岳曉鳳,闕亞偉,王政逸
(浙江大學農業與生物技術學院水稻生物學國家重點實驗室,杭州 310058)
基于RNA-Seq的稻瘟病菌Δznf1突變體的表達譜分析
岳曉鳳,闕亞偉,王政逸
(浙江大學農業與生物技術學院水稻生物學國家重點實驗室,杭州 310058)
【目的】稻瘟病菌(Magnaporthe oryzae)引起的水稻稻瘟病是威脅全球水稻生產的重要病害之一,而該菌附著胞介導的侵染又是病害循環的重要環節。在前期的研究中發現一個編碼C2H2鋅指結構的轉錄因子基因ZNF1,參與稻瘟病菌附著胞形成、穿透和致病過程,論文旨在從轉錄水平上了解受Znf1調控的基因及其調控機理,為深入研究稻瘟病菌致病分子機理提供基礎數據。【方法】利用RNA-Seq技術對稻瘟病菌野生型菌株Guy11和突變體Δznf1的營養菌絲體進行表達譜測序,采用FPKM法計算基因表達量,以FDR≤0.001且log2ratio (Δznf1/Guy11)≥1為篩選標準,獲得Δznf1中差異表達基因(differentially expressed genes, DEGs);通過與Gene Ontology(GO)數據庫和KEGG Pathway數據庫比對,獲得差異基因可能的生物學功能和參與的分子調控途徑。為了更詳細地研究受Znf1調控的基因,在同樣的條件下,利用RNA-Seq技術對稻瘟病菌絲裂原活化蛋白激酶(mitogen-activated protein kinase,MAPK)編碼基因PMK1的缺失突變體進行表達譜分析,通過對Δznf1和Δpmk1中的差異表達基因進行比較,篩選受Znf1和Pmk1共同調控的基因,并與前人的研究數據比較,分析獲得在稻瘟病菌附著胞發育階段上調表達但在Δznf1和Δpmk1中同時下調表達的基因。【結果】與野生型Guy11相比,Δznf1中共有709個差異表達基因,其中上調表達的有299個,下調表達的有410個;GO功能富集分析顯示差異表達基因歸類到生物學過程、細胞組分和分子功能上的基因數目分別有118、299和308個;KEGG Pathway富集分析顯示,這些差異表達基因主要參與代謝途徑、次生代謝物質生物合成、甘油磷脂代謝等。一些已知的稻瘟病菌致病相關基因,如LPP3、HOX7、PBS2、MPG1等,在Δznf1中表達水平下調。與Δpmk1中差異表達基因比較發現,Δznf1中約56%的差異表達基因同時也受Pmk1調控。其中,編碼isotrichodermin C-15 羥化酶的3個基因MGG_03825、MGG_02329和MGG_08498,在Δznf1和Δpmk1中的表達水平均顯著下調。此外,在附著胞階段上調表達的48個基因,在Δznf1和Δpmk1中同時下調表達,表明這些與附著胞形成可能相關的基因直接或間接受Znf1和Pmk1調控。采用qRT-PCR方法隨機檢測10個基因的表達情況,結果與RNA-Seq數據基本一致,說明本試驗RNA-Seq數據的可靠性。【結論】RNA-Seq分析獲得了受Znf1調控的基因信息和可能的生物學功能。一些與稻瘟病菌致病相關的基因受Znf1調控。此外,與Pmk1類似,一些在附著胞階段上調表達的基因也同時受Znf1調控。結果可為進一步研究Znf1下游基因調控網絡提供信息。
水稻;稻瘟病菌;附著胞;Δznf1; RNA-Seq; 差異表達基因
【研究意義】稻瘟病菌(Magnaporthe oryzae)侵染水稻引起的稻瘟病是水稻上的重要病害,每年可造成10%—30%的稻谷產量損失,嚴重威脅世界各水稻產區糧食生產安全[1]。由于經濟的重要性和分子遺傳的可操作性,稻瘟病菌-水稻互作機制已成為研究病原菌-寄主植物互作的模式系統[1-3]。對稻瘟病菌致病分子機理的深入了解不僅有助于新的稻瘟病防治策略的研發,有效控制病害流行,而且對其他植物病原真菌的研究及其病害防治具有重要的指導意義。【前人研究進展】稻瘟病菌通過形成一種特異性的侵染結構——附著胞侵入寄主細胞[4]。當分生孢子著落在稻株表面后,在適宜的水分條件下萌發產生芽管,芽管頂端迅速膨大并逐漸分化形成附著胞。成熟的附著胞黑色素化并通過甘油等溶質的積累而產生強大膨壓(高達8 MPa)。在膨壓的作用下,附著胞產生足夠的機械壓力驅動稻瘟病菌成功穿透寄主表皮進行侵染,隨后鱗莖狀的侵染菌絲在細胞內和細胞間擴展。侵染3—5 d后水稻葉片表面形成可見的壞死病斑[1,5-6]。研究表明,cAMP-PKA信號途徑調控早期表面信號識別和附著胞分化,外源添加cAMP能誘導分生孢子在親水表面形成附著胞[7-12]。Pmk1-MAPK信號途徑調控附著胞成熟、穿透及擴展[11-14]。PMK1缺失突變體不能形成附著胞,不能穿透寄主表皮,對寄主致病性完全喪失[13]。Mst12是位于Pmk1下游的轉錄因子,參與調控侵染釘形成和穿透。Δmst12能形成成熟的附著胞,但不能穿透寄主表皮而完全喪失對寄主的致病性[15-17]。由于MST12不是附著胞發育與成熟所必需,因此研究者們認為還存在其他受Pmk1調控的轉錄因子參與附著胞的形成。近期,筆者實驗室研究發現了一個C2H2型鋅指結構轉錄因子Znf1,其可能位于cAMP-PKA和Pmk1-MAPK信號途徑下游,在附著胞介導的稻瘟病菌侵染過程中有重要作用[18]。Δznf1在營養生長、色素沉積以及有性生殖等方面與野生型菌株沒有明顯的差異,但Δznf1芽管頂端不能分化形成成熟的附著胞,不能穿透寄主表皮,即使是在劃傷或針刺的大麥和水稻葉片表面都不能產生病斑。在稻瘟病菌附著胞發育階段,Znf1受Pmk1調控,并且同Δpmk1能響應外源cAMP刺激類似,外源cAMP或IBMX能誘導Δznf1芽管頂端分化形成囊泡狀的膨大結構。但酵母雙雜交實驗表明Znf1與Pmk1沒有直接的互作[18]。【本研究切入點】Znf1下游調控的基因尚不明確,Znf1對附著胞相關基因的調控以及與Pmk1的關系有待挖掘,而且對Znf1作用機制的深入研究能夠加深對稻瘟病菌附著胞調控機理的認識。本研究通過高通量測序技術,從轉錄水平上解析Znf1的調控機制。【擬解決的關鍵問題】利用RNA-Seq(RNA-sequencing)技術對稻瘟病菌野生菌株Guy11和Δznf1突變體進行表達譜分析和差異表達基因篩選,以期為進一步鑒定和研究受Znf1調控的基因提供基礎數據。此外,通過比較Δznf1和Δpmk1中的差異表達基因,篩選受Znf1和Pmk1共同調控的基因,深入了解Znf1與Pmk1的關系以及鑒定新的與稻瘟病菌附著胞形成相關基因,從而為完善稻瘟病菌致病分子機理提供數據。
1.1 供試材料
RNA-Seq所用的稻瘟病菌野生型Guy11、Δznf1和Δpmk1突變體均為筆者實驗室保存或研究獲得的菌株。供試菌株在CM液體培養基中振蕩培養48 h(28℃,180 r/min)后,2層紗布過濾收集菌絲,經無菌水沖洗數遍后,將水分壓干,液氮速凍后儲存于-80℃保存備用。每個菌株3個重復。CM培養基配方:10 g·L-1glucose, 2 g·L-1peptone,1 g·L-1yeast extract,1 g·L-1casamino acids,0.1%(v/v)trace elements,0.1%(v/v)vitamin supplement,6 g·L-1NaNO3,0.5 g·L-1KCl,0.5 g·L-1MgSO4,1.5 g·L-1KH2PO4,pH 6.5。
1.2 RNA提取及質量檢測
2015年9月樣品組織送至深圳華大基因科技服務中心,RNA-Seq測序在該中心進行。采用Trizol法分別提取各菌株的菌絲樣品總RNA,并使用DnaseI去除樣品中的DNA雜質。通過1%瓊脂糖凝膠電泳,以及NanoDrop ND-2000和Agilent 2100對RNA樣品進行濃度、純度和完整性等檢測。OD值標準:OD260/280≥1.8,OD260/230≥1.8;RIN(RNA完整系數)≥8,28S/18S≥1。為了提高試驗的準確性,將3個生物學重復樣品分別提取RNA,然后等量混合作為一個樣本用于RNA-Seq。
1.3 文庫構建及RNA-Seq測序
用帶有Oligo(dT)的磁珠富集mRNA,向得到的mRNA中加入適量打斷試劑高溫條件下使其片斷化,再以片斷化后的mRNA為模板,合成cDNA,經過磁珠純化、末端修復、3′末端加堿基A、加測序接頭后,進行PCR擴增,從而完成整個文庫制備工作。構建好的文庫用Agilent 2100 Bioanalyzer和ABI StepOne Plus Real-Time PCR System進行質量和產量檢測,文庫質控合格后進行Illumina HiSeqTM2000測序分析,測序反應進行一次。
1.4 基因定量分析及差異基因篩選
基因表達量用FPKM(Fragments Per Kilobase of exon per Million fragments mapped)法計算[19]。根據野生菌株Guy11和突變體Δznf1或Δpmk1中基因的FPKM值來比較不同樣品間的基因差異表達。在本試驗分析中,差異基因篩選標準為錯誤發現率(false discovery rate,FDR)≤0.001且差異倍數在2倍以上即∣log2(樣品間基因表達量的比值)∣≥1。
1.5 差異基因GO功能注釋及KEGG Pathway富集分析
將所有差異表達基因向Gene Ontology(GO)數據庫(http://www.geneontology.org/)的各個term映射,計算每個term的基因數目,然后應用超幾何檢驗,找出與整個稻瘟病菌基因組相比,在差異表達基因中顯著富集的GO條目。得到差異基因的GO注釋后,利用WEGO軟件對差異基因進行GO功能分類統計[20]。Pathway顯著性富集分析以KEGG Pathway為單位[21],應用GO富集原理可以得出差異表達基因中顯著性富集的Pathway。
1.6 實時熒光定量PCR(qRT-PCR)
為了驗證RNA-Seq結果的可靠性,隨機選擇10個差異表達基因進行qRT-PCR檢測,引物見表1。通過Trizol法提取CM液體培養基振蕩培養48 h的菌絲總RNA,用反轉錄試劑盒PrimeScript?RT Reagent Kit With gDNA Eraser(TaKaRa)合成cDNA。采用GoTag?qPCR Master Mix(Promega)試劑,一個反應體系為20 μL,3個重復。qRT-PCR反應在BIO-RAD CFX96TMReal-Time System儀上運行。反應程序為:95℃ 30 s,95℃5 s,56℃ 15 s,72℃ 20 s,39個循環。以稻瘟病菌β-tubulin(MGG_00604)為內參基因,通過2-△△CT法計算基因相對表達水平[22]。通過3次獨立重復試驗計算基因相對表達的平均值和標準差。

表1 本研究qRT-PCR引物Table 1 qRT-PCR primers used in the study
2.1 表達譜測序及測序質量評估
為了深入了解稻瘟病菌中受轉錄因子ZNF1調控的基因,對稻瘟病菌野生型菌株Guy11以及ZNF1基因缺失突變體菌株Δznf1進行表達譜分析。收集菌株Guy11和Δznf1在液體CM培養基中培養2 d的菌絲,并分別進行樣品Total RNA抽提。NanoDrop ND-2000及Agilent 2100對Total RNA的質檢結果表明,樣品RNA的濃度、純度及完整性等各項指標達到建庫測序要求。進而構建測序文庫,文庫質控合格后利用Illumina HiSeqTM2000進行測序。
測序得到的原始圖像數據經base calling轉化的序列數據稱為raw reads。將低質量序列以及接頭序列等雜質raw reads過濾后得到可用于數據分析的clean reads。菌株Guy11和Δznf1分別獲得22 100 589和 22 074 094個clean reads,分別占原始數據的98.85%和98.72%。對數據質量評估合格后(Q20>95%),將clean reads比對到水稻稻瘟病菌基因組序列(http://www. broadinstitute.org/annotation/genome/magnaporthe_grise a/MultiHome.html)。比對結果顯示,Guy11和Δznf1分別有92.63%和92.37%的clean reads能有效的比對到參考基因組上,并且具有唯一比對位點的reads數分別占比對到基因組上總reads數的89.20%和87.88%(表2),表明樣品測序質量較高。

表2 樣品RNA-Seq序列與參考基因組的比對統計Table 2 Statistical analysis of RNA-Seq reads mapping to the reference genome
測序飽和度在一定程度上可以評估測序數據量是否達到要求。由圖1所示,在測序量(reads數量)較小時,樣品檢測到的基因數均隨著測序量的增加而隨之上升,當測序量達到5 M左右后,其增長速度趨于平緩,說明檢測到的基因數趨于飽和。菌株Guy11和Δznf1均產生不低于20 M的clean reads,因此可以認為測序檢測到的基因數能夠基本覆蓋細胞表達的全部基因,測序量已達到要求。

圖1 RNA-Seq測序飽和度分析Fig. 1 Analysis of sequencing saturation
2.2 Δznf1差異表達基因的篩選
為鑒定受Znf1調控相關基因,對野生型Guy11和Δznf1表達譜進行比較,獲得差異表達基因(differentially expressed genes,DEGs)。根據基因的表達量(FPKM值)計算該基因在兩個樣品間的差異表達倍數,通過控制錯誤發現率FDR來決定P-value的域值。以∣log2ratio (Δznf1/Guy11)∣≥1(即倍數差異在2倍以上),并且FDR≤0.001為篩選標準,共獲得709個差異表達基因,其中上調表達基因299個,∣log2ratio∣值>5(即上調倍數大于32)的有22個,下調表達基因410個,∣log2ratio∣值>5的有12個(圖2-A、2-B;附表1)。
為分析DEGs與哪些生物學功能顯著相關,利用GO注釋及GO功能富集分析,對差異表達基因進行功能分類(圖2-C)。結果顯示,在細胞組分(cellular component)、分子功能(molecular function)和生物過程(biological process)3類功能注釋的DEGs分別有118、299和308個。此外,細胞組分、分子功能和生物過程分別包含8、11和16個功能分類(圖2-C)。其中,在細胞組分分組中,DEGs在細胞(cell; GO:0005623)和細胞區域(cell part;GO:0044464)類所占比例最高,大分子復合物(macromolecular complex;GO:0032991)類所占比例最低;在分子功能分組中,催化活性(catalytic activity;GO:0003824)和結合(binding;GO:0005488)類,DEGs所占比例最高,在結構分子活性(structural molecule activity;GO:0005198)和營養庫活性類(nutrient reservoir activity;GO:0045735)所占比例最低;在生物過程分組中,DEGs在代謝過程(metabolic process;GO:0008152)和細胞過程(cellular process;GO:0009987)類所占比例最高,而在生物過程負調控(negative regulation of biological process;GO:0048519)類所占比例最低。
通過Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway富集分析確定了DEGs參與的最主要生化代謝途徑和信號轉導途徑[23],發現共有143個DEGs具有KEGG注釋。結合注釋結果,進行pathway富集分析,發現這些DEGs位于65個pathway中(附表2)。其中,DEGs位于代謝途徑(metabolic pathways;pathway ID:ko04146)的數目最多(41個),其次位于次生代謝物質生物合成(biosynthesis of secondary metabolites;pathway ID:ko01110)(24個),甘油磷脂代謝(glycerophospholipid metabolism;pathway ID: ko00564)(6個),酵母MAPK信號通路(MAPK signaling pathway-yeast;pathway ID:ko04011)(5個),內質網對蛋白質的加工(protein processing in endoplasmic reticulum;pathway ID:ko04141)(5個),酵母細胞周期(cell cycle-yeast;pathway ID:ko04111)(5個)等途徑中(附表2)。
2.3 稻瘟病菌部分已知致病相關基因受Znf1調控
對Δznf1 RNA-Seq數據分析發現大約有20個已知的參與稻瘟病菌形態分化與致病性的基因受Znf1調控(表3)。其中,轉錄因子編碼基因HOX7、FLBC以及脂質磷酸磷酸酶基因LPP2和LPP3在Δznf1中顯著下調表達。此外,參與細胞滲透調節的MAPK(mitogen-activated protein kinase)基因OSM1和MAPKK基因PBS2,以及細胞壁形成相關基因CHS3和AGS1的表達也明顯下調。然而,與一氧化氮合成和致病相關基因NOL3,參與黑色素合成相關基因ALB1、BUF1和RSY1以及編碼熱激蛋白40的MHF21的表達水平明顯上調,說明在營養生長階段Znf1對這些基因的轉錄可能起負調控作用。數據結果表明,這些與稻瘟病菌侵染相關形態分化、致病過程以及代謝相關基因可能直接或間接受Znf1調控。

圖2 Δznf1差異表達基因分析Fig. 2 Analysis of differentially expressed genes in Δznf1

表3 稻瘟病菌部分致病相關基因在Δznf1表達譜數據中的分析Table 3 Analysis of Δznf1 RNA-Seq data for several pathogenicity-related genes in M. oryzae
2.4 受Znf1和Pmk1共同調控基因的分析
篩選Znf1和Pmk1共調控基因可為進一步有效鑒定Znf1下游調控基因以及明確Znf1與Pmk1的關系提供數據支持。因此,在同等條件下對Δpmk1進行了表達譜分析。將Δznf1與Δpmk1中的DEGs比較分析發現,Δznf1的410個下調表達基因中,有201個(約50%)基因在Δpmk1中的表達同樣為下調;而Δznf1的299個上調基因中,有116個(約40%)基因在Δpmk1中也上調(圖3,附表3)。比如,與在野生菌株Guy11中相比,LPP3以及HOX7都在Δznf1和Δpmk1中有相似的下調表達倍數,疏水蛋白基因MPG1在Δpmk1中顯著下調表達(log2ratio為-7.4),但在Δznf1 中MPG1僅下調表達2.5倍(log2ratio為-1.4)。功能未知基因MGG_14997和MGG_03044在Δznf1和Δpmk1中均顯著下調,log2ratio(Δznf1/Guy11)和log2ratio(Δpmk1/Guy11)分別為-12.1、-12.1、-4.3、-3.6,說明這兩個基因受Znf1和Pmk1共同調控,且調控水平相似(附表3)。試驗結果表明,Znf1可能作為Pmk1 MAPK信號途徑下游的轉錄因子與Pmk1共同調控許多基因的轉錄過程。
2.5 qRT-PCR驗證
為了驗證RNA-seq數據的準確性,隨機選擇了10個DEGs進行qRT-PCR驗證(表4)。結果顯示,與RNA-Seq數據一致,與在野生菌株Guy11中相比,MGG_01391、MGG_03825、MGG_09000等基因表達水平在Δznf1 和Δpmk1中顯著下調,而MGG_08944、MGG_11084在Δznf1 中表達水平顯著升高。MGG_02246在Δznf1中下調表達,但在Δpmk1中上調表達26倍(圖4)。

圖3 Δznf1和Δpmk1中共同差異表達基因統計Fig. 3 Statistical analysis of differentially expressed genes in Δznf1 and Δpmk1

表4 用于qRT-PCR驗證的基因及其RNA-Seq測序結果Table 4 The RNA-Seq result of genes selected for qRT-PCR analysis

圖4 10個差異表達基因的qRT-PCR分析Fig. 4 qRT-PCR analysis on 10 DEGs
RNA-Seq是用來研究某一生物對象在特定生物過程中基因表達差異的技術[39-40]。該技術結合了轉錄組建庫實驗方法與數字基因表達譜的信息分析手段,可廣泛應用于生理調控、農業性狀、環境改造等領域。該技術主要用來研究基因表達的情況,在基因表達量分析、基因表達差異分析以及差異基因模式和功能聚類等方面應用廣泛[41]。近年來,基于RNA-Seq的全基因表達譜分析技術已廣泛應用于稻瘟病菌,為稻瘟病菌基因功能和結構的研究提供了許多有參考價值的數據。SOANES等[42]通過RNA-Seq和HT-SuperSAGE技術研究了稻瘟病菌在不同營養生長條件以及附著胞形成各階段中基因的差異表達情況,鑒定到了一組在附著胞形成階段特異高表達的基因;LI等[43]利用RNA-Seq初步明確了稻瘟病菌產孢相關轉錄因子Cos1的調控基因;PHAM等[44]將Chip-Seq和RNA-Seq數據結合分析了組蛋白H3K4甲基轉移酶MoSET1在營養生長階段和附著胞發育階段的調控網絡。稻瘟病菌Znf1是與附著胞形成、侵染、致病過程相關的轉錄因子[18],利用RNA-Seq技術,可為進一步鑒定Znf1下游調控基因,明確Znf1的調控網絡提供參考數據。因此,本研究中,筆者對稻瘟病菌野生菌株Guy11和突變體Δznf1 進行RNA-Seq分析,獲得了Δznf1在營養生長階段的差異表達基因。同時,對稻瘟病菌附著胞形成調控因子PMK1的缺失突變體也進行了RNA-Seq測序,并篩選出了Δznf1和Δpmk1中共同的差異表達基因。測序質量評估分析顯示測序質量較高,qRT-PCR驗證表明測序結果可靠,測序所得數據可為后續研究提供依據。
Δznf1表達譜分析共篩選到709個差異表達基因,其中上調表達基因299個,下調表達基因410個(附表1)。本試驗差異表達基因的篩選標準為∣log2ratio (Δznf1/Guy11)∣≥1,且FDR≤0.001,因此可能還有部分受Znf1調控的基因,但不符合標準而未被篩選到。一些與稻瘟病菌致病相關的基因表達與Znf1有關。例如,HOX7表達水平在Δznf1 中有一定程度的下調(表3),且Δhox7與Δznf1 的表型類似,均不能形成成熟的附著胞,僅在芽管或菌絲尖端形成無黑色素化的膨大結構[16],因此,HOX7可能直接或間接受Znf1調控。之前的研究發現,與野生菌株Guy11相比,Δznf1對胞壁降解酶Glucanex敏感性升高,同等條件下Δznf1原生質體釋放量增加[18]。用等量的Glucanex對Guy11和Δznf1菌絲處理2.5 h,計數顯示,Guy11原生質體釋放量為(15.2±1.17)×107個,而Δznf1原生質體釋放量為(27.2±0.71)×107個。本試驗RNA-Seq數據顯示幾丁質合成相關基因CHS3以及α-1,3-葡聚糖編碼基因AGS1在Δznf1中有一定程度的下調表達(表3)。因此,筆者推測Znf1可能通過調控CHS3和AGS1的表達水平從而影響稻瘟病菌細胞壁結構的完整性。在Δznf1差異表達基因中,有近60%的基因編碼預測蛋白(hypothetical protein)或保守的假定蛋白(conserved hypothetical protein)。MGG_08944編碼一個假定蛋白,在其他絲狀真菌中不能找到其同源蛋白。測序數據顯示log2ratio(Δznf1/Guy11)為6.1,qRT-PCR進一步證明其在Δznf1中上調表達30倍。MGG_11005、MGG_14426等在Δznf1中顯著下調(附表1)。在今后的研究中,可以通過基因敲除技術進一步明確這些受Znf1調控的假定蛋白基因的功能。最近,有研究以稻瘟病菌70-15菌株為背景,對47個C2H2轉錄因子基因進行了敲除,其中MGG_14931(本文的ZNF1)命名為VRF1,并對Δvrf1在饑餓誘導下的菌絲進行了表達譜分析[25]。本研究以Δznf1營養菌絲為材料進行表達譜測序,結果與Δvrf1數據有一定的差異,可能是由于菌株的不同以及對菌絲樣品的處理不同。
Pmk1是稻瘟病菌附著胞形成相關基因的重要調控因子[42]。Δznf1和Δpmk1表型類似,都不能形成附著胞,對寄主致病性完全喪失,都能響應外源cAMP的誘導[13,18]。在附著胞發育階段,ZNF1表達水平在Δpmk1中顯著下調[18]。將Δznf1和Δpmk1中差異表達基因比較發現,Δznf1里709個差異表達基因中,有397個(約56%)基因同時也受Pmk1調控,其中,317個基因在Δznf1和Δpmk1 中上調/下調趨勢相同(圖3,附表3)。該結果可以進一步證明Znf1可能是位于Pmk1下游,參與調控附著胞的形成[18]。3個在Δznf1和Δpmk1中均顯著下調的基因,MGG_03825、MGG_02329和MGG_08498,都編碼isotrichodermin C-15羥化酶,它們都含有細胞色素P450超家族的保守結構域,其中MGG_03825的表達經qRT-PCR驗證(圖4,附表3)。擬分枝鐮孢(Fusarium sporotrichioides)和小麥赤霉病菌(Fusarium graminearum)中TRI11與這3個基因同源,其編碼一個細胞色素P450單加氧酶。研究表明TRI11與單端孢霉烯毒素合成相關,主要負責C-15的羥基化反應[45-46]。這3個基因是否與稻瘟病菌生長、產孢、附著胞形成、致病等過程相關尚不明確,有待進一步研究。此外,Δznf1和Δpmk1中的共同差異基因數僅占Δpmk1中差異基因數目(3 169個)的12.6%,表明Znf1和Pmk1在調控機制上存在很大差異,Pmk1下游還存在其他轉錄因子負責這些差異表達基因的轉錄。而且,有一些基因在Δznf1和Δpmk1中上調/下調趨勢雖然相同,但上調/下調倍數有很大差異。疏水蛋白基因MPG1在Δpmk1中下調倍數達130倍,但在Δznf1中僅有輕微的下調表達。菌落疏水性測定表明Δpmk1 菌落疏水性喪失,但Δznf1菌落疏水性沒有明顯的改變(數據未顯示)。可見,在這些基因的調控上,Znf1與Pmk1有很大的不同。
SOANES等[42]通過RNA-Seq和HT-SuperSAGE技術對稻瘟病菌菌株Guy11在營養生長(CM培養基)階段和附著胞形成階段(分生孢子分別誘導4、6、8、14和 16 h)分別進行了表達譜分析,發現與在營養生長階段相比,共有1 838個基因的表達水平在附著胞形成階段顯著上調。結合本試驗數據分析發現,這些在附著胞發育階段上調表達的基因中有48個基因在Δznf1 和Δpmk1中均顯著下調表達(附表4)。比如,MGG_09000編碼CMGC/CDK蛋白激酶,其log2ratio(Δznf1/Guy11)及log2ratio(Δpmk1/Guy11)分別為-2.23和-11.72,而在CM及附著胞形成階段(T4、T6、T8、T14、T16)表達量分別為1.96、40.35、25.67、32.17、33.44、49.80[42](附表4)。HOX7(MGG_12865)編碼一個含Homeobox結構域的轉錄因子,參與稻瘟病菌附著胞形成、侵染和致病過程[16],其在稻瘟病菌附著胞形成階段,特別是在分生孢子誘導4 h后表達水平顯著升高(附表4)。然而,在突變體Δznf1和Δpmk1中,HOX7表達水平降低。這些與附著胞形成相關的基因同時受Znf1和Pmk1調控,表明與Pmk1類似,Znf1也參與這些附著胞相關基因的調控。
本研究獲得的Δznf1在菌絲生長階段的差異表達基因數目相對較少,而且表達差異倍數在10倍以上的基因不多,可能是由于Δznf1營養生長與野生型Guy11相比沒有明顯的差異。與野生型菌株相比,Δznf1產孢量略微增多,不能形成附著胞,不能穿透寄主表皮和進行侵染生長,說明病菌的這些發育階段受Znf1調控,但調控的基因可能未被篩選到。此外,有小部分基因無論是在Guy11還是Δznf1或Δpmk1中表達豐度都較低,這可能與這些基因呈階段特異性表達有關。因此,在后續的研究中可對Δznf1在分生孢子、附著胞形成的不同階段、侵染階段的樣品進行RNA-Seq測序,獲得差異表達基因,并與本試驗的數據比較分析,獲得階段性受Znf1調控的基因,為更系統深入的研究稻瘟病菌致病分子機理提供參考數據。
利用RNA-Seq技術獲得了Δznf1在營養生長階段709個差異表達基因的信息,其中一些稻瘟病菌致病相關基因以及附著胞階段表達水平升高的基因受Znf1調控;397個基因受Znf1和Pmk1共同調控。研究結果為進一步明確稻瘟病菌Znf1轉錄調控機制以及挖掘新的稻瘟病菌致病相關基因提供了數據資源。
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(責任編輯 岳梅)
Analysis of RNA-Seq-Based Expression Profiles of Δznf1 Mutants in Magnaporthe oryzae
YUE Xiao-feng, QUE Ya-wei, WANG Zheng-yi
(State Key Laboratory for Rice Biology, Institute of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058)
【Objective】Magnaporthe oryzae is the causal agent of rice blast, which is one of the most important disease threatening the production of cultivated rice worldwide. Appressorium-mediated penetration is a key step in the disease cycle of thefungus. Previously, it was reported that a C2H2zinc finger transcription factor encoded by ZNF1 is essential for appressorium development, penetration and pathogenicity in the rice blast fungus. The objective of this study is to understand the regulatory mechanism of Znf1 and reveal the genes transcriptionally regulated by Znf1, thus providing new clues for further investigating molecular mechanism of pathogenicity in this fungus. 【Method】The transcriptome profiles of vegetative mycelia of the wild-type strain Guy11 and a Δznf1 mutant were assayed with the RNA-Seq technique. The gene expression levels were calculated using the FPKM method. The criteria of false discovery rate (FDR)≤0.001 and absolute value of log2ratio≥1 were used to identify differentially expressed genes (DEGs). The sequences of the DEGs were subjected to BLAST queries against the gene ontology (GO) database and KEGG pathway database to predict their biological function and pathways. In order to define in more detail about the sub-set of genes regulated by Znf1, transcriptome profiles of a mutant lacking the PMK1 MAP kinase-encoding gene was also analyzed based on the RNA-Seq technique. To identify the genes regulated by both Znf1 and Pmk1, the DEGs between Δznf1 and Δpmk1 were compared. In addition, the genes highly expressed during appressorium formation but down-regulated in either Δznf1 or Δpmk1 were obtained by comparison with the previous transcriptional profile data. 【Result】 Totally, 709 DEGs in the Δznf1 mutant, including 299 up-regulated and 410 down-regulated genes, were identified by comparison with the wild-type strain Guy11. Gene ontology enrichment analysis showed that 118, 299 and 308 DEGs were classified into cellular component, molecular function and biological process, respectively. KEGG pathway enrichment analysis revealed that the DEGs were mainly involved in metabolic pathways, biosynthesis of secondary metabolites and glycerophospholipid metabolism. Several known pathogenicity-related genes, including LPP3, HOX7, PBS2 and MPG1, were found down-regulated in Δznf1. The comparison of DEGs showed that about 56% DEGs in Δznf1 shared identical to those in Δpmk1. Three isotrichodermin C-15 hydroxylase encoding genes, MGG_03825, MGG_02329 and MGG_08498, were significantly down-regulated in both Δznf1 and Δpmk1. In addition, 48 genes up-regulated during appressorium formation were down-regulated in the two mutants, indicating that these putative appressorium-associated genes were regulated directly or indirectly by Znf1 and Pmk1. To confirm the reliability of the RNA-Seq data, 10 DEGs were randomly selected for qRT-PCR. The results showed that the expression patterns in qRT-PCR were consistent with those in RNA-Seq.【Conclusion】 The expression profiling data and predicted molecular function of Znf1-dependent DEGs were obtained by RNA-Seq technique. Several pathogenicity-associated genes were regulated by Znf1. Additionally, several genes highly expressed during appressoria formation were also regulated by Znf1 as well as Pmk1. This study provided valuable information for further research on Znf1 downstream gene regulatory network.
rice; Magnaporthe oryzae; appressorium; Δznf1; RNA-Seq; differentially expressed genes
2016-06-08;接受日期:2016-07-11
國家重點基礎研究發展計劃(“973”計劃)(2012CB114002)、國家自然科學基金(31370172)
聯系方式:岳曉鳳,Tel:13515713893;E-mail:xiaofengl19870207@163.com。通信作者王政逸,Tel:0571-88982042;E-mail:zhywang@zju.edu.cn