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. 2024 Jul 4;15(1):91.
doi: 10.1186/s40104-024-01049-w.

Transcriptomic and epigenomic landscapes of muscle growth during the postnatal period of broilers

Affiliations

Transcriptomic and epigenomic landscapes of muscle growth during the postnatal period of broilers

Shuang Gu et al. J Anim Sci Biotechnol. .

Abstract

Background: Broilers stand out as one of the fastest-growing livestock globally, making a substantial contribution to animal meat production. However, the molecular and epigenetic mechanisms underlying the rapid growth and development of broiler chickens are still unclear. This study aims to explore muscle development patterns and regulatory networks during the postnatal rapid growth phase of fast-growing broilers. We measured the growth performance of Cornish (CC) and White Plymouth Rock (RR) over a 42-d period. Pectoral muscle samples from both CC and RR were randomly collected at day 21 after hatching (D21) and D42 for RNA-seq and ATAC-seq library construction.

Results: The consistent increase in body weight and pectoral muscle weight across both breeds was observed as they matured, with CC outpacing RR in terms of weight at each stage of development. Differential expression analysis identified 398 and 1,129 genes in the two dimensions of breeds and ages, respectively. A total of 75,149 ATAC-seq peaks were annotated in promoter, exon, intron and intergenic regions, with a higher number of peaks in the promoter and intronic regions. The age-biased genes and breed-biased genes of RNA-seq were combined with the ATAC-seq data for subsequent analysis. The results spotlighted the upregulation of ACTC1 and FDPS at D21, which were primarily associated with muscle structure development by gene cluster enrichment. Additionally, a noteworthy upregulation of MUSTN1, FOS and TGFB3 was spotted in broiler chickens at D42, which were involved in cell differentiation and muscle regeneration after injury, suggesting a regulatory role of muscle growth and repair.

Conclusions: This work provided a regulatory network of postnatal broiler chickens and revealed ACTC1 and MUSTN1 as the key responsible for muscle development and regeneration. Our findings highlight that rapid growth in broiler chickens triggers ongoing muscle damage and subsequent regeneration. These findings provide a foundation for future research to investigate the functional aspects of muscle development.

Keywords: ATAC-seq; Broiler; Pectoral muscle development; RNA-seq; Rapid growth.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Growth performance of postnatal broiler chickens. a The changes in body weight (BW) of individuals with Cornish (CC) and White Plymouth Rock (RR) from the day of hatching (DOH) and day 7 after hatching (D7), D14, D21, D28, D35, D42. b The changes in pectoral muscle weight (PMW) of individuals with CC and RR from DOH to D42. c Cross-sectional area (CSA) of muscle fibers from D7 to D42. d Muscle fiber density (MFD) changes from D7 to D42. e Morphology of the myofibers stained by hematoxylin–eosin from D7 to D42. The corresponding scale is marked in the lower left corner of each image. Scale bars: 100 μm. f The scatter plot and Pearson’s correlation of broiler chickens at D21 and D42. g Pectoral muscles were collected at D21 and D42 for RNA-seq and ATAC-seq analysis. ** and * indicate P value less than 0.01 and 0.05, respectively
Fig. 2
Fig. 2
Analysis of RNA-seq data from the pectoral muscle. a PCA plot of RNA-seq data of CC and RR groups at D21 and D42. Each point represents a sample. b Volcano plot of differential expressed genes (DEGs) obtained through the comparison between pairwise groups. c The GO enrichment results of CC-biased DEGs (CBGs) and RR-biased DEGs (RBGs) at D21 and D42. d GO enrichment results of D21-biased DEGs (D21BGs) and D42-biased DEGs (D42BGs) of CC and RR
Fig. 3
Fig. 3
Analysis of chromatin accessibility from the pectoral muscle. a Fragment insert length distribution plots of ATAC-seq samples. b PCA plot of ATAC-seq data of CC and RR groups at D21 and D42. Each point represents a sample. c The feature distribution of ATAC-seq peak dataset. d Overlap peaks between two groups. e Heatmaps of differential accessible regions (DARs)
Fig. 4
Fig. 4
Integration of RNA-seq and ATAC-seq to identify candidate genes. a Venn diagrams showed the DEGs carrying DARs. b The relationship between DEGs and DARs. c The 16 RBGs at D21 and the 65 D21BGs of RR were combined for GO enrichment analysis. d Frequency analysis of DEGs of top 20 terms. e The network analysis and functional enrichment analysis of the DEGs was performed using GeneMANIA. f Differential expression results among the four groups. ** and * indicate P value less than 0.01 and 0.05, respectively
Fig. 5
Fig. 5
Intense muscle damage with rapid muscle growth at D42. a The 12 CBGs at D42 and the 69 D42BGs of CC were combined for GO enrichment analysis. b Frequency analysis of 9 DEGs of top 10 terms. c Network analysis and functional enrichment analysis using GeneMANIA on the 9 DEGs that were present in at least 2 terms among the 20 DEGs. d The network analysis of DEGs was performed using STRING. e Differential expression results among the four groups. ** and * indicate P value less than 0.01 and 0.05, respectively. f Gene expression and chromatin accessibility of FOS and MUSTN1 displayed similar dynamic changes in CC at D42

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