Liver Transcriptome Response to Heat Stress in Beijing You Chickens and Guang Ming Broilers

Abstract

Heat stress is one of the most prevalent issues in poultry production that reduces performance, robustness, and economic gains. Previous studies have demonstrated that native chickens are more tolerant of heat than commercial breeds. However, the underlying mechanisms of the heat tolerance observed in native chicken breeds remain unelucidated. Therefore, we performed a phenotypical, physiological, liver transcriptome comparative analysis and WGCNA in response to heat stress in one native (Beijing You, BY) and one commercial (Guang Ming, GM) chicken breed. The objective of this study was to evaluate the heat tolerance and identify the potential driver and hub genes related to heat stress in these two genetically distinct chicken breeds. In brief, 80 BY and 60 GM, 21 days old chickens were submitted to a heat stress experiment for 5 days (33 °C, 8 h/day). Each breed was divided into experimental groups of control (Ctl) and heat stress (HS). The results showed that BY chickens were less affected by heat stress and displayed reduced DEGs than GM chickens, 365 DEGs and 382 DEGs, respectively. The transcriptome analysis showed that BY chickens exhibited enriched pathways related to metabolism activity, meanwhile GM chickens' pathways were related to inflammatory reactions. CPT1A and ANGPTL4 for BY chickens, and HSP90B1 and HSPA5 for GM chickens were identified as potential candidate genes associated with HS. The WGCNA revealed TLR7, AR, BAG3 genes as hub genes, which could play an important role in HS. The results generated in this study provide valuable resources for studying liver transcriptome in response to heat stress in native and commercial chicken lines.

Keywords: Beijing You; Guang Ming; WGCNA; heat stress; transcriptome.

Figure 1

Phenotypical and physiological differences between BY and GM chickens in response to heat stress. (A) Heterophils/Lymphocytes (H/L) ratio differences between BY and GM (Ctl, n = 13 and HS, n = 10). (B) Body weight (BW) differences between BY and GM (Ctl, n = 13 and HS, n = 12). (C) Concentration differences of Superoxide Dismutase (SOD) between BY and GM (Ctl, n = 7; and HS, n = 8). (D) Concentration differences of Total antioxidant capacity (T-AOC) between BY and GM (Ctl, n = 7; and HS, n = 8). All the parameters were measured 5 days post-heat stress. Data analysis was performed using two-way ANOVA, with Sidak’s multiple comparison (α = 0.05). ns (no significant); * (p < 0.05); ** (p < 0.01); **** (p < 0.0001).

Figure 2

Identification of Differential Expressed Genes (DEGs) in BY and GM chickens. (A) Summary of total DEGs between BY and GM in response to heat stress (p < 0.05 was used to determine significant DEGs). (B) Venn diagram showing the number of unique and shared DEGs between BY and GM in response to heat stress. BY_Ctl: Beijing You control group, GM_Ctl: Guang Ming control group, BY_HS: Beijing You heat stress group, GM_HS: Guang Ming heat stress group.

Figure 3

Identification of Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment of Beijing You and Guang Ming chickens in response to heat stress. (A) The enriched GO terms are based on the DEGs identified in BY_Ctl vs. BY_HS. (B) KEGG pathways enriched based on the DEGs identified in BY_Ctl vs. BY_HS. (C) The enriched GO terms are based on the DEGs identified in GM_Ctl vs. GM_HS. (D) KEGG pathways enriched based on the DEGs identified in GM_Ctl vs. GM_HS.

Figure 4

Weighted Gene-Co-Expression Network Analysis (WGCNA) results of Beijing You chickens (liver transcriptomic) show the modules significantly correlated with treatment (heat stress) and blood indicators (H/L, SOD, and T-AOC). (A) Scale-free topology model and Mean connectivity. (B) Cluster dendrogram of Beijing You chickens reveals the module’s colors and the merged dynamic. (C) Heat map of module-trait relationships, each cell has two values. The upper is the absolute value of the correlation coefficient, and down is the p-value. Red and blue colors represent positive and negative correlations, respectively.

Figure 5

Weighted Gene-Co-Expression Network Analysis (WGCNA) results of Guang Ming chickens (liver transcriptomic) show the modules significantly correlated with treatment (heat stress) and blood indicators (H/L, SOD, and T-AOC). (A) Scale-free topology model and Mean connectivity. (B) Cluster dendrogram of Guang Ming chickens reveals the module’s colors and the merged dynamic. (C) Heat map of module-trait relationships, each cell has two values. The upper is the absolute value of the correlation coefficient, and down is the p-value. Red and blue colors represent positive and negative correlations, respectively.

Figure 6

Co-expression network of hub genes in BY chickens: (A) Filtered co-expression network treatment grey module. (B) Filtered co-expression network H/L brown module. (C) Filtered co-expression network H/L turquoise module. (D) Filtered co-expression network SOD black module. (E) Filtered co-expression network T-AOC greenyellow module.

Figure 7

Co-expression network of hub genes in GM chickens: (A) Filtered co-expression network treatment darkorange module. (B) Filtered co-expression network H/L black module. (C) Filtered co-expression network H/L lightcyan module.