To study the mechanism of the biomolecular response in Exopalaemon carinicauda to starvation stress, we subjected muscle tissue RNA samples from four stress points, including 0 d(control group), 10 d, 20 d, and 30 d, to starvation stress on white ridgetail prawn with a body weight of 1.41 + 0.42 g, aquaculture water temperature of 23-25 °C, salinity of 26, dissolved oxygen ≥5 mg/L, and pH 8-8.5, Then performed de novo transcriptome assembly and gene expression analysis using BGISEQ-500 with a tag-based digital gene expression (DGE) system. By de novo assembling at the four times, we obtained 28,167, 21,115, 24,497, and 27,080 reads, respectively. The results showed that the stress at 10 d led to no significant difference in the expressed genes, while the stress at 20 d and 30 d showed a significant increase (or decrease) in the expression of 97 (276) and 143 (410) genes, respectively, which were involved in 8 different metabolic pathways. In addition, we detected 2647 unigene transcription factors. Eleven upregulated and sixteen downregulated genes from the different starvation stress groups were choose to verify the reliability of the transcriptome data, and the results showed that the expression trends of these genes were consistent with the results shown by the transcriptome. The analysis of the experimental data and our discussion of the response mechanism of white ridgetail prawn under starvation stress provides a foundation for further screening of the key genes of starvation stress and may help to elucidate their functions.
Enhancers are crucial in gene expression regulation, dictating the specificity and timing of transcriptional activity, which highlights the importance of their identification for unravelling the intricacies of genetic regulation. Therefore, it is critical to identify enhancers and their strengths. Repeated sequences in the genome are repeats of the same or symmetrical fragments. There has been a great deal of evidence that repetitive sequences contain enormous amounts of genetic information. Thus, We introduce the W2V-Repeated Index, designed to identify enhancer sequence fragments and evaluates their strength through the analysis of repeated K-mer sequences in enhancer regions. Utilizing the word2vector algorithm for numerical conversion and Manta Ray Foraging Optimization for feature selection, this method effectively captures the frequency and distribution of K-mer sequences. By concentrating on repeated K-mer sequences, it minimizes computational complexity and facilitates the analysis of larger K values. Experiments indicate that our method performs better than all other advanced methods on almost all indicators.