| Literature DB >> 28634825 |
Dong-Xiu Xue1,2, Yu-Long Li1,2, Jin-Xian Liu3,4.
Abstract
As one of the most informative and versatile DNA-based markers, microsatellites have been widely used in population and conservation genetic studies. However, the development of microsatellites has traditionally been laborious, time-consuming, and expensive. In the present study, a rapid and cost-effective "RAD-seq-Assembly-Microsatellite" approach was developed to identify abundant microsatellite markers in non-model species using the roughskin sculpin Trachidermus fasciatus as a representative. Overlapping paired-end Illumina reads generated by restriction-site-associated DNA sequencing (RAD-seq) were clustered based on the similarity of reads containing the restriction enzyme recognition site and then assembled into contigs, which were used for microsatellite discovery and primer design. A total of 121,750 RAD contigs were generated with a mean length of 522 bp, and 19,782 contigs contained microsatellite motifs. A total of 156,150 primer pairs were successfully designed based on 16,497 contigs containing priming sites. Experimental validation of 52 randomly selected microsatellite loci demonstrated that 45 (86.54%) loci were successfully amplified and polymorphic in two geographically isolated populations of T. fasciatus. Compared with traditional approaches based on DNA cloning and other approaches based on next-generation sequencing, our newly developed approach could yield thousands of microsatellite loci with much higher successful amplification rate and lower costs, especially for non-model species with shallow background of genomic information. The "RAD-seq-Assembly-Microsatellite" approach holds great promise for microsatellite development in future ecological and evolutionary studies of non-model species.Entities:
Keywords: Microsatellite; Next generation RAD sequencing; Non-model species; Population genetics; Trachidermus fasciatus
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Year: 2017 PMID: 28634825 DOI: 10.1007/s00438-017-1337-x
Source DB: PubMed Journal: Mol Genet Genomics ISSN: 1617-4623 Impact factor: 3.291