# Multi-omics analysis revealed that oxidative phosphorylation contributed to the heterosis for feed efficiency in laying chickens

**Authors:** Qin Li, Jingwei Yuan, Yanyan Sun, Yuanmei Wang, Yunlei Li, Aixin Ni, Yunhe Zong, Hanhan Yang, Xinyi Li, Xiaolong Huang, Hui Ma, Jilan Chen

PMC · DOI: 10.1016/j.psj.2026.106658 · 2026-02-18

## TL;DR

This study shows that oxidative phosphorylation in laying chickens plays a key role in improving feed efficiency through interactions between gut microbes, genes, and metabolites.

## Contribution

The study identifies non-additive gut microbes and metabolic pathways contributing to feed efficiency heterosis in laying chickens.

## Key findings

- Non-additive gut microbes like Leyella, Paraprevotella, and Zongyangia are associated with feed efficiency heterosis.
- RFI-associated metabolites are enriched in glycerophospholipid metabolism and oxidative phosphorylation pathways.
- Zongyangia's non-additive expression correlates with UQCR10 and Ubiquinone-1 in oxidative phosphorylation, improving feed efficiency.

## Abstract

Improving feed efficiency has been the top priority in animal husbandry. Host genetics and gut microbiota synergistically regulate feed efficiency in laying chicken. However, the role of gut microbiota in heterosis for feed efficiency was rarely investigated. Herein, we used multi-omics data to elucidate the regulatory mechanisms of heterosis for feed efficiency in White Leghorn, Beijing-You chicken, and their reciprocal crosses. We observed divergent heterosis for residual feed intake (RFI) between two crossbreds during the laying period from 43 to 46 weeks of age. Metagenomic analysis showed the significant difference in richness and function of cecal microbiota among crossbreds and purebreds (P < 0.05), and the differential functional pathways were mainly related to metabolism. Most microorganisms (>90 %) were non-additive in crossbreds. Weighted gene co-expression network analysis and LDA effect size analysis revealed seven non-additive RFI-associated microorganisms, such as Leyella, Paraprevotella, and Zongyangia. We also identified 544 RFI-associted metabolites, which were mainly overrepresented in glycerophospholipid metabolism and oxidative phosphorylation. Integrative analysis further revealed the interactions among non-additive microorganisms, genes, and metabolites. Specifically, the non-additive expression of Zongyangia was positively correlated with UQCR10 and Ubiquinone-1 levels within the oxidative phosphorylation pathway. These factors were negatively correlated with RFI, contributing to the RFI heterosis. Our study highlighted that key microorganisms, genes, and metabolites involved in oxidative phosphorylation interact to regulate negative heterosis for RFI in laying hens. The findings established a theoretical and practical foundation for further exploring the molecular mechanisms that drive heterosis for feed efficiency.

## Linked entities

- **Genes:** UQCR10 (ubiquinol-cytochrome c reductase, complex III subunit X) [NCBI Gene 29796]
- **Chemicals:** Ubiquinone-1 (PubChem CID 4462)

## Full-text entities

- **Genes:** UQCR10 (ubiquinol-cytochrome c reductase, complex III subunit X) [NCBI Gene 770937], ATP5I (ATP synthase, H+ transporting, mitochondrial Fo complex subunit E) [NCBI Gene 769146] {aka ATP5ME, RBF, RPF-1}, ACHE (acetylcholinesterase (Cartwright blood group)) [NCBI Gene 396388]
- **Diseases:** inflammatory (MESH:D007249), RFI (MESH:D018365)
- **Chemicals:** paraformaldehyde (MESH:C003043), nicotinate (MESH:D009525), carbohydrate (MESH:D002241), ATP (MESH:D000255), SCFAs (MESH:D005232), glycerophospholipid (MESH:D020404), P (MESH:D010758), water (MESH:D014867), polysaccharide (MESH:D011134), starch (MESH:D013213), nicotinamide (MESH:D009536), mannose (MESH:D008358), nitrogen (MESH:D009584), purine (MESH:C030985), Ca (MESH:D002118), lysine (MESH:D008239), Phenyl-Alanine (MESH:D010649), 3-Dehydrosphinganine (-), H&amp;E (MESH:D006371), Lysophosphatidylcholine (MESH:D008244), methanol (MESH:D000432), fatty acids (MESH:D005227), sphingolipid (MESH:D013107), glycogen (MESH:D006003), LysoPC (MESH:C006065), Dodemorph (MESH:C077547), fructose (MESH:D005632), Deoxyadenosine (MESH:C058118), glyoxylate (MESH:C031150), PA (MESH:D011478), amino acids (MESH:D000596)
- **Species:** Gallus gallus (bantam, species) [taxon 9031], Candidatus Stoquefichus (genus) [taxon 1470349], Homo sapiens (human, species) [taxon 9606], Butyricicoccus (genus) [taxon 580596], Prevotella (genus) [taxon 838], Bacteroides (genus) [taxon 816], Bos taurus (bovine, species) [taxon 9913], Clostridium (genus) [taxon 1485], Bifidobacterium (genus) [taxon 1678], Paraprevotella (genus) [taxon 577309], Anas platyrhynchos (duck, species) [taxon 8839]

## Figures

9 figures with captions in the complete paper: https://tomesphere.com/paper/PMC13010968/full.md

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Source: https://tomesphere.com/paper/PMC13010968