Journal articles: 'Meta-transcriptomics'

1

Caldas, José, and Susana Vinga. "Global Meta-Analysis of Transcriptomics Studies." PLoS ONE 9, no. 2 (February 26, 2014): e89318. http://dx.doi.org/10.1371/journal.pone.0089318.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Cobbin, Joanna CA, Justine Charon, Erin Harvey, Edward C. Holmes, and Jackie E. Mahar. "Current challenges to virus discovery by meta-transcriptomics." Current Opinion in Virology 51 (December 2021): 48–55. http://dx.doi.org/10.1016/j.coviro.2021.09.007.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Shi, Mang, Yong-Zhen Zhang, and Edward C. Holmes. "Meta-transcriptomics and the evolutionary biology of RNA viruses." Virus Research 243 (January 2018): 83–90. http://dx.doi.org/10.1016/j.virusres.2017.10.016.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Fung, Wing Tung, Joseph T. Wu, Wai Man Mandy Chan, Henry H. Chan, and Herbert Pang. "Pathway‐based meta‐analysis for partially paired transcriptomics analysis." Research Synthesis Methods 11, no. 1 (November 10, 2019): 123–33. http://dx.doi.org/10.1002/jrsm.1381.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Wittekindt, Nicola E., Abinash Padhi, Stephan C. Schuster, Ji Qi, Fangqing Zhao, Lynn P. Tomsho, Lindsay R. Kasson, Michael Packard, Paul Cross, and Mary Poss. "Nodeomics: Pathogen Detection in Vertebrate Lymph Nodes Using Meta-Transcriptomics." PLoS ONE 5, no. 10 (October 18, 2010): e13432. http://dx.doi.org/10.1371/journal.pone.0013432.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Gust, Kurt A., Fares Z. Najar, Tanwir Habib, Guilherme R. Lotufo, Alan M. Piggot, Bruce W. Fouke, Jennifer G. Laird, et al. "Coral-zooxanthellae meta-transcriptomics reveals integrated response to pollutant stress." BMC Genomics 15, no. 1 (2014): 591. http://dx.doi.org/10.1186/1471-2164-15-591.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Brown, Laurence A., and Stuart N. Peirson. "Improving Reproducibility and Candidate Selection in Transcriptomics Using Meta-analysis." Journal of Experimental Neuroscience 12 (January 2018): 117906951875629. http://dx.doi.org/10.1177/1179069518756296.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Chialva, Matteo, Stefano Ghignone, Mara Novero, Wael N. Hozzein, Luisa Lanfranco, and Paola Bonfante. "Tomato RNA-seq Data Mining Reveals the Taxonomic and Functional Diversity of Root-Associated Microbiota." Microorganisms 8, no. 1 (December 24, 2019): 38. http://dx.doi.org/10.3390/microorganisms8010038.

Full text

Abstract:

Next-generation approaches have enabled researchers to deeply study the plant microbiota and to reveal how microbiota associated with plant roots has key effects on plant nutrition, disease resistance, and plant development. Although early “omics” experiments focused mainly on the species composition of microbial communities, new “meta-omics” approaches such as meta-transcriptomics provide hints about the functions of the microbes when interacting with their plant host. Here, we used an RNA-seq dataset previously generated for tomato (Solanum lycopersicum) plants growing on different native soils to test the hypothesis that host-targeted transcriptomics can detect the taxonomic and functional diversity of root microbiota. Even though the sequencing throughput for the microbial populations was limited, we were able to reconstruct the microbial communities and obtain an overview of their functional diversity. Comparisons of the host transcriptome and the meta-transcriptome suggested that the composition and the metabolic activities of the microbiota shape plant responses at the molecular level. Despite the limitations, mining available next-generation sequencing datasets can provide unexpected results and potential benefits for microbiota research.

APA, Harvard, Vancouver, ISO, and other styles

9

Delhomme, Nicolas, Görel Sundström, Neda Zamani, Henrik Lantz, Yao-Cheng Lin, Torgeir R. Hvidsten, Marc P. Höppner, et al. "Serendipitous Meta-Transcriptomics: The Fungal Community of Norway Spruce (Picea abies)." PLOS ONE 10, no. 9 (September 28, 2015): e0139080. http://dx.doi.org/10.1371/journal.pone.0139080.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Porter, Ashleigh F., Mang Shi, John-Sebastian Eden, Yong-Zhen Zhang, and Edward C. Holmes. "Diversity and Evolution of Novel Invertebrate DNA Viruses Revealed by Meta-Transcriptomics." Viruses 11, no. 12 (November 25, 2019): 1092. http://dx.doi.org/10.3390/v11121092.

Full text

Abstract:

DNA viruses comprise a wide array of genome structures and infect diverse host species. To date, most studies of DNA viruses have focused on those with the strongest disease associations. Accordingly, there has been a marked lack of sampling of DNA viruses from invertebrates. Bulk RNA sequencing has resulted in the discovery of a myriad of novel RNA viruses, and herein we used this methodology to identify actively transcribing DNA viruses in meta-transcriptomic libraries of diverse invertebrate species. Our analysis revealed high levels of phylogenetic diversity in DNA viruses, including 13 species from the Parvoviridae, Circoviridae, and Genomoviridae families of single-stranded DNA virus families, and six double-stranded DNA virus species from the Nudiviridae, Polyomaviridae, and Herpesviridae, for which few invertebrate viruses have been identified to date. By incorporating the sequence of a “blank” experimental control we also highlight the importance of reagent contamination in metagenomic studies. In sum, this work expands our knowledge of the diversity and evolution of DNA viruses and illustrates the utility of meta-transcriptomic data in identifying organisms with DNA genomes.

APA, Harvard, Vancouver, ISO, and other styles

11

Wang, Hong-Qiang, Chun-Hou Zheng, and Xing-Ming Zhao. "jNMFMA: a joint non-negative matrix factorization meta-analysis of transcriptomics data." Bioinformatics 31, no. 4 (October 16, 2014): 572–80. http://dx.doi.org/10.1093/bioinformatics/btu679.

Full text

APA, Harvard, Vancouver, ISO, and other styles

12

Voutetakis, Konstantinos, Aristotelis Chatziioannou, Efstathios S. Gonos, and Ioannis P. Trougakos. "Comparative Meta-Analysis of Transcriptomics Data during Cellular Senescence andIn VivoTissue Ageing." Oxidative Medicine and Cellular Longevity 2015 (2015): 1–17. http://dx.doi.org/10.1155/2015/732914.

Full text

Abstract:

Several studies have employed DNA microarrays to identify gene expression signatures that mark human ageing; yet the features underlying this complicated phenomenon remain elusive. We thus conducted a bioinformatics meta-analysis on transcriptomics data from human cell- and biopsy-based microarrays experiments studying cellular senescence orin vivotissue ageing, respectively. We report that coregulated genes in the postmitotic muscle and nervous tissues are classified into pathways involved in cancer, focal adhesion, actin cytoskeleton, MAPK signalling, and metabolism regulation. Genes that are differentially regulated during cellular senescence refer to pathways involved in neurodegeneration, focal adhesion, actin cytoskeleton, proteasome, cell cycle, DNA replication, and oxidative phosphorylation. Finally, we revealed genes and pathways (referring to cancer, Huntington’s disease, MAPK signalling, focal adhesion, actin cytoskeleton, oxidative phosphorylation, and metabolic signalling) that are coregulated during cellular senescence andin vivotissue ageing. The molecular commonalities between cellular senescence and tissue ageing are also highlighted by the fact that pathways that were overrepresented exclusively in the biopsy- or cell-based datasets are modules either of the same reference pathway (e.g., metabolism) or of closely interrelated pathways (e.g., thyroid cancer and melanoma). Our reported meta-analysis has revealed novel age-related genes, setting thus the basis for more detailed future functional studies.

APA, Harvard, Vancouver, ISO, and other styles

13

Dovrou, Aikaterini, Ekaterini Bei, Stelios Sfakianakis, Kostas Marias, Nickolas Papanikolaou, and Michalis Zervakis. "Synergies of Radiomics and Transcriptomics in Lung Cancer Diagnosis: A Pilot Study." Diagnostics 13, no. 4 (February 15, 2023): 738. http://dx.doi.org/10.3390/diagnostics13040738.

Full text

Abstract:

Radiotranscriptomics is an emerging field that aims to investigate the relationships between the radiomic features extracted from medical images and gene expression profiles that contribute in the diagnosis, treatment planning, and prognosis of cancer. This study proposes a methodological framework for the investigation of these associations with application on non-small-cell lung cancer (NSCLC). Six publicly available NSCLC datasets with transcriptomics data were used to derive and validate a transcriptomic signature for its ability to differentiate between cancer and non-malignant lung tissue. A publicly available dataset of 24 NSCLC-diagnosed patients, with both transcriptomic and imaging data, was used for the joint radiotranscriptomic analysis. For each patient, 749 Computed Tomography (CT) radiomic features were extracted and the corresponding transcriptomics data were provided through DNA microarrays. The radiomic features were clustered using the iterative K-means algorithm resulting in 77 homogeneous clusters, represented by meta-radiomic features. The most significant differentially expressed genes (DEGs) were selected by performing Significance Analysis of Microarrays (SAM) and 2-fold change. The interactions among the CT imaging features and the selected DEGs were investigated using SAM and a Spearman rank correlation test with a False Discovery Rate (FDR) of 5%, leading to the extraction of 73 DEGs significantly correlated with radiomic features. These genes were used to produce predictive models of the meta-radiomics features, defined as p-metaomics features, by performing Lasso regression. Of the 77 meta-radiomic features, 51 can be modeled in terms of the transcriptomic signature. These significant radiotranscriptomics relationships form a reliable basis to biologically justify the radiomics features extracted from anatomic imaging modalities. Thus, the biological value of these radiomic features was justified via enrichment analysis on their transcriptomics-based regression models, revealing closely associated biological processes and pathways. Overall, the proposed methodological framework provides joint radiotranscriptomics markers and models to support the connection and complementarities between the transcriptome and the phenotype in cancer, as demonstrated in the case of NSCLC.

APA, Harvard, Vancouver, ISO, and other styles

14

Villatoro-García, Juan Antonio, Jordi Martorell-Marugán, Daniel Toro-Domínguez, Yolanda Román-Montoya, Pedro Femia, and Pedro Carmona-Sáez. "DExMA: An R Package for Performing Gene Expression Meta-Analysis with Missing Genes." Mathematics 10, no. 18 (September 17, 2022): 3376. http://dx.doi.org/10.3390/math10183376.

Full text

Abstract:

Meta-analysis techniques allow researchers to jointly analyse different studies to determine common effects. In the field of transcriptomics, these methods have gained popularity in recent years due to the increasing number of datasets that are available in public repositories. Despite this, there is a limited number of statistical software packages that implement proper meta-analysis functionalities for this type of data. This article describes DExMA, an R package that provides a set of functions for performing gene expression meta-analyses, from data downloading to results visualization. Additionally, we implemented functions to control the number of missing genes, which can be a major issue when comparing studies generated with different analytical platforms. DExMA is freely available in the Bioconductor repository.

APA, Harvard, Vancouver, ISO, and other styles

15

Soul, Jamie, Tim E. Hardingham, Ray P. Boot-Handford, and Jean-Marc Schwartz. "SkeletalVis: an exploration and meta-analysis data portal of cross-species skeletal transcriptomics data." Bioinformatics 35, no. 13 (November 27, 2018): 2283–90. http://dx.doi.org/10.1093/bioinformatics/bty947.

Full text

Abstract:

Abstract Motivation Skeletal diseases are prevalent in society, but improved molecular understanding is required to formulate new therapeutic strategies. Large and increasing quantities of available skeletal transcriptomics experiments give the potential for mechanistic insight of both fundamental skeletal biology and skeletal disease. However, no current repository provides access to processed, readily interpretable analysis of this data. To address this, we have developed SkeletalVis, an exploration portal for skeletal gene expression experiments. Results The SkeletalVis data portal provides an exploration and comparison platform for analysed skeletal transcriptomics data. It currently hosts 287 analysed experiments with 739 perturbation responses with comprehensive downstream analysis. We demonstrate its utility in identifying both known and novel relationships between skeletal expression signatures. SkeletalVis provides users with a platform to explore the wealth of available expression data, develop consensus signatures and the ability to compare gene signatures from new experiments to the analysed data to facilitate meta-analysis. Availability and implementation The SkeletalVis data portal is freely accessible at http://phenome.manchester.ac.uk. Supplementary information Supplementary data are available at Bioinformatics online.

APA, Harvard, Vancouver, ISO, and other styles

16

Coelho, Antonio Victor Campos, Rossella Gratton, João Paulo Britto de Melo, José Leandro Andrade-Santos, Rafael Lima Guimarães, Sergio Crovella, Paola Maura Tricarico, and Lucas André Cavalcanti Brandão. "HIV-1 Infection Transcriptomics: Meta-Analysis of CD4+ T Cells Gene Expression Profiles." Viruses 13, no. 2 (February 4, 2021): 244. http://dx.doi.org/10.3390/v13020244.

Full text

Abstract:

HIV-1 infection elicits a complex dynamic of the expression various host genes. High throughput sequencing added an expressive amount of information regarding HIV-1 infections and pathogenesis. RNA sequencing (RNA-Seq) is currently the tool of choice to investigate gene expression in a several range of experimental setting. This study aims at performing a meta-analysis of RNA-Seq expression profiles in samples of HIV-1 infected CD4+ T cells compared to uninfected cells to assess consistently differentially expressed genes in the context of HIV-1 infection. We selected two studies (22 samples: 15 experimentally infected and 7 mock-infected). We found 208 differentially expressed genes in infected cells when compared to uninfected/mock-infected cells. This result had moderate overlap when compared to previous studies of HIV-1 infection transcriptomics, but we identified 64 genes already known to interact with HIV-1 according to the HIV-1 Human Interaction Database. A gene ontology (GO) analysis revealed enrichment of several pathways involved in immune response, cell adhesion, cell migration, inflammation, apoptosis, Wnt, Notch and ERK/MAPK signaling.

APA, Harvard, Vancouver, ISO, and other styles

17

Xue, Yaxin, Anders Lanzén, and Inge Jonassen. "Reconstructing ribosomal genes from large scale total RNA meta-transcriptomic data." Bioinformatics 36, no. 11 (March 13, 2020): 3365–71. http://dx.doi.org/10.1093/bioinformatics/btaa177.

Full text

Abstract:

Abstract Motivation Technological advances in meta-transcriptomics have enabled a deeper understanding of the structure and function of microbial communities. ‘Total RNA’ meta-transcriptomics, sequencing of total reverse transcribed RNA, provides a unique opportunity to investigate both the structure and function of active microbial communities from all three domains of life simultaneously. A major step of this approach is the reconstruction of full-length taxonomic marker genes such as the small subunit ribosomal RNA. However, current tools for this purpose are mainly targeted towards analysis of amplicon and metagenomic data and thus lack the ability to handle the massive and complex datasets typically resulting from total RNA experiments. Results In this work, we introduce MetaRib, a new tool for reconstructing ribosomal gene sequences from total RNA meta-transcriptomic data. MetaRib is based on the popular rRNA assembly program EMIRGE, together with several improvements. We address the challenge posed by large complex datasets by integrating sub-assembly, dereplication and mapping in an iterative approach, with additional post-processing steps. We applied the method to both simulated and real-world datasets. Our results show that MetaRib can deal with larger datasets and recover more rRNA genes, which achieve around 60 times speedup and higher F1 score compared to EMIRGE in simulated datasets. In the real-world dataset, it shows similar trends but recovers more contigs compared with a previous analysis based on random sub-sampling, while enabling the comparison of individual contig abundances across samples for the first time. Availability and implementation The source code of MetaRib is freely available at https://github.com/yxxue/MetaRib. Contact yaxin.xue@uib.no or Inge.Jonassen@uib.no Supplementary information Supplementary data are available at Bioinformatics online.

APA, Harvard, Vancouver, ISO, and other styles

18

Massimino, Luca, Luigi Antonio Lamparelli, Yashar Houshyar, Silvia D’Alessio, Laurent Peyrin-Biroulet, Stefania Vetrano, Silvio Danese, and Federica Ungaro. "The Inflammatory Bowel Disease Transcriptome and Metatranscriptome Meta-Analysis (IBD TaMMA) framework." Nature Computational Science 1, no. 8 (August 2021): 511–15. http://dx.doi.org/10.1038/s43588-021-00114-y.

Full text

Abstract:

AbstractInflammatory bowel disease (IBD) is a class of chronic disorders whose etiogenesis is still unknown. Despite the high number of IBD-related omics studies, the RNA-sequencing data produced results that are hard to compare because of the experimental variability and different data analysis approaches. We here introduce the IBD Transcriptome and Metatranscriptome Meta-Analysis (TaMMA) framework, a comprehensive survey of publicly available IBD RNA-sequencing datasets. IBD TaMMA is an open-source platform where scientists can explore simultaneously the freely available IBD-associated transcriptomics and microbial profiles thanks to its interactive interface, resulting in a useful tool to the IBD community.

APA, Harvard, Vancouver, ISO, and other styles

19

Evgeniou, Michail, Juan Manuel Sacnun, Klaus Kratochwill, and Paul Perco. "A Meta-Analysis of Human Transcriptomics Data in the Context of Peritoneal Dialysis Identifies Novel Receptor-Ligand Interactions as Potential Therapeutic Targets." International Journal of Molecular Sciences 22, no. 24 (December 10, 2021): 13277. http://dx.doi.org/10.3390/ijms222413277.

Full text

Abstract:

Peritoneal dialysis (PD) is one therapeutic option for patients with end-stage kidney disease (ESKD). Molecular profiling of samples from PD patients using different Omics technologies has led to the discovery of dysregulated molecular processes due to PD treatment in recent years. In particular, a number of transcriptomics (TX) datasets are currently available in the public domain in the context of PD. We set out to perform a meta-analysis of TX datasets to identify dysregulated receptor-ligand interactions in the context of PD-associated complications. We consolidated transcriptomics profiles from twelve untargeted genome-wide gene expression studies focusing on human cell cultures or samples from human PD patients. Gene set enrichment analysis was used to identify enriched biological processes. Receptor-ligand interactions were identified using data from CellPhoneDB. We identified 2591 unique differentially expressed genes in the twelve PD studies. Key enriched biological processes included angiogenesis, cell adhesion, extracellular matrix organization, and inflammatory response. We identified 70 receptor-ligand interaction pairs, with both interaction partners being dysregulated on the transcriptional level in one of the investigated tissues in the context of PD. Novel receptor-ligand interactions without prior annotation in the context of PD included BMPR2-GDF6, FZD4-WNT7B, ACKR2-CCL2, or the binding of EPGN and EREG to the EGFR, as well as the binding of SEMA6D to the receptors KDR and TYROBP. In summary, we have consolidated human transcriptomics datasets from twelve studies in the context of PD and identified sets of novel receptor-ligand pairs being dysregulated in the context of PD that warrant investigation in future functional studies.

APA, Harvard, Vancouver, ISO, and other styles

20

Ortiz-Baez, Ayda Susana, John-Sebastian Eden, Craig Moritz, and Edward C. Holmes. "A Divergent Articulavirus in an Australian Gecko Identified Using Meta-Transcriptomics and Protein Structure Comparisons." Viruses 12, no. 6 (June 4, 2020): 613. http://dx.doi.org/10.3390/v12060613.

Full text

Abstract:

The discovery of highly divergent RNA viruses is compromised by their limited sequence similarity to known viruses. Evolutionary information obtained from protein structural modelling offers a powerful approach to detect distantly related viruses based on the conservation of tertiary structures in key proteins such as the RNA-dependent RNA polymerase (RdRp). We utilised a template-based approach for protein structure prediction from amino acid sequences to identify distant evolutionary relationships among viruses detected in meta-transcriptomic sequencing data from Australian wildlife. The best predicted protein structural model was compared with the results of similarity searches against protein databases. Using this combination of meta-transcriptomics and protein structure prediction we identified the RdRp (PB1) gene segment of a divergent negative-sense RNA virus, denoted Lauta virus (LTAV), in a native Australian gecko (Gehyra lauta). The presence of this virus was confirmed by PCR and Sanger sequencing. Phylogenetic analysis revealed that Lauta virus likely represents a newly described genus within the family Amnoonviridae, order Articulavirales, that is most closely related to the fish virus Tilapia tilapinevirus (TiLV). These findings provide important insights into the evolution of negative-sense RNA viruses and structural conservation of the viral replicase among members of the order Articulavirales.

APA, Harvard, Vancouver, ISO, and other styles

21

Akrioti, Elissavet, Timokratis Karamitros, Panagiotis Gkaravelas, Georgia Kouroupi, Rebecca Matsas, and Era Taoufik. "Early Signs of Molecular Defects in iPSC-Derived Neural Stems Cells from Patients with Familial Parkinson’s Disease." Biomolecules 12, no. 7 (June 23, 2022): 876. http://dx.doi.org/10.3390/biom12070876.

Full text

Abstract:

Parkinson’s disease (PD) is the second most common neurodegenerative disorder, classically associated with extensive loss of dopaminergic neurons of the substantia nigra pars compacta. The hallmark of the disease is the accumulation of pathogenic conformations of the presynaptic protein, α-synuclein (αSyn), and the formation of intraneuronal protein aggregate inclusions. Neurodegeneration of dopamine neurons leads to a prominent dopaminergic deficiency in the basal ganglia, responsible for motor disturbances. However, it is now recognized that the disease involves more widespread neuronal dysfunction, leading to early and late non-motor symptoms. The development of in vitro systems based on the differentiation of human-induced pluripotent stem cells provides us the unique opportunity to monitor alterations at the cellular and molecular level throughout the differentiation procedure and identify perturbations that occur early, even at the neuronal precursor stage. Here we aim to identify whether p.A53T-αSyn induced disturbances at the molecular level are already present in neural precursors. Towards this, we present data from transcriptomics analysis of control and p.A53T-αSyn NPCs showing altered expression in transcripts involved in axon guidance, adhesion, synaptogenesis, ion transport, and metabolism. The comparative analysis with the transcriptomics profile of p.A53T-αSyn neurons shows both distinct and overlapping pathways leading to neurodegeneration while meta-analysis with transcriptomics data from both neurodegenerative and neurodevelopmental disorders reveals that p.A53T-pathology has a significant overlap with the latter category. This is the first study showing that molecular dysregulation initiates early at the p.A53T-αSyn NPC level, suggesting that synucleinopathies may have a neurodevelopmental component.

APA, Harvard, Vancouver, ISO, and other styles

22

Keskus, Ayse Gokce, Melike Tombaz, Burcin Irem Arici, Fatma Betul Dincaslan, Afshan Nabi, Huma Shehwana, and Ozlen Konu. "Functional analysis of co-expression networks of zebrafish ace2 reveals enrichment of pathways associated with development and disease." Genome 65, no. 2 (February 2022): 57–74. http://dx.doi.org/10.1139/gen-2021-0033.

Full text

Abstract:

Human Angiotensin I Converting Enzyme 2 (ACE2) plays an essential role in blood pressure regulation and SARS-CoV-2 entry. ACE2 has a highly conserved, one-to-one ortholog (ace2) in zebrafish, which is an important model for human diseases. However, the zebrafish ace2 expression profile has not yet been studied during early development, between genders, across different genotypes, or in disease. Moreover, a network-based meta-analysis for the extraction of functionally enriched pathways associated with differential ace2 expression is lacking in the literature. Herein, we first identified significant development-, tissue-, genotype-, and gender-specific modulations in ace2 expression via meta-analysis of zebrafish Affymetrix transcriptomics datasets (ndatasets = 107); and the correlation analysis of ace2 meta-differential expression profile revealed distinct positively and negatively correlated local functionally enriched gene networks. Moreover, we demonstrated that ace2 expression was significantly modulated under different physiological and pathological conditions related to development, tissue, gender, diet, infection, and inflammation using additional RNA-seq datasets. Our findings implicate a novel translational role for zebrafish ace2 in organ differentiation and pathologies observed in the intestines and liver.

APA, Harvard, Vancouver, ISO, and other styles

23

Wille, Michelle, Hans Netter, Margaret Littlejohn, Lilly Yuen, Mang Shi, John-Sebastian Eden, Marcel Klaassen, Edward Holmes, and Aeron Hurt. "A Divergent Hepatitis D-Like Agent in Birds." Viruses 10, no. 12 (December 17, 2018): 720. http://dx.doi.org/10.3390/v10120720.

Full text

Abstract:

Hepatitis delta virus (HDV) is currently only found in humans and is a satellite virus that depends on hepatitis B virus (HBV) envelope proteins for assembly, release, and entry. Using meta-transcriptomics, we identified the genome of a novel HDV-like agent in ducks. Sequence analysis revealed secondary structures that were shared with HDV, including self-complementarity and ribozyme features. The predicted viral protein shares 32% amino acid similarity to the small delta antigen of HDV and comprises a divergent phylogenetic lineage. The discovery of an avian HDV-like agent has important implications for the understanding of the origins of HDV and sub-viral agents.

APA, Harvard, Vancouver, ISO, and other styles

24

Chung, Matthew, Preston J. Basting, Rayanna S. Patkus, Alexandra Grote, Ashley N. Luck, Elodie Ghedin, Barton E. Slatko, et al. "A Meta-Analysis of Wolbachia Transcriptomics Reveals a Stage-Specific Wolbachia Transcriptional Response Shared Across Different Hosts." G3 Genes|Genomes|Genetics 10, no. 9 (September 1, 2020): 3243–60. http://dx.doi.org/10.1534/g3.120.401534.

Full text

Abstract:

Abstract Wolbachia is a genus containing obligate, intracellular endosymbionts with arthropod and nematode hosts. Numerous studies have identified differentially expressed transcripts in Wolbachia endosymbionts that potentially inform the biological interplay between these endosymbionts and their hosts, albeit with discordant results. Here, we re-analyze previously published Wolbachia RNA-Seq transcriptomics data sets using a single workflow consisting of the most up-to-date algorithms and techniques, with the aim of identifying trends or patterns in the pan-Wolbachia transcriptional response. We find that data from one of the early studies in filarial nematodes did not allow for robust conclusions about Wolbachia differential expression with these methods, suggesting the original interpretations should be reconsidered. Across datasets analyzed with this unified workflow, there is a general lack of global gene regulation with the exception of a weak transcriptional response resulting in the upregulation of ribosomal proteins in early larval stages. This weak response is observed across diverse Wolbachia strains from both nematode and insect hosts suggesting a potential pan-Wolbachia transcriptional response during host development that diverged more than 700 million years ago.

APA, Harvard, Vancouver, ISO, and other styles

25

Newton, Richard, and Lorenz Wernisch. "A Meta-Analysis of Multiple Matched Copy Number and Transcriptomics Data Sets for Inferring Gene Regulatory Relationships." PLoS ONE 9, no. 8 (August 22, 2014): e105522. http://dx.doi.org/10.1371/journal.pone.0105522.

Full text

APA, Harvard, Vancouver, ISO, and other styles

26

Cho, Sangkyun, Jerome Irianto, and Dennis E. Discher. "Mechanosensing by the nucleus: From pathways to scaling relationships." Journal of Cell Biology 216, no. 2 (January 2, 2017): 305–15. http://dx.doi.org/10.1083/jcb.201610042.

Full text

Abstract:

The nucleus is linked mechanically to the extracellular matrix via multiple polymers that transmit forces to the nuclear envelope and into the nuclear interior. Here, we review some of the emerging mechanisms of nuclear mechanosensing, which range from changes in protein conformation and transcription factor localization to chromosome reorganization and membrane dilation up to rupture. Nuclear mechanosensing encompasses biophysically complex pathways that often converge on the main structural proteins of the nucleus, the lamins. We also perform meta-analyses of public transcriptomics and proteomics data, which indicate that some of the mechanosensing pathways relaying signals from the collagen matrix to the nucleus apply to a broad range of species, tissues, and diseases.

APA, Harvard, Vancouver, ISO, and other styles

27

Rue-Albrecht, Kevin, Federico Marini, Charlotte Soneson, and Aaron T. L. Lun. "iSEE: Interactive SummarizedExperiment Explorer." F1000Research 7 (June 14, 2018): 741. http://dx.doi.org/10.12688/f1000research.14966.1.

Full text

Abstract:

Data exploration is critical to the comprehension of large biological data sets generated by high-throughput assays such as sequencing. However, most existing tools for interactive visualisation are limited to specific assays or analyses. Here, we present the iSEE (Interactive SummarizedExperiment Explorer) software package, which provides a general visual interface for exploring data in a SummarizedExperiment object. iSEE is directly compatible with many existing R/Bioconductor packages for analysing high-throughput biological data, and provides useful features such as simultaneous examination of (meta)data and analysis results, dynamic linking between plots and code tracking for reproducibility. We demonstrate the utility and flexibility of iSEE by applying it to explore a range of real transcriptomics and proteomics data sets.

APA, Harvard, Vancouver, ISO, and other styles

28

Mishra, Aastha, Shankar Chanchal, and Mohammad Z. Ashraf. "Host–Viral Interactions Revealed among Shared Transcriptomics Signatures of ARDS and Thrombosis: A Clue into COVID-19 Pathogenesis." TH Open 04, no. 04 (October 2020): e403-e412. http://dx.doi.org/10.1055/s-0040-1721706.

Full text

Abstract:

AbstractSevere novel corona virus disease 2019 (COVID-19) infection is associated with a considerable activation of coagulation pathways, endothelial damage, and subsequent thrombotic microvascular injuries. These consistent observations may have serious implications for the treatment and management of this highly pathogenic disease. As a consequence, the anticoagulant therapeutic strategies, such as low molecular weight heparin, have shown some encouraging results. Cytokine burst leading to sepsis which is one of the primary reasons for acute respiratory distress syndrome (ARDS) drive that could be worsened with the accumulation of coagulation factors in the lungs of COVID-19 patients. However, the obscurity of this syndrome remains a hurdle in making decisive treatment choices. Therefore, an attempt to characterize shared biological mechanisms between ARDS and thrombosis using comprehensive transcriptomics meta-analysis is made. We conducted an integrated gene expression meta-analysis of two independently publicly available datasets of ARDS and venous thromboembolism (VTE). Datasets GSE76293 and GSE19151 derived from National Centre for Biotechnology Information–Gene Expression Omnibus (NCBI-GEO) database were used for ARDS and VTE, respectively. Integrative meta-analysis of expression data (INMEX) tool preprocessed the datasets and effect size combination with random effect modeling was used for obtaining differentially expressed genes (DEGs). Network construction was done for hub genes and pathway enrichment analysis. Our meta-analysis identified a total of 1,878 significant DEGs among the datasets, which when subjected to enrichment analysis suggested inflammation–coagulation–hypoxemia convolutions in COVID-19 pathogenesis. The top hub genes of our study such as tumor protein 53 (TP53), lysine acetyltransferase 2B (KAT2B), DExH-box helicase 9 (DHX9), REL-associated protein (RELA), RING-box protein 1 (RBX1), and proteasome 20S subunit beta 2 (PSMB2) gave insights into the genes known to be participating in the host–virus interactions that could pave the way to understand the various strategies deployed by the virus to improve its replication and spreading.

APA, Harvard, Vancouver, ISO, and other styles

29

Vahlensieck, Christian, Cora S. Thiel, Jan Adelmann, Beatrice A. Lauber, Jennifer Polzer, and Oliver Ullrich. "Rapid Transient Transcriptional Adaptation to Hypergravity in Jurkat T Cells Revealed by Comparative Analysis of Microarray and RNA-Seq Data." International Journal of Molecular Sciences 22, no. 16 (August 6, 2021): 8451. http://dx.doi.org/10.3390/ijms22168451.

Full text

Abstract:

Cellular responses to micro- and hypergravity are rapid and complex and appear within the first few seconds of exposure. Transcriptomic analyses are a valuable tool to analyze these genome-wide cellular alterations. For a better understanding of the cellular dynamics upon altered gravity exposure, it is important to compare different time points. However, since most of the experiments are designed as endpoint measurements, the combination of cross-experiment meta-studies is inevitable. Microarray and RNA-Seq analyses are two of the main methods to study transcriptomics. In the field of altered gravity research, both methods are frequently used. However, the generation of these data sets is difficult and time-consuming and therefore the number of available data sets in this research field is limited. In this study, we investigated the comparability of microarray and RNA-Seq data and applied the results to a comparison of the transcriptomics dynamics between the hypergravity conditions during two real flight platforms and a centrifuge experiment to identify temporal adaptation processes. We performed a comparative study on an Affymetrix HTA2.0 microarray and a paired-end RNA-Seq data set originating from the same Jurkat T cell RNA samples from a short-term hypergravity experiment. The overall agreeability was high, with better sensitivity of the RNA-Seq analysis. The microarray data set showed weaknesses on the level of single upregulated genes, likely due to its normalization approach. On an aggregated level of biotypes, chromosomal distribution, and gene sets, both technologies performed equally well. The microarray showed better performance on the detection of altered gravity-related splicing events. We found that all initially altered transcripts fully adapted after 15 min to hypergravity and concluded that the altered gene expression response to hypergravity is transient and fully reversible. Based on the combined multiple-platform meta-analysis, we could demonstrate rapid transcriptional adaptation to hypergravity, the differential expression of the ATPase subunits ATP6V1A and ATP6V1D, and the cluster of differentiation (CD) molecules CD1E, CD2AP, CD46, CD47, CD53, CD69, CD96, CD164, and CD226 in hypergravity. We could experimentally demonstrate that it is possible to develop methodological evidence for the meta-analysis of individual data.

APA, Harvard, Vancouver, ISO, and other styles

30

Turnbull, Olivia M. H., Ayda Susana Ortiz-Baez, John-Sebastian Eden, Mang Shi, Jane E. Williamson, Troy F. Gaston, Yong-Zhen Zhang, Edward C. Holmes, and Jemma L. Geoghegan. "Meta-Transcriptomic Identification of Divergent Amnoonviridae in Fish." Viruses 12, no. 11 (November 4, 2020): 1254. http://dx.doi.org/10.3390/v12111254.

Full text

Abstract:

Tilapia lake virus (TiLV) has caused mass mortalities in farmed and wild tilapia with serious economic and ecological consequences. Until recently, this virus was the sole member of the Amnoonviridae, a family within the order Articulavirales comprising segmented negative-sense RNA viruses. We sought to identify additional viruses within the Amnoonviridae through total RNA sequencing (meta-transcriptomics) and data mining of published transcriptomes. Accordingly, we sampled marine fish species from both Australia and China and discovered several segments of two new viruses within the Amnoonviridae, tentatively called Flavolineata virus and Piscibus virus, respectively. In addition, by mining vertebrate transcriptome data, we identified nine additional virus transcripts matching to multiple genomic segments of TiLV in both marine and freshwater fish. These new viruses retained sequence conservation with the distantly related Orthomyxoviridae in the RdRp subunit PB1, but formed a distinct and diverse phylogenetic group. These data suggest that the Amnoonviridae have a broad host range within fish and that greater animal sampling will identify additional divergent members of the Articulavirales.

APA, Harvard, Vancouver, ISO, and other styles

31

Bazile, Jeanne, Florence Jaffrezic, Patrice Dehais, Matthieu Reichstadt, Christophe Klopp, Denis Laloe, and Muriel Bonnet. "Molecular signatures of muscle growth and composition deciphered by the meta-analysis of age-related public transcriptomics data." Physiological Genomics 52, no. 8 (August 1, 2020): 322–32. http://dx.doi.org/10.1152/physiolgenomics.00020.2020.

Full text

Abstract:

The lean-to-fat ratio is a major issue in the beef meat industry from both carcass and meat production perspectives. This industrial perspective has motivated meat physiologists to use transcriptomics technologies to decipher mechanisms behind fat deposition within muscle during the time course of muscle growth. However, synthetic biological information from this volume of data remains to be produced to identify mechanisms found in various breeds and rearing practices. We conducted a meta-analysis on 10 transcriptomic data sets stored in public databases, from the longissimus thoracis of five different bovine breeds divergent by age. We updated gene identifiers on the last version of the bovine genome (UCD1.2), and the 715 genes common to the 10 studies were subjected to the meta-analysis. Of the 238 genes differentially expressed (DEG), we identified a transcriptional signature of the dynamic regulation of glycolytic and oxidative metabolisms that agrees with a known shift between those two pathways from the animal puberty. We proposed some master genes of the myogenesis, namely MYOG and MAPK14, as probable regulators of the glycolytic and oxidative metabolisms. We also identified overexpressed genes related to lipid metabolism (APOE, LDLR, MXRA8, and HSP90AA1) that may contribute to the expected enhanced marbling as age increases. Lastly, we proposed a transcriptional signature related to the induction (YBX1) or repression (MAPK14, YWAH, ERBB2) of the commitment of myogenic progenitors into the adipogenic lineage. The relationships between the abundance of the identified mRNA and marbling values remain to be analyzed in a marbling biomarkers discovery perspectives.

APA, Harvard, Vancouver, ISO, and other styles

32

Noori, Ayush, Aziz M. Mezlini, Bradley T. Hyman, Alberto Serrano-Pozo, and Sudeshna Das. "Systematic review and meta-analysis of human transcriptomics reveals neuroinflammation, deficient energy metabolism, and proteostasis failure across neurodegeneration." Neurobiology of Disease 149 (February 2021): 105225. http://dx.doi.org/10.1016/j.nbd.2020.105225.

Full text

APA, Harvard, Vancouver, ISO, and other styles

33

Riquelme-Perez, Miriam, Fernando Perez-Sanz, Jean-François Deleuze, Carole Escartin, Eric Bonnet, and Solène Brohard. "DEVEA: an interactive shiny application for Differential Expression analysis, data Visualization and Enrichment Analysis of transcriptomics data." F1000Research 11 (June 28, 2022): 711. http://dx.doi.org/10.12688/f1000research.122949.1.

Full text

Abstract:

We are at a time of considerable growth in the use and development of transcriptomics studies and subsequent in silico analysis. RNA sequencing is one of the most widely used approaches, now integrated in many studies. The processing of these data may typically require a noteworthy number of steps, statistical knowledge, and coding skills which is not accessible to all scientists. Despite the undeniable development of software applications over the years to address this concern, it is still possible to improve. Here we present DEVEA, an R shiny application tool developed to perform differential expression analysis, data visualization and enrichment pathway analysis mainly from transcriptomics data, but also from simpler gene lists with or without statistical values. Its intuitive and easy-to-manipulate interface facilitates gene expression exploration through numerous interactive figures and tables, statistical comparisons of expression profile levels between groups and further meta-analysis such as enrichment analysis, without bioinformatics expertise. DEVEA performs a thorough analysis from multiple and flexible input data representing distinct analysis stages. From them, it produces dynamic graphs and tables, to explore the expression levels and statistical differential expression analysis results. Moreover, it generates a comprehensive pathway analysis to extend biological insights. Finally, a complete and customizable HTML report can be extracted for further result exploration outside the application. DEVEA is accessible at https://shiny.imib.es/devea/ and the source code is available on our GitHub repository https://github.com/MiriamRiquelmeP/DEVEA.

APA, Harvard, Vancouver, ISO, and other styles

34

Rosales, Stephanie M., and Rebecca Vega Thurber. "Brain Meta-Transcriptomics from Harbor Seals to Infer the Role of the Microbiome and Virome in a Stranding Event." PLOS ONE 10, no. 12 (December 2, 2015): e0143944. http://dx.doi.org/10.1371/journal.pone.0143944.

Full text

APA, Harvard, Vancouver, ISO, and other styles

35

Casanova Ferrer, Franc, María Pascual, Marta R. Hidalgo, Pablo Malmierca-Merlo, Consuelo Guerri, and Francisco García-García. "Unveiling Sex-Based Differences in the Effects of Alcohol Abuse: A Comprehensive Functional Meta-Analysis of Transcriptomic Studies." Genes 11, no. 9 (September 21, 2020): 1106. http://dx.doi.org/10.3390/genes11091106.

Full text

Abstract:

The abuse of alcohol, one of the most popular psychoactive substances, can cause several pathological and psychological consequences, including alcohol use disorder (AUD). An impaired ability to stop or control alcohol intake despite adverse health or social consequences characterize AUD. While AUDs predominantly occur in men, growing evidence suggests the existence of distinct cognitive and biological consequences of alcohol dependence in women. The molecular and physiological mechanisms participating in these differential effects remain unknown. Transcriptomic technology permits the detection of the biological mechanisms responsible for such sex-based differences, which supports the subsequent development of novel personalized therapeutics to treat AUD. We conducted a systematic review and meta-analysis of transcriptomics studies regarding alcohol dependence in humans with representation from both sexes. For each study, we processed and analyzed transcriptomic data to obtain a functional profile of pathways and biological functions and then integrated the resulting data by meta-analysis to characterize any sex-based transcriptomic differences associated with AUD. Global results of the transcriptomic analysis revealed the association of decreased tissue regeneration, embryo malformations, altered intracellular transport, and increased rate of RNA and protein replacement with female AUD patients. Meanwhile, our analysis indicated that increased inflammatory response and blood pressure and a reduction in DNA repair capabilities are associated with male AUD patients. In summary, our functional meta-analysis of transcriptomic studies provides evidence for differential biological mechanisms of AUD patients of differing sex.

APA, Harvard, Vancouver, ISO, and other styles

36

Deffur, Armin, Robert J. Wilkinson, Bongani M. Mayosi, and Nicola M. Mulder. "ANIMA: Association network integration for multiscale analysis." Wellcome Open Research 3 (March 12, 2018): 27. http://dx.doi.org/10.12688/wellcomeopenres.14073.1.

Full text

Abstract:

Contextual functional interpretation of -omics data derived from clinical samples is a classical and difficult problem in computational systems biology. The measurement of thousands of data points on single samples has become routine but relating ‘big data’ datasets to the complexities of human pathobiology is an area of ongoing research. Complicating this is the fact that many publically available datasets use bulk transcriptomics data from complex tissues like blood. The most prevalent analytic approaches derive molecular ‘signatures’ of disease states or apply modular analysis frameworks to the data. Here we describe ANIMA (association network integration for multiscale analysis), a network-based data integration method using clinical phenotype and microarray data as inputs. ANIMA is implemented in R and Neo4j and runs in Docker containers. In short, the build algorithm iterates over one or more transcriptomics datasets to generate a large, multipartite association network by executing multiple independent analytic steps (differential expression, deconvolution, modular analysis based on co-expression, pathway analysis) and integrating the results. Once the network is built, it can be queried directly using Cypher, or via custom functions that communicate with the graph database via language-specific APIs. We developed a web application using Shiny, which provides fully interactive, multiscale views of the data. Using our approach, we show that we can reconstruct multiple features of disease states at various scales of organization, from transcript abundance patterns of individual genes through co-expression patterns of groups of genes to patterns of cellular behaviour in whole blood samples, both in single experiments as well as in a meta-analysis of multiple datasets.

APA, Harvard, Vancouver, ISO, and other styles

37

Di Nanni, Noemi, Matteo Bersanelli, Francesca Anna Cupaioli, Luciano Milanesi, Alessandra Mezzelani, and Ettore Mosca. "Network-Based Integrative Analysis of Genomics, Epigenomics and Transcriptomics in Autism Spectrum Disorders." International Journal of Molecular Sciences 20, no. 13 (July 9, 2019): 3363. http://dx.doi.org/10.3390/ijms20133363.

Full text

Abstract:

Current studies suggest that autism spectrum disorders (ASDs) may be caused by many genetic factors. In fact, collectively considering multiple studies aimed at characterizing the basic pathophysiology of ASDs, a large number of genes has been proposed. Addressing the problem of molecular data interpretation using gene networks helps to explain genetic heterogeneity in terms of shared pathways. Besides, the integrative analysis of multiple omics has emerged as an approach to provide a more comprehensive view of a disease. In this work, we carry out a network-based meta-analysis of the genes reported as associated with ASDs by studies that involved genomics, epigenomics, and transcriptomics. Collectively, our analysis provides a prioritization of the large number of genes proposed to be associated with ASDs, based on genes’ relevance within the intracellular circuits, the strength of the supporting evidence of association with ASDs, and the number of different molecular alterations affecting genes. We discuss the presence of the prioritized genes in the SFARI (Simons Foundation Autism Research Initiative) database and in gene networks associated with ASDs by other investigations. Lastly, we provide the full results of our analyses to encourage further studies on common targets amenable to therapy.

APA, Harvard, Vancouver, ISO, and other styles

38

Rosales, Stephanie M., and Rebecca Vega Thurber. "Correction: Brain Meta-Transcriptomics from Harbor Seals to Infer the Role of the Microbiome and Virome in a Stranding Event." PLOS ONE 10, no. 12 (December 29, 2015): e0146208. http://dx.doi.org/10.1371/journal.pone.0146208.

Full text

APA, Harvard, Vancouver, ISO, and other styles

39

Kori, Medi, and Kazim Yalcin Arga. "Potential biomarkers and therapeutic targets in cervical cancer: Insights from the meta-analysis of transcriptomics data within network biomedicine perspective." PLOS ONE 13, no. 7 (July 18, 2018): e0200717. http://dx.doi.org/10.1371/journal.pone.0200717.

Full text

APA, Harvard, Vancouver, ISO, and other styles

40

Tsiantas, Konstantinos, Spyridon J. Konteles, Eftichia Kritsi, Vassilia J. Sinanoglou, Thalia Tsiaka, and Panagiotis Zoumpoulakis. "Effects of Non-Polar Dietary and Endogenous Lipids on Gut Microbiota Alterations: The Role of Lipidomics." International Journal of Molecular Sciences 23, no. 8 (April 7, 2022): 4070. http://dx.doi.org/10.3390/ijms23084070.

Full text

Abstract:

Advances in sequencing technologies over the past 15 years have led to a substantially greater appreciation of the importance of the gut microbiome to the health of the host. Recent outcomes indicate that aspects of nutrition, especially lipids (exogenous or endogenous), can influence the gut microbiota composition and consequently, play an important role in the metabolic health of the host. Thus, there is an increasing interest in applying holistic analytical approaches, such as lipidomics, metabolomics, (meta)transcriptomics, (meta)genomics, and (meta)proteomics, to thoroughly study the gut microbiota and any possible interplay with nutritional or endogenous components. This review firstly summarizes the general background regarding the interactions between important non-polar dietary (i.e., sterols, fat-soluble vitamins, and carotenoids) or amphoteric endogenous (i.e., eicosanoids, endocannabinoids-eCBs, and specialized pro-resolving mediators-SPMs) lipids and gut microbiota. In the second stage, through the evaluation of a vast number of dietary clinical interventions, a comprehensive effort is made to highlight the role of the above lipid categories on gut microbiota and vice versa. In addition, the present status of lipidomics in current clinical interventions as well as their strengths and limitations are also presented. Indisputably, dietary lipids and most phytochemicals, such as sterols and carotenoids, can play an important role on the development of medical foods or nutraceuticals, as they exert prebiotic-like effects. On the other hand, endogenous lipids can be considered either prognostic indicators of symbiosis or dysbiosis or even play a role as specialized mediators through dietary interventions, which seem to be regulated by gut microbiota.

APA, Harvard, Vancouver, ISO, and other styles

41

Deffur, Armin, Robert J. Wilkinson, Bongani M. Mayosi, and Nicola M. Mulder. "ANIMA: Association network integration for multiscale analysis." Wellcome Open Research 3 (June 5, 2018): 27. http://dx.doi.org/10.12688/wellcomeopenres.14073.2.

Full text

Abstract:

Contextual functional interpretation of -omics data derived from clinical samples is a classical and difficult problem in computational systems biology. The measurement of thousands of data points on single samples has become routine but relating ‘big data’ datasets to the complexities of human pathobiology is an area of ongoing research. Complicating this is the fact that many publicly available datasets use bulk transcriptomics data from complex tissues like blood. The most prevalent analytic approaches derive molecular ‘signatures’ of disease states or apply modular analysis frameworks to the data. Here we describe ANIMA (association network integration for multiscale analysis), a network-based data integration method using clinical phenotype and microarray data as inputs. ANIMA is implemented in R and Neo4j and runs in Docker containers. In short, the build algorithm iterates over one or more transcriptomics datasets to generate a large, multipartite association network by executing multiple independent analytic steps (differential expression, deconvolution, modular analysis based on co-expression, pathway analysis) and integrating the results. Once the network is built, it can be queried directly using Cypher (a graph query language), or by custom functions that communicate with the graph database via language-specific APIs. We developed a web application using Shiny, which provides fully interactive, multiscale views of the data. Using our approach, we show that we can reconstruct multiple features of disease states at various scales of organization, from transcript abundance patterns of individual genes through co-expression patterns of groups of genes to patterns of cellular behaviour in whole blood samples, both in single experiments as well in meta-analyses of multiple datasets.

APA, Harvard, Vancouver, ISO, and other styles

42

Deffur, Armin, Robert J. Wilkinson, Bongani M. Mayosi, and Nicola M. Mulder. "ANIMA: Association network integration for multiscale analysis." Wellcome Open Research 3 (November 14, 2018): 27. http://dx.doi.org/10.12688/wellcomeopenres.14073.3.

Full text

Abstract:

Contextual functional interpretation of -omics data derived from clinical samples is a classical and difficult problem in computational systems biology. The measurement of thousands of data points on single samples has become routine but relating ‘big data’ datasets to the complexities of human pathobiology is an area of ongoing research. Complicating this is the fact that many publicly available datasets use bulk transcriptomics data from complex tissues like blood. The most prevalent analytic approaches derive molecular ‘signatures’ of disease states or apply modular analysis frameworks to the data. Here we describe ANIMA (association network integration for multiscale analysis), a network-based data integration method using clinical phenotype and microarray data as inputs. ANIMA is implemented in R and Neo4j and runs in Docker containers. In short, the build algorithm iterates over one or more transcriptomics datasets to generate a large, multipartite association network by executing multiple independent analytic steps (differential expression, deconvolution, modular analysis based on co-expression, pathway analysis) and integrating the results. Once the network is built, it can be queried directly using Cypher (a graph query language), or by custom functions that communicate with the graph database via language-specific APIs. We developed a web application using Shiny, which provides fully interactive, multiscale views of the data. Using our approach, we show that we can reconstruct multiple features of disease states at various scales of organization, from transcript abundance patterns of individual genes through co-expression patterns of groups of genes to patterns of cellular behaviour in whole blood samples, both in single experiments as well in meta-analyses of multiple datasets.

APA, Harvard, Vancouver, ISO, and other styles

43

Li, Ci-Xiu, Wei-Shan Chang, Katerina Mitsakos, James Rodger, Edward C. Holmes, and Bernard J. Hudson. "Identification of a Novel Equine Papillomavirus in Semen from a Thoroughbred Stallion with a Penile Lesion." Viruses 11, no. 8 (August 4, 2019): 713. http://dx.doi.org/10.3390/v11080713.

Full text

Abstract:

Papillomaviruses (PVs) have been identified in a wide range of animal species and are associated with a variety of disease syndromes including classical papillomatosis, aural plaques, and genital papillomas. In horses, 13 PVs have been described to date, falling into six genera. Using total RNA sequencing (meta-transcriptomics) we identified a novel equine papillomavirus in semen taken from a thoroughbred stallion suffering a genital lesion, which was confirmed by nested RT-PCR. We designate this novel virus Equus caballus papillomavirus 9 (EcPV9). The complete 7656 bp genome of EcPV9 exhibited similar characteristics to those of other horse papillomaviruses. Phylogenetic analysis based on concatenated E1-E2-L2-L1 amino acid sequences revealed that EcPV9 clustered with EcPV2, EcPV4, and EcPV5, although was distinct enough to represent a new viral species within the genus Dyoiotapapillomavirus (69.35%, 59.25%, and 58.00% nucleotide similarity to EcPV2, EcPV4, and EcPV5, respectively). In sum, we demonstrate the presence of a novel equine papillomavirus for which more detailed studies of disease association are merited.

APA, Harvard, Vancouver, ISO, and other styles

44

Rohr, Michael Walter, Jordan Beardsley, Sai Preethi Nakkina, Dexter Hadley, and Deborah Altomare. "Abstract 2689: FGF19 is a novel serum colorectal cancer biomarker that exerts endocrine paraneoplastic effects on hepatic tissue." Cancer Research 82, no. 12_Supplement (June 15, 2022): 2689. http://dx.doi.org/10.1158/1538-7445.am2022-2689.

Full text

Abstract:

Abstract Despite having excellent prognosis when detected early, colorectal cancer (CRC) remains a leading cause of cancer-related deaths globally. Barriers to screening reduces compliance and negatively impacts patient outcomes, necessitating alternatives. A blood-based approach provides a more convenient and accessible modality, but serum markers are lacking. Using a meta-transcriptomics approach, we identified Fibroblast Growth Factor 19 (FGF19), an enteroendocrine FGF responsible for bile acid (BA) homeostasis, as an attractive CRC marker. However, whether FGF19 is aberrantly secreted into blood by colorectal tumors or induces endocrine-like paraneoplastic effects is unknown. To assess the strength of FGF19 as a CRC biomarker, expression data from the Genotype-Tissue Expression consortium (GTEx), The Cancer Genome Atlas (TCGA-COADREAD), and our curated Meta-dataset (E-MTAB-10089) were downloaded and analyzed for associations with prognostic indicators. Next, in silico FGF19 expression profiles were validated in vitro using a panel of five CRC cell lines via western blot with secretion quantitated by sandwich ELISA. To determine whether colorectal tumors contribute FGF19 to circulation, subcutaneous xenografts of HCT116 and Colo201 cells were established in four male and female NOD Scid gamma (NSG) mice. Tumor volume, as well as serum and urine FGF19 were assessed weekly over a 36-day period. Following euthanasia, murine liver and ileal tissue were processed for downstream mRNA and bile acid quantification. To determine if malignant FGF19 exerts paraneoplastic effects RNA sequencing was performed on hepatic mRNA using the Illumina NovaSeq 6000 system. Reads were processed, aligned, mapped, and analyzed for differential expression and functional enrichment using an integrated informatics pipeline implemented in R. Meta-transcriptomics revealed that ectopic overexpression of FGF19 was highly indicative of CRC and associated with unfavorable prognostic indicators including disease progression, treatment failure, and poor survival. In vitro testing recapitulated in silico findings, showing that that four out of five CRC cell lines constitutively express and secrete FGF19. We also readily detected FGF19 in serum and urine of mice harboring xenografts derived from Colo201, but not HCT116, cells. Moreover, circulating FGF19 levels increased with tumor size and exerted paraneoplastic effects on liver tissue such as suppression of BA synthesis, dysregulation of cholesterol metabolism, and induction of pre-neoplasia. In summary, we describe FGF19 as a putative serum CRC biomarker that exerts novel endocrine-like paraneoplastic effects on the liver. Study limitations included the lack of FGF19 quantification in CRC patient blood, in vivo experimentation using two different cell lines, and gender-related batch effects identified by RNA sequencing. Citation Format: Michael Walter Rohr, Jordan Beardsley, Sai Preethi Nakkina, Dexter Hadley, Deborah Altomare. FGF19 is a novel serum colorectal cancer biomarker that exerts endocrine paraneoplastic effects on hepatic tissue [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2689.

APA, Harvard, Vancouver, ISO, and other styles

45

Dekker, Simone E., Ted Bambakidis, Martin Sillesen, Baoling Liu, Yongqing Li, and Hasan B. Alam. "Unraveling the Cytoprotective Effects of Valproic Acid: A Transcriptomics Meta-Analysis of Transfusion Strategies for Hemorrhagic Shock and Traumatic Brain Injury." Blood 138, Supplement 1 (November 5, 2021): 3245. http://dx.doi.org/10.1182/blood-2021-151075.

Full text

Abstract:

Abstract Introduction: Traumatic brain injury (TBI) results in widespread impairment of hemostasis, fibrinolysis, coagulation, endothelial function, and immune function. While damage control resuscitation (DCR) is a well-established treatment strategy for life-threatening hemorrhage, alternative treatment strategies should be applied to patients with concurrent TBI. Commonly used resuscitation fluids such as crystalloids or colloids have several disadvantages and may even be harmful when administered in large quantities. In contrast, pharmacologic agents, such as the histone deacetylase inhibitor valproic acid (VPA), have shown promising results in animal studies of TBI and hemorrhagic shock (HS). We previously showed that VPA not only decreases platelet hyper-activation and improves clot dynamics in in-vitro experiments, but also decreases transfusion requirements and improves survival in a porcine DCR model. In those animal models, VPA was administered in conjunction with fluid resuscitation such as fresh frozen plasma (FFP) or hextend (HEX). However, we wondered whether VPA itself induces cytoprotective properties that may underlie the restoration of hemostasis, endothelial function, and immune function that we observed in our models. This meta-analysis used computational biology to identify changes in the brain transcriptome due to VPA treatment that occurred independent of the chosen transfusion fluid. Methods: Swine underwent TBI+HS, kept in shock for 2 hours, and resuscitated with normal saline (control), FFP, FFP+VPA, HEX, or HEX+VPA (n=5/group; all VPA doses 300 mg/kg). After 6 hours of observation, brain RNA was isolated and gene expression was analyzed using a microarray. Gene expression data were normalized to a normal saline control group. Transcriptomic data were imported into iPathwayGuide to identify significantly enriched genes and Gene Ontology (GO) terms. Genes were considered to be differentially expressed if they exhibited a log-fold change (logFC) > 1.0 (fold change > 2) and a p-value < 0.05. The differences in gene expression where then summarized in a Venn-diagram. GO terms identified the Biological Processes with the greatest modulation based on both significance and number of DE genes. GO term P-values were corrected using Elim-pruning. Results: A total of 673 differentially expressed genes were identified. The FFP+VPA group exhibited 206 uniquely expressed genes and the HEX+VPA group 121. We found a total of 113 genes that were expressed in both the FFP+VPA and HEX+VPA groups, but not in the FFP and HEX only groups (Figure). Table 1 summarizes the 10 most up- and down-regulated genes that are only expressed in VPA groups (i.e. FFP+VPA and HEX+VPA). Unregulated genes specifically associated with VPA were involved in promotion of cell division, neurogenesis, cytoskeleton, and ion-channels, while down-regulated genes were involved in metalloproteins, neurodegenerative diseases, and cell cycle arrest. Significantly modulated Biological Processes identified by GO terms include: erythrocyte maturation, macrophage activation, microglial cell proliferation, signal transduction by P53, fibrinolysis and plasminogen activation, fibroblast migration, and neurogenesis. Conclusion: Overall, this meta-analysis suggests that VPA altered the expression of approximately 1/6 th of all genes that were differentially expressed in our cohort. These genes are involved in a variety of biological processes such as cell division, neurogenesis, coagulation, cytoskeleton, and inflammation. These results suggest that VPA treatment may promote an environment that favors the restoration of hemostasis, production of new neurons, removal of damaged cells, and attenuation of inflammation. Such findings suggest that VPA treatment alone may be a promising therapeutic for the treatment of life-threatening hemorrhage and TBI. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

APA, Harvard, Vancouver, ISO, and other styles

46

Hovhannisyan, Hrant, Ahmed Hafez, Carlos Llorens, and Toni Gabaldón. "CROSSMAPPER: estimating cross-mapping rates and optimizing experimental design in multi-species sequencing studies." Bioinformatics 36, no. 3 (August 8, 2019): 925–27. http://dx.doi.org/10.1093/bioinformatics/btz626.

Full text

Abstract:

Abstract Motivation Numerous sequencing studies, including transcriptomics of host-pathogen systems, sequencing of hybrid genomes, xenografts, mixed species systems, metagenomics and meta-transcriptomics, involve samples containing genetic material from divergent organisms. A crucial step in these studies is identifying from which organism each sequencing read originated, and the experimental design should be directed to minimize biases caused by cross-mapping of reads to incorrect source genomes. Additionally, pooling of sufficiently different genetic material into a single sequencing library could significantly reduce experimental costs but requires careful planning and assessment of the impact of cross-mapping. Having these applications in mind we designed Crossmapper, the first to our knowledge tool able to assess cross-mapping prior to sequencing, therefore allowing optimization of experimental design. Results Using any combination of reference genomes, Crossmapper performs read simulation and back-mapping of those reads to the pool of references, quantifies and reports the cross-mapping rates for each organism. Crossmapper performs these analyses with numerous user-specified parameters, including, among others, read length, read layout, coverage, mapping parameters, genomic or transcriptomic data. Additionally, it outputs the results in highly interactive and publication-ready reports. This allows the user to perform multiple comparisons at once and choose the experimental setup minimizing cross-mapping rates. Moreover, Crossmapper can be used for resource optimization in sequencing facilities by pooling different samples into one sequencing library. Availability and implementation Crossmapper is a command line tool implemented in Python 3.6 and available as a conda package, allowing effortless installation. The source code, detailed information and a step-by-step tutorial is available at our GitHub page https://github.com/Gabaldonlab/crossmapper. Supplementary information Supplementary data are available at Bioinformatics online.

APA, Harvard, Vancouver, ISO, and other styles

47

Kanakoglou, Dimitrios S., Theodora-Dafni Michalettou, Christina Vasileiou, Evangelos Gioukakis, Dorothea Maneta, Konstantinos V. Kyriakidis, Alexandros G. Georgakilas, and Ioannis Michalopoulos. "Effects of High-Dose Ionizing Radiation in Human Gene Expression: A Meta-Analysis." International Journal of Molecular Sciences 21, no. 6 (March 12, 2020): 1938. http://dx.doi.org/10.3390/ijms21061938.

Full text

Abstract:

The use of high-dose Ionizing Radiation (IR) is currently one of the most common modalities in treatment of many types of cancer. The objective of this work was to investigate the effects of high-dose ionizing radiation on healthy human tissue, utilizing quantitative analysis of gene expression. To this end, publicly available transcriptomics datasets from human samples irradiated with a high dose of radiation and non-irradiated (control) ones were selected, and gene expression was determined using RNA-Seq data analysis. Raw data from these studies were subjected to quality control and trimming. Mapping of RNA-Seq reads was performed by the partial selective alignment method, and differential gene expression analysis was conducted. Subsequently, a meta-analysis was performed to select differentially expressed genes across datasets. Based on the differentially expressed genes discovered by meta-analysis, we constructed a protein-to-protein interaction network, and we identified biological pathways and processes related to high-dose IR effects. Our findings suggest that cell cycle arrest is activated, supported by our top down-regulated genes associated with cell cycle activation. DNA repair genes are down-regulated in their majority. However, several genes implicated in the nucleotide excision repair pathway are upregulated. Nevertheless, apoptotic mechanisms seem to be activated probably due to severe high-dose-induced complex DNA damage. The significant upregulation of CDKN1A, as a downstream gene of TP53, further validates programmed cell death. Finally, down-regulation of TIMELESS, signifies a correlation between IR response and circadian rhythm. Nonetheless, high-dose IR exposure effects regarding normal tissue (radiation toxicity) and its possible long-term outcomes should be studied to a greater extend.

APA, Harvard, Vancouver, ISO, and other styles

48

Zubcevic, Jasenka, Ashley Baker, and Christopher J. Martyniuk. "Transcriptional networks in rodent models support a role for gut-brain communication in neurogenic hypertension: a review of the evidence." Physiological Genomics 49, no. 7 (July 1, 2017): 327–38. http://dx.doi.org/10.1152/physiolgenomics.00010.2017.

Full text

Abstract:

Hypertension (HTN) is the most prevalent condition observed in primary health care. Hypertension shows complex etiology, and neuroinflammation, overactive sympathetic drive, and the microbiome are each associated with the disease. To obtain mechanistic perspective into neurogenic HTN, we first constructed a framework for transcriptional regulators of the disease using the Comparative Toxicogenomics Database. This approach yielded a core group of 178 transcripts that are prevalent in studies of HTN, including leptin and neuropeptide Y. We then conducted a meta-analysis for transcriptome data generated in brain tissue from HTN studies. Eight expression studies were reanalyzed, in which transcriptomics was conducted in hypertensive animal models [spontaneously hypertensive rats (SHR) and high blood pressure (BPH/2J) Schlager mice] (140 microarrays). Most strikingly, a gut-brain connection was a dominant theme in both rodent models of HTN. The transcriptomic data in the rat CNS converged on processes that included gastrointestinal motility and appetite, among others. In the mouse model, pathways converged on gastrointestinal transit. Thus, our data provide a powerful review of current molecular evidence of the interplay between gut and brain in HTN. Analyses of meta-genome data also suggested that transcriptome networks related to natriuresis, thermoregulation, reproduction (lactation and pregnancy), and vasoconstriction were associated to HTN, supporting physiological observations in independent studies by others. Lastly, we present novel transcriptome networks that may contribute to a neurogenic origin of HTN. Using this framework, new therapeutic targets can be proposed and investigated in treatment strategies.

APA, Harvard, Vancouver, ISO, and other styles

49

Cho, Seong Beom. "Uncovering Oncogenic Mechanisms of Tumor Suppressor Genes in Breast Cancer Multi-Omics Data." International Journal of Molecular Sciences 23, no. 17 (August 25, 2022): 9624. http://dx.doi.org/10.3390/ijms23179624.

Full text

Abstract:

Tumor suppressor genes (TSGs) are essential genes in the development of cancer. While they have many roles in normal cells, mutation and dysregulation of the TSGs result in aberrant molecular processes in cancer cells. Therefore, understanding TSGs and their roles in the oncogenic process is crucial for prevention and treatment of cancer. In this research, multi-omics breast cancer data were used to identify molecular mechanisms of TSGs in breast cancer. Differentially expressed genes and differentially coexpressed genes were identified in four large-scale transcriptomics data from public repositories and multi-omics data analyses of copy number, methylation and gene expression were performed. The results of the analyses were integrated using enrichment analysis and meta-analysis of a p-value summation method. The integrative analysis revealed that TSGs have a significant relationship with genes of gene ontology terms that are related to cell cycle, genome stability, RNA processing and metastasis, indicating the regulatory mechanisms of TSGs on cancer cells. The analysis frame and research results will provide valuable information for the further identification of TSGs in different types of cancers.

APA, Harvard, Vancouver, ISO, and other styles

50

Lu, Yuanping, Renjun Yang, Nuoya Yin, and Francesco Faiola. "In vivo and in vitro transcriptomics meta-analyses reveal that BPA may affect TGF-beta signaling regardless of the toxicology system employed." Environmental Pollution 285 (September 2021): 117472. http://dx.doi.org/10.1016/j.envpol.2021.117472.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Journal articles on the topic 'Meta-transcriptomics'

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles