title: [Data mining of simple sequence repeats in transcriptome sequences of Tibetan medicinal plant Zangyinchen Swertia mussotii].
abstract: MISA (MicroSAtelite) software was employed to screen SSRs in 68 787 contigs of Swertia mussotii transcriptome sequences. 5 610 SSRs were distributed in 5 099 contigs which accounted for 7.41% of 68 787 contigs. There are 220 kinds of SSR motifs existing in S. mussotii transcriptome. On average, SSRs occurred every 12.60 kb in length. In the SSRs, the tri-nucleotide repeat motif was the most abundant (45.99%), followed by the di-nucleotide (41.62%). AT/TA and AAT/TTA were the main types of motif in di-, tri-nucleotide repeats. The repeat numbers of SSRs which from S. mussotii transcriptome SSRs were mainly from 5 to 10 and motif length of them mostly ranged from 12 bp to 30 bp. A total of 30 651 contigs were annotated, and only 1 447 SSRs were occurred in protein-coding regions. In the six repeat motifs, tri-nucleotide repeats were the most abundant in coding regions (928). There are abundant SSRs in S. mussotii transcriptome with high frequency and various types, indicating their usefulness in theory. This research may lay the foundation for designing the targeted SSR primers and developing SSR molecular markers by mining the information of SSRs loci in S. mussotii transcriptome sequences data.
authors.forename: Yue
authors.initials: Y
authors.lastname: Liu
authors.lastname: Yue Chun-Jiang
authors.forename: Yi
authors.initials: Y
authors.lastname: Wang
authors.forename: Jia-qiang
authors.initials: JQ
authors.lastname: Ma
authors.forename: Hong-bo
authors.initials: HB
authors.lastname: Sun
authors.forename: Min
authors.initials: M
authors.lastname: Luo
authors.forename: Peng-ju
authors.initials: PJ
authors.lastname: Ma
authors.forename: Lin-xia
authors.initials: LX
authors.lastname: Zhang
authors.forename: Xu
authors.initials: X
authors.lastname: Ma
authors.forename: Chuan-chuan
authors.initials: CC
authors.lastname: Chen
authors.forename: Hua
authors.initials: H
authors.lastname: Li
authors.forename: Li
authors.initials: L
authors.lastname: Tang
mesh_terms: D057225:Data Mining; D038861:Medicine, Tibetan Traditional; D018895:Microsatellite Repeats; D010946:Plants, Medicinal / Q000235:genetics; D029967:Swertia / Q000235:genetics*; D059467:Transcriptome