發(fā)布時(shí)間：2018-05-30 08:01

  本文選題：毛棉 + 種間雜交�。� 參考：《中國農(nóng)業(yè)科學(xué)院》2016年博士論文

【摘要】：中國是世界最大的棉花生產(chǎn)國、消費(fèi)國、進(jìn)口國和紡織品出口國,棉花在國民經(jīng)濟(jì)中起到不可替代的重要作用,也是我國出口創(chuàng)匯的重要商品。由于糧食安全問題,棉花種植區(qū)開始向東部沿海、西北內(nèi)陸及內(nèi)蒙古等鹽堿、旱地轉(zhuǎn)移。棉花屬于耗水作物,干旱抑制棉花地上地下部分生長(zhǎng),對(duì)營養(yǎng)生長(zhǎng)、生殖生長(zhǎng)發(fā)育和光合作用等造成嚴(yán)重影響,最終導(dǎo)致棉花產(chǎn)量下降、品質(zhì)降低。培育抗旱品種是解決旱地植棉的重要途徑,由于栽培種資源遺傳基礎(chǔ)狹窄,難以挖掘到如野生棉具有的優(yōu)異基因,加之傳統(tǒng)育種難以聚合高產(chǎn)、優(yōu)質(zhì)和抗旱等優(yōu)良性狀,而利用相關(guān)基因檢測(cè)及分子標(biāo)記輔助選擇為挖掘野生種優(yōu)異基因提供了有效手段。因此,本研究采用四倍體野生種毛棉和我國黃河流域歷史主栽品種中棉所12為親本進(jìn)行雜交,配制(中棉所12×毛棉)F2作圖群體,并構(gòu)建遺傳連鎖圖譜,通過對(duì)F2:3家系苗期、蕾期、盛花期和盛鈴期抗旱相關(guān)性狀及盛花期的光合性狀進(jìn)行QTL定位,以期揭示毛棉抗旱和光合作用性狀的遺傳基礎(chǔ),檢測(cè)穩(wěn)定的主效QTL,為有效發(fā)掘利用毛棉的優(yōu)異基因,開展抗旱及高光效分子標(biāo)記輔助選擇育種奠定基礎(chǔ)。1.苗期抗旱性狀QTL定位利用復(fù)合區(qū)間作圖法,對(duì)干旱脅迫(W1)及正常灌水(W2)環(huán)境下F2:3群體苗期形態(tài)和生理性狀進(jìn)行QTL定位,共檢測(cè)到41個(gè)形態(tài)和生理性狀QTL。其中,在干旱脅迫下,檢測(cè)到21個(gè)控制形態(tài)和生理性狀的QTL位點(diǎn),包括2個(gè)寬高比、3個(gè)葉片數(shù)、2個(gè)葉面積、5個(gè)株高的形態(tài)性狀QTL位點(diǎn)和2個(gè)葉綠素含量、2個(gè)脯氨酸、5個(gè)丙二醛的生理性狀QTL位點(diǎn),其中13個(gè)增效等位基因來自于毛棉,8個(gè)增效等位基因來自于中棉12,共檢測(cè)到6個(gè)加性QTL,單個(gè)位點(diǎn)可解釋6.93-16.93%的表型變異。在正常灌水下,共檢測(cè)到20個(gè)控制形態(tài)和生理性狀的QTL,包括2個(gè)株寬、6個(gè)寬高比、3個(gè)葉面積、4個(gè)株高的形態(tài)性狀的QTL位點(diǎn)和4個(gè)丙二醛、1個(gè)脯氨酸的生理性狀的QTL位點(diǎn),其中12個(gè)增效等位基因來自于中棉所12,8個(gè)增效等位基因來自于毛棉,共檢測(cè)到5個(gè)加性QTL,單個(gè)位點(diǎn)可解釋6.61-15.19%的表型變異。共檢測(cè)到16個(gè)控制苗期形態(tài)和生理性狀抗旱系數(shù)QTL位點(diǎn),其中與株高、葉片數(shù)、葉綠素含量、脯氨酸含量和丙二醛含量抗旱系數(shù)的QTL位點(diǎn)分別有5個(gè)、1個(gè)、3個(gè)、3個(gè)和4個(gè),其中10個(gè)增效等位基因來自于毛棉,6個(gè)增效等位基因來自于中棉所12,共檢測(cè)到5個(gè)加性QTL,單個(gè)位點(diǎn)可解釋8.60-25.80%的表型變異。2.蕾期、盛花期、盛鈴期抗旱性狀QTL定位利用復(fù)合區(qū)間作圖法,對(duì)2014-2015連續(xù)兩年在干旱脅迫(W1)及正常灌水(W2)條件下F2:3群體蕾期、盛花期和盛鈴期的13個(gè)形態(tài)和生理性狀進(jìn)行QTL定位,總共檢測(cè)到166個(gè)QTL:W1環(huán)境下檢測(cè)到71個(gè)控制形態(tài)及生理性狀的QTL位點(diǎn),其中蕾期包括8個(gè)葉綠素含量、5個(gè)葉面積、10個(gè)葉片數(shù)、7個(gè)株高的QTL位點(diǎn),盛花期包括5個(gè)葉綠素含量、7個(gè)葉鮮重、7個(gè)葉干重、8個(gè)株高的QTL位點(diǎn),盛鈴期包括7個(gè)單鈴重、8個(gè)果枝數(shù)、4個(gè)株高的QTL位點(diǎn),其中31個(gè)增效等位基因來自于毛棉,40個(gè)增效等位基因來自于中棉所12,共檢測(cè)到13個(gè)加性QTL,單個(gè)位點(diǎn)可解釋6.07-13.34%的表型變異;正常灌水(W2)環(huán)境下檢測(cè)到35個(gè)控制形態(tài)和生理性狀的QTL,其中蕾期包括3個(gè)株高、1個(gè)葉片數(shù)、2個(gè)葉面積、4個(gè)葉綠素含量的QTL位點(diǎn),盛花期包括4個(gè)葉鮮重、6個(gè)葉干重、2個(gè)葉綠素含量的QTL位點(diǎn),盛鈴期包括4個(gè)單鈴重、5個(gè)果枝數(shù)、4個(gè)株高的QTL位點(diǎn),其中20個(gè)增效等位基因來自于毛棉,15個(gè)增效等位基因來自于中棉所12,共檢測(cè)到8個(gè)加性QTL,單個(gè)位點(diǎn)可解釋9.2-19.88%的表型變異。共檢測(cè)到24個(gè)控制蕾期形態(tài)和生理性狀抗旱系數(shù)QTL,包括控制8個(gè)葉綠素含量、5個(gè)葉面積、4個(gè)葉片數(shù)和7個(gè)株高的抗旱系數(shù)QTL位點(diǎn),其中9個(gè)增效等位基因來自于毛棉,15個(gè)增效等位基因來自于中棉所12,檢測(cè)到2個(gè)加性QTL,單個(gè)位點(diǎn)可解釋10.93-15.8%的表型變異。共檢測(cè)到9個(gè)控制盛花期形態(tài)和生理性狀抗旱系數(shù)QTL,包括2個(gè)葉綠素含量、6個(gè)株高和1個(gè)葉鮮重的抗旱系數(shù)QTL位點(diǎn),其中6個(gè)增效等位基因來自于毛棉,3個(gè)增效等位基因來自于中棉所12,檢測(cè)到2個(gè)加性QTL,單個(gè)位點(diǎn)可解釋29.73-16.18%的表型變異。共檢測(cè)到27個(gè)控制盛鈴期形態(tài)性狀抗旱系數(shù)QTL,包括5個(gè)單鈴重、5個(gè)果枝數(shù),11個(gè)主莖粗、5個(gè)果枝始節(jié)和1個(gè)株高的抗旱系數(shù)QTL位點(diǎn),其中10個(gè)增效等位基因來自于毛棉,17個(gè)增效等位基因來自于中棉所12,共檢測(cè)到4個(gè)加性QTL,單個(gè)位點(diǎn)可解釋8.41-11.97%的表型變異。2014、2015連續(xù)兩年在干旱脅迫環(huán)境下檢測(cè)到6個(gè)穩(wěn)定的抗旱性狀QTL位點(diǎn),包括1個(gè)控制蕾期葉面積(qBLA-Chr5-1)的QTL位點(diǎn),單個(gè)位點(diǎn)可解釋9.00-13.30%的表型變異;1個(gè)控制蕾期葉綠素含量(qBCC-Chr9-1)的QTL位點(diǎn),1個(gè)控制盛花期葉綠素含量(q FCC-Chr8-1)的QTL位點(diǎn),單個(gè)位點(diǎn)可解釋4.10-16.00%的表型變異;1個(gè)控制單鈴重(qFBBW-Chr16-1)的QTL位點(diǎn),單個(gè)位點(diǎn)可解釋6.4-7.0%的表型變異、2個(gè)控制主莖粗(qFBSD-Chr21-1和qFbsd-Chr21-2)的QTL位點(diǎn),單個(gè)位點(diǎn)可解釋0.8-2.3%的表型變異。11個(gè)QTL簇分布在Chr2、5、6、14、16和21染色體上,其中Chr16染色體上分布了4個(gè)QTL簇。3.光合性狀QTL定位利用復(fù)合區(qū)間作圖法(CIM),對(duì)2014年、2015年干旱脅迫(W1)及正常灌水(W2)兩個(gè)環(huán)境下F2:3家系花鈴期光合性狀QTL進(jìn)行定位,共檢測(cè)到45個(gè)QTL。在干旱脅迫下,檢測(cè)到27個(gè)控制光合性狀的QTL位點(diǎn),包括6個(gè)凈光合速率、2個(gè)胞間CO2濃度、2個(gè)蒸騰速率、5個(gè)氣孔導(dǎo)度、5個(gè)葉片溫度和7個(gè)水分利用率的QTL位點(diǎn),共檢測(cè)到4個(gè)加性QTL,單個(gè)位點(diǎn)可解釋為11.00-13.76%的表型變異。在正常灌水下,共檢測(cè)到18個(gè)控制光合性狀QTL位點(diǎn),包括1個(gè)凈光合速率、3個(gè)胞間CO2濃度、1個(gè)氣孔導(dǎo)度、4個(gè)葉片溫度和9個(gè)水分利用率(WUE)的QTL位點(diǎn),共檢測(cè)到4個(gè)加性QTL,單個(gè)位點(diǎn)可解釋為11.00-13.76%的表型變異。qPn-Chr16-1是在2014、2015連續(xù)兩年在干旱脅迫環(huán)境下檢測(cè)到穩(wěn)定的控制光合速率的QTL位點(diǎn),位于Chr16染色體上,單個(gè)位點(diǎn)可解釋9.44-18.61%的表型變異。qGs-Chr5-1在2015年干旱和正常灌水環(huán)境中檢測(cè)到控制氣孔導(dǎo)度的QTL位點(diǎn),單個(gè)位點(diǎn)可解釋0.66-0.67%的表型變異。
[Abstract]:China is the world's largest cotton producer, consumer, importer and textile exporter. Cotton plays an irreplaceable role in the national economy. It is also an important commodity for China's export of foreign exchange. Because of the problem of food security, the cotton planting area has begun to transfer to the east coast, the northwest inland and Inner Mongolia and other saline alkali, dryland transfer. In water consumption crops, drought inhibits the growth of the upper and subterranean parts of the cotton ground, which has a serious effect on the growth of nutrition, reproductive growth and photosynthesis, and eventually leads to the decrease of cotton yield and quality. It is an important way to solve the cotton planting in dry land. Some excellent genes, in addition to traditional breeding, are difficult to polymerize high yield, high quality and drought resistance, and the use of related gene detection and molecular marker assisted selection provides an effective means for the mining of the excellent genes of wild species. Therefore, this study uses the tetraploid wild wool cotton and the main plant of the the Yellow River basin, China, as a parent. In order to reveal the genetic basis of drought resistance and Photosynthesis Characteristics of cotton wool, the genetic basis of drought resistance and Photosynthesis Characteristics of wool cotton were revealed by using the genetic linkage map of F2 F2 mapping population and genetic linkage map. The genetic basis of the drought resistance and photosynthesis character of wool cotton was revealed, and the stable main effect QTL was detected, which was effectively excavated. Using the excellent genes of wool cotton, the drought resistance and high light efficiency molecular marker assisted selection breeding were used to lay the foundation for the drought resistance of.1. at seedling stage and QTL positioning using compound interval mapping method. The morphological and physiological characters of the seedling stage of F2:3 population in the environment of drought stress (W1) and normal irrigation (W2) were located by QTL, and 41 morphological and physiological traits, QTL., were detected. Under drought stress, the QTL loci of 21 control morphology and physiological characters were detected, including 2 width height ratio, 3 leaf number, 2 leaf area, 5 plant height morphological characters QTL and 2 chlorophyll content, 2 proline and 5 malondialdehyde's physiological character QTL locus, and 13 synergistic alleles from wool cotton and 8 synergistic alleles. Due to a total of 6 additive QTL from China Cotton 12, single loci could explain the phenotypic variation of 6.93-16.93%. Under normal irrigation, 20 QTL of control morphology and physiological characters were detected, including 2 plant width, 6 width to height ratio, 3 leaf area, 4 plant height and 4 malondialdehyde and 1 proline physiological QTL. The 12 alleles of the synergistic allele were derived from the 12,8 allele of CCP from wool cotton, and 5 additive QTL were detected. A single locus could be used to explain the phenotypic variation of 6.61-15.19%. A total of 16 physiological traits controlling the drought resistance coefficient QTL loci were detected, including plant height, leaf number, chlorophyll content and proline content QTL loci and malondialdehyde content resistance coefficient were 5, 1, 3, 3 and 4, of which 10 synergistic alleles came from wool cotton, 6 synergistic alleles came from Mian 12, and 5 additive QTL was detected. Single loci could explain the phenotypic variation of 8.60-25.80% in.2. buds, flowering period, and QTL location and utilization of drought resistance during the flourishing period. In 2014-2015 consecutive years, 13 morphological and physiological characters of F2:3 population under drought stress (W1) and normal irrigation (W2), 13 morphological and physiological characters in full bloom and boll stage were located in 2014-2015 consecutive years. In total, 71 control forms and QTL loci were detected in 166 QTL:W1 environments, including 8 chlorophyll content in buds. The amount, 5 leaf area, 10 leaf number and 7 plant height QTL loci, including 5 chlorophyll content, 7 leaf fresh weight, 7 leaf dry weight, 8 plant high QTL loci, including 7 single bell weight, 8 fruit branches and 4 high QTL loci, of which 31 synergistic alleles come from wool cotton and 40 alleles come from Central Cotton 12, A total of 13 additive QTL were detected, single loci could explain the phenotypic variation of 6.07-13.34%; 35 control morphology and physiological characters were detected in normal irrigation (W2) environment, and bud period included 3 plant height, 1 leaf number, 2 leaf area, 4 chlorophyll content QTL site, 4 leaf fresh weight, 6 leaf dry weight, 2 chlorophyll content in blossom period. The QTL site, which consists of 4 single bolls weight, 5 fruit branches and 4 QTL loci, of which 20 synergistic alleles come from wool cotton, 15 synergistic alleles come from the middle cotton station 12, and 8 additive QTL are detected, and the single locus can explain the phenotypic variation of 9.2-19.88%. A total of 24 control buds and physiological traits are tested for drought resistance. Coefficient QTL, including controlling 8 chlorophyll content, 5 leaf area, 4 leaf number and 7 plant height resistance coefficient QTL loci, of which 9 synergistic alleles come from wool cotton, 15 synergistic alleles come from middle cotton 12, 2 additive QTL, single loci can explain the phenotypic variation of 10.93-15.8%. A total of 9 controlled flowering periods were detected. The drought resistance coefficient QTL of morphological and physiological characters, including 2 chlorophyll content, 6 plant height and 1 leaf fresh weight resistance coefficient QTL loci, 6 synergistic alleles come from wool cotton, 3 synergistic alleles come from the middle cotton station 12, 2 additive QTL, and single loci can explain the phenotypic variation of 29.73-16.18%. A total of 27 controls were detected. The drought resistance coefficient QTL, including 5 single bolls weight, 5 fruit branches, 11 main stems, 5 fruit branches and 1 plant high drought resistance QTL loci, 10 of the synergistic alleles came from wool cotton, 17 synergistic alleles came from the middle cottoninstitute 12, and 4 additive QTL were detected. The single locus could explain the phenotypic variation of 8.41-11.97%. 6 stable Drought Resistant Traits QTL loci were detected by.20142015 for two years under drought stress, including 1 QTL locus to control bud leaf area (qBLA-Chr5-1). Single loci could explain the phenotypic variation of 9.00-13.30%, 1 QTL locus of chlorophyll content (qBCC-Chr9-1) at the bud control period, and 1 chlorophyll content (Q FCC-Chr8-1) during the flowering period (Q FCC-Chr8-1). ) QTL loci, single loci can explain the phenotypic variation of 4.10-16.00%, 1 QTL locus controlling single boll weight (qFBBW-Chr16-1), single loci which can explain the phenotypic variation of 6.4-7.0%, 2 QTL loci for controlling the main stem (qFBSD-Chr21-1 and qFbsd-Chr21-2), and the phenotypic variation of 0.8-2.3% in single loci,.11 QTL cluster of.11, distributed in Chr2,5,6,14,16 and On the 21 chromosome, 4 QTL cluster.3. photosynthetic characters were located on the Chr16 chromosome, and QTL location using compound interval mapping (CIM) was used. In 2014, 2015, drought stress (W1) and normal irrigation (W2), the photosynthetic characteristics of the flower and boll phase of F2:3 family were located in two environments, and 45 QTL. were detected under drought stress and 27 controlled photosynthetic characteristics were detected. The QTL locus, including 6 net photosynthetic rates, 2 intercellular CO2 concentrations, 2 transpiration rates, 5 stomatal conductance, 5 leaf temperatures and 7 QTL loci of 7 water utilization, detected 4 additive QTL, single loci can be interpreted as the phenotypic variation of 11.00-13.76%. Under normal irrigation, 18 controlled photosynthetic traits were detected, including 1. Net photosynthetic rate, 3 intercellular CO2 concentrations, 1 stomatal conductance, 4 leaf temperatures and 9 water use rate (WUE) QTL loci, a total of 4 additive QTL were detected, and single loci could be interpreted as 11.00-13.76% phenotypic variation.QPn-Chr16-1 is a stable QTL locus for controlling photosynthetic rate under 20142015 consecutive years of drought stress. On the Chr16 chromosome, a single locus can explain the phenotypic variation of 9.44-18.61%,.QGs-Chr5-1, to detect the QTL locus for controlling stomatal conductance in the drought and normal irrigation environment in 2015, and a single locus can explain the phenotypic variation of 0.66-0.67%.
【學(xué)位授予單位】：中國農(nóng)業(yè)科學(xué)院
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類號(hào)】：S562

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