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Genome-wide cis-expression Quantitative Trait Loci (eQTL) and transcriptomic signals reveal distinct molecular regulation across correlated feed efficiency traits

Aug 2026 · Frontiers in Genetics · Vol 17 · 0 citations · 73 references
Medicine

TL;DR

The results highlight that integrated multi-trait candidate gene identification approaches can reveal key genes that lower feed intake while maintaining animal growth, supporting breeding strategies aimed at improving efficiency and long-term economic sustainability in sheep.

Abstract

Introduction Feed efficiency (FE) is a complex trait which determines livestock production profitability, yet the molecular mechanisms behind it remain unclear. This study investigated the blood transcriptomic profile of lambs, alongside genotype data with the aim to uncover the genetic basis of FE traits such as absolute dry matter intake (DMIabsolute), DMI adjusted for body size (DMIadjusted), average daily live weight gain (ADG), and residual feed intake (RFI). Materials and Methods Bulk RNA-Seq and genotype data were analysed using three complementary approaches: differential gene expression (DGE) analysis, weighted gene co-expression network analysis (WGCNA), and cis-expression Quantitative Trait Loci (cis-eQTL) mapping. These methods were used independently to identify genes and regulatory networks associated with FE traits and to investigate evidence supporting multi-trait candidate gene selection. Results DGE analysis revealed 2, 24, 85 and 4 differentially expressed genes for DMIabsolute, DMIadjusted, ADG, and RFI (Padjusted < 0.05), functionally enriched in sensory perception, ATP-dependent chromatin remodeling, Notch signaling and immune response pathways. 9 gene modules significantly associated with the FE traits (P ≤ 0.05) with correlations ranging from r = -0.56 to 0.49, were identified using WGCNA. Single nucleotide polymorphism (SNP)-level cis-eQTL analysis identified 93 eSNPs associated with 74 genes (false discovery rate (FDR) < 0.05), while permutation-derived gene level analysis identified 280 eGenes (FDR < 0.2, empirical P < 0.03). Across the three analyses, applying thresholds of DGE (Padjusted < 0.05), WGCNA (correlation, P ≤ 0.05), and cis-eQTL gene-level significance (empirical P < 0.05), multiple overlapping genes were identified including DNMT3A, KANSL1, NCOR1 for DMIadjusted, ACOX2, FANCF, CIMIP2B, LOC101115106, ARMH2, LOC132657496 for ADG, and LOC114114576 for RFI representing regulators of variations in FE. Discussion The integration of DGE, WGCNA, and cis-eQTL analyses identified key genes and regulatory mechanisms associated with variation in FE traits. These results highlight that integrated multi-trait candidate gene identification approaches can reveal key genes that lower feed intake while maintaining animal growth, supporting breeding strategies aimed at improving efficiency and long-term economic sustainability in sheep.

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