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. 2024 Jun 6;103(8):103950. doi: 10.1016/j.psj.2024.103950

Hypothalamic transcriptome profile from laying period to incubation period of Changshun green-shell laying hens

Zhi Chen *,†,1, Di Wen *, Jian Cen *, Ren Mu *,†
PMCID: PMC11255903  PMID: 38917610

Abstract

Incubation behavior in chickens is closely associated with hypothalamus. Here, RNA sequencing of hypothalamus from Changshun green-shell laying hens, an indigenous chicken breed from China, in egg-laying period (LP) and incubation period (BP) was conducted to identify critical pathways and candidate genes involved in controlling the incubation behavior in hypothalamus. A total of 637 up-regulated and 305 down-regulated differently expressed genes (DEGs) were identified in chicken hypothalamus between LP and BP groups. Gene ontology term (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis further revealed that neuroactive ligand-receptor interaction, hippo signaling pathway, and focal adhesion were significantly enriched. Five candidate genes (POMC, IGF1R, CHAD, VCL, and MYL9) were suggested to play crucial roles in the regulation of chicken incubation behavior. Our results further indicated the complexity of reproductive behavior of different chicken breeds.

Key words: transcriptome analysis, hypothalamus, laying period, incubation period, Changshun green-shell laying hen

INTRODUCTION

Incubation behavior is a common maternal behavior of domestic chickens, which is usually characterized by persistent nesting, anorexia, turning and retrieval of eggs, clucking, weight loss, defense of the nest and increased body temperature (Sherry et al., 1980; El Halawani et al., 1984; Romanov et al., 2002;). The cessation of egg-laying related to incubation results in huge economic losses for the poultry industry. Incubation behavior has been investigated since 1930s, it is now generally accepted that avian incubation behavior is strictly mediated by the central nervous system and is mainly associated with multiple neuroendocrine hormones and neurotransmitters (Riddle et al., 1935; Geng et al., 2014; Zhao et al., 2023). Concretely, the hypothalamus, also known as a relay center of the endocrine system, can integrate multiple signals derived from upper cortical inputs, autonomic functions, environmental cues and peripheral endocrine feedback (de la Iglesia and Schwartz, 2006). In turn, the hypothalamus controls the release of the pituitary hormones that influence endocrine systems in chickens. Pituitaric prolactin (PRL) is considered to be a primary hormonal inducer of incubation behavior in chickens. A characteristic increase of PRL in plasma induces the initiation of incubation behavior in chickens (Sharp et al., 1979; Sharp et al., 1988; Zadworny et al., 1988; Sharp et al., 1989; March et al., 1994). Meanwhile, luteinizing hormone (LH) in plasma decreases simultaneously with the exaggerated increase of plasma PRL (Zadworny et al., 1988). Furthermore, increased hypothalamic neuropeptide vasoactive intestinal polypeptide (VIP) and decreased hypothalamic gonadotropin-releasing hormone (GnRH) are reported to be correlated with increased PRL and decreased LH secretion in incubating chickens, respectively. The VIP as an avian PRL-releasing hormone can increase the expression and release of PRL in pituitary gland (Macnamee et al., 1986; Opel et al., 1988; El Halawani et al., 1990; Rozenboim et al., 1993). In addition to VIP, neurotransmitter dopamine (DA), 5-hydroxytryptophan (5-HTP) and dynorphin are also reported to be involved in the secretion and release of avian PRL (Youngren et al., 1993; el Halawani et al., 1995; Youngren et al., 1996).

Although, neuroendocrine plays a major role for the initiation of avian incubation behavior, the overall molecular mechanism involving avian incubation behavior should be further clarified. The high-throughput sequencing technology based on RNA sequencing (RNA-Seq) makes it possible to identify additional candidate genes and signal pathways involved in the regulation of avian incubation behavior. A total of 19 differentially expressed genes (DEGs) were screened out in the hypothalamus between laying and incubating geese (Liu et al., 2018). The down-regulated hypocretin (HCRT) and up-regulated pro-opiomelanocortin (POMC) in the hypothalamus of incubating geese may be responsible for appetite reduction (Liu et al., 2018). Similarly, transcriptome by cap analysis of gene expression identified 217 hypothalamic DEGs including appetite-related transthyretin (TTR) and prolactin-releasing peptide (PrRP) in incubating Silkie hens (Takeda and Ohkubo, 2019). In tree swallows (Tachycineta bicolor), 188 DEGs were identified in hypothalamus between territory establishment and incubation (Bentz et al., 2019). Further analysis revealed that DEGs whch are related to neuroplasticity, signaling and DNA damage were highly expressed during incubation (Bentz et al., 2019). In Muscovy ducks (Cairina moschata), 614 DEGs were identified in hypothalamus during the transition from egg-laying to incubation, and Gene Ontology Term (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis further indicated that serotonergic synapse, dopaminergic synapse, GABAergic synapse and glutamatergic synapse pathway seemly played critical roles in the process from egg-laying to incubation (Ye et al., 2019). Considering the complexity and variety differences of reproductive behavior in different poultry breeds, it is essential to understand the genetic basis of the transition from egg-laying to incubation phase of chickens at transcriptome level.

It is known that China has a wide variety of indigenous poultry, with more than 100 native chicken breeds (Chen et al., 2021). Broodiness is considered to be a behavioral trait observed in most common breeds of domestic chickens with the exception of the White Leghorn (Romanov et al., 1999; Romanov et al., 2002). Many studies have shown that there are different incubation characteristics among different breeds of chickens (Xu et al., 2010a; Xu et al., 2010b; Zhou et al., 2008). Changshun green-shell laying hen is a notable indigenous chicken breed in Guizhou province, China, and has strong broodiness. It is well known for its more nutritious green-shell eggs with better amino acid composition, higher contents of protein and lower fat and cholesterol content. Recently, it has become an important model to study incubation behavior of poultry due to its strong tendency for broodiness (Chen et al., 2024). Considering the fact that the overall molecular mechanism involving incubation behavior in domestic chickens still needs to be further clarified, we therefore comprehensively analyzed the hypothalamic transcriptome of Changshun green-shell laying hens at egg-laying period (LP) and incubation period (BP) in this study. Candidate genes involved in chicken incubation were screened out, and related signal pathways were evaluated through KEGG and GO enrichment analysis. The main question addressed in this study is how the hypothalamic transcriptome of Changshun green-shell laying hens are altered during these 2 distinct reproductive phases. By characterizing the hypothalamic transcriptome, this study advances poultry science by illuminating the genetic basis of incubation behavior in avian species. Meanwhile, the results of the present study will further reveal the complexity of reproductive behavior in different breeds of chickens, and provide new insights into the regulation mechanism of incubation behavior in poultry.

MATERIALS AND METHODS

Ethics Statement

The methods and procedures in the present study were conducted in accordance with the relevant guidelines formulated by the Ministry of Science and Technology of the People's Republic of China. The ethical approval was obtained from the Animal Ethics Committee of the College of Biological Science and Agriculture, Qiannan Normal University for Nationalities (AEC No. QNUN2022023).

Sample Collection

In the present study, the Changshun green-shell laying hens were obtained from Changshun Sanyuan Agricultural Development Co., Ltd., China and were then raised in the poultry breeding farm of Qiannan Normal University for Nationalities. 100 females and 15 males were reared on the floor with litter and artificial nest and exposed to natural temperature conditions. The Changshun hens were then divided into egg-laying hens and incubating hens according to the nesting behavior and number of eggs laid by hens at 28 weeks of age. Chickens in the phase of the nesting process were first identified by their nesting behaviors. Those chickens sat in the nest while exhibiting characteristic clucking, aggressive or defensive behavior for one week were sorted as incubation, further confirmation can be obtained by anatomical observation of a lack of hierarchical follicles in ovaries (Figure 1B). On the other hand, the egg-laying chickens were distinguished by the continuous sequence of ovulation, and further confirmed by the presence of hierarchical follicles on ovaries (Figure 1A). Finally, a total of eight hens were captured during LP (n = 4) and BP (n = 4). Hens were euthanized with exsanguination under sodium pentobarbital anesthesia (60 mg/kg), and the hypothalamus tissues were rapidly dissected out from brain according to the landmarks of the optic chiasm rostrally and the mammillary bodies caudally which were described as previous studies (Xu et al., 2011; Piórkowska et al., 2018) and then frozen in liquid nitrogen and then transferred to -80°C in the lab until further analysis.

Figure 1.

Figure 1

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Ovary morphology of chicken hens at LP (A) and BP (B).

RNA Isolation and Sequencing

Total RNA from four individuals in each of the LP and BP groups was extracted from hypothalamus tissues using the Trizol reagent (Life technologies, CA) in accordance with the manufacturer's instructions. The NanoDrop 2000 (Thermo Fisher Scientific, Wilmington, DE) and electrophoresis were used to analyze the concentration and quality of the total RNA. The RNA Nano 6000 Assay Kit of the Agilent Bioanalyzer 2100 system (Agilent Technologies, CA) was used to evaluate the integrity of samples. The libraries were sequenced on an Illumina NovaSeq6000 platform using 150 bp paired-end reads in accordance with the manufacturer's instructions.

Principal Component Analysis and Differential Expression Analysis

Raw sequences were firstly transformed into clean reads through removing adaptor sequences and discarding low-quality sequences. Hisat2 tools software (v2.2.1) was then used to map against the chicken reference genome (Gallus_gallus.GRCg6a_release106.genome.fa) (Kim et al., 2015). Both known and novel transcripts from Hisat2 alignment results were detected by the method of the StringTie Reference Annotation Based Transcript (v2.2.1) (Pertea et al., 2015). The gene function was annotated with the KEGG, Eukaryotic Orthologous Groups of proteins, National Center for Biotechnology Information for non-redundant proteins, Protein family, GO and Swiss-Prot databases. The similarity between the 2 groups was assessed by PCA. DEGs were identified using the DESeq2 (v1.30.1) (Love et al., 2014). DESeq2 provides statistical routines for determining differential expression in digital gene expression data using a model based on the negative binomial distribution. The resulting P-values were adjusted using the Benjamini-Hochberg corrections. Genes with an adjusted P-value < 0.05 and Fold Change ≥1.5 found by DESeq2 were considered as statistically differentially expressed.

KEGG Pathway, GO Enrichment Analysis and protein-protein interaction

The clusterProfiler package (v3.16.1) implemented the GO enrichment analysis of DEGs, and KOBAS software (v3.0) was then implied to test the statistical enrichment of DEGs in KEGG pathways (Mao et al., 2005; Young et al., 2010). The protein-protein interaction (PPI) analysis was performed using Cytoscape (v3.5.1) (Shannon et al., 2003). Circle node represents a protein, rectangle node represents a KEGG pathway. The solid line represents an interaction between 2 proteins, and the dashed line represents the edge of KEGG pathway in the PPI network.

Gene Expression Analysis by Quantitative Real-Time PCR

Previous studies showed that POMC, FST, VIP and UCN3 might be implicated in avian broodiness (Ogino et al., 2014; Dunn et al., 2015; Liu et al., 2018). Therefore, these 4 genes, including POMC, FST, VIP and UCN3, were selected to further validate the results of RNA-seq. The primers designed with Primer 5 were listed in the Table S1. The relative mRNA expression levels were calculated by the 2−ΔΔCt method with the β-actin used as an internal control (Livak and Schmittgen, 2001). Data was analyzed using the Student's t-test after testing for the homogeneity of variance with Levene's test. All data are presented as the mean ± SD, and statistical significance was shown as *P < 0.05.

RESULTS

RNA Sequencing Quality Assessment and Transcriptome Alignment

A total of eight cDNA libraries (4 egg-laying period samples and 4 incubation period samples) were constructed and sequenced on the Illumina NovaSeq platform. The data quality and mapping data statistics of RNA-seq libraries were shown in Table 1. The clean reads from each library averaged more than 19 million. The base percentage of the Q20 and Q30 was above 98.21% and 94.79%, respectively, and the GC content of eight hypothalamus samples ranged from 48.35% to 48.87%. More than 93.51% of clean reads were perfectly mapped to the reference genome of Gallus gallus. The percentage of multiple and uniquely mapped reads in clean reads ranged from 1.77 to 2.00% and 91.51 to 92.44%, respectively. The results indicated that the transcriptome data were reliable and suitable for subsequent analysis.

Table 1.

Data quality and mapping data statistics of RNA-seq libraries.

Sample Clean reads Clean bases Q20 (%) Q30 (%) GC (%) Total mapped Multiple mapped Uniquely mapped
LP1 23,992,696 7,171,231,500 98.36 95.19 48.87 44,955,805 (93.69%) 928,830 (1.94%) 44,026,975 (91.75%)
LP2 19,695,915 5,888,849,074 98.42 95.33 48.64 37,063,622 (94.09%) 742,217 (1.88%) 36,321,405 (92.21%)
LP3 21,802,114 6,517,860,002 98.26 94.88 48.79 40,910,108 (93.82%) 838,408 (1.92%) 40,071,700 (91.90%)
LP4 22,479,323 6,723,723,904 98.28 94.95 48.80 42,066,411 (93.57%) 886,129 (1.97%) 41,180,282 (91.60%)
BP1 20,897,622 6,249,143,208 98.41 95.30 48.36 39,265,486 (93.95%) 738,321 (1.77%) 38,527,165 (92.18%)
BP2 21,013,381 6,281,087,476 98.26 94.92 48.86 39,299,285 (93.51%) 841,865 (2.00%) 38,457,420 (91.51%)
BP3 21,392,712 6,396,957,128 98.21 94.79 48.60 40,096,498 (93.72%) 762,981 (1.78%) 39,333,517 (91.93%)
BP4 24,200,913 7,238,721,602 98.40 95.25 48.35 45,599,155 (94.21%) 856,156 (1.77%) 44,742,999 (92.44%)
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LP, hypothalamic samples of egg-laying group; BP, hypothalamic samples of incubation group; Q20, sequencing error rates lower than 1%; Q20, sequencing error rates lower than 1%; Q30, sequencing error rates lower than 0.1%; GC, the percentage of G and C bases in clean data.

Differentially Expressed Analysis

PCA was subsequently performed to analyze the hypothalamic samples. As shown in Figure 2A, 8 samples were obviously divided into 2 parts in the PCA score plot of hypothalamic transcriptome, indicating that there was obvious difference in mRNA expression between LP and BP groups. Subsequently, square correlation coefficient of gene expression levels between 4 individuals within each group was applied in the present study (Figure 2B). Pearson correlation analysis demonstrated a positive correlation between 2 groups. Meanwhile, the correlation coefficient of gene expression levels between samples was observed to be higher than 0.795, indicating that the following analysis of DEGs would be reliable and reasonable. Further analysis revealed that a total of 942 DEGs were identified in chicken hypothalamus, including 637 up-regulated and 305 down-regulated genes (Figure 3 and Table S2). Subsequently, hierarchical clustering analysis of DEGs showed that hypothalamic samples from the same group were clustered together, and the expression patterns of the genes in the hypothalamic samples between LP and BP groups were visualized in heatmap (Figure S1).

Figure 2.

Figure 2

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Features of sequencing data. (A) PCA score plot of hypothalamus transcriptomes. Red and green nodes represent individuals from incubation phase (BP) and egg-laying phase (LP), respectively. (B) Pearson correlation analysis of LP and BP samples. LP1, LP2, LP3 and LP4 are hypothalamic samples from egg-laying hens, and BP1, BP2, BP3 and BP4 are hypothalamic samples from incubation hens. Color indicates the value of Pearson correlation. The more concentrated the points near the diagonal, the stronger the correlation of gene expression levels in the 2 samples, and the points deviating from the diagonal represent differentially expressed genes.

Figure 3.

Figure 3

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Volcano map of all expressed genes. The horizontal and longitudinal coordinates represent the fold changes of genes and the statistical significance of the changes in gene expression, respectively. Blue and red plots represent significantly down- and up-regulated genes, respectively.

KEGG Pathway and GO Enrichment Analysis

The KEGG and GO enrichment analysis were performed to understand the biological functions of DEGs identified in hypothalamus. As shown in Figure 4, the top 10 significantly enriched KEGG pathways in hypothalamus were neuroactive ligand-receptor interaction, hippo signaling pathway, focal adhesion, complement and coagulation cascades, ECM-receptor interaction, parathyroid hormone synthesis, secretion and action, hedgehog signaling pathway, MAPK signaling pathway, arachidonic acid metabolism, and endocrine and other factor-regulated calcium reabsorption. Notably, synaptic vesicle cycle and JAK-STAT signaling pathway had the largest enrichment factor. GO enrichment analysis indicated that the functions of these DEGs were classified into 3 main categories, including biological process, cellular component and molecular function, and 37 subcategories (Figure 5 and Table S3). In the category of biological process, dominant subcategories included cellular process (523), biological regulation (398) and response to stimulus (277). Among cellular component terms, cellular anatomical entity (576), intracellular (348) and protein-containing complex (121) were highly represented. For molecular function, binding (475) and catalytic activity (216) were most represented, followed by molecular function regulator (82). Only a few genes were assigned to subcategories of translation regulator activity (1), protein folding chaperone (2) and other organism part (1) (Figure 5 and Table S3).

Figure 4.

Figure 4

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Top 18 KEGG pathways enriched by the DEGs in hypothalamus between LP and BP groups. The longitudinal and horizontal coordinates represent the name of pathway and the pathway corresponding rich factor, respectively. Each bubble represents a KEGG pathway. Bubble size indicates the number of DEGs in each pathway, and the color corresponds to the q value of each pathway.

Figure 5.

Figure 5

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GO classification of DEGs identified in hypothalamus between LP and BP groups. The longitudinal and horizontal coordinates represent the GO term and the number of DEGs annotated to the term, respectively. Orange, green and purple indicate the molecular function, cellular component and biological process, respectively.

Interaction Network Construction of DEGs

To further identify the hub genes associated with incubation behavior in hypothalamus, the DEGs from the hypothalamus between LP and BP groups were used to build the protein-protein interaction (PPI) networks which were visualized in Cytoscape. As shown in Figure 6, the PPI network of DEGs contained 201 nodes and 444 edges, and were mainly enriched into 9 important pathways including neuroactive ligand-receptor interaction, MAPK signaling pathway, focal adhesion, ECM-receptor interaction, hedgehog signaling pathway, hippo signaling pathway-multiple species, endocrine and other factor-regulated calcium reabsorption, parathyroid hormone synthesis, secretion and action, and arachidonic acid metabolism. The hub nodes with the highest degree in PPI network were proopiomelanocortin (POMC), insulin like growth factor 1 receptor (IGF1R), chondroadherin (CHAD), vinculin (VCL) and myosin light chain 9 (MYL9), which are mainly involved in food intake, reproduction and development. Our data indicated that POMC, IGF1R, CHAD, VCL and MYL9 might be key candidate DEGs because they seemed to be located in a core position in the regulatory networks (Figure 6).

Figure 6.

Figure 6

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PPI networks of DEGs in hypothalamus. Red and green circle nodes indicate up-regulated and down-regulated DEGs, respectively. Blue rectangles indicate the KEGG pathway. Interactions were shown as solid lines between proteins, and edges of KEGG pathway in dashed lines.

Validation of DEGs by qRT-PCR

To evaluate the RNA-seq results, 4 genes, including up-regulated POMC, FST and VIP and down-regulated UCN3, were randomly selected from DEGs identified in hypothalamus for qRT-PCR analysis. While there are clear differences in the expression levels of these selected DEGs, the expression trends validated via qRT-PCR were consistent with our RNA-Seq results, confirming that the RNA-seq results were reliable (Figure 7).

Figure 7.

Figure 7

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qRT-PCR validation of DEGs identified in transcriptome sequencing. The results were expressed as mean ± SD. * p < 0.05. LP, egg-laying group; BP, incubation group.

DISCUSSION

Broodiness in birds is known to be controlled accurately by the central nervous system which are possibly associated with multiple neuroendocrine hormones and neurotransmitters secreted by hypothalamus and pituitary gland. The hypothalamus, as a relay center of the endocrine system, plays a critical role in chicken broodiness. To explore the regulatory mechanisms underlying broodiness in Changshun chickens, we performed an analysis of whole hypothalamus transcriptome differences in the present study. The RNA sequencing data obtained from hypothalamus of Changshun chickens will provide us novel insights into broodiness in poultry.

Neuroactive ligand-receptor interaction pathway is known to play an important role in regulating the reproductive behavior of poultry. In this study, 38 DEGs in hypothalamus, including VIP, HCRT, NMU, TSHR, UCN3, NTS, and TRHR3, were identified to enriched in neuroactive ligand-receptor interaction pathway. The onset and maintain of incubation behavior is known to be associated with hyperprolactinemia in domestic chickens. Hypothalamic VIP, as a PRL-releasing factor, plays an important role in the regulation of avain broodiness. We observed that the expression of VIP was significantly increased in BP groups, indicating that the transcriptome data in the present study were reliable for subsequent analysis. During the incubation phase, hens reduce food intake and spend most of their time in the nest to warm their eggs. In birds, appetite-related HCRT may play critical roles in incubation phase. Previous studies indicated that decreased HCRT in hypothalamus may involve in appetite reduction in incubating Tianfu meat geese (Liu et al., 2018). Similarly, we also found that HCRT was decreased in incubating Changshun green-shell laying hens. Neuromedin U (NMU) is a catabolic neuropeptide and implicate in energy expenditure, feed intake, stress response, and circadian rhythm (Kamisoyama et al., 2007; Teranishi and Hanada, 2021; Uyanga et al., 2023). Meanwhile, NMU can induce wing-flapping behavior of chicks (Kamisoyama et al., 2007). Whole-genome sequencing reveals that thyroid stimulating hormone receptor (TSHR) may be a domestication locus under selection during chicken domestication (Rubin et al., 2010). A subsequent investigation on the domestic White Leghorns and the wild ancestor Red Junglefowls further indicated that TSHR can affect domestication-related traits of chickens, including incubation time, fearful behaviors and the number of aggressive behaviors (Karlsson et al., 2015). Urocortin 3 (UCN3) is a member of the corticotropin-releasing hormone peptide family, and is expressed predominantly in hypothalamus, pons and medulla of chicken brain (Grommen et al., 2017). Exogenous UCN3 has been shown to decrease food intake and crop-emptying rate and increase rectal temperature, the number of jumps, wing-flaps and scratching behaviors, indicating the complexity of the functions of UCN3 in chickens (Ogino et al., 2014). Neurotensin (NTS) is an anorectic neuropeptide neurotransmitter which is expressed in the nervous system and the gastrointestinal system of mammals (Reinecke, 1985). Avian NTS was reported to be initially purified from chicken intestine (Carraway and Bhatnagar, 1980). A wealth of studies indicated that NTS is involved in gastrointestinal functions, such as the gastrointestinal motility, pancreatic exocrine secretion, pepsin output, and hepatic bile acid secretion in chickens (Rawson et al., 1990; DeGolier et al., 1997; DeGolier et al., 1999; Gui et al., 2000). In addition, mamalian NTS appears to exert a direct or indirect stimulatory influence on the synthesis of GnRH and DA and secretion of PRL (Rostène and Alexander, 1997; Memo et al., 1986; Alexander, 1993). Thyrotropin-releasing hormone receptor 3 (TRHR3) has been recently established to be a novel functional receptor of thyrotropin-releasing hormone (TRH) in chickens (Li et al., 2020). It is widely expressed in chicken tissues examined with a relatively higher expression level noted in the muscle, testes, anterior pituitary, hindbrain, spinal cord, and hypothalamus (Li et al., 2020). Functional analysis revealed that the chicken TRHR3 might mediate TRH function via the intracellular Gq protein-related signaling pathway (Li et al., 2020). A recent study indicated that TRHR3 might be involved in the release of PRL in the metamorphosing bullfrog larvae (Nakano et al., 2018). Increased TRHR3 in the present study indicated that it might play an important role in the transition from laying to incubation in chickens.

POMC, IGF1R, CHAD, VCL and MYL9 were suggested to be key candidate DEGs because they were located in a core position in the regulatory networks. POMC is known to be a polypeptide precursor of several hormones, including adrenocorticotropic hormone, opioidhormone β-endorphin, β-lipotropin, and α-, β-, and γ-melanotropin, in many species (Bertagna, 1994). In avians, the analysis of mRNA expression pattern showed that POMC was mainly expressed in the pituitary, brain, hypothalamus (Gerets et al., 2000; Liu et al., 2020). Hypothalamic POMC is identified to be associated with food intake in chickens (Takeda and Ohkubo, 2019). Increasing evidence has indicated the important role of POMC in regulating the avian reproduction, including incubation behavior. The polymorphism of POMC has been recently reported to be closely association with reproduction traits in chickens (Liu et al., 2020). Meanwhile, increased POMC in hypothalamus can cause appetite reduction of incubating avians, which is considered to be a prerequisite to initiate incubation. Transcriptome analysis further revealed that POMC seemingly occupied a key position in the regulatory network of incubating avian hypothalamus (Liu et al., 2018; Takeda and Ohkubo, 2019). Consistently, POMC were observed to increase in incubating Changshun hens. Interestingly, POMC was reported to be unchanged in incubating white leghorn hens, which seems to be contradictory to previous findings (Dunn et al., 2015). Our results further indicated the complexity of differences in incubation behavior of different chicken breeds. IGF1R as a membrane glycoprotein mediates the half-life time and activity of IGF-1 and IGF-2 in chickens. It has been shown to play critical roles on the chicken growth, carcass, meat quality traits and production performance (Amills et al., 2003; Lei et al., 2008; Bai et al., 2023). Additionally, IGF-1/IGF1R axis is reported to be involved in cerebral angiogenesis, neurogenesis and neuroprotection in animals (Zhu et al., 2008; Zhang et al., 2019). Interestingly, starvation induces the expression of IGF1R in various tissues, excluding brain, suggesting the functional complexity of IGF1R (Matsumura et al., 1996). CHAD, as an ECM-related protein, is mainly localized in the territorial matrix of the deeper parts of the articular cartilage (Shen et al., 1998). It mediates intracellular signal transduction between the ECM and chondrocytes via binding with the α2β1 integrin (Camper et al., 1997). In chickens, CHAD is identified to involve in the intramuscular fat deposition (Zhang et al., 2020). VCL is a cytoplasmic protein which is a critical component of the membrane-associated adhesion complexes that tether cells to the extracellular matrix and adjacent cells (Peng et al., 2011). Although VCL has no enzymatic activity, it might play important roles in animal reproduction. The normal spermiogenesis in rats seemingly depends on the peripheral distribution of sertoli cell f-actin and vinculin (Muffly et al., 1993). Estrogen, as an important regulator of the function of the anterior pituitary gland, is reported to regulate the expression of pituitaric VCL (Blake et al., 2005). However, whether estrogen acted directly on the anterior pituitary gland or indirectly via the hypothalamus or by some other means is still unknown. String network analysis indicated that spectrin alpha chain, non-erythrocytic 1 (SPTAN1) may mediate estradiol-17β-induced masculinization and defeminization, and disrupted reproductive function in adult rats through association with kirrel, actinin, alpha 4 and VCL (Govindaraj and Rao, 2016). MYL9 gene encodes a regulatory light chain which is required for the stabilization of myosin II and cellular integrity (Park et al., 2011). In chickens, MYL9 is reported to be associated with muscle-fiber development and cold stress (Chen et al., 2014; Ye et al., 2017). Additionally, MYL9 is involved in the interactions between feed efficiency and meat quality in chickens (Poompramun et al., 2021).

In conclusion, we characterized and evaluated the hypothalamic transcriptome in LP and BP Changshun hens. The results suggest that neuroactive ligand-receptor interaction, hippo signaling pathway, and focal adhesion are critical for incubation behavior in Changshun hens. Five candidate genes (POMC, IGF1R, CHAD, VCL, and MYL9) might play crucial roles in the process of chicken incubation behavior. The identification of specific genes and pathways in the present study provide valuable insights into the molecular mechanisms underlying chicken incubation behavior.

DISCLOSURES

The authors declare no conflicts of interest.

ACKNOWLEDGMENTS

This study was supported by Guizhou Provincial Basic Research Program (Natural Science) (ZK[2021]167, ZK[2023]455); Natural Science Research Project of the Department of Education of Guizhou Province of China (KY[2020]071, Innovation team No.[2023]089 and No.[2022]066).

Author Contributions: Z. C. and D. W. designed this study, Z. C., D. W., J. C., and R. M. performed the transcriptome analysis. Z. C. and R. M. wrote the manuscript. All authors approved this manuscript.

Footnotes

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.psj.2024.103950.

Appendix. Supplementary materials

mmc1.docx (285.1KB, docx)
mmc2.docx (11.6KB, docx)
mmc3.xlsx (260.5KB, xlsx)
mmc4.docx (14.6KB, docx)

REFERENCES

  1. Alexander M.J. Estrogen-regulated synthesis of neurotensin in neurosecretory cells of the hypothalamic arcuate nucleus in the female rat. Endocrinology. 1993;133:1809–1816. doi: 10.1210/endo.133.4.8404623. [DOI] [PubMed] [Google Scholar]
  2. Amills M., Jiménez N., Villalba D., Tor M., Molina E., Cubiló D., Marcos C., Francesch A., Sànchez A., Estany J. Identification of three single nucleotide polymorphisms in the chicken insulin-like growth factor 1 and 2 genes and their associations with growth and feeding traits. Poult. Sci. 2003;82:1485–1493. doi: 10.1093/ps/82.10.1485. [DOI] [PubMed] [Google Scholar]
  3. Bai J., Wang X., Zhao Y. Research Note: Association of insulin-like growth factor 1 receptor gene polymorphism with production performance in Savimalt and French Giant meat-type quails. Poult. Sci. 2023;102 doi: 10.1016/j.psj.2023.103074. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Bentz A.B., Rusch D.B., Buechlein A., Rosvall K.A. The neurogenomic transition from territory establishment to parenting in a territorial female songbird. BMC Genomics. 2019;20:819. doi: 10.1186/s12864-019-6202-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Bertagna X. Proopiomelanocortin-derived peptides. Endocrinol. Metab. Clin. North. Am. 1994;23:467–485. [PubMed] [Google Scholar]
  6. Blake C.A., Brown L.M., Duncan M.W., Hunsucker S.W., Helmke S.M. Estrogen regulation of the rat anterior pituitary gland proteome. Exp. Biol. Med. 2005;230:800–807. doi: 10.1177/153537020523001104. [DOI] [PubMed] [Google Scholar]
  7. Camper L., Heinegârd D., Lundgren-Akerlund E. Integrin α2β1 is a receptor for the cartilage matrix protein chondroadherin. J. Cell. Biol. 1997;138:1159–1167. doi: 10.1083/jcb.138.5.1159. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Carraway R., Bhatnagar Y.M. Isolation, structure and biologic activity of chicken intestinal neurotensin. Peptides. 1980;1:167–174. doi: 10.1016/0196-9781(80)90082-0. [DOI] [PubMed] [Google Scholar]
  9. Chen S., Chen K., Xu J., Li F., Ding J., Ma Z., Li G., Li H. Insights Into mRNA and long non-coding RNA profiling RNA sequencing in uterus of chickens with pink and blue eggshell colors. Front. Vet. Sci. 2021;8 doi: 10.3389/fvets.2021.736387. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Chen X.Y., Li R., Wang M., Geng Z.Y. Identification of differentially expressed genes in hypothalamus of chicken during cold stress. Mol. Biol. Rep. 2014;41:2243–2248. doi: 10.1007/s11033-014-3075-z. [DOI] [PubMed] [Google Scholar]
  11. Chen Z., Wen D., Zhang Y., Chen J., Pan F., Zhang W., Zhou S., Wang F., Mu R. Pituitary transcriptome profile from laying period to incubation period of Changshun green-shell laying hens. BMC Genomics. 2024;25:309. doi: 10.1186/s12864-024-10233-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. de la Iglesia H.O., Schwartz W.J. Minireview: timely ovulation: circadian regulation of the female hypothalamo-pituitary-gonadal axis. Endocrinology. 2006;147:1148–1153. doi: 10.1210/en.2005-1311. [DOI] [PubMed] [Google Scholar]
  13. Degolier T.F., Duke G.E., Carraway R.E. Neurotensin decreases pepsin output and gastrointestinal motility in chickens. Poult. Sci. 1997;76:1435–1439. doi: 10.1093/ps/76.10.1435. [DOI] [PubMed] [Google Scholar]
  14. DeGolier T.F., Place A.R., Duke G.E., Carraway R.E. Neurotensin modulates the composition of pancreatic exocrine secretions in chickens. J. Exp. Zool. 1999;283:455–462. doi: 10.1002/(sici)1097-010x(19990301/01)283:4/5<455::aid-jez15>3.3.co;2-n. [DOI] [PubMed] [Google Scholar]
  15. Dunn I.C., Wilson P.W., D'Eath R.B., Boswell T. Hypothalamic agouti-related peptide mRNA is elevated during natural and stress-induced anorexia. J. Neuroendocrinol. 2015;27:681–691. doi: 10.1111/jne.12295. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. El Halawani M.E., Burke W.H., Millam J.R., Fehrer S.C., Hargis B.M. Regulation of prolactin and its role in gallinaceous bird reproduction. J. Exp. Zool. 1984;232:521–529. doi: 10.1002/jez.1402320319. [DOI] [PubMed] [Google Scholar]
  17. el Halawani M.E., Silsby J.L., Mauro L.J. Vasoactive intestinal peptide is a hypothalamic prolactin-releasing neuropeptide in the turkey (Meleagris gallopavo) Gen. Comp. Endocrinol. 1990;78:66–73. doi: 10.1016/0016-6480(90)90048-q. [DOI] [PubMed] [Google Scholar]
  18. el Halawani M.E., Youngren O.M., Rozenboim I., Pitts G.R., Silsby J.L., Phillips R.E. Serotonergic stimulation of prolactin secretion is inhibited by vasoactive intestinal peptide immunoneutralization in the turkey. Gen. Comp. Endocrinol. 1995;99:69–74. doi: 10.1006/gcen.1995.1086. [DOI] [PubMed] [Google Scholar]
  19. Geng A.L., Xu S.F., Zhang Y., Zhang J., Chu Q., Liu H.G. Effects of photoperiod on broodiness, egg-laying and endocrine responses in native laying hens. Br. Poult. Sci. 2014;55:264–269. doi: 10.1080/00071668.2013.878782. [DOI] [PubMed] [Google Scholar]
  20. Gerets H.H., Peeters K., Arckens L., Vandesande F., Berghman L.R. Sequence and distribution of pro-opiomelanocortin in the pituitary and the brain of the chicken (Gallus gallus) J. Comp. Neurol. 2000;417:250–262. [PubMed] [Google Scholar]
  21. Govindaraj V., Rao A.J. Proteomic identification of non-erythrocytic alpha-spectrin-1 down-regulation in the pre-optic area of neonatally estradiol-17β treated female adult rats. Horm. Mol. Biol. Clin. Investig. 2016;26:165–172. doi: 10.1515/hmbci-2016-0008. [DOI] [PubMed] [Google Scholar]
  22. Grommen S.V.H., Scott M.K., Darras V.M., De Groef B. Spatial and temporal expression profiles of urocortin 3 mRNA in the brain of the chicken (Gallus gallus) J. Comp. Neurol. 2017;525:2583–2591. doi: 10.1002/cne.24223. [DOI] [PubMed] [Google Scholar]
  23. Gui X., Degolier T.F., Duke G.E., Carraway R.E. Neurotensin elevates hepatic bile acid secretion in chickens by a mechanism requiring an intact enterohepatic circulation. Comp. Biochem. Physiol. C Toxicol. Pharmacol. 2000;127:61–70. doi: 10.1016/s0742-8413(00)00126-2. [DOI] [PubMed] [Google Scholar]
  24. Kamisoyama H., Honda K., Saneyasu T., Sugahara K., Hasegawa S. Central administration of neuromedin U suppresses food intake in chicks. Neurosci. Lett. 2007;420:1–5. doi: 10.1016/j.neulet.2007.03.062. [DOI] [PubMed] [Google Scholar]
  25. Karlsson A.C., Svemer F., Eriksson J., Darras V.M., Andersson L., Jensen P. The effect of a mutation in the thyroid stimulating hormone receptor (TSHR) on development, behaviour and TH levels in domesticated chickens. PloS One. 2015;10 doi: 10.1371/journal.pone.0129040. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Kim D., Langmead B., Salzberg S.L. HISAT: a fast spliced aligner with low memory requirements. Nat. Methods. 2015;12:357–360. doi: 10.1038/nmeth.3317. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Lei M., Peng X., Zhou M., Luo C., Nie Q., Zhang X. Polymorphisms of the IGF1R gene and their genetic effects on chicken early growth and carcass traits. BMC Genet. 2008;9:70. doi: 10.1186/1471-2156-9-70. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Li X., Li Z., Deng Y., Zhang J., Li J., Wang Y. Characterization of a novel thyrotropin-releasing hormone receptor, TRHR3, in chickens. Poult. Sci. 2020;99:1643–1654. doi: 10.1016/j.psj.2019.10.062. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Liu H., Wang J., Li L., Han C., He H., Xu H. Transcriptome analysis revealed the possible regulatory pathways initiating female geese broodiness within the hypothalamic-pituitary-gonadal axis. PLos One. 2018;13 doi: 10.1371/journal.pone.0191213. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Liu K., Wen Y.Y., Liu H.H., Cao H.Y., Dong X.Y., Mao H.G., Yin Z.Z. POMC gene expression, polymorphism, and the association with reproduction traits in chickens. Poult. Sci. 2020;99:2895–2901. doi: 10.1016/j.psj.2019.12.070. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Livak K.J., Schmittgen T.D. Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔCT method. Methods. 2001;25:402–408. doi: 10.1006/meth.2001.1262. [DOI] [PubMed] [Google Scholar]
  32. Love M.I., Huber W., Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550. doi: 10.1186/s13059-014-0550-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Macnamee M.C., Sharp P.J., Lea R.W., Sterling R.J., Harvey S. Evidence that vasoactive intestinal polypeptide is a physiological prolactin-releasing factor in the bantam hen. Gen. Comp. Endocrinol. 1986;62:470–478. doi: 10.1016/0016-6480(86)90057-2. [DOI] [PubMed] [Google Scholar]
  34. Mao X., Cai T., Olyarchuk J.G., Wei L. Automated genome annotation and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary. Bioinformatics. 2005;21:3787–3793. doi: 10.1093/bioinformatics/bti430. [DOI] [PubMed] [Google Scholar]
  35. March J.B., Sharp P.J., Wilson P.W., Sang H.M. Effect of active immunization against recombinant-derived chicken prolactin fusion protein on the onset of broodiness and photoinduced egg laying in bantam hens. J. Reprod. Fertil. 1994;101:227–233. doi: 10.1530/jrf.0.1010227. [DOI] [PubMed] [Google Scholar]
  36. Matsumura Y., Domeki M., Sugahara K., Kubo T., Roberts C.T., Jr, LeRoith D., Kato H. Nutritional regulation of insulin-like growth factor-I receptor mRNA levels in growing chickens. Biosci. Biotechnol. Biochem. 1996;60:979–982. doi: 10.1271/bbb.60.979. [DOI] [PubMed] [Google Scholar]
  37. Memo M., Castelletti L., Valerio A., Missale C., Spano P.F. Identification of neurotensin receptors associated with calcium channels and prolactin release in rat pituitary. J. Neurochem. 1986;47:1682–1688. doi: 10.1111/j.1471-4159.1986.tb13074.x. [DOI] [PubMed] [Google Scholar]
  38. Muffly K.E., Nazian S.J., Cameron D.F. Junction-related Sertoli cell cytoskeleton in testosterone-treated hypophysectomized rats. Biol. Reprod. 1993;49:1122–1132. doi: 10.1095/biolreprod49.5.1122. [DOI] [PubMed] [Google Scholar]
  39. Nakano M., Hasunuma I., Minagawa A., Iwamuro S., Yamamoto K., Kikuyama S., Machida T., Kobayashi T. Possible involvement of thyrotropin-releasing hormone receptor 3 in the release of prolactin in the metamorphosing bullfrog larvae. Gen. Comp. Endocrinol. 2018;267:36–44. doi: 10.1016/j.ygcen.2018.05.029. [DOI] [PubMed] [Google Scholar]
  40. Ogino M., Okumura A., Khan M.S., Cline M.A., Tachibana T. Comparison of brain urocortin-3 and corticotrophin-releasing factor for physiological responses in chicks. Physiol. Behav. 2014;125:57–61. doi: 10.1016/j.physbeh.2013.11.006. [DOI] [PubMed] [Google Scholar]
  41. Opel H., Proudman J.A. Stimulation of prolactin release in turkeys by vasoactive intestinal peptide. Proc. Soc. Exp. Biol. Med. 1988;187:455–460. doi: 10.3181/00379727-187-42688. [DOI] [PubMed] [Google Scholar]
  42. Park I., Han C., Jin S., Lee B., Choi H., Kwon J.T., Kim D., Kim J., Lifirsu E., Park W.J. Myosin regulatory light chains are required to maintain the stability of myosin II and cellular integrity. Biochem. J. 2011;434:171–180. doi: 10.1042/BJ20101473. [DOI] [PubMed] [Google Scholar]
  43. Peng X., Nelson E.S., Maiers J.L., DeMali K.A. New insights into vinculin function and regulation. Int. Rev. Cell. Mol. Biol. 2011;287:191–231. doi: 10.1016/B978-0-12-386043-9.00005-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Pertea M., Pertea G.M., Antonescu C.M., Chang T.C., Mendell J.T., Salzberg S.L. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat. Biotechnol. 2015;33:290–295. doi: 10.1038/nbt.3122. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Piórkowska K., Żukowski K., Połtowicz K., Nowak J., Wojtysiak D., Derebecka N., Wesoły J., Ropka-Molik K. Transcriptomic changes in broiler chicken hypothalamus during growth and development. Int. J. Genomics. 2018;6049469:1–10. doi: 10.1155/2018/6049469. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Poompramun C., Hennequet-Antier C., Thumanu K., Sinpru P., Pengsanthia S., Molee W., Molee A., Le Bihan-Duval E., Juanchich A. Revealing pathways associated with feed efficiency and meat quality traits in slow-growing chickens. Animals. 2021;11:2977. doi: 10.3390/ani11102977. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Rawson R.E., Duke G.E., Brown D.R. Effect of avian neurotensin on motility of chicken (Gallus domesticus) lower gut in vivo and in vitro. Peptides. 1990;11:641–645. doi: 10.1016/0196-9781(90)90173-3. [DOI] [PubMed] [Google Scholar]
  48. Reinecke M. Neurotensin. Immunohistochemical localization in central and peripheral nervous system and in endocrine cells and its functional role as neurotransmitter and endocrine hormone. Prog. Histochem. Cytochem. 1985;16:1–172. [PubMed] [Google Scholar]
  49. Riddle O., Baxter R.W., Lahr E.L. Prolactin induces broodiness in fowl. Am. J. Physiol. 1935;111:352–360. [Google Scholar]
  50. Romanov M.N., Talbot R.T., Wilson P.W., Sharp P.J. Inheritance of broodiness in the domestic fowl. Br. Poult. Sci. 1999;40:20–21. doi: 10.1080/00071669986611. [DOI] [PubMed] [Google Scholar]
  51. Romanov M.N., Talbot R.T., Wilson P.W., Sharp P.J. Genetic control of incubation behavior in the domestic hen. Poult. Sci. 2002;81:928–931. doi: 10.1093/ps/81.7.928. [DOI] [PubMed] [Google Scholar]
  52. Rostène W.H., Alexander M.J. Neurotensin and neuroendocrine regulation. Front. Neuroendocrinol. 1997;18:115–173. doi: 10.1006/frne.1996.0146. [DOI] [PubMed] [Google Scholar]
  53. Rozenboim I., Silsby J.L., Tabibzadeh C., Pitts G.R., Youngren O.M., Halawani M.E. Hypothalamic and posterior pituitary content of vasoactive intestinal peptide and gonadotropin-releasing hormones I and II in the turkey hen. Biol. Reprod. 1993;49:622–626. doi: 10.1095/biolreprod49.3.622. [DOI] [PubMed] [Google Scholar]
  54. Rubin C.J., Zody M.C., Eriksson J., Meadows J.R., Sherwood E., Webster M.T., Jiang L., Ingman M., Sharpe T., Ka S., Hallböök F., Besnier F., Carlborg O., Bed'hom B., Tixier-Boichard M., Jensen P., Siegel P., Lindblad-Toh K., Andersson L. Whole-genome resequencing reveals loci under selection during chicken domestication. Nature. 2010;464:587–591. doi: 10.1038/nature08832. [DOI] [PubMed] [Google Scholar]
  55. Shannon P., Markiel A., Ozier O., Baliga N.S., Wang J.T., Ramage D., Amin N., Schwikowski B., Ideker T. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13:2498–2504. doi: 10.1101/gr.1239303. [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Sharp P.J., Macnamee M.C., Sterling R.J., Lea R.W., Pedersen H.C. Relationships between prolactin, LH and broody behaviour in bantam hens. J. Endocrinol. 1988;118:279–286. doi: 10.1677/joe.0.1180279. [DOI] [PubMed] [Google Scholar]
  57. Sharp P.J., Scanes C.G., Williams J.B., Harvey S., Chadwick A. Variations in concentrations of prolactin, luteinizing hormone, growth hormone and progesterone in the plasma of broody bantams (Gallus domesticus) J. Endocrinol. 1979;80:51–57. doi: 10.1677/joe.0.0800051. [DOI] [PubMed] [Google Scholar]
  58. Sharp P.J., Sterling R.J., Talbot R.T., Huskisson N.S. The role of hypothalamic vasoactive intestinal polypeptide in the maintenance of prolactin secretion in incubating bantam hens: observations using passive immunization, radioimmunoassay and immunohistochemistry. J. Endocrinol. 1989;122:5–13. doi: 10.1677/joe.0.1220005. [DOI] [PubMed] [Google Scholar]
  59. Shen Z., Gantcheva S., Mânsson B., Heinegârd D., Sommarin Y. Chondroadherin expression changes in skeletal development. Biochem. J. 1998;330:549–557. doi: 10.1042/bj3300549. [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Sherry D.F., Mrosovsky N., Hogan J.A. Weight loss and anorexia during incubation in birds. J. Comp. Physiol. Psychol. 1980;94:89–98. [Google Scholar]
  61. Takeda M., Ohkubo T. Identification of hypothalamic genes in associating with food intake during incubation behavior in domestic chicken. Anim. Sci. J. 2019;90:1293–1302. doi: 10.1111/asj.13261. [DOI] [PubMed] [Google Scholar]
  62. Teranishi H., Hanada R. Neuromedin U, a Key Molecule in Metabolic Disorders. Int. J. Mol. Sci. 2021;22:4238. doi: 10.3390/ijms22084238. [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Uyanga V.A., Bello S.F., Qian X., Chao N., Li H., Zhao J., Wang X., Jiao H., Onagbesan O.M., Lin H. Transcriptomics analysis unveils key potential genes associated with brain development and feeding behavior in the hypothalamus of L-citrulline-fed broiler chickens. Poult. Sci. 2023;102 doi: 10.1016/j.psj.2023.103136. [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. Xu H., Shen X., Zhou M., Fang M., Zeng H., Nie Q., Zhang X. The genetic effects of the dopamine D1 receptor gene on chicken egg production and broodiness traits. BMC Genet. 2010;11:17. doi: 10.1186/1471-2156-11-17. [DOI] [PMC free article] [PubMed] [Google Scholar]
  65. Xu H.P., Shen X., Zhou M., Luo C.L., Kang L., Liang Y., Zeng H., Nie Q.H., Zhang D.X., Zhang X.Q. The dopamine D2 receptor gene polymorphisms associated with chicken broodiness. Poult. Sci. 2010;89:428–438. doi: 10.3382/ps.2009-00428. [DOI] [PubMed] [Google Scholar]
  66. Xu P., Siegel P.B., Denbow D.M. Genetic selection for body weight in chickens has altered responses of the brain's AMPK system to food intake regulation effect of ghrelin, but not obestatin. Behav. Brain Res. 2011;221:216–226. doi: 10.1016/j.bbr.2011.02.034. [DOI] [PubMed] [Google Scholar]
  67. Ye M., Ye F., He L., Luo B., Yang F., Cui C., Zhao X., Yin H., Li D., Xu H. Transcriptomic analysis of chicken Myozenin 3 regulation reveals its potential role in cell proliferation. PLoS One. 2017;12 doi: 10.1371/journal.pone.0189476. [DOI] [PMC free article] [PubMed] [Google Scholar]
  68. Ye P., Li M., Liao W., Ge K., Jin S., Zhang C., Chen X., Geng Z. Hypothalamic transcriptome analysis reveals the neuroendocrine mechanisms in controlling broodiness of Muscovy duck (Cairina moschata) PloS One. 2019;14 doi: 10.1371/journal.pone.0207050. [DOI] [PMC free article] [PubMed] [Google Scholar]
  69. Young M.D., Wakefield M.J., Smyth G.K., Oshlack A. Gene ontology analysis for RNA-seq: accounting for selection bias. Genome Biol. 2010;11:R14. doi: 10.1186/gb-2010-11-2-r14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  70. Youngren O.M., Pitts G.R., Phillips R.E., el Halawani M.E. Dopaminergic control of prolactin secretion in the turkey. Gen. Comp. Endocrinol. 1996;104:225–230. doi: 10.1006/gcen.1996.0165. [DOI] [PubMed] [Google Scholar]
  71. Youngren O.M., Silsby J.L., Phillips R.E., el Halawani M.E. Dynorphin modulates prolactin secretion in the turkey. Gen. Comp. Endocrinol. 1993;91:224–231. doi: 10.1006/gcen.1993.1121. [DOI] [PubMed] [Google Scholar]
  72. Zadworny D., Shimada K., Ishida H., Sumi C., Sato K. Changes in plasma levels of prolactin and estradiol, nutrient intake, and time spent nesting during the incubation phase of broodiness in the Chabo hen (Japanese bantam) Gen. Comp. Endocrinol. 1988;71:406–412. doi: 10.1016/0016-6480(88)90269-9. [DOI] [PubMed] [Google Scholar]
  73. Zhang J., Liu M., Huang M., Chen M., Zhang D., Luo L., Ye G., Deng L., Peng Y., Wu X., Liu G., Ye W., Zhang D. Ginsenoside F1 promotes angiogenesis by activating the IGF-1/IGF1R pathway. Pharmacol. Res. 2019;144:292–305. doi: 10.1016/j.phrs.2019.04.021. [DOI] [PubMed] [Google Scholar]
  74. Zhang M., Li D., Zhai Y., Wang Z., Ma X., Zhang D., Li G., Han R., Jiang R., Li Z., Kang X., Sun G. The landscape of dna methylation associated with the transcriptomic network of intramuscular adipocytes generates insight into intramuscular fat deposition in chicken. Front. Cell. Dev. Biol. 2020;8:206. doi: 10.3389/fcell.2020.00206. [DOI] [PMC free article] [PubMed] [Google Scholar]
  75. Zhao J., Pan H., Liu Y., He Y., Shi H., Ge C. Interacting networks of the hypothalamic-pituitary-ovarian axis regulate layer hens performance. Genes. 2023;14:141. doi: 10.3390/genes14010141. [DOI] [PMC free article] [PubMed] [Google Scholar]
  76. Zhou M., Lei M., Rao Y., Nie Q., Zeng H., Xia M., Liang F., Zhang D., Zhang X. Polymorphisms of vasoactive intestinal peptide receptor-1 gene and their genetic effects on broodiness in chickens. Poult. Sci. 2008;87:893–903. doi: 10.3382/ps.2007-00495. [DOI] [PubMed] [Google Scholar]
  77. Zhu W., Fan Y., Frenzel T., Gasmi M., Bartus R.T., Young W.L., Yang G.Y., Chen Y. Insulin growth factor-1 gene transfer enhances neurovascular remodeling and improves long-term stroke outcome in mice. Stroke. 2008;39:1254–1261. doi: 10.1161/STROKEAHA.107.500801. [DOI] [PMC free article] [PubMed] [Google Scholar]

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