DOI QR코드

DOI QR Code

Ovarian transcriptomic analysis of Shan Ma ducks at peak and late stages of egg production

  • Zhu, ZhiMing (Institute of Animal Husbandry and Veterinary Medicine, Fujian Academy of Agricultural Sciences) ;
  • Miao, ZhongWei (Institute of Animal Husbandry and Veterinary Medicine, Fujian Academy of Agricultural Sciences) ;
  • Chen, HongPing (Longyan Original Breeder's Farm of Shan Ma Duck) ;
  • Xin, QingWu (Institute of Animal Husbandry and Veterinary Medicine, Fujian Academy of Agricultural Sciences) ;
  • Li, Li (Institute of Animal Husbandry and Veterinary Medicine, Fujian Academy of Agricultural Sciences) ;
  • Lin, RuLong (Longyan Original Breeder's Farm of Shan Ma Duck) ;
  • Huang, QinLou (Institute of Animal Husbandry and Veterinary Medicine, Fujian Academy of Agricultural Sciences) ;
  • Zheng, NenZhu (Institute of Animal Husbandry and Veterinary Medicine, Fujian Academy of Agricultural Sciences)
  • Received : 2016.06.20
  • Accepted : 2016.12.17
  • Published : 2017.09.01

Abstract

Objective: To assess the differences in ovarian transcriptomes in Shan Ma ducks between their peak and late stages of egg production, and to obtain new transcriptomic data of these egg-producing ducks. Methods: The Illumina HiSeq 2000 system was used for high throughput sequencing of ovarian transcriptomes from Shan Ma ducks at their peak or late stages of egg production. Results: Greater than 93% of the sequencing data had a base quality score (Q score) that was not less than 20 (Q20). From ducks at their peak stage of egg production, 42,782,676 reads were obtained, with 4,307,499,083 bp sequenced. From ducks at their late stage of egg production, 45,316,166 reads were obtained, with 4,562,063,363 bp sequenced. A comparison of the two datasets identified 2,002 differentially expressed genes, with 790 upregulated and 1,212 downregulated. Further analysis showed that 1,645 of the 2,002 differentially expressed genes were annotated in the non-redundant (NR) database, with 646 upregulated and 999 downregulated. Among the differentially expressed genes with annotations in the NR database, 696 genes were functionally annotated in the clusters of orthologous groups of proteins database, involving 25 functional categories. One thousand two hundred four of the differentially expressed genes with annotations in the NR database were functionally annotated in the gene ontology (GO) database, and could be divided into three domains and 56 categories. The three domains were cellular component, molecular function, and biological process. Among the genes identified in the GO database, 451 are involved in development and reproduction. Analysis of the differentially expressed genes with annotations in the NR database against the Kyoto encyclopedia of genes and genomes database revealed that 446 of the genes could be assigned to 175 metabolic pathways, of which the peroxisome proliferator-activated receptor signaling pathway, insulin signaling pathway, fructose and mannose metabolic pathways, gonadotropin releasing hormone signaling pathway and transforming growth factor beta signaling pathway were significantly enriched. Conclusion: The differences in ovarian transcriptomes in Shan Ma ducks between their peak and late stages of egg production were elucidated, which greatly enriched the ovarian transcriptomic information of egg-producing ducks.

Keywords

Transcriptome;Ovary;Differentially Expressed Genes;Shan Ma Ducks

References

  1. Luan XH, Liu DW, Gao ZZ, et al. Transcriptome profiling identifies differentially expressed genes in huoyan goose ovaries between the laying period and ceased period. PLOS ONE 2014;9:e113211. https://doi.org/10.1371/journal.pone.0113211
  2. Yi B, Chen L, Sa RN, et al. Transcriptome profile analysis of breast muscle tissues from high or low levels of atmospheric ammonia exposed broilers (gallus gallus). PLOS ONE 2016;11:e0162631. https://doi.org/10.1371/journal.pone.0162631
  3. Xu TS, Gu LH, Schachtschneider KM, et al. Identification of differentially expressed genes in breast muscle and skin fat of postnatal pekin duck. PLOS ONE 2014;9:e107574. https://doi.org/10.1371/journal.pone.0107574
  4. Chen L, Luo J, Li JX, et al. Transcriptome analysis of adiposity in domestic ducks by transcriptomic comparison with their wild counterparts. Anim Genet 2015;46:299-307. https://doi.org/10.1111/age.12294
  5. Trapnell C, Pachter L, Saizberg SL. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 2009;9:1105-11.
  6. Trapnell C, Williams BA, Pertea G, et al. Transcript assembly and quantification by RNA-seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol 2010;28:511-5. https://doi.org/10.1038/nbt.1621
  7. Conesa A, Gotz S, Garcir-Gomez JM, et al. Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics 2005;21:3674-6. https://doi.org/10.1093/bioinformatics/bti610
  8. Livaka KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the $2^{-{\Delta}{\Delta}Ct}$ method. Methods 2001;25:402-8. https://doi.org/10.1006/meth.2001.1262
  9. Colonello-Frattini NA, Hartfelder K. Differential gene expression profiling in mucus glands of honey bee (Apis mellifera) drones during sexual maturation. Apidologie 2009;40:481-95. https://doi.org/10.1051/apido/2009009
  10. Du C, Fu SY, Gao HY, et al. Transcriptome analysis of intramuscular preadipocytes and matureadipocyte in cashmere goats. Acta Vet Zoot Sin 2014;45:714-21.
  11. Zeng T, Zhang LP, Li JJ, et al. De novo assembly and characterization of Muscovy duck liver transcriptome and analysis of differentially regulated genes in response to heat stress. Cell Stress Chaperones 2015;20:483-93. https://doi.org/10.1007/s12192-015-0573-4
  12. Zhang XD, Huang L, Wu T, et al. Transcriptomic analysis of ovaries from pigs with high and low litter size. PLOS ONE 2015;10:e0139514. https://doi.org/10.1371/journal.pone.0139514
  13. Gan L, Xie L, Zuo F, Xiang Z, He N. Transcriptomic analysis of Rongchang pig brains and livers. Gene 2015; 560:96-106. https://doi.org/10.1016/j.gene.2015.01.051
  14. Xia JH, Yuan J, Xin LL, et al. Transcriptome analysis on the inflammatory cell infiltration of nonalcoholic steatohepatitis in bama minipigs induced by along-term high-fat, high-sucrose diet. PLOS ONE 2014;9:e113724. https://doi.org/10.1371/journal.pone.0113724
  15. Wang XL, Zhou GX, Xu XC, et al. Transcriptome profile analysis of adipose tissues from fat and short-tailed sheep. Gene 2014;549:252-7. https://doi.org/10.1016/j.gene.2014.07.072
  16. Pierre A, Pisselet C, Dupont J, et al. Molecular basis of bone Morphogenetic protein-4 inhibitory action on progesterone secretion by ovine granulose cells. J Mol Endocrinol 2005;33:805-17.
  17. Dong CY, Kang B, Jia XJ, Yang HM. Construction of the full-length cDNA libarary and analysis in part of ESTs in Zi goose ovary. J Agric Biotechnol 2010;18:389-93.
  18. Xu GF, Chen KW. Photograh album of China indigeneous poultry breeds. Beijing, China: China Agricultural Press; 2003.
  19. Lin RL, Chen HP, Rourvier R, Marie-Etancelin C. Genetic parameters of body weight, egg production, and shell quality traits in the Shan Ma laying duck (Anas platyrhynchos). Poult Sci 2016;95:2514-9. https://doi.org/10.3382/ps/pew222
  20. Tariq M, Chen R, Yuan HY, et al. De novo transcriptomic analysis of peripheral blood lymphocytes from the Chinese goose: gene discovery and immune system pathway description. PLOS ONE 2015;10:e0121015. https://doi.org/10.1371/journal.pone.0121015
  21. Gao GL, Zhao XZ, Li Q, Su J, Wang QG. Gene expression profiles in the pituitary glands of sichuan white geese during prelaying and laying periods. Genet Mol Res 2015;14:12636-45. https://doi.org/10.4238/2015.October.19.7
  22. Ding N, Han Q, Zhao XZ, et al. Differential gene expression in pre-laying and laying period ovaries of Sichuan white geese (Anser cygnoides). Genet Mol Res 2015;14:6773-85. https://doi.org/10.4238/2015.June.18.20
  23. Dube JL, Wang P, Elvin J, et al. The bone morphogenetic protein 15 Gene is X-linked and expressed in oocytes. Mol Endocrinol 1999;12:1809-17.
  24. Ba6ran A, Silverman KA, Zeskand J, et al. The modifier of min2 (mom2) locus: embryonic lethality of a mutation in the apt5a1 gene suggests a novel mechanism of polyp suppression. Genome Res 2007;17:566-77. https://doi.org/10.1101/gr.6089707
  25. Kang B, Guo JR, Yang HM, et al. Differential expression profiling of ovarian genes in prelaying and laying geese. Poult Sci 2009;88:1975-83. https://doi.org/10.3382/ps.2008-00519
  26. Wang ZF, Whitfield ML, Ingledue TC, Dominski Z, Marzluff WF. The protein that binds the 3V end of histone mRNA: a novel RNA-binding protein required for histone pre-mRNA processing. Genes Dev 1996;10:3028-40. https://doi.org/10.1101/gad.10.23.3028
  27. Dominski Z, Zheng LX, Sanchez R, Marzluff WF. The stem-loop binding protein facilitates 3′end formation by stabilizing U7 snRNP binding to the histone pre-mRNA. Mol Cell Biol 1999;19:3561-70. https://doi.org/10.1128/MCB.19.5.3561
  28. Patrick A, Yang Q, Marzluff WF, Clarke HJ. The stem-loop binding protein regulates translation of histone mRNA during mammalian oogenesis. Dev Biol 2005;286:195-206. https://doi.org/10.1016/j.ydbio.2005.07.023
  29. Lan DL, Xiong XR, Wei YL, et al. RNA-Seq analysis of yak ovary: improving yak gene structure information and mining reproductionrelated genes. Sci China Life Sci 2014;44:307-17.
  30. Regassa A, Rings F, Hoelker M, et al. Transcriptome dynamics and molecular cross-talk between bovine oocyte and its companion cumulus cells. BMC Genomics 2011;12:57. https://doi.org/10.1186/1471-2164-12-57
  31. Mamo S, Carter F, Lonergan P, et al. Sequential analysis of global gene expression profiles in immature and in vitro matured bovine oocytes: potential molecular markers of oocyte maturation. BMC Genomics 2011;12:151. https://doi.org/10.1186/1471-2164-12-151
  32. Seto-Young D, Zajac J, Liu HC, Rosenwaks Z, Poretsky L. The role of mitogen-activated protein kinase in insulin and insulin-like growth factor I (IGF-I) signaling cascades for progesterone and IGF-binding protein-1 production in human granulosa cells. J Clin Endocrinol Metab 2003;88:3385-91. https://doi.org/10.1210/jc.2002-021965
  33. Richardson MC, Cameron IT, Simonis CD, et al. Insulin and human chorionic gonadotropin cause a shift in the balance of sterol regulatory element-binding protein (SREBP) isoforms toward the SREBP-1c isoform in cultures of human granulosa cells. J Clin Endocrinol Metab 2005;90:3738-46. https://doi.org/10.1210/jc.2004-2057
  34. Clarke IJ, Smith JT, Caraty A, Goodman R, Lehman MN. Kisspeptin and seasonality in sheep. Peptides 2009;30:154-63. https://doi.org/10.1016/j.peptides.2008.08.022
  35. Casan EM, Raga F, Bonilla-Musoles F, Polan M. Human oviductal gonadotropin-releasing hormone: Possible implications in fertilization, early embryonic development and implantation. J Clin Endocrinol Metab 2000;85:1377-81.
  36. Lee VH, Lee LT, Chow BK. Gonadotropin-releasing hormone: regulation of the GnRH gene. FEBS J 2008;275:5458-78. https://doi.org/10.1111/j.1742-4658.2008.06676.x
  37. Shi Y, Massague J. Mechanisms of TGF-${\beta}$ signaling from cell membrane to the nucleus. Cell 2003;13:685-700.
  38. Drummond AE. $TGF{\beta}$ signaling in the development of ovary function. Cell Tissue Res 2005;322:107-15. https://doi.org/10.1007/s00441-005-1153-1
  39. Konrad L, Keilani M, Laible L, Nottelmann U, Hofmann R. Effects of TGF-betas and a specific antagonist on apoptosis of immature rat male germ cells in vitro. Apoptosis 2006;11:739-45. https://doi.org/10.1007/s10495-006-5542-z

Cited by

  1. Nutritional requirements of meat-type and egg-type ducks: what do we know? vol.9, pp.1, 2018, https://doi.org/10.1186/s40104-017-0217-x