RESUMO
To better understand the reproductive transformation mechanism of Daphnia carinata, a Doublesex (Dsx) gene was cloned based on rapid amplification of cDNA ends (RACE), and was designated DapcaDsx2. Next, we compared similarities and assumed homology based on deduced amino acid sequences. It showed 97.52, 87.94, and 85.11% identity to orthologous genes in D. magna, D. pulex, and D. galeata respectively. Phylogenetic analysis revealed that DapcaDsx2 clustered in the same class, and was evolutionarily more distant to sequences from other species. qRT-PCR showed that DapcaDsx2 was most abundantly expressed during sexual reproduction (P < 0.05). Using digoxigenin-labeled RNA probes, we studied DapcaDsx2 expression in parthenogenetic and sexual females by whole-mount in situ hybridization. The results revealed that DapcaDsx2 was mainly expressed in the second antennae and several sites of the ventral carapace, whereas higher expression levels were found in sexual than in parthenogenetic females. This suggests that the DapcaDsx2 gene is involved in switching modes of reproduction and in sexual differentiation.
Assuntos
Proteínas de Artrópodes/genética , Daphnia/genética , Partenogênese/genética , Filogenia , Reprodução/genética , Sequência de Aminoácidos , Animais , Clonagem Molecular , DNA Complementar , Proteínas de Ligação a DNA/genética , Daphnia/crescimento & desenvolvimento , Proteínas de Drosophila/genética , Feminino , Regulação da Expressão Gênica no DesenvolvimentoRESUMO
Aimed to address the defects of the large mean square error (MSE), and the slow convergence speed in equalizing the multi-modulus signals of the constant modulus algorithm (CMA), a multi-modulus algorithm (MMA) based on global artificial fish swarm (GAFS) intelligent optimization of DNA encoding sequences (GAFS-DNA-MMA) was proposed. To improve the convergence rate and reduce the MSE, this proposed algorithm adopted an encoding method based on DNA nucleotide chains to provide a possible solution to the problem. Furthermore, the GAFS algorithm, with its fast convergence and global search ability, was used to find the best sequence. The real and imaginary parts of the initial optimal weight vector of MMA were obtained through DNA coding of the best sequence. The simulation results show that the proposed algorithm has a faster convergence speed and smaller MSE in comparison with the CMA, the MMA, and the AFS-DNA-MMA.