurance competition. Multiple factor analysis also identified potential biomarkers at T0 for an increased likelihood for failure to finish an endurance competition.

Conclusions

To the best of our knowledge, the present study is the first to provide a comprehensive and integrated overview of the metabolome, transcriptome, and miRNome co-regulatory networks that may have a key role in regulating the metabolic and immune response to endurance exercise in horses.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3571-3) contains supplementary material, which is available to authorized users.

Multi-breed and multi-trait co-association analysis of meat tenderness and other meat quality traits in three French beef cattle breeds

Background

Studies to identify markers associated with beef tenderness have focused on Warner–Bratzler shear force (WBSF) but the interplay between the genes associated with WBSF has not been explored. We used the association weight matrix (AWM), a systems biology approach, to identify a set of interacting genes that are co-associated with tenderness and other meat quality traits, and shared across the Charolaise, Limousine and Blonde d’Aquitaine beef cattle breeds.

Results

Genome-wide association studies were performed using ~500K single nucleotide polymorphisms (SNPs) and 17 phenotypes measured on more than 1000 animals for each breed. First, this multi-trait approach was applied separately for each breed across 17 phenotypes and second, between- and across-breed comparisons at the AWM and functional levels were performed. Genetic heterogeneity was observed, and most of the variants that were associated with WBSF segregated within rather than across breeds. We identified 206 common candidate genes associated with WBSF across the three breeds. SNPs in these common genes explained between 28 and 30 % of the phenotypic variance for WBSF. A reduced number of common SNPs mapping to the 206 common genes were identified, suggesting that different mutations may target the same genes in a breed-specific manner. Therefore, it is likely that, depending on allele frequencies and linkage disequilibrium patterns, a SNP that is identified for one breed may not be informative for another unrelated breed. Well-known candidate genes affecting beef tenderness were identified. In addition, some of the 206 common genes are located within previously reported quantitative trait loci for WBSF in several cattle breeds. Moreover, the multi-breed co-association analysis detected new candidate genes, regulators and metabolic pathways that are likely involved in the determination of meat tenderness and other meat quality traits in beef cattle.

Conclusions

Our results suggest that systems biology approaches that explore associations of correlated traits increase statistical power to identify candidate genes beyond the one-dimensional approach. Further studies on the 206 common genes, their pathways, regulators and interactions will expand our knowledge on the molecular basis of meat tenderness and could lead to the discovery of functional mutations useful for genomic selection in a multi-breed beef cattle context.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-016-0216-y) contains supplementary material, which is available to authorized users.