Shih (Asteraceae), an endangered genus endemic to the Taihang Mountains of China, is a high-value ornamental and medicinal plant consisting of two species, shih and (Ling) Shih. However, the evolutionary relationships and the taxonomic characteristics between the two species remain unknown. In this study, high-throughput transcriptome sequencing was used to analyze the differential metabolic activity and gene expression and screened special molecular markers for exploring the genetic variation and species differentiation in Shih. The results showed that 33,974 unigenes with an average size of 801 bp were obtained with optimization of assembly. The comprehensive functional annotation based on Gene Ontology (GO), Cluster of Orthologous Group (COG) and Kyoto Encyclopedia of Genes and Genomes pathway database (KEGG) revealed that these unigenes were mainly related to many physiological, metabolic, and molecular processes. Furthermore, the comparative transcriptome analysis indicated that 3,410 differentially expressed genes were mainly involved in lipid, carbohydrate and amino acid metabolism, xenobiotics biodegradation and metabolism as well as environment adaptation via KEGG. Such as the , , and so on, could be the potential candidate genes for further investigating the molecular mechanism of physiological variations between and . In addition, the potential 71,804 high quality single nucleotide polymorphisms (SNPs) and 1,444 simple sequence repeats (SSRs) were estimated. Based on the predicted SNP, we have developed eight SNP markers for population genetic analysis in Shih. A significantly high level of genetic differentiation between the populations of and were found, and they were clearly grouped into two distinct genetic clusters. These results conformed to the record of Flora Reipublicae Popularis Sinicae (FRPS) and unsupported the taxonomic status in the Flora of China. The transcriptome analysis of Shih can contribute to in-depth exploring of internal mechanisms in species variation and differentiation based on molecular evidence. With the rich and valuable data resources, the more novel structural, functional, and comparative genomic studies will provide comprehensive insights into the evolutionary relationships between and .