Scientific criteria and guidelines for identifying, reporting and interpreting omics data – transcriptomics, proteomics, metabolomics and lipidomics – in meat science research

Omics approaches offer a rapidly expanding and highly valuable means to study meat science research questions associated with on-farm and post-farm activities. To help ensure the reliability, reproducibility, and transparency of these methodologies, this paper provides practical recommendations for identifying, reporting and interpreting transcriptomics, proteomics, metabolomics, and lipidomics studies in meat research with a focus on best practices regarding the experimental designs, data analysis, and interpretation of the results. Rather than restricting methodological innovation, these guidelines aim to establish recommended scientific criteria that enhance reproducibility, facilitate the integration of independently generated omics datasets through standardized reporting, compatible metadata and transparent analytical workflows among studies submitted to Meat Science journal. Although individual technologies continue to evolve, adherence to the key principles and criteria will substantially improve the scientific soundness and long-term impact of omics generated data applied to meat science research.

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Publication Details

Journal
Meat Science
Published
2026-11-06
DOI
https://doi.org/10.1016/j.meatsci.2026.110250
Primary Topic
Meat and Animal Product Quality
Type
article
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article

Scientific criteria and guidelines for identifying, reporting and interpreting omics data – transcriptomics, proteomics, metabolomics and lipidomics – in meat science research

Marjeta Čandek‐Potokar, Eric N. Ponnampalam, David Edwin Gerrard, Thierry Astruc et al.
Meat Science
Meat and Animal Product Quality
article

Scientific criteria and guidelines for identifying, reporting and interpreting omics data – transcriptomics, proteomics, metabolomics and lipidomics – in meat science research

Marjeta Čandek‐Potokar, Eric N. Ponnampalam, David Edwin Gerrard, Thierry Astruc, Flores Monica, Mohammed Gagaoua, Peter Purslow, Wangang Zhang
article en

Abstract

Omics approaches offer a rapidly expanding and highly valuable means to study meat science research questions associated with on-farm and post-farm activities. To help ensure the reliability, reproducibility, and transparency of these methodologies, this paper provides practical recommendations for identifying, reporting and interpreting transcriptomics, proteomics, metabolomics, and lipidomics studies in meat research with a focus on best practices regarding the experimental designs, data analysis, and interpretation of the results. Rather than restricting methodological innovation, these guidelines aim to establish recommended scientific criteria that enhance reproducibility, facilitate the integration of independently generated omics datasets through standardized reporting, compatible metadata and transparent analytical workflows among studies submitted to Meat Science journal. Although individual technologies continue to evolve, adherence to the key principles and criteria will substantially improve the scientific soundness and long-term impact of omics generated data applied to meat science research.

Meat ScienceVol. 244
Nanjing Agricultural University (CN), The University of Melbourne (AU), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage (FR), Instituto de Agroquímica y Tecnología de Alimentos (ES), Agricultural institute of Slovenia (SI), L'Institut Agro (FR), Qualité des Produits Animaux (FR), Virginia Tech (US)
Zero hunger
Openalex Percentile: Top 15%
Meat and Animal Product Quality
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