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Integrated Analysis of Methylome and Transcriptome Changes Reveals the Underlying Regulatory Signatures Driving Curly Wool Transformation in Chinese Zhongwei Goats

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Integrated Analysis of Methylome and Transcriptome Changes Reveals the Underlying Regulatory Signatures Driving Curly Wool Transformation in Chinese Zhongwei Goats

Ping Xiao et al. Front Genet.

Abstract

The Zhongwei goat is kept primarily for its beautiful white, curly pelt that appears when the kid is approximately 1 month old; however, this representative phenotype often changes to a less curly phenotype during postnatal development in a process that may be mediated by multiple molecular signals. DNA methylation plays important roles in mammalian cellular processes and is essential for the initiation of hair follicle (HF) development. Here, we sought to investigate the effects of genome-wide DNA methylation by combining expression profiles of the underlying curly fleece dynamics. Genome-wide DNA methylation maps and transcriptomes of skin tissues collected from 45- to 108-day-old goats were used for whole-genome bisulfite sequencing (WGBS) and RNA sequencing, respectively. Between the two developmental stages, 1,250 of 3,379 differentially methylated regions (DMRs) were annotated in differentially methylated genes (DMGs), and these regions were mainly related to intercellular communication and the cytoskeleton. Integrated analysis of the methylome and transcriptome data led to the identification of 14 overlapping genes that encode crucial factors for wool fiber development through epigenetic mechanisms. Furthermore, a functional study using human hair inner root sheath cells (HHIRSCs) revealed that, one of the overlapping genes, platelet-derived growth factor C (PDGFC) had a significant effect on the messenger RNA expression of several key HF-related genes that promote cell migration and proliferation. Our study presents an unprecedented analysis that was used to explore the enigma of fleece morphological changes by combining methylome maps and transcriptional expression, and these data revealed stage-specific epigenetic changes that potentially affect fiber development. Furthermore, our functional study highlights a possible role for the overlapping gene PDGFC in HF cell growth, which may be a predictable biomarker for fur goat selection.

Keywords: Zhongwei goat; curly pelts; deoxyribonucleic acid methylation; epigenetics; platelet-derived growth factor C; transcriptomics.

Figures

Figure 1
Figure 1
The dynamics of fleece shape. (A) The fur of the Zhongwei goat at 45 days old and transverse/longitudinal sections of single hair follicle. (B) The fur of Zhongwei goat at 108 days old and transverse/longitudinal sections of a single hair follicle. Asterisk symbol highlights the gap between the hair shaft and inner root sheath at 45 days; the bar in all images of HE stained sections is 50 μm.
Figure 2
Figure 2
The transcriptional profile of two groups during early hair growth. (A) Averaged RNA expression level among six individuals. (B) Validation of selected differently expressed genes (DEGs) through real-time quantitative PCR. The value is presented as the logarithmic form of the fold change (FC) between two groups. P values were calculated using Student’s t tests (*P < 0.05). (C) Clustered heatmap representation of DEG expression. Clustering was performed according to Pearson’s correlation values. The black and gray bars outlined in the picture represent the DEGs that are involved in epidermal growth factor receptor tyrosine kinase inhibitor resistance and transforming growth factor beta signaling pathways, respectively.
Figure 3
Figure 3
The transcriptional process is changed during wool fiber development. (A) Count of the differential splicing events between D45 and D108 transcripts (P < 0.05). SE, skipped exon; RI, retained intron; MXE, mutually exclusive exons; A5SS, alternative 5’ splice site; A3SS, alternative 3’ splice site. There are 938 significantly different skipped exon events between the two stages, which was much greater than other events. (B) Transcription factor binding sites enriched among differentially expressed genes in D45 and D108. Only the transcription factors of upregulated or downregulated genes that had a P value < 0.01 were retained. All P values were corrected using the Benjamini–Hochberg method (BH-corrected P value < 0.05).
Figure 4
Figure 4
DNA methylation profiles of skin samples in shift stages in the wool shape of Zhongwei goats. (A) The proportion of methylated cytosines (mCs) (mCpG, mCHH, and mCHG) in the D45 and D108 tissue samples. (B) The average methylation level (%) of cytosine sites [CpG, CHH, and chlorhexidine gluconate (CHG)] in six individual samples. (C) The methylation level (%) of three mCs in different genomic regions or elements. The vertical axis on the left represents the methylation levels of CpG in two stages, and the values on the right axis represents methylation levels of CHG and CHH.
Figure 5
Figure 5
Distribution of differentially methylated regions (DMRs) in different categories. (A) Manhattan plot of DMRs in a chromosomal landscape. Dots above the dotted line presented DMRs with –log10 (p) > 20. The heatmap below the dots represents the density (counts) of the DMR distribution within chromosomes. The blue and red dots indicate the status of hypomethylation and hypermethylation in the D45 regions, respectively. (B) The filtration of differentially methylated genes and the number of DMRs in different genomic regions.
Figure 6
Figure 6
Integrated analysis was used to identify genes with coupled differential DNA methylation and RNA transcription. (A) Venn diagram representing methylation-modified differently expressed genes during wool transformation. (B) Quadrant plot showing differentially methylated genes and expression levels of the corresponding genes. The vertical dotted lines indicate a threshold of the P value below 0.05, and parallel dotted lines show a threshold of the P value below 10−4. (C) The protein-protein interaction (PPI) network among overlapping genes. Four genes identified from our analysis are included because both the confidence score and combined score were greater than 0.8. Circles filled with blue and green indicate downregulated and upregulated genes in D45, respectively. Circles with yellow and red margins indicate hypomethylation and hypermethylation in D45, respectively. Smaller gray circles with green margins denote genes attributed to the interaction.
Figure 7
Figure 7
The PDGFC gene affects human hair inner root sheath cell (HHIRSC) migration and proliferation by regulating hair follicle-related gene expression. (A) A wound healing assay was conducted after the transient transfection of PDGFC vectors or si-PDGFC. Wound closure was monitored after 12 h, and the calculation of the wound closure area is explained in the methods. The mean ± standard deviation (n = 3), *P < 0.05 (two-sided t-test). (B) The cell proliferation rate was evaluated at four time points using the Cell Counting Kit-8 assay after the corresponding cell treatments. The mean ± standard deviation (n = 3), *P < 0.05, (two-sided t-test). (C) Results from the quantitation of gene expression related to hair development by quantitative PCR in HHIRSCs at 48 h after transfection with control (scrambled) or the PDGFC vector or si-PDGFC. N = 3; *P < 0.05, **P <0.01 (two-sided t-test).

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