Synergistic transcriptomic and metabolomic analyses in Zi geese ovaries with different clutch lengths

Abstract

The clutch is defined as consecutive days of oviposition. Clutch length is an index that reflects ovulation persistence, and is highly correlated with egg production in birds. To identify the genetic markers associated with clutch length in geese, two consecutive experiments were conducted. In the first experiment, 200 Zi geese were selected, all 230 days old, were selected from the same batch and raised individually in the same environment. Data of egg-laying and clutch traits were recorded. After the laying period, three geese with the longest clutch lengths were selected to form the length clutch group (LCG) and three geese with the shortest clutch lengths were formed the short clutch group (SCG). In the second experiment, the ovaries of six geese were collected for transcriptomic and metabolomic analyses. The results showed that large clutch length (LCL) and average clutch length (ACL) were positively correlated with egg number (EN) (P < 0.01; r = 0.63 and 0.60, respectively). Large clutch number (LCN) was significantly correlated with the peak egg number (PEN) (r = 0.58, P < 0.01) and EN (r = 0.60, P < 0.01). EN, LCN, LCL, and ACL showed significant differences (P < 0.01) between the two clutch length groups. Transcriptomic analysis identified 424 differentially expressed genes (DEGs). Functional enrichment analysis revealed that these DEGs were mainly involved in neuroactive ligand-receptor interactions, ovarian steroidogenesis, and calcium signaling pathways. Further, AVPR1A, FGF14, and LHCGR were predicted as the key genes regulating LCL. Metabolomic analysis identified 349 differential metabolites (DMs) in both the positive and negative ion modes. Pyruvate, isocitric acid, D/L‑serine, 3-phospho-d-glycerate, succinate, glycine, and glutamic acid were identified as the key metabolites mainly enriched in the signaling pathways of the TCA cycle. Integration of transcriptomic and metabolomic data revealed critical gene-metabolite pairs, including ACSL4-phosphoenolpyruvate, implicated in LCL regulation. In summary, this study provides new insights into the genes and molecular markers affecting LCL in Zi geese.

Keywords: Metabolome; Ovary; Synergistic; Transcriptome; Zi goose.

Fig. 1

Observation of ovarian tissue in the length clutch group (LCG) and short clutch group (SCG). (A–C) LCG ovarian tissue sections showing well-developed oocytes (black arrowheads) and intact zona pellucida (white arrows). (D–F) SCG sections with atretic follicles (red arrows) and indented zona pellucida (yellow arrows). Note: H&E staining;. Magnification, 100×.

Fig. 2

Quality analysis of transcriptome samples. (A) Fragments per kilobase of transcript per million fragments mapped (FPKM) box plot. The difference in the overall expression of each sample can be measured by density. (B) Principal component analysis (PCA). Each point in the figure represents a sample, with the horizontal coordinate indicating the value of principal component 1 and the vertical coordinate indicating the value of principal component 2. (C) Differentially expressed genes (DEGs) volcano map analysis. The red dots represent upregulated DEGs, and the blue dots represent downregulated DEGs.

Fig. 3

Functional enrichment analysis of differentially expressed genes (DEGs). (A) Gene ontology (GO) enrichment analysis of DEGs. The top six or seven terms enriched with DEGs in each subcategory: Biological Process (BP), Molecular Function (MF), Cellular Component (CC). The horizontal coordinate represents the rich factor. (B) Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of DEGs. The top 20 signaling pathways with DEGs significantly enriched are shown, excluding those classified as human diseases in the primary classification. The horizontal coordinate represents the rich factor. (C) Description of DEGs co-enriched by KEGG pathway and GO terminology. The enrichment of important DEGs in the KEGG pathway and GO terminology is shown.

Fig. 4

Metabolome sample quality analysis. (A) Fragments per kilobase of transcript per million fragments mapped (FPKM) box plot. The difference in the overall expression of each sample can be measured by density. (B) Score scatter plot of the orthogonal partial least squares-discriminant analysis (OPLS-DA)model. R2X and R2Y represent the interpretation rate of the model for X and Y matrices; Q²Y∈[0,1]. The larger the Q²Y, the better the model prediction performance. (C) Principal component analysis (PCA). Each point in the figure represents a sample, with the horizontal coordinate indicating the value of principal component 1 and the vertical coordinate indicating the value of principal component 2. (D) Differential metabolites (DMs) volcano map analysis. The red metabolites are significantly up-regulated, whereas the blue metabolites are significantly down-regulated.

Fig. 5

Functional enrichment analysis of differential metabolites (DMs). (A) Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of DMs. Only the top 20 metabolic pathways with the most significant enrichment of DMs are shown. The horizontal coordinate represents the rich factor. (B) Description of enriched DMs by the relevant KEGG pathways. The enrichment of important DMs in the KEGG pathways is shown.

Fig. 6

Integration analysis of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways between the transcriptome and metabolome. (A) Venn diagram of KEGG enrichment pathways in the transcriptome and metabolome. Among them, the differentially expressed gene (DEG) enriched pathway only shows that classified as metabolism. (B) Pathway analysis for the coenriched DEGs and differential metabolites (DMs). The top 20 pathways of co-enrichment were shown. (C) Correlation analysis of DEGs enriched in the KEGG pathways and the top 50 DMs.

Fig. 7

Interaction network diagram of differentially expressed genes (DEG) and differential metabolites (DMs). (A) Carbohydrate metabolism, (B) Energy metabolism, (C) Lipid metabolism, (D) Nucleotide metabolism, (E) Amino acid metabolism, and (F) Coenzyme factors and vitamin metabolism according to the Kyoto Encyclopedia of Genes and Genomes (KEGG) secondary classification. The pink triangle represents mRNA up-regulation, the pink V-shape represents mRNA down-regulation, the yellow triangle represents metabolite up-regulation, the yellow V-shape represents metabolite down-regulation, dashed lines represent negative correlation, and solid lines represent positive correlation.