Multiomics analysis provides insights into musk secretion in muskrat and musk deer.

IF 11.8 2区 生物学 Q1 MULTIDISCIPLINARY SCIENCES
Tao Wang, Maosen Yang, Xin Shi, Shilin Tian, Yan Li, Wenqian Xie, Zhengting Zou, Dong Leng, Ming Zhang, Chengli Zheng, Chungang Feng, Bo Zeng, Xiaolan Fan, Huimin Qiu, Jing Li, Guijun Zhao, Zhengrong Yuan, Diyan Li, Hang Jie
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引用次数: 0

Abstract

Background: Musk, secreted by the musk gland of adult male musk-secreting mammals, holds significant pharmaceutical and cosmetic potential. However, understanding the molecular mechanisms of musk secretion remains limited, largely due to the lack of comprehensive multiomics analyses and available platforms for relevant species, such as muskrat (Ondatra zibethicus Linnaeus) and Chinese forest musk deer (Moschus berezovskii Flerov).

Results: We generated chromosome-level genome assemblies for the 2 species of muskrat (Ondatra zibethicus Linnaeus) and musk deer (Moschus berezovskii Flerov), along with 168 transcriptomes from various muskrat tissues. Comparative analysis with 11 other vertebrate genomes revealed genes and amino acid sites with signs of adaptive convergent evolution, primarily linked to lipid metabolism, cell cycle regulation, protein binding, and immunity. Single-cell RNA sequencing in muskrat musk glands identified increased acinar/glandular epithelial cells during secretion, highlighting the role of lipometabolism in gland development and evolution. Additionally, we developed MuskDB (http://muskdb.cn/home/), a freely accessible multiomics database platform for musk-secreting mammals.

Conclusions: The study concludes that the evolution of musk secretion in muskrats and musk deer is likely driven by lipid metabolism and cell specialization. This underscores the complexity of the musk gland and calls for further investigation into musk secretion-specific genetic variants.

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来源期刊
GigaScience
GigaScience MULTIDISCIPLINARY SCIENCES-
CiteScore
15.50
自引率
1.10%
发文量
119
审稿时长
1 weeks
期刊介绍: GigaScience seeks to transform data dissemination and utilization in the life and biomedical sciences. As an online open-access open-data journal, it specializes in publishing "big-data" studies encompassing various fields. Its scope includes not only "omic" type data and the fields of high-throughput biology currently serviced by large public repositories, but also the growing range of more difficult-to-access data, such as imaging, neuroscience, ecology, cohort data, systems biology and other new types of large-scale shareable data.
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