DOI: 10.5281/zenodo.14046073
title: Merging metabolomics and genomics provides a catalog of genetic factors that infuence molecular phenotypes in pigs linking relevant metabolic pathways

description: Content

Metabolites included in the study. Summary statistics of metabolite levels for the Large White and Duroc pig populations are provided.
description: Contributors

Samuele Bovo1*, Anisa Ribani1, Flaminia Fanelli2,3, Giuliano Galimberti4, Pier Luigi Martelli5, Paolo Trevisi6, Francesca Bertolini1, Matteo Bolner1, Rita Casadio5, Stefania Dall’Olio1, Maurizio Gallo7, Diana Luise6, Gianluca Mazzoni1, Giuseppina Schiavo1, Valeria Taurisano1, Paolo Zambonelli1, Paolo Bosi6, Uberto Pagotto2,3, Luca Fontanesi1*

1 Animal and Food Genomics Group, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy2 Endocrinology Research Group, Center for Applied Biomedical Research, Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy3 Division of Endocrinology and Prevention and Care of Diabetes, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Policlinico di Sant’Orsola, Bologna, Italy4 Department of Statistical Sciences “Paolo Fortunati”, University of Bologna, Bologna, Italy5 Biocomputing Group, Department of Pharmacology and Biotechnology, University of Bologna, Bologna, Italy6 Laboratory on Animal Nutrition and Feeding for Livestock Sustainability and Resilience, Division of Animal Sciences, Department of Agricultural and Food Sciences, University of Bologna, Bologna, Italy7 Associazione Nazionale Allevatori Suini, Roma, Italy

*E-mail addresses:SB: samuele.bovo@unibo.itLF: luca.fontanesi@unibo.it

 
description: Background Metabolomics opens novel avenues to study the basic biological mechanisms underlying complex traits, starting from characterization of metabolites. Metabolites and their levels in a biofuid represent simple molecular phenotypes (metabotypes) that are direct products of enzyme activities and relate to all metabolic pathways, including catabolism and anabolism of nutrients. In this study, we demonstrated the utility of merging metabolomics and genomics in pigs to uncover a large list of genetic factors that infuence mammalian metabolism.Results We obtained targeted characterization of the plasma metabolome of more than 1300 pigs from two populations of Large White and Duroc pig breeds. The metabolomic profles of these pigs were used to identify genetically infuenced metabolites by estimating the heritability of the level of 188 metabolites. Then, combining breed-specifc genome-wide association studies of single metabolites and their ratios and across breed meta-analyses, we identifed a total of 97 metabolite quantitative trait loci (mQTL), associated with 126 metabolites. Using these results, we constructed a human-pig comparative catalog of genetic factors infuencing the metabolomic profle. Whole genome resequencing data identifed several putative causative mutations for these mQTL. Additionally, based on a major mQTL for kynurenine level, we designed a nutrigenetic study feeding piglets that carried diferent genotypes at the candidate gene kynurenine 3-monooxygenase (KMO) varying levels of tryptophan and demonstrated the efect of this genetic factor on the kynurenine pathway. Furthermore, we used metabolomic profles of Large White and Duroc pigs to reconstruct metabolic pathways using Gaussian Graphical Models, which included perturbation of the identifed mQTL.Conclusions This study has provided the frst catalog of genetic factors afecting molecular phenotypesthat describe the pig blood metabolome, with links to important metabolic pathways, opening novel avenuesto merge genetics and nutrition in this livestock species. The obtained results are relevant for basic and applied 
description: FundingSequencing data of autochthonous pig breeds were from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 634476 for the project with acronym TREASURE. We thank the TREASURE Consortium for the collaboration. This manuscript reflects only the authors’ views and opinions, neither the European Union nor the European Commission can be considered responsible for them.

This study was supported by: (1) PRIN2017 PigPhenomics that has received funding from the Italian MUR (for the production of the genomic and metabolomic data) (to LF); (2) the Horizon Europe Re-Livestock project that has received funding from the European Union's Horizon Europe research and innovation programme under the grant agreement No. 01059609 (for the elaboration and analysis of the data) (to LF and MG); (3) the Italian PRIN2022 project FEEDTHEPIG, Funded by the European Union - NextGenerationEU under the National Recovery and Resilience Plan (PNRR) - Mission 4 Education and research - Component 2 From research to business - Investment 1.1 Notice PRIN 2022 PNRR (DD N. 1409 del 14/09/2022), proposal code P2022FZMJ9 - CUP J53D23018310001 for the analysis of part of the data (to FB); (4) the Italian PRIN2022 HamCapture, funded by the European Union - NextGenerationEU under the National Recovery and Resilience Plan (PNRR) - Mission 4 Education and research - Component 2 From research to business - Investment 1.1 Notice Prin 2022 - DD N. 104 del 2/2/2022, proposal code 202238NP9N – CUP J53D23009570001 (for the analysis of part of the data) (to GS); (5) the Programma di Sviluppo Rurale Nazionale (PSRN) SUIS-2, co-funded by the European Agricultural Fund for Rural Development of the European Union and by the MASAF (for pig sequencing data) (to LF and MG);(6) the European Union Next-GenerationEU (PIANO NAZIONALE DI RIPRESA E RESILIENZA (PNRR) – MISSIONE 4 COMPONENTE 2, INVESTIMENTO 1.4 – D.D. 1032 17/06/2022, CN00000022), within the Agritech National Research Center (Agritech Spoke 1) (to LF and GS).