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Identification and Regulatory Network Analysis of Genes Related to Reproductive Performance in the Hypothalamus and Pituitary of Angus Cattle
- Source :
- Genes, Vol 13, Iss 6, p 965 (2022)
- Publication Year :
- 2022
- Publisher :
- MDPI AG, 2022.
-
Abstract
- In this study, we explored the gene expression patterns of the pituitary gland and hypothalamus of Angus cows at different growth and developmental stages by deep sequencing and we identified genes that affect bovine reproductive performance to provide new ideas for improving bovine fertility in production practice. We selected three 6-month-old (weaning period), three 18-month-old (first mating period), and three 30-month-old (early postpartum) Angus cattle. The physiological status of the cows in each group was the same, and their body conformations were similar. After quality control of the sequencing, the transcriptome analyses of 18 samples yielded 129.18 GB of clean data. We detected 13,280 and 13,318 expressed genes in the pituitary gland and hypothalamus, respectively, and screened 35 and 50 differentially expressed genes (DEGs) for each, respectively. The differentially expressed genes in both tissues were mainly engaged in metabolism, lipid synthesis, and immune-related pathways in the 18-month-old cows as compared with the 6-month-old cows. The 30-month-old cows presented more regulated reproductive behavior, and pituitary CAMK4 was the main factor regulating the reproductive behavior during this period via the pathways for calcium signaling, longevity, oxytocin, and aldosterone synthesis and secretion. A variant calling analysis also was performed. The SNP inversions and conversions in each sample were counted according to the different base substitution methods. In all samples, most base substitutions were represented by substitutions between bases A and G, and the probability of base conversion exceeded 70%, far exceeding the transversion. Heterozygous SNP sites exceeded 37.68%.
Details
- Language :
- English
- ISSN :
- 20734425
- Volume :
- 13
- Issue :
- 6
- Database :
- Directory of Open Access Journals
- Journal :
- Genes
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.4c44cee48a144785b237958b6c4fd6ef
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/genes13060965