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      基于55K SNP芯片的普通小麥穗長(zhǎng)非條件和條件QTL分析

      2022-05-16 05:17:20唐華蘋陳黃鑫李聰茍璐璐譚翠牟楊唐力為蘭秀錦魏育明馬建
      關(guān)鍵詞:穗長(zhǎng)穗數(shù)株系

      唐華蘋,陳黃鑫,李聰,茍璐璐,譚翠,牟楊,唐力為,蘭秀錦,魏育明,馬建*

      基于55K SNP芯片的普通小麥穗長(zhǎng)非條件和條件QTL分析

      唐華蘋1,陳黃鑫1,李聰1,茍璐璐1,譚翠2,牟楊1,唐力為3,蘭秀錦1,魏育明1,馬建1*

      1四川農(nóng)業(yè)大學(xué)小麥研究所,成都 611130;2四川農(nóng)業(yè)大學(xué)動(dòng)物營(yíng)養(yǎng)研究所,成都 611130;3攀枝花市農(nóng)林科學(xué)研究院,四川攀枝花 617061

      【目的】進(jìn)一步挖掘小麥穗長(zhǎng)具有利用價(jià)值的數(shù)量遺傳位點(diǎn)(QTL),同時(shí)深入探究穗長(zhǎng)與其他重要農(nóng)藝性狀之間的遺傳關(guān)系,為精細(xì)定位和分子輔助選擇育種奠定基礎(chǔ)?!痉椒ā恳?0828為母本、SY95-71為父本,構(gòu)建126份F7代重組自交系群體。將親本及其重組自交系分別于2016—2017年和2017—2018年生長(zhǎng)季種植在中國(guó)四川省成都市溫江區(qū)試驗(yàn)基地、中國(guó)四川省崇州市試驗(yàn)基地、中國(guó)四川省雅安市試驗(yàn)基地以及孟加拉國(guó)庫(kù)爾納市試驗(yàn)田,調(diào)查7個(gè)不同環(huán)境下的穗長(zhǎng)表型。利用基于小麥55K SNP芯片構(gòu)建的遺傳連鎖圖譜進(jìn)行非條件QTL的定位,并分析其效應(yīng)。分別以株高、穗莖長(zhǎng)、每穗小穗數(shù)和千粒重為條件,對(duì)定位到的主效QTL進(jìn)行條件QTL分析,分析穗長(zhǎng)與它們的遺傳關(guān)系?!窘Y(jié)果】通過(guò)非條件QTL定位到13個(gè)穗長(zhǎng)QTL,分別位于1A、1D、2B、2D、4B、6D和7A染色體,LOD值為2.79—6.19,貢獻(xiàn)率為5.35%—12.77%。其中,定位到3個(gè)穩(wěn)定遺傳的主效QTL:、和,貢獻(xiàn)率分別為6.54%—11.72%、10.16%—12.57%和5.35%—10.92%。這三個(gè)主效QTL在多環(huán)境分析中也可以檢測(cè)到。進(jìn)一步聚合分析表明,聚合、和增效位點(diǎn)的株系穗長(zhǎng)表型顯著長(zhǎng)于聚合任意2個(gè)主效QTL或僅含單個(gè)主效QTL增效位點(diǎn)的株系。同時(shí),發(fā)現(xiàn)對(duì)于株高、穗莖長(zhǎng)、每穗小穗數(shù)和千粒重均沒(méi)有顯著影響,對(duì)于千粒重有顯著影響,達(dá)到3.98%,而對(duì)于株高、穗莖長(zhǎng)和每穗小穗數(shù)沒(méi)有顯著影響,對(duì)于株高和穗莖長(zhǎng)有極顯著影響,分別達(dá)到-12.28%和-22.26%,而對(duì)于每穗小穗數(shù)和千粒重沒(méi)有顯著影響。條件QTL分析結(jié)果表明,在QTL水平上,與株高和穗莖長(zhǎng)無(wú)關(guān),但受到每穗小穗數(shù)和千粒重的影響,與穗莖長(zhǎng)、每穗小穗數(shù)和千粒重?zé)o關(guān),但受到株高的影響,與穗莖長(zhǎng)和千粒重?zé)o關(guān),但受到株高和每穗小穗數(shù)的影響?!窘Y(jié)論】定位到3個(gè)控制穗長(zhǎng)且穩(wěn)定遺傳的主效QTL——、和。其中,可能為新的QTL,獨(dú)立于株高和穗莖長(zhǎng)遺傳。

      普通小麥;55K SNP芯片;穗長(zhǎng);非條件QTL;條件QTL

      0 引言

      【研究意義】小麥的營(yíng)養(yǎng)物質(zhì)由各種碳水化合物、蛋白質(zhì)和脂肪分子組成,作為全球糧食供應(yīng)的關(guān)鍵,小麥為人類營(yíng)養(yǎng)來(lái)源提供了約20%的卡路里和蛋白質(zhì)[1-3]。自21世紀(jì)以來(lái),人口的不斷劇增導(dǎo)致產(chǎn)量供不應(yīng)求。高產(chǎn)、穩(wěn)產(chǎn)逐漸成為現(xiàn)代小麥育種的重要目標(biāo),對(duì)其產(chǎn)量相關(guān)農(nóng)藝性狀進(jìn)行遺傳改良,是實(shí)現(xiàn)這一目標(biāo)的有效途徑之一[4]。小麥的穗長(zhǎng)不僅是株型重要的組成部分,也是關(guān)鍵的穗部性狀,與產(chǎn)量高度相關(guān)。因此,進(jìn)一步挖掘穗長(zhǎng)相關(guān)的數(shù)量遺傳位點(diǎn)(QTL),研究穗長(zhǎng)與其他農(nóng)藝性狀的遺傳關(guān)系,有利于提高小麥現(xiàn)代分子育種效率?!厩叭搜芯窟M(jìn)展】關(guān)于穗長(zhǎng)的非條件QTL定位已有大量研究。JI等[5]利用BSE-Seq分析方法對(duì)極端混池進(jìn)行基因分型,在5A染色體上初步定位到了,貢獻(xiàn)7.88%—26.60%的表型變異。Li等[6]利用小麥55K SNP芯片鑒定和驗(yàn)證了2個(gè)控制穗密度和穗長(zhǎng)的主效QTL,對(duì)株高、千粒重和粒長(zhǎng)具有多效性效應(yīng)。Zhou等[7]基于9K SNP芯片檢測(cè)到9個(gè)穗長(zhǎng)QTL,最高解釋23.60%的貢獻(xiàn)率。Liu等[8]利用全基因組關(guān)聯(lián)分析在192個(gè)小麥品系和地方品種中檢測(cè)到51個(gè)與穗長(zhǎng)相關(guān)的顯著SNP位點(diǎn)。Zhai等[9]結(jié)合SNP和SSR標(biāo)記構(gòu)建遺傳連鎖圖譜,檢測(cè)到30個(gè)穗長(zhǎng)QTL。利用條件QTL解析遺傳關(guān)系,可以從QTL水平更加深入解析不同關(guān)聯(lián)性狀之間的遺傳關(guān)系[10-11]。例如,Li等[12]等通過(guò)條件QTL分析發(fā)現(xiàn),確定控制穗莖長(zhǎng)的獨(dú)立于株高遺傳。Zhang等[13]檢測(cè)到與產(chǎn)量三要素相關(guān)的33個(gè)非條件QTL和59個(gè)條件QTL,可解釋4.48%—34.07%的表型變異,發(fā)現(xiàn)可在不影響千粒重和小穗數(shù)的情況下改良穗粒數(shù)。Fan等[14]結(jié)合非條件QTL和條件QTL定位分析不同氮處理下小麥穗部性狀的多效QTL區(qū),結(jié)果表明,在缺氮條件下,和能通過(guò)積累優(yōu)良等位基因維持理想的小穗育性和粒數(shù)。【本研究切入點(diǎn)】穗長(zhǎng)相關(guān)的QTL較多,然而能夠真正運(yùn)用于生產(chǎn)實(shí)際的卻很少[15]。與此同時(shí),針對(duì)穗長(zhǎng)與其他株型性狀和產(chǎn)量性狀之間的條件QTL研究也較少,其遺傳關(guān)系并不清晰[16-18]?!緮M解決的關(guān)鍵問(wèn)題】本研究以小麥品系20828和SY95-71為親本構(gòu)建的128份(含親本)重組自交系(RIL)群體為材料,利用55K SNP芯片構(gòu)建遺傳連鎖圖譜,通過(guò)非條件QTL進(jìn)一步挖掘穗長(zhǎng)穩(wěn)定遺傳的主效QTL,并分析其效應(yīng),同時(shí)結(jié)合條件QTL分析,分析穗長(zhǎng)與2個(gè)株型相關(guān)性狀株高和穗莖長(zhǎng)以及2個(gè)產(chǎn)量相關(guān)性狀每穗小穗數(shù)和千粒重之間的遺傳關(guān)系,為精細(xì)定位和分子輔助選擇育種奠定基礎(chǔ)。

      1 材料與方法

      1.1 試驗(yàn)材料

      試驗(yàn)材料為20282×SY95-71通過(guò)單籽粒傳法構(gòu)建的F7代RIL群體(2SY群體),包含親本共128個(gè)株系。20828(G214-5/3/川育19//Lang 9247/50788)是由中國(guó)科學(xué)院成都生物研究所創(chuàng)制的一個(gè)品系,穗型較好,每穗小穗數(shù)在多年多點(diǎn)的表型鑒定中介于25.67—30.50,而SY95-71(Eronga 83/繁6//繁6)由四川農(nóng)業(yè)大學(xué)小麥研究所創(chuàng)制并保存,穗型較差,每穗小穗數(shù)介于19.00—22.00[19-21]。兩者均是普通小麥(圖1)。

      圖1 2SY群體親本和部分株系的穗長(zhǎng)

      1.2 試驗(yàn)設(shè)計(jì)和表型評(píng)估

      在小麥成熟期,對(duì)2SY群體的親本及其RIL分別于2017年在中國(guó)四川省成都市溫江區(qū)試驗(yàn)基地(E1)、中國(guó)四川省崇州市試驗(yàn)基地(E2)和中國(guó)四川省雅安市試驗(yàn)基地(E3),于2018年在中國(guó)四川省成都市溫江區(qū)試驗(yàn)基地(E4)、中國(guó)四川省崇州市試驗(yàn)基地(E5)、中國(guó)四川省雅安市試驗(yàn)基地(E6)和孟加拉國(guó)庫(kù)爾納市試驗(yàn)田(E7)進(jìn)行多年多環(huán)境下穗長(zhǎng)的表型鑒定。播種方法按前人描述[22]進(jìn)行,每個(gè)株系種植在1.5 m寬的單行中,行間間隔0.3 m,播種密度為15粒/行,行內(nèi)種子間隔0.1 m,田間管理按照當(dāng)?shù)爻R?guī)生產(chǎn)方式進(jìn)行。選取生長(zhǎng)勢(shì)一致的至少3個(gè)單株,使用直尺測(cè)量每個(gè)單株的主穗穗長(zhǎng)(不包括芒長(zhǎng))。試驗(yàn)所用2SY群體穗長(zhǎng)的最佳線性無(wú)偏預(yù)測(cè)值(BLUP)在課題組前期文章中已用作相關(guān)性分析,單個(gè)生態(tài)環(huán)境的數(shù)據(jù)未公布[12];而2SY群體株高[22]、穗莖長(zhǎng)[12]、每穗小穗數(shù)[21]和千粒重[23]的BLUP來(lái)自課題組已發(fā)表的文章。

      1.3 遺傳圖譜構(gòu)建和QTL檢測(cè)

      試驗(yàn)使用Liu等[22]基于55K SNP芯片構(gòu)建的高密度遺傳連鎖圖譜。運(yùn)用IciMapping 4.1(https:// www.isbreeding.net/),設(shè)置PIN=0.001、Step=1 cM、LOD≥2.5,利用完備區(qū)間作圖法進(jìn)行穗長(zhǎng)的非條件QTL檢測(cè),設(shè)置PIN=0.001、Step=1 cM、LOD≥7進(jìn)行穗長(zhǎng)的多環(huán)境分析。利用中國(guó)春參考基因組2.1[24]查詢前人報(bào)道的QTL物理位置,并與本試驗(yàn)所定位到的QTL進(jìn)行比較。定位到的QTL命名遵循國(guó)際常用命名方法(https://wheat.pw.usda.gov/ggpages/wgc/98/ Intro.htm)。

      使用QGAStation 2.0計(jì)算以株高、穗莖長(zhǎng)、每穗小穗數(shù)和千粒重為條件的穗長(zhǎng)條件表型值(SL|PH、SL|SEL、SL|SNS和SL|TGW),利用IciMapping 4.1,設(shè)置PIN=0.001、Step=1 cM、LOD≥2.5,對(duì)條件表型值的條件QTL進(jìn)行分析。條件表型值(T1|T2)表示以性狀T2為條件的性狀T1。條件QTL分析中,以T2為條件的T1條件QTL與T1非條件QTL具有相似加性效應(yīng)值和LOD值時(shí),則認(rèn)為該QTL與T2無(wú)關(guān),而條件QTL與其非條件QTL的加性效應(yīng)值和LOD值明顯降低或增加時(shí),則認(rèn)為該QTL受到T2的影響。

      1.4 統(tǒng)計(jì)分析

      運(yùn)用Microsoft Excel 2016計(jì)算不同環(huán)境下穗長(zhǎng)表型的平均值和標(biāo)準(zhǔn)差。利用SAS 9.1.3的MIXED進(jìn)程計(jì)算不同環(huán)境下穗長(zhǎng)表型的BLUP。廣義遺傳力(2)公式2=VG/(VG+VE),其中,VG表示遺傳方差,VE表示環(huán)境方差。使用IBM SPSS Statistics 27計(jì)算不同環(huán)境下穗長(zhǎng)表型的偏度和峰度以及分析數(shù)據(jù)之間的顯著性水平。使用Origin 2021繪制數(shù)據(jù)相關(guān)的頻率分布圖和箱線圖。

      2 結(jié)果

      2.1 穗長(zhǎng)的表型變異

      對(duì)2SY群體穗長(zhǎng)在不同環(huán)境中的表型數(shù)據(jù)進(jìn)行評(píng)價(jià)。在E1—E7中,親本20828的穗長(zhǎng)平均值為11.28— 15.60 cm,親本SY95-71的穗長(zhǎng)平均值為7.54—9.83 cm,兩者在所有環(huán)境中均呈現(xiàn)極顯著差異(表1,<0.01)。穗長(zhǎng)的頻率分布在所有環(huán)境中呈現(xiàn)近似正態(tài)分布,且其偏度和峰度均趨于0,符合典型的數(shù)量性狀特點(diǎn)(表1和圖2)。同時(shí),穗長(zhǎng)的廣義遺傳力為0.63,表明穗長(zhǎng)受遺傳因素的影響大于環(huán)境因素(表1)。此外,對(duì)不同環(huán)境下穗長(zhǎng)之間進(jìn)行相關(guān)性分析,發(fā)現(xiàn)其Pearson相關(guān)系數(shù)為0.192—0.867,除在環(huán)境E4和E7、E5和E7之間為顯著相關(guān)外(<0.01),其余均為極顯著相關(guān)(表2,<0.01)。

      表1 2SY群體親本及其RIL穗長(zhǎng)表型變異

      E1:2017年中國(guó)四川省成都市溫江區(qū)試驗(yàn)基地;E2:2017年中國(guó)四川省崇州市試驗(yàn)基地;E3:2017年中國(guó)四川省雅安市試驗(yàn)基地;E4:2018年中國(guó)四川省成都市溫江區(qū)試驗(yàn)基地;E5:2018年中國(guó)四川省崇州市試驗(yàn)基地;E6:2018年中國(guó)四川省雅安市試驗(yàn)基地;E7:2018年孟加拉國(guó)庫(kù)爾納市試驗(yàn)田。**:在0.01水平差異顯著。下同

      E1: Wenjiang experiment base, Chengdu, Sichuan Province, China in 2017; E2: Chongzhou experiment base, Sichuan Province, China in 2017; E3: Ya'an experiment base, Sichuan Province, China in 2017; E4: Wenjiang experiment base, Chengdu, Sichuan, China in 2018; E5: Chongzhou experiment base, Sichuan Province, China in 2018; E6: Ya'an experiment base, Sichuan Province, China in 2018; E7: Experiment field in Khulna, Bangladesh in 2018.**: The significant difference at 0.01 levels.The same as below

      表2 2SY群體的穗長(zhǎng)在不同環(huán)境中的相關(guān)性

      *:在0.05水平差異顯著 *: The significant difference at 0.05 levels

      2.2 非條件QTL定位和效應(yīng)分析

      基于2SY群體已有的遺傳連鎖圖譜[22],結(jié)合2年7個(gè)環(huán)境的穗長(zhǎng)表型數(shù)據(jù),共鑒定到13個(gè)控制穗長(zhǎng)的非條件QTL,分布在1A、1D、2B、2D、4B、6D和7A染色體,貢獻(xiàn)率為5.35%—12.77%(表3)。其中,可在E4、E5和BLUP中檢測(cè)到,提供了6.54%—11.72%的貢獻(xiàn)率,正效應(yīng)位點(diǎn)來(lái)源于SY95-71;可在E1、E4和BLUP中檢測(cè)到,貢獻(xiàn)率為10.16%—12.57%,正效應(yīng)等位位點(diǎn)來(lái)源于20828;可在E3、E4和E5中檢測(cè)到,提供5.35%—10.92%的貢獻(xiàn)率,正效應(yīng)位點(diǎn)來(lái)源于20828。同時(shí),、和可在多環(huán)境分析中檢測(cè)到的,表明這3個(gè)QTL不易受環(huán)境影響,為穩(wěn)定的主效QTL(表4)。其余10個(gè)非條件QTL僅能在單個(gè)環(huán)境中檢測(cè)到,易受環(huán)境影響,貢獻(xiàn)率為7.26%—12.77%(表3)。

      E1:2017年中國(guó)四川省成都市溫江區(qū)試驗(yàn)基地;E2:2017年中國(guó)四川省崇州市試驗(yàn)基地;E3:2017年中國(guó)四川省雅安市試驗(yàn)基地;E4:2018年中國(guó)四川省成都市溫江區(qū)試驗(yàn)基地;E5:2018年中國(guó)四川省崇州市試驗(yàn)基地;E6:2018年中國(guó)四川省雅安市試驗(yàn)基地;E7:2018年孟加拉國(guó)庫(kù)爾納市試驗(yàn)田

      利用主效QTL側(cè)翼標(biāo)記的基因型,將RIL分為攜帶和不攜帶目標(biāo)QTL增效位點(diǎn)的2種類型。結(jié)合穗長(zhǎng)數(shù)據(jù)的BLUP對(duì)其主效QTL的聚合效應(yīng)進(jìn)行分析(圖3)。結(jié)果表明,僅攜帶或單個(gè)主效QTL增效位點(diǎn)株系的穗長(zhǎng)顯著長(zhǎng)于不攜帶任何QTL增效位點(diǎn)的株系;攜帶任意2個(gè)主效QTL增效位點(diǎn)株系的穗長(zhǎng)均顯著長(zhǎng)于不含任何QTL增效位點(diǎn)的株系;攜帶和或和增效位點(diǎn)株系的穗長(zhǎng)顯著長(zhǎng)于僅含增效位點(diǎn)的株系;同時(shí)攜帶、和增效位點(diǎn)株系的穗長(zhǎng)顯著長(zhǎng)于攜帶任意2個(gè)主效QTL株系或僅含單個(gè)主效QTL增效位點(diǎn)株系的穗長(zhǎng)(圖3)。同時(shí),結(jié)合2SY群體株高、穗莖長(zhǎng)、每穗小穗數(shù)和千粒重?cái)?shù)據(jù)的BLUP,分析主效QTL對(duì)其可能存在的影響(圖4)。結(jié)果發(fā)現(xiàn)對(duì)于株高、穗莖長(zhǎng)、每穗小穗數(shù)和千粒重均沒(méi)有顯著影響。對(duì)于千粒重有顯著影響(<0.05),達(dá)到3.98%,而對(duì)于株高、穗莖長(zhǎng)和每穗小穗數(shù)沒(méi)有顯著影響。對(duì)于株高和穗莖長(zhǎng)有極顯著影響(<0.05),分別達(dá)到-12.28%和-22.26%,而對(duì)于每穗小穗數(shù)和千粒重沒(méi)有顯著影響(圖4)。

      2.3 條件QTL分析

      分別以2個(gè)株型相關(guān)性狀株高、穗莖長(zhǎng)以及2個(gè)產(chǎn)量相關(guān)性狀每穗小穗數(shù)和千粒重的BLUP為條件,對(duì)穗長(zhǎng)進(jìn)行條件QTL分析。通過(guò)比較穗長(zhǎng)的BLUP在條件與非條件下QTL之間加性效應(yīng)值和LOD值的變化,分析株高、穗莖長(zhǎng)、每穗小穗數(shù)和千粒重與穗長(zhǎng)之間的遺傳關(guān)系(表5)。

      在條件QTL分析中,共檢測(cè)到18個(gè)控制穗長(zhǎng)的條件QTL,分布在2B、2D、4B、6B、7A和7D染色體上,貢獻(xiàn)率為6.07%—12.29%(表5)。和無(wú)論在條件與非條件QTL中均可檢測(cè)到。其中,在以株高和穗莖長(zhǎng)為條件下的加性效應(yīng)值和LOD值與非條件下相似,而在以每穗小穗數(shù)和千粒重為條件下的加性效應(yīng)值和LOD值明顯下降,表明與株高和穗莖長(zhǎng)無(wú)關(guān),而受到每穗小穗數(shù)和千粒重的影響。在以穗莖長(zhǎng)、每穗小穗數(shù)和千粒重為條件下的加性效應(yīng)值和LOD值與非條件下相似,而在以株高為條件下時(shí)明顯下降,表明與穗莖長(zhǎng)、每穗小穗數(shù)和千粒重?zé)o關(guān),但受到株高的影響(表5)。在非條件下的BLUP中未檢測(cè)到,而在以株高和每穗小穗數(shù)為條件下能夠檢測(cè)到,以穗莖長(zhǎng)和千粒重為條件下未檢測(cè)到,表明其與穗莖長(zhǎng)和千粒重?zé)o關(guān),而受到了株高和小穗數(shù)的影響(表5)。

      +和?:攜帶和不攜帶目標(biāo)QTL增效位點(diǎn)的株系;#RILs:相應(yīng)株系的數(shù)量;a、b、c和d代表顯著性差異。下同

      表3 2SY群體穗長(zhǎng)的非條件QTL

      表4 2SY群體穗長(zhǎng)的多環(huán)境QTL

      LOD(A):顯性和加性效應(yīng);LOD(AbyE):環(huán)境對(duì)加性和顯性效應(yīng)的影響;PVE(A):加性和顯性效應(yīng)的貢獻(xiàn)率;PVE(AbyE):環(huán)境對(duì)加性和顯性效應(yīng)的貢獻(xiàn)率

      LOD(A): Dominant and additive effects; LOD(AbyE): The influence of environment on additive and dominant effects; PVE(A): Contribution of additive and dominant effects; PVE(AbyE): Contribution of environment to additive and dominant effects

      a—d:QSl-sau-2SY-2B對(duì)于株高、穗莖長(zhǎng)、每穗小穗數(shù)和千粒重的影響,+:包含50個(gè)株系,?:包含60個(gè)株系。e—h:QSl-sau-2SY-2D.5對(duì)于株高、穗莖長(zhǎng)、每穗小穗數(shù)和千粒重的影響,+:包含40個(gè)株系,?:包含46個(gè)株系。i—l:QSl-sau-2SY-4B對(duì)于株高、穗莖長(zhǎng)、每穗小穗數(shù)和千粒重的影響,+:包含43個(gè)株系,?:包含61個(gè)株系。*和**:在0.05和0.01水平上差異顯著

      3 討論

      3.1 與前人研究的比較分析

      比較本研究中穗長(zhǎng)的主效QTL與前人研究已報(bào)道的QTL在中國(guó)春參考基因組2.1[24]上的物理位置時(shí),發(fā)現(xiàn)定位于標(biāo)記之間,與[25]、[26]和[8]等均無(wú)重疊部分,因此,可能是新的QTL位點(diǎn)。定位于標(biāo)記之間,定位于標(biāo)記之間,分別與李聰?shù)萚27]研究中的和物理位置有重疊的部分,且均使用共同親本20828構(gòu)建的群體,說(shuō)明這些QTL極有可能是同一位點(diǎn),側(cè)面驗(yàn)證了其真實(shí)性和有效性。

      表5 2SY群體穗長(zhǎng)的條件QTL條件

      T1|T2:條件表型值;SL|PH、SL|SEL、SL|SNS和SL|TGW:以株高、穗莖長(zhǎng)、每穗小穗數(shù)和千粒重為條件下的穗長(zhǎng)條件表型值;-:條件QTL結(jié)果中沒(méi)有相應(yīng)的主效非條件QTL;非條件QTL的LOD、PVE和Add為BLUP下的結(jié)果

      T1|T2: Conditional phenotype values; SL|PH, SL|SEL, SL|SNS and SL|TGW: The conditional phenotypic values of spike length under the conditions of plant height, spike extension length, spikelet number per spike and thousand-kernel weight; -: There was no corresponding major unconditional QTL in conditional QTL results; LOD, PVE and Add of unconditional QTL was calculated based on BLUP

      穗長(zhǎng)和株型、產(chǎn)量相關(guān)農(nóng)藝性狀之間有著很強(qiáng)的關(guān)聯(lián)性,控制其相關(guān)的基因也是高度相關(guān)的,甚至由同一基因調(diào)控[28]。因此,比較與2B染色體上的[29]、與4B染色體上的[30]的物理位置,發(fā)現(xiàn)它們的距離非常接近,有可能為同一位點(diǎn)。同時(shí),發(fā)現(xiàn)本研究中穗長(zhǎng)的主效位點(diǎn)與株高的主效位點(diǎn)[22]和穗莖長(zhǎng)的主效位點(diǎn)[12]存在共定位,而與每穗小穗數(shù)的主效位點(diǎn)[21]、千粒重的主效位點(diǎn)[23]沒(méi)有共定位。對(duì)于這些“一因多效”的位點(diǎn),還需進(jìn)一步深入挖掘基因來(lái)探索其關(guān)系。

      3.2 聚合育種的前景

      聚合育種在聚合不同抗性基因方面的研究很多。由于生理小種的多樣和環(huán)境的復(fù)雜,僅含單個(gè)抗病基因的品種抗性并不能長(zhǎng)久維持,因此聚合多個(gè)抗病基因有利于提高品種抗病的廣譜性和持久性[31-32]。相對(duì)應(yīng)的,大多數(shù)QTL的遺傳效應(yīng)不高,被運(yùn)用到分子輔助選擇育種時(shí),會(huì)出現(xiàn)表型提升不夠顯著的情況,而聚合育種是有效提高分子輔助效率的手段之一。例如,Qu等[23]利用側(cè)翼標(biāo)記基因型,分析3個(gè)粒長(zhǎng)QTL的聚合效應(yīng),發(fā)現(xiàn)同時(shí)攜帶3個(gè)主效QTL可以顯著提升表型。在本研究非條件QTL定位的3個(gè)主效穗長(zhǎng)QTL中,僅攜帶1個(gè)主效QTL增效位點(diǎn)時(shí)的效應(yīng)最大;聚合2個(gè)QTL增效位點(diǎn)時(shí)選擇和對(duì)表型有顯著提升;同時(shí)聚合、和增效位點(diǎn)的株系穗長(zhǎng)表型顯著長(zhǎng)于聚合任意2個(gè)主效QTL或僅含單個(gè)主效QTL增效位點(diǎn)的株系(圖3)。這一結(jié)果進(jìn)一步說(shuō)明了聚合育種可以促進(jìn)穗長(zhǎng)的遺傳改良。然而,聚合多個(gè)QTL來(lái)提升表型并非基因的簡(jiǎn)單累加,基因具體如何起到作用仍需深入探究其分子機(jī)制才能揭示其原理。

      3.3 穗長(zhǎng)與其他農(nóng)藝性狀的遺傳關(guān)系

      小麥產(chǎn)量相關(guān)農(nóng)藝性狀的遺傳基礎(chǔ)非常復(fù)雜,受到眾多性狀的影響和調(diào)節(jié),使用條件QTL分析方法可以從QTL水平解析性狀與其構(gòu)成因素之間的遺傳關(guān)系[13, 33-34]。例如,Cui等[16]基于2個(gè)定位群體的條件QTL分析株高與其組成成分穗長(zhǎng)和節(jié)間長(zhǎng)之間的遺傳關(guān)系,結(jié)果表明,在QTL水平上,穗長(zhǎng)對(duì)株高的貢獻(xiàn)最小,其次是第一節(jié)間長(zhǎng)度;第二節(jié)間長(zhǎng)度對(duì)株高的影響最大,第三節(jié)間長(zhǎng)度和第四節(jié)間長(zhǎng)度次之。而本研究基于穗長(zhǎng)的條件QTL結(jié)果,分析穗長(zhǎng)與2個(gè)株型相關(guān)性狀株高、穗莖長(zhǎng)以及2個(gè)產(chǎn)量相關(guān)性狀每穗小穗數(shù)、千粒重之間的遺傳關(guān)系。結(jié)果表明,在QTL水平上,與株高和穗莖長(zhǎng)無(wú)關(guān),但受到每穗小穗數(shù)和千粒重的影響。與穗莖長(zhǎng)、每穗小穗數(shù)和千粒重?zé)o關(guān),但受到株高的影響。與穗莖長(zhǎng)和千粒重?zé)o關(guān),但受到株高和每穗小穗數(shù)的影響。此外,利用穗長(zhǎng)主效位點(diǎn)、和緊密連鎖的側(cè)翼標(biāo)記基因型分析它們對(duì)于其他農(nóng)藝性狀的影響。發(fā)現(xiàn)對(duì)于株高、穗莖長(zhǎng)、每穗小穗數(shù)和千粒重沒(méi)有顯著影響,對(duì)于千粒重有顯著影響,對(duì)于株高和穗莖長(zhǎng)有極顯著影響,表明是一個(gè)單獨(dú)控制穗長(zhǎng)的QTL,可能有助于產(chǎn)量的提升,在影響株型的方面起著重要作用。穗長(zhǎng)與株高、穗莖長(zhǎng)、每穗小穗數(shù)和千粒重在QTL水平上遺傳關(guān)系的揭示,結(jié)合非條件QTL的分析結(jié)果,加深了對(duì)穗長(zhǎng)遺傳基礎(chǔ)的認(rèn)識(shí),可為未來(lái)穗長(zhǎng)的遺傳改良提供理論依據(jù)。

      4 結(jié)論

      定位到3個(gè)控制穗長(zhǎng)且穩(wěn)定遺傳的主效QTL——、和,貢獻(xiàn)率分別為6.54%—11.72%、10.16%—12.57%和5.35%—10.92%。其中,可能為新的QTL。聚合這3個(gè)主效QTL增效位點(diǎn)的株系穗長(zhǎng)表型顯著長(zhǎng)于聚合任意2個(gè)主效QTL或僅含單個(gè)主效QTL增效位點(diǎn)的株系。對(duì)于株高、穗莖長(zhǎng)、每穗小穗數(shù)和千粒重沒(méi)有顯著影響,對(duì)于千粒重有顯著影響,對(duì)于株高和穗莖長(zhǎng)有極顯著影響。在QTL水平上,獨(dú)立于株高和穗莖長(zhǎng)遺傳,獨(dú)立于穗莖長(zhǎng)、每穗小穗數(shù)和千粒重遺傳,獨(dú)立于穗莖長(zhǎng)和千粒重遺傳。

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      Unconditional and Conditional QTL Analysis of Wheat Spike Length in common wheat based on 55K SNP Array

      TANG HuaPing1, CHEN HuangXin1, LI Cong1, GOU LuLu1, TAN Cui2, MU Yang1, TANG LiWei3, LAN XiuJin1, WEI YuMing1, MA Jian1*

      1Triticeae Research Institute, Sichuan Agricultural University, Chengdu 611130;2Institute of Animal Nutrition, Sichuan Agricultural University, Chengdu 611130;3PanZhiHua Academy of Agricultural and Forestry Sciences, Panzhihua 617061, Sichuan

      【Objective】This study is to excavate spike length (SL)-related quantitative trait loci (QTL) with potential breeding value, explore the genetic relationship between SL and other important agronomic traits in wheat, and aim at laying a foundation for fine mapping and molecular-assisted selection breeding.【Method】A total of 126 F7recombinant inbred lines (RIL) constructed by crossing 20828 and SY95-71 were used in this study.The RIL population including their parents were planted in seven different environments for phenotypic evaluation: Wenjiang, Chongzhou, Ya'an of Sichuan Province in China, and Khulna in Bangladesh during 2016-2017 and 2017-2018 growing seasons.Unconditional QTL mapping was performed using a genetic linkage map constructed using the wheat 55K SNP array, and QTLs’ effects were further analyzed.Conditional QTL analysis was performed to analyze the relationship between SL and other agronomic traits including plant height (PH), spike extension length (SEL), spikelet number per spike (SNS) and thousand-kernel weight (TKW).【Result】Thirteen QTLs controlling SL were identified using unconditional QTL mapping, and they were located on chromosomes 1A, 1D, 2B, 2D, 4B, 6D, and 7A.The LOD values ranged from 2.79 to 6.19, and the phenotypic variation rate ranged from 5.35% to 12.77%.Three stable and major QTLs (,and) were identified, and they explained 6.54% to 11.72%, 10.16% to 12.57%, and 5.35% to 10.92% of phenotypic variation rate, respectively.Furthermore, these three major QTLs could be also detected in multi-environment analysis.Moreover, aggregation analysis suggested that the SL of lines polymerizing the positive allels at these three major QTLs was significantly longer than that of those with any two ones or those carrying only one.Meanwhile, it was found thathad no significant effect on PH, SEL, SNS and TKW.had a significant effect on improving TKW (3.98%), but no significant effect on PH, SEL and SNS.had a significant effect on decreasing PH (-12.28%) and SEL (-22.26%), but no significant effect on SNS and TKW.The conditional QTL analysis showed thatwas independent of PH and SEL, whereas, affected by SNS and TKW.was independent of SEL, SNS and TKW, but affected by PH.was independent of SEL and TKW, but affected by PH and SNS.【Conclusion】In this study, three stable and major QTLs were identified for SL:,,and, among whichmay be a novel QTL independent of PH and SEL.

      common wheat; 55K SNP array; spike length; unconditional QTL; conditional QTL

      2021-10-20;

      2021-12-16

      四川省國(guó)際合作交流項(xiàng)目(2021YFH0083)、四川省應(yīng)用基礎(chǔ)研究計(jì)劃(2021YJ0503)

      唐華蘋,E-mail:707952940@qq.com。陳黃鑫,E-mail:1252153393@qq.com。唐華蘋和陳黃鑫為同等貢獻(xiàn)作者。通信作者馬建,E-mail:jianma@sicau.edu.cn

      (責(zé)任編輯 李莉)

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