[Alberti C., Cochella L. (2017). A framework for understanding the roles of miRNAs in animal development. Development, 144: 2548–2559.]Search in Google Scholar
[Andersen C.L., Jensen J.L., Ørntoft T.F. (2004). Normalisation of real-time quantitative reverse transcription-PCR data: a model-based variance estimation approach to identify genes suited for normalisation, applied to bladder and colon cancer data sets. Cancer Res., 64: 5245–5250.]Search in Google Scholar
[Androvic P., Valihrach L., Elling J., Sjoback R., Kubista M. (2017). Two-tailed RT-qPCR: a novel method for highly accurate miRNA quantification. Nucleic Acids Res., 45:e144.]Search in Google Scholar
[Bannister S.C., Tizard M.L., Doran T.J., Sinclair A.H., Smith C.A. (2009). Sexually dimorphic microRNA expression during chicken embryonic gonadal development. Biol. Reprod., 81: 165–176.]Search in Google Scholar
[Bartel D.P. (2004). MicroRNAs: genomics, biogenesis, mechanism, and function. Cell, 116: 281–297.]Search in Google Scholar
[Burnside J., Ouyang M., Anderson A., Bernberg E., Lu C., Meyers B.C., Green P.J., Markis M., Isacs G., Huang E., Morgan R.W. (2008). Deep sequencing of chicken microRNAs. BMC Genomics, 9: 185.]Search in Google Scholar
[Bustin S.A., Benes V., Garson J.A., Hellemans J., Huggett J., Kubista M., Mueller R., Nolan T., Pfaffl M.W., Shipley G.L., Vandesompele J., Wittwer C.T. (2009). The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. Clin. Chem., 55: 611–622.]Search in Google Scholar
[Darnell D.K., Kaur S., Stanislaw S., Konieczka J.H., Yatskievych T.A., Antin P.B. (2006). MicroRNA expression during chick embryo development. Dev. Dynam., 235: 3156–165.]Search in Google Scholar
[Fang G., Jia X., Li H., Tan S., Nie Q., Yu H., Yang Y. (2018). Characterization of microRNA and mRNA expression profiles in skin tissue between early-feathering and late-feathering chickens. BMC Genomics, 19: 399.]Search in Google Scholar
[Git A., Dvinge H., Salmon-Divon M., Osborne M., Kutter C., Hadfield J., Bertone P., Caldas C. (2010). Systematic comparison of microarray profiling, real-time PCR, and next-generation sequencing technologies for measuring differential microRNA expression. RNA, 16: 991–1006.]Search in Google Scholar
[Glazov E.A., Cottee P.A., Barris W.C., Moore R.J., Dalrymple B.P., Tizard M.L. (2008). A microRNA catalog of the developing chicken embryo identified by a deep sequencing approach. Genome Res., 18: 957–964.]Search in Google Scholar
[He L., Hannon G.J. (2004). MicroRNAs: small RNAs with a big role in gene regulation. Nat. Rev. Genet., 5: 522–531.]Search in Google Scholar
[Hicks J.A., Tembhurne P.A., Liu H.C. (2009). Identification of microRNA in the developing chick immune organs. Immunogenetics, 61: 231–240.]Search in Google Scholar
[Kang L., Cui X., Zhang Y., Yang C., Jiang Y. (2013). Identification of miRNAs associated with sexual maturity in chicken ovary by Illumina small RNA deep sequencing. BMC Genomics, 14:e352.]Search in Google Scholar
[Li H., Ma Z., Jia L., Li Y., Xu C., Wang T., Han R., Jiang R., Li Z., Sun G., Kang X., Liu X. (2016). Systematic analysis of the regulatory functions of microRNAs in chicken hepatic lipid metabolism. Sci. Rep., 6: 31766.]Search in Google Scholar
[Li T., Wang S., Wu R., Zhou X., Zhu D., Zhang Y. (2012). Identification of long non-protein coding RNAs in chicken skeletal muscle using next generation sequencing. Genomics, 99: 292–298.]Search in Google Scholar
[Lim W., Song G. (2014). Identification of novel regulatory genes in development of the avian reproductive tracts. PLosOne, 9(4):e96175.]Search in Google Scholar
[Liu L., Xiao Q., Gilbert E.R., Cui Z., Zhao X., Wang Y., Yin H., Li D., Zhang H., Zhu Q. (2018). Whole-transcriptome analysis of atrophic ovaries in broody chickens reveals regulatory pathways associated with proliferation and apoptosis. Sci. Rep., 8: 7231.]Search in Google Scholar
[Mansfield J.H., Harfe B.D., Nissen R., Obenauer J., Srineel J., Chaudhuri A., Farzan-Kashani R., Zuker M., Pasquinelli A.E., Ruvkun G., Sharp P.A., Tabin C.J., Mc Manus M.T. (2004). MicroRNA responsive ‘sensor’ transgenes uncover Hox- like and other developmentally regulated patterns of vertebrate microRNA expression. Nat. Genet., 36: 1079–1083.]Search in Google Scholar
[Meyer S.U., Pfaffl M.W., Ulbrich S.E. (2010). Normalisation strategies for microRNA profiling experiments: a ‘normal’ way to hidden layer of complexity? Biotechnol. Lett., 33: 1777–1788.]Search in Google Scholar
[Morozova O., Marra M.A. (2008). Applications of next-generation sequencing technologies in functional genomics. Genomics, 92: 255–264.]Search in Google Scholar
[Nothnick W.B. (2012). The role of micro-RNAs in the female reproductive tract. Reproduction, 143: 559–576.]Search in Google Scholar
[Pfaffl M.W. (2001). A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acids Res., 29:e45.]Search in Google Scholar
[Pfaffl M.W., Tichopad A., Prgomet C., Neuvians T.P. (2004). Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: BestKeeper-Excel-based tool using pair-wise correlations. Biotechnol. Lett., 26: 509–515.]Search in Google Scholar
[Schmittgen T.D., Livak K.J. (2008). Analyzing real-time PCR data by the comparative C(T) method. Nat. Protoc., 3: 1101–1108.]Search in Google Scholar
[Sirotkin A.V., Kisová G., Brenaut P., Ovcharenko D., Grossmann R., Mlyncek M. (2014). Involvement of microRNA Mir15a in control of human ovarian granulosa cell proliferation, apoptosis, steroidogenesis, and response to FSH. MicroRNA, 3: 29–36.]Search in Google Scholar
[Tian F., Luo J., Zhang H., Chang S., Song J. (2012). MiRNA expression signatures induced by Marek’s disease virus infection in chickens. Genomics, 99: 152–159.]Search in Google Scholar
[Vandesompele J., De Preter K., Pattyn F., Poppe B., Van Roy N., De Paepe A., Speleman F. (2002). Accurate normalisation of real-time quantitative RT×PCR data by geometric averaging of multiple internal control genes. Genome Biol., 18:3, Research 0034.]Search in Google Scholar
[Wang Q., Gao Y., Ji X., Qi X., Qin L., Gao H., Wang Y., Wang X. (2013). Differential expression of microRNAs in avian leukosis virus subgroup J-induced tumors. Vet. Microbiol., 162: 232–238.]Search in Google Scholar
[Wang W., Wu K., Jia M., Sun S., Kang L., Zhang Q., Tang H. (2018). Dynamic changes in the global microRNAome and transcriptome identify key nodes associated with ovarian development in chickens. Front. Genet., 9: 491.]Search in Google Scholar
[Wu N., Gaur U., Zhu Q., Chen B., Xu Z., Zhao X., Yang M., Li D. (2017). Expressed microRNA associated with high rate of egg production in chicken ovarian follicles. Anim. Genet., 48: 2005–2016.]Search in Google Scholar
[Xu Q., Zhang Y., Chen Y., Tong Y.Y., Rong G.H., Huang Z.Y., Zhao R.X., Zhao W.M., Wu X.S., Chang G.B., Chen G.H. (2014). Identification and differential expression of microRNAs in ovaries of laying and broody geese (Anser cygnoides) by Solexa sequencing. PLosOne, 9(2):e87920.]Search in Google Scholar