Chromosome-level echidna genome illuminates evolution of multiple sex chromosome system in monotremes.

IF 11.8 2区生物学 Q1 MULTIDISCIPLINARY SCIENCES GigaScience Pub Date : 2025-01-06 DOI:10.1093/gigascience/giae112

Yang Zhou, Jiazheng Jin, Xuemei Li, Gregory Gedman, Sarah Pelan, Arang Rhie, Chuan Jiang, Olivier Fedrigo, Kerstin Howe, Adam M Phillippy, Erich D Jarvis, Frank Grutzner, Qi Zhou, Guojie Zhang

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引用次数: 0

Abstract

Background: A thorough analysis of genome evolution is fundamental for biodiversity understanding. The iconic monotremes (platypus and echidna) feature extraordinary biology. However, they also exhibit rearrangements in several chromosomes, especially in the sex chromosome chain. Therefore, the lack of a chromosome-level echidna genome has limited insights into genome evolution in monotremes, in particular the multiple sex chromosomes complex.

Results: Here, we present a new long reads-based chromosome-level short-beaked echidna (Tachyglossus aculeatus) genome, which allowed the inference of chromosomal rearrangements in the monotreme ancestor (2n = 64) and each extant species. Analysis of the more complete sex chromosomes uncovered homology between 1 Y chromosome and multiple X chromosomes, suggesting that it is the ancestral X that has undergone reciprocal translocation with ancestral autosomes to form the complex. We also identified dozens of ampliconic genes on the sex chromosomes, with several ancestral ones expressed during male meiosis, suggesting selective constraints in pairing the multiple sex chromosomes.

Conclusion: The new echidna genome provides an important basis for further study of the unique biology and conservation of this species.

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来源期刊

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.