Comparative transcriptome analysis of eggplant (Solanum melongena L.) and turkey berry (Solanum torvum Sw.): phylogenomics and disease resistance analysis

茄子(Solanum melongena L.)和土耳其莓(Solanum torvum Sw.)的比较转录组分析:系统发育基因组学和抗病性分析

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Abstract

BACKGROUND: Eggplant (Solanum melongena L.) and turkey berry (S. torvum Sw.), a wild ally of eggplant with promising multi-disease resistance traits, are of great economic, medicinal and genetic importance, but genomic resources for these species are lacking. In the present study, we sequenced the transcriptomes of eggplant and turkey berry to accelerate research on these two non-model species. RESULTS: We built comprehensive, high-quality de novo transcriptome assemblies of the two Leptostemonum clade Solanum species from short-read RNA-Sequencing data. We obtained 34,174 unigenes for eggplant and 38,185 unigenes for turkey berry. Functional annotations based on sequence similarity to known plant datasets revealed a distribution of functional categories for both species very similar to that of tomato. Comparison of eggplant, turkey berry and another 11 plant proteomes resulted in 276 high-confidence single-copy orthologous groups, reasonable phylogenetic tree inferences and reliable divergence time estimations. From these data, it appears that eggplant and its wild Leptostemonum clade relative turkey berry split from each other in the late Miocene, ~6.66 million years ago, and that Leptostemonum split from the Potatoe clade in the middle Miocene, ~15.75 million years ago. Furthermore, 621 and 815 plant resistance genes were identified in eggplant and turkey berry respectively, indicating the variation of disease resistance genes between them. CONCLUSIONS: This study provides a comprehensive transcriptome resource for two Leptostemonum clade Solanum species and insight into their evolutionary history and biological characteristics. These resources establish a foundation for further investigations of eggplant biology and for agricultural improvement of this important vegetable. More generally, we show that RNA-Seq is a fast, reliable and cost-effective method for assessing genome evolution in non-model species.

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