%A Xia,En-Hua %A Yao,Qiu-Yang %A Zhang,Hai-Bin %A Jiang,Jian-Jun %A Zhang,Li-Ping %A Gao,Li-Zhi %D 2016 %J Frontiers in Plant Science %C %F %G English %K transferability,CandiSSR,multiple assembled genomes,multiple assembled transcriptomes,microsatellites,Polymorphic SSR %Q %R 10.3389/fpls.2015.01171 %W %L %M %P %7 %8 2016-January-07 %9 Methods %+ Dr Li-Zhi Gao,Plant Germplasm and Genomics Center, Germplasm Bank of Wild Species in Southwest China, Kunming Institute of Botany, Chinese Academy of Sciences,Kunming, China,lgao@mail.kib.ac.cn %# %! An efficient polymorphic SSRs identification pipeline %* %< %T CandiSSR: An Efficient Pipeline used for Identifying Candidate Polymorphic SSRs Based on Multiple Assembled Sequences %U https://www.frontiersin.org/articles/10.3389/fpls.2015.01171 %V 6 %0 JOURNAL ARTICLE %@ 1664-462X %X Simple sequence repeats (SSRs), also known as microsatellites, are ubiquitous short tandem duplications commonly found in genomes and/or transcriptomes of diverse organisms. They represent one of the most powerful molecular markers for genetic analysis and breeding programs because of their high mutation rate and neutral evolution. However, traditionally experimental screening of the SSR polymorphic status and their subsequent applicability to genetic studies are extremely labor-intensive and time-consuming. Thankfully, the recently decreased costs of next generation sequencing and increasing availability of large genome and/or transcriptome sequences have provided an excellent opportunity and sources for large-scale mining this type of molecular markers. However, current tools are limited. Thus we here developed a new pipeline, CandiSSR, to identify candidate polymorphic SSRs (PolySSRs) based on the multiple assembled sequences. The pipeline allows users to identify putative PolySSRs not only from the transcriptome datasets but also from multiple assembled genome sequences. In addition, two confidence metrics including standard deviation and missing rate of the SSR repetitions are provided to systematically assess the feasibility of the detected PolySSRs for subsequent application to genetic characterization. Meanwhile, primer pairs for each identified PolySSR are also automatically designed and further evaluated by the global sequence similarities of the primer-binding region, ensuring the successful rate of the marker development. Screening rice genomes with CandiSSR and subsequent experimental validation showed an accuracy rate of over 90%. Besides, the application of CandiSSR has successfully identified a large number of PolySSRs in the Arabidopsis genomes and Camellia transcriptomes. CandiSSR and the PolySSR marker sources are publicly available at: http://www.plantkingdomgdb.com/CandiSSR/index.html.