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BackgroundMicrosatellite markers or Simple Sequence Repeats (SSRs) are the most popular markers in population/conservation genetics. However, the development of novel microsatellite markers has been impeded by high costs, a lack of available sequence data and technical difficulties. New species-specific microsatellite markers were required to investigate the evolutionary history of the Euphratica tree, Populus euphratica, the only tree species found in the desert regions of Western China and adjacent Central Asian countries.Methodology/principal findingsA total of 94,090 non-redundant Expressed Sequence Tags (ESTs) from P. euphratica comprising around 63 Mb of sequence data were searched for SSRs. 4,202 SSRs were found in 3,839 ESTs, with 311 ESTs containing multiple SSRs. The most common motif types were trinucleotides (37%) and hexanucleotides (33%) repeats. We developed primer pairs for all of the identified EST-SSRs (eSSRs) and selected 673 of these pairs at random for further validation. 575 pairs (85%) gave successful amplification, of which, 464 (80.7%) were polymorphic in six to 24 individuals from natural populations across Northern China. We also tested the transferability of the polymorphic eSSRs to nine other Populus species. In addition, to facilitate the use of these new eSSR markers by other researchers, we mapped them onto Populus trichocarpa scaffolds in silico and compiled our data into a web-based database (http://202.205.131.253:8080/poplar/resources/static_page/index.html).ConclusionsThe large set of validated eSSRs identified in this work will have many potential applications in studies on P. euphratica and other poplar species, in fields such as population genetics, comparative genomics, linkage mapping, QTL, and marker-assisted breeding. Their use will be facilitated by their incorporation into a user-friendly web-based database.

Predicting protein domains is essential for understanding a protein's function at the molecular level. However, up till now, there has been no direct and straightforward method for predicting protein domains in species without a reference genome sequence. In this study, we developed a functionality with a set of programs that can predict protein domains directly from genomic sequence data without a reference genome. Using whole genome sequence data, the programming functionality mainly comprised DNA assembly in combination with next-generation sequencing (NGS) assembly methods and traditional methods, peptide prediction and protein domain prediction. The proposed new functionality avoids problems associated with de novo assembly due to micro reads and small single repeats. Furthermore, we applied our functionality for the prediction of leucine rich repeat (LRR) domains in four species of Ficus with no reference genome, based on NGS genomic data. We found that the LRRNT_2 and LRR_8 domains are related to plant transpiration efficiency, as indicated by the stomata index, in the four species of Ficus. The programming functionality established in this study provides new insights for protein domain prediction, which is particularly timely in the current age of NGS data expansion.