**5. Conclusions**

This study applied a novel approach for metabolome-transcriptome data integration using the linear model unveiling potential gene-metabolite pairs a ffecting the biological processes related to FE in pigs. To the best of our knowledge, this is the first study to report the gene-metabolite interaction mechanisms that may determine nutrient partitioning and energy utilization and hence a ffect FE in pigs. The approach followed here provided many interesting genes and metabolites with significant *p*-values. While some of the metabolites and genes identified were known with their association for FE, others are novel and provide new avenues for further research. The unique metabolites were associated with valine-leucine-isoleucine biosynthesis/degradation and arginine-proline metabolism. The unique genes enriched for sphingolipid metabolism, valine-leucine-isoleucine degradation, alanine-aspartate-glutamate pathway (breed-specific), and cGMP-PKG signaling pathway (FE-specific). Further validation of genes, metabolites, and gene-metabolite interactions in a cohort with more animals with additional features such as alteration in dietary components, farm variations, and other environmental effects would help to establish a framework for future FE prediction using metabolomics biomarker profiles that could be practical to use in large populations other than genomic profiling. More data would also make it possible to model the complex relations in gene-metabolite profiles over time more accurately and will help to elucidate the regulatory mechanisms affecting the pathways underlying FE.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2218-1989/10/7/275/s1, Figure S1: The principal component analysis of metabolites and genes. A and B: PCA plot of genes and metabolites, respectively, in (1) Duroc and (2) Landrace; C and D: PCA plot of genes and metabolites, respectively, in high and low feed e fficient groups, Table S1: Pathways enriched by unique gene-metabolite pairs. Spreadsheet tabs are divided into (a) metabolite enrichment analysis results by Metaboanalyst; (b) list of the co-functional genes by GeneMania; (c) gene ontology pathways enriched by Gorilla; (d) KEGG pathways enriched by ClueGO.

**Author Contributions:** H.N.K. conceived and designed this "FeedOMICS" project, obtained funding as the main applicant. V.A.O.C. and H.N.K designed blood sampling experiments, phenotype data collection, metabolite profiling, and RNA-Seq experiments. P.B. carried out biostatistical and bioinformatic data analysis and wrote the manuscript. All authors collaborated in the interpretation of results, discussion, and write up of the manuscript. All authors have read, reviewed, and approved the final manuscript. All authors have read and agreed to the published version of the manuscript.

**Funding:** This study was funded by the Independent Research Fund Denmark (DFF)—Technology and Production (FTP) gran<sup>t</sup> (grant number: 4184-00268B).

**Acknowledgments:** This study was funded by the Independent Research Fund Denmark (DFF)—Technology and Production (FTP) gran<sup>t</sup> (grant number: 4184-00268B). V.A.O.C. received partial Ph.D. stipends from the University of Copenhagen and Technical University of Denmark. Authors thank Wellison Jarles Da Silva Diniz for helping in the interpretation of results. Authors thank SEGES—Pig Research Centre (VSP) Denmark for access to blood samples and phenotype datasets used in this study.

**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

**Consent for Publication:** The blood sampling and experiment were approved and carried out in accordance with the Ministry of Environment and Food of Denmark, Animal Experiments Inspectorate under the license number (tilladelsesnummer) 2016-15-0201-01123, and C-permit granted to the principal investigator/senior author (HK).

**Availability of Data and Material:** The metabolites dataset generated and analyzed during the current study is publicly available at the Metabolights database https://www.ebi.ac.uk/metabolights/MTBLS1384 with accession ID: MTBLS1384. (https://doi.org/10.1093/nar/gks1004; PubMed PMID: 2310955). The transcriptome dataset analyzed during the present study is also publicly available at the NCBI-GEO database with Accession ID GSE148889 and can be accessed at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE148889.
