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What is it about?
Researchers investigated the genetic basis of fertility in Ji'ning Gray goats using single-cell RNA sequencing (scRNA-seq) data. They compared granulosa cells from high-fertility and low-fertility goats, identifying 150 differentially expressed genes (DEGs) with 80 upregulated and 70 downregulated genes. Additionally, they found 81 mRNAs, 58 circRNAs, 8 lincRNAs, 19 lncRNAs, and 55 miRNAs through literature mining. A ceRNA regulatory network was constructed integrating these RNAs with gene regulatory networks. This study provides insights into the complex reproductive functions of goats and contributes to understanding the genetic basis of high- versus low-fertility goats.
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Why is it important?
The research focuses on the genetic improvement of fertility traits in female goats using single-cell RNA sequencing (scRNA-seq). The study investigates comparative transcriptome profiling of granulosa cells (GCs) of high- and low-fertility goats, identifying 150 differentially expressed genes (DEGs) between the two groups. The study also explores the functional enrichment of these genes, predicts interactions between types of RNAs, and constructs a ceRNA regulatory network. The research is significant because it provides insights into the genetic basis of fertility in goats and identifies potential genes and molecular pathways involved in fertility. Key Takeaways: 1. The study identifies 150 DEGs between high- and low-fertility goats, which can be used as potential targets for future research on improving fertility in goats. 2. The study predicts interactions between different types of RNAs, providing a better understanding of the complex regulatory networks involved in fertility. 3. The ceRNA regulatory network constructed in the study can serve as a basis for further research on the molecular mechanisms underlying fertility in goats.
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This page is a summary of: Construction of a circRNA– lincRNA–lncRNA–miRNA–mRNA ceRNA regulatory network identifies genes and pathways linked to goat fertility, Frontiers in Genetics, July 2023, Frontiers,
DOI: 10.3389/fgene.2023.1195480.
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