Reconstruction of genes co-expression network related to the growth and development of fiber follicle in Cashmere goat fetus

Document Type : Genetics & breeding

Authors

• Arsalan Barazandeh ¹
• Morteza Mokhtari ¹
• Elham Behdani
• Zahra Roudbari ²

¹ Department of Animal Science, Faculty of Agriculture, University of Jiroft, Jiroft, Iran,

² Department of Animal Science, Faculty of Agriculture, University of Jiroft, Jiroft, Iran.

10.22067/ijasr.v12i2.81710

Abstract

Introduction[1] In most mammals, each hair follicle is a mammalian skin organ that produces hair and controls the hair growth cycle. The hair follicle is central to most economically important fiber growth in livestock. Previous studies have shown that changes in the level of genes expression play a role in the development and growth of hair follicles. With the advent of high throughput, next-generation sequencing technology measuring the level of expression of thousands of genes was possible simultaneously. As a result, many regulatory conflicts between genes can be extracted from these data. Expression profiles are generated by combining expression levels resulting from experiments in various conditions or times. Similarities and differences between expression profiles reveal many of these regulatory relationships. Despite recent advances in the identification of the molecular signaling/co-expression networks that govern the development of the skin and hair follicle, the mechanisms controlling of fiber production in Cashmere goat still remains unclear. Therefore, the present study was conducted to investigate the most important molecules controlling the growth and development of hair follicles in cashmere goats in order to decode the genes involved in the growth and development of hair follicles in cashmere goats.
Materials and Methods Publicly available preprocessed transcript data (accession no. SRP059481) was downloaded from the NCBI database in the SRA section. In this investigation, nine goats were selected at the same stage of gestation. Three fetuses were obtained at 55-65 days’ gestation (60-days old) and three fetuses were obtained at 105-125 days’ gestation (120 –day- old) through cesarean operation and three fetuses were also sacrificed within two hours of birth (newborn). For analysis of RNA-seq data, a random sampling from the right mid-side of the fetal skin and each time point had three replicates. The 60 days (E60) of gestation represented the initiation stage of growth, and the 120 d (E120) represented the development stage, as well as the newborn samples, represented the primary hair follicle maturation stage. The FastQC software (Version 11.7) was used to check the quality of the readings. This software check the quality of the reads, in case of low-quality sequencing, the data were edited by Trimmomatic software (Version 0.39), and filtered reads were evaluated with FastQC software, After removing low-quality reads mapping was performed on the goat reference genome (GCA_001704415.1) downloaded from the ensemble site using the Hisat2 software(Version 2.1.0). The HTSeq2 (Version 10.0) was used to create the count matrix, changes in the expression of genes between the groups (E60, E120, and newborns) was identified using the software Deseq2 (Version 1.24). In this stage, the genes between the two groups were compared to give an expression difference 1- Genes that are expressed throughout the growth process of the follicle 2. Co-Expression networks of up and down genes were created using the STRING database (Version 11) at https://string-db.org. The PPI network was constructed by Cytoscape software (Version 3.6.0). Cytoscape is commonly used for analysis and visualization of biological networks. Gene ontology analysis of effective gene related to development stage of hair follicle in Cashmere goat from fetal to birth was done using DAVID database.
Results and Discussion After determining the level of expression of each gene at different stages of sampling, genes that increased expression in all comparisons were considered as up-regulated genes that, by increasing their expression, control the growth and development of hair follicle. On the other hand, those genes that have been shown to reduce expression in all of the follicle growth stages comparisons were considered as genes which by decreasing their expression, causes the growth and development of the hair follicle. The interaction relations were investigated between the increased and reduced genes expressed separately by STRING database. Among the up-regulated genes, the relationships between 145 genes with 203 edge were confirmed. Also, the interaction network between the down-regulated genes confirmed between 650 genes with 1302 edge. Among the genes with differential expression, the co-expression genes (genes with the most interacting) were identified based on the results of the analysis of the statistical parameters of the network using computational algorithms in Cytoscape software. These results led to the identification of seven unique genes that were SHH, KLF4, MMP9, MSX1, KRT17, COL2A1 and VEGFA, ontology analysis of these genes showed that involved the hair cycle process, hair follicle development, skin epidermis development, epidermis morphogenesis and epidermal cell differentiation that these pathways are activated in the cashmere production process. Therefore, these genes have been used as regulators of cashmere growth and development to better understand the cashmere production process and improve its quality.
Conclusion The results have been able to introduce genes with major effects that regulate the expression of genes and molecular signals associated with the production of fiber that including KLF4, MMP9, MSX1, KRT17, COL2A1 and VEGFA in Cashmere goats. Based on functional analysis, these genes can play a significant role in the improvement of cashmere goats breeding. We hope that the obtained results would be beneficial toward finding the smart strategies for Cashmere production improvement.

 

Keywords

• Cashmere goat
• Differential expression
• Regulatory network
• Transcriptome analysis

20.1001.1.20083106.1399.12.2.7.6

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