title: PeerJ description: Articles published in PeerJ link: https://peerj.com/articles/index.rss3?journal=peerj&page=1392 creator: info@peerj.com PeerJ errorsTo: info@peerj.com PeerJ language: en title: Respiratory syncytial virus, human metapneumovirus, and influenza virus infection in Bangkok, 2016-2017 link: https://peerj.com/articles/6748 last-modified: 2019-04-11 description: Children and adults residing in densely populated urban centers around the world are at risk of seasonal influenza-like illness caused by respiratory viruses such as influenza virus, human metapneumovirus (hMPV), and respiratory syncytial virus (RSV). In a large metropolitan of Thailand’s capital city Bangkok, most respiratory infections are rarely confirmed by molecular diagnostics. We therefore examined the frequency of RSV, hMPV, and influenza virus in 8,842 patients who presented influenza-like illness and sought medical care at a large hospital in Bangkok between 2016 and 2017. Using a multiplex real-time reverse-transcription polymerase chain reaction (RT-PCR), 30.5% (2,699/8,842) of nasopharyngeal (NP) swab samples tested positive for one or more of these viruses. Influenza virus comprised 17.3% (1,528/8,842), of which the majority were influenza A/H3N2. Such infection was most prevalent among adults and the elderly. RSV was identified in 11.4% (1,011/8,842) and were mostly ON1 and BA9 genotypes. Of the hMPV-positive samples (3.6%, 318/8,842), genotypes A2, B1, and B2 were detected. A small number of individuals experienced co-infections (1.8%, 155/8,842), most commonly between RSV and influenza A/H3N2. RSV and hMPV co-infections were also found, but mainly in young children. Viral respiratory tract infection peaked locally in the rainy season (June to September). These findings support the utility of rapid nucleic acid testing of RSV, hMPV, and influenza virus in patients with ILI. creator: Ilada Thongpan creator: Nungruthai Suntronwong creator: Preeyaporn Vichaiwattana creator: Nasamon Wanlapakorn creator: Sompong Vongpunsawad creator: Yong Poovorawan uri: https://doi.org/10.7717/peerj.6748 license: http://creativecommons.org/licenses/by/4.0/ rights: ©2019 Thongpan et al. title: Genome-wide analysis of maize OSCA family members and their involvement in drought stress link: https://peerj.com/articles/6765 last-modified: 2019-04-11 description: BackgroundWorldwide cultivation of maize is often impacted negatively by drought stress. Hyperosmolality-gated calcium-permeable channels (OSCA) have been characterized as osmosensors in Arabidopsis. However, the involvement of members of the maize OSCA (ZmOSCA) gene family in response to drought stress is unknown. It is furthermore unclear which ZmOSCA gene plays a major role in genetic improvement of drought tolerance in Maize.MethodsWe predicted the protein domain structure and transmembrane regions by using the NCBI Conserved Domain Database database and TMHMM server separately. The phylogeny tree was built by Mega7. We used the mixed linear model in TASSEL to perform the family-based association analysis.ResultsIn this report, 12 ZmOSCA genes were uncovered in the maize genome by a genome-wide survey and analyzed systematically to reveal their synteny and phylogenetic relationship with the genomes of rice, maize, and sorghum. These analyses indicated a relatively conserved evolutionary history of the ZmOSCA gene family. Protein domain and transmembrane analysis indicated that most of the 12 ZmOSCAs shared similar structures with their homologs. The result of differential expression analysis under drought at various stages, as well as the expression profiles in 15 tissues, revealed a functional divergence of ZmOSCA genes. Notably, the expression level of ZmOSCA4.1 being up-regulated in both seedlings and adult leaves. Notably, the association analysis between genetic variations in these genes and drought tolerance was detected. Significant associations between genetic variation in ZmOSCA4.1 and drought tolerance were found at the seedling stage. Our report provides a detailed analysis of the ZmOSCAs in the maize genome. These findings will contribute to future studies on the functional characterization of ZmOSCA proteins in response to water deficit stress, as well as understanding the mechanism of genetic variation in drought tolerance in maize. creator: Shuangcheng Ding creator: Xin Feng creator: Hewei Du creator: Hongwei Wang uri: https://doi.org/10.7717/peerj.6765 license: http://creativecommons.org/licenses/by/4.0/ rights: © 2019 Ding et al. title: Leaf anatomy and ultrastructure in senescing ancient tree, Platycladus orientalis L. (Cupressaceae) link: https://peerj.com/articles/6766 last-modified: 2019-04-11 description: Platycladus orientalis L. (Cupressaceae) has a lifespan of thousands of years. Ancient trees have very high scientific, economic and cultural values. The senescence of ancient trees is a new research area but is poorly understood. Leaves are the primary and the most sensitive organ of a tree. To understand leaf structural response to tree senescence in ancient trees, experiments investigating the morphology, anatomy and ultrastructure were conducted with one-year leaves of ancient P. orientalis (ancient tree >2,000 years) at three different tree senescent levels (healthy, sub-healthy and senescent) at the world’s largest planted pure forest in the Mausoleum of Yellow Emperor, Shaanxi Province, China. Observations showed that leaf structure significantly changed with the senescence of trees. The chloroplast, mitochondria, vacuole and cell wall of mesophyll cells were the most significant markers of cellular ultrastructure during tree senescence. Leaf ultrastructure clearly reflected the senescence degree of ancient trees, confirming the visual evaluation from above-ground parts of trees. Understanding the relationships between leaf structure and tree senescence can support decision makers in planning the protection of ancient trees more promptly and effectively by adopting the timely rejuvenation techniques before the whole tree irreversibly recesses. creator: Qianyi Zhou creator: Zhaohong Jiang creator: Xin Zhang creator: Tian Zhang creator: Hailan Zhu creator: Bei Cui creator: Yiming Li creator: Fei Zhao creator: Zhong Zhao uri: https://doi.org/10.7717/peerj.6766 license: http://creativecommons.org/licenses/by/4.0/ rights: © 2019 Zhou et al. title: Robust and accurate quantification of biomarkers of immune cells in lung cancer micro-environment using deep convolutional neural networks link: https://peerj.com/articles/6335 last-modified: 2019-04-10 description: Recent years have seen a growing awareness of the role the immune system plays in successful cancer treatment, especially in novel therapies like immunotherapy. The characterization of the immunological composition of tumors and their micro-environment is thus becoming a necessity. In this paper we introduce a deep learning-based immune cell detection and quantification method, which is based on supervised learning, i.e., the input data for training comprises labeled images. Our approach objectively deals with staining variation and staining artifacts in immunohistochemically stained lung cancer tissue and is as precise as humans. This is evidenced by the low cell count difference to humans of 0.033 cells on average. This method, which is based on convolutional neural networks, has the potential to provide a new quantitative basis for research on immunotherapy. creator: Lilija Aprupe creator: Geert Litjens creator: Titus J. Brinker creator: Jeroen van der Laak creator: Niels Grabe uri: https://doi.org/10.7717/peerj.6335 license: http://creativecommons.org/licenses/by/4.0/ rights: ©2019 Aprupe et al. title: Genetic data of museum specimens allow for inferring evolutionary history of the cosmopolitan genus Sirthenea (Heteroptera: Reduviidae) link: https://peerj.com/articles/6640 last-modified: 2019-04-10 description: Among the 30 known genera within subfamily Peiratinae, only the genus Sirthenea has a cosmopolitan distribution. The results of our studies are the first comprehensive analysis concerning one of the representatives of mentioned subfamily based on joint phylogenetic analyses of molecular and morphological data as well as molecular dating. A total of 32 species were included into the dataset with all known species of the genus Sirthenea. Material of over 400 dry specimens was examined for the morphological part of this study. The cosmopolitan distribution of Sirthenea and the inaccessibility of specimens preserved in alcohol required the extraction of DNA from the dried skeletal muscles of specimens deposited in 24 entomological collections. The oldest specimens used for the successful extraction and sequencing were collected more than 120 years ago in India. We performed Bayesian Inference analyses of molecular and morphological data separately, as well as combined analysis. The molecular and morphological data obtained during our research verify the correlation of the divergence dates of all known Sirthenea species. Results of the relaxed molecular clock analysis of the molecular data show that, the genus Sirthenea started diverging in the Late Cretaceous into two clades, which subsequently began to branch off in the Paleocene. Our results of phylogenetic analyses suggest that the fossula spongiosa and its development could be one of the most important morphological characters in the evolution of the genus, most likely associated with the ecological niche inhabited by Sirthenea representatives. Confirmation of the results obtained in our studies is the reconciliation of the evolutionary history of Sirthenea with the biogeographical processes that have shaped current global distribution of the genus. creator: Dominik Chłond creator: Natalia Sawka-Gądek creator: Dagmara Żyła uri: https://doi.org/10.7717/peerj.6640 license: http://creativecommons.org/licenses/by/4.0/ rights: © 2019 Chłond et al. title: Germination characteristics among different sheepgrass (Leymus chinensis) germplasm during the seed development and after-ripening stages link: https://peerj.com/articles/6688 last-modified: 2019-04-10 description: Sheepgrass (Leymus chinensis (Trin.) Tzvel) is an important forage grass in the Eurasian steppe. However, little information is available concerning its seed morphological features and germination characteristics during seed development and after-ripening among different germplasm. To clarify the appropriate seed harvest time and the effects of germplasm, seed development and after-ripening on seed germination, 20 germplasm of sheepgrass were selected. Moreover, the seed morphological and physical changes as well as the seed germination and dormancy characteristics of sheepgrass during seed development stages were analyzed using a seven—d gradient of day after pollination (DAP). The results indicated that the seed water content decreased significantly during 35–42 DAP and that the highest seed germination rate of most germplasm was observed at 35–42 DAP. Thus, 35–42 DAP may be the best time to harvest sheepgrass to obtain the maximum seed germination rate and avoid seed shattering. Furthermore, our results indicated that there were six types of germination patterns, including germplasm with increasing germination rates in the developing seed, such as S19 and S13, and germplasm that maintained a consistently low germination rate, such as S10. Moreover, we compared the seed germination rate of eight germplasm during seed development in both 2016 and 2017, and the results indicated that the seed germination patterns of the eight germplasm were highly consistent between the two consecutive years, suggesting that germplasm rather than year is the major factor in determining germination during seed development. The effect of after-ripening on seed germination was different among the germplasm where four types of germination patterns were revealed for 10 germplasm and resulted in various dormancy features. A two-factor ANOVA analysis suggested that the germplasm of the sheepgrass has a large influence on seed germination, whether during seed development or after-ripening. Thus, these findings lay the foundation for future studies on seed dormancy and germination and may guide the breeding of new cultivars of sheepgrass with better germination performance. creator: Weiguang Yang creator: Shu Liu creator: Guangxiao Yuan creator: Panpan Liu creator: Dongmei Qi creator: Xiaobing Dong creator: Hui Liu creator: Gongshe Liu creator: Xiaoxia Li uri: https://doi.org/10.7717/peerj.6688 license: http://creativecommons.org/licenses/by/4.0/ rights: © 2019 Yang et al. title: virMine: automated detection of viral sequences from complex metagenomic samples link: https://peerj.com/articles/6695 last-modified: 2019-04-10 description: Metagenomics has enabled sequencing of viral communities from a myriad of different environments. Viral metagenomic studies routinely uncover sequences with no recognizable homology to known coding regions or genomes. Nevertheless, complete viral genomes have been constructed directly from complex community metagenomes, often through tedious manual curation. To address this, we developed the software tool virMine to identify viral genomes from raw reads representative of viral or mixed (viral and bacterial) communities. virMine automates sequence read quality control, assembly, and annotation. Researchers can easily refine their search for a specific study system and/or feature(s) of interest. In contrast to other viral genome detection tools that often rely on the recognition of viral signature sequences, virMine is not restricted by the insufficient representation of viral diversity in public data repositories. Rather, viral genomes are identified through an iterative approach, first omitting non-viral sequences. Thus, both relatives of previously characterized viruses and novel species can be detected, including both eukaryotic viruses and bacteriophages. Here we present virMine and its analysis of synthetic communities as well as metagenomic data sets from three distinctly different environments: the gut microbiota, the urinary microbiota, and freshwater viromes. Several new viral genomes were identified and annotated, thus contributing to our understanding of viral genetic diversity in these three environments. creator: Andrea Garretto creator: Thomas Hatzopoulos creator: Catherine Putonti uri: https://doi.org/10.7717/peerj.6695 license: http://creativecommons.org/licenses/by/4.0/ rights: ©2019 Garretto et al. title: MetaMSD: meta analysis for mass spectrometry data link: https://peerj.com/articles/6699 last-modified: 2019-04-10 description: Mass spectrometry-based proteomics facilitate disease understanding by providing protein abundance information about disease progression. For the same type of disease studies, multiple mass spectrometry datasets may be generated. Integrating multiple mass spectrometry datasets can provide valuable information that a single dataset analysis cannot provide. In this article, we introduce a meta-analysis software, MetaMSD (Meta Analysis for Mass Spectrometry Data) that is specifically designed for mass spectrometry data. Using Stouffer’s or Pearson’s test, MetaMSD detects significantly more differential proteins than the analysis based on the single best experiment. We demonstrate the performance of MetaMSD using simulated data, urinary proteomic data of kidney transplant patients, and breast cancer proteomic data. Noting the common practice of performing a pilot study prior to a main study, this software will help proteomics researchers fully utilize the benefit of multiple studies (or datasets), thus optimizing biomarker discovery. MetaMSD is a command line tool that automatically outputs various graphs and differential proteins with confidence scores. It is implemented in R and is freely available for public use at https://github.com/soyoungryu/MetaMSD. The user manual and data are available at the site. The user manual is written in such a way that scientists who are not familiar with R software can use MetaMSD. creator: So Young Ryu creator: George A. Wendt uri: https://doi.org/10.7717/peerj.6699 license: http://creativecommons.org/licenses/by/4.0/ rights: ©2019 Ryu and Wendt title: Automated analysis of small RNA datasets with RAPID link: https://peerj.com/articles/6710 last-modified: 2019-04-10 description: Understanding the role of short-interfering RNA (siRNA) in diverse biological processes is of current interest and often approached through small RNA sequencing. However, analysis of these datasets is difficult due to the complexity of biological RNA processing pathways, which differ between species. Several properties like strand specificity, length distribution, and distribution of soft-clipped bases are few parameters known to guide researchers in understanding the role of siRNAs. We present RAPID, a generic eukaryotic siRNA analysis pipeline, which captures information inherent in the datasets and automatically produces numerous visualizations as user-friendly HTML reports, covering multiple categories required for siRNA analysis. RAPID also facilitates an automated comparison of multiple datasets, with one of the normalization techniques dedicated for siRNA knockdown analysis, and integrates differential expression analysis using DESeq2.Availability and ImplementationRAPID is available under MIT license at https://github.com/SchulzLab/RAPID. We recommend using it as a conda environment available from https://anaconda.org/bioconda/rapid creator: Sivarajan Karunanithi creator: Martin Simon creator: Marcel H. Schulz uri: https://doi.org/10.7717/peerj.6710 license: http://creativecommons.org/licenses/by/4.0/ rights: ©2019 Karunanithi et al. title: Decoupling species richness variation and spatial turnover in beta diversity across a fragmented landscape link: https://peerj.com/articles/6714 last-modified: 2019-04-10 description: BackgroundHow habitat fragmentation affects the relationship between local richness and the variation in community composition across space is important to both ecology and conservation biology, but this effect remains poorly understood.MethodsHere, we present an empirical study to address this topic in a fragmented landscape, the Thousand Island Lake (TIL), an artificial land-bridge island system with more than 1,000 islands, which provides an “experimental” fragmented landscape with a homogeneous matrix and similar successional history. We measured species composition and plant functional type (PFT) on 29 islands, and tested the effects of island area and isolation on the relationship between α- and β-diversity. General Linear Models were applied to test the impact of habitat fragmentation. In addition, variation partitioning was used to decouple α-diversity dependent and α-diversity independent spatial turnover in β-diversity of the plant community and across different PFTs.ResultsWe found habitat fragmentation influences β-diversity of plants primarily by modifying local α-diversity, not spatial turnover in the TIL system. We also found area-dependent environmental filtering and differential plant responses across functional types were the most likely underlying driving mechanisms.DiscussionThese results highlight the importance of hierarchical linkages between components of biodiversity across scales in fragmented landscapes, and have practical conservation implications. creator: Guang Hu creator: Maxwell C. Wilson creator: Jianguo Wu creator: Jingjing Yu creator: Mingjian Yu uri: https://doi.org/10.7717/peerj.6714 license: http://creativecommons.org/licenses/by/4.0/ rights: © 2019 Hu et al.