International Journal of Molecular Zoology, 2025, Vol.15, No.1, 10-19 http://animalscipublisher.com/index.php/ijmz 11 weight. This indicator reflects the efficiency of a chicken in converting feed into body weight. RFI is the difference between the actual feed consumed and the predicted feed needed. This indicator has little relation to growth rate and yield and is independent (Prakash et al., 2020). Both of these traits have certain heritability. The heritability of FCR is between 0.31 and 0.49, and that of RFI is between 0.42 and 0.52. This indicates that FE can be improved through selection and breeding. To measure these indicators, it is necessary to record the feed intake, weight changes, or egg production of each chicken over a period of time, and then calculate the values of these traits and the relationships among them using genetic and statistical models (Aggrey et al., 2010; Marchesi et al., 2021; Zhou et al., 2022). 2.2 Factors affecting FE in chickens Feed efficiency is influenced by factors such as genetics, physiology and nutrition, and the interaction among these factors is very complex. The genetic factors of the host play a significant role in the differences in feed efficiency, but the intestinal microbiota, especially the flora in the cecum, cannot be ignored either. Wen et al. (2021) and Zhou et al. (2022) found that the composition of cecal microbiota could explain up to 28% of the differences in RFI. The research by Wu et al. (2019) and Zampiga et al. (2021) indicates that the composition of the diet, such as energy and nutrient density, as well as the addition of additives like amino acids and minerals, can directly affect the absorption and utilization of feed, thereby enhancing feed efficiency. Dao et al. 's research in 2023 indicates that environmental factors, such as chicken coop conditions, management methods, and the use of kitchen waste as alternative feed, can also affect feed intake, digestibility, and health, thereby influencing feed efficiency. The interaction between genetics and diet can also regulate the intestinal flora and further affect feed efficiency (Wen et al., 2021; Bernard et al., 2024). 2.3 Physiological and molecular basis of FE variability Physiologically, factors such as digestive efficiency, nutrient absorption, metabolic level, and body composition (such as protein deposition and fat accumulation) all affect the feed efficiency of chickens (Aggrey et al., 2010; Tallentire et al., 2016). At the molecular level, genome-wide association studies (GWAS) identified many candidate genes and gene regions related to feed efficiency, such as ATRNL1, PIK3C2A, and SORCS3, which are involved in metabolic regulatory pathways (Figure 1) (Marchesi et al., 2021). The microbiota in the intestinal tract, especially some bacteria in the cecum and duodenum, can also affect energy acquisition, short-chain fatty acid production and nutrient absorption, thereby influencing feed efficiency (Wen et al., 2021; Zhou et al., 2022; Bernard et al., 2024). The research results of Wen et al. (2021) and Zhou et al. (2022) indicate that although the interaction between host genes and microorganisms is not strong, some specific bacterial classifications remain stable in chicken flocks with high feed efficiency, suggesting that they may have potential for utilization in breeding and microbial management. 3 Transcriptomic Approaches to Study Feed Efficiency 3.1 RNA-seq and gene expression profiling Zhou et al. (2015), Yang et al. (2020), and Xiao et al. (2021) conducted transcriptome comparisons in the mammary muscle, liver, duodenum, and adipose tissue of chickens with high and low feed efficiency, and discovered hundreds and thousands of differentially expressed genes (DEGs) related to feed efficiency. Yi et al. (2015) and Ye et al. (2024) found that quantitative RT-PCR was often used in these studies to verify the expression differences of some key genes to ensure the reliability of RNA-seq data. Some new sequencing techniques, such as 3’UTR-seq, have also discovered regulatory features like intron retention, which is helpful for understanding the transcriptional regulatory mechanisms related to feed efficiency (Wang et al., 2022). 3.2 Key biological pathways identified The genes related to mitochondrial function, oxidative phosphorylation and tricarboxylic acid cycle (TCA) in high-efficiency chickens are often upregulated, indicating that their energy metabolism capacity is stronger (Xiao et al., 2021; Yuan et al., 2024); but, the immune and inflammatory response pathways of low-efficiency chickens are often more active, which may imply that high immune system activity consumes energy and thereby affects
RkJQdWJsaXNoZXIy MjQ4ODYzNA==