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<p>The growing wealth of single-cell omics datasets presents unprecedented opportunities to uncover new insights into temporal gene dynamics during development. However, this relies on accessible, diverse time-series data and robust <i>in-silico</i> analysis methods—resources that are underutilized in current databases. Herein, we present TEDD 2.0 (<a href="https://tedd.obg.cuhk.edu.hk/">https://tedd.obg.cuhk.edu.hk/</a>), an enhanced version of our Temporal Expression during Development Database, featuring advanced <i>in-silico</i> tools to characterize developmental lineages, investigate functional roles of temporally regulated genes, and compare developmental mechanisms across diverse species and life stages. This database integrates over 15 million cells from nine species, spanning 81 tissue-types and 42 time points, with three new analytical modules offered through an easy-to-use interface with dedicated cloud-based computational resources: (i) virtual gene knockout to assess transcriptome-wide responses to gene perturbation and their functional consequences; (ii) cross-species integration which minimizes species and data batch effects to reveal evolutionarily conserved and divergent temporal gene expression patterns; and (iii) trajectory inference and marker gene analysis to infer developmental lineages and detect marker genes relevant in cell fates decisions. Overall, this database provides researchers with a powerful platform to explore the temporal expression patterns of target genes, decipher finer regulation of developmental mechanisms, and guide both research design and discovery across development.</p>

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TEDD 2.0: an advanced temporal gene expression database enabled by in-silico functional analyses for developmental mechanism investigation

  • 期刊论文

  • 发表日期：

    2025年11月26日

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  • Chi Chun Chan,
  • King Kin Lam,
  • Lin Chen,
  • Mingyang Yu,
  • Jingwen Hu,
  • Yujie Zhu,
  • Yuting Zheng,
  • Jia Zheng,
  • Kwong Wai Choy,
  • Zirui Dong

摘要

The growing wealth of single-cell omics datasets presents unprecedented opportunities to uncover new insights into temporal gene dynamics during development. However, this relies on accessible, diverse time-series data and robust in-silico analysis methods—resources that are underutilized in current databases. Herein, we present TEDD 2.0 (https://tedd.obg.cuhk.edu.hk/), an enhanced version of our Temporal Expression during Development Database, featuring advanced in-silico tools to characterize developmental lineages, investigate functional roles of temporally regulated genes, and compare developmental mechanisms across diverse species and life stages. This database integrates over 15 million cells from nine species, spanning 81 tissue-types and 42 time points, with three new analytical modules offered through an easy-to-use interface with dedicated cloud-based computational resources: (i) virtual gene knockout to assess transcriptome-wide responses to gene perturbation and their functional consequences; (ii) cross-species integration which minimizes species and data batch effects to reveal evolutionarily conserved and divergent temporal gene expression patterns; and (iii) trajectory inference and marker gene analysis to infer developmental lineages and detect marker genes relevant in cell fates decisions. Overall, this database provides researchers with a powerful platform to explore the temporal expression patterns of target genes, decipher finer regulation of developmental mechanisms, and guide both research design and discovery across development.