Passion fruit (Passiflora edulis Sims) can be divided into yellow and purple varieties. However, information about coloration and fruit quality between the two varieties is limited. To reveal the underlying mechanism of color formation in this fruit, a combined analysis of the metabolome and transcriptome was conducted in this study. The results showed that most of the evaluated flavonols, anthocyanins, and flavanols were significantly upregulated in purple fruit compared to their levels in yellow fruit. Flavonoid and flavonoid carbonoside accumulation was markedly higher in yellow fruit than in purple fruit. The accumulation of organic acids, phenolic acids, lipids, sugars, and lignans was significantly different in the yellow and purple varieties. These results were consistent with the results from the RNA-Seq profile. This study will enable us to identify genes for targeted genetic engineering to improve the nutritional and market value of passion fruit. In addition, the peel and pulp of passion fruit contained certain health-promoting compounds, highlighting the potential application of passion fruit as a functional food and providing direction for future breeding programs and production.

BackgroundSugarcane (Saccharum officinarum L.) is an economically important crop, mainly due to the production of sugar and biofuel (Azevedo RA, Carvalho RF, Cia MC, & Gratão PL, Trop Plant Biol 4:42-51, 2011). Grown mainly in tropical and subtropical countries, sugarcane is a highly polyploid plant with up to ten copies of each chromosome, which increases the difficulties of genome assembly and genetic, physiologic and biochemical analyses. The increasing demands of sugar and the increasing cost of sugarcane harvest require sugarcane varieties which can shed their leaves during the maturity time, so it is important to study the mechanism of leaf abscission in sugarcane.ResultsTo improve the understanding of miRNA roles in sugarcane leaf abscission, we reported the genome-wide characterization of miRNAs and their putative targets in sugarcane using deep sequencing for six small RNA libraries. In total, 93 conserved miRNAs and 454 novel miRNAs were identified in sugarcane using previously reported transcriptome as reference. Among them, 25 up-regulated and 13 down-regulated miRNAs were identified in leaf abscission sugarcane plants (LASP) compared to leaf packaging sugarcane plants (LPSP). Target prediction revealed several miRNA-mRNA modules including miR156-SPL, miR319-TPR2, miR396-GRF and miR408-LAC3 might be involved in the sugarcane leaf abscission. KEGG pathway enrichment analysis showed differentially expressed miRNAs may regulate pathways like “plant hormone signal transduction” and “plant-pathogen interaction”, which is consistent with previous transcriptome study. In addition, we identified 96 variant miRNAs with 135 single nucleotide polymorphisms (SNPs). The expression of sugarcane miRNAs and variant miRNAs were confirmed by qRT-PCR. We identified a possible poaceae specific miRNA called miR5384 for the first time in sugarcane.ConclusionsWe not only reported miR5384, a possible poaceae specific miRNA, for the first time in sugarcane but also presented some miRNA-mRNA modules including miR156-SPL, miR319-TPR2, miR396-GRF and miR408-LAC in sugarcane. These modules might be involved in the regulation of sugarcane leaf abscission during the maturity time. All of these findings may lay ground work for future application of sugarcane breeding program and benefit research studies of sugarcane miRNAs.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-017-4053-3) contains supplementary material, which is available to authorized users.

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In this paper, an ARTLoc (accuracy and real-time commercial localization) system is proposed, which is applicable for positioning the Minimization of Drive-Tests(MDT) data in the long-termevolution(LTE) cellular communication network system. This system utilizes a collaborative filtering algorithm to ensure the robustness and accuracy of the fingerprint database when both base station position and GPS MDT data are abnormal in commercial communication service provider(CSP) MDT localization scene. Then, a fast matching KNN algorithm including coarse matching and fine matching is proposed to improve the location efficiency and reduce the location cost under the premise of ensuring high location accuracy. The results of experiments conducted in an in-service LTE network using more than 1000 LTE base station demonstrate that the proposed technique yields a location accuracy of 65.7 meters(@67%) with DT data and 62.1 meters(@67%) with massive GPS MDT data(over 10 million), which provides at least 184.2% and 145.2% enhancement in accuracy respectively compared to the traditional technology. In addition, our system provides a more than 7 times improvement in location efficiency compared to traditional technology. This proposed localization technique is applicable in network optimization and Operation and Maintenance(O&M) to assist CSP to reduce their operating expense(OPEX) by positioning those MDT data without GPS location.

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