首次组装的高海拔自交单倍体单倍型基因组(Rhododendron nivale subsp.

IF 11.8 2区 生物学 Q1 MULTIDISCIPLINARY SCIENCES
Zhen-Yu Lyu, Xiong-Li Zhou, Si-Qi Wang, Gao-Ming Yang, Wen-Guang Sun, Jie-Yu Zhang, Rui Zhang, Shi-Kang Shen
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引用次数: 0

摘要

背景:Rhododendron nivale subsp. boreale Philipson et M. N. Philipson 是一种具有观赏价值的高山木本物种,是海拔 4,200 米以上山地灌丛生境中的主要物种。尽管其生态学意义重大,但基因组资源的缺乏阻碍了对其在高海拔山区环境中的进化和适应特征的全面了解:nivale subsp. boreale的基因组进行了测序和组装,这是杜鹃花亚属的第一个基因组,也是第一个高海拔木本开花四倍体,为高山木本植物群提供了重要的基因组资源。该组配包括 52 个假染色体(支架 N50 = 42.93 Mb;BUSCO = 98.8%;QV = 45.51;S-AQI = 98.69),分属 4 个单倍型,包含 127,810 个预测的蛋白编码基因。联合 k-mer 分析、共线性评估和系统发育调查证实了自四倍体的身份。比较基因组分析表明,R. nivale亚种起源于R. nivale的新多倍体,经历了两轮古老的多倍体事件。转录表达分析表明,等位基因之间的表达差异很常见,并且随机分布在基因组中。我们发现了扩展的基因家族和正选择的特征,它们不仅参与了对山顶生态系统的适应(对压力的反应和发育调节),还参与了自交四倍体的繁殖(减数分裂的稳定)。此外,(第七组乙烯响应因子转录因子)ERF VIIs 的表达水平明显高于全球基因的平均表达水平。我们怀疑这些变化使该物种在高海拔地区获得了成功:我们组装了首个高海拔自多倍体基因组,并在杜鹃花亚属中实现了染色体组水平的组装。此外,我们还合理推测了北海道杜鹃亚种的高海拔适应策略。该研究为探索高山山顶适应性以及极端环境与物种多倍体化之间的相关性提供了宝贵的数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The first high-altitude autotetraploid haplotype-resolved genome assembled (Rhododendron nivale subsp. boreale) provides new insights into mountaintop adaptation.

Background: Rhododendron nivale subsp. boreale Philipson et M. N. Philipson is an alpine woody species with ornamental qualities that serve as the predominant species in mountainous scrub habitats found at an altitude of ∼4,200 m. As a high-altitude woody polyploid, this species may serve as a model to understand how plants adapt to alpine environments. Despite its ecological significance, the lack of genomic resources has hindered a comprehensive understanding of its evolutionary and adaptive characteristics in high-altitude mountainous environments.

Findings: We sequenced and assembled the genome of R. nivale subsp. boreale, an assembly of the first subgenus Rhododendron and the first high-altitude woody flowering tetraploid, contributing an important genomic resource for alpine woody flora. The assembly included 52 pseudochromosomes (scaffold N50 = 42.93 Mb; BUSCO = 98.8%; QV = 45.51; S-AQI = 98.69), which belonged to 4 haplotypes, harboring 127,810 predicted protein-coding genes. Conjoint k-mer analysis, collinearity assessment, and phylogenetic investigation corroborated autotetraploid identity. Comparative genomic analysis revealed that R. nivale subsp. boreale originated as a neopolyploid of R. nivale and underwent 2 rounds of ancient polyploidy events. Transcriptional expression analysis showed that differences in expression between alleles were common and randomly distributed in the genome. We identified extended gene families and signatures of positive selection that are involved not only in adaptation to the mountaintop ecosystem (response to stress and developmental regulation) but also in autotetraploid reproduction (meiotic stabilization). Additionally, the expression levels of the (group VII ethylene response factor transcription factors) ERF VIIs were significantly higher than the mean global gene expression. We suspect that these changes have enabled the success of this species at high altitudes.

Conclusions: We assembled the first high-altitude autopolyploid genome and achieved chromosome-level assembly within the subgenus Rhododendron. In addition, a high-altitude adaptation strategy of R. nivale subsp. boreale was reasonably speculated. This study provides valuable data for the exploration of alpine mountaintop adaptations and the correlation between extreme environments and species polyploidization.

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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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