Budd Alyssa M, Mayne Benjamin, Berry Oliver, Jarman Simon
School of Biological Sciences, The University of Western Australia, Perth, Western Australia, Australia.
Environomics Future Science Platform, Indian Ocean Marine Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Crawley, Western Australia, Australia.
Mol Ecol Resour. 2025 Jul;25(5):e13774. doi: 10.1111/1755-0998.13774. Epub 2023 Mar 19.
Lifespan is a key attribute of a species' life cycle and varies extensively among major lineages of animals. In fish, lifespan varies by several orders of magnitude, with reported values ranging from less than 1 year to approximately 400 years. Lifespan information is particularly useful for species management, as it can be used to estimate invasion potential, extinction risk and sustainable harvest rates. Despite its utility, lifespan is unknown for most fish species. This is due to the difficulties associated with accurately identifying the oldest individual(s) of a given species, and/or deriving lifespan estimates that are representative for an entire species. Recently it has been shown that CpG density in gene promoter regions can be used to predict lifespan in mammals and other vertebrates, with variable accuracy across taxa. To improve accuracy of lifespan prediction in a non-mammalian vertebrate group, here we develop a fish-specific genomic lifespan predictor. Our new model includes more than eight times the number of fish species included in the previous vertebrate model (n = 442) and uses fish-specific gene promoters as reference sequences. The model predicts fish lifespan from genomic CpG density alone (measured as CpG observed/expected ratio), explaining 64% of the variance between known and predicted lifespans. The predictions are highly robust to variation in genome quality and are applicable to all classes of fish; a taxonomically diverse and speciose group. The results demonstrate the value of promoter CpG density as a universal predictor of fish lifespan that can applied where empirical data are unavailable, or impracticable to obtain.
寿命是物种生命周期的一个关键属性，在动物的主要谱系中差异很大。在鱼类中，寿命相差几个数量级，报道的数值范围从不到1年到约400年。寿命信息对于物种管理特别有用，因为它可用于估计入侵潜力、灭绝风险和可持续捕捞率。尽管其有用性，但大多数鱼类物种的寿命尚不清楚。这是由于难以准确识别给定物种中最年长的个体，和/或得出代表整个物种的寿命估计值。最近有研究表明，基因启动子区域的CpG密度可用于预测哺乳动物和其他脊椎动物的寿命，不同分类群的预测准确性各不相同。为了提高非哺乳动物脊椎动物群体寿命预测的准确性，我们在此开发了一种鱼类特异性基因组寿命预测器。我们的新模型所包含的鱼类物种数量是先前脊椎动物模型（n = 442）的八倍多，并使用鱼类特异性基因启动子作为参考序列。该模型仅根据基因组CpG密度（以观察到的/预期的CpG比率衡量）预测鱼类寿命，解释了已知寿命和预测寿命之间64%的差异。这些预测对基因组质量的变化具有高度稳健性，适用于所有鱼类类别；鱼类是一个分类多样且物种丰富的群体。结果表明，启动子CpG密度作为鱼类寿命的通用预测指标具有重要价值，可应用于无法获得或难以获得实证数据的情况。
