Strategies towards Improved Feed Efficiency in Pigs Comprise Molecular Shifts in Hepatic Lipid and Carbohydrate Metabolism

African Local Pig Genetic Resources in the Context of Climate Change Adaptation

Africa is home to a wide diversity of locally adapted pig breeds whose genetic architecture offers important insights into livestock adaptation to climate change. However, the majority of these inherent traits have not been fully highlighted. This review presents an overview of the current state of African pig genetic resources, providing highlights on their population and production statistics, production system, population diversity indices, and genomic evidence underlying their evolutionary potential. The study results reveal an incomplete characterization of local pig genotypes across the continent. The characterized population, however, demonstrates moderate to high levels of genetic diversity, enough to support breeding and conservation programs. Owing to low genetic differentiation and limited evidence of distinct population structures, it appears that most local pig populations are strains within larger breeds. Genomic evidence has shown a higher number of selection signatures associated with various economically important traits, thus making them potential candidates for climate change adaptation. The reportedly early evidence of hybridization with wild suid groups further suggests untapped insights into disease resistance and resilience traits that need to be illuminated using higher-density markers. Nevertheless, gene introgression from commercial breeds is prevalent across Africa; thus, efforts to realize and utilize these traits must increase before they are permanently depleted.

Liver transcriptome analysis reveal the metabolic and apoptotic responses of Trachinotus ovatus under acute cold stress

Trachinotus ovatus is an economically important fish and has been recommended as a high-quality aquaculture fish breed for the high-quality development of sea ranches in the South China Sea. However, T. ovatus shows intolerance to low temperature, greatly limiting the extension of farming scale, reducing production efficiency in winter, and increasing farming risks. In this study, liver transcriptome analysis was investigated in T. ovatus under acute low temperature conditions (20 and 15 °C) using RNA sequencing (RNA-Seq) technology. Inter-groups differential expression analysis and trend analysis screened 1219 DEGs and four significant profiles (profiles 0, 3, 4, and 7), respectively. GO enrichment analysis showed that these DEGs were mainly related to metabolic process and cell growth and death process. KEGG enrichment analysis found that DEGs were mainly associated with lipid metabolism, carbohydrate metabolism, and cell growth and death, such as gluconeogenesis, glycolysis, fatty acid oxidation, cholesterol biosynthesis, p53 signaling pathway, cell cycle arrest, and apoptotic cell death. Moreover, protein-protein interaction networks identified two hub genes (FOS and JUNB) and some important genes related to metabolic process and cell growth and death process, that corresponding to enrichment analysis. Overall, gluconeogenesis, lipid mobilization, and fatty acid oxidation in metabolic process and cell cycle arrest and apoptotic cell death in cell growth and death process were enhanced, while glycolysis, liver glycogen synthesis and cholesterol biosynthesis in metabolic process were inhibited. The enhancement or attenuatment of metabolic process and cell growth and death process is conducive to maintain energy balance, normal fluidity of cell membrane, normal physiological functions of liver cell, enhancing the tolerance of T. ovatus to cold stress. These results suggested that metabolic process and cell growth and death process play important roles in response to acute cold stress in the liver of T. ovatus. Gene expreesion level analysis showed that acute cold stress at 15 °C was identified as a critical temperature point for T. ovatus in term of cellular metabolism alteration and apoptosis inducement, and rewarming intervention should be timely implemented above 15 °C. Our study can provide theoretical support for breeding cold-tolerant cultivars of T. ovatus, which is contributed to high-quality productions fish production.

A genome-wide association study for loin depth and muscle pH in pigs from intensely selected purebred lines

BACKGROUND

Genome-wide association studies (GWAS) aim at identifying genomic regions involved in phenotype expression, but identifying causative variants is difficult. Pig Combined Annotation Dependent Depletion (pCADD) scores provide a measure of the predicted consequences of genetic variants. Incorporating pCADD into the GWAS pipeline may help their identification. Our objective was to identify genomic regions associated with loin depth and muscle pH, and identify regions of interest for fine-mapping and further experimental work. Genotypes for ~ 40,000 single nucleotide morphisms (SNPs) were used to perform GWAS for these two traits, using de-regressed breeding values (dEBV) for 329,964 pigs from four commercial lines. Imputed sequence data was used to identify SNPs in strong ([Formula: see text] 0.80) linkage disequilibrium with lead GWAS SNPs with the highest pCADD scores.

RESULTS

Fifteen distinct regions were associated with loin depth and one with loin pH at genome-wide significance. Regions on chromosomes 1, 2, 5, 7, and 16, explained between 0.06 and 3.55% of the additive genetic variance and were strongly associated with loin depth. Only a small part of the additive genetic variance in muscle pH was attributed to SNPs. The results of our pCADD analysis suggests that high-scoring pCADD variants are enriched for missense mutations. Two close but distinct regions on SSC1 were associated with loin depth, and pCADD identified the previously identified missense variant within the MC4R gene for one of the lines. For loin pH, pCADD identified a synonymous variant in the RNF25 gene (SSC15) as the most likely candidate for the muscle pH association. The missense mutation in the PRKAG3 gene known to affect glycogen content was not prioritised by pCADD for loin pH.

CONCLUSIONS

For loin depth, we identified several strong candidate regions for further statistical fine-mapping that are supported in the literature, and two novel regions. For loin muscle pH, we identified one previously identified associated region. We found mixed evidence for the utility of pCADD as an extension of heuristic fine-mapping. The next step is to perform more sophisticated fine-mapping and expression quantitative trait loci (eQTL) analysis, and then interrogate candidate variants in vitro by perturbation-CRISPR assays.

Transcription Analysis of Liver and Muscle Tissues from Landrace Finishing Pigs with Different Feed Conversion Ratios

The efficiency of feed utilization determines the cost and economic benefits of pig production. In the present study, two pairs of full-sibling and two pairs of half-sibling female Landrace finishing pigs were selected, with each pair including individuals with different feed conversion rates, with liver and longissimus muscle tissue samples collected from each group for transcriptome analysis. A total of 561 differentially expressed genes (DEGs), among which 224 were up-regulated and 337 were down-regulated, were detected in the liver transcriptomes in the high-feed efficiency group compared to the low-feed efficiency group. The DEGs related to phosphorus and phosphate metabolism, arginine biosynthesis, chemical carcinogenesis, cytokine-cytokine receptor interaction, the biosynthesis of amino acids, and drug metabolism-cytochrome P450 in liver tissue were also associated with feed efficiency. In total, 215 DEGs were screened in the longissimus muscle tissue and were mainly related to disease and immune regulation, including complement and coagulation cascades, systemic lupus erythematosus, and prion diseases. The combination of gene expression and functional annotation results led to the identification of candidate feed efficiency-related biomarkers, such as ARG1, ARG2, GOT1, GPT2, ACAA2, ACADM, and ANGPTL4, members of cytochrome P450 family, and complement component family genes. Although the novel feed efficiency-related candidate genes need to be further evaluated by a larger sample size and functional studies, the present study identifies novel candidate biomarkers for the identification of functional SNPs underlying porcine feed efficiency.

Meta-analysis across Nellore cattle populations identifies common metabolic mechanisms that regulate feed efficiency-related traits

Background

Feed efficiency (FE) related traits play a key role in the economy and sustainability of beef cattle production systems. The accurate knowledge of the physiologic background for FE-related traits can help the development of more efficient selection strategies for them. Hence, multi-trait weighted GWAS (MTwGWAS) and meta-analyze were used to find genomic regions associated with average daily gain (ADG), dry matter intake (DMI), feed conversion ratio (FCR), feed efficiency (FE), and residual feed intake (RFI). The FE-related traits and genomic information belong to two breeding programs that perform the FE test at different ages: post-weaning (1,024 animals IZ population) and post-yearling (918 animals for the QLT population).

Results

The meta-analyze MTwGWAS identified 14 genomic regions (-log10(p -value) > 5) regions mapped on BTA 1, 2, 3, 4, 7, 8, 11, 14, 15, 18, 21, and 29. These regions explained a large proportion of the total genetic variance for FE-related traits across-population ranging from 20% (FCR) to 36% (DMI) in the IZ population and from 22% (RFI) to 28% (ADG) in the QLT population. Relevant candidate genes within these regions (LIPE, LPL, IGF1R, IGF1, IGFBP5, IGF2, INS, INSR, LEPR, LEPROT, POMC, NPY, AGRP, TGFB1, GHSR, JAK1, LYN, MOS, PLAG1, CHCD7, LCAT, and PLA2G15) highlighted that the physiological mechanisms related to neuropeptides and the metabolic signals controlling the body's energy balance are responsible for leading to greater feed efficiency. Integrated meta-analysis results and functional pathway enrichment analysis highlighted the major effect of biological functions linked to energy, lipid metabolism, and hormone signaling that mediates the effects of peptide signals in the hypothalamus and whole-body energy homeostasis affecting the genetic control of FE-related traits in Nellore cattle.

Conclusions

Genes and pathways associated with common signals for feed efficiency-related traits provide better knowledge about regions with biological relevance in physiological mechanisms associated with differences in energy metabolism and hypothalamus signaling. These pleiotropic regions would support the selection for feed efficiency-related traits, incorporating and pondering causal variations assigning prior weights in genomic selection approaches.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08671-w.

Transcriptome analysis reveals the potential roles of long non-coding RNAs in feed efficiency of chicken

Feed efficiency is an important economic trait and reduces the production costs per unit of animal product. Up to now, few studies have conducted transcriptome profiling of liver tissue in feed efficiency-divergent chickens (Ross vs native breeds). Also, molecular mechanisms contributing to differences in feed efficiency are not fully understood, especially in terms of long non-coding RNAs (lncRNAs). Hence, transcriptome profiles of liver tissue in commercial and native chicken breeds were analyzed. RNA-Seq data along with bioinformatics approaches were applied and a series of lncRNAs and target genes were identified. Furthermore, protein-protein interaction network construction, co-expression analysis, co-localization analysis of QTLs and functional enrichment analysis were used to functionally annotate the identified lncRNAs. In total, 2,290 lncRNAs were found (including 1,110 annotated, 593 known and 587 novel), of which 53 (including 39 known and 14 novel), were identified as differentially expressed genes between two breeds. The expression profile of lncRNAs was validated by RT-qPCR. The identified novel lncRNAs showed a number of characteristics similar to those of known lncRNAs. Target prediction analysis showed that these lncRNAs have the potential to act in cis or trans mode. Functional enrichment analysis of the predicted target genes revealed that they might affect the differences in feed efficiency of chicken by modulating genes associated with lipid metabolism, carbohydrate metabolism, growth, energy homeostasis and glucose metabolism. Some gene members of significant modules in the constructed co-expression networks were reported as important genes related to feed efficiency. Co-localization analysis of QTLs related to feed efficiency and the identified lncRNAs suggested several candidates to be involved in residual feed intake. The findings of this study provided valuable resources to further clarify the genetic basis of regulation of feed efficiency in chicken from the perspective of lncRNAs.

A Transcriptome Analysis Reveals that Hepatic Glycolysis and Lipid Synthesis Are Negatively Associated with Feed Efficiency in DLY Pigs

Feed efficiency (FE) is an important trait in the porcine industry. Therefore, understanding the molecular mechanisms of FE is vital for the improvement of this trait. In this study, 6 extreme high-FE and 6 low-FE pigs were selected from 225 Duroc × (Landrace × Yorkshire) (DLY) pigs for transcriptomic analysis. RNA-seq analysis was performed to determine differentially expressed genes (DEGs) in the liver tissues of the 12 individuals, and 507 DEGs were identified between high-FE pigs (HE- group) and low-FE pigs (LE- group). A gene ontology (GO) enrichment and pathway enrichment analysis were performed and revealed that glycolytic metabolism and lipid synthesis-related pathways were significantly enriched within DEGs; all of these DEGs were downregulated in the HE- group. Moreover, Weighted gene co-expression analysis (WGCNA) revealed that oxidative phosphorylation, thermogenesis, and energy metabolism-related pathways were negatively related to HE- group, which might result in lower energy consumption in higher efficiency pigs. These results implied that the higher FE in the HE- group may be attributed to a lower glycolytic, energy consumption and lipid synthesizing potential in the liver. Furthermore, our findings suggested that the inhibition of lipid synthesis and glucose metabolic activity in the liver may be strategies for improving the FE of DLY pigs.

Genome Wide Assessment of Genetic Variation and Population Distinctiveness of the Pig Family in South Africa

Genetic diversity is of great importance and a prerequisite for genetic improvement and conservation programs in pigs and other livestock populations. The present study provides a genome wide analysis of the genetic variability and population structure of pig populations from different production systems in South Africa relative to global populations. A total of 234 pigs sampled in South Africa and consisting of village (n = 91), commercial (n = 60), indigenous (n = 40), Asian (n = 5) and wild (n = 38) populations were genotyped using Porcine SNP60K BeadChip. In addition, 389 genotypes representing village and commercial pigs from America, Europe, and Asia were accessed from a previous study and used to compare population clustering and relationships of South African pigs with global populations. Moderate heterozygosity levels, ranging from 0.204 for Warthogs to 0.371 for village pigs sampled from Capricorn municipality in Eastern Cape province of South Africa were observed. Principal Component Analysis of the South African pigs resulted in four distinct clusters of (i) Duroc; (ii) Vietnamese; (iii) Bush pig and Warthog and (iv) a cluster with the rest of the commercial (SA Large White and Landrace), village, Wild Boar and indigenous breeds of Koelbroek and Windsnyer. The clustering demonstrated alignment with genetic similarities, geographic location and production systems. The PCA with the global populations also resulted in four clusters that where populated with (i) all the village populations, wild boars, SA indigenous and the large white and landraces; (ii) Durocs (iii) Chinese and Vietnamese pigs and (iv) Warthog and Bush pig. K = 10 (The number of population units) was the most probable ADMIXTURE based clustering, which grouped animals according to their populations with the exception of the village pigs that showed presence of admixture. AMOVA reported 19.92%-98.62% of the genetic variation to be within populations. Sub structuring was observed between South African commercial populations as well as between Indigenous and commercial breeds. Population pairwise F ST analysis showed genetic differentiation (P ≤ 0.05) between the village, commercial and wild populations. A per marker per population pairwise F ST analysis revealed SNPs associated with QTLs for traits such as meat quality, cytoskeletal and muscle development, glucose metabolism processes and growth factors between both domestic populations as well as between wild and domestic breeds. Overall, the study provided a baseline understanding of porcine diversity and an important foundation for porcine genomics of South African populations.

Genome-Wide Epistatic Interaction Networks Affecting Feed Efficiency in Duroc and Landrace Pigs

Interactions among genomic loci have often been overlooked in genome-wide association studies, revealing the combinatorial effects of variants on phenotype or disease manifestation. Unexplained genetic variance, interactions among causal genes of small effects, and biological pathways could be identified using a network biology approach. The main objective of this study was to determine the genome-wide epistatic variants affecting feed efficiency traits [feed conversion ratio (FCR) and residual feed intake (RFI)] based on weighted interaction SNP hub (WISH-R) method. Herein, we detected highly interconnected epistatic SNP modules, pathways, and potential biomarkers for the FCR and RFI in Duroc and Landrace purebreds considering the whole population, and separately for low and high feed efficient groups. Highly interacting SNP modules in Duroc (1,247 SNPs) and Landrace (1,215 SNPs) across the population and for low feed efficient (Duroc-80 SNPs, Landrace-146 SNPs) and high feed efficient group (Duroc-198 SNPs, Landrace-232 SNPs) for FCR and RFI were identified. Gene and pathway analyses identified ABL1, MAP3K4, MAP3K5, SEMA6A, KITLG, and KAT2B from chromosomes 1, 2, 5, and 13 underlying ErbB, Ras, Rap1, thyroid hormone, axon guidance pathways in Duroc. GABBR2, GNA12, and PRKCG genes from chromosomes 1, 3, and 6 pointed towards thyroid hormone, cGMP-PKG and cAMP pathways in Landrace. From Duroc low feed efficient group, the TPK1 gene was found involved with thiamine metabolism, whereas PARD6G, DLG2, CRB1 were involved with the hippo signaling pathway in high feed efficient group. PLOD1 and SETD7 genes were involved with lysine degradation in low feed efficient group in Landrace, while high feed efficient group pointed to genes underpinning valine, leucine, isoleucine degradation, and fatty acid elongation. Some SNPs and genes identified are known for their association with feed efficiency, others are novel and potentially provide new avenues for further research. Further validation of epistatic SNPs and genes identified here in a larger cohort would help to establish a framework for modelling epistatic variance in future methods of genomic prediction, increasing the accuracy of estimated genetic merit for FE and helping the pig breeding industry.

Metabolomic networks and pathways associated with feed efficiency and related-traits in Duroc and Landrace pigs

Improving feed efficiency (FE) is a major goal of pig breeding, reducing production costs and providing sustainability to the pig industry. Reliable predictors for FE could assist pig producers. We carried out untargeted blood metabolite profiling in uncastrated males from Danbred Duroc (n = 59) and Danbred Landrace (n = 50) pigs at the beginning and end of a FE testing phase to identify biomarkers and biological processes underlying FE and related traits. By applying linear modeling and clustering analyses coupled with WGCNA framework, we identified 102 and 73 relevant metabolites in Duroc and Landrace based on two sampling time points. Among them, choline and pyridoxamine were hub metabolites in Duroc in early testing phase, while, acetoacetate, cholesterol sulfate, xanthine, and deoxyuridine were identified in the end of testing. In Landrace, cholesterol sulfate, thiamine, L-methionine, chenodeoxycholate were identified at early testing phase, while, D-glutamate, pyridoxamine, deoxycytidine, and L-2-aminoadipate were found at the end of testing. Validation of these results in larger populations could establish FE prediction using metabolomics biomarkers. We conclude that it is possible to identify a link between blood metabolite profiles and FE. These results could lead to improved nutrient utilization, reduced production costs, and increased FE.

Effect of divergence in residual feed intake on expression of lipid metabolism-related genes in the liver of meat-type ducks1

Lipid metabolism is considered one of the important factors affecting residual feed intake (RFI). However, the relationship between RFI and expression of lipid metabolism-related genes is unknown in meat-type ducks. To address this issue, a total of 1,000 male meat-type ducks with similar body weight were randomly selected to measure body weight gain and feed intake from 21 to 42 d of age to estimate RFI. The 8 greatest- (high RFI [HRFI]) and lowest- (low RFI [LRFI]) ranking birds were then selected for the present study. Relative expressions of key genes, namely sirtuin 1 (Sirt1), forkhead box O1 (Foxo1), peroxisome proliferator-activated receptor gamma (PPARγ), sterol regulatory element-binding transcription factor 1c (SREBP-1c), fas cell surface death receptor (FAS), acetyl-CoA carboxylase alpha (ACC), carnitine palmitoyltransferase 1A (CPT1A), and acyl-CoA oxidase 1 (ACOX1), were then determined in the HRFI and LRFI ducks by quantitative PCR. The results showed that RFI, feed conversion ratio (FCR), and average daily feed intake (ADFI) were significantly lower (P < 0.05) in LRFI ducks than in HRFI ducks. In addition, expression of Sirt1, Foxo1, CPT1A, and ACOX1 were significantly higher in LRFI ducks than in HRFI ducks (P < 0.05), whereas PPARγ and FAS expression levels were significantly lower in LRFI ducks than in HRFI ducks (P < 0.01). Correlation analysis showed that Sirt1, CPT1A, and ACOX1 expressions were significantly negatively correlated with FCR (r = -0.81 to -0.93; P < 0.01), whereas PPARγ and FAS expressions were significantly positively correlated with FCR (r = 0.74 to 0.87; P < 0.01). PPARγ expression was significantly positively correlated with RFI (r = 0.83; P < 0.01), whereas CPT1A and ACOX1 expressions were significantly negatively correlated with RFI (r = -0.84 to -0.89; P < 0.01). Sirt1 mRNA expression was positively correlated with Foxo1, CPT1A, and ACOX1 mRNA expression (r = 0.78 to 0.92; P < 0.01). Association of Foxo1 with CPT1A and ACOX1 was positive (r = 0.88 to 0.96; P < 0.01). These results suggest that genes related to fatty acid oxidation are upregulated in the liver of ducks with high feed efficiency, while genes associated with lipid synthesis are downregulated. Furthermore, the inclusion of lipid metabolism-related genes in future breeding programs might be beneficial for selecting ducks with greater feed efficiency phenotype.

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.

Expression of genes related to lipid transport in meat-type ducks divergent for low or high residual feed intake

Objective

This study examined the effects of divergence in residual feed intake (RFI) on expression profiles of key genes related to lipid transport in the liver and duodenal epithelium and their associations with feed efficiency traits in meat-type ducks.

Methods

A total of 1,000 male ducks with similar body weight (1,042.1±87.2 g) were used in this study, and their individual RFI was calculated from 21 to 42 d of age. Finally, the 10 highest RFI (HRFI) and 10 lowest RFI (LRFI) ducks were chosen for examining the expression of key genes related to lipid transport in the liver and duodenal epithelium using quantitative polymerase chain reaction.

Results

In the liver, expression levels of albumin (ALB), CD36 molecule (CD36), fatty acid hydroxylase domain containing 2 (FAXDC2), and choline kinase alpha (CHKA) were significantly higher in LRFI ducks than in HRFI ducks (p<0.01); negative correlations (p<0.05) between expression levels of ALB, CD36, FAXDC2, and CHKA and RFI were detected in the liver. Additionally, ALB expression was strongly positively correlated (p<0.05) with CD36, FAXDC2, CHKA, and apolipoprotein H (APOH) expression in the liver. In duodenal epithelium, we found that mRNA levels of ALB, CD36, FAXDC2, and APOH were significantly higher in LRFI ducks than in HRFI ducks (p<0.01); RFI was strongly negatively correlated (p<0.05) with ALB, FAXDC2, and APOH expression, while ALB expression was strongly positively correlated with APOH expression (p<0.01) in duodenal epithelium. Furthermore, expression levels of both ALB and FAXDC2 genes were significantly associated with feed conversion ratio and RFI in both liver and duodenal epithelium (p<0.05).

Conclusion

Our findings therefore suggest that ALB and FAXDC2 genes might be used as potential gene markers designed to improve feed efficiency in future meat-type duck breeding programs.

Investigation of muscle transcriptomes using gradient boosting machine learning identifies molecular predictors of feed efficiency in growing pigs

Background

Improving feed efficiency (FE) is a major challenge in pig production. This complex trait is characterized by a high variability. Therefore, the identification of predictors of FE may be a relevant strategy to reduce phenotyping efforts in breeding and selection programs. The aim of this study was to investigate the suitability of expressed muscle genes in prediction of FE traits in growing pigs. The approach considered different transcriptomics experiments to cover a large range of FE values and identify reliable predictors.

Results

Microarrays data were obtained from longissimus muscles of two lines divergently selected for residual feed intake (RFI). Pigs (n = 71) from three experiments belonged to generations 6 to 8 of selection, were fed either a diet with a standard composition or a diet rich in fiber and lipids, received feed ad libitum or at restricted level, and weighed between 80 and 115 kg at slaughter. For each pig, breeding value for RFI was estimated (RFI-BV), and feed conversion ratio (FCR) and energy-based feed conversion ratio (FCRe) were calculated during the test periods. Gradient boosting algorithms were used on the merged muscle transcriptomes to identify very important predictors of FE traits. About 20,405 annotated molecular probes were commonly expressed in longissimus muscle across experiments. Six to 267 expressed muscle genes covering a variety of biological processes were found as important predictors for RFI-BV (R² = 0.63–0.65), FCR (R² = 0.61–0.70) and FCRe (R² = 0.49–0.52). The error of prediction was less than 8% for FCR. Altogether, 56 predictors were common to RFI-BV and FCR. Expression levels of 24 target genes were further measured by qPCR. Linear regression confirmed the good accuracy of combining mRNA levels of these genes to fit FE traits (RFI-BV: R² = 0.73, FRC: R² = 0.76; FCRe: R² = 0.75). Stepwise regression procedure highlighted 10 genes (FKBP5, MUM1, AKAP12, FYN, TMED3, PHKB, TGF, SOCS6, ILR4, and FRAS1) in a linear combination predicting FCR and FCRe. In addition, FKBP5 and expression levels of five other genes (IGF2, SERINC3, CSRNP3, EZR and RPL16) significantly contributed to RFI-BV.

Conclusion

It was possible to identify few genes expressed in muscle that might be reliable predictors of feed efficiency.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-6010-9) contains supplementary material, which is available to authorized users.

Porcine Feed Efficiency-Associated Intestinal Microbiota and Physiological Traits: Finding Consistent Cross-Locational Biomarkers for Residual Feed Intake

Optimal feed efficiency (FE) in pigs is important for economic and environmental reasons. Previous research identified FE-associated bacterial taxa within the intestinal microbiota of growing pigs. This study investigated whether FE-associated bacteria and selected FE-associated physiological traits were consistent across geographic locations (Republic of Ireland [ROI] [two batches of pigs, ROI1 and ROI2], Northern Ireland [NI], and Austria [AT]), where differences in genetic, dietary, and management factors were minimized. Pigs (n = 369) were ranked, within litter, on divergence in residual feed intake (RFI), and 100 extremes were selected (50 with high RFI and 50 with low RFI) across geographic locations for intestinal microbiota analysis using 16S rRNA amplicon sequencing and examination of FE-associated physiological parameters. Microbial diversity varied by geographic location and intestinal sampling site but not by RFI rank, except in ROI2, where more-feed-efficient pigs had greater ileal and cecal diversity. Although none of the 188 RFI-associated taxonomic differences found were common to all locations/batches, Lentisphaerae, Ruminococcaceae, RF16, Mucispirillum, Methanobrevibacter, and two uncultured genera were more abundant within the fecal or cecal microbiota of low-RFI pigs in two geographic locations and/or in both ROI batches. These are major contributors to carbohydrate metabolism, which was reflected in functional predictions. Fecal volatile fatty acids and salivary cortisol were the only physiological parameters that differed between RFI ranks. Despite controlling genetics, diet specification, dietary phases, and management practices in each rearing environment, the rearing environment, encompassing maternal influence, herd health status, as well as other factors, appears to impact intestinal microbiota more than FE.IMPORTANCE Interest in the role of intestinal microbiota in determining FE in pigs has increased in recent years. However, it is not known if the same FE-associated bacteria are found across different rearing environments. In this study, geographic location and intestinal sampling site had a greater influence on the pig gut microbiome than FE. This presents challenges when aiming to identify consistent reliable microbial biomarkers for FE. Nonetheless, seven FE-associated microbial taxa were common across two geographic locations and/or two batches within one location, and these indicated a potentially "healthier" and metabolically more capable microbiota in more-feed-efficient pigs. These taxa could potentially be employed as biomarkers for FE, although bacterial consortia, rather than individual taxa, may be more likely to predict FE. They may also merit consideration for use as probiotics or could be targeted by dietary means as a strategy for improving FE in pigs in the future.

A comparative analysis of the transcriptome profiles of liver and muscle tissue in pigs divergent for feed efficiency

BACKGROUND

The improvement of feed efficiency is a key economic goal within the pig production industry. The objective of this study was to examine transcriptomic differences in both the liver and muscle of pigs divergent for feed efficiency, thus improving our understanding of the molecular mechanisms influencing feed efficiency and enabling the identification of candidate biomarkers. Residual feed intake (RFI) was calculated for two populations of pigs from two different farms of origin/genotype. The 6 most efficient (LRFI) and 6 least efficient (HRFI) animals from each population were selected for further analysis of Longissimus Dorsi muscle (n = 22) and liver (n = 23). Transcriptomic data were generated from liver and muscle collected post-slaughter.

RESULTS

The transcriptomic data segregated based on the RFI value of the pig rather than genotype/farm of origin. A total of 6463 genes were identified as being differentially expressed (DE) in muscle, while 964 genes were identified as being DE in liver. Genes that were commonly DE between muscle and liver (n = 526) were used for the multi-tissue analysis. These 526 genes were associated with protein targeting to membrane, extracellular matrix organisation and immune function. In the muscle-only analysis, genes associated with RNA processing, protein synthesis and energy metabolism were down regulated in the LRFI animals while in the liver-only analysis, genes associated with cell signalling and lipid homeostasis were up regulated in the LRFI animals.

CONCLUSIONS

Differences in the transcriptome segregated on pig RFI value rather than the genotype/farm of origin. Multi-tissue analysis identified that genes associated with GO terms protein targeting to membrane, extracellular matrix organisation and a range of terms relating to immune function were over represented in the differentially expressed genes of both liver and muscle.

RNA-Seq of Liver From Pigs Divergent in Feed Efficiency Highlights Shifts in Macronutrient Metabolism, Hepatic Growth and Immune Response

Liver is a metabolically complex organ that influences nutrient partitioning and potentially modulates the efficiency of converting energy acquired from macronutrients ingestion into a muscle and/or adipose tissue (referred to as feed efficiency, FE). The objective of this study was to sequence the hepatic tissue transcriptome of closely related but differently feed efficient pigs (n = 16) and identify relevant biological processes that underpin the differences in liver phenotype between FE groups. Liver weight did not significantly differ between the FE groups, however, blood parameters showed that total protein, glucose, cholesterol and percentage of lymphocytes were significantly greater in high-FE pigs. Ontology analysis revealed carbohydrate, lipid and protein metabolism to be significantly enriched with differentially expressed genes. In particular, high-FE pigs exhibited gene expression patterns suggesting improved absorption of carbohydrates and cholesterol as well as enhanced reverse cholesterol transport. Furthermore, the inferred decrease in bile acid synthesis in high-FE pigs may contribute to the observed greater levels of serum glucose, which can be then delivered to cells and utilized for growth and maintenance. Gene ontology analysis also suggested that livers of more efficient pigs may be characterized by higher protein turnover and increased epithelial cell differentiation, whereby an enhanced quantity of invariant natural killer T-cells and viability of natural killer cells could induce a quicker and more effective hepatic response to inflammatory stimuli. Our findings suggest that this prompt hepatic response to inflammation in high-FE group may contribute to the more efficient utilization of nutrients for growth in these animals.

Transcriptome analysis of adipose tissue from pigs divergent in feed efficiency reveals alteration in gene networks related to adipose growth, lipid metabolism, extracellular matrix, and immune response

Adipose tissue is hypothesized to play a vital role in regulation of feed efficiency (FE; efficiency in converting energy and nutrients into tissue), of which improvement will simultaneously reduce environmental impact and feed cost per pig. The objective of the present study was to sequence the subcutaneous adipose tissue transcriptome in FE-divergent pigs (n = 16) and identify relevant biological processes underpinning observed differences in FE. We previously demonstrated that high-FE pigs were associated with lower fatness when compared to their counterparts. Here, ontology analysis of a total of 209 annotated genes that were differentially expressed at a p < 0.01 revealed establishment of a dense extracellular matrix and inhibition of capillary formation as one underlying mechanism to achieve suppressed adipogenesis. Moreover, mechanisms ensuring an efficient utilization of lipids in high-FE pigs might be orchestrated by upstream regulators including CEBPA and EGF. Consequently, high-FE adipose tissue could exhibit more efficient cholesterol disposal, whilst inhibition of inflammatory and immune response in high-FE pigs may be an indicator of an optimally functioning adipose tissue. Taken together, adipose tissue growth, extracellular matrix formation, lipid metabolism and inflammatory and immune response are key biological events underpinning the differences in FE. Further investigations focusing on elucidating these processes would assist the animal production industry in optimizing strategies related to nutrient utilization and product quality.

Feed-efficient pigs exhibit molecular patterns allowing a timely circulation of hormones and nutrients

Feed efficiency (FE) is a measure of the rate between feed intake and body weight gain and is subject to constant progress in pigs, based on extensive performance tests and analyses of physiological parameters. However, endocrine regulatory circuits that comprise the sensation and perception of intrinsic requirements and appropriate systemic responses have not yet been fully elucidated. It is hypothesized that the gut-brain axis, which is a network of hierarchical anterior regulatory tissues, contributes largely to variations in FE. Therefore, full-sib pigs with extreme residual feed intake values were assigned to experimental groups of high and low FE. Relevant hormones, minerals, and metabolites including fatty acid profiles were analyzed in serum to assess postprandial conditions. Transcriptome profiles were deduced from intestinal (duodenum, jejunum, ileum) and neuroendocrine tissues (hypothalamus). Serum analyses of feed-efficient animals showed an increased content of the incretin GIP, calcium, magnesium, β-hydroxybutyric acid, and fat compared with low-FE pigs. Complementary expression profiles in intestinal tissues indicate a modulated permeability and host-microbe interaction in FE-divergent pigs. Transcriptomic analyses of the hypothalamus showed that differences between the FE groups in appetite and satiety regulation are less pronounced. However, hypothalamic abundance of transcripts like ADCY7, LHCGR, and SLC2A7 and molecular signatures in local and systemic tissue sites indicate that increased allocation and circulation of energy equivalents, minerals, and hormones are promoted in feed-efficient animals. Overall, patterns of gastrointestinal hormones and gene expression profiles identified host-microbiota interaction, intestinal permeability, feed intake regulation, and energy expenditure as potential mechanisms affecting FE in pigs.

Integrative approach using liver and duodenum RNA-Seq data identifies candidate genes and pathways associated with feed efficiency in pigs

This study aims identifying candidate genes and pathways associated with feed efficiency (FE) in pigs. Liver and duodenum transcriptomes of 37 gilts showing high and low residual feed intake (RFI) were analysed by RNA-Seq. Gene expression data was explored through differential expression (DE) and weighted gene co-expression network analyses. DE analysis revealed 55 and 112 differentially regulated genes in liver and duodenum tissues, respectively. Clustering genes according to their connectivity resulted in 23 (liver) and 25 (duodenum) modules of genes with a co-expression pattern. Four modules, one in liver (with 444 co-expressed genes) and three in duodenum (gathering 37, 126 and 41 co-expressed genes), were significantly associated with FE indicators. Intra-module analyses revealed tissue-specific candidate genes; 12 of these genes were also identified as DE between individuals with high and low RFI. Pathways enriched by the list of genes showing DE and/or belonging to FE co-expressed modules included response to oxidative stress, inflammation, immune response, lipid metabolism and thermoregulation. Low overlapping between genes identified in duodenum and liver tissues was observed but heat shock proteins were associated to FE in both tissues. Our results suggest tissue-specific rather than common transcriptome regulatory processes associated with FE in pigs.