Integrated analysis of lncRNA and mRNA reveals novel insights into cashmere fineness in Tibetan cashmere goats
Tibetan cashmere goats are famous for producing the finest, softest and lightest cashmere fiber in China. The growth and development of skin are closely related to fineness and are the key factors affecting the quality of cashmere. To investigate the specific role of long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) in regulating cashmere fineness of Tibetan Cashmere goats in the anagen phase, we conducted high-throughput RNA sequencing of fine-type and coarse-type skin tissues. We identified 2,059 lncRNA candidates (1,589 lncRNAs annotated, 470 lncRNAs novel), and 80 differentially expressed (DE) lncRNAs and their potential targets were predicted. We also identified 384 DE messenger RNAs (mRNAs) out of 29,119 mRNAs. Several key genes in KRT26, KRT28, KRT39, IFT88, JAK3, NOTCH2 and NOTCH3 and a series of lncRNAs, including ENSCHIT00000009853, MSTRG.16794.17, MSTRG.17532.2, were shown to be potentially important for regulating cashmere fineness. GO and KEGG enrichment analyses of DE mRNAs and DE lncRNAs targets significantly enriched in positive regulation of the canonical Wnt signaling pathway, regulation of protein processing and metabolism processes. The mRNA-mRNA and lncRNA-mRNA regulatory networks further revealed potential transcripts involved in cashmere fineness. We further validated the expression patterns of DE mRNAs and DE lncRNAs by quantitative real-time PCR (qRT-PCR), and the results were consistent with the sequencing data. This study will shed new light on selective cashmere goat breeding, and these lncRNAs and mRNAs that were found to be enriched in Capra hircus RNA database.
Fu et al. (2020) Integrated analysis of lncRNA and mRNA reveals novel insights into cashmere fineness in Tibetan cashmere goats. PeerJ 8:e10217 https://doi.org/10.7717/peerj.10217
Loading history changes the morphology and compressive force-induced expression of receptor activator of nuclear factor kappa B ligand/osteoprotegerin in MLO-Y4 osteocytes
Background In this study, we investigated the effect of the mechanical loading history on the expression of receptor activator of nuclear factor kappa B ligand (RANKL) and osteoprotegerin (OPG) in MLO-Y4 osteocyte-like cells. Methods Three hours after MLO-Y4 osteocytes were seeded, a continuous compressive force (CCF) of 31 dynes/cm2 with or without additional CCF (32 dynes/cm2) was loaded onto the osteocytes. After 36 h, the additional CCF (loading history) was removed for a recovery period of 10 h. The expression of RANKL, OPG, RANKL/OPG ratio, cell numbers, viability and morphology were time-dependently examined at 0, 3, 6 and 10 h. Then, the same additional CCF was applied again for 1 h to all osteocytes with or without the gap junction inhibitor to examine the expression of RANKL, OPG, the RANKL/OPG ratio and other genes that essential to characterize the phenotype of MLO-Y4 cells. Fluorescence recovery after photobleaching technique was also applied to test the differences of gap-junctional intercellular communications (GJIC) among MLO-Y4 cells. Results The expression of RANKL and OPG by MLO-Y4 osteocytes without a loading history was dramatically decreased and increased, respectively, in response to the 1-h loading of additional weight. However, the expression of RANKL, OPG and the RANKL/OPG ratio were maintained at the same level as in the control group in the MLO-Y4 osteocytes with a loading history but without gap junction inhibitor treatment. Treatment of loading history significantly changed the capacity of GJIC and protein expression of connexin 43 (Cx43) but not the mRNA expression of Cx43. No significant difference was observed in the cell number or viability between the MLO-Y4 osteocyte-like cells with and without a loading history or among different time checkpoints during the recovery period. The cell morphology showed significant changes and was correlated with the expression of OPG, Gja1 and Dmp1 during the recovery period. Conclusion Our findings indicated that the compressive force-induced changes in the RANKL/OPG expression could be habituated within at least 11 h by 36-h CCF exposure. GJIC and cell morphology may play roles in response to loading history in MLO-Y4 osteocyte-like cells.
Wang et al. (2020) Loading history changes the morphology and compressive force-induced expression of receptor activator of nuclear factor kappa B ligand/osteoprotegerin in MLO-Y4 osteocytes. PeerJ 8:e10244 https://doi.org/10.7717/peerj.10244
MutRank: an R shiny web-application for exploratory targeted mutual rank-based coexpression analyses integrated with user-provided supporting information
The rapid assignment of genotypes to phenotypes has been a historically challenging process. The discovery of genes encoding biosynthetic pathway enzymes for defined plant specialized metabolites has been informed and accelerated by the detection of gene clusters. Unfortunately, biosynthetic pathway genes are commonly dispersed across chromosomes or reside in genes clusters that provide little predictive value. More reliably, transcript abundance of genes underlying biochemical pathways for plant specialized metabolites display significant coregulation. By rapidly identifying highly coexpressed transcripts, it is possible to efficiently narrow candidate genes encoding pathway enzymes and more easily predict both functions and functional associations. Mutual Rank (MR)-based coexpression analyses in plants accurately demonstrate functional associations for many specialized metabolic pathways; however, despite the clear predictive value of MR analyses, the application is uncommonly used to drive new pathway discoveries. Moreover, many coexpression databases aid in the prediction of both functional associations and gene functions, but lack customizability for refined hypothesis testing. To facilitate and speed flexible MR-based hypothesis testing, we developed MutRank, an R Shiny web-application for coexpression analyses. MutRank provides an intuitive graphical user interface with multiple customizable features that integrates user-provided data and supporting information suitable for personal computers. Tabular and graphical outputs facilitate the rapid analyses of both unbiased and user-defined coexpression results that accelerate gene function predictions. We highlight the recent utility of MR analyses for functional predictions and discoveries in defining two maize terpenoid antibiotic pathways. Beyond applications in biosynthetic pathway discovery, MutRank provides a simple, customizable and user-friendly interface to enable coexpression analyses relating to a breadth of plant biology inquiries. Data and code are available at GitHub: https://github.com/eporetsky/MutRank.
Poretsky et al. (2020) MutRank: an R shiny web-application for exploratory targeted mutual rank-based coexpression analyses integrated with user-provided supporting information. PeerJ 8:e10264 https://doi.org/10.7717/peerj.10264
Effects of substrate and water depth of a eutrophic pond on the physiological status of a submerged plant, Vallisneria natans
Effects of substrate and water depth on the physiological status of a submerged macrophyte, Vallisneria natans (Lour.) H. Hara, were determined by measuring biomarkers in leaves and roots, to understand factors limiting the re-establishment of V. natans in urban eutrophic ponds. Ramets of V. natans were grown in the laboratory using aquaria containing water and bottom mud from a eutrophic pond and maintained under sufficient light in an incubator. The growth and chlorophyll-a (Chl-a) content of leaves were greater in aquaria with mud than in those with sand, which was used as the reference substrate. The contents of a peroxidation product (malondialdehyde (MDA)) and three antioxidant enzymes (superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD)) in leaves and roots, used as stress biomarkers, changed during the experiment, although differences in these contents between mud and sand were not consistent across the experimental days. To control water depth in the field, ramets of V. natans were grown in cages with different substrates (mud and sand) installed at different depths (0.5, 1.2, and 2.0 m) in the pond. The mean light quantum during the experiment decreased with increasing depth, from 79.3 μmol/m2 s at 0.5 m to 7.9 μmol/m2 s at 2.0 m. The Chl-a content in leaves decreased, whereas the MDA content in both leaves and roots increased with increasing water depth. All enzyme activities increased at the beginning and then decreased to the end of the experiment at 2.0 m depth, suggesting deterioration of enzyme activities due to depth-related stress. The MDA content and CAT activity were higher for sand than for mud, whereas the difference in the growth and the leaf Chl-a content between substrates remained unclear in the pond. On comparing the laboratory and field experiments, the leaf Chl-a content was found to be lower and the MDA content and enzyme activities exhibited sharp increase for ramets grown in the pond, even at 0.5 m depth, when compared with those grown in the aquaria. Our results suggest that the bottom mud of the pond is not the major limiting factor in the re-establishment of V. natans. Because water depth and light attenuation exerted strong stress on V. natans, shallow areas or measures to improve water transparency are required to promote the introduction of V. natans in eutrophic ponds for successful restoration in urban areas.
Environmental Contamination and Remediation
Hao et al. (2020) Effects of substrate and water depth of a eutrophic pond on the physiological status of a submerged plant, Vallisneria natans. PeerJ 8:e10273 https://doi.org/10.7717/peerj.10273
The genetic diversity and population structure of two endemic Amazonian quillwort (Isoetes L.) species
Background Two endemic lycophyte species Isoetes cangae and Isoetes serracarajensis have been recently described in the State of Pará in the Amazon forest located in northern Brazil. Isoetes L. has survived through three mass extinctions. Plants are considered small-sized, heterosporous, and can display a great diversity of physiological adaptations to different environments. Thus, the current study aimed to estimate the genetic variation of the populations of I. cangae and I. serracarajensis to generate information about their different mechanisms for survival at the same geographical location that could point to different reproductive, adaptative and dispersal strategies and should be considered for effective conservation strategies. Methods The genetic diversity and population structure of I. cangae and I. serracarajensis were investigated using Inter Simple Sequence Repeat (ISSR) molecular markers. Total genomic DNA was isolated, and the genetic diversity parameters were calculated. Results The sixteen primers produced 115 reproducible bands, 87% of which were polymorphic. A high level of polymorphic loci (81.74% and 68.48%) and a high Shannon index (Sh = 0.376 and 0.289) were observed for I. cangae and I. serracarajensis, respectively. The coefficient of genetic differentiation between population areas (GST) showed a higher value in I. serracarajensis (0.5440). Gene flow was higher in I. cangae (1.715) and lower in I. serracarajensis populations (0.419). Overall, the results further show that I. serracarajensis and I. cangae are two species with considerable genetic variation and that these differences may reflect their habitats and modes of reproduction. These results should be considered in the development of effective conservation strategies for both species.
Santos et al. (2020) The genetic diversity and population structure of two endemic Amazonian quillwort (Isoetes L.) species. PeerJ 8:e10274 https://doi.org/10.7717/peerj.10274
Foraging efficiency, social status and body condition in group-living horses and ponies
Individual animals experience different costs and benefits associated with group living, which may impact on their foraging efficiency in ways not yet well specified. This study investigated associations between social dominance, body condition and interruptions to foraging behaviour in a cross-sectional study of 116 domestic horses and ponies, kept in 20 discrete herds. Social dominance was measured for each individual alongside observations of winter foraging behaviour. During bouts of foraging, the duration, frequency and category (vigilance, movement, social displacements given and received, scratching and startle responses) of interruptions were recorded, with total interruption time taken as a proxy measure of foraging efficiency. Total foraging time was not influenced by body condition or social dominance. Body condition was associated with social dominance, but more strongly associated with foraging efficiency. Specifically, lower body condition was associated with greater vigilance. This demonstrates that factors other than social dominance can result in stable differences in winter body condition.
Giles et al. (2020) Foraging efficiency, social status and body condition in group-living horses and ponies. PeerJ 8:e10305 https://doi.org/10.7717/peerj.10305
COVID-19 infection: Disease detection and mobile technology
Background A pneumonia outbreak of unknown etiology took place in Wuhan, Hubei province, China and spread quickly worldwide in December 2019. Chinese Center for Disease Control and Prevention identified a novel beta-coronavirus called 2019-nCoV, now officially known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) that is responsible for the pandemic. The coronavirus COVID-19 affected 215 countries and territories around the world and more than 99 hundred thousand people at present (Nature Nanotechnology, 2020). At present, there are no specific vaccines or treatments available for COVID-19. However, there are many ongoing clinical trials evaluating potential treatments. At this time the experts recommend precautions such as social distancing, hand washing, and wearing face masks to reduce disease transmission. This review article aims to improve the readers’ awareness towards the important role of mobile technology for SARS-CoV-2. Methodology To achieve this objective, we performed a COVID-19 literature review from various sources that include data from the published articles as well as World Health Organization reports on coronavirus disease and how mobile technology is useful to fight against this disease. Results Mobile technology can be helpful in mapping disease spread and provides an easy way to provide awareness that promotes safety and adoption of necessary precautions to mitigate and stop community transmission. Conclusion The spread rate of COVID-19 is very high and until now no vaccines are available to control this disease. To this end we should leverage other avenues such as digital technologies to protect ourselves from this disease. Mobile technology such as smartphones are playing an important role in this pandemic, by launching apps to track coronavirus infected people. These apps are very easy to use and provide self-isolation guidelines as well as other safety tips.
Verma et al. (2020) COVID-19 infection: Disease detection and mobile technology. PeerJ 8:e10345 https://doi.org/10.7717/peerj.10345
De novo transcriptome analysis of Cnidium monnieri (L.) Cuss and detection of genes related to coumarin biosynthesis
Cnidium monnieri (L.) Cuss (C. monnieri) is one of the most widely used traditional herbal medicines, exhibiting a wide range of pharmacological functions for treating asynodia, trichomonas vaginitis, and osphyalgia. Its important medicinal value comes from its abundance of coumarins. To identify genes involved in coumarin biosynthesis and accumulation, we analyzed transcriptome data from flower, leaf, root and stem tissues of C. monnieri. A total of 173,938 unigenes with a mean length of 1,272 bp, GC content of 38.79%, and N50 length of 2,121 bp were assembled using the Trinity program. Of these, 119,177 unigenes were annotated in public databases. We identified differentially expressed genes (DEGs) based on expression profile analysis. These DEGs exhibited higher expression levels in flower tissue than in leaf, stem or root tissues. We identified and analyzed numerous genes encoding enzymes involved in coumarin biosynthesis, and verified genes encoding key enzymes using quantitative real-time PCR. Our transcriptome data will make great contributions to research on C. monnieri and provide clues for identifying candidate genes involved in coumarin metabolic pathways.
Shi et al. (2020) De novo transcriptome analysis of Cnidium monnieri (L.) Cuss and detection of genes related to coumarin biosynthesis. PeerJ 8:e10157 https://doi.org/10.7717/peerj.10157
Dependence structure analysis of multisite river inflow data using vine copula-CEEMDAN based hybrid model
Several data-driven and hybrid models are univariate and not considered the dependance structure of multivariate random variables, especially the multi-site river inflow data, which requires the joint distribution of the same river basin system. In this paper, we proposed a Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) Vine copula-based approach to address this issue. The proposed hybrid model comprised on two stages: In the first stage, the CEEMDAN is used to extract the high dimensional multi-scale features. Further, the multiple models are used to predict multi-scale components and residuals. In the second stage, the residuals obtained from the first stage are used to model the joint uncertainty of multi-site river inflow data by using Canonical Vine. For the application of the proposed two-step architecture, daily river inflow data of the Indus River Basin is used. The proposed two-stage methodology is compared with only the first stage proposed model, Vector Autoregressive and copula-based Autoregressive Integrated Moving Average models. The four evaluation measures, that is, Mean Absolute Relative Error (MARE), Mean Absolute Deviation (MAD), Nash-Sutcliffe Efficiency (NSE) and Mean Square Error (MSE), are used to observe the prediction performance. The results demonstrated that the proposed model outperforms significantly with minimum MARE, MAD, NSE, and MSE for two case studies having significant joint dependance. Therefore, it is concluded that the prediction can be improved by appropriately modeling the dependance structure of the multi-site river inflow data.
Spatial and Geographic Information Science
Nazir et al. (2020) Dependence structure analysis of multisite river inflow data using vine copula-CEEMDAN based hybrid model. PeerJ 8:e10285 https://doi.org/10.7717/peerj.10285
No conclusive evidence that difficult general knowledge questions cause a “Google Stroop effect”. A replication study
Access to the digital “all-knowing cloud” has become an integral part of our daily lives. It has been suggested that the increasing offloading of information and information processing services to the cloud will alter human cognition and metacognition in the short and long term. A much-cited study published in Science in 2011 provided first behavioral evidence for such changes in human cognition. Participants had to answer difficult trivia questions, and subsequently showed longer response times in a variant of the Stroop task with internet-related words (“Google Stroop effect”). The authors of this study concluded that the concept of the Internet is automatically activated in situations where information is missing (e.g., because we might feel the urge to “google” the information). However, the “Google Stroop effect” could not be replicated in two recent replication attempts as part of a large replicability project. After the failed replication was published in 2018, the first author of the original study pointed out some problems with the design of the failed replication. In our study, we therefore aimed to replicate the “Google Stroop effect” with a research design closer to the original experiment. Our results revealed no conclusive evidence in favor of the notion that the concept of the Internet or internet access (via computers or smartphones) is automatically activated when participants are faced with hard trivia questions. We provide recommendations for follow-up research.
Hesselmann (2020) No conclusive evidence that difficult general knowledge questions cause a “Google Stroop effect”. A replication study. PeerJ 8:e10325 https://doi.org/10.7717/peerj.10325