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. 2019 May 9;14(5):e0207050.
doi: 10.1371/journal.pone.0207050. eCollection 2019.

Hypothalamic transcriptome analysis reveals the neuroendocrine mechanisms in controlling broodiness of Muscovy duck (Cairina moschata)

Affiliations

Hypothalamic transcriptome analysis reveals the neuroendocrine mechanisms in controlling broodiness of Muscovy duck (Cairina moschata)

Pengfei Ye et al. PLoS One. .

Abstract

Broodiness, one of the maternal behaviors and instincts for natural breeding in birds, is an interesting topic in reproductive biology. Broodiness in poultry is characterized by persistent nesting, usually associated with cessation of egg laying. The study of avian broodiness is essential for bird conservation breeding and commercial poultry industry. In this study, we examined the hypothalamus transcriptome of Muscovy duck in three reproductive stages, including egg-laying anaphase (LA), brooding prophase (BP) and brooding metaphase (BM). Differences in gene expression during the transition from egg-laying to broodiness were examined, and 155, 379, 292 differently expressed genes (DEGs) were obtained by pairwise comparisons of LA-vs-BP, LA-vs-BM and BP-vs-BM, respectively (fold change≥1.5, P < 0.05). Gene Ontology Term (GO) enrichment analysis suggested a possible role of oxidative stress in the hypothalamus might invoke reproductive costs that potentially change genes expression. KEGG analysis revealed glutamatergic synapse, dopaminergic synapse, serotonergic synapse and GABAergic synapse pathway were significantly enriched, and regulator genes were identified. Eight gene expression patterns were illustrated by trend analysis and further clustered into three clusters. Additional six hub genes were identified through combining trend analysis and protein-protein interaction (PPI) analysis. Our results suggested that the cyclical mechanisms of reproductive function conversion include effects of oxidative stress, biosynthesis of neurotransmitters or their receptors, and interactions between glucocorticoids and thyroid hormones and regulatory genes. These candidate genes and biological pathways may be used as targets for artificial manipulation and marker-assisted breeding in the reproductive behavior.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig 1
Fig 1. Principal component analysis (PCA) of sample relationship.
Correlations between 12 hypothalamic sample mapped onto first two principal components of PCA analysis based on genome-wide expression profiles. Triangle nodes standard for sample of egg-laying anaphase (LA), square nodes for sample of brooding prophase (BP), circle nodes for sample of brooding metaphase (BM).
Fig 2
Fig 2. Statistical results, GO enrichment and KEGG enrichment of different expressed genes (DEGs).
(A) Histogram of DEGs in pairwise comparisons of three group. Red bar for up-regulated genes, green bar for down-regulated genes. (B) Venn diagrams of DEGs in pairwise comparisons of three group. (C) Top 20 significantly enriched Biological processes of GO enrichment of DEGs in three comparisons. (D) The significantly enriched KEGG pathways of DEGs in three comparisons.
Fig 3
Fig 3. Validation of the gene expression profile by qPCR.
Plot of gene expression log2 ratios (LA vs BP, LA vs BM and BP vs BM) determined by the RNA-Seq (X-axis) and RT-qPCR (Y-axis) for 24 selected genes (S6 Table). Correlation between RNA-Seq and RT-qPCR was calculated by Pearson product moment correlation in pairwise comparisons of three stages. Each dot represents one tested gene and the plots present linear regression lines, P values and correlation coefficients (r).
Fig 4
Fig 4. Overall patterns of differentially expressed genes and the representative profiles in reproductive stages of LA, BP and BM.
(A) Patters were plotted on the heatmap using Treeview. Red represents up-regulated genes while green represents down-regulated genes. Hierarchical clustering is shown on the left. All 8 expression profiles identified by Short Time-series Expression analysis are shown in the middle and the summarized representative profiles are shown on the right. (B) STEM analysis grouping of significant differentially-expressed genes into three temporal profile clusters.
Fig 5
Fig 5. Protein-protein interaction (PPI) networks of DEGs.
Circle nodes for genes/proteins, pentagon for transcription factors, rectangle nodes for KEGG pathway or biological process. Nodes with a degree of connectivity greater than 5 were labeled and all nodes in S1 Fig were labeled. According to trend analysis, genes/proteins were colored in red (Cluster 1, representing up-regulation over time), green (Cluster 2, representing down-regulation over time) and gray (Cluster 3, gene expression changed in BP stage only). Interaction were show as solid lines between genes/proteins, edges of KEGG pathway/biological process in dashed lines.

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Grants and funding

This study was financed by Natural Science Foundation of Anhui Province (CN) (1508085MC53), National Science and Technology Pillar Program during the Twelfth Five-year plan period (2015BAD03B06), The Open Fund of Anhui Province Key Laboratory of Local Livestock and Poultry, Genetical Resource Conservation and Breeding (AKLGRCB2017008), National key R&D project (2018YFD0501500).