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多组学整合网络: 一把精准解码玉米功能基因组的钥匙

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  • 中国农业大学, 植物生理学与生物化学国家重点实验室, 国家玉米改良中心, 北京 100193

收稿日期: 2022-12-05

  录用日期: 2022-12-13

  网络出版日期: 2022-12-29

基金资助

国家自然科学基金(32025027)

Multi-omics Integrative Network Map, a Key to Accurately Deco-ding the Maize Functional Genomics

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  • State Key Laboratory of Plant Physiology and Biochemistry, National Maize Improvement Center of China, China Agricultural University, Beijing 100193, China

Received date: 2022-12-05

  Accepted date: 2022-12-13

  Online published: 2022-12-29

摘要

高通量组学技术的快速发展使生命科学进入大数据时代。科学家们从基因组、转录组、蛋白质组和代谢组等多组学数据中剥茧抽丝, 逐步揭示生物体内复杂而巧妙的调控网络。近日, 华中农业大学李林课题组联合杨芳课题组和严建兵课题组构建了玉米(Zea mays)首个多组学整合网络。该网络包括3万个玉米基因在三维基因组水平、转录水平、翻译水平和蛋白质互作水平的调控关系, 由280万个网络连接组成, 构成1 412个调控模块。利用该整合网络, 研究团队预测并证实了5个调控玉米分蘖、侧生器官发育和籽粒皱缩的新基因。进一步结合机器学习方法, 他们预测出2 651个影响玉米开花期的候选基因, 鉴定到8条可能参与玉米开花期的调控通路, 并利用基因编辑技术和EMS突变体证实了20个候选基因的生物学功能。此外, 通过对整合调控网络的进化分析, 他们发现玉米两套亚基因组在转录组、翻译组和蛋白互作组水平上存在渐进式的功能分化。这套集合多组学数据构建的整合网络图谱是玉米功能基因组学研究的重大进展, 为玉米重要性状新基因克隆、分子调控通路解析和玉米基因组进化分析提供了新工具, 是解锁玉米功能基因组学的一把新钥匙。

本文引用格式

郭丽, 王雪涵, 田丰 . 多组学整合网络: 一把精准解码玉米功能基因组的钥匙[J]. 植物学报, 2023 , 58(1) : 1 -5 . DOI: 10.11983/CBB22271

Abstract

Life science is entering into the era of big data due to the rapid development of high-throughput omics technology. Multi-omics data such as genome, transcriptome, proteome, metabolome have greatly facilitated dissecting the complex and sophisticated regulatory networks of organisms. Recently, a collaborative team led by Lin Li, Fang Yang and Jianbing Yan from Huazhong Agricultural University constructed the first multi-omics integrative network map of maize. This map comprises over 30 000 genes and 2.8 million network edges at the levels of genome, transcriptome, translatome, and proteome, finally forming 1 412 regulatory modules. Using the integrative network map, the research team successfully predicted and confirmed five new functional genes regulating the development of tiller, lateral organ, and kernel in maize. Based on the integrative map and machine learning, the research team identified 2 651 maize flowering time genes that are enriched in eight candidate subnetworks. The biological functions of 20 flowering candidate genes were further validated using CRISPR/Cas9 gene editing technology and EMS mutants. Furthermore, evolutionary analysis of the integrative network map showed that the two subgenomes of maize had undergone a progressive functional differentiation from the levels of co-expression, co-translation to interactome. The construction of the multi-omics integrative network map represents an important breakthrough in maize functional genomics, which provides a new tool for cloning new genes, identifying novel molecular regulatory pathways, and revealing maize genome evolutionary features. This multi-omics integrative network map is a new key to decode maize functional genomics.

参考文献

[1] 汪海, 赖锦盛, 王海洋, 李新海 (2022). 作物智能设计育种——自然变异的智能组合和人工变异的智能创制. 中国农业科技导报 24(6), 1-8.
[2] 王向峰, 才卓 (2019). 中国种业科技创新的智能时代——“玉米育种4.0”. 玉米科学 27, 1-9.
[3] Chen Q, Li W, Tan L, Tian F (2021). Harnessing knowledge from maize and rice domestication for new crop breeding. Mol Plant 14, 9-26.
[4] Doebley J, Stec A, Hubbard L (1997). The evolution of apical dominance in maize. Nature 386, 485-488.
[5] Dong ZB, Li W, Unger-Wallace E, Yang JL, Vollbrecht E, Chuck G (2017). Ideal crop plant architecture is mediated by tassels replace upper ears1, a BTB/POZ ankyrin repeat gene directly targeted by TEOSINTE BRANCHED1. Proc Natl Acad Sci USA 114, E8656-E8664.
[6] Gallavotti A, Zhao Q, Kyozuka J, Meeley RB, Ritter MK, Doebley JF, Pè ME, Schmidt RJ (2004). The role of barren stalk1 in the architecture of maize. Nature 432, 630-635.
[7] G?lweiler L, Guan CH, Müller A, Wisman E, Mendgen K, Yephremov A, Palme K (1998). Regulation of polar auxin transport by AtPIN1 in Arabidopsis vascular tissue. Science 282, 2226-2230.
[8] Gui ST, Wei WJ, Jiang CL, Luo JY, Chen L, Wu SS, Li WQ, Wang YB, Li SY, Yang N, Li Q, Fernie AR, Yan JB (2022). A pan-Zea genome map for enhancing maize improvement. Genome Biol 23, 178.
[9] Han LQ, Zhong WS, Qian J, Jin ML, Tian P, Zhu WC, Zhang HW, Sun YH, Feng JW, Liu XG, Chen G, Farid B, Li RN, Xiong ZM, Tian ZH, Li J, Luo Z, Du DX, Chen SJ, Jin QX, Li JX, Li Z, Liang Y, Jin XM, Peng Y, Zheng C, Ye XN, Yin YJ, Chen H, Li WF, Chen LL, Li Q, Yan JB, Yang F, Li L (2022). A multi-omics integrative network map of maize. Nat Genet https://www.nature.com/articles/s41588-022-01262-1
[10] Hufford MB, Seetharam AS, Woodhouse MR, Chougule KM, Ou SJ, Liu JN, Ricci WA, Guo TT, Olson A, Qiu YJ, Della Coletta R, Tittes S, Hudson AI, Marand AP, Wei S, Lu ZY, Wang B, Tello-Ruiz MK, Piri RD, Wang N, Kim DW, Zeng YB, O’Connor CH, Li XR, Gilbert AM, Baggs E, Krasileva KV, Portwood JL II, Cannon EKS, Andorf CM, Manchanda N, Snodgrass SJ, Hufnagel DE, Jiang QH, Pedersen S, Syring ML, Kudrna DA, Llaca V, Fengler K, Schmitz RJ, Ross-Ibarra J, Yu JM, Gent JI, Hirsch CN, Ware D, Dawe RK (2021). De novo assembly, annotation, and comparative analysis of 26 diverse maize genomes. Science 373, 655-662.
[11] Liang YM, Liu HJ, Yan JB, Tian F (2021). Natural variation in crops: realized understanding, continuing promise. Annu Rev Plant Biol 72, 357-385.
[12] Matsuoka Y, Vigouroux Y, Goodman MM, Sanchez GJ, Buckler E, Doebley J (2002). A single domestication for maize shown by multilocus microsatellite genotyping. Proc Natl Acad Sci USA 99, 6080-6084.
[13] Peng Y, Xiong D, Zhao L, Ouyang WZ, Wang SQ, Sun J, Zhang Q, Guan PP, Xie L, Li WQ, Li GL, Yan JB, Li XW (2019). Chromatin interaction maps reveal genetic regulation for quantitative traits in maize. Nat Commun 10, 2632.
[14] Schnable JC, Springer NM, Freeling M (2011). Differentiation of the maize subgenomes by genome dominance and both ancient and ongoing gene loss. Proc Natl Acad Sci USA 108, 4069-4074.
[15] Tu XY, Mejía-Guerra MK, Valdes Franco JA, Tzeng D, Chu PY, Shen W, Wei YY, Dai XR, Li PH, Buckler ES, Zhong SL (2020). Reconstructing the maize leaf regulatory network using ChIP-seq data of 104 transcription factors. Nat Commun 11, 5089.
[16] Walley JW, Sartor RC, Shen ZX, Schmitz RJ, Wu KJ, Urich MA, Nery JR, Smith LG, Schnable JC, Ecker JR, Briggs SP (2016). Integration of omic networks in a developmental atlas of maize. Science 353, 814-818.
[17] Wen WW, Jin M, Li K, Liu HJ, Xiao YJ, Zhao MC, Alseekh S, Li WQ, de Abreu e Lima F, Brotman Y, Willmitzer L, Fernie AR, Yan JB (2018). An integrated multi-layered analysis of the metabolic networks of different tissues uncovers key genetic components of primary metabolism in maize. Plant J 93, 1116-1128.
[18] Whipple CJ, Kebrom TH, Weber AL, Yang F, Hall D, Meeley R, Schmidt R, Doebley J, Brutnell TP, Jackson DP (2011). grassy tillers1 promotes apical dominance in maize and responds to shade signals in the grasses. Proc Natl Acad Sci USA 108, E506-E512.
[19] Xiao YG, Guo JY, Dong ZB, Richardson A, Patterson E, Mangrum S, Bybee S, Bertolini E, Bartlett M, Chuck G, Eveland AL, Scanlon MJ, Whipple C (2022). Boundary domain genes were recruited to suppress bract growth and promote branching in maize. Sci Adv 8, m6835.
[20] Xu XS, Crow M, Rice BR, Li F, Harris B, Liu L, Demesa-Arevalo E, Lu ZF, Wang LY, Fox N, Wang XF, Drenkow J, Luo AD, Char SN, Yang B, Sylvester AW, Gingeras TR, Schmitz RJ, Ware D, Lipka AE, Gillis J, Jackson D (2021). Single-cell RNA sequencing of developing maize ears facilitates functional analysis and trait candidate gene discovery. Dev Cell 56, 557-568.
[21] Yang F, Lei YY, Zhou ML, Yao QL, Han YC, Wu X, Zhong WS, Zhu CH, Xu WZ, Tao R, Chen X, Lin D, Rahman K, Tyagi R, Habib Z, Xiao SB, Wang D, Yu Y, Chen HC, Fu ZF, Cao G (2018). Development and application of a recombination-based library versus library high-throughput yeast two-hybrid (RLL-Y2H) screening system. Nucleic Acids Res 46, e17.
[22] Zhu WC, Xu J, Chen SJ, Chen J, Liang Y, Zhang CJ, Li Q, Lai JS, Li L (2021). Large-scale translatome profiling annotates the functional genome and reveals the key role of genic 3' untranslated regions in translatomic variation in plants. Plant Commun 2, 100181.
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