Multi-ome analysis to predict feed efficiency in pigs

TY - ABST

T1 - Multi-ome analysis to predict feed efficiency in pigs

AU - Verschuren, Lisanne M G

AU - Jansman, A.

AU - van Milgen, J.

AU - Zemb, O.

AU - Hedemann, Mette Skou

AU - Bergsma, R.

AU - Calus, M P L

PY - 2021/8

Y1 - 2021/8

N2 - This study aimed to use relationships between the faecal microbiome, the systemic metabolome, and animal genome to predict feed efficiency related traits in pigs (i.e. feed intake, body weight gain, and feed conversion ratio). Datawere collected from 530 three-way crossbred male grower-finisher pigs, all genotyped at 50k SNPs. Pigs were offered feed ad libitum in a three-phase feeding program with a commercial diet based on wheat, barley and by-products. On the day before slaughter (mean body weight 125 kg), individual faecal and blood samples were collected. Faecal samples were sequenced for the 16S hypervariable region of bacteria (V3/V4) to profile the faecal microbiome.Blood serum samples were analysed with untargeted LC-MS for metabolites. Using these data, we calculated the proportion of variance in feed efficiency related traits that was explained by variation in the faecal microbiome (m2),blood metabolites (b2), and genetic background (h2). The m2 values ranged from 34 to 52%, b2 values ranged from 50 to 63%, and h2 values from 23 to 28%. Using cross-validation, we estimated the accuracy of prediction based on the microbiome, metabolome, and genome profile of the pigs. Prediction accuracies were highest based on the metabolic profile (r=0.56-0.63), followed by the faecal microbiome profile (r=0.30-0.48), and the genome profile (r=0.21-0.29). Modelling all three profiles simultaneously resulted in the highest prediction accuracy (r=0.59-0.66). In conclusion, combining information on the genotype of the pig and its faecal microbiota and blood metabolite profiles improves the accuracy of prediction of phenotypes for feed efficiency related traits, but almost the same prediction accuracy could be achieved using blood metabolite profiles only. This study was part of the Feed-a-Gene Project, funded from the European Union’s H2020 Programme under grant agreement no 633531.

AB - This study aimed to use relationships between the faecal microbiome, the systemic metabolome, and animal genome to predict feed efficiency related traits in pigs (i.e. feed intake, body weight gain, and feed conversion ratio). Datawere collected from 530 three-way crossbred male grower-finisher pigs, all genotyped at 50k SNPs. Pigs were offered feed ad libitum in a three-phase feeding program with a commercial diet based on wheat, barley and by-products. On the day before slaughter (mean body weight 125 kg), individual faecal and blood samples were collected. Faecal samples were sequenced for the 16S hypervariable region of bacteria (V3/V4) to profile the faecal microbiome.Blood serum samples were analysed with untargeted LC-MS for metabolites. Using these data, we calculated the proportion of variance in feed efficiency related traits that was explained by variation in the faecal microbiome (m2),blood metabolites (b2), and genetic background (h2). The m2 values ranged from 34 to 52%, b2 values ranged from 50 to 63%, and h2 values from 23 to 28%. Using cross-validation, we estimated the accuracy of prediction based on the microbiome, metabolome, and genome profile of the pigs. Prediction accuracies were highest based on the metabolic profile (r=0.56-0.63), followed by the faecal microbiome profile (r=0.30-0.48), and the genome profile (r=0.21-0.29). Modelling all three profiles simultaneously resulted in the highest prediction accuracy (r=0.59-0.66). In conclusion, combining information on the genotype of the pig and its faecal microbiota and blood metabolite profiles improves the accuracy of prediction of phenotypes for feed efficiency related traits, but almost the same prediction accuracy could be achieved using blood metabolite profiles only. This study was part of the Feed-a-Gene Project, funded from the European Union’s H2020 Programme under grant agreement no 633531.

U2 - 10.3920/978-90-8686-918-3

DO - 10.3920/978-90-8686-918-3

M3 - Conference abstract in proceedings

SN - 978-90-8686-366-2

T3 - EAAP Book of Abstracts

SP - 572

EP - 572

BT - Book of Abstracts of the 72nd Annual Meeting of the European Federation of Animal Science

A2 - Strandberg, E.

A2 - Pinotti, L.

A2 - Messori, S.

A2 - Kenny, D.

A2 - Lee, M.

A2 - Hocquette, J.F.

A2 - Cadavez, V.A.P.

A2 - Millet, S.

A2 - Evans, R.

A2 - Veldkamp, T.

A2 - Pastell, M.

A2 - Pollott, G.

PB - Wageningen Academic Publishers

T2 - 72nd Annual Meeting of the European Federation of Animal Science

Y2 - 29 August 2021 through 3 September 2021

ER -