Simultaneously, multiplexed genome engineering and targeting multiple genomic loci are valuable to elucidating gene interactions and characterizing genetic networks that affect phenotypes. Here, we developed a general CRISPR-based platform to perform four functions and target multiple genome loci encoded in a single transcript. To establish multiple functions for multiple loci targets, we fused four RNA hairpins, MS2, PP7, com and boxB, to stem–loops of gRNA (guide RNA) scaffolds, separately. The RNA-hairpin-binding domains MCP, PCP, Com and λN22 were fused with different functional effectors. These paired combinations of cognate-RNA hairpins and RNA-binding proteins generated the simultaneous, independent regulation of multiple target genes. To ensure that all proteins and RNAs are expressed in one transcript, multiple gRNAs were constructed in a tandemly arrayed tRNA (transfer RNA)-gRNA architecture, and the triplex sequence was cloned between the protein-coding sequences and the tRNA-gRNA array. By leveraging this system, we illustrate the transcriptional activation, transcriptional repression, DNA methylation and DNA demethylation of endogenous targets using up to 16 individual CRISPR gRNAs delivered on a single transcript. This system provides a powerful platform to investigate synthetic biology questions and engineer complex-phenotype medical applications.

Background Insulin regulates glucose homeostasis and has important effects on metabolism, cell growth, and differentiation. Depending on the cell type and physiological context, insulin signal has specific pathways and biological outcomes in different tissues and cells. For studying the signal pathway of insulin on glycolipid metabolism in porcine embryonic fibroblast (PEF), we used high-throughput sequencing to monitor gene expression patterns regulated by insulin. Objectives The goal of our research was to see how insulin affected glucose and lipid metabolism in PEFs. Methods We cultured the PEFs with the addition of insulin and sampled them at 0, 48, and 72 h for RNA-Seq analysis in triplicate for each time point. Results At 48 and 72 h, 801 and 1,176 genes were differentially expressed, respectively. Of these, 272 up-regulated genes and 264 down-regulated genes were common to both time points. Gene Ontology analysis was used to annotate the functions of the differentially expressed genes (DEGs), the biological processes related to lipid metabolism and cell cycle were dominant. And the DEGs were significantly enriched in interleukin-17 signaling pathway, phosphatidylinositol-3-kinase-protein kinase B signaling pathway, pyruvate metabolism, and others pathways related to lipid metabolism by Kyoto Encyclopedia of Genes and Genomes enrichment analysis. Conclusions These results elucidate the transcriptomic response to insulin in PEF. The genes and pathways involved in the transcriptome mechanisms provide useful information for further research into the complicated molecular processes of insulin in PEF.