近日，中國農(nóng)業(yè)科學院深圳農(nóng)業(yè)基因組研究所（嶺南現(xiàn)代農(nóng)業(yè)科學與技術(shù)廣東省實驗室深圳分中心）聯(lián)合山西農(nóng)業(yè)大學、崖州灣國家實驗室等單位在《自然通訊（Nature Communications）》上在線發(fā)表了題為“GWAS meta-analysis using a graph-based pan-genome enhanced gene mining efficiency for agronomic traits in rice”的研究論文。該研究通過整合7765份水稻種質(zhì)資源，基于圖形泛基因組的meta-GWAS分析，顯著提高了水稻種質(zhì)資源群體中挖掘關(guān)鍵產(chǎn)量相關(guān)基因的效率。這一成果不僅為大規(guī)模水稻種質(zhì)資源利用提供了新的工具和思路，也為水稻高產(chǎn)分子設(shè)計育種提供了新的重要基因資源。

豐富的水稻種質(zhì)資源中積累了大量可以用來提高產(chǎn)量性狀的優(yōu)異自然變異。產(chǎn)量性狀是復(fù)雜變異控制的復(fù)雜性狀。目前對種質(zhì)資源遺傳變異尤其是復(fù)雜變異的解析尚不夠深入，這一現(xiàn)狀限制了產(chǎn)量性狀相關(guān)基因的深入挖掘，進而影響了其在育種中的應(yīng)用。圍繞該科學問題，團隊前期開展了深入系統(tǒng)的工作，包括：基于全球水稻核心種質(zhì)資源，構(gòu)建了基因組充分注釋的水稻圖形泛基因組（Shang et al., Cell Research, 2022）和日本晴完整參考基因組（Shang et al., Molecular Plant, 2023），提高了復(fù)雜變異鑒定的準確度。基于泛基因組并深入解析了轉(zhuǎn)座子變異（Li et al., National Science Review, 2024）、倒位變異（He et al., Science Bulletin, 2024）和著絲粒序列變異（Lv et al., Journal of Integrative Plant Biology, 2023）等復(fù)雜結(jié)構(gòu)變異對產(chǎn)量相關(guān)基因的影響，挖掘到了qTGW1.2a等多個產(chǎn)量新基因，為水稻種質(zhì)資源挖掘和功能基因組研究提供了新平臺。同時，突破了二等位GWAS挖掘產(chǎn)量基因傳統(tǒng)研究方法的局限性，基于復(fù)等位變異GWAS挖掘到產(chǎn)量新基因TRGW6，以遺傳學實驗證明了復(fù)等位變異對產(chǎn)量性狀有獨立于二等位變異的劑量調(diào)控效應(yīng)，并實現(xiàn)了產(chǎn)量性狀的精準個性化設(shè)計（He et al., Nature Communications, 2024）。未被充分挖掘的產(chǎn)量稀有變異可能攜帶獨特的遺傳信息，在水稻高產(chǎn)性狀調(diào)控中發(fā)揮重要作用。常見變異僅能解釋部分遺傳力，稀有等位基因的協(xié)同作用可能成為找回“遺傳力缺失”的關(guān)鍵。團隊前期基于10548份水稻資源進行了包含結(jié)構(gòu)變異的稀有變異挖掘，并深入挖掘了產(chǎn)量等性狀多個基因的稀有優(yōu)異等位基因型，為水稻高產(chǎn)優(yōu)異自然變異挖掘提供了新的重要資源（Wang et al., Nucleic Acids Research, 2023）。

在本研究中，為了進一步克服傳統(tǒng)GWAS方法對群體結(jié)構(gòu)和樣本量的敏感性，以及在低頻變異分析和微效基因挖掘方面的局限性，進而整合更多大規(guī)模數(shù)據(jù)資源，實現(xiàn)對超大規(guī)模群體的高效基因挖掘。研究團隊采用meta-GWAS策略，整合來自6個不同種質(zhì)資源群體的7765份水稻種質(zhì)資源基因型和表型數(shù)據(jù)，挖掘產(chǎn)量相關(guān)新基因。基于圖形泛基因組，共鑒定了6,604,898個單核苷酸多態(tài)性和42,879個結(jié)構(gòu)變異。通過對6個群體開展獨立GWAS分析，并進一步整合進行meta分析，共鑒定出156個與關(guān)鍵農(nóng)藝性狀相關(guān)的遺傳位點，其中116個僅能通過meta-GWAS鑒定得到，顯著提高了QTL的檢測能力和遺傳力的解釋率。在此基礎(chǔ)上，成功挖掘了水稻粒寬和粒長性狀相關(guān)的新基因GW10.2和GL11，并通過分子遺傳學實驗進行了功能驗證。本研究為水稻種質(zhì)資源的高效深入挖掘和遺傳改良提供了新的思路和工具，也為水稻高產(chǎn)分子設(shè)計育種提供了寶貴的基因資源。

圖1 基于meta-GWAS高效深入挖掘水稻產(chǎn)量重要性狀相關(guān)基因

基因組所（大鵬灣實驗室）商連光研究員和崖州灣國家實驗室錢前院士為論文的共同通訊作者。基因組所（大鵬灣實驗室）和山西農(nóng)業(yè)大學聯(lián)培碩士研究生楊龍波、基因組所（大鵬灣實驗室）賀文闖副研究員、福建省農(nóng)業(yè)科學院朱義旺副研究員和已畢業(yè)博士生呂陽（現(xiàn)浙江省農(nóng)科院）為論文共同第一作者。感謝華南農(nóng)業(yè)大學的薛紅衛(wèi)教授為本研究提供的寶貴建議。該研究得到國家自然科學基金基礎(chǔ)科學中心、中國農(nóng)業(yè)科學院科技創(chuàng)新工程科學中心和中國農(nóng)科院青年創(chuàng)新專項資金資助。該工作得到了基因組所、中國水稻研究所和崖州灣科技城超級計算平臺的支持。

原文鏈接：https://www.nature.com/articles/s41467-025-58081-1

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