The central mechanism which drives every living cell is protein synthesis, the so-called transcription, which is realized according to the genetic code. There are complex regulatory interactions that control transcription of genes to proteins. Owing to their inherent complexity, analysis of dynamical models of such interactions requires a scalable computational approach. In this paper we employ parallel LTL model checking for a case study of selected dynamic properties of an in silico model of transcription in Bacillus subtilis, a bacterium living in soil. Moreover, we show the general fact that crucial LTL properties characterising transcriptional dynamics can be inferred from network motifs commonly studied in systems biology.