李法計(jì),程敦公,余曉叢,聞偉鍔,劉金棟,翟勝男,劉愛(ài)峰,郭軍,曹新有,劉成,宋健民,劉建軍,李豪圣
冠層活性相關(guān)性狀全基因組關(guān)聯(lián)分析及其對(duì)產(chǎn)量性狀遺傳效應(yīng)的解析
1山東省農(nóng)業(yè)科學(xué)院作物研究所/小麥玉米國(guó)家工程研究中心/農(nóng)業(yè)農(nóng)村部黃淮北部小麥生物學(xué)與遺傳育種重點(diǎn)實(shí)驗(yàn)室/山東省小麥技術(shù)創(chuàng)新中心/濟(jì)南市小麥遺傳改良重點(diǎn)實(shí)驗(yàn)室,濟(jì)南 250100;2菏澤學(xué)院農(nóng)業(yè)與生物工程學(xué)院(牡丹學(xué)院),山東菏澤 274015;3遵義醫(yī)科大學(xué)細(xì)胞生物學(xué)教研室,貴州遵義 563099;4中國(guó)農(nóng)業(yè)科學(xué)院作物科學(xué)研究所,北京 100081
【目的】冠層活性是反映作物生長(zhǎng)發(fā)育的重要指標(biāo),發(fā)掘小麥冠層活性相關(guān)基因并分析其與產(chǎn)量性狀的關(guān)系,為解析產(chǎn)量遺傳結(jié)構(gòu)和輔助育種提供理論支撐。【方法】以166份國(guó)內(nèi)外小麥品種為材料,將其種植于河南安陽(yáng)和安徽濉溪,結(jié)合已構(gòu)建的包含326 570個(gè)來(lái)源于小麥90K和660K SNP芯片標(biāo)記的高密度整合物理圖譜,對(duì)苗期和花后10 d歸一化植被指數(shù)(NDVI-S和NDVI-10)及花后10 d旗葉葉綠素含量(Chl-10)進(jìn)行關(guān)聯(lián)分析,并與前期利用相同材料得到的產(chǎn)量相關(guān)性狀結(jié)果進(jìn)行比較?!窘Y(jié)果】NDVI-S、NDVI-10和Chl-10在基因型、環(huán)境及基因型×環(huán)境互作間變異方差均達(dá)極顯著(<0.01)差異,廣義遺傳力(2)分別為0.81、0.81和0.91。分別檢測(cè)到13、12和15個(gè)與NDVI-S、NDVI-10和Chl-10顯著相關(guān)的位點(diǎn),其中,有12、11和12個(gè)為新位點(diǎn),5個(gè)位點(diǎn)與2個(gè)以上性狀有關(guān)。166份小麥品種含有NDVI-S、NDVI-10和Chl-10優(yōu)異等位基因數(shù)變幅分別為4-11、3-11和4-12,且隨著優(yōu)異等位基因數(shù)目增加其對(duì)應(yīng)表型值呈遞增趨勢(shì)。NDVI-S與千粒重、粒長(zhǎng)和粒寬顯著正相關(guān)(<0.01);Chl-10與產(chǎn)量和旗葉寬顯著正相關(guān)(<0.01),與單位面積穗數(shù)、株高和穗下節(jié)長(zhǎng)顯著負(fù)相關(guān)(<0.01)。檢測(cè)到7個(gè)同時(shí)與產(chǎn)量和冠層活性相關(guān)的多效性位點(diǎn)?!窘Y(jié)論】NDVI-S可用于品種產(chǎn)量性狀的選擇,檢測(cè)到的穩(wěn)定位點(diǎn)和多效性位點(diǎn)可在開(kāi)發(fā)標(biāo)記后用于育種材料的檢測(cè)。
小麥;冠層活性;產(chǎn)量;歸一化植被指數(shù);葉綠素含量;關(guān)聯(lián)分析
【研究意義】高產(chǎn)是小麥育種永恒的目標(biāo)。作物冠層活性主要受綠色植被覆蓋度、葉綠素(chlorophyll,Chl)含量、蒸騰速率和光合速率等相關(guān)性狀影響,是表征作物群體活力的重要性狀,也是作物高產(chǎn)形成的重要基礎(chǔ)。歸一化植被指數(shù)(normalized difference vegetation index,NDVI)是反映作物地上部綠色植被覆蓋度的重要參數(shù)之一,被廣泛應(yīng)用于不同時(shí)期及水肥處理下小麥群體冠層活性研究[1-8]。葉綠素是植物進(jìn)行光合作用的重要色素,灌漿期葉片Chl含量可直接影響小麥光合速率和灌漿速率[9]。發(fā)掘小麥NDVI和Chl相關(guān)基因并分析其與產(chǎn)量性狀的關(guān)系,是解析產(chǎn)量形成機(jī)理、進(jìn)行高產(chǎn)分子遺傳改良的重要途徑?!厩叭搜芯窟M(jìn)展】前人將灌漿期NDVI相關(guān)QTL(quantitative trait locus)定位在2D、3A、4A、4B、4D、5A、5B、6A和6B染色體上[10-11],將苗期NDVI相關(guān)QTL定位在1B、5A和7B染色體上[12],將灌漿期旗葉Chl含量相關(guān)QTL定位在1B、2A、2B、2D、3A、3B、4A、4B、4D、5A、6A、6B和6D染色體上[11-22]。此外,前期利用3個(gè)RIL群體結(jié)合小麥90K SNP芯片對(duì)產(chǎn)量和冠層活性相關(guān)性狀進(jìn)行了QTL定位,分別檢測(cè)到6、16和14個(gè)與苗期NDVI(NDVI-S)、花后10 d NDVI(NDVI-10)和花后10 d旗葉Chl(Chl-10)含量相關(guān)的QTL,其中,有6、10和10個(gè)為新QTL;將冠層活性相關(guān)性狀QTL與產(chǎn)量性狀QTL位點(diǎn)進(jìn)行比較,檢測(cè)到12個(gè)同時(shí)包含冠層活性和產(chǎn)量相關(guān)性狀QTL位點(diǎn)的區(qū)段[23-24]。【本研究切入點(diǎn)】目前,利用自然群體進(jìn)行關(guān)聯(lián)分析發(fā)掘冠層活性相關(guān)位點(diǎn)的研究報(bào)道較少,冠層活性與產(chǎn)量相關(guān)性狀表型和基因型關(guān)系的研究也較為缺乏?!緮M解決的關(guān)鍵問(wèn)題】本研究以166份國(guó)內(nèi)外小麥品種為材料,結(jié)合已構(gòu)建的包含小麥90K和660K SNP芯片的高密度整合物理圖譜,對(duì)冠層活性相關(guān)性狀NDVI-S、NDVI-10和Chl-10進(jìn)行全基因組關(guān)聯(lián)分析,發(fā)掘相關(guān)遺傳位點(diǎn)。同時(shí),結(jié)合前期研究結(jié)果,從表型和基因型分析冠層活性與產(chǎn)量相關(guān)性狀的關(guān)系,為小麥高產(chǎn)分子遺傳改良提供理論支撐和基因資源。
選用166份國(guó)內(nèi)外小麥品種作為試驗(yàn)材料。其中,144份為國(guó)內(nèi)黃淮麥區(qū)主栽品種,22份為國(guó)外引進(jìn)的種質(zhì)。品種具體來(lái)源見(jiàn)Li等[25]。
將試驗(yàn)材料種植于中國(guó)農(nóng)業(yè)科學(xué)院安陽(yáng)棉花所白壁試驗(yàn)站和安徽省農(nóng)業(yè)科學(xué)院濉溪試驗(yàn)站。在白壁試驗(yàn)站2年度播種期分別為10月6日和10月4日,在濉溪試驗(yàn)站2年度播種期分別為10月10日和10月8日,田間試驗(yàn)采用隨機(jī)區(qū)組設(shè)計(jì),3行區(qū),50粒/行,均勻點(diǎn)播,行距20 cm,行長(zhǎng)2 m,3次重復(fù)。田間管理與當(dāng)?shù)卮筇锷a(chǎn)一致。
分別于播種后30 d和花后10 d,在每個(gè)小區(qū)內(nèi)選取相鄰的2行離冠層50 cm高度,利用手持式GreenSeeker(GreenSeeker, Ntech Industries, Inc, Ukiah, CA)進(jìn)行掃描,作為該品種的NDVI值;于花后10 d,在每個(gè)小區(qū)內(nèi)隨機(jī)選取10片旗葉利用手持式SPAD-502葉綠素測(cè)定儀(Minolta, Japan)進(jìn)行測(cè)定,作為該品種的Chl含量值。產(chǎn)量相關(guān)性狀調(diào)查方法見(jiàn)LI等[25]。
利用Illumina公司(http://www.illumina.com/)的90K及中國(guó)農(nóng)業(yè)科學(xué)院作物科學(xué)研究所賈繼增課題組開(kāi)發(fā)的660K SNP芯片對(duì)166份品種的DNA進(jìn)行檢測(cè)和基因型分析。SNP基因芯片檢測(cè)在北京博奧晶典生物技術(shù)有限公司(http://cn.capitalbio.com/)進(jìn)行。參照中國(guó)春參考基因組IWGSC v1.0(http://www. wheatgenome.org/)進(jìn)行本地比對(duì)(BLASTn,e<10— 20)[29],構(gòu)建整合物理圖譜[25]。利用Structure v2.3.4軟件(http://pritchardlab.stanford.edu/structure. html)[30]進(jìn)行群體結(jié)構(gòu)分析,然后利用Tassel v5.0進(jìn)行主成分分析(principal components analysis,PCA)和親緣關(guān)系分析[25]。
以位點(diǎn)間的相關(guān)系數(shù)平方(2)作為衡量多態(tài)性位點(diǎn)兩兩之間連鎖不平衡(linkage disequilibrium,LD)的參數(shù)。采用Tassel v5.0計(jì)算標(biāo)記間的LD值。由于A、B和D基因組間標(biāo)記密度差異較大,分別對(duì)A、B、D和全基因組進(jìn)行LD衰減分析[25]。
利用Tassel v5.0軟件的混合線性模型(MLM),在考慮群體結(jié)構(gòu)(Q)和親緣關(guān)系(K)的情況下,分別對(duì)NDVI-S、NDVI-10和Chl-10 3個(gè)性狀的E1—E5 5個(gè)數(shù)據(jù)集進(jìn)行GWAS分析,E1:2012—2013安陽(yáng);E2:2012—2013濉溪;E3:2013—2014安陽(yáng);E4:2013—2014濉溪;E5:E1—E4的BLUE值。根據(jù)GWAS分析結(jié)果,當(dāng)<0.001時(shí),認(rèn)為該標(biāo)記與性狀顯著關(guān)聯(lián)。GWAS分析的QQ圖(quantile-quantile plot)可表示在當(dāng)前模型下的分析效果,實(shí)際與期望的接近程度反映了該模型對(duì)群體結(jié)構(gòu)和親緣關(guān)系對(duì)GWAS分析影響的控制效果。曼哈頓圖(manhattan plot)是一種表示點(diǎn)與數(shù)值間對(duì)應(yīng)關(guān)系的散點(diǎn)圖,橫坐標(biāo)為連鎖群位置即染色體,縱坐標(biāo)為SNP標(biāo)記的負(fù)常用對(duì)數(shù):Y=-log10()。根據(jù)圖中SNP位點(diǎn)的分布可以觀察標(biāo)記與性狀的關(guān)聯(lián)程度。在2個(gè)及以上環(huán)境下(包含BLUE值)檢測(cè)到的位點(diǎn)作為顯著性位點(diǎn)[25]。
以增加表型值的等位基因作為優(yōu)異等位基因,統(tǒng)計(jì)每個(gè)品種多環(huán)境下重復(fù)被檢測(cè)到的顯著性位點(diǎn)的優(yōu)異等位基因數(shù)目。將含有不同數(shù)目?jī)?yōu)異等位基因的品種進(jìn)行分組,利用R語(yǔ)言繪制優(yōu)異等位基因數(shù)目對(duì)3個(gè)性狀表型BLUE值的效應(yīng)。
方差分析(表1)表明,NDVI-S、NDVI-10和Chl-10在基因型、環(huán)境及基因型×環(huán)境互作間變異方差均達(dá)極顯著(<0.01)差異;除NDVI-10外,NDVI-S和Chl-10在重復(fù)間變異方差達(dá)極顯著(<0.01)水平。NDVI-S、NDVI-10和Chl-10的分別為0.81、0.81和0.91,說(shuō)明遺傳因素是導(dǎo)致3個(gè)性狀變異的主要原因。
頻率分布直方圖(圖1)顯示,NDVI-S、NDVI-10和Chl-10 3個(gè)性狀表型值呈連續(xù)分布,表型值分布頻率均在變異范圍內(nèi)呈現(xiàn)先增加后降低的趨勢(shì)。3個(gè)性狀的表型值在不同品種間變異較大,環(huán)境對(duì)性狀表型值也有一定影響,性狀表型數(shù)據(jù)的平均值接近中間值。其中,NDVI-S的變異系數(shù)大于NDVI-10和Chl-10(表2)。
表1 冠層活性相關(guān)性狀的方差分析和廣義遺傳力
NDVI-S:苗期歸一化植被指數(shù);NDVI-10:花后10 d歸一化植被指數(shù);Chl-10:花后10 d旗葉葉綠素含量;**表示在0.01水平差異顯著。下同
NDVI-S: normalized difference vegetation index at seedling stage; NDVI-10: Normalized difference vegetation index at 10 days after flowering; Chl-10: Chlorophyll content in flag leaf at 10 days after flowering; ** Significant at<0.01. The same as below
圖1 NDVI-S、NDVI-10和Chl-10 BLUE值的頻率分布直方圖
表2 166份小麥品種冠層活性相關(guān)性狀的均值、標(biāo)準(zhǔn)差和變異范圍
E1:2012—2013安陽(yáng);E2:2012—2013濉溪;E3:2013—2014安陽(yáng);E4:2013—2014濉溪;E5:最佳線性無(wú)偏估計(jì)值。下同
E1: 2012-2013 Anyang; E2: 2012-2013 Suixi; E3: 2013-2014 Anyang; E4: 2013-2014 Suixi; E5: Best linear unbiased estimation. The same as below
經(jīng)過(guò)分析,共檢測(cè)到40個(gè)與NDVI-S、NDVI-10和Chl-10相關(guān)的顯著性位點(diǎn)(圖2和表3)。
檢測(cè)到13個(gè)與NDVI-S相關(guān)的顯著性位點(diǎn),分別位于1A、2A、2B、3B、4A、4B、5A、5B、5D、6B、7A和7B(2)染色體上。其中,位于3B()和4B()染色體上的位點(diǎn)均在3個(gè)環(huán)境及BLUE值下被檢測(cè)到,分別解釋表型變異的6.9%—9.8%和7.0%—11.1%。位于2B()和7B()染色體上的位點(diǎn)分別可解釋表型變異的6.9%—12.5%和6.8%—13.5%。
檢測(cè)到12個(gè)與NDVI-10相關(guān)的顯著性位點(diǎn),分別位于2A、3A、4A、5A(3)、5B(2)、5D、7A(2)和7B染色體上。其中,位于3A()和4B()染色體上的位點(diǎn)均在3個(gè)環(huán)境及BLUE值下被檢測(cè)到,分別解釋表型變異的7.3%— 13.7%和7.0%—11.5%。位于7B()染色體上的位點(diǎn)可解釋表型變異的6.7%—18.5%。
檢測(cè)到15個(gè)與Chl-10相關(guān)的顯著性位點(diǎn),分別位于1A(2)、1B(4)、2B、2D、4A(3)、5A、5B、6A和7A染色體上。其中,位于1B()、2B()、2D()、4A()、5A()和7A()染色體上的位點(diǎn)均在4個(gè)環(huán)境及BLUE值下被檢測(cè)到,分別解釋表型變異的6.9%—11.7%、6.8%—10.1%、6.9%—11.0%、6.8%—9.7%、6.5%—12.1%和6.7%— 10.3%。
在檢測(cè)到的冠層活性相關(guān)性狀顯著性位點(diǎn)中,有5個(gè)位點(diǎn)與2個(gè)或2個(gè)以上性狀有關(guān),分布在2A、4A(2)、5A和7A染色體上。其中,5A()染色體上的位點(diǎn)與NDVI-S、NDVI-10和Chl-10均顯著相關(guān);2A()和7A()染色體上的位點(diǎn)均與NDVI-S和NDVI-10顯著相關(guān)。
圖2 NDVI-S、NDVI-10和Chl-10 BLUE值的曼哈頓圖(左)和QQ圖(右)
表3 冠層活性相關(guān)性狀顯著性位點(diǎn)及與前人研究比較
a代表性標(biāo)記;bSNP標(biāo)記在中國(guó)春基因組上的物理位置;c優(yōu)異等位基因(SNP)下標(biāo)注橫線;d已報(bào)道的相關(guān)位點(diǎn)附近的QTL、標(biāo)記或基因
aRepresentative markers;bThe physical positions of SNP markers based on Chinese Spring genome sequences from the International Wheat Genome Sequencing Consortium;cFavorable allele (SNP) is underlined;dThe previously reported QTL, markers or genes near the loci identified in the present study
把增加表型值的等位基因記作優(yōu)異等位基因,NDVI-S、NDVI-10和Chl-10在166份小麥品種中優(yōu)異等位基因變異范圍分別為4—11、3—11和4—12。對(duì)含有不同等位基因數(shù)的品種的表型值分析顯示,隨著優(yōu)異等位基因數(shù)目的增加,3個(gè)性狀的表型值均呈遞增趨勢(shì)(圖3)。
圖3 優(yōu)異等位基因數(shù)目增加對(duì)NDVI-S、NDVI-10和Chl-10表型值的作用
將冠層活性相關(guān)性狀與前期研究的產(chǎn)量性狀進(jìn)行相關(guān)分析顯示,NDVI-S與千粒重(thousand-kernel weight,TKW)、粒長(zhǎng)(kernel length,KL)、粒寬(kernel width,KW)、穗干重(spike dry weight,SDW)、株高(plant height,PH)、穗下節(jié)長(zhǎng)(uppermost internode length,UIL)和旗葉長(zhǎng)(flag leaf length,F(xiàn)LL)呈顯著正相關(guān)(<0.01),與抽穗期(heading date,HD)呈顯著負(fù)相關(guān)(<0.01)(表4)[25]。NDVI-10與穗長(zhǎng)(spike length,SL)、PH和UIL呈顯著負(fù)相關(guān)(<0.01)。Chl-10與產(chǎn)量(grain yield, GY)和FLW(flag leaf width,F(xiàn)LW)顯著正相關(guān)(<0.01),與單位面積穗數(shù)(spike number per unit area,SN)、PH和UIL顯著負(fù)相關(guān)(<0.01)。
通過(guò)比較冠層活性相關(guān)位點(diǎn)與前期利用相同材料檢測(cè)到的產(chǎn)量性狀相關(guān)位點(diǎn)的關(guān)系,在1A、2A、5A(2)、5B、6B和7A染色體上檢測(cè)到7個(gè)同時(shí)與產(chǎn)量和冠層活性相關(guān)的多效性位點(diǎn)(表5)[25]。發(fā)現(xiàn)GY與NDVI-S、NDVI-10和Chl-10分別有3、3和1個(gè)位點(diǎn)一致,SL與NDVI-S、NDVI-10和Chl-10分別有2、3和3個(gè)位點(diǎn)一致,PH與NDVI-S、NDVI-10和Chl-10分別有2、3和1個(gè)位點(diǎn)一致。
近年來(lái),與小麥發(fā)育進(jìn)程相關(guān)的生理性狀基因位點(diǎn)被報(bào)道越來(lái)越多,但不同材料、檢測(cè)方法得到的位點(diǎn)差異較大。本研究在6B染色體檢測(cè)到的NDVI-S顯著性位點(diǎn)()與前期利用豆麥/石4185構(gòu)建的重組自交系群體(recombinant inbred line,RIL)檢測(cè)到的QTL()位置一致[24]。5A染色體上NDVI-10顯著相關(guān)的位點(diǎn)與前期利用臨麥2號(hào)/中892 RIL群體檢測(cè)到的QTL()位置一致[24]。Chl-10顯著性位點(diǎn)(2D)與Gao等[11]定位到的位置一致,(5A)與Liu等[21]檢測(cè)到的位點(diǎn)(5A)位置一致,(6A)與Gao等[11]、Hassan等[20]和楊等[22]分別定位到的、和位置一致。除以上位點(diǎn)外,本研究檢測(cè)到的其他冠層活性相關(guān)位點(diǎn)可能為新位點(diǎn)。另外,已報(bào)道的5A染色體上與NDVI和Chl相關(guān)的位點(diǎn)約有30個(gè),該染色體可能對(duì)調(diào)控小麥生理性狀起重要作用[11-14,16,21,24]。
表4 冠層活性相關(guān)性狀與產(chǎn)量相關(guān)性狀間的相關(guān)分析
GY:產(chǎn)量;SN:每平米穗數(shù);KNS:穗粒數(shù);TKW:千粒重;KL:粒長(zhǎng);KW:粒寬;SL:穗長(zhǎng);SDW:穗干重;HD:抽穗期;PH:株高;UIL:穗下節(jié)長(zhǎng);FLL:旗葉長(zhǎng);FLW:旗葉寬;*表示在<0.05水平差異顯著
GY: grain yield; SN: spike number per unit area; KNS: kernel number per spike; TKW: thousand-kernel weight; KL: kernel length; KW: kernel width; SL: spike length; SDW: spike dry weight; HD: heading date; PH: plant height; UIL: uppermost internode length; FLL: flag leaf length; FLW: flag leaf width; *indicate significantly different at<0.05
表5 冠層活性和產(chǎn)量相關(guān)性狀多效性位點(diǎn)
NDVI和Chl含量是表征作物綠色植被覆蓋度和光合活力的重要指標(biāo),對(duì)作物產(chǎn)量形成具有重要影響。國(guó)內(nèi)外學(xué)者在作物生長(zhǎng)過(guò)程中NDVI和Chl含量等冠層活性相關(guān)性狀與產(chǎn)量性狀的遺傳關(guān)系研究開(kāi)展了大量工作,其中,灌漿期NDVI已經(jīng)被越來(lái)越多地應(yīng)用于小麥產(chǎn)量的預(yù)測(cè)研究[1-7]。Bellundagi等[31]研究發(fā)現(xiàn),出苗后25 d地面綠色植被覆蓋率與小麥產(chǎn)量呈極顯著(<0.01)正相關(guān),相關(guān)系數(shù)達(dá)0.662,這與本研究中NDVI-S與GY相關(guān)性不高的結(jié)果存在差異。Shi等利用1個(gè)雙單倍體(doubled haploid,DH)群體進(jìn)行研究,發(fā)現(xiàn)在雨養(yǎng)條件下返青、拔節(jié)和孕穗期NDVI與產(chǎn)量均呈顯著(<0.05)或極顯著(<0.01)正相關(guān);在充分灌溉條件下,返青、拔節(jié)和孕穗期NDVI與TKW在多數(shù)環(huán)境下呈極顯著(<0.01)負(fù)相關(guān),與GY在多數(shù)環(huán)境下呈極顯著(<0.01)正相關(guān),開(kāi)花期和灌漿期旗葉Chl含量與TKW和GY呈負(fù)相關(guān),并在半數(shù)環(huán)境下達(dá)顯著(<0.05)負(fù)相關(guān)。前期利用豆麥/石4185、藁城8901/周麥16、臨麥2號(hào)/中892 3個(gè)RIL群體研究發(fā)現(xiàn),NDVI-S與TKW在3個(gè)群體中均顯著正相關(guān)(<0.01),這與本研究結(jié)果一致;Chl-10與FLW在3個(gè)群體中均顯著正相關(guān)(<0.01),與株高(PH)顯著負(fù)相關(guān)(<0.01),與本研究結(jié)果也一致[23-24]。以上研究表明,試驗(yàn)材料、環(huán)境和性狀調(diào)查時(shí)期對(duì)冠層活性相關(guān)性狀與產(chǎn)量性狀關(guān)系的影響較大,NDVI-S在遺傳群體與自然群體中與TKW相關(guān)性均較高,可用于育種材料粒重的初步選擇。
前人在冠層活性相關(guān)性狀與產(chǎn)量性狀一致性位點(diǎn)發(fā)掘方面也取得了一定成效。Hassan等[20]在2B染色體上定位到一個(gè)熱處理下與旗葉Chl含量和GY同時(shí)相關(guān)的QTL。Liu等[21]利用1個(gè)RIL群體發(fā)掘到多個(gè)旗葉Chl含量和產(chǎn)量性狀多效性位點(diǎn),其中,1D染色體上—標(biāo)記區(qū)間內(nèi)的QTL同時(shí)與灌漿中期Chl含量和GY有關(guān),3B染色體上—標(biāo)記區(qū)間內(nèi)的QTL同時(shí)與灌漿后期Chl含量和TKW有關(guān),3D染色體上—標(biāo)記區(qū)間內(nèi)的QTL同時(shí)與開(kāi)花期Chl含量和TKW有關(guān)。Shi等[12]利用DH群體,在4D染色體上發(fā)掘到1個(gè)與拔節(jié)期NDVI、灌漿期旗葉Chl含量、TKW和PH相關(guān)的QTL區(qū)段,該區(qū)段與前期利用藁城8901/周麥16和臨麥2號(hào)/中892 2個(gè)RIL群體發(fā)掘到的QTL簇位置相近,可能為作用所致[24];此外,在5A染色體上還檢測(cè)到1個(gè)與返青、拔節(jié)和孕穗期NDVI、開(kāi)花期Chl含量和TKW均相關(guān)的QTL區(qū)段。Xu等[18]利用1個(gè)RIL群體在2B、3A、5B和7B染色體上檢測(cè)到4個(gè)與旗葉Chl含量及產(chǎn)量性狀同時(shí)相關(guān)的QTL簇,其中3A和7B染色體上的QTL簇與前期利用3個(gè)RIL群體檢測(cè)到的QTL簇位置不一致[24],5B染色體上的QTL簇與本研究檢測(cè)到的多效性位點(diǎn)位置也不一致。綜上所述,NDVI和Chl含量相關(guān)位點(diǎn)與產(chǎn)量性狀相關(guān)位點(diǎn)存在部分重合現(xiàn)象,說(shuō)明NDVI和Chl含量對(duì)產(chǎn)量形成起重要作用。已報(bào)道的灌漿期Chl含量與TKW一致性位點(diǎn)較多,Chl含量可能對(duì)小麥粒重影響較大。
小麥90K和660K SNP芯片分別有64 643和229 266個(gè)SNP位于帶注釋的基因或啟動(dòng)子間隔中[32],相關(guān)性狀的顯著性位點(diǎn)可直接與基因進(jìn)行關(guān)聯(lián)。本研究將選用的166份小麥品種同時(shí)進(jìn)行了小麥90K和660K SNP芯片檢測(cè),共篩選到326 570個(gè)SNP標(biāo)記用于構(gòu)建物理圖譜和進(jìn)行關(guān)聯(lián)分析。然后將1個(gè)LD內(nèi)的顯著性標(biāo)記看作1個(gè)顯著性位點(diǎn),有效提升了位點(diǎn)的可靠性,也為相關(guān)基因發(fā)掘奠定了良好的基礎(chǔ)。本研究發(fā)現(xiàn),優(yōu)異等位基因累積可有效提高品種性狀的表型值。因此,聚合優(yōu)異等位基因是提升品種性狀表現(xiàn)和進(jìn)行遺傳改良的重要策略。與NDVI-S顯著相關(guān)的(3B)和(4B)、與NDVI-10顯著相關(guān)的(3A)和(4B)以及與Chl-10顯著相關(guān)的(1B)、(2B)、(2D)、(4A)、(5A)和(7A)位點(diǎn)穩(wěn)定性較好,以上位點(diǎn)與5個(gè)多效性位點(diǎn)可在標(biāo)記轉(zhuǎn)化后用于育種材料的檢測(cè)。
檢測(cè)到35個(gè)與小麥冠層活性相關(guān)性狀有關(guān)的新位點(diǎn),5個(gè)與2個(gè)或以上性狀有關(guān)的多效性位點(diǎn)。其中,與NDVI-S顯著相關(guān)的(3B)和(4B)、與NDVI-10顯著相關(guān)的(3A)和(4B),以及與Chl-10顯著相關(guān)的(1B)、(2B)、(2D)、(4A)、(5A)和(7A)位點(diǎn)穩(wěn)定性較好。
[1] FREEMAN K W, RAUN W R, JOHNSON G V, MULLEN R W, STONE M L, SOLIE J B. Late-season prediction of wheat grain yield and grain protein. Communications in Soil Science and Plant Analysis, 2003, 34(13/14): 1837-1852.
[2] BABAR M A, REYNOLDS M P, VAN GINKEL M, KLATT A R, RAUN W R, STONE M L. Spectral reflectance indices as a potential indirect selection criteria for wheat yield under irrigation. Crop Science, 2006, 46(2): 578-588.
[3] BABAR M A, REYNOLDS M P, VAN GINKEL M, KLATT A R, RAUN W R, STONE M L. Spectral reflectance to estimate genetic variation for in-season biomass, leaf chlorophyll, and canopy temperature in wheat. Crop Science, 2006, 46(3): 1046-1057.
[4] HAZRATKULOVA S, SHARMA R C, ALIKULOV S, ISLOMOV S, YULDASHEV T, ZIYAEV Z, KHALIKULOV Z, ZIYADULLAEV Z, TUROK J. Analysis of genotypic variation for normalized difference vegetation index and its relationship with grain yield in winter wheat under terminal heat stress. Plant Breeding, 2012, 131(6): 716-721.
[5] XIAO Y G, QIAN Z G, WU K, LIU J D, XIA X C, JI W Q, HE Z H. Genetic gains in grain yield and physiological traits of winter wheat in Shandong province, China, from 1969 to 2006. Crop Science, 2012, 52: 44-56.
[6] GAO F M, MA D Y, YIN G H, RASHEED A, DONG Y, XIAO Y G, XIA X C, WU X X, HE Z H. Genetic progress in grain yield and physiological traits in Chinese wheat cultivars of southern yellow and Huai valley since 1950. Crop Science, 2017, 57(2): 760-773.
[7] HASSAN M A, YANG M J, RASHEED A, YANG G J, REYNOLDS M, XIA X C, XIAO Y G, HE Z H. A rapid monitoring of NDVI across the wheat growth cycle for grain yield prediction using a multi-spectral UAV platform. Plant Science, 2019, 282: 95-103.
[8] 李龍, 彭智, 毛新國(guó), 王景一, 昌小平, 柳玉平, 景蕊蓮. 小麥高密度遺傳圖譜構(gòu)建及抗旱相關(guān)生理性狀的遺傳解析. 植物遺傳資源學(xué)報(bào), 2018, 19(3): 531-538.
LI L, PENG Z, MAO X G, WANG J Y, CHANG X P, LIU Y P, JING R L. Genetic map construction and genetic dissection of drought- tolerant related physiological traits in wheat. Journal of Plant Genetic Resources, 2018, 19(3): 531-538. (in Chinese)
[9] AVENSON T J, CRUZ J A, KANAZAWA A, KRAMER D M. Regulating the proton budget of higher plant photosynthesis. Proceedings of the National Academy of Sciences of the United States of America, 2005, 102(27): 9709-9713.
[10] EL-FEKI W M, BYRNE P, REID S, HALEY S. Mapping quantitative trait loci for bread making quality and agronomic traits in winter wheat under different soil moisture levels[D]. Fort Collins: Colorado State University, 2010.
[11] GAO F M, WEN W E, LIU J D, RASHEED A, YIN G H, XIA X C, WU X X, HE Z H. Genome-wide linkage mapping of QTL for yield components, plant height and yield-related physiological traits in the Chinese wheat cross Zhou 8425B/Chinese Spring. Frontiers in Plant Science, 2015, 6: 1099.
[12] SHI S K, AZAM F I, LI H H, CHANG X P, LI B Y, JING R L. Mapping QTL for stay-green and agronomic traits in wheat under diverse water regimes. Euphytica, 2017, 213(11): 246.
[13] ZHANG K P, FANG Z J, LIANG Y, TIAN J C. Genetic dissection of chlorophyll content at different growth stages in common wheat. Journal of Genetics, 2009, 88(2): 183-189.
[14] GENC Y, OLDACH K, VERBYLA A P, LOTT G, HASSAN M, TESTER M, WALLWORK H, MCDONALD G K. Sodium exclusion QTL associated with improved seedling growth in bread wheat under salinity stress. Theoretical and Applied Genetics, 2010, 121(5): 877-894.
[15] KUMAR S, SEHGAL S K, KUMAR U, VARA PRASAD P V, JOSHI A K, GILL B S. Genomic characterization of drought tolerance-related traits in spring wheat. Euphytica, 2012, 186(1): 265-276.
[16] JIA H Y, WAN H S, YANG S H, ZHANG Z Z, KONG Z X, XUE S L, ZHANG L X, MA Z Q. Genetic dissection of yield-related traits in a recombinant inbred line population created using a key breeding parent in China’s wheat breeding. Theoretical and Applied Genetics, 2013, 126(8): 2123-2139.
[17] TALUKDER S K, ALI BABAR M, VIJAYALAKSHMI K, POLAND J, PRASAD P V V, BOWDEN R, FRITZ A. Mapping QTL for the traits associated with heat tolerance in wheat (L.). BMC Genetics, 2014, 15(1): 97.
[18] XU Y F, LI S S, LI L H, MA F F, FU X Y, SHI Z L, XU H X, MA P T, AN D G. QTL mapping for yield and photosynthetic related traits under different water regimes in wheat. Molecular Breeding, 2017, 37(3): 34.
[19] BHUSAL N, SHARMA P, SAREEN S, SARIAL A K. Mapping QTLs for chlorophyll content and chlorophyll fluorescence in wheat under heat stress. Biologia Plantarum, 2018, 62(4): 721-731.
[20] HASSAN F S C, SOLOUKI M, ALI FAKHERI B, NEZHAD N M, MASOUDI B. Mapping QTLs for physiological and biochemical traits related to grain yield under control and terminal heat stress conditions in bread wheat (L.). Physiology and Molecular Biology of Plants, 2018, 24(6): 1231-1243.
[21] LIU Y X, WANG R, HU Y G, CHEN J L. Genome-wide linkage mapping of quantitative trait loci for late-season physiological and agronomic traits in spring wheat under irrigated conditions. Agronomy, 2018, 8(5): 60.
[22] 楊斌, 喬玲, 趙佳佳, 武棒棒, 溫宏偉, 張樹(shù)偉, 鄭興衛(wèi), 鄭軍. 小麥旗葉葉綠素含量的QTL定位及驗(yàn)證. 作物學(xué)報(bào), 2023, 49(3): 744-754.
YANG B, QIAO L, ZHAO J J, WU B B, WEN H W, ZHANG S W, ZHENG X W, ZHENG J. QTL mapping and validation of chlorophyll content of flag leaves in wheat (L.). Acta Agronomica Sinica, 2023, 49(3): 744-754. (in Chinese)
[23] LI F J, WEN W E, HE Z H, LIU J D, JIN H, CAO S H, GENG H W, YAN J, ZHANG P Z, WAN Y X, XIA X C. Genome-wide linkage mapping of yield related traits in three Chinese bread wheat populations using high-density SNP markers. Theoretical and Applied Genetics, 2018, 131(19): 1903-1924.
[24] LI F J, WEN W E, LIU J D, ZHAI S N, CAO X Y, LIU C, CHENG D G, GUO J, ZI Y, HAN R, WANG X L, LIU A F, SONG J M, LIU J J, LI H S, XIA X C. Genome-wide linkage mapping for canopy activity related traits using three RIL populations in bread wheat. Euphytica, 2021, 217(4): 1-16.
[25] LI F J, WEN W E, LIU J D, ZHANG Y, CAO S H, HE Z H, RASHEED A, JIN H, ZHANG C, YAN J, ZHANG P Z, WAN Y X, XIA X C. Genetic architecture of grain yield in bread wheat based on genome-wide association studies. BMC Plant Biology, 2019, 19(1): 168.
[26] LI H H, YE G Y, WANG J K. A modified algorithm for the improvement of composite interval mapping. Genetics, 2007, 175(1): 361-374.
[27] NYQUIST W E, BAKER R J. Estimation of heritability and prediction of selection response in plant populations. Critical Reviews in Plant Sciences, 1991, 10(3): 235-322.
[28] HOLLAND J, NYQUIST W, CERVANTES-MARTíNEZ C T. Estimating and interpreting heritability for plant breeding: an update. Plant Breeding Reviews, 2010, 22: 9-112.
[29] INTERNATIONAL WHEAT GENOME SEQUENCING CONSORTIUM (IWGSC). A chromosome-based draft sequence of the hexaploid bread wheat () genome. Science, 2014, 345(6194): 1251788.
[30] PRITCHARD J K, STEPHENS M, ROSENBERG N A, DONNELLY P. Association mapping in structured populations. The American Journal of Human Genetics, 2000, 67(1): 170-181.
[31] BELLUNDAGI A, SINGH G P, PRABHU K V, ARORA A, JAIN N, RAMYA P, SINGH A M, SINGH P K, AHLAWAT A. Early ground cover and other physiological traits as efficient selection criteria for grain yield under moisture deficit stress conditions in wheat (L.). Indian Journal of Plant Physiology, 2013, 18(3): 277-281.
[32] SUN C W, DONG Z D, ZHAO L, REN Y, ZHANG N, CHEN F. The Wheat 660K SNP array demonstrates great potential for marker- assisted selection in polyploid wheat. Plant Biotechnology Journal, 2020, 18(6): 1354-1360.
Genome-wide association studies for canopy activity related traits and its genetic effects on yield-related traits
1Crop Research Institute, Shandong Academy of Agricultural Sciences/National Engineering Research Center of Wheat and Maize/Key Laboratory of Wheat Biology and Genetics and Breeding in Northern Huang-Huai River Plain, Ministry of Agriculture and Rural Affairs/Shandong Technology Innovation Center of Wheat/Jinan Key Laboratory of Wheat Genetic Improvement, Jinan 250100;2College of Agricultral and Biological Engineering (College of Tree Peony), Heze University, Heze 274015, Shandong;3Department of Cell Biology, Zunyi Medical University, Zunyi 563099, Guizhou;4Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081
【Objective】Canopy activity is an important indicator of wheat growth and development. Identification the loci for canopy activity related traits and their relationships with grain yield (GY) related traits can provide theoretical support for the dissection of genetic structure of yield trait and assisted wheat breeding.【Method】A total of 166 wheat varieties originating from both domestic and international sources were planted in Anyang of Henan province and Suixi of Anhui province in cropping seasons. With the integrated physical map containing 326 570 SNP markers from the wheat 90K and 660K chips, genome-wide association studies for normalized difference vegetation index at seedling stage (NDVI-S) and 10 days after flowering (NDVI-10), and chlorophyll content in flag leaf at 10 days after flowering (Chl-10) were carried out. The results were compared with the previous study for GY related traits using the same material. 【Result】Analysis of variance (ANOVA) showed highly significant effects (<0.01) of genotypes, environments and genotype×environment interactions on NDVI-S, NDVI-10 and Chl-10, with broad-sense heritabilities (2of 0.81, 0.81 and 0.91, respectively. Thirteen, 12 and 15 loci were detected to be significantly correlated with NDVI-S, NDVI-10 and Chl-10, respectively, among which 12, 11 and 12 were new, and five loci were associated with two or more traits. The number of favorable alleles for NDVI-S, NDVI-10 and Chl-10 ranged from 4 to 11, 3 to 11 and 4 to 12, respectively, in the 166 wheat varieties, and the phenotypic values increased with the accumulation of favorable alleles. NDVI-S showed significant (<0.01) and positive correlations with thousand-kernel weight, kernel length and kernel width. Chl-10 was significant positively correlated with GY and flag leaf width (<0.01), whereas significant negatively correlated with spike number per unit area, plant height and uppermost internode length (<0.01). Seven pleiotropic loci were detected co-related with both GY and canopy activity related traits.【Conclusion】NDVI-S can be directly used for selection of yield traits. The stable and pleiotropic loci detected in this study can be used for marker-assisted selection.
; canopy activity; grain yield; normalized difference vegetation index; chlorophyll content; genome- wide association studies
2023-07-17;
2023-09-12
山東省重點(diǎn)研發(fā)計(jì)劃(重大科技創(chuàng)新工程)(2021LZGC009)、泰山產(chǎn)業(yè)領(lǐng)軍人才工程(LJNY202006)、國(guó)家現(xiàn)代農(nóng)業(yè)產(chǎn)業(yè)技術(shù)體系(CARS-03-6)、2023年山東省農(nóng)業(yè)科學(xué)院科技創(chuàng)新工程(CXGC2023A01)、濟(jì)南市“新高校20條”資助項(xiàng)目(202228067)
李法計(jì),E-mail:lifajily@163.com。通信作者李豪圣,E-mail:lihaosheng810@163.com
(責(zé)任編輯 李莉)