Project description:Purpose: With the advent of next generation sequencing technologies, several researches have been focused on the molecular mechanism underlying the innate immunity of insects based on the changes of gene expression profiles in hemolymph. The goal of this study is to detect the differences in transcript levels in A. pernyi hemolymph in response to ApNPV. Methods:The A. pernyi hemolymph infected by ApNPV and normal samples were generated by deep sequencing, in triplicate, using Illumina Hiseq 4000. The high-quality reads were obtained by removing the reads that contained adaptor contamination, low quality bases and undetermined bases.The transcriptome were de novo assembly. Results:We constructed six cDNA libraries using RNA samples from the hemolymph in ApNPV-infected and non-infected A. pernyi larvae with three replicates for each group. A total of 50459962, 49797542, 54402474 and 56342454, 56036432, 55471402 raw reads in ApNPV-infected and control groups were generated. After filtering, 48009732, 47241848, 51319586 and 53555764, 53364108, 53077540 clean reads were obtained. All short-read sequences were assembled into 49966 transcripts and 37498 unigenes. Conclusions: The transcriptome sequences were de novo assembled. The differentially expressed genes (DEGs) including both up- and down-regulated genes were obtained. We focused on the innate immunity related DEGs, and screened numerous of DEGs involved in cellular and humoral immune related pathways via bioinformatic analysis. The results of this study lay the foundation for a better understanding of the molecular mechanisms of cellular and humoral immunity of A. pernyi.
Project description:Purpose: The goal of this study is to analyze the transcriptome profile changes of the cuticles between ApNPV-infected and non-infected A. pernyi larvae for investigating themolecular mechanisms of cuticle liquefaction of A. pernyi induced by ApNPV infection. Methods:The A. pernyi cuticles infected by ApNPV and normal samples were generated by deep sequencing, in triplicate, using Illumina Hiseq 4000. The high-quality reads were obtained by removing the reads that contained adaptor contamination, low quality bases and undetermined bases.The transcriptome were de novo assembly. Results:The RNA-seq data generated 57332226, 48859400, 50197630 and 52086538, 52447736, 47585326 raw reads from ApNPV-infected and control groups, respectively. After data filtering, 55715544, 48130252, 49354556, 51102012, 51633978, 46798094 clean reads were obtained (Table1). Using the Trinity de novo assembly programme, all short-read sequences were assembled into 87036 transcripts and 50126 unigenes. Conclusions:We systematically analyzed the gene expressional profiles and obtained both up- and down-regulated genes in ApNPV-infected cuticle compared with control. Meanwhile, we screened the chitin metabolism-related differentially expressed genes (DEGs) from the transcriptome data, and further characterized those DEGs based on their expression profiles challenged by ApNPV. Our research findings lay the foundation for further research on the molecular mechanisms of liquefaction induced by viral infection in insect.
