您好,欢迎访问中国农业科学院 机构知识库!

Cotton2035: From genomics research to optimized breeding

文献类型: 外文期刊

作者: Wang, Kun 1 ; He, Shoupu 2 ; Zhu, Yuxian 1 ;

作者机构: 1.Wuhan Univ, Coll Life Sci, Wuhan 430072, Peoples R China

2.Chinese Acad Agr Sci, State Key Lab Cotton Biobreeding & Integrated Util, Inst Cotton Res, Anyang 455000, Peoples R China

3.Wuhan Univ, Inst Adv Studies, Wuhan 430072, Peoples R China

4.Hubei Hongshan Lab, Wuhan 430072, Peoples R China

5.Wuhan Univ, Taikang Ctr Life & Med Sci, Wuhan 430072, Peoples R China

6.Chinese Acad Agr Sci, Natl Nanfan Res Inst Sanya, Sanya 572000, Hainan, Peoples R China

关键词: cotton genomics; cotton ENCODE project; cotton breeding; genomics-to-breeding (G2B)

期刊名称:MOLECULAR PLANT ( 影响因子:24.1; 五年影响因子:25.8 )

ISSN: 1674-2052

年卷期: 2025 年 18 卷 2 期

页码:

收录情况: SCI

摘要: Cotton is the world's most important natural fiber crop and serves as an ideal model for studying plant genome evolution, cell differentiation, elongation, and cell wall biosynthesis. The first draft genome assembly for Gossypium raimondii, completed in 2012, marked the beginning of global efforts in studying cotton genomics. Over the past decade, the cotton research community has continued to assemble and refine the genomes for both wild and cultivated Gossypium species. With the accumulation of de novo genome assemblies and resequencing data across virous cotton populations, significant progress has been made in uncovering the genetic basis of key agronomic traits. Achieving the goal of cotton genomics-to-breeding (G2B) will require a deeper understanding of the spatiotemporal regulatory mechanisms involved in genome information storage and expression. We advocate for a cotton ENCODE project to systematically decode the functional elements and regulatory networks within the cotton genome. Technological advances, particularly on single-cell sequencing and high-resolution spatiotemporal omics, will be essential for elucidating these regulatory mechanisms. By integrating multi-omics data, genome editing tools, and artificial intelligence, these efforts will empower the genomics-driven strategies needed for future cotton G2B breeding.

  • 相关文献
作者其他论文 更多>>