RESUMO
Callicarpa nudiflora,which is a big brand of Li nationality medicine with Hainan characteristics,has the effects of dissolving stasis,hemostasis,anti-inflammatory and antibacterial. At present,there is a lack of information about the reference genome of C. nudiflora. The study of the genome size,heterozygosity rate and characteristics of SSR of C. nudiflora,can provide an effective basis for the formulation of the whole genome de novo sequencing strategy and development of SSR molecular markers of C. nudiflora. To realize this purpose,high throughput sequencing platform Illumina Hiseq was used to sequence the genome structure of C. nudiflora and K-mer analysis was applied to estimate genome size,repeat sequences and heterozygosity rate. Simple-sequence repeat( SSR) loci that are suitable as markers were identified by MISA software. The results showed the estimated genome size of C. nudiflora was 822. 43 Mb,with a 0. 85% heterozygosity rate and 71. 67% repeats,and the GC content of genome was about 49. 20%. Therefore,C. nudiflora belongs to a complex genome with high heterozygosity and repetition. SSR molecular genetic markers were analyzed in the genome sequence,and a total of 206 049 SSRs were identified,among which mono-nucleotide,di-nucleotide and tri-nucleotide repetitive motifs summed up to 198 993,accounting for 96. 57% of the total SSRs. Among the 2-6 nucleotide repeats,AT/AT,AAT/ATT,AGCC/CTGG,AAAAT/ATTTT and AGATAT/ATATCT have the largest number,respectively. This report represents the first genome-wide characterization of C. nudiflora,and provides a reference for the construction of the library for the fine sequencing of the genome,and a molecular basis for the development of SSR molecular markers as well as for the protection and utilization of gene resources.
Assuntos
Callicarpa/genética , Genoma de Planta , Repetições de Microssatélites , Marcadores Genéticos , Polimorfismo GenéticoRESUMO
A novel method was developed for the rapid determination of multi-indicators in corni fructus by means of near infrared (NIR) spectroscopy. Particle swarm optimization (PSO) based least squares support vector machine was investigated to increase the levels of quality control. The calibration models of moisture, extractum, morroniside and loganin were established using the PSO-LS-SVM algorithm. The performance of PSO-LS-SVM models was compared with partial least squares regression (PLSR) and back propagation artificial neural network (BP-ANN). The calibration and validation results of PSO-LS-SVM were superior to both PLS and BP-ANN. For PSO-LS-SVM models, the correlation coefficients (r) of calibrations were all above 0.942. The optimal prediction results were also achieved by PSO-LS-SVM models with the RMSEP (root mean square error of prediction) and RSEP (relative standard errors of prediction) less than 1.176 and 15.5% respectively. The results suggest that PSO-LS-SVM algorithm has a good model performance and high prediction accuracy. NIR has a potential value for rapid determination of multi-indicators in Corni Fructus.