Co-Expression Network and Time-Course Expression Analyses to Identify Silk Protein Regulatory Factors in .

is an important economic insect and an animal model in pharmacomedical research. Although its physiology has been studied for many years, the mechanism via which silk protein genes are regulated remains unclear. In this study, we performed two-step expression screening, namely co-expression network and time-course expression analyses to screen silk protein regulation factors. A co-expression network analysis using RNA-seq data that were obtained from various tissues, including the silk glands of , was performed to identify novel silk protein regulatory factors. Overall, 91 transcription factors, including some known ones, were found to be co-expressed with silk protein genes. Furthermore, time-course expression analysis during the fifth instar larvae stage revealed that the expression pattern of 13 novel transcription factors was highly relevant to that of silk protein genes and their known regulatory factor genes. In particular, the expression peak of several transcription factors (TFs) was detected before the expression of silk protein genes peak. These results indicated that a larger number of genes than expected may be involved in silk protein regulation in . Functional analyses of function-unknown transcription factors should enhance our understanding of this system.