A draft genome and transcriptome of common milkweed (Asclepias syriaca) as resources for evolutionary, ecological, and molecular studies in milkweeds and Apocynaceae
Milkweeds (Asclepias) are used in wide-ranging studies including floral development, pollination biology, plant-insect interactions and co-evolution, secondary metabolite chemistry, and rapid diversification. We present a transcriptome and draft nuclear genome assembly of the common milkweed, Asclepias syriaca. This reconstruction of the nuclear genome is augmented by linkage group information, adding to existing chloroplast and mitochondrial genomic resources for this member of the Apocynaceae subfamily Asclepiadoideae. The genome was sequenced to 80.4× depth and the draft assembly contains 54,266 scaffolds ≥1 kbp, with N50 = 3,415 bp, representing 37% (156.6 Mbp) of the estimated 420 Mbp genome. A total of 14,474 protein-coding genes were identified based on transcript evidence, closely related proteins, and ab initio models, and 95% of genes were annotated. A large proportion of gene space is represented in the assembly, with 96.7% of Asclepias transcripts, 88.4% of transcripts from the related genus Calotropis, and 90.6% of proteins from Coffea mapping to the assembly. Scaffolds covering 75 Mbp of the Asclepias assembly formed 11 linkage groups. Comparisons of these groups with pseudochromosomes in Coffea found that six chromosomes show consistent stability in gene content, while one may have a long history of fragmentation and rearrangement. The progesterone 5β-reductase gene family, a key component of cardenolide production, is likely reduced in Asclepias relative to other Apocynaceae. The genome and transcriptome of common milkweed provide a rich resource for future studies of the ecology and evolution of a charismatic plant family.
Weitemier et al. (2019) A draft genome and transcriptome of common milkweed (Asclepias syriaca) as resources for evolutionary, ecological, and molecular studies in milkweeds and Apocynaceae. PeerJ 7:e7649 https://doi.org/10.7717/peerj.7649
Transposon mutagenesis reveals Pseudomonas cannabina pv. alisalensis optimizes its virulence factors for pathogenicity on different hosts
Pseudomonas cannabina pv. alisalensis (Pcal), which causes bacterial blight disease of Brassicaceae, is an economically important pathogen worldwide. To identify Pcal genes involved in pathogenesis, we conducted a screen for 1,040 individual Pcal KB211 Tn5 mutants with reduced virulence on cabbage plants using a dip-inoculation method. We isolated 53 reduced virulence mutants and identified several potential virulence factors involved in Pcal virulence mechanisms such as the type III secretion system, membrane transporters, transcription factors, and amino acid metabolism. Importantly, Pcal is pathogenic on a range of monocotyledonous and dicotyledonous plants. Therefore, we also carried out the inoculation test on oat plants, which are cultivated after cabbage cultivation as green manure crops. Interestingly among the 53 mutants, 31 mutants also exhibited reduced virulence on oat seedlings, indicating that Pcal optimizes its virulence factors for pathogenicity on different host plants. Our results highlight the importance of revealing the virulence factors for each plant host-bacterial interaction, and will provide new insights into Pcal virulence mechanisms.
Sakata et al. (2019) Transposon mutagenesis reveals Pseudomonas cannabina pv. alisalensis optimizes its virulence factors for pathogenicity on different hosts. PeerJ 7:e7698 https://doi.org/10.7717/peerj.7698
Complete chloroplast genome sequence of the mangrove species Kandelia obovata and comparative analyses with related species
As one of the most cold and salt-tolerant mangrove species, Kandelia obovata is widely distributed in China. Here, we report the complete chloroplast genome sequence K. obovata (Rhizophoraceae) obtained via next-generation sequencing, compare the general features of the sampled plastomes of this species to those of other sequenced mangrove species, and perform a phylogenetic analysis based on the protein-coding genes of these plastomes. The complete chloroplast genome of K. obovata is 160,325 bp in size and has a 35.22% GC content. The genome has a typical circular quadripartite structure, with a pair of inverted repeat (IR) regions 26,670 bp in length separating a large single-copy (LSC) region (91,156 bp) and a small single-cope (SSC) region (15,829 bp). The chloroplast genome of K. obovata contains 128 unique genes, including 80 protein-coding genes, 38 tRNA genes, 8 rRNA genes and 2 pseudogenes (ycf1 in the IRA region and rpl22 in the IRB region). In addition, a simple sequence repeat (SSR) analysis found 108 SSR loci in the chloroplast genome of K. obovata, most of which are A/T rich. IR expansion and contraction regions were compared between K. obovata and five related species: two from Malpighiales and three mangrove species from different orders. The mVISTA results indicated that the genome structure, gene order and gene content are highly conserved among the analyzed species. The phylogenetic analysis using 54 common protein-coding genes from the chloroplast genome showed that the plant most closely related to K. obovata is Ceriops tagal of Rhizophoraceae. The results of this study provide useful molecular information about the evolution and molecular biology of these mangrove trees.
Yang et al. (2019) Complete chloroplast genome sequence of the mangrove species Kandelia obovata and comparative analyses with related species. PeerJ 7:e7713 https://doi.org/10.7717/peerj.7713
Role of miR-10b-5p in the prognosis of breast cancer
Breast cancer is the leading cause of cancer-related death in women worldwide. Aberrant expression levels of miR-10b-5p in breast cancer has been reported while the molecular mechanism of miR-10b-5p in tumorigenesis remains elusive. Therefore, this study was aimed to investigate the role of miR-10b-5p in breast cancer and the network of its target genes using bioinformatics analysis. In this study, the expression profiles and prognostic value of miR-10b-5p in breast cancer were analyzed from public databases. Association between miR-10b-5p and clinicopathological parameters were analyzed by non-parametric test. Moreover, the optimal target genes of miR-10b-5p were obtained and their expression patterns were examined using starBase and HPA database. Additionally, the role of these target genes in cancer development were explored via Cancer Hallmarks Analytics Tool (CHAT). The protein–protein interaction (PPI) networks were constructed to further investigate the interactive relationships among these genes. Furthermore, GO, KEGG pathway and Reactome pathway analyses were carried out to decipher functions of these target genes. Results demonstrated that miR-10b-5p was down-regulated in breast cancer and low expression of miR-10b-5p was significantly correlated to worse outcome. Five genes, BIRC5, E2F2, KIF2C, FOXM1, and MCM5, were considered as potential key target genes of miR-10b-5p. As expected, higher expression levels of these genes were observed in breast cancer tissues than in normal tissues. Moreover, analysis from CHAT revealed that these genes were mainly involved in sustaining proliferative signaling in cancer development. In addition, PPI networks analysis revealed strong interactions between target genes. GO, KEGG, and Reactome pathway analysis suggested that these target genes of miR-10b-5p in breast cancer were significantly involved in cell cycle. Predicted target genes were further validated by qRT-PCR analysis in human breast cancer cell line MDA-MB-231 transfected with miR-10b mimic or antisense inhibitors. Taken together, our data suggest that miR-10b-5p functions to impede breast carcinoma progression via regulation of its key target genes and hopefully serves as a potential diagnostic and prognostic marker for breast cancer.
Wang et al. (2019) Role of miR-10b-5p in the prognosis of breast cancer. PeerJ 7:e7728 https://doi.org/10.7717/peerj.7728
Sleep apnea detection from a single-lead ECG signal with automatic feature-extraction through a modified LeNet-5 convolutional neural network
Sleep apnea (SA) is the most common respiratory sleep disorder, leading to some serious neurological and cardiovascular diseases if left untreated. The diagnosis of SA is traditionally made using Polysomnography (PSG). However, this method requires many electrodes and wires, as well as an expert to monitor the test. Several researchers have proposed instead using a single channel signal for SA diagnosis. Among these options, the ECG signal is one of the most physiologically relevant signals of SA occurrence, and one that can be easily recorded using a wearable device. However, existing ECG signal-based methods mainly use features (i.e. frequency domain, time domain, and other nonlinear features) acquired from ECG and its derived signals in order to construct the model. This requires researchers to have rich experience in ECG, which is not common. A convolutional neural network (CNN) is a kind of deep neural network that can automatically learn effective feature representation from training data and has been successfully applied in many fields. Meanwhile, most studies have not considered the impact of adjacent segments on SA detection. Therefore, in this study, we propose a modified LeNet-5 convolutional neural network with adjacent segments for SA detection. Our experimental results show that our proposed method is useful for SA detection, and achieves better or comparable results when compared with traditional machine learning methods.
Wang et al. (2019) Sleep apnea detection from a single-lead ECG signal with automatic feature-extraction through a modified LeNet-5 convolutional neural network. PeerJ 7:e7731 https://doi.org/10.7717/peerj.7731
Genetic variability evaluation and cultivar identification of tetraploid annual ryegrass using SSR markers
Annual ryegrass (Lolium multiflorum) is a widely used cool-season turf and forage grass with high productivity and ornamental characteristics. However, the abundant intra-cultivar genetic variability usually hampers the application of conventional techniques for cultivar identification. The objectives of this study were to: (1) describe an efficient strategy for identification of six tetraploid annual ryegrass cultivars and (2) investigate the genetic diversity based on SSR markers. A total of 242 reliable bands were obtained from 29 SSR primer pairs with an average of 8.3 bands for each primer pair and the average value of polymorphic information content (PIC) was 0.304. The result of analysis of molecular variance (AMOVA) revealed that 81.99% of the genetic variation occurred in within-cultivars and 18.01% among-cultivars. The principal coordinate analysis (PCoA) showed that the first two principal axes explain 8.57% (PC1) and 6.05% (PC2) of total variation, respectively. By using multi-bulk strategy based on different filtering thresholds, the results suggested that bands frequency of 40% could be used as a reliable standard for cultivar identification in annual ryegrass. Under this threshold, 12 SSR primer pairs (00-04A, 02-06G, 02-08C, 03-05A, 04-05B, 10-09E, 12-01A, 13-02H, 13-12D, 14-06F, 15-01C and 17-10D) were detected for direct identification of six tetraploid annual ryegrass cultivars, which could be incorporated into conservation schemes to protect the intellectual property of breeders, ensure purity for consumers, as well as guarantee effective use of cultivars in future.
Nie et al. (2019) Genetic variability evaluation and cultivar identification of tetraploid annual ryegrass using SSR markers. PeerJ 7:e7742 https://doi.org/10.7717/peerj.7742
Curcumin plays a synergistic role in combination with HSV-TK/GCV in inhibiting growth of murine B16 melanoma cells and melanoma xenografts
Melanoma is a global concern and accounts for the major mortality of skin cancers. Herpes simplex virus thymidine kinase gene with ganciclovir (HSV-TK/GCV) is a promising gene therapy for melanoma. Despite its low efficiency, it is well known for its bystander effect which is mainly mediated by gap junction. In this study, we found that curcumin reduced B16 melanoma cell viability in both time- and dose-dependent manner. Further study showed that curcumin improved the gap junction intercellular communication (GJIC) function, and upregulated the proteins essential to gap junction, such as connexin 32 and connexin 43, indicating the potential role in enhancing the bystander effect of HSV-TK/GCV. By co-culturing the B16TK cells, which stably expressed TK gene, with wildtype B16 (B16WT) cells, we found that co-treatment of curcumin and GCV synergistically inhibited B16 cell proliferation, but the effect could be eliminated by the gap junction inhibitor AGA. Moreover, curcumin markedly increased apoptosis rate of B16WT cells, suggesting its effect in enhancing the bystander effect of HSV-TK/GCV. In the in-vivo study, we established the xenografted melanoma model in 14 days by injecting mixture of B16TK and B16WT cell in a ratio of 3:7. The result demonstrated that, co-administration of curcumin and GCV significantly inhibited the xenograft growth, as indicated by the smaller size and less weight. The combinational effect was further confirmed as a synergistic effect. In conclusion, the results demonstrated that curcumin could enhance the killing effect and the bystander effect of HSV-TK/GCV in treating melanoma, which might be mediated by improved gap junction. Our data suggested that combination of HSV-TK/GCV with curcumin could be a potential chemosensitization strategy for cancer treatment.
Li et al. (2019) Curcumin plays a synergistic role in combination with HSV-TK/GCV in inhibiting growth of murine B16 melanoma cells and melanoma xenografts. PeerJ 7:e7760 https://doi.org/10.7717/peerj.7760
Identification of pivotal lncRNAs in papillary thyroid cancer using lncRNA–mRNA–miRNA ceRNA network analysis
Background To identify pivotal lncRNAs in papillary thyroid cancer (PTC) using lncRNA–mRNA–miRNA ceRNA network analysis. Methods We obtained gene expression profiles from the gene expression omnibus database. Cancer specific lncRNA, cancer specific miRNA and cancer specific mRNA were identified. An integrated analysis was conducted to detect potential lncRNA–miRNA–mRNA ceRNA in regulating disease transformation. The lncRNA regulated gene ontology (GO) terms and regulated pathways were performed by function analysis. Survival analysis was performed for the pivotal lncRNAs. Results A total of four lncRNAs, 15 miRNAs and 375 mRNAs are identified as the key mediators in the pathophysiological processes of PTC. GO annotation enrichment analysis showed the most relevant GO terms are signal transduction, integral component of membrane and calcium ion binding. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis showed different changed genes mainly enriched in pathways in cancer, PI3K-Akt signaling pathway and focal adhesion. Among four lncRNAs, only SLC26A4-AS1 was significantly associated with PTC patient disease free survival. Conclusion This study has constructed lncRNA–mRNA–miRNA ceRNA networks in PTC. The study provides a set of pivotal lncRNAs for future investigation into the molecular mechanisms.
Liang et al. (2019) Identification of pivotal lncRNAs in papillary thyroid cancer using lncRNA–mRNA–miRNA ceRNA network analysis. PeerJ 7:e7441 https://doi.org/10.7717/peerj.7441
Ankle and midtarsal joint quasi-stiffness during walking with added mass
Examination of how the ankle and midtarsal joints modulate stiffness in response to increased force demand will aid understanding of overall limb function and inform the development of bio-inspired assistive and robotic devices. The purpose of this study is to identify how ankle and midtarsal joint quasi-stiffness are affected by added body mass during over-ground walking. Healthy participants walked barefoot over-ground at 1.25 m/s wearing a weighted vest with 0%, 15% and 30% additional body mass. The effect of added mass was investigated on ankle and midtarsal joint range of motion (ROM), peak moment and quasi-stiffness. Joint quasi-stiffness was broken into two phases, dorsiflexion (DF) and plantarflexion (PF), representing approximately linear regions of their moment-angle curve. Added mass significantly increased ankle joint quasi-stiffness in DF (p < 0.001) and PF (p < 0.001), as well as midtarsal joint quasi-stiffness in DF (p < 0.006) and PF (p < 0.001). Notably, the midtarsal joint quasi-stiffness during DF was ~2.5 times higher than that of the ankle joint. The increase in midtarsal quasi-stiffness when walking with added mass could not be explained by the windlass mechanism, as the ROM of the metatarsophalangeal joints was not correlated with midtarsal joint quasi-stiffness (r = −0.142, p = 0.540). The likely source for the quasi-stiffness modulation may be from active foot muscles, however, future research is needed to confirm which anatomical structures (passive or active) contribute to the overall joint quasi-stiffness across locomotor tasks.
Kern et al. (2019) Ankle and midtarsal joint quasi-stiffness during walking with added mass. PeerJ 7:e7487 https://doi.org/10.7717/peerj.7487
Negative emotional state slows down movement speed: behavioral and neural evidence
Background Athletic performance is affected by emotional state. Athletes may underperform in competition due to poor emotion regulation. Movement speed plays an important role in many competition events. Flexible control of movement speed is critical for effective athletic performance. Although behavioral evidence showed that negative emotion can influence movement speed, the nature of the relationship remains controversial. Thus, the present study investigated how negative emotion affects movement speed and the neural mechanism underlying the interaction between emotion processing and movement control. Methods The present study combined electroencephalography (EEG) technology with a cued-action task to investigate the effect of negative emotion on movement speed. In total, 21 undergraduate students were recruited for this study. Participants were asked to perform six consecutive action tasks after viewing an emotional picture. Pictures were presented in two blocks (one negative and one neutral). After the participants completed a set of tasks (neutral of negative), they were subjected to complete a 9-point self-assessment manikin scale. Participants underwent EEG while performing the tasks. Results At the behavior level, there was a significant main effect of emotional valence on movement speed, with participants exhibiting significantly slower movements in the negative emotional condition than in the neutral condition. EEG data showed increased theta oscillation and larger P1 amplitude in response to negative than to neural images suggesting that more cognitive resources were required to process negative than neutral images. EEG data also showed a larger late CNV area in the neutral condition than in the negative condition, which suggested that there was a significant decrease in brain activation during action tasks in negative emotional condition than in the neural. While the early CNV did not reveal a significant main effect of emotional valence. Conclusion The present results indicate that a negative emotion can slow movement, which is largely due to negative emotional processing consuming more resources than non-emotional processing and this interference effect mainly occurred in the late movement preparation phase.
Li et al. (2019) Negative emotional state slows down movement speed: behavioral and neural evidence. PeerJ 7:e7591 https://doi.org/10.7717/peerj.7591