文献类型： 外文期刊

作者： Wang, Meiyue ¹ ; Li, Zijuan ⁴ ; Wang, Haoyu ⁵ ; Zhao, Junwei ¹ ; Zhang, Yuyun ⁴ ; Lin, Kande ⁶ ; Zheng, Shusong ⁷ ; Feng, Yilong ⁶ ; Zhang, Yu'e ⁷ ; Teng, Wan ⁸ ; Tong, Yiping ⁸ ; Zhang, Wenli ⁶ ; Xue, Yongbiao ⁷ ; Mao, Hude ⁹ ; Li, Hao ⁵ ; Zhang, Bo ¹⁰ ; Rasheed, Awais ¹¹ ; Bhavani, Sridhar ¹³ ; Liu, Chenghong ³ ; Ling, Hong-Qing ⁷ ; Hu, Yue-Qing ² ; Zhang, Yijing ² ;

作者机构： 1.Beijing Life Sci Acad, Beijing, Peoples R China

2.Fudan Univ, Sch Life Sci, Collaborat Innovat Ctr Genet & Dev, State Key Lab Genet Engn,Inst Plant Biol,Dept Bioc, Shanghai 200438, Peoples R China

3.Shanghai Acad Agr Sci, Biotechnol Res Inst, Shanghai Key Lab Agr Genet & Breeding, Shanghai 201106, Peoples R China

4.Chinese Acad Sci, Shanghai Inst Plant Physiol & Ecol, Shanghai Inst Biol Sci, CAS Ctr Excellence Mol Plant Sci,Natl Key Lab Plan, Shanghai 200032, Peoples R China

5.Henan Univ, Coll Agr, Sch Life Sci, State Key Lab Crop Stress Adaptat & Improvement, Kaifeng 475004, Henan, Peoples R China

6.Nanjing Agr Univ, Natl Key Lab Crop Genet & Germplasm Enhancement &, CIC MCP, Nanjing 210095, Jiangsu, Peoples R China

7.Chinese Acad Sci, Inst Genet & Dev Biol, State Key Lab Plant Cell & Chromosome Engn, Beijing 100101, Peoples R China

8.Chinese Acad Sci, Inst Genet & Dev Biol, Beijing 100101, Peoples R China

9.Northwest A&F Univ, Coll Agron, State Key Lab Crop Stress Resistance & High Effici, Yangling 712100, Shaanxi, Peoples R China

10.Chinese Acad Sci, Northwest Inst Plateau Biol, Key Lab Adaptat & Evolut Plateau Biota, Xining 81008, Qinghai, Peoples R China

11.Quaid I Azam Univ, Dept Plant Sci, Islamabad 45320, Pakistan

12.CAAS, Int Maize & Wheat Improvement Ctr CIMMYT, China Off, Beijing 100081, Peoples R China

13.Int Maize & Wheat Improvement Ctr CIMMYT, Km 45,Carretera Mexico Veracruz, Texcoco 56237, E Do De Mexico, Mexico

14.Yazhouwan Natl Lab, Sanya 572025, Hainan, Peoples R China

关键词： pgDQ; scRNA-seq; allopolyploid; subgenome diversity; evo-devo

期刊名称：MOLECULAR BIOLOGY AND EVOLUTION （ 影响因子：5.3； 五年影响因子：11.9 ）

ISSN： 0737-4038

年卷期： 2024 年 41 卷 9 期

页码：

收录情况： SCI

摘要： Polyploidization drives regulatory and phenotypic innovation. How the merger of different genomes contributes to polyploid development is a fundamental issue in evolutionary developmental biology and breeding research. Clarifying this issue is challenging because of genome complexity and the difficulty in tracking stochastic subgenome divergence during development. Recent single-cell sequencing techniques enabled probing subgenome-divergent regulation in the context of cellular differentiation. However, analyzing single-cell data suffers from high error rates due to high dimensionality, noise, and sparsity, and the errors stack up in polyploid analysis due to the increased dimensionality of comparisons between subgenomes of each cell, hindering deeper mechanistic understandings. In this study, we develop a quantitative computational framework, called "pseudo-genome divergence quantification" (pgDQ), for quantifying and tracking subgenome divergence directly at the cellular level. Further comparing with cellular differentiation trajectories derived from single-cell RNA sequencing data allows for an examination of the relationship between subgenome divergence and the progression of development. pgDQ produces robust results and is insensitive to data dropout and noise, avoiding high error rates due to multiple comparisons of genes, cells, and subgenomes. A statistical diagnostic approach is proposed to identify genes that are central to subgenome divergence during development, which facilitates the integration of different data modalities, enabling the identification of factors and pathways that mediate subgenome-divergent activity during development. Case studies have demonstrated that applying pgDQ to single-cell and bulk tissue transcriptomic data promotes a systematic and deeper understanding of how dynamic subgenome divergence contributes to developmental trajectories in polyploid evolution.