DataSheet2_Characterization of lncRNA/circRNA-miRNA-mRNA network to reveal potential functional ceRNAs in the skeletal muscle of chicken.xls

Skeletal muscle, comprising approximately 40% of body mass, is a highly complex and heterogeneous tissue serving a multitude of functions in the organism. Non-coding RNAs (ncRNAs) are known to participate in skeletal muscle development as critical regulators. However, the regulatory mechanisms of ncRNAs on chicken muscle traits are not well understood. In the present study, we collected the leg muscle from male embryos of Tibetan chicken at embryonic (E) 10 and E18 for RNA sequencing. A total of 6,583 differentially expressed mRNAs (DEMs) including 3,055 down-regulated and 3,528 up-regulated were identified in E18. We identified 695 differentially expressed lncRNAs (DELs) (187 down-regulated and 508 up-regulated) and 1,906 differentially expressed circRNAs (DECs) (1,224 down-regulated and 682 up-regulated) in E18. Among the 130 differentially expressed miRNAs (DEMIs), 59 were up-regulated and 71 were down-regulated in E18. Numerous DEMs and target genes for miRNAs/lncRNAs were significantly enriched in the muscle system process and cell cycle. We constructed a miRNA-gene-pathway network by considering target relationships between genes related to skeletal muscle development and miRNAs. A competing endogenous RNA (ceRNA) network was also constructed by integrating competing relationships between DEMs, DELs, and DECs. Several DELs and DECs were predicted to regulate the ADRA1B, ATP2A2, ATP2B1, CACNA1S, CACNB4, MYLK2, and ROCK2 genes. We discovered the crosstalk between the ncRNAs and their competing mRNAs, which provides insights into ceRNA function and mechanisms in the skeletal muscle development of chicken.</p

DataSheet1_Characterization of lncRNA/circRNA-miRNA-mRNA network to reveal potential functional ceRNAs in the skeletal muscle of chicken.docx

Skeletal muscle, comprising approximately 40% of body mass, is a highly complex and heterogeneous tissue serving a multitude of functions in the organism. Non-coding RNAs (ncRNAs) are known to participate in skeletal muscle development as critical regulators. However, the regulatory mechanisms of ncRNAs on chicken muscle traits are not well understood. In the present study, we collected the leg muscle from male embryos of Tibetan chicken at embryonic (E) 10 and E18 for RNA sequencing. A total of 6,583 differentially expressed mRNAs (DEMs) including 3,055 down-regulated and 3,528 up-regulated were identified in E18. We identified 695 differentially expressed lncRNAs (DELs) (187 down-regulated and 508 up-regulated) and 1,906 differentially expressed circRNAs (DECs) (1,224 down-regulated and 682 up-regulated) in E18. Among the 130 differentially expressed miRNAs (DEMIs), 59 were up-regulated and 71 were down-regulated in E18. Numerous DEMs and target genes for miRNAs/lncRNAs were significantly enriched in the muscle system process and cell cycle. We constructed a miRNA-gene-pathway network by considering target relationships between genes related to skeletal muscle development and miRNAs. A competing endogenous RNA (ceRNA) network was also constructed by integrating competing relationships between DEMs, DELs, and DECs. Several DELs and DECs were predicted to regulate the ADRA1B, ATP2A2, ATP2B1, CACNA1S, CACNB4, MYLK2, and ROCK2 genes. We discovered the crosstalk between the ncRNAs and their competing mRNAs, which provides insights into ceRNA function and mechanisms in the skeletal muscle development of chicken.</p

Stocking density affects transcriptome changes in the hypothalamic-pituitary-gonadal axis and reproductive performance in ducks

The hypothalamic-pituitary-adrenal (HPA) axis and hypothalamic-pituitary-gonadal (HPG) axis plays a central role in mediating physiological responses related to the reproductive system under any stressful condition. However, the molecular mechanism underlying the effects of stress on physiology still needs to be elucidated. This study demonstrated that increasing the stocking density from 4 to 8 birds/m2 during the laying period decreased the egg production rate of laying ducks by 13.04 − 63.55% and feed intake by 7.40 − 23.44%. Transcriptome analysis between high- and low-feeding-density laying ducks revealed 469, 509, 428 and 210 differentially expressed genes (DEGs) in the hypothalamus, pituitary, ovary and follicular membrane, respectively. Gene ontology (GO) and KEGG enrichment analysis showed that the DEGs in the hypothalamus and pituitary were primarily enriched in the biostimulation and dopamine secretion pathways. The major enrichment pathways in the ovarian and follicular membranes involved lipid metabolism, negative regulation of inflammatory response, and steroid hormone biosynthesis. Among the DEGs in the HPG system, POMC and GnRH1 were identified, which may be manifesting their crucial roles in regulating the stress response and reproduction. Our data showed that a high stocking density as environmental stress negatively affects the reproductive performance in ducks through transcriptional changes in the HPG axis.HighlightsRaising the stocking density from 4 to 8 birds/m2 decreased the egg production rate and feed intake in laying ducks.The transcriptome indicated that stocking density affects the stress response of laying ducks through the hypothalamus-pituitary.The stress signals are subsequently transmitted to affect gene expression related to the reproduction process in laying ducks’ ovarian and follicular tissues.The hypothalamic expression of POMC and GnRH1 may play a central role in integrating stress signals and the reproductive processes of laying ducks. Raising the stocking density from 4 to 8 birds/m2 decreased the egg production rate and feed intake in laying ducks. The transcriptome indicated that stocking density affects the stress response of laying ducks through the hypothalamus-pituitary. The stress signals are subsequently transmitted to affect gene expression related to the reproduction process in laying ducks’ ovarian and follicular tissues. The hypothalamic expression of POMC and GnRH1 may play a central role in integrating stress signals and the reproductive processes of laying ducks.</p

Lipid Deposition and Progesterone Synthesis Are Increased by miR-181b-5p through RAP1B/ERK1/2 Pathway in Chicken Granulosa Cells

Steroid hormones secreted by granulosa cells are essential for maintaining normal development of chicken follicles. Our previous sequencing data indicated that miR-181b-5p and RAS-related protein 1B (RAP1B) appeared to function in chicken granulosa cells, which was further explored in this study. The results suggested that miR-181b-5p facilitated the aggregation of lipid droplets and the synthesis of progesterone. In contrast, RAP1B astricted lipid deposition and progesterone secretion. Cotransfection of the RAP1B overexpression vector with miR-181b-5p mimic eliminated the promoting effect of miR-181b-5p. Dual-luciferase reporter assay confirmed that miR-181b-5p bound directly to the 3′ untranslated region (3′ UTR) of RAP1B. We also found that miR-181b-5p and RAP1B reduced and enhanced the phosphorylation levels of extracellular signal-regulated kinases 1 and 2 (ERK1/2), respectively. The application of ERK1/2 activators and inhibitors demonstrated that ERK1/2 is a negative regulator of lipid deposition and progesterone synthesis. In conclusion, we revealed that miR-181b-5p accelerated lipid deposition and progesterone synthesis through the RAP1B/ERK1/2 pathway in chicken granulosa cells. miR-181b-5p and RAP1B may serve as new biomarkers in breeding to improve chicken reproductive performance and prevent ovary-related diseases

Primer information for detecting SNPs in PPARα coding regions.

Primer information for detecting SNPs in PPARα coding regions.</p

Polymorphisms in the Egl nine homolog 3 (<i>EGLN3</i>) and Peroxisome proliferator activated receptor-alpha (<i>PPARα</i>) genes and their correlation with hypoxia adaptation in Tibetan chickens

<div><p><i>Peroxisome proliferator activated receptor-alpha (PPARα)</i> and <i>Egl nine homolog 3</i> (<i>EGLN3)</i> play critical roles in facilitating the adaptation to a hypoxic environment. However, the relationship between <i>EGLN3</i> and <i>PPARα</i> variants and hypoxic adaptation remains poorly understood in Tibetan chickens. To better understand the effects of genetic variation, we sequenced exons of <i>PPARα</i> and <i>EGLN3</i> in 138 Lowland chickens (LC) from 7 breeds that were located in Emei, Miyi, Shimian, Wanyuan, Pengxian, and Muchuan in the Sichuan province, and Wenchang in the Hainan province (altitudes for these locations are below 1800 meters). Total 166 Tibetan chickens (TC) from 7 subpopulations that were located in Shigatse, Lhoka, Lhasa, Garze, Aba, Diqing and Yushu in the Tibetan area were also sequenced (altitudes greater than 2700 meters). One single-nucleotide polymorphism (rs316017491, C > T) was identified in <i>EGLN3</i> and was shared by TC and LC with no significant difference for allele frequencies between them (P > 0.05). Six single-nucleotide polymorphisms (SNP1, A29410G; SNP2, rs13886097; SNP3, T29467C; SNP4, rs735915170; SNP5, rs736599044; and SNP6, rs740077421) including one non-synonymous mutation (SNP2, T > C) were identified in <i>PPARα</i>. This is the first report of SNP1 and SNP3. There was a difference between TC and LC for allele frequencies (P <0.01), except for SNP1, SNP4, and SNP5) The fix index statistic test indicated that there was population differentiation between TC and LC for SNP2, SNP3, and SNP6 in <i>PPARα</i> (P < 0.05). Phylogenetic analysis showed that the genetic distance among chickens, finch and great tit were close for both <i>EGLN3</i> and <i>PPARα</i>. Bioinformatics analysis of <i>PPARα</i> showed that SNP2 leads to an amino acid substitution of Ile for Met, which results in the protein being more likely to be hydrolyzed. Thus, genetic variation in <i>PPARα</i> may play a role in the ability of TC to adapt to a high altitude environment; however we were unable to identify a relationship between polymorphisms in <i>EGLN3</i> and environmental adaptability.</p></div

Whole-genome resequencing reveals aberrant autosomal SNPs affect chicken feathering rate

Previous studies have shown that the feather growth rate of chicks is determined by two alleles located on the sex chromosome Z; however, in chicken production, feathering is usually not consistently controlled by the sex chromosome. To identify whether the feathering rate is related to autosomal inheritance, whole-genome resequencing was performed in eight chickens with slow- and fast-feathering rate. A total of 54,984 autosomal single nucleotide polymorphisms (SNPs) were identified, including 393 and 376 exonic SNPs in slow-feathering and fast-feathering chickens, respectively. Mutated genes were mainly involved in response to stimuli and growth and reproduction processes. Mutated genes related to slow-feathering rate were mainly involved in wingless-type MMTV integration site signaling pathway and mitogen-activated protein kinase signaling pathway, whereas mutated genes associated with fast-feathering rate were primarily enriched in autophagy, calcium signaling pathway, extracellular matrix-receptor interaction, and Focal adhesion processes. Importantly, two SNPs, involved in feather development, were found in the exonic regions of Wnt signaling genes. These results shed new light on the relationship between genetic mutation and feather growth rate from the perspective of autosomal inheritance and may have economic significance in chicken breeding.</p

Mutation information for <i>EGLN3</i> and <i>PPARα</i>.

<p>Mutation information for <i>EGLN3</i> and <i>PPARα</i>.</p

Protein hydrophobicity analyses for the PPARα protein.

<p>(A) Hydrophobic analysis before mutation; (B) Hydrophobic analysis after mutation; Positive values represent hydrophobic and negative values represent hydrophilic.</p

Primer information for detecting SNPs in <i>EGLN3</i> coding regions.

<p>Primer information for detecting SNPs in <i>EGLN3</i> coding regions.</p