Disentangling plant response to biotic and abiotic stress using HIVE, a novel tool to perform unpaired multi-transcriptomics integration DOI Creative Commons

Giulia Calia,

Sophia Marguerit,

Ana Paula Zotta Mota

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: March 5, 2024

Abstract All organisms are subjected to multiple stresses usually occurring at the same time, requiring activation of appropriate signalling pathways respond all or by prioritizing response one stress factor. Plants, as sessile organisms, particularly impacted constantly changing environment that is often unfavourable even hostile. Because experimental complexity studying organism stressors simultaneously, experiments conducted considering individual factor time. An alternative consists in performing silico integration those data on single response. Currently used methods integrate unpaired consist meta-analysis finding differentially expressed genes for each condition separately and then selecting commonly regulated ones. Although these approaches allowed find valuable results, they mainly identify specific signatures very few signature responding lack modulated differently condition. For this purpose, we developed HIVE (Horizontal Integration analysis using Variational AutoEncoders) single-stress transcriptomics datasets composed experiments. Briefly, coupled a variational autoencoder, alleviates batch effects, with random forest regression SHAP explainer select relevant specifically stresses. We illustrate functionality study transcriptional changes several different plants namely Arabidopsis thaliana , rice, maize, wheat, grapevine peanut collecting publicly available stress, either biotic and/or abiotic, jointly analyse them. performed better than differential expression analysis, state-of-the-art tool horizontal allowing novel promising candidates responsible triggering effective defence responses

Language: Английский

Introduction to multi-omics technology DOI

Eiman I. Ahmed,

Muzafar A. Macha, Ajaz A. Bhat

et al.

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 12

Published: Jan. 1, 2025

Language: Английский

Citations

0
Integrative analysis of serum proteomics and transcriptomics in hepatitis C DOI Creative Commons

Jianqiong Wang,

Andong Xia, Min Tang

et al.

Virology Journal, Journal Year: 2025, Volume and Issue: 22(1)

Published: March 13, 2025

Hepatitis C is a contagious disease caused by infection with the hepatitis virus (HCV) through blood and mother-to-child routes. This study intends to characterize serum molecular features of using proteomics transcriptomics. Ctrl (normal population), HCV (population previous infection), chronic (patients persistent infection) groups were set up, expression profiles proteomes transcriptomes samples identified TMT RNA-seq. Bioinformatics was applied perform enrichment analysis PPI network construction differentially expressed proteins/genes (DEPs/DEGs). RT-qPCR western blot verified differences DEPs/DEGs. Compared group, group had 356 DEPs in serum; compared 381 serum. are predominantly immunoglobulins exosomal proteins that regulate carbon dioxide transport, initiation transcription, immune responses, bacterial viral infections. HSPA4, HSPD1, COPS5, PSMD2 TCP1 key HCV-associated DEPs. The 684 DEGs 350 group. primarily encode extracellular matrix wound healing, cellular communication, oxidative stress, cell adhesion, infection, immunity. KIF11, CENPE, TTK, CDC20 ASPM HCV-related hub genes DEGs. Combined analyses revealed interactions between DEGs, especially EIF4A3, MNAT1, UBE2D1. Moreover, patterns EIF2B1, SNRNP70, UBE2D1 DEPs/DEGs from Ctrl, HCV, consistent sequencing results. involved process pathogenesis, they may be potential biomarkers for treatment patients C.

Language: Английский

Citations

0
The Identification of Novel Therapeutic Biomarkers in Rheumatoid Arthritis: A Combined Bioinformatics and Integrated Multi-Omics Approach DOI Open Access
Muhammad Hamza Tariq, Dia Advani,

Buttia Mohamed Almansoori

et al.

International Journal of Molecular Sciences, Journal Year: 2025, Volume and Issue: 26(6), P. 2757 - 2757

Published: March 19, 2025

Rheumatoid arthritis (RA) is a multifaceted autoimmune disease that marked by complex molecular profile influenced an array of factors, including genetic, epigenetic, and environmental elements. Despite significant advancements in research, the precise etiology RA remains elusive, presenting challenges developing innovative therapeutic markers. This study takes integrated multi-omics approach to uncover novel markers for RA. By analyzing both transcriptomics epigenomics datasets, we identified common gene candidates span these two omics levels patients diagnosed with Remarkably, discovered eighteen multi-evidence genes (MEGs) are prevalent across epigenomics, twelve which have not been previously linked directly The bioinformatics analyses MEGs revealed they part tightly interconnected protein–protein interaction networks related RA-associated KEGG pathways ontology terms. Furthermore, exhibited direct interactions miRNAs RA, underscoring their critical role disease’s pathogenicity. Overall, this comprehensive opens avenues identifying new candidate empowering researchers validate efficiently through experimental studies. advancing our understanding can pave way more effective therapies improved patient outcomes.

Language: Английский

Citations

0
Precision or Personalized Nutrition: A Bibliometric Analysis DOI Open Access
Daniel Hinojosa-Nogueira, Alba Subiri-Verdugo, Cristina Diaz-Perdigones

et al.

Nutrients, Journal Year: 2024, Volume and Issue: 16(17), P. 2922 - 2922

Published: Sept. 1, 2024

Food systems face the challenge of maintaining adequate nutrition for all populations. Inter-individual responses to same diet have made precision or personalized (PN) an emerging and relevant topic. The aim this study is analyze evolution PN field, identifying principal actors topics, providing a comprehensive overview. Therefore, bibliometric analysis scientific research available through Web Science (WOS) database was performed, revealing 2148 papers up June 2024. VOSviewer WOS platform were employed processing analysis, included evaluation diverse data such as country, author most frequent keywords, among others. revealed period exponential growth from 2015 2023, with USA, Spain, England top contributors. field “Nutrition Dietetics” particularly significant, comprising nearly 33% total publications. highly cited institutions are universities Tufts, College Dublin, Navarra. relationship between nutrition, genetics, omics sciences, along dietary intervention studies, has been defining factor in PN. In conclusion, represents promising significant potential further advancement growth.

Language: Английский

Citations

2
Omics Analysis Unveils the Pathway Involved in the Anthocyanin Biosynthesis in Tomato Seedling and Fruits DOI Open Access
Rui He, Kaizhe Liu, Shuchang Zhang

et al.

International Journal of Molecular Sciences, Journal Year: 2023, Volume and Issue: 24(10), P. 8690 - 8690

Published: May 12, 2023

The purple tomato variety 'Indigo Rose' (InR) is favored due to its bright appearance, abundant anthocyanins and outstanding antioxidant capacity. SlHY5 associated with anthocyanin biosynthesis in plants. However, residual still present Slhy5 seedlings fruit peel indicated there was an induction pathway that independent of HY5 molecular mechanism formation mutants unclear. In this study, we performed omics analysis clarify the regulatory network underlying seedling mutant. Results showed total amount both InR significantly higher than those mutant, most genes exhibited expression levels InR, suggesting play pivotal roles flavonoid fruit. Yeast two-hybrid (Y2H) results revealed SlBBX24 physically interacts SlAN2-like SlAN2, while SlWRKY44 could interact SlAN11 protein. Unexpectedly, SlPIF1 SlPIF3 were found SlBBX24, SlAN1 SlJAF13 by yeast assay. Suppression virus-induced gene silencing (VIGS) retarded coloration peel, indicating important role regulation accumulation. These deepen understanding color fruits HY5-dependent or manner via excavating involved based on analysis.

Language: Английский

Citations

6
Host genetics and gut microbiota synergistically regulate feed utilization in egg-type chickens DOI Creative Commons
Wenxin Zhang, Fangren Lan, Qianqian Zhou

et al.

Journal of Animal Science and Biotechnology/Journal of animal science and biotechnology, Journal Year: 2024, Volume and Issue: 15(1)

Published: Sept. 9, 2024

Language: Английский

Citations

2
Cross-omics strategies and personalised options for lung cancer immunotherapy DOI Creative Commons

Yalan Yan,

Siyi Shen,

Jiamin Li

et al.

Frontiers in Immunology, Journal Year: 2024, Volume and Issue: 15

Published: Sept. 25, 2024

Lung cancer is one of the most common malignant tumours worldwide and its high mortality rate makes it a leading cause cancer-related deaths. To address this daunting challenge, we need comprehensive understanding pathogenesis progression lung in order to adopt more effective therapeutic strategies. In regard, integrating multi-omics data provides highly promising avenue. Multi-omics approaches such as genomics, transcriptomics, proteomics, metabolomics have become key tools study cancer. The application these methods not only helps resolve immunotherapeutic mechanisms cancer, but also theoretical basis for development personalised treatment plans. By multi-omics, gained process progression, discovered potential immunotherapy targets. This review summarises studies on immunology explores early diagnosis, selection prognostic assessment with aim providing options patients.

Language: Английский

Citations

2
SignalingProfiler2.0: a network-based approach to bridge multi-omics data to phenotypic hallmarks DOI Creative Commons
Veronica Venafra, Francesca Sacco, Livia Perfetto

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 29, 2024

Abstract Unraveling the cellular signaling remodeling upon a perturbation is fundamental challenge to understand disease mechanisms and identify potential drug targets. In this pursuit, computational tools that generate mechanistic hypotheses from multi-omics data have invaluable potential. Here we present SignalingProfiler 2.0, multi-step pipeline systematically derive context-specific models by integrating proteogenomic with prior knowledge-causal networks. This freely accessible flexible tool incorporates statistical, footprint-based, graph algorithms accelerate integration interpretation of data. Through benchmarking rigorous parameter selection on proof-of-concept study, performed in metformin-treated breast cancer cells, demonstrate tool’s ability hierarchical network recapitulates novel known drug-perturbed phenotypic outcomes. summary, S ignalingProfiler 2.0 addresses emergent need biologically relevant information complex extracting interpretable

Language: Английский

Citations

1
Bioinformatics Databases and Tools for Analysis of Multi-omics DOI

Chung Anh Pham,

Anh Dao Ngo,

Nhat Le Bui

et al.

Published: Jan. 1, 2024

The development of molecular biological techniques and omic research recently, especially sequencing, has led to a huge amount data, including information on DNA, RNA, proteins, metabolites. Due their close relationship, investigating multiple layers which is called multi-omics, preferred the single-omic approach describe comprehensive understanding these biomolecules linkage several diseases. Bioinformatics an effective indispensable for biologic scientists translate data into biologically meaning conclusions. We present general overview multi-omics its applications in human microbiomes this chapter. Moreover, we also discuss role technology, particularly bioinformatics, analyzing multi-omic data. Several popular bioinformatics tools databases analysis have been presented. With potential initial results, machine learning artificial intelligence are predicted play important analysis. Although like sequences gene/protein or gene expression available, database integration still challenge needs further development.

Language: Английский

Citations

1
nipalsMCIA: Flexible Multi-Block Dimensionality Reduction in R via Non-linear Iterative Partial Least Squares DOI Creative Commons

Max Mattessich,

Joaquin Reyna, E Aron

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: June 10, 2024

Abstract Motivation With the increased reliance on multi-omics data for bulk and single cell analyses, availability of robust approaches to perform unsupervised analysis clustering, visualization, feature selection is imperative. Joint dimensionality reduction methods can be applied datasets derive a global sample embedding analogous single-omic techniques such as Principal Components Analysis (PCA). Multiple co-inertia (MCIA) method joint that maximizes covariance between block- global-level embeddings. Current implementations MCIA are not optimized large those arising from studies, lack capabilities with respect new data. Results We introduce nipalsMCIA , an implementation solves objective function using extension Non-linear Iterative Partial Least Squares (NIPALS), shows significant speed-up over earlier rely eigendecompositions It also removes dependence eigendecomposition calculating variance explained, allows users out-of-sample provides variety pre-processing parameter options, well ease functionality down-stream global-embedding factors. Availability available BioConductor package at https://bioconductor.org/packages/release/bioc/html/nipalsMCIA.html includes detailed documentation application vignettes. Supplementary Materials online.

Language: Английский

Citations

1