A novel RT‐qPCR health assay reveals differential expression of stress and immunoregulatory genes between the seasonal migrations of humpback whales (Megaptera novaeangliae)

生物 鲸脂 基因表达 瘦素 小鼠苗条素受体 微阵列 人口 基因 动物 遗传学 内分泌学 肥胖 人口学 社会学
作者
Jacob M. J. Linsky,Rebecca A. Dunlop,Lee McMichael
出处
期刊:Molecular Ecology [Wiley]
卷期号:33 (2)
标识
DOI:10.1111/mec.17209
摘要

Abstract Health information is essential for the conservation management of whale species. However, assessing the health of free‐ranging whales is challenging as samples are primarily limited to skin and blubber tissue. Reverse transcription quantitative polymerase chain reaction (RT‐qPCR) offers a method to measure health from blubber RNA, providing insights into energetic status, stress and immune activity. To identify changes in health, natural differences in baseline gene expression linked to an individual's sex, reproductive status and life‐history stage must first be quantified. This study aimed to establish baseline gene expression indices of health in migrating humpback whales ( Megaptera novaeangliae ). To do this, we developed an assay to quantify seven health‐related gene transcripts (Leptin, Leptin Receptor, Adiponectin, Aryl Hydrocarbon Receptor, Tumour Necrosis Factor‐α, Interleukin‐6, Heat Shock Protein‐70) and used Bayesian mixed effect models to assess differential baseline expression based on sex, lactation status and migration stage (northbound to and southbound from the annual breeding grounds). Results showed no significant contribution of sex to differential baseline expression. However, lactating individuals exhibited downregulated AhR and HSP‐70 compared to non‐lactating conspecifics. Additionally, southbound individuals demonstrated significantly upregulated HSP‐70 and downregulated TNF‐alpha, suggesting a relationship between these inflammation‐linked transcripts and migratory fasting. Our results suggest that baseline differences due to migratory stage and lactation status should be considered in health applications of this assay. Future monitoring efforts can use our baseline measurements to better understand how gene expression is tied to population‐level impacts, such as reduced prey availability or migratory stressors.
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