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.

Using next-generation sequencing technology alone, we have successfully generated and assembled a draft sequence of the giant panda genome. The assembled contigs (2.25 gigabases (Gb)) cover approximately 94% of the whole genome, and the remaining gaps (0.05 Gb) seem to contain carnivore-specific repeats and tandem repeats. Comparisons with the dog and human showed that the panda genome has a lower divergence rate. The assessment of panda genes potentially underlying some of its unique traits indicated that its bamboo diet might be more dependent on its gut microbiome than its own genetic composition. We also identified more than 2.7 million heterozygous single nucleotide polymorphisms in the diploid genome. Our data and analyses provide a foundation for promoting mammalian genetic research, and demonstrate the feasibility for using next-generation sequencing technologies for accurate, cost-effective and rapid de novo assembly of large eukaryotic genomes.

Dendritic cells (DC) are professional antigen-presenting cells that orchestrate immune responses. The human DC population comprises two main functionally specialized lineages, whose origins and differentiation pathways remain incompletely defined. Here, we combine two high-dimensional technologies-single-cell messenger RNA sequencing (scmRNAseq) and cytometry by time-of-flight (CyTOF)-to identify human blood CD123CD33CD45RA DC precursors (pre-DC). Pre-DC share surface markers with plasmacytoid DC (pDC) but have distinct functional properties that were previously attributed to pDC. Tracing the differentiation of DC from the bone marrow to the peripheral blood revealed that the pre-DC compartment contains distinct lineage-committed subpopulations, including one early uncommitted CD123 pre-DC subset and two CD45RACD123 lineage-committed subsets exhibiting functional differences. The discovery of multiple committed pre-DC populations opens promising new avenues for the therapeutic exploitation of DC subset-specific targeting.

ResultsActivation of NLRP3 inflammasome is dampened in bat primary immune cells. Following priming (signal 1) and activation (signal 2), NLRP3 triggers assembly of the diffuse cytosolic apoptosis-associated speck-like protein containing a CARD (ASC) protein to form ASC specks 40 . These then recruit and activate caspase-1 to promote inflammatory cell death via pyroptosis and cleavage/secretion of the potent pro-inflammatory cytokine interleukin-1β (IL-1β) ( Fig. 1a).Bats are special in their ability to host emerging viruses. As the only flying mammal, bats endure high metabolic rates yet exhibit elongated lifespans. It is currently unclear whether these unique features are interlinked. The important inflammasome sensor, NLR family pyrin domain containing 3 (NLRP3), has been linked to both viral-induced and age-related inflammation. Here, we report significantly dampened activation of the NLRP3 inflammasome in bat primary immune cells compared to human or mouse counterparts. Lower induction of apoptosis-associated speck-like protein containing a CARD (ASC) speck formation and secretion of interleukin-1β in response to both 'sterile' stimuli and infection with multiple zoonotic viruses including influenza A virus (−single-stranded (ss) RNA), Melaka virus (PRV3M, double-stranded RNA) andMiddle East respiratory syndrome coronavirus (+ssRNA) was observed. Importantly, this reduction of inflammation had no impact on the overall viral loads. We identified dampened transcriptional priming, a novel splice variant and an altered leucine-rich repeat domain of bat NLRP3 as the cause. Our results elucidate an important mechanism through which bats dampen inflammation with implications for longevity and unique viral reservoir status.

BackgroundMicroRNAs (miRNAs) are small (~19-24nt) non-coding RNAs that play important roles in various biological processes. To date, the next-generation sequencing (NGS) technology has been widely used to discover miRNAs in plants and animals. Although evolutionary analysis is important to reveal the functional dynamics of miRNAs, few computational tools have been developed to analyze the evolution of miRNA sequence and expression across species, especially the newly emerged ones,ResultsWe developed miREvo, an integrated software platform with a graphical user interface (GUI), to process deep-sequencing data of small RNAs and to analyze miRNA sequence and expression evolution based on the multiple-species whole genome alignments (WGAs). Three major features are provided by miREvo: (i) to identify novel miRNAs in both plants and animals, based on a modified miRDeep algorithm, (ii) to detect miRNA homologs and measure their pairwise evolutionary distances among multiple species based on a WGA, and (iii) to profile miRNA expression abundances and analyze expression divergence across multiple species (small RNA libraries). Moreover, we demonstrated the utility of miREvo with Illumina data sets from Drosophila melanogaster and Arabidopsis, respectively.ConclusionThis work presents an integrated pipline, miREvo, for exploring the expressional and evolutionary dynamics of miRNAs across multiple species. MiREvo is standalone, modular, and freely available at http://evolution.sysu.edu.cn/software/mirevo.htm under the GNU/GPL license.

Identifying interactions between known drugs and targets is a major challenge in drug repositioning. In silico prediction of drug-target interaction (DTI) can speed up the expensive and time-consuming experimental work by providing the most potent DTIs. In silico prediction of DTI can also provide insights about the potential drug-drug interaction and promote the exploration of drug side effects. Traditionally, the performance of DTI prediction depends heavily on the descriptors used to represent the drugs and the target proteins. In this paper, to accurately predict new DTIs between approved drugs and targets without separating the targets into different classes, we developed a deep-learning-based algorithmic framework named DeepDTIs. It first abstracts representations from raw input descriptors using unsupervised pretraining and then applies known label pairs of interaction to build a classification model. Compared with other methods, it is found that DeepDTIs reaches or outperforms other state-of-the-art methods. The DeepDTIs can be further used to predict whether a new drug targets to some existing targets or whether a new target interacts with some existing drugs.

Most aerial surfaces of plants are covered by cuticular wax that is synthesized in epidermal cells. The wax mixture on the inflorescence stems of Arabidopsis (Arabidopsis thaliana) is dominated by alkanes, secondary alcohols, and ketones, all thought to be formed sequentially in the decarbonylation pathway of wax biosynthesis. Here, we used a reverse-genetic approach to identify a cytochrome P450 enzyme (CYP96A15) involved in wax biosynthesis and characterized it as a midchain alkane hydroxylase (MAH1). Stem wax of T-DNA insertional mutant alleles was found to be devoid of secondary alcohols and ketones (mah1-1) or to contain much lower levels of these components (mah1-2 and mah1-3) than wild type. All mutant lines also had increased alkane amounts, partially or fully compensating for the loss of other compound classes. In spite of the chemical variation between mutant and wild-type waxes, there were no discernible differences in the epicuticular wax crystals on the stem surfaces. Mutant stem wax phenotypes could be partially rescued by expression of wild-type MAH1 under the control of the native promoter as well as the cauliflower mosaic virus 35S promoter. Cauliflower mosaic virus 35S-driven overexpression of MAH1 led to ectopic accumulation of secondary alcohols and ketones in Arabidopsis leaf wax, where only traces of these compounds are found in the wild type. The newly formed leaf alcohols and ketones had midchain functional groups on or next to the central carbon, thus matching those compounds in wild-type stem wax. Taken together, mutant analyses and ectopic expression of MAH1 in leaves suggest that this enzyme can catalyze the hydroxylation reaction leading from alkanes to secondary alcohols and possibly also a second hydroxylation leading to the corresponding ketones. MAH1 expression was largely restricted to the expanding regions of the inflorescence stems, specifically to the epidermal pavement cells, but not in trichomes and guard cells. MAH1-green fluorescent protein fusion proteins localized to the endoplasmic reticulum, providing evidence that both intermediate and final products of the decarbonylation pathway are generated in this subcellular compartment and must subsequently be delivered to the plasma membrane for export toward the cuticle.

Cassava is a major tropical food crop in the Euphorbiaceae family that has high carbohydrate production potential and adaptability to diverse environments. Here we present the draft genome sequences of a wild ancestor and a domesticated variety of cassava and comparative analyses with a partial inbred line. We identify 1,584 and 1,678 gene models specific to the wild and domesticated varieties, respectively, and discover high heterozygosity and millions of single-nucleotide variations. Our analyses reveal that genes involved in photosynthesis, starch accumulation and abiotic stresses have been positively selected, whereas those involved in cell wall biosynthesis and secondary metabolism, including cyanogenic glucoside formation, have been negatively selected in the cultivated varieties, reflecting the result of natural selection and domestication. Differences in microRNA genes and retrotransposon regulation could partly explain an increased carbon flux towards starch accumulation and reduced cyanogenic glucoside accumulation in domesticated cassava. These results may contribute to genetic improvement of cassava through better understanding of its biology.