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Despite thousands of sex-biased genes being found in chickens, the genetic control of sexually dimorphic and left-right asymmetry during gonadal differentiation is not yet completely understood. This study aimed to identify microRNAs ( miRNAs ), long noncoding RNAs ( lncRNAs ), messenger RNAs ( mRNAs ), and signaling pathways during gonadal differentiation in chick embryos (day 6/stage 29). The left and right gonads were collected for RNA sequencing. Sex-biased, side-biased miRNAs, lncRNAs, mRNAs, and shared differentially expressed miRNAs ( DEmiRNA )–differentially expressed mRNAs ( DEmRNA )–differentially expressed lncRNAs ( DElncRNA ) interaction networks were performed. A total of 8 DEmiRNAs, 183 DElncRNAs, and 123 DEmRNAs were identified for the sex-biased genes, and 7 DEmiRNAs, 189 DElncRNAs, and 183 DEmRNAs for the side-biased genes. The results of quantitative real-time PCR were generally consistent with the RNA-sequencing results. The study suggested that miRNAs and lncRNAs regulation were novel gene-specific dosage compensation mechanism and they could contribute to left-right asymmetry of chicken, but sex-biased and side-biased miRNAs, lncRNAs, and mRNAs were independent of each other. The competing endogenous RNA ( ceRNA ) networks showed that 17 target pairs including miR-7b ( CYP19A1 , FSHR , GREB1 , STK31 , CORIN , and TDRD9 ), miR-211 ( FSHR , GREB1 , STK31 , CORIN , and TDRD9 ), miR-204 ( FSHR , GREB1 , CORIN , and TDRD9 ), and miR-302b-5p ( CYP19A1 and TDRD9 ) may play crucial roles in ovarian development. These analyses provide new clues to uncover molecular mechanisms and signaling networks of ovarian development.

During the COVID-19 epidemic, college students could not return to the school, which had a great impact on the talent training of colleges and universities. Based on the statistical learning theory, this paper puts forward an evaluation model for the cultivation of innovative talents in universities after the epidemic. In this paper, the evaluation index system of the quality of innovative and entrepreneurial personnel training in Universities, which is composed of four first-class indexes: environment, teaching links, teachers and students, is constructed. At the same time, this paper uses the fuzzy comprehensive evaluation method for empirical research. Firstly, the factor set of the evaluation object and the grade domain of the comprehensive evaluation are determined. Then, AHP is used to determine the weight of evaluation indexes and expert scoring method is used to determine the single factor fuzzy comprehensive evaluation matrix of each level. According to the evaluation matrix, the fuzzy relation between evaluation object and evaluation set is calculated. Finally, according to the principle of maximum membership degree, the evaluation grade corresponding to the maximum value in the fuzzy relation set is calculated as the evaluation result of the final evaluation object. The empirical results show that this method can improve the accuracy of the evaluation model of innovation and entrepreneurship talent training, and has a certain reference value for the talent training in Universities.

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