【作者】 刘大军；

【导师】 张正圣；

【作者基本信息】 西南大学 ， 作物遗传育种， 2010， 博士

【摘要】 棉属有四个栽培棉种,包括亚洲棉（G. arboreum L.）、草棉（G. herbaceum L.）、陆地棉（G.hirsutum L.）、海岛棉（G. barbadense L.）,其中陆地棉是世界范围最主要的栽培种,占总产量的90%。棉花不仅是纺织工业的重要原料,而且是仅次于大豆的重要油料和蛋白质来源。棉子油的产量约占世界食用植物油料供应量的10%,棉子蛋白质资源达到世界植物蛋白质资源的6%。棉花也是调整农业结构、发展畜牧业和多种经济的重要支柱。目前棉花育种的研究重点仍是产量与纤维品质改良,而关于种子性状特别是营养品质性状的研究极少,世界上被广泛栽培的陆地棉品种种子的油脂与蛋白含量至今仍维持其50年前甚至100年前的水平。棉花产量、纤维品质的遗传改良可以提高与化学纤维的竞争力,而改良作为食物、饲料的棉籽将为人们提供充足的营养和食物资源。因此,在改良棉花产量、纤维品种的同时,改良棉花种子油脂、脂肪酸组分以及蛋白含量等性状,更能充分发挥棉花的经济价值。有关棉籽油脂和蛋白质含量的遗传研究主要采用经典数量遗传学分析方法,由于棉花油脂、脂肪酸组分以及蛋白含量等性状属多个基因控制的数量性状,经典数量遗传学研究方法只能在群体水平对这些性状进行分析,难以对数量性状基因的效应、作用方式以及染色体分布进行准确研究。为此,我们利用（渝棉1号×T586）F2：7重组近交系群体,用SSR、SRAP、IT-ISJ和形态标记构建高密度陆地棉遗传连锁图谱,结合多个环境重组近交系群体种子物理性状、营养品质性状鉴定结果,定位陆地棉种子物理性状、营养品质性状QTL。研究结果将为陆地棉的分子标记辅助选择奠定基础。其主要研究结果如下：1.种子物理性状、营养品质性状的表型分析亲本渝棉1号与T586之间种子物理性状、营养品质性状差异大。渝棉1号种子重10.67g,短绒重1.43g,短绒率11.79%,种仁重6.33g,种子壳重4.34g,种仁率59.30%；T586种子重13.02g,短绒重Og,短绒率0%,种仁重8.66g,种子壳重4.33g,种仁率66.49%；渝棉1号粗蛋白质含量约为50.28%,粗油含量约为24.80%；T586粗蛋白质含量约为36.45%,粗油含量约为36.85%。渝棉1号种子蛋白质含量较高,油脂含量较低；而T586蛋白质含量较低,油脂含量较高。两亲本在脂肪酸组分上差异不大。种子物理性状、营养品质性状表现超高亲的超亲分离,各性状表现连续分布,呈现多基因控制的数量性状遗传特点。（渝棉1号×T586）F_2：7重组近交系群体种子物理性状、营养品质性状的环境方差均达显著或极显著,表明种子物理性状、营养品质性状的表现同时受基因与环境的共同作用。种子重、种仁重和种子壳重之间存在显著的正相关,短绒重和短绒率之间呈显著的正相关,粗蛋白质含量和粗油含量呈显著的负相关,短绒重和短绒率与粗蛋白质含量呈显著的正相关,短绒重和短绒率与粗油含量呈显著的负相关。2.作图亲本间SRAP标记多态性筛选与群体标记基因型检测1536对SRAP引物筛选亲本渝棉1号与T586之间DNA的多态性,共获得88对多态性引物,多态性引物比例5.73%。经群体标记基因型检测88对多态性引物得到105个标记位点,平均每个多态性引物组合产生1.19个位点。3.陆地棉遗传连锁图谱的构建利用105个SRAP标记与567个SSR、64个IT-ISJ标记、8个形态标记进行遗传连锁分析,构建的遗传连锁图包括730个标记位点和62个连锁群。62个连锁群分布于棉花基因组的所有26条染色体。另有15个标记位点没有发现与任何位点连锁。遗传连锁图谱包括102个SRAP标记,556个SSR标记,64个IT-ISJ标记,8个形态标记,所得的遗传连锁图谱覆盖3434.3cM,约占棉花基因组的77.22%，标记间的平均距离为4.70cM。该图谱是目前国内外标记数最多、基因组覆盖最广的陆地棉遗传连锁图谱。4.QTL效应与有利等位基因来源采用MQM作图法,共获得88个种子物理性状QTLs。检测到22个种子重QTLs,单个QTL解释种子重变异的3.4%-9.7%，11个种子重QTLs的有利等位基因来源于T586,另11个种子重QTLs的有利等位基因来源于渝棉1号；检测到11个短绒重QTLs,单个QTL解释短绒重变异的3.6%--63.9%，5个短绒重QTLs的有利等位基因来源于T586，6个短绒重QTLs的有利等位基因来源于渝棉1号；检测到10个短绒率QTLs,单个QTL解释短绒率变异的3.6%～75.3%,3个短绒率QTLs的有利等位基因来源于T586,7个短绒率QTLs的有利等位基因来源于渝棉1号；检测到18个种仁重QTLs,单个QTL解释种仁重变异的3.6%～8.8%，9个种仁重QTLs的有利等位基因来源于T586,另9个种仁重QTLs的有利等位基因来源于渝棉1号；检测到13个种子壳重QTLs,单个QTL解释种子壳重变异的3.8%～7.9%，6个种子壳重QTLs的有利等位基因来源于T586,7个种子壳重QTLs的有利等位基因来源于渝棉1号；检测到14个种仁率QTLs,单个QTL解释种仁率变异的3.6%11.7%，10个种仁率QTLs的有利等位基因来源于T586，4个种仁率QTLs的有利等位基因来源于渝棉1号。88个种子物理性状QTLs中,有57个QTLs（占全部种子物理性状QTLs的64.77%）对表型效应的贡献率在5-20%之间,5%以下的占32.95%。短绒重、短绒率分别检测到一个主效QTL,分别能解释约53.6%、64.9%的表型变异。共获得43个种子营养品质性状QTLs。检测到12个粗蛋白质含量QTLs,单个QTL解释粗蛋白质含量变异的3.8%～28.8%，2个粗蛋白质含量QTLs的有利等位基因来源于T586，10个粗蛋白质含量QTLs的有利等位基因来源于渝棉1号；检测到12个粗油含量QTLs,单个QTL解释粗油含量变异4.0%～23.0%，8个粗油含量QTLs的有利等位基因来源于T586,4个粗油含量QTLs的有利等位基因来源于渝棉1号；检测到4个亚油酸含量QTLs,单个QTL解释亚油酸含量变异的3.5%～5.5%，1个亚油酸含量QTL的有利等位基因来源于T586，3个亚油酸含量QTLs的有利等位基因来源于渝棉1号；检测到3个油酸含量QTLs,单个QTL解释油酸含量变异的3.7%～11.3%，3个油酸含量QTLs的有利等位基因均来源于T586；检测到5个棕榈酸含量QTLs;单个QTL解释棕榈酸含量变异的5.3%～7.0%,1个棕榈酸含量QTL的有利等位基因来源于T586，4个棕榈酸含量QTLs的有利等位基因来源于渝棉1号；检测到7个硬脂酸含量QTLs,单个QTL解释硬脂酸含量变异的37%～9.3%，4个硬脂酸含量QTLs的有利等位基因来源于T586，3个硬脂酸含量QTLs的有利等位基因来源于渝棉1号。43个种子营养品质性状QTLs中,有27个QTLs（占全部种子营养品质性状QTLs的62.79%）贡献率在5-20%之间,5%以下的占32.56%。粗蛋白质含量、粗油含量分别检测到一个主效QTL,分别能解释约23%、22.5%的表型变异。5.环境对QTL的影响在所检测的种子物理性状QTLs中,有27个QTL能够在2个或3个环境同时检测到,占全部QTL的30.68%。其中有6个种子重QTLs,占种子重QTL的27.27%；5个短绒重QTLs,占短绒重QTL的45.45%；3个短绒率QTLs,占短绒率QTL的30%；6个种仁重QTLs,占种仁重QTL的33.33%；6个种子壳重QTLs,占种子壳重QTL的46.15%；2个种仁率QTLs,占种仁率QTL的14.28%。种子营养品质性状中,有6个QTL（粗蛋白质含量、粗油含量QTL各有3个）在2个环境同时检测到,占两者全部QTL的25%。脂肪酸组分中,油酸含量与棕榈酸含量各有1个QTL在2个环境均检测到。5.QTL染色体分布88个物理性状QTL中有65个QTL表现成簇分布。种子重、种仁重和种子壳重QTL多分布在一起,短绒重和短绒率QTL分布在一起。短绒重和短绒率QTL成簇分布于chr.3、chr7.、chr.13、chr.15、chr.20和chr.21,种子重、种仁重和种子壳重QTL成簇分布于chr.11、chr.12、chr.14、chr.15、chr.24和chr.25。5个种仁率QTL与种子重、种仁重QTL分布于chr.6、chr.8、chr.18、chr.20、chr.23上。24个粗蛋白质含量和粗油含量QTL有16个QTL表现成簇分布,包括两个主效QTL,占粗蛋白质含量和粗油含量全部QTL的66.67%。第12染色体第3连锁群集中分布有种子重、种仁重、种子壳重、短绒重、短绒率5个物理性状QTL和粗蛋白质含量、粗油含量2个营养品质性状QTL,其中短绒重、短绒率、粗蛋白质含量、粗油含量QTL均为主效QTL,这些QTL可能是-因多效引起。更多还原

【Abstract】 Cotton genus comprises of 4 cultivation species including Asian cotton （G. arboreum L.）, African cotton （G. herbaceum L.）, Upland cotton （G. hirsutum L.） and Sea-island cotton （G. barbadense L.）. Upland cotton as the most widely cultivated cotton cultivars accounts for 90% of the world’s total cotton production. Cotton is not only important textile fiber raw materials, but also important oil and protein resources. Cotton seed accounts for 10% of world’s edible oil and 6% of world’s plant protein. Cotton is an important economy mainstay of the agricultural structural adjustment and livestock development. The current objective of cotton breeding is still the improvement of yield and fiber quality. Unfortunately, the researches of seed traits, especially nutrition, are ignored. Cotton seed oil and protein content is still same as its 50 years ago or even 100 years ago. The genetic improvement of yield and fiber quality can ensure the competition with chemical fiber, and the modifying cotton seed as food and feed will provide people with adequate nutrition and food resources. Therefore, with the improvement of cotton yield and fiber quality, the improvement of cotton seed oil, fatty acid composition and protein content could exert the economic value of cotton. Cotton oil, fatty acid composition and protein content are quantitative traits controlled by multiple genes, so conventional quantitative genetics methods can only analyze these traits at the population level, and cannot analyze the effect and expression mode, and chromosome distribution of quantitative trait genes. Herein, （Yumian 1×T586） F_2:7 recombinant inbred line population was used to construct upland cotton high-density genetic linkage map with SSR, SRAP, IT-ISJ and morphological markers, and also the QTLs of seed physical and nutritional quality traits were mapped in the present study. The results lay the foundation for molecular marker-assisted selection of upland cotton. The mainly results were as following:1. Phenotypic analysis of seed physical and nutritional quality traits The significant differences of physical and nutritional quality traits exist between parent Yumian 1 and T586. Yumian 1 had 10.67g for seed weight,1.43g for fuzz weight,11.79% for fuzz percentage,6.33g for kernel weight,4.34g for hull weight，59.30% for kernel percentage; about 50.28% for coarse protein contents,24.80% for coarse oil contents; while T586 had 13.02g for seed weight, 0g for fuzz weight,0% for fuzz percentage,8.66g for kernel weight,4.33g for hull weight,66.49% for kernel percentage; about 36.45% for coarse protein contents,36.85% for coarse oil contents. Compared with T586, Yumian 1 had high protein content and low fatty acid content, whereas T586 had low protein content and high fatty acid content. The fatty acid composition was similar in two cultivars. Transgressive high parent segregation appeared in seed physical and nutritional quality traits, and all traits showed continuous distribution and quantitative traits genetics characteristics controlled by multi-gene.The significant or extremely significant environment variances of seed physical and nutritional quality traits showed that seed physical and nutritional quality traits are affected by both genotype and environment. Significantly positive correlation existed between seed weight, seed kernel and seed shell was, and significantly positive correlation also existed between short fiber weight and short fiber. Significantly negative correlation existed between crude protein content and crude oil content. Significantly positive correlation existed between short fiber weight, short fiber rate and crude protein content whereas significantly negative correlation existed between short fiber weight, short fiber rate and crude oil content.2. SRAP polymorphism between mapping parentsA total of 1563 SRAP primer combinations produced a total of 88 polymorphic primer combinations. The polymorphic primers were used to genotyp the recombinant inbred line population, and 105 SRAP loci were obtained, averaging 1.16 informative SRAP loci per polymorphic primer combinations.3. Construction of upland cotton linkage mapA total of 105 SRAP loci, together with 567 SSR,64 IT-ISJ and 8 morphological loci, were employed to perform genetic linkage analysis, and a genetic linkage map comprising of 730 loci and 62 linkage groups was constructed, whereas 15 loci could not be located on any chromosome. The sixty-two linkage groups were distributed into all 26 chromosomes. The genetic linkage map consisted of 102 SRAP,556 SSR,64 IT-ISJ, and eight morphological markers, and covered 3434.3 cM or approximately 77.22% of the total recombination length of cotton genome. The average distance was 4.70 cM between two markers. Up to date, this map is the upland cotton linkage map with largest marker number and the most extensive genome coverage.4. QTL effect and favorable allele origin Based on MQM mapping, eighty-eight QTLs were identified for seed physical traits. Twenty-two QTLs for seed weight explained 3.4%～9.7% of seed weight variance. Favorable allele of eleven QTLs for seed weight originated from T586, whereas favorable allele of eleven QTLs for seed weight originated from Yumian 1. Eleven QTLs for fuzz weight explained 3.6%～63.9% of fuzz weight variance. Favorable allele of five QTLs for fuzz weight originated from T586, whereas favorable allele of six QTLs for fuzz weight originated from Yumian l.Ten QTLs for fuzz percentage explained 3.6%～75.3% of fuzz percentage variance. Favorable allele of three QTLs for fuzz percentage originated from T586, whereas favorable allele of seven QTLs for fuzz percentage originated from Yumian 1. Eighteen QTLs for kernel weight explained 3.6%～8.8% of kernel weight variance. Favorable allele of nine QTLs for kernel weight originated from T586, whereas favorable allele of nine QTLs for kernel weight originated from Yumian 1. Thirteen QTLs for hull weight explained 3.8%～7.9% of hull weight variance. Favorable allele of six QTLs for hull weight originated from T586, whereas favorable allele of seven QTLs for hull weight originated from Yumian 1. Fourteen QTLs for kernel percentage explained 3.6%～11.7% of kernel percentage variance. Favorable allele of ten QTLs for kernel percentage originated from T586, whereas favorable allele of four QTLs for kernel percentage originated from Yumian 1. Among eighty-eight QTLs for seed physical traits, fifty-seven （64.77%） QTLs explained 5-20% of the total phenotypic variation whereas twenty-nine （32.95%） QTLs explained less than 5% of the phenotypic variation. Two main-effect QTLs for fuzz weight and fuzz percentage explained about 53.6%,64.9% of phenotypic variation, respectively.Forty-three QTLs were identified for seed nutritional quality traits. Twelve QTLs for coarse protein contents explained 3.8%～28.8% of coarse protein contents variance. Favorable allele of two QTLs for coarse protein contents originated from T586, whereas favorable allele of ten QTLs for coarse protein contents originated from Yumian 1. Twelve QTLs for coarse oil contents explained 4.0%～23.0% of coarse oil contents variance. Favorable allele of eight QTLs for coarse oil contents originated from T586, whereas favorable allele of four QTLs for coarse oil contents originated from Yumian 1. Four QTLs for linoleic acid contents explained 3.5%～5.5% of linoleic acid contents variance. Favorable allele of one QTL for linoleic acid contents originated from T586, whereas favorable allele of three QTLs for linoleic acid contents originated from Yumian 1. Three QTLs for oleic acid contents explained 3.7%～11.3% of oleic acid contents variance. Favorable allele of three QTLs for oleic acid contents originated from T586. Five QTLs for palmitate acid contents explained 5.3%～7.0% of palmitate acid contents variance. Favorable allele of one QTL for palmitate acid contents originated from T586, whereas favorable allele of four QTLs for palmitate contents originated from Yumian 1. Seven QTLs for stearic acid contents explained 3.7%～9.3% of stearic acid contents variance. Favorable allele of four QTLs for stearic contents originated from T586, whereas favorable allele of three QTLs for stearic contents originated from Yumian 1. Among forty-three QTLs for seed nutritional quality traits, twenty-seven （62.79%） QTLs had effects controlling 5-20% of total phenotypic variation, and fourteen （32.56%） QTLs explained less than 5% of the phenotypic variation. Two main-effect QTLs for crude protein content and crude oil content explained about 23% and 22.5% of phenotypic variation, respectively.5. The interaction of QTL and environmentAmong the QTLs for physical traits, twenty seven QTLs （30.68%） could be identified simultaneously in 2 or 3 different environments, including six QTLs （27.27%） for seed weight, five QTLs （45.45%） for fuzz weight, three QTLs （30%） for fuzz percentage, six QTLs （33.33%） for kernel weight, six QTLs （46.15%） for hull weight, and two QTLs （14.28%） for kernel percentage, respectively.Among the QTL for seed nutritional quality traits, six QTL （25%） for coarse protein and coarse oil contents （each of three QTL） were identified in two environments. One QTL for oleic acid and palmitate acid was identified in two environments.6. QTL chromosome distributionAmong eighty-eight QTLs for physical traits, sixty-five are clustered. The QTLs for the seed weight, kernel weight and hull weight always clustered on the same chromosome region whereas QTLs for fuzz weigh and fuzz percentage always clustered on the same region. QTLs for fuzz weigh and fuzz percentage clustered on chr.3, chr.7, chr.13, chr.15, chr.20 and chr.21, and QTLs for seed weigh, kernel and hull weight clustered on chr.11, chr.12, chr.14, chr.15, chr.24 and chr.25. Five QTLs for kernel percentage clustered on chr.6, chr.8, chr.18, chr.20, chr.23 with QTLs for seed weight and kernel weight.Out of twenty-four QTLs for coarse protein and coarse oil contents,16 QTLs are clustered, including two main-effect QTLs, which accounted for 66.67% of all QTL for coarse protein and coarse oil contents.Main-effect QTLs for five physical traits, seed weight, kernel weight, hull weight, fuzz weigh, fuzz percentage, and two nutritional quality traits, coarse protein and coarse oil contents clustered on chromosome 12, suggesting these clustered QTLs maybe resulted from pleiotropy.更多还原