SSR‐patchwork: An optimized protocol to obtain a rapid and inexpensive SSR library using first‐generation sequencing technology1. (2nd January 2013)

• Record Type: Journal Article
• Authors: Di Maio, Antonietta; De Castro, Olga
• Is Part Of: Applications in plant sciences. Volume 1:Number 1(2013)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2013-01-02
• Subjects: double PCR enrichment -- first‐generation sequencing -- microsatellites -- optimized protocol -- patchwork -- SSR library; Plants -- Periodicals; Plant physiology -- Periodicals; Plant Physiological Phenomena; Plant physiology; Plants; Periodicals; Periodicals; Fulltext; Internet Resources; Periodicals; 580
• DOI: 10.3732/apps.1200158
• Languages: English
• ISSNs: 2168-0450

Abstract

Abstract : Premise of the study: We have optimized a version of a microsatellite loci isolation protocol for first‐generation sequencing (FGS) technologies. The protocol is optimized to reduce the cost and number of steps, and it combines some procedures from previous simple sequence repeat (SSR) protocols with several key improvements that significantly affect the final yield of the SSR library. This protocol may be accessible for laboratories with a moderate budget or for which next‐generation sequencing (NGS) is not readily available. Methods and Results: We drew from classic protocols for library enrichment by digestion, ligation, amplification, hybridization, cloning, and sequencing. Three different systems were chosen: two with very different genome sizes ( Galdieria sulphuraria, 10 Mbp; Pancratium maritimum, 30 000 Mbp), and a third with an undetermined genome size ( Kochia saxicola ). Moreover, we also report the optimization of the sequencing reagents. A good frequency of the obtained microsatellite loci was achieved. Conclusions: The method presented here is very detailed; comparative tests with other SSR protocols are also reported. This optimized protocol is a promising tool for low‐cost genetic studies and the rapid, simple construction of homemade SSR libraries for small and large genomes.