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Integrated transcriptomic analysis on small yellow follicles reveals that sosondowah ankyrin repeat domain family member A inhibits chicken follicle selection

  • Zhong, Conghao (Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Veterinary Medicine, Shandong Agricultural University) ;
  • Liu, Zemin (Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Veterinary Medicine, Shandong Agricultural University) ;
  • Qiao, Xibo (Shandong Jihua Poultry Breeding Co. Ltd.) ;
  • Kang, Li (Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Veterinary Medicine, Shandong Agricultural University) ;
  • Sun, Yi (Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Veterinary Medicine, Shandong Agricultural University) ;
  • Jiang, Yunliang (Shandong Provincial Key Laboratory of Animal Biotechnology and Disease Control and Prevention, College of Animal Science and Veterinary Medicine, Shandong Agricultural University)
  • Received : 2020.06.11
  • Accepted : 2020.09.02
  • Published : 2021.08.01

Abstract

Objective: Follicle selection is an important process in chicken egg laying. Among several small yellow (SY) follicles, the one exhibiting the highest expression of follicle stimulation hormone receptor (FSHR) will be selected to become a hierarchal follicle. The role of lncRNA, miRNA and other non-coding RNA in chicken follicle selection is unclear. Methods: In this study, the whole transcriptome sequencing of SY follicles with different expression levels of FSHR in Jining Bairi hens was performed, and the expression of 30 randomly selected mRNAs, lncRNAs and miRNAs was validated by quantitative real-time polymerase chain reaction. Preliminary studies and bioinformatics analysis were performed on the selected mRNA, lncRNA, miRNA and their target genes. The effect of identified gene was examined in the granulosa cells of chicken follicles. Results: Integrated transcriptomic analysis on chicken SY follicles differing in FSHR expression revealed 467 differentially expressed mRNA genes, 134 differentially expressed lncRNA genes and 34 differentially expressed miRNA genes, and sosondowah ankyrin repeat domain family member A (SOWAHA) was the common target gene of three miRNAs and one lncRNA. SOWAHA was mainly expressed in small white (SW) and SY follicles and was affected by follicle stimulation hormone (FSH) treatment in the granulosa cells. Knockdown of SOWAHA inhibited the expression of Wnt family member 4 (Wnt4) and steroidogenic acute regulatory protein (StAR) in the granulosa cells of prehierarchal follicles, while stimulated Wnt4 in hierarchal follicles. Overexpression of SOWAHA increased the expression of Wnt4 in the granulosa cells of prehierarchal follicles, decreased that of StAR and cytochrome P450 family 11 subfamily A member 1 in the granulosa cells of hierarchal follicles and inhibited the proliferation of granulosa cells. Conclusion: Integrated analysis of chicken SY follicle transcriptomes identified SOWAHA as a network gene that is affected by FSH in granulosa cells of ovarian follicles. SOWAHA affected the expression of genes involved in chicken follicle selection and inhibited the proliferation of granulosa cells, suggesting an inhibitory role in chicken follicle selection.

Keywords

Acknowledgement

This research was financially supported by grants from the National Natural Science Foundation of China (NSFC 31672 414, 31972545, 31772588), the Shandong Agricultural Breed Project (2019LZGC019) and the Funds of Shandong "Double Tops" Program (SYL2017YSTD12). The funding body had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript. We are grateful to Zhang Hao for sampling Jining Bairi hens.

References

  1. Johnson AL. Ovarian follicle selection and granulosa cell differentiation. Poult Sci 2015;94:781-5. https://doi.org/10.3382/ps/peu008
  2. Woods DC, Johnson AL. Regulation of follicle-stimulating hormone-receptor messenger RNA in hen granulosa cells relative to follicle selection. Biol Reprod 2005;72:643-50. https://doi.org/10.1095/biolreprod.104.033902
  3. Kang L, Cui X, Zhang Y, Yang C, Jiang Y. Identification of miRNAs associated with sexual maturity in chicken ovary by Illumina small RNA deep sequencing. BMC Genomics 2013;14:352. https://doi.org/10.1186/1471-2164-14-352
  4. Wang Y, Chen Q, Liu Z, et al. Transcriptome analysis on single small yellow follicles reveals that Wnt4 is involved in chicken follicle selection. Front Endocrinol 2017;15:317. https://doi.org/10.3389/fendo.2017.00317
  5. Cheng CY, Tu WL, Chen CJ, et al. Functional genomics study of acute heat stress response in the small yellow follicles of layer-type chickens. Sci Rep 2018;8:1320. https://doi.org/10.1038/s41598-017-18335-5
  6. Jing R, Gu L, Li J, Gong Y. A transcriptomic comparison of theca and granulosa cells in chicken and cattle follicles reveals ESR2 as a potential regulator of CYP19A1 expression in the theca cells of chicken follicles. Comp Biochem Physiol Part D Genomics Proteomics 2018;27:40-53. https://doi.org/10.1016/j.cbd.2018.04.002
  7. Fan Y, Zhang C, Zhu G. Profiling of RNA N6-methyladenosine methylation during follicle selection in chicken ovary. Poult Sci 2019;98:6117-24. https://doi.org/10.3382/ps/pez277
  8. Chen Q, Wang Y, Liu Z, et al. Transcriptomic and proteomic analyses of ovarian follicles reveal the role of VLDLR in chicken follicle selection. BMC Genomics 2020;21:486. https://doi.org/10.1186/s12864-020-06855-w
  9. Fabian MR, Sonenberg N, Filipowicz W. Regulation of mRNA translation and stability by microRNAs. Annu Rev Biochem 2010;79:351-79. https://doi.org/10.1146/annurev-biochem-060308-103103
  10. Gil N, Ulitsky I. Regulation of gene expression by cis-acting long non-coding RNAs. Nat Rev Genet 2020;21:102-17. https://doi.org/10.1038/s41576-019-0184-5
  11. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2-ΔCT method. Methods 2001;25:402-8. https://doi.org/10.1006/meth.2001.1262
  12. Maeso I, Irimia M, Tena JJ, et al. An ancient genomic regulatory block conserved across bilaterians and its dismantling in tetrapods by retrogene replacement. Genome Res 2012; 22:642-55. https://doi.org/10.1101/gr.132233.111
  13. Brass AL, Dykxhoorn DM, Benita Y, et al. Identification of host proteins required for HIV infection through a functional genomic screen. Science 2008;319:921-6. https://doi.org/10.1126/science.1152725
  14. Tucker ES, Segall S, Gopalakrishna D, et al. Molecular specification and patterning of progenitor cells in the lateral and medial ganglionic eminences. J Neurosci 2008;28:9504-18. https://doi.org/10.1523/JNEUROSCI.2341-08.2008
  15. Yoshitake R, Saeki K, Watanabe M, et al. Molecular investigation of the direct anti-tumour effects of nonsteroidal antiinflammatory drugs in a panel of canine cancer cell lines. Vet J 2017;221:38-47. https://doi.org/10.1016/j.tvjl.2017.02.001
  16. Johnson AL, Solovieva EV, Bridgham JT. Relationship between steroidogenic acute regulatory protein expression and progesterone production in hen granulosa cells during follicle development. Biol Reprod 2002;67:1313-20. https://doi.org/10.1095/biolreprod67.4.1313

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