Cucumber is an economically important crop as well as a model system for sex determination studies and plant vascular biology. Here we report the draft genome sequence of Cucumis sativus var. sativus L., assembled using a novel combination of traditional Sanger and next-generation Illumina GA sequencing technologies to obtain 72.2-fold genome coverage. The absence of recent whole-genome duplication, along with the presence of few tandem duplications, explains the small number of genes in the cucumber. Our study establishes that five of the cucumber's seven chromosomes arose from fusions of ten ancestral chromosomes after divergence from Cucumis melo. The sequenced cucumber genome affords insight into traits such as its sex expression, disease resistance, biosynthesis of cucurbitacin and 'fresh green' odor. We also identify 686 gene clusters related to phloem function. The cucumber genome provides a valuable resource for developing elite cultivars and for studying the evolution and function of the plant vascular system.

BackgroundCucumber, Cucumis sativus L., is an economically and nutritionally important crop of the Cucurbitaceae family and has long served as a primary model system for sex determination studies. Recently, the sequencing of its whole genome has been completed. However, transcriptome information of this species is still scarce, with a total of around 8,000 Expressed Sequence Tag (EST) and mRNA sequences currently available in GenBank. In order to gain more insights into molecular mechanisms of plant sex determination and provide the community a functional genomics resource that will facilitate cucurbit research and breeding, we performed transcriptome sequencing of cucumber flower buds of two near-isogenic lines, WI1983G, a gynoecious plant which bears only pistillate flowers, and WI1983H, a hermaphroditic plant which bears only bisexual flowers.ResultUsing Roche-454 massive parallel pyrosequencing technology, we generated a total of 353,941 high quality EST sequences with an average length of 175bp, among which 188,255 were from gynoecious flowers and 165,686 from hermaphroditic flowers. These EST sequences, together with ~5,600 high quality cucumber EST and mRNA sequences available in GenBank, were clustered and assembled into 81,401 unigenes, of which 28,452 were contigs and 52,949 were singletons. The unigenes and ESTs were further mapped to the cucumber genome and more than 500 alternative splicing events were identified in 443 cucumber genes. The unigenes were further functionally annotated by comparing their sequences to different protein and functional domain databases and assigned with Gene Ontology (GO) terms. A biochemical pathway database containing 343 predicted pathways was also created based on the annotations of the unigenes. Digital expression analysis identified ~200 differentially expressed genes between flowers of WI1983G and WI1983H and provided novel insights into molecular mechanisms of plant sex determination process. Furthermore, a set of SSR motifs and high confidence SNPs between WI1983G and WI1983H were identified from the ESTs, which provided the material basis for future genetic linkage and QTL analysis.ConclusionA large set of EST sequences were generated from cucumber flower buds of two different sex types. Differentially expressed genes between these two different sex-type flowers, as well as putative SSR and SNP markers, were identified. These EST sequences provide valuable information to further understand molecular mechanisms of plant sex determination process and forms a rich resource for future functional genomics analysis, marker development and cucumber breeding.

Robot hands with tactile perception can improve the safety of object manipulation and also improve the accuracy of object identification. Here, we report the integration of quadruple tactile sensors onto a robot hand to enable precise object recognition through grasping. Our quadruple tactile sensor consists of a skin-inspired multilayer microstructure. It works as thermoreceptor with the ability to perceive thermal conductivity of a material, measure contact pressure, as well as sense object temperature and environment temperature simultaneously and independently. By combining tactile sensing information and machine learning, our smart hand has the capability to precisely recognize different shapes, sizes, and materials in a diverse set of objects. We further apply our smart hand to the task of garbage sorting and demonstrate a classification accuracy of 94% in recognizing seven types of garbage.