大豆泛基因组研究进展

doi:10.16288/j.yczz.23-321

遗传 ›› 2024, Vol. 46 ›› Issue (3): 183-198.doi: 10.16288/j.yczz.23-321

大豆泛基因组研究进展

刘羽诚¹(), 申妍婷¹, 田志喜¹^,²()

1.中国科学院遗传与发育生物学研究所，种子创新重点实验室，北京 100101
2.中国科学院大学，北京 101408

收稿日期:2023-12-29 修回日期:2024-02-09 出版日期:2024-03-20 发布日期:2024-02-22
通讯作者: 田志喜 E-mail:ychliu@genetics.ac.cn;zxtian@genetics.ac.cn
作者简介:刘羽诚，副研究员，研究方向：大豆比较基因组学。E-mail: ychliu@genetics.ac.cn。2016—2020年就读于中国科学院遗传与发育生物学研究所，在田志喜课题组攻读博士学位；2021—2023年在该课题组开展博士后工作；2023年至今任中国科学院遗传与发育生物学研究所副研究员，从事大豆功能基因组学、比较基因组学、大数据挖掘与数据库开发相关研究。博士期间，开展大豆泛基因组工作，完成26个大豆种质的高质量参考基因组，在植物中创造性实践了图泛基因组构建策略，系统阐释了染色体结构变异在大豆演化/驯化过程中的作用，为后续泛基因组研究提供了经典的思路和范例。获得“博士后创新人才计划”、“中国科学院稳定支持青年团队”项目资助；主持国家自然科学基金委青年科学基金项目。博士论文《大豆泛基因组研究》荣获2023年中国科学院优秀博士生论文。
基金资助:
国家自然科学基金项目(32201775);国家自然科学基金项目(U22A20473);中国科学院稳定支持青年团队计划(YSBR-078)

Frontiers of soybean pan-genome studies

Yucheng Liu¹(), Yanting Shen¹, Zhixi Tian¹^,²()

1. Key Laboratory of Seed Innovation, Institute of Genetics and Development of Biology, Chinese Academy of Sciences, Beijing 100101, China
2. University of Chinese Academy of Sciences, Beijing 101408, China

Received:2023-12-29 Revised:2024-02-09 Published:2024-03-20 Online:2024-02-22
Contact: Zhixi Tian E-mail:ychliu@genetics.ac.cn;zxtian@genetics.ac.cn
Supported by:
National Natural Science Foundation of China(32201775);National Natural Science Foundation of China(U22A20473);CAS Project for Young Scientists in Basic Research(YSBR-078)

摘要/Abstract

摘要：

人工驯化为农业发展提供了原始驱动力，也深刻地改变了许多动植物的遗传背景。伴随组学大数据理论和技术体系的发展，作物基因组研究已迈入泛基因组时代。借助泛基因组的研究思路，通过多基因组间的比较和整合，能够评估物种遗传信息上界和下界，认知物种的遗传多样性全貌。此外，将泛基因组与染色体大尺度结构变异、群体高通量测序及多层次组学数据相结合，可以进行更为深入的性状-遗传机制解析。大豆(Glycine max (L.) Merr.)是重要的粮油经济作物，大豆产能关乎国家粮食安全。对大豆遗传背景形成、重要农艺性状关键位点的解析，是实现更高效的大豆育种改良的前提。本文首先对泛基因组学的核心问题进行了阐述，解释了从头组装/比对组装、迭代式组装和图基因组等泛基因组研究策略的演变历程和各自特征；接着对作物泛基因组研究的热点问题进行了概括，并且以大豆为例详细阐释了包括类群选择、泛基因组构建、数据挖掘等方面在内的泛基因组研究的开展思路，着重说明染色体结构变异在大豆演化/驯化历程中的贡献及其在农艺性状遗传基础挖掘上的价值；最后讨论了图泛基因组在数据整合、结构变异计算方面的应用前景。本文对作物泛基因组未来的发展趋势进行了展望，以期为作物基因组学及数据科学研究提供参考。

关键词: 大豆, 泛基因组, 结构变异, 演化, 驯化

Abstract:

Artificial domestication provided the original motivation to the blooming of agriculture, following with the dramatic change of the genetic background of crops and livestock. According to theory and technology upgradation that contributing to the omics, we appreciate using the pan-genome instead of single reference genome for crop study. By comparison and integration of multiple genomes under the guidance of pan-genome theory, we can estimate the genomic information range of a species, leading to a global understanding of its genetic diversity. Combining pan-genome with large size chromosomal structural variations, high throughput population resequencing, and multi-omics data, we can profoundly study the genetic basis behind species traits we focus on. Soybean is one of the most important commercial crops over the world. It is also essential to our food security. Dissecting the formation of genetic diversity and the causal loci of key agricultural traits of soybean will make the modern soybean breeding more efficiently. In this review, we summarize the core idea of pan-genome and clarified the characteristics of construction strategies of pan-genome such as de novo/mapping assembly, iterative assembly and graph-based genome. Then we used the soybean pan-genome work as a case study to introduce the general way to study pan-genome. We highlighted the contribution of structural variation (SV) to the evolution/domestication of soybean and its value in understanding the genetic bases of agronomy traits. By those, we approved the value of graph-based pan-genome for data integration and SV calculation. Future research directions are also discussed for crop genomics and data science.

Key words: soybean, pan-genome, structural variation, evolution, domestication

刘羽诚, 申妍婷, 田志喜. 大豆泛基因组研究进展[J]. 遗传, 2024, 46(3): 183-198.

Yucheng Liu, Yanting Shen, Zhixi Tian. Frontiers of soybean pan-genome studies[J]. Hereditas(Beijing), 2024, 46(3): 183-198.

图/表 2

表1

植物泛基因组研究实例汇总"

类群	发表年份	样品数	测序方式	泛基因组构建策略	参考文献
拟南芥(Arabidopsis thaliana)	2011	18	二代测序	迭代组装+从头组装	[33]
野生大豆(Glycine soja)	2014	7	二代测序	从头组装	[17]
甘蓝(Brassica oleracea)	2016	9	二代测序	迭代组装	[22]
苜蓿(Medicago truncatula)	2017	15	二代测序	从头组装	[76]
二穗短柄草(Brachypodium distachyon)	2017	54	二代测序	从头组装	[16]
水稻(Oryza sativa)	2018	3010	二代测序+三代测序	比对组装	[21]
野生及栽培水稻(O. rufipogon, O. sativa)	2018	66	二代测序	比对组装	[42]
水稻属及亲缘物种(Oryza, Leersia)	2018	13	三代测序+二代测序	从头组装	[18]
辣椒属(Capsicum)	2018	168	二代测序	比对组装	[77]
芝麻(Sesamum indicum)	2018	5	二代测序	比对组装	[78]
番茄及野生亲缘种(Solanum section Lycopersicon)	2019	725	二代测序	比对组装	[19]
向日葵(Helianthus annuus)	2019	287	二代测序	比对组装	[20]
油菜(Brassica napus)	2020	8	三代测序	从头组装	[43]
野生及栽培大豆(Glycine subgenus Soja)	2020	29	三代测序	从头组装+图基因组	[39]
大麦(Hordeum vulgare)	2020	20	二代测序+三代测序	从头组装	[79]
番茄及野生亲缘种(Solanum section Lycopersicon)	2020	14	二代测序+三代测序	比对组装(泛结构变异)	[45]
鹰嘴豆(Cicer arietinum)	2021	3366	二代测序	比对组装	[80]
棉花及亲缘种(Gossypium)	2021	1961	二代测序	比对组装	[81]
野生及栽培高粱(Sorghum bicolor)	2021	13	三代测序	从头组装	[82]
玉米(Zea may)	2021	26	三代测序	从头组装	[83]
水稻(O. sativa)	2021	33	三代测序	从头组装+图基因组	[34]
野生及栽培萝卜(Raphanus)	2021	11	三代测序	从头组装+图基因组	[84]
黄瓜 (Cucumis sativus)	2022	12	三代测序	从头组装+图基因组	[38]
水稻属(Oryza)	2022	251	三代测序	从头组装+图基因组	[85]
棉花属(Gossypium)	2022	10	三代测序	从头组装+图基因组	[86]
多年生大豆(Glycine subgenus Glycine)	2022	6	三代测序	从头组装	[62]
野生及栽培马铃薯(Solanum section Petota)	2022	44	三代测序	从头组装	[87]
番茄(Solanum lycopersicum)	2022	32	三代测序	从头组装+图基因组	[35]
野生及栽培谷子(Setaria)	2023	110	三代测序	从头组装+图基因组	[40]
茶(Camellia sinensis)	2023	22	三代测序	从头组装+图基因组	[41]
柑橘属(Citrus)	2023	12	三代测序	从头组装+图基因组	[36]
番茄及野生亲缘种(Solanum section Lycopersicon)	2023	13	三代测序	从头组装+图基因组	[85]
玉米(Z. mays)	2023	12	三代测序	从头组装	[88]
野生及栽培黍(Panicum miliaceum)	2023	32	三代测序	从头组装+图基因组	[46]

表1

图1

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