Coenurosis, caused by the larval coenurus of the tapeworm Taenia multiceps, is a fatal central nervous system disease in both sheep and humans. Though treatment and prevention options are available, the control of coenurosis still faces presents great challenges. Here, we present a high-quality genome sequence of T. multiceps in which 240 Mb (96%) of the genome has been successfully assembled using Pacbio single-molecule real-time (SMRT) and Hi-C data with a N50 length of 44.8 Mb. In total, 49.5 Mb (20.6%) repeat sequences and 13, 013 gene models were identified. We found that Taenia spp. have an expansion of transposable elements and recent small-scale gene duplications following the divergence of Taenia from Echinococcus, but not in Echinococcus genomes, and the genes underlying environmental adaptability and dosage effect tend to be over-retained in the T. multiceps genome. Moreover, we identified several genes encoding proteins involved in proglottid formation and interactions with the host central nervous system, which may contribute to the adaption of T. multiceps to its parasitic life style. Our study not only provides insights into the biology and evolution of T. multiceps, but also identifies a set of species-specific gene targets for developing novel treatment and control tools for coenurosis.

Background: With the fast development of next generation sequencing technologies, increasing numbers of genomes are being de novo sequenced and assembled. However, most are in fragmental and incomplete draft status, and thus it is often difficult to know the accurate genome size and repeat content. Furthermore, many genomes are highly repetitive or heterozygous, posing problems to current assemblers utilizing short reads. Therefore, it is necessary to develop efficient assembly-independent methods for accurate estimation of these genomic characteristics. Results: Here we present a framework for modeling the distribution of k-mer frequency from sequencing data and estimating the genomic characteristics such as genome size, repeat structure and heterozygous rate. By introducing novel techniques of k-mer individuals, float precision estimation, and proper treatment of sequencing error and coverage bias, the estimation accuracy of our method is significantly improved over existing methods. We also studied how the various genomic and sequencing characteristics affect the estimation accuracy using simulated sequencing data, and discussed the limitations on applying our method to real sequencing data. Conclusion: Based on this research, we show that the k-mer frequency analysis can be used as a general and assembly-independent method for estimating genomic characteristics, which can improve our understanding of a species genome, help design the sequencing strategy of genome projects, and guide the development of assembly algorithms. The programs developed in this research are written using C/C++, and freely accessible at Github URL (this https URL) or BGI ftp ( this ftp URL).