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<p>Shrimp aquaculture is a key industry in global aquaculture, contributing to high-quality nutrition, food security, and economic development. However, environmental changes driven by climate change and pathogenic infections are among the challenges that negatively affect shrimp supply and economic growth. Transcriptomic approaches, particularly RNA sequencing (RNA-seq), have been widely applied to investigate molecular features of shrimp stress responses to abiotic and biotic stressors by identifying differentially expressed genes (DEGs). However, these technologies impose a limit on the molecular interactions among the identified DEGs. Molecular interaction information is essential, as most biological processes function through groups of interacting genes rather than a single gene. Thus, this review aims to explore the potential of network analysis approaches for available transcriptomic datasets to understand the mechanisms of shrimp stress responses. This review provides an overview of current progress in shrimp transcriptomics and highlights available network approaches, i.e., protein–protein interaction (PPI), gene co-expression, and gene regulatory networks, that can be integrated with the transcriptomic data. Relevant databases and tools are outlined to provide available sources for network construction and analysis. A framework for network analysis of a transcriptomic dataset was presented to illustrate how network approaches can be used to identify genes and associated biological functions involved in shrimp stress responses. The future directions and challenges of integrating network analysis into shrimp research are also discussed for the way forward. This review demonstrates that network-integrated transcriptomics can provide a systems-level understanding of shrimp responses to stress, assisting in improving shrimp aquaculture production.</p>

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Network perspectives on transcriptomic datasets to understand shrimp response mechanisms to environmental and pathogenic stresses: a review

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月24日

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  • Noorul Darlina Edlin Abd Rahim,
  • Nor Azlan Nor Muhammad,
  • Khor Waiho,
  • Sarahani Harun,
  • Rabiatul-Adawiah Zainal-Abidin,
  • Min Pau Tan,
  • Yeong Yik Sung,
  • Zeti-Azura Mohamed-Hussein,
  • Nor Afiqah-Aleng

摘要

Shrimp aquaculture is a key industry in global aquaculture, contributing to high-quality nutrition, food security, and economic development. However, environmental changes driven by climate change and pathogenic infections are among the challenges that negatively affect shrimp supply and economic growth. Transcriptomic approaches, particularly RNA sequencing (RNA-seq), have been widely applied to investigate molecular features of shrimp stress responses to abiotic and biotic stressors by identifying differentially expressed genes (DEGs). However, these technologies impose a limit on the molecular interactions among the identified DEGs. Molecular interaction information is essential, as most biological processes function through groups of interacting genes rather than a single gene. Thus, this review aims to explore the potential of network analysis approaches for available transcriptomic datasets to understand the mechanisms of shrimp stress responses. This review provides an overview of current progress in shrimp transcriptomics and highlights available network approaches, i.e., protein–protein interaction (PPI), gene co-expression, and gene regulatory networks, that can be integrated with the transcriptomic data. Relevant databases and tools are outlined to provide available sources for network construction and analysis. A framework for network analysis of a transcriptomic dataset was presented to illustrate how network approaches can be used to identify genes and associated biological functions involved in shrimp stress responses. The future directions and challenges of integrating network analysis into shrimp research are also discussed for the way forward. This review demonstrates that network-integrated transcriptomics can provide a systems-level understanding of shrimp responses to stress, assisting in improving shrimp aquaculture production.