BMC Genomics (Jun 2024)

Identification of genes associated with sperm storage capacity in hens at different times after insemination by RNA-seq and Ribo-seq

  • Ruitang Chai,
  • Cong Xiao,
  • Zhuliang Yang,
  • Wenya Du,
  • Ke Lv,
  • Jiayi Zhang,
  • Xiurong Yang

DOI
https://doi.org/10.1186/s12864-024-10472-2
Journal volume & issue
Vol. 25, no. 1
pp. 1 – 15

Abstract

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Abstract Background Sperm storage capacity (SSC) determines the duration of fertility in hens and is an important reproduction trait that cannot be ignored in production. Currently, the genetic mechanism of SSC is still unclear in hens. Therefore, to explore the genetic basis of SSC, we analyzed the uterus-vagina junction (UVJ) of hens with different SSC at different times after insemination by RNA-seq and Ribo-seq. Results Our results showed that 589, 596, and 527 differentially expressed genes (DEGs), 730, 783, and 324 differentially translated genes (DTGs), and 804, 625, and 467 differential translation efficiency genes (DTEGs) were detected on the 5th, 10th, and 15th days after insemination, respectively. In transcription levels, we found that the differences of SSC at different times after insemination were mainly reflected in the transmission of information between cells, the composition of intercellular adhesion complexes, the regulation of ion channels, the regulation of cellular physiological activities, the composition of cells, and the composition of cell membranes. In translation efficiency (TE) levels, the differences of SSC were mainly related to the physiological and metabolic activities in the cell, the composition of the organelle membrane, the physiological activities of oxidation, cell components, and cell growth processes. According to pathway analysis, SSC was related to neuroactive ligand-receptor interaction, histidine metabolism, and PPAR signaling pathway at the transcriptional level and glutathione metabolism, oxidative phosphorylation, calcium signaling pathway, cell adhesion molecules, galactose metabolism, and Wnt signaling pathway at the TE level. We screened candidate genes affecting SSC at transcriptional levels (COL4A4, MUC6, MCHR2, TACR1, AVPR1A, COL1A1, HK2, RB1, VIPR2, HMGCS2) and TE levels(COL4A4, MUC6, CYCS, NDUFA13, CYTB, RRM2, CAMK4, HRH2, LCT, GCK, GALT). Among them, COL4A4 and MUC6 were the key candidate genes differing in transcription, translation, and translation efficiency. Conclusions Our study used the combined analysis of RNA-seq and Ribo-seq for the first time to investigate the SSC and reveal the physiological processes associated with SSC. The key candidate genes affecting SSC were screened, and the theoretical basis was provided for the analysis of the molecular regulation mechanism of SSC.

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