李鵬 劉銳濤 譚西北 張穎 劉崇懷
摘要:葡萄在生長發(fā)育過程中易遭受多種病原菌的侵染,影響果實品質(zhì)和產(chǎn)量,制約葡萄產(chǎn)業(yè)的發(fā)展。生產(chǎn)中多采用殺菌劑對病原菌進行防治,增加了投資成本,且會對環(huán)境造成污染,因此培育高品質(zhì)抗病品種對葡萄生產(chǎn)具有重要意義。葡萄抗病性為多基因控制的數(shù)量性狀,QTL 定位是研究數(shù)量性狀的一種有效方法,遺傳圖譜的構(gòu)建是檢測QTLs和克隆基因的基礎(chǔ)。多年來,研究人員通過構(gòu)建遺傳圖譜鑒定了一系列霜霉病、白粉病、皮爾斯病等抗性遺傳位點,同時,根據(jù)抗性位點的基因組區(qū)域,開發(fā)了多個連鎖標記,并應(yīng)用到葡萄抗病性遺傳研究中,加速了葡萄的育種進程。對葡萄遺傳連鎖圖譜的構(gòu)建和抗病相關(guān)QTL定位研究進展進行了綜述,分析了目前研究中存在的問題并提出建議,為今后葡萄抗病基因定位和分子標記輔助選擇育種提供借鑒。
關(guān)鍵詞:葡萄;遺傳圖譜;抗?。籕TL定位
中圖分類號:S663.1 文獻標志碼:A 文章編號:1009-9980(2023)06-1245-10
葡萄是多年生落葉藤本植物,果實風味濃郁,營養(yǎng)價值高,既可鮮食,也可加工成各種產(chǎn)品,在農(nóng)業(yè)經(jīng)濟中發(fā)揮著重要作用。據(jù)世界糧農(nóng)組織(FAO,2020)統(tǒng)計,中國葡萄產(chǎn)量達1 476.9 萬t,居世界第一位。葡萄生長過程中各種生物或非生物脅迫對產(chǎn)量有著較大影響,由病原菌引起的生物脅迫是非常嚴重的危害因子[1]。目前葡萄生產(chǎn)上對病原菌治理主要是藥劑防治,不僅增加栽培成本,更危害環(huán)境及食品安全[2],培育抗病品種有利于葡萄產(chǎn)業(yè)健康發(fā)展。葡萄具有童期長、雜合度高等特點,使用常規(guī)育種耗時長、效率低,通過分子標記輔助選擇育種(molecular marker assistant selection,MAS)技術(shù)能提高定向育種效率,加速育種進程[3]。
構(gòu)建遺傳連鎖圖譜(genetic linkage map),進行數(shù)量性狀位點(quantitative trait locus,QTL)定位,建立標記與表型之間的連鎖關(guān)系,是實施分子標記輔助育種的有效途徑[4]。自Lodhi 等[5]基于隨機擴增多態(tài)性DNA 標記(random amplified polymorphicDNA,RAPD)和擴增片段長度多態(tài)性標記(amplifiedfragment length polymorphism,AFLP)構(gòu)建了第一張葡萄遺傳圖譜以來,世界上已經(jīng)發(fā)布了160 多張葡萄遺傳圖譜[6],其中約40 張與葡萄抗病性有關(guān)。以遺傳連鎖圖譜為基礎(chǔ),研究人員已對多個葡萄抗病相關(guān)位點進行定位,并開發(fā)了連鎖標記,部分已經(jīng)應(yīng)用于育種中[7]。筆者在本文中對葡萄遺傳圖譜構(gòu)建與抗病QTL定位的研究進展進行綜述,為葡萄抗病性定位相關(guān)研究和分子標記輔助選擇育種提供借鑒和參考。
1 葡萄遺傳圖譜的構(gòu)建
構(gòu)建高密度遺傳圖譜是進行基因定位、分子標記輔助育種,以及圖位克隆的基礎(chǔ)[8]。構(gòu)建遺傳圖譜主要包括選擇合適的作圖群體、采用多態(tài)性分子標記以及根據(jù)重組率利用相關(guān)作圖軟件計算分子標記間的連鎖排序和遺傳距離。
作圖群體的選擇是構(gòu)建遺傳圖譜的前提。目前F1群體、F2群體、BC 群體、DH群體、RIL 群體(重組自交系)等作圖群體在QTL 定位研究中均有使用[3,9]。但葡萄童期長、純合與雜合位點共存、遺傳背景復雜等問題難以獲得高世代群體。針對這一問題,Weeden 等[10]提出了著名的“雙假測交”理論,即將F1雜交群體視為與隱性親本測交得到的回交一代(BC1)群體。當F1群體出現(xiàn)分離重組,其分離重組發(fā)生在親本所特有遺傳標記位點,則將其中一個親本的雜合位點看作是另一個親本的隱性純合,后代群體1∶1 分離,則相當于“測交”;若分離重組位于兩親本共有的標記位點,則將兩親本都視為雜合位點,如若是共顯性標記,后代群體分離比為1∶2∶1,若是顯性標記后代,分離比則為3∶1。基于此理論,葡萄常用于構(gòu)建遺傳圖譜的群體類型主要為雜交F1代,少數(shù)為回交群體、自交群體。葡萄F1代雜交群體雖易于構(gòu)建,可以縮短定位群體建立周期,但該群體屬于暫時分離群體僅能使用一次,遺傳背景復雜容易造成定位偏差[9]。
分子標記由于變異豐富、穩(wěn)定、不受環(huán)境影響等因素成為葡萄遺傳圖譜研究的有效手段。早期葡萄遺傳圖譜主要采用RAPD和AFLP分子標記進行構(gòu)建。1995 年Lodhi 等[5]利用Cayuga White × Aurore的F1群體,結(jié)合RAPD和AFLP 等標記構(gòu)建2 張遺傳圖譜,其中Cayuga White 構(gòu)成的遺傳圖譜包含214 個標記,全長為1196 cM;Aurore 構(gòu)成的遺傳圖譜包含225 個標記,全長為1477 cM。這兩種標記可以快速構(gòu)建圖譜,但構(gòu)建的不同葡萄品種的遺傳圖譜之間無法比較[11],局限性較大。隨著測序技術(shù)的發(fā)展,簡單序列重復標記(simple sequence repeat,SSR)因共顯性、高度多態(tài)性,在不同葡萄品種間具有較高的通用性,成為構(gòu)建遺傳圖譜使用頻率最高的標記。葡萄第一套SSR 標記(共371 個)由葡萄微衛(wèi)星聯(lián)盟(Vitis Microsatellite Consortium,VMC)開發(fā)[11]。Riaz 等[12] 利用Riesling × CabernetSauvignon 雜交群體結(jié)合152 個SSR標記(主要來自VMC)構(gòu)建了第一張葡萄SSR 遺傳圖譜,該圖譜總長為1728 cM,標記間平均距離為11.0 cM。DiGaspero 等[13]開發(fā)了另外兩組基于微衛(wèi)星的標記(169 個VVI 和108 個UDV)。Adam-Blondon 等[14]以Syrah × Grenache 的F1 群體為材料,利用220 個SSR 標記(包含123 個VVI 標記)構(gòu)建了總長度為1 406.1 cM、標記平均距離為6.4 cM 的遺傳圖譜。
為了提高SSR 標記構(gòu)建圖譜的飽和度、通用性和實用性,Doligez 等[15]將5 個遺傳群體整合得到一張含515 個標記(502 個SSR 標記)的遺傳圖譜,該圖譜總長度為1647 cM,標記間平均距離為3 cM。此圖譜是基于SSR 標記最為完整的圖譜之一。但SSR標記數(shù)量有限[16],遺傳圖譜密度和精度受限,無法對性狀相關(guān)的候選基因進行有效定位[11]。伴隨著測序技術(shù)的發(fā)展,單核苷酸多態(tài)性(single nucleotidepolymorphisms,SNP)標記越來越多地被應(yīng)用在遺傳圖譜構(gòu)建上。相較之前的標記,SNP 在基因組均勻分布,多態(tài)性好,可以避免圖譜標記密度偏小的問題,顯著提高精細定位程度[6,17]。全基因組測序(whole genome sequencing)、簡化基因組測序(reduced- representation genome sequencing,RRGS)和SNP-array 是開發(fā)SNP 標記的主要高通量測序技術(shù)。Sapkota 等[1]用Norton × Cabernet Sauvignon 的159 個F1單株為作圖群體,結(jié)合1665 個SNP 標記和407個SSR標記獲得抗霜霉病遺傳圖譜。Sun等[18]利用Red Globe × Muscat Hamburg 的95 個F1群體,結(jié)合27 454 個SNP標記,構(gòu)成覆蓋長度為1 442.64 cM的遺傳圖譜。Su 等[19]利用Zhuosexiang × Victoria 的F1 代群體,采用6249 個SNP 構(gòu)建的抗白腐病整合圖譜大小為3 118.13 cM,平均標記密度是0.5 cM。
最近,一種基于擴增子測序(AmpSeq)的新型高效分子標記應(yīng)用于遺傳圖譜的構(gòu)建。Karn 等[20]利用Horizon × Illinois 547-1 的F1 群體,構(gòu)建一張包含1171 個Ampseq 標記、覆蓋總長度為1 082.16 cM的圖譜。Reshef 等[21]利用V. rupestris B38 × Horizon的雜交群體,構(gòu)建一張包含1944 個Ampseq標記、總長度范圍為1 050.7 cM的遺傳圖譜。葡萄主要圖譜的基本情況見表1。從表1 可以看出,國內(nèi)外對葡萄遺傳圖譜研究中作圖群體數(shù)量大多在100 株以上;標記類型從最初的AFLP 標記到大規(guī)模測序開發(fā)SNP標記,不斷向前發(fā)展;遺傳圖譜標記數(shù)目和密度不斷增加,使得標記之間的平均距離從12.7 cM 降至0.28 cM。
構(gòu)建遺傳圖譜需將分子標記分配到不同的連鎖群,每個連鎖群內(nèi)根據(jù)重組率對標記進行排序并估計遺傳距離。目前常用的構(gòu)圖軟件有JoinMap、Mapmaker 和TMAP等[6,44]。但同一作圖軟件不會包含所有分離類型,不同軟件構(gòu)建的遺傳圖譜也存在差異,應(yīng)根據(jù)實際情況進行選擇。
2 抗病性狀QTL定位
2.1 葡萄霜霉病抗性QTL定位
葡萄霜霉病作為全球性真菌性病害,抗性位點研究最多。Merdinoglu等[22]利用Syrah×28-8-78的F1分離群體進行抗霜霉病QTL分析,首次在28-8-78的12 號染色體上鑒定到一個主效QTLRpv1(Resistanceto Plasmopara viticola 1),該位點能夠解釋73%的表型變異,與其緊密連鎖的標記為VVIb32。來源于圓葉葡萄的Rpv1 抗性基因已被克隆并進行了功能驗證。Rpv1 是核苷酸結(jié)合/富含亮氨酸重復(nucleotidebinding/leucine-rich repeat,NB-LRR)受體,參與病原菌的識別和植物防御的信號轉(zhuǎn)導[45- 46]。
Welter等[26]利用Regent ×Lemberge的F1代群體通過4年霜霉病抗性鑒定,最終在18 號染色體中得到1 個主效QTLRpv3,該位點解釋了37.3%表型差異,富含TIR-NBS-LRR基因,并在不同群體的研究中得到進一步驗證[22,47]。含有Rpv3 位點的葡萄植株葉片在受到霜霉病侵染時,霜霉病菌絲體生長受限,新生孢子囊和孢子囊數(shù)量減少[48-49]。Marguerit 等[3]通過CabernetSauvignon × Gloire De Montpellie 的F1子代霜霉病抗性鑒定,發(fā)現(xiàn)在9和12號染色體存在2個抗性位點Rpv5 和Rpv6,其中Rpv5 緊密連鎖的標記VVIO52;Rpv6 是第二個定位在12 號染色體上抗性位點。Bellin 等[47]使用Chardonnay × Bianca 群體通過多種霜霉病表型鑒定方法,發(fā)現(xiàn)Bianca 的7 號染色體上存在抗性位點Rpv7,該位點解釋的表型變異率為12.7%。Blasi 等[32]使用雌雄同株山葡萄品種(V. amurensis‘Ruprecht)自交后代,通過5種抗性評價體系,在14 號染色體上發(fā)現(xiàn)抗性位點Rpv8,該位點解釋的表型變異率高達86.3%。Schwander等[33]將Rpv10 定位在9 號連鎖群,并將其范圍精確定位到2.1 cM,大小為314 kb。研究還發(fā)現(xiàn)該區(qū)域包含8 個核苷酸結(jié)合/富含亮氨酸重復(nucleotide binding/leucine-rich repeat,NBS-LRR)類型的RGA。隨后越來越多的抗霜霉病位點被挖掘,目前,在4、5、6、7、8、9、10、12、14、17和18號染色體上共定位到28個抗性主效或微效QTL(表2),解釋的表型變異率從3.5%到86.3%。這些QTL 抗性位點來源于不同的葡萄品種。Rpv1 和Rpv2 來源于圓葉葡萄(Muscadinia rotundifolia);Rpv3、Rpv19 和Rpv28 來源于沙地葡萄(V. rupestris);Rpv4、Rpv7、Rpv11、Rpv17、Rpv18、Rpv20 和Rpv21 來源于北美種群但未確定品種;Rpv5、Rpv6、Rpv9 和Rpv13 來源于河岸葡萄(V. riparia);Rpv8、Rpv10、Rpv12、Rpv22、Rpv23、Rpv24、Rpv25 和Rpv26來源于山葡萄(V. amurensis);Rpv14來源于甜冬葡萄(V. cinerea); Rpv27 來源于夏葡萄(V. aestivalis)。這表明利用優(yōu)異的種質(zhì)資源去挖掘更豐富的優(yōu)異變異,是尋找葡萄抗病基因的重要途徑。
2.2 葡萄白粉病抗性QTL定位
葡萄白粉病是由致病菌Erysiphe necator [synonymUncinula necator (Schw.) Burr.]引起的真菌性病害,可引起葉片褪綠,覆蓋白色粉層進而導致葉片卷曲、枯萎等癥狀。同葡萄霜霉病一樣,葡萄白粉病抗性位點較多(表3),命名為Run(Resistance to Uncinulanecator)或Ren(Resistance to Erysiphe necator)。Barker 等[59]首次將抗白粉病Run1 定位在圓葉葡萄的12 號染色體上,而歐亞種不攜帶該基因。目前以圓葉葡萄和歐亞種葡萄的BC5為材料,已經(jīng)獲得與Run1 基因連鎖的分子標記[60]。Hoffmann 等[53]將Ren1 抗性位點定位于Nimrang 的LG13 上的VMC9H4-2、VMCNG4E10-1 和UDV-020 附近,該區(qū)域包含多個NBS-LRR基因。在中國野生群體利用中,Pap 等[35]在中國野生葡萄變?nèi)~葡萄V. piasezkii(Dvit2027)中發(fā)現(xiàn)了2 個抗白粉病的QTL位點Ren6和Ren7,分別位于第9 和第19 染色體上。目前白粉病抗性位點在2(Ren10)、9(Ren6)、12(Run1)、13(Ren1)、14(Ren2,Ren5)、15(Ren3,Ren9)、18(Run2.1、Run2.2、Ren4、Ren8)、19(Ren7)號染色體上鑒定出來(表3)解釋的表型變異率從14%到76%。
2.3 其他病害抗性QTL定位
其他葡萄病害,如皮爾斯病、冠癭病、黑腐病、炭疽病、白腐病等,對葡萄也有較大危害,但QTL定位研究相對較少。在抗皮爾斯病的QTL 研究中,Krivanek 等[61]首先將抗皮爾斯病Pdr1(Pierces diseaseresistance 1)定位于14 號染色體上;隨后Riaz等[62]通過精細定位將抗皮爾斯病的主效QTL定位到14 號染色體VVIn64 和UDV095 標記附近。在抗冠癭病QTL 定位方面,Kuczmog 等[63]將Rcg1(Resistanceto Crown gall 1)定位在抗冠癭病親本Kunbarát(V. amurensis)的15 號染色體上,緊密連鎖標記9M3-3 距Rcg1 位點576 kb 遠。關(guān)于黑腐病QTL 研究較少,Rex 等[34]將黑腐病2 個抗性位點Rgb1(Resistanceto Guignardia bidwellii 1)和Rgb2 分別定位在14 號和16 號染色體上。近年來,部分科技人員對葡萄抗炭疽病進行QTL定位,高曉銘等[64]利用里扎馬特×黑珍珠雜交F1代群體,在12 號染色體檢測到解釋表型變異率37.07%、貢獻率為71.50%的抗炭疽病主效QTL。Fu 等[40]對Cabernet Sauvignon × ShuangHong 雜交群體進行了連續(xù)3 年抗炭疽病鑒定,在14 號染色體發(fā)現(xiàn)抗性位點Rgr1(Resistance toColletotrichum 1),此區(qū)間包含了11 個NBS-LRR 基因。2021 年,Su 等[19]利用Zhuosexiang × Victoria 雜交群體在14 號染色體上定位到一個抗葡萄白腐病QTL,并預(yù)測了7個可能抗白腐病的候選基因。這些定位結(jié)果為分子標記在育種中的使用奠定了基礎(chǔ)。
3 問題及展望
構(gòu)建遺傳圖譜和開發(fā)目標性狀緊密連鎖的分子標記,對MAS育種效率的提升具有重要意義。近年來,葡萄遺傳圖譜的構(gòu)建發(fā)展較快,獲得一些成果,但仍存在問題。許多葡萄遺傳圖譜使用RFLP、AFLP、RAPD、SSR 等第一代和第二代標記構(gòu)建,導致圖譜標記密度較低,各連鎖群標記間距較大,標記在基因組分布不均勻,無法有效定位候選基因。隨著測序技術(shù)的發(fā)展,SNP標記已經(jīng)用來構(gòu)建高密度遺傳圖譜,提高了圖譜的飽和度并顯著提高精細定位程度。但SNP 在不同種群間通用性較低[6],在將來應(yīng)考慮構(gòu)建多種標記整合的圖譜,提高圖譜的飽和性與通用性。分子標記輔助選擇是將分子標記應(yīng)用于葡萄品種改良過程中進行選擇的一種輔助手段,主要包括對目標性狀的前景選擇和對遺傳背景的背景選擇。目前葡萄分子標記輔助育種仍以SSR標記為主,但SSR分子標記通性低、費時,而SNP標記適合高通量、自動化檢測,可能成為未來首選的標記系統(tǒng)[6]。然而SNP 分子標記在葡萄MAS中的實際應(yīng)用仍然較少[37,65],因此應(yīng)加大對性狀關(guān)聯(lián)SNP標記的轉(zhuǎn)化和應(yīng)用。
葡萄抗病性作為一個復雜的數(shù)量性狀,受到較多基因的調(diào)控,且基因之間還存在著互作效應(yīng),遺傳機制非常復雜。雖然已有許多針對抗病性狀的QTL定位研究,但由于抗病性狀往往受到多個QTL控制,且影響群體QTL 檢測的因素很多,如環(huán)境因素、群體大小及分子標記連鎖圖譜的飽和度等[6]。
另外葡萄定位常使用群體數(shù)量較小的初級作圖群體F1,容易造成定位誤差。因此,將來在研究中應(yīng)構(gòu)建群體數(shù)量較大的F2、BC(回交群體)等群體,消除遺傳背景對QTL定位產(chǎn)生的不利影響[9],提高QTL檢測靈敏度和定位精度。隨后通過這些位點解析抗病性狀的遺傳和分子機制,挖掘葡萄抗病優(yōu)良基因,為葡萄抗病育種奠定基礎(chǔ)。另外葡萄抗病定位研究主要集中在霜霉病和白粉病,而對我國危害較大的灰霉病和黑痘病尚未見報道,應(yīng)加大對這些病害的解析。
葡萄多個圖譜以及病害抗性QTL 位點已經(jīng)發(fā)表,但這些實驗數(shù)據(jù)(基因型、表型)和位點信息未儲存在公共數(shù)據(jù)庫,極大限制了圖譜的整合以及定位信息的有效利用。作為模式作物水稻,其表型和圖譜信息以及QTL 相關(guān)數(shù)據(jù)可以在Gramene 數(shù)據(jù)庫進行檢索,促進了QTL 位點利用和候選基因的挖掘[66]。因此未來應(yīng)構(gòu)建可以共享的葡萄的QTL定位數(shù)據(jù)庫,以提高QTL數(shù)據(jù)的利用與挖掘。
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