陆地棉SRAP图谱构建与种子物理、营养品质性状QTL定位
|
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。
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 parents
A 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 map
A 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 environment
Among 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 distribution
Among 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.
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。
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 parents
A 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 map
A 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 environment
Among 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 distribution
Among 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.
引文
陈利,张正圣,胡美纯,王威,张建,刘大军,郑靓,郑风敏,马靖.陆地棉遗传图谱构建及产量和纤维品质性状QTL定位.作物学报,(2008)，34：1199-1205
董合忠,李维江,张晓洁.棉花种子学.北京,科学出版社,2004a,46-48
董合忠,李维江,唐薇,张晓洁,刘继永,崔正鹏,张冬梅.生态条件和制种期对棉花杂交种质量的影响.棉花学报,2004b，16(5)：265-269
范术丽,喻树迅,宋美珍,原日红.短季棉早熟性的分子标记及QTL定位.棉花学报,2006，18(3)：135～13
房卫平,许守明,孙玉堂,唐中杰,王家典.棉花抗黄萎病的RAPD标记.河南农业科学,2001(9)：11-13
高玉千,聂以春,张献龙.棉花抗黄萎病基因的QTL定位.棉花学报,2003，15(2)：73～78
季道藩,朱军.陆地棉品种间杂种的种仁油分和氨基酸成份的遗传分析.作物学报,1988，14(1)：1-6
葛海燕,汪业春,郭旺珍,张天真.陆地棉抗黄萎病性状的遗传及分子标记研究.棉花学报,2008,20(1)：19-22
胡美纯.陆地棉遗传图谱构建与纤维品质性状QTL定位[硕士学位论文].重庆：西南大学,2008
胡文静,张晓阳,张天真,郭旺珍.陆地棉优质纤维QTL的分子标记筛选及优质来源分析.作物学报,2008,34(4)：578-586
李成奇,郭旺珍,马晓玲,张天真.陆地棉衣分差异群体产量及产量构成因素的QTL标记和定位.棉花学报,2008,20(3)：163-169.
李大庆,钱大顺,倪金柱.棉铃发育研究-Ⅳ.伏桃、晚秋桃棉籽质量的鉴定.江苏农业科学,1982，3：21-24
李维明,吴为人,卢浩然.检测作物数量性状基因与遗传连锁关系的方差分析法及应用.作物学报,1993,19(2)：92-102
刘冬青,庞居勤,葛逢珠.棉花不同品种棉子仁粗蛋白、粗脂肪含量在不同地点差异的分析.江西棉花,1995,4：11-12
刘明,范君华,由宝昌,梅拥军.海岛棉棉仁蛋白质和脂肪含量分析.作物品种资源，1994(4)：25-28.
刘巷禄,袁钧,李永山,潘转霞,樊立强.棉花种子质量对棉花生长发育及产量效应的影响.山西农业科学,1997,25(4)：40-43
秦永生,刘任重,梅鸿献,张天真,郭旺珍.陆地棉产量相关性状的QTL定位.作物学报,2009，35(10)：1812-1821
沈乃愚,陈铭狄,叶惠珍.不同成熟度棉种的素质及其育苗效果研究简报.中国棉花学会论文集, 1981,35-36
盛志廉,陈瑶生.数量遗传学.科学出版社,1999：340-347
孙善康,陈建华,项时康,魏守军.棉花种子营养品质研究.中国农业科学,1987，20(5)：12-16
唐薇,张冬梅,李振怀,李维江,董合忠.Bt杂交棉种子的成熟度与某些播种品质指标的关系.种子,2004,23(6)：3-8
王芙蓉,刘任重,王留明,张传云,刘国栋,刘勤红,马小波,张军.陆地棉品种抗黄萎病性状的分子标记及其辅助选择效果.棉花学报,2007,19(6)：424-430
王红梅,张献龙,贺道华,林忠旭,聂以春,李运海,陈伟.陆地棉对黄萎病抗性的分子标记研究.植物病理学报,2005,35(4)：333～339
王国印,李蒙恩.棉子品质性状的遗传研究.华北农学报,1991，6(2)：20-25
王国建,朱军,臧荣春,许馥华,季道藩.陆地棉棉仁营养品质及种子物理性状的遗传相关分析.浙江农业大学学报,1996,22(6)：585-590
王娟,郭旺珍,张天真.渝棉1号优质纤维QTL的标记与定位.作物学报,2007，33(12)：1915-1921
王沛政,秦利,苏丽,胡保民,张天真.新疆陆地棉主栽品种部分产量性状QTL的标记与定位.中国农业科学,2008，41(10)：2947-2956
王学德,俞碧霞,夏如冰,王洁.低酚棉产量、纤维品质和棉仁营养品质的表现及其相关性.浙江农业科学,1989,(3)：118-120
王延琴,杨伟华,周大云,许红霞,冯新爱,夏俊英.棉子营养成分与发芽率及出苗率的关系.棉花学报,2003,15(20)：109-112
汪保华.湘杂棉2号强优势组合杂种优势表现的遗传机理研究[博士学位论文].南京农业大学,2006,79-88
魏红,钟红舰,汪红.索氏抽提法测定粗脂肪含量的改进.中国油脂,2004，29(6)：52-54.
吴吉样,王国建,朱军,许馥华,季道藩.陆地棉种子性状直接效应和母体效应的遗传分析.作物学报,1995,21(6)：659-664
吴茂清,张献龙,聂以春,贺道华.四倍体栽培棉种产量和纤维品质性状的QTL定位(英文).遗传学报,2003,30(5)：443-452
项时康,孙善康.1982.陆地棉种子蛋白质、脂肪含量与籽指、衣分的相关性.中国棉花,(3)：27-28
闰建庆,胡保民,陈爱民.新疆陆地棉棉子粗脂肪和粗蛋白的研究.新疆农业科学,2000(3)：106-109.
杨奎华.陆地棉种仁脂肪含量及蛋白质等几种性状相关性的研究. 棉花学报,1985，1：48-53
殷剑美,武耀廷,张军,张天真,郭旺珍,朱协飞.陆地棉产量性状QTLs的分子标记及定位.生物工程学报,2002,18(3)：162-166
张培通,郭旺珍,朱协飞,俞敬忠,张天真.高产棉花品种泗棉3号产量及其构成因素的QTL标记和定位.作物学报,2006,32(8)：1197-1203
张培通,朱协飞,郭旺珍, 张天真.陆地棉衣分及相关性状的遗传和QTL分子标记.江苏农业学
报,2005,21(4)：264～271
张天真,郭旺珍.棉花分子育种的现状、问题与展望.中国农业科技导报,2007，9(2)：19～25
张正圣.陆地棉遗传连锁图谱的构建与纤维相关性状QTL分析[博士学位论文].重庆：西南农业大学,2005
郑靓,张正圣,陈利,万群,胡美纯,王威,张轲,刘大军,陈笑,魏新琦.IT-ISJ标记及其在陆地棉遗传图谱构建中的应用.中国农业科学,2008，39：2241-2248
周治国,许玉章,许萱. 棉子品质与纤维品质及铃期温度相关性的研究.陕西农业科学,1992,(3)：3-5
周有耀.棉花种子营养品质与纤维品质的关系.中国棉花,1993，(2)：13-14
周延清.DNA分子标记技术在植物研究中的应用.化学工业出版社,2005,11-15
朱乾浩,俞碧霞,许复华.低酚棉品种间杂种产量性状的遗传分析.棉花学报,1994，6(4)：215-220
朱乾浩,俞碧霞,许复华.低酚棉棉子品质性状的遗传分析.棉花学报，1995,7(2)：94-99
朱军.Mixed model approaches for estimating genetic varances and covariances.生物数学学报,1992,(7)：1-11
左开井,孙济中,张献龙,聂以春,刘金兰,冯纯大.利用RFLP、SSR和RAPD标记构建陆地棉分子标记连锁图.华中农业大学学报,2000，19(3)：190-193
Alford BB, Liepa GU, Vanbeber AD. Cottonseed protein:What does the future hold? Plant Foods for Humam Nutrition.1996,49:1-11
Ali S, Muller CR, Epplen JT. DNA finger printing by oligonucleotide probes specific for simple repeats. Hum. Genetics,1986, (74):239-243
Bolek Y, El-Zik KM, Pepper AE, Bell AA, Magill CW, Thaxton PM, Reddy UK. Mapping of Verticilliumwilt resistance genes in cotton. Plant Sci,2005,168(66):1581-1590
Botsien D, White RL, Skolnick M, Davis RW. Construction of a genetic map in man using restriction fragment polymorphisms. Am J Hum Genet,1980,32:314-331
Chee P, Draye X, Jiang CX, Decanini L, Delmonte TA, Bredhauer R, Smithc W, Parterson AH. Molecular dissection of phenotypic variation between Gossypium hirsutum and Gossypium barbadense (cotton) by a backcross-self approach:Ⅲ. Fiber length. Theor. Appl. Genet.,2005,111:772-781
Chen ZJ, Scheffler BE, Dennis E, Triplett BA, Zhang T, Guo W, Chen X, Stelly DM, Rabinowicz PD, Town CD, Arioli T, Brubaker C, Cantrell RG, Lacape JM, Ulloa M, Chee P, Gingle AR, Haigler CH, Percy R, Saha S, Wilkins T, Wright RJ, Deynze AV, Zhu Y, Yu S, Abdurakhmonov I, Katageri I, Kumar PA, Rahman M, Zafar Y, Yu JZ, Kohel RJ, Wendel JF, Paterson AH. Toward sequencing cotton (Gossypium) genomes. Plant Physiol,2007,145:1303-1310
Collins FS, Guyer MS, Chakravarti A. Variations on a theme:cataloging human DNA sequence variation. Science,1997,278:1580-1581
Collins NC, Webb CA, Seah S, Ellis JG, Hulbert SH, Pryor A. The isolation and mapping of disease resistance gene analogs inmaize. Mol Plant Microbe Interact,1998,11:968-978.
Darvasi A, Soller M. Selective DNA pooling for determination of linkage between a marker and a quantitative trait locus. Genetics,1994,138:1365-1373
Draye X, Chee P, Jiang CX, et al. Molecular dissection of interspecific variation between Gossypium hirsutum and G. Barbadense (cotton) by a backcross-self approach:Ⅱ. Fiber fineness. Theor. Appl. Genet.,2005,111:764-771
Dudley JW. Molecular markers in plant improvement:manipulation of genes affecting quantitative traits. Crop Sci,1993,33:660-668
Dulbeeeo R.A. turning point in gene research:sequencing the human genome. Science,1986, 231:1055-1056
Frelichowski Jr JE, Palmer MB, Main D, Tomkins JP, Cantrell RG, Stelly DM, Yu J, Kohel RJ, Ulloa M. Cotton genome mapping with new microsatellites from Acala 'Maxxa' BAC-ends. Mol. Gen. Genomics,2006,275:479-491
Fryxell PA. A revised taxonomic interption of Gossypium(Malvaceae). Rheelea,1992,2:108-165
Guo W, Cai C, Wang C, Han Z, Song X, Wang K, Niu X,Wang C, Lu K, Shi B. Zhang T. A microsatellite-based, gene-rich linkage map reveals genome structure, function and evolution in Gossypium. Genetics,2007,176:527-541
Guo W, Cai C, Wang C, Zhao L, Wang L, Zhang T. A preliminary analysis of genome structure and composition in Gossypium hirsutum. BMC Genomics,2008,9:314-331
Guo W, Ma G, Zhu Y, Yi C, Zhang T. Molecular tagging and mapping of quantitative trait loci for lint percentage and morphological marker genes in upland cotton. J Integrative Plant Biology,2006,48: 320-326
Han Z G, Guo W Z, Song X L, Zhang T Z. Genetic mapping of EST-derived microsatellites from the diploid (Gossypium arboreum) in allotetraploid cotton. Molecular Genet Genom,2004,272:308-327
Hanny BW, Meredith WR, Jr., Bailey JC, Harvey AJ. Gentics relationships among chemical constituents in seed,.flower buds terminals and mature leaves of cotton. Crop Sci,1978,18:1071-1074
He DH, Lin ZX, Zhang XL, Nie YC, Guo XP, Feng CD, Stewart JM. Mapping QTLs of traits contributing to yield and analysis of genetic effects in tetraploid cotton. Euphytica,2005,144:141-149
He DH, Lin ZX, Zhang XL, Nie YC, Guo XP, Zhang YX, Li W. QTL mapping for economic traits based on a dense genetic map of cotton with PCR-based markers using the interspecific cross of Gossypium hirsutum × Gossypium barbadense. Euphytica,2007,153:181-197
Hu J, Vick BA. Target Region Amplification Polymorphism:A novel marker technique for plant genotyping. Plant Molecular Biology Reporter,2003,21:289-294
Jefferys AJ, Wilson V, Thein SL. Hypervariable "microsatellite" regions in human DNA. Nature,1985, (316):76-79
Jiang CX, Wright RJ, Woo SS, DelMontelTA, Paterson AH. QTL analysis of leaf morphology in tetraploid Gossypium(cotton).Thero Appl Genet,2000,100:409-418
Jiang CX, Wright RJ, El-Zik KM, Paterson AH. Polyploid formation created unique avenues for response to selectionin Gossypium (cotton). Proc Natl Acad Sci USA,1998,95:4419-4424
Khan MA, Steward JM, Zhang J, et al. Addition of new markers to the trispecific cotton map[C]//Proc of the beltwide cotton conference. National Cotton Council, Memphis, TN,1999:439
Kohel R J. Genetic studies of seed oil in cotton.Crop Sci,1980,20:784-788
Kohel RJ, Yu J, Park YH, Lazo GR. Molecular mapping and characterization of traits controlling fiber quality in cotton. Euphytica,2001,121:163-172.
Kosambi DD. The estimation of map distance from recombination values. Ann. Eugen,1944,12:172-175
Lacape JM, Jacobs J, Arioli T, Derijcker R, Forestier-Chiron N, Llewellyn D, Jean J, Thomas E, Viot C. A new interspecific, Gossypium hirsutum × G. barbadense, RIL population:towards a unified consensus linkage map of tetraploid cotton. Theor Appl Genet,2009,119:281-292
Lander ES, Botstein D. Mapping Mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics,1989,121:185-199
Lee JA, Cockerham CC, Smith FH. The inheritance of gossypol level in Gossypium I.Additive, dominance, epistatic and maternal effects associated with seed gossypol in two varieties of G. hirsutum L. Genetics, 1968,59:285-298
Li G, Quiros C F. Sequence-related amplified polymorphism (SRAP), a new marker system based on a simple PCR reaction:its application to mapping and gene tagging in Brassica. Theoretical and Applied Genetics,2001,103:455-461.
Lin ZX, He DH, Zhang X L, Nie Y C, Guo X P, Feng C D, James M D. Linkage map construction and mapping QTL for cotton fiber quality using SRAP,SSR and RAPD. Plant Breeding,2005, 124:180-187.
Lin ZX, Zhang YX, Zhang XL, Guo XP. A high-density integrative linkage map for Gossypium hirsutum. Euphytica,2009,166:35-45
Lowe AJ, Moule C, Trick M, Edwards KJ. Efficient large-scale development of microsatellites for marker and mapping applications in Brassica crop species. Theoretical and Applied Genetics,2004, 108:1103-1112
Lusas EW & Jividen GM. Glandless cottonseed:A review of the first 25 years of processing and utilization research. J Am Oil Chem Soc,1987,64:839-854
Lyon. DNA markers and molecular breeding of cotton. The Australian cotton grower,1999,20 (5):80-83.
Malm N. Combining ability and heritability of protein and oil content in upland cotton. Proc Belt Cotton Prod Res Conf,1979:83-84
McCouch SR, Cho YG, Yano M, Paul E, Morishima H and Kinoshita T. Report on QTL nomenclature. Rice. Genet. Newsl.,1997,14:11-13
Mei M, Syed NH, Gao W, Thaxton PM, Smith CW, Stelly DM, Chen ZJ. Genetic mapping and QTL analysis of fiber-related traits in cotton (Gossypium). Theoretical and Applied Genetics,2004, 108:280-291
Olson M, Hood L, Cantor C, Botstein D. A common language for physical mapping of the human genome. Science,1989,245:1434-1435
Park YH, Alabady MS, Ulloa M, Sickler B, Wilkins TA, Yu J, Stelly DM, Kohel RJ, el-Shihy OM, Cantrell RG. Genetic mapping of new cotton fiber loci using EST-derived microsatellites in an interspecific recombinant inbred line cotton population. Mol. Gen. Genomics,2005,274:428-441
Paterson AH, Saranga Y, Menz M, Jiang CX, Wright RJ. QTL analysis of genotypex environment interaction affecting cotton fiber quality. Theor Appl Genet,2003,6:384-396
Pizzinatto MA, Menten JOM, Soave J, Cia E, Maeda JA. Relationship between cotton seed weight and quality. Bragantia,1991,50:269-289
Qin H, Guo W, Zhang YM, Zhang T. QTL mapping of yield and fiber traits based on a four-way cross population in Gossypium hirsutum L. TAG Theoretical and Applied Genetics,2008,117:883-894
Qureshi SN, Saha S, Kantety RV, Jenkins JN. EST-SSR:a new class of genetic markers in cotton. J Cotton Science,2004,8:112-123
Ramalingam J, Vera Cruz CM, Kukreja K, Chittoor JM, Wu JL, Lee SW, Baraoidan M, George ML, Cohen MB, Hulbert SH, Leach JE, Leung H. Candidate defense genes from rice, barley, and maize and their association with qualitative and quantitative resistance in rice. Mol. Plant Microbe Interact,2003, 16:14-24
Reinisch AJ, Dong JM, Brubaker CL, Stelly DM, Wendel JF, Paterson AH. A detailed RFLP map of cotton, Gossypium hirsutum × Gossypium barbadense:chromosome organization and evolution in a disomic polyploid genome. Genetics,1994,138:829-847
Ren LH, Guo WZ, Zhang TZ. Identification of quantitative trait loci (QTLs) affecting yield and fiber properties in chromosome 16 in cotton using substitution line. Acta Botanica Sinica,2002,44(7): 815-820
Risch N, Merikangas K.The future of genetic studies of complex human diseases. Science,1996, 273:1516-1517
Rong J, Abbey C, Bowers JE, Brubaker CL, Chang C, Chee PW, Delmonte TA, Ding X, Garza JJ, Marler BS, Park C-h, Pierce GJ, Rainey KM, Rastogi VK, Schulze SR, Trolinder NL, Wendel JF, Wilkins TA, Williams-Coplin TD, Wing RA, Wright RJ, Zhao X, Zhu L, Paterson AH. A 3347-locus genetic recombination map of sequence-tagged sites reveals features of genome organization, transmission and evolution of cotton (Gossypium). Genetics,2004,166:389-417
Saha S, Karaca M, Jenkins J N, Zipf A E, Reddy OUK, Kantety R V. Simple sequence repeats as useful resources to study transcribed genes of cotton. Euphytica,2003,130:355-364
Saranga Y, Jiang CX, Wright RJ, Yakir D, Paterson AH. Genetic dissection of cotton physiological responses to arid conditions and their inter-relationships with productivity. Plant Cell and environment, 2004,27:263-277
Sax K. The association of size differences with seed-coat pattern and pigmentation in phaseolus vulgaris. Genetics,1923,8(6):552-560
Shappley ZW, Jenkins JN, Meredith WR, Jack C. McCarty J. An RFLP linkage map of Upland cotton (Gossypium hirsutum L.). Theor Appl Genet,1998a,97:756-761
Shappley ZW, Jenkins JN, Zhu J, Jack C. McCarty J. Quantitative trait loci associated with agronomic and fiber traits of upland cotton. J Cotton Sci,1998b,2:153-163
Shaver T N, R H Dilday. Measurement of and correlations among selected seed quality actors for 36 Texas race stock s of cotton. Crop Sci,1982,22:779-781
Shen X L, Guo W Z, Zhu X, Yuan Y L, Yu J Z, Kohel R J, Zhang T Z. Molecular mapping of QTLs for fiber qualities in three diverse lines in Upland cotton using SSR markers. Molecular Breeding,2005, 15:169-181
Shen X, Zhang T, Guo W, Zhu X, Zhang X. Mapping fiber and yield QTL with main, epistatic, and QTL×environment interaction effects in recombinant inbred lines of upland cotton. Crop Sci,2006,46: 61
Shen X, Guo W, Lu Q, Zhu X, Yuan Y, Zhang T. Genetic mapping of quantitative trait loci for fiber quality and yield trait by RIL approach in upland cotton. Euphytica,2007,155:371-380
Singh M, Singh TH, Chahal GS. Genetics analysis of some seed quality characters in upland cotton (G. hirsutum L.).TAG,1985,71:126-128
Song XL, Zhang TZ. Identification of quantitative trait loci controlling seed physical and nutrient traits in cotton. Seed Science Research,2007,17:243-251
Speed TR, Kzieg D.R, Jividen G. Relationship between cotton seedling cold tolerance and physical and chemical properties. Proceedings Beltwide Cotton Conferences,1996,2:1170-1171
Turner JH, Ramey HH, Jr. and Smith Worley Jr.. Relationship of yield, seed quality and fiber properties in upland cotton. Crop Sci,1976,16:578-580
Ulloa M, Meredith WR, Shappley ZW, Kahler AL. RFLP genetic linkage maps from four F_(2-3) populations and a joinmap of Gossypium hirsutum L. Theor Appl Genet,2002,104:200-208
Ulloa M, Meredith WR. Genetic linkage map and QTL analysis of agronomic and fiber quality traits in an intraspecific population. Cotton Science,2000a,4:161-171.
Ulloa M, Cantrell RG, Percy RG, Zeiger E, Lu Z. QTL analysis of stomatal conductance and relationship to lint yield in an interspecific cotton. J Cotton Sci,2000b,4:10-18
Van Ooijen JW. MapQTL5.0 software for the maping of quantitative trait loci in experimental population. Plant Research International BV, Wageningen,2002. The Netherlands Arailable at http://www.intl-pag.org
Voorrips RE. MapChart:Software for the graphical presentation of linkage maps and QTL. J. Hered,2002, 93:77-78, Available at hattp://www.biometris.nl
Wan Q, Zhang ZS, Hu MC, Chen L, Liu DJ, Chen X, Wang W, Zheng J. T, locus in cotton is the candidate gene affecting lint percentage, fiber quality and spiny bollworm(Earias spp.) resistance. Euphytica, 2007,158:241-247
Wang B, Guo W, Zhu X, Wu Y, Huang N, Zhang T. QTL mapping of fiber quality in an elite hybrid derived-RIL population of upland cotton. Euphytica,2006,152:367-378
Wendel J F, Brubaker C L, Percival E. Genetic diversity in Gossypim hirsutum and the origin of Upland cotton. Am J Bot,1992,79:1291-1310
Williams GK, Kubelik AR, Livak KJ, Rafalski JA, Tingey SV. DNA polymorphisms amplified by arbitrary primers are useful as genetic markers. Nucleic Acid res,1990,18:6531-6534
Willson FD,Lee JA. Interralationships among gland density, gossypol content and lint and seed characters in cotton. Crop Sci,1976,16:860-861
Wright RJ, Thaxton PM, El-Zik KM, Paterson AH. D-sub-genome bias of Xcm resistance genes in tetraploid Gossypium(cotton) suggests that polyploid formation has created novel avenues for evolution. Genetics,1998,149:1987-1996
Wright RJ, Thaxton PM, El-Zik KM, Paterson AH. Molecular mapping of genes affecting pubescence of cotton. J Hered,1999,90:215-219
Wu MQ, Zhang XL, Nie YC, He DH. Localization of QTLs for yield and fiber quality traits of tetraploid cotton cultivar. Acta Genetica Scinica,2003,30:443-452.
Young ND, Tanksley SD. RFLP analysis of the size of chromosomal segments retained around the Tm-2 locus of tomato during backross breeding. Theor Appl Genet,1989,77:353-359
Yu ZH, Park YH, Lazo GR, Wolff NC, Kohel RJ. Molecular map-ping of cotton genome and its application to cotton improvement. Proc Belt Cotton Pro Res Conf,1996:636-637
Zabeau M, Vos P. Selective restriction fragment amplification:a general method for DNA fingerprinting. European Patent Application.1993, Publication No.0 534 858 A1
Zietkiewicz E, Rafalski A, Labuda D. Genome fingerprinting by simple sequence repeat (SSR)-auchored polymerase chain reaction amplification. Genomics,1994,20:176-183
Zhang TZ, Yuan YL, Yu J, Guo WZ, Kohel RJ. Molecular tagging of a major QTL for fiber strength in Upland cotton. Theor. Appl. Genet.,2003,106:262-268
Zhang Z, Xiao Y, Luo M, Li X, Luo X, Hou L, Li D & Pei Y. Construction of a genetic linkage map and QTL analysis of fiber-related traits in upland cotton (Gossypium hirsutum L.). Euphytica,2005,144: 91-99
Zhang ZS, Hu MC, Zhang J, Liu DJ, Zheng J, Zhang Ke, Wang W, Wan Q. Construction of a comprehensive PCR-based marker linkage map and QTL mapping for fiber quality traits in (Gossypium hirsutum L.).Molecular Breeding,2009,24:49-61
Zhu J, Weir BS. Analysis of cytoplasmic and maternal effects:I, a genetic model for diaploid plant seeds and animals. Theoretical and Applted Genetics,1994,89:153-159
董合忠,李维江,张晓洁.棉花种子学.北京,科学出版社,2004a,46-48
董合忠,李维江,唐薇,张晓洁,刘继永,崔正鹏,张冬梅.生态条件和制种期对棉花杂交种质量的影响.棉花学报,2004b，16(5)：265-269
范术丽,喻树迅,宋美珍,原日红.短季棉早熟性的分子标记及QTL定位.棉花学报,2006，18(3)：135～13
房卫平,许守明,孙玉堂,唐中杰,王家典.棉花抗黄萎病的RAPD标记.河南农业科学,2001(9)：11-13
高玉千,聂以春,张献龙.棉花抗黄萎病基因的QTL定位.棉花学报,2003，15(2)：73～78
季道藩,朱军.陆地棉品种间杂种的种仁油分和氨基酸成份的遗传分析.作物学报,1988，14(1)：1-6
葛海燕,汪业春,郭旺珍,张天真.陆地棉抗黄萎病性状的遗传及分子标记研究.棉花学报,2008,20(1)：19-22
胡美纯.陆地棉遗传图谱构建与纤维品质性状QTL定位[硕士学位论文].重庆：西南大学,2008
胡文静,张晓阳,张天真,郭旺珍.陆地棉优质纤维QTL的分子标记筛选及优质来源分析.作物学报,2008,34(4)：578-586
李成奇,郭旺珍,马晓玲,张天真.陆地棉衣分差异群体产量及产量构成因素的QTL标记和定位.棉花学报,2008,20(3)：163-169.
李大庆,钱大顺,倪金柱.棉铃发育研究-Ⅳ.伏桃、晚秋桃棉籽质量的鉴定.江苏农业科学,1982，3：21-24
李维明,吴为人,卢浩然.检测作物数量性状基因与遗传连锁关系的方差分析法及应用.作物学报,1993,19(2)：92-102
刘冬青,庞居勤,葛逢珠.棉花不同品种棉子仁粗蛋白、粗脂肪含量在不同地点差异的分析.江西棉花,1995,4：11-12
刘明,范君华,由宝昌,梅拥军.海岛棉棉仁蛋白质和脂肪含量分析.作物品种资源，1994(4)：25-28.
刘巷禄,袁钧,李永山,潘转霞,樊立强.棉花种子质量对棉花生长发育及产量效应的影响.山西农业科学,1997,25(4)：40-43
秦永生,刘任重,梅鸿献,张天真,郭旺珍.陆地棉产量相关性状的QTL定位.作物学报,2009，35(10)：1812-1821
沈乃愚,陈铭狄,叶惠珍.不同成熟度棉种的素质及其育苗效果研究简报.中国棉花学会论文集, 1981,35-36
盛志廉,陈瑶生.数量遗传学.科学出版社,1999：340-347
孙善康,陈建华,项时康,魏守军.棉花种子营养品质研究.中国农业科学,1987，20(5)：12-16
唐薇,张冬梅,李振怀,李维江,董合忠.Bt杂交棉种子的成熟度与某些播种品质指标的关系.种子,2004,23(6)：3-8
王芙蓉,刘任重,王留明,张传云,刘国栋,刘勤红,马小波,张军.陆地棉品种抗黄萎病性状的分子标记及其辅助选择效果.棉花学报,2007,19(6)：424-430
王红梅,张献龙,贺道华,林忠旭,聂以春,李运海,陈伟.陆地棉对黄萎病抗性的分子标记研究.植物病理学报,2005,35(4)：333～339
王国印,李蒙恩.棉子品质性状的遗传研究.华北农学报,1991，6(2)：20-25
王国建,朱军,臧荣春,许馥华,季道藩.陆地棉棉仁营养品质及种子物理性状的遗传相关分析.浙江农业大学学报,1996,22(6)：585-590
王娟,郭旺珍,张天真.渝棉1号优质纤维QTL的标记与定位.作物学报,2007，33(12)：1915-1921
王沛政,秦利,苏丽,胡保民,张天真.新疆陆地棉主栽品种部分产量性状QTL的标记与定位.中国农业科学,2008，41(10)：2947-2956
王学德,俞碧霞,夏如冰,王洁.低酚棉产量、纤维品质和棉仁营养品质的表现及其相关性.浙江农业科学,1989,(3)：118-120
王延琴,杨伟华,周大云,许红霞,冯新爱,夏俊英.棉子营养成分与发芽率及出苗率的关系.棉花学报,2003,15(20)：109-112
汪保华.湘杂棉2号强优势组合杂种优势表现的遗传机理研究[博士学位论文].南京农业大学,2006,79-88
魏红,钟红舰,汪红.索氏抽提法测定粗脂肪含量的改进.中国油脂,2004，29(6)：52-54.
吴吉样,王国建,朱军,许馥华,季道藩.陆地棉种子性状直接效应和母体效应的遗传分析.作物学报,1995,21(6)：659-664
吴茂清,张献龙,聂以春,贺道华.四倍体栽培棉种产量和纤维品质性状的QTL定位(英文).遗传学报,2003,30(5)：443-452
项时康,孙善康.1982.陆地棉种子蛋白质、脂肪含量与籽指、衣分的相关性.中国棉花,(3)：27-28
闰建庆,胡保民,陈爱民.新疆陆地棉棉子粗脂肪和粗蛋白的研究.新疆农业科学,2000(3)：106-109.
杨奎华.陆地棉种仁脂肪含量及蛋白质等几种性状相关性的研究. 棉花学报,1985，1：48-53
殷剑美,武耀廷,张军,张天真,郭旺珍,朱协飞.陆地棉产量性状QTLs的分子标记及定位.生物工程学报,2002,18(3)：162-166
张培通,郭旺珍,朱协飞,俞敬忠,张天真.高产棉花品种泗棉3号产量及其构成因素的QTL标记和定位.作物学报,2006,32(8)：1197-1203
张培通,朱协飞,郭旺珍, 张天真.陆地棉衣分及相关性状的遗传和QTL分子标记.江苏农业学
报,2005,21(4)：264～271
张天真,郭旺珍.棉花分子育种的现状、问题与展望.中国农业科技导报,2007，9(2)：19～25
张正圣.陆地棉遗传连锁图谱的构建与纤维相关性状QTL分析[博士学位论文].重庆：西南农业大学,2005
郑靓,张正圣,陈利,万群,胡美纯,王威,张轲,刘大军,陈笑,魏新琦.IT-ISJ标记及其在陆地棉遗传图谱构建中的应用.中国农业科学,2008，39：2241-2248
周治国,许玉章,许萱. 棉子品质与纤维品质及铃期温度相关性的研究.陕西农业科学,1992,(3)：3-5
周有耀.棉花种子营养品质与纤维品质的关系.中国棉花,1993，(2)：13-14
周延清.DNA分子标记技术在植物研究中的应用.化学工业出版社,2005,11-15
朱乾浩,俞碧霞,许复华.低酚棉品种间杂种产量性状的遗传分析.棉花学报,1994，6(4)：215-220
朱乾浩,俞碧霞,许复华.低酚棉棉子品质性状的遗传分析.棉花学报，1995,7(2)：94-99
朱军.Mixed model approaches for estimating genetic varances and covariances.生物数学学报,1992,(7)：1-11
左开井,孙济中,张献龙,聂以春,刘金兰,冯纯大.利用RFLP、SSR和RAPD标记构建陆地棉分子标记连锁图.华中农业大学学报,2000，19(3)：190-193
Alford BB, Liepa GU, Vanbeber AD. Cottonseed protein:What does the future hold? Plant Foods for Humam Nutrition.1996,49:1-11
Ali S, Muller CR, Epplen JT. DNA finger printing by oligonucleotide probes specific for simple repeats. Hum. Genetics,1986, (74):239-243
Bolek Y, El-Zik KM, Pepper AE, Bell AA, Magill CW, Thaxton PM, Reddy UK. Mapping of Verticilliumwilt resistance genes in cotton. Plant Sci,2005,168(66):1581-1590
Botsien D, White RL, Skolnick M, Davis RW. Construction of a genetic map in man using restriction fragment polymorphisms. Am J Hum Genet,1980,32:314-331
Chee P, Draye X, Jiang CX, Decanini L, Delmonte TA, Bredhauer R, Smithc W, Parterson AH. Molecular dissection of phenotypic variation between Gossypium hirsutum and Gossypium barbadense (cotton) by a backcross-self approach:Ⅲ. Fiber length. Theor. Appl. Genet.,2005,111:772-781
Chen ZJ, Scheffler BE, Dennis E, Triplett BA, Zhang T, Guo W, Chen X, Stelly DM, Rabinowicz PD, Town CD, Arioli T, Brubaker C, Cantrell RG, Lacape JM, Ulloa M, Chee P, Gingle AR, Haigler CH, Percy R, Saha S, Wilkins T, Wright RJ, Deynze AV, Zhu Y, Yu S, Abdurakhmonov I, Katageri I, Kumar PA, Rahman M, Zafar Y, Yu JZ, Kohel RJ, Wendel JF, Paterson AH. Toward sequencing cotton (Gossypium) genomes. Plant Physiol,2007,145:1303-1310
Collins FS, Guyer MS, Chakravarti A. Variations on a theme:cataloging human DNA sequence variation. Science,1997,278:1580-1581
Collins NC, Webb CA, Seah S, Ellis JG, Hulbert SH, Pryor A. The isolation and mapping of disease resistance gene analogs inmaize. Mol Plant Microbe Interact,1998,11:968-978.
Darvasi A, Soller M. Selective DNA pooling for determination of linkage between a marker and a quantitative trait locus. Genetics,1994,138:1365-1373
Draye X, Chee P, Jiang CX, et al. Molecular dissection of interspecific variation between Gossypium hirsutum and G. Barbadense (cotton) by a backcross-self approach:Ⅱ. Fiber fineness. Theor. Appl. Genet.,2005,111:764-771
Dudley JW. Molecular markers in plant improvement:manipulation of genes affecting quantitative traits. Crop Sci,1993,33:660-668
Dulbeeeo R.A. turning point in gene research:sequencing the human genome. Science,1986, 231:1055-1056
Frelichowski Jr JE, Palmer MB, Main D, Tomkins JP, Cantrell RG, Stelly DM, Yu J, Kohel RJ, Ulloa M. Cotton genome mapping with new microsatellites from Acala 'Maxxa' BAC-ends. Mol. Gen. Genomics,2006,275:479-491
Fryxell PA. A revised taxonomic interption of Gossypium(Malvaceae). Rheelea,1992,2:108-165
Guo W, Cai C, Wang C, Han Z, Song X, Wang K, Niu X,Wang C, Lu K, Shi B. Zhang T. A microsatellite-based, gene-rich linkage map reveals genome structure, function and evolution in Gossypium. Genetics,2007,176:527-541
Guo W, Cai C, Wang C, Zhao L, Wang L, Zhang T. A preliminary analysis of genome structure and composition in Gossypium hirsutum. BMC Genomics,2008,9:314-331
Guo W, Ma G, Zhu Y, Yi C, Zhang T. Molecular tagging and mapping of quantitative trait loci for lint percentage and morphological marker genes in upland cotton. J Integrative Plant Biology,2006,48: 320-326
Han Z G, Guo W Z, Song X L, Zhang T Z. Genetic mapping of EST-derived microsatellites from the diploid (Gossypium arboreum) in allotetraploid cotton. Molecular Genet Genom,2004,272:308-327
Hanny BW, Meredith WR, Jr., Bailey JC, Harvey AJ. Gentics relationships among chemical constituents in seed,.flower buds terminals and mature leaves of cotton. Crop Sci,1978,18:1071-1074
He DH, Lin ZX, Zhang XL, Nie YC, Guo XP, Feng CD, Stewart JM. Mapping QTLs of traits contributing to yield and analysis of genetic effects in tetraploid cotton. Euphytica,2005,144:141-149
He DH, Lin ZX, Zhang XL, Nie YC, Guo XP, Zhang YX, Li W. QTL mapping for economic traits based on a dense genetic map of cotton with PCR-based markers using the interspecific cross of Gossypium hirsutum × Gossypium barbadense. Euphytica,2007,153:181-197
Hu J, Vick BA. Target Region Amplification Polymorphism:A novel marker technique for plant genotyping. Plant Molecular Biology Reporter,2003,21:289-294
Jefferys AJ, Wilson V, Thein SL. Hypervariable "microsatellite" regions in human DNA. Nature,1985, (316):76-79
Jiang CX, Wright RJ, Woo SS, DelMontelTA, Paterson AH. QTL analysis of leaf morphology in tetraploid Gossypium(cotton).Thero Appl Genet,2000,100:409-418
Jiang CX, Wright RJ, El-Zik KM, Paterson AH. Polyploid formation created unique avenues for response to selectionin Gossypium (cotton). Proc Natl Acad Sci USA,1998,95:4419-4424
Khan MA, Steward JM, Zhang J, et al. Addition of new markers to the trispecific cotton map[C]//Proc of the beltwide cotton conference. National Cotton Council, Memphis, TN,1999:439
Kohel R J. Genetic studies of seed oil in cotton.Crop Sci,1980,20:784-788
Kohel RJ, Yu J, Park YH, Lazo GR. Molecular mapping and characterization of traits controlling fiber quality in cotton. Euphytica,2001,121:163-172.
Kosambi DD. The estimation of map distance from recombination values. Ann. Eugen,1944,12:172-175
Lacape JM, Jacobs J, Arioli T, Derijcker R, Forestier-Chiron N, Llewellyn D, Jean J, Thomas E, Viot C. A new interspecific, Gossypium hirsutum × G. barbadense, RIL population:towards a unified consensus linkage map of tetraploid cotton. Theor Appl Genet,2009,119:281-292
Lander ES, Botstein D. Mapping Mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics,1989,121:185-199
Lee JA, Cockerham CC, Smith FH. The inheritance of gossypol level in Gossypium I.Additive, dominance, epistatic and maternal effects associated with seed gossypol in two varieties of G. hirsutum L. Genetics, 1968,59:285-298
Li G, Quiros C F. Sequence-related amplified polymorphism (SRAP), a new marker system based on a simple PCR reaction:its application to mapping and gene tagging in Brassica. Theoretical and Applied Genetics,2001,103:455-461.
Lin ZX, He DH, Zhang X L, Nie Y C, Guo X P, Feng C D, James M D. Linkage map construction and mapping QTL for cotton fiber quality using SRAP,SSR and RAPD. Plant Breeding,2005, 124:180-187.
Lin ZX, Zhang YX, Zhang XL, Guo XP. A high-density integrative linkage map for Gossypium hirsutum. Euphytica,2009,166:35-45
Lowe AJ, Moule C, Trick M, Edwards KJ. Efficient large-scale development of microsatellites for marker and mapping applications in Brassica crop species. Theoretical and Applied Genetics,2004, 108:1103-1112
Lusas EW & Jividen GM. Glandless cottonseed:A review of the first 25 years of processing and utilization research. J Am Oil Chem Soc,1987,64:839-854
Lyon. DNA markers and molecular breeding of cotton. The Australian cotton grower,1999,20 (5):80-83.
Malm N. Combining ability and heritability of protein and oil content in upland cotton. Proc Belt Cotton Prod Res Conf,1979:83-84
McCouch SR, Cho YG, Yano M, Paul E, Morishima H and Kinoshita T. Report on QTL nomenclature. Rice. Genet. Newsl.,1997,14:11-13
Mei M, Syed NH, Gao W, Thaxton PM, Smith CW, Stelly DM, Chen ZJ. Genetic mapping and QTL analysis of fiber-related traits in cotton (Gossypium). Theoretical and Applied Genetics,2004, 108:280-291
Olson M, Hood L, Cantor C, Botstein D. A common language for physical mapping of the human genome. Science,1989,245:1434-1435
Park YH, Alabady MS, Ulloa M, Sickler B, Wilkins TA, Yu J, Stelly DM, Kohel RJ, el-Shihy OM, Cantrell RG. Genetic mapping of new cotton fiber loci using EST-derived microsatellites in an interspecific recombinant inbred line cotton population. Mol. Gen. Genomics,2005,274:428-441
Paterson AH, Saranga Y, Menz M, Jiang CX, Wright RJ. QTL analysis of genotypex environment interaction affecting cotton fiber quality. Theor Appl Genet,2003,6:384-396
Pizzinatto MA, Menten JOM, Soave J, Cia E, Maeda JA. Relationship between cotton seed weight and quality. Bragantia,1991,50:269-289
Qin H, Guo W, Zhang YM, Zhang T. QTL mapping of yield and fiber traits based on a four-way cross population in Gossypium hirsutum L. TAG Theoretical and Applied Genetics,2008,117:883-894
Qureshi SN, Saha S, Kantety RV, Jenkins JN. EST-SSR:a new class of genetic markers in cotton. J Cotton Science,2004,8:112-123
Ramalingam J, Vera Cruz CM, Kukreja K, Chittoor JM, Wu JL, Lee SW, Baraoidan M, George ML, Cohen MB, Hulbert SH, Leach JE, Leung H. Candidate defense genes from rice, barley, and maize and their association with qualitative and quantitative resistance in rice. Mol. Plant Microbe Interact,2003, 16:14-24
Reinisch AJ, Dong JM, Brubaker CL, Stelly DM, Wendel JF, Paterson AH. A detailed RFLP map of cotton, Gossypium hirsutum × Gossypium barbadense:chromosome organization and evolution in a disomic polyploid genome. Genetics,1994,138:829-847
Ren LH, Guo WZ, Zhang TZ. Identification of quantitative trait loci (QTLs) affecting yield and fiber properties in chromosome 16 in cotton using substitution line. Acta Botanica Sinica,2002,44(7): 815-820
Risch N, Merikangas K.The future of genetic studies of complex human diseases. Science,1996, 273:1516-1517
Rong J, Abbey C, Bowers JE, Brubaker CL, Chang C, Chee PW, Delmonte TA, Ding X, Garza JJ, Marler BS, Park C-h, Pierce GJ, Rainey KM, Rastogi VK, Schulze SR, Trolinder NL, Wendel JF, Wilkins TA, Williams-Coplin TD, Wing RA, Wright RJ, Zhao X, Zhu L, Paterson AH. A 3347-locus genetic recombination map of sequence-tagged sites reveals features of genome organization, transmission and evolution of cotton (Gossypium). Genetics,2004,166:389-417
Saha S, Karaca M, Jenkins J N, Zipf A E, Reddy OUK, Kantety R V. Simple sequence repeats as useful resources to study transcribed genes of cotton. Euphytica,2003,130:355-364
Saranga Y, Jiang CX, Wright RJ, Yakir D, Paterson AH. Genetic dissection of cotton physiological responses to arid conditions and their inter-relationships with productivity. Plant Cell and environment, 2004,27:263-277
Sax K. The association of size differences with seed-coat pattern and pigmentation in phaseolus vulgaris. Genetics,1923,8(6):552-560
Shappley ZW, Jenkins JN, Meredith WR, Jack C. McCarty J. An RFLP linkage map of Upland cotton (Gossypium hirsutum L.). Theor Appl Genet,1998a,97:756-761
Shappley ZW, Jenkins JN, Zhu J, Jack C. McCarty J. Quantitative trait loci associated with agronomic and fiber traits of upland cotton. J Cotton Sci,1998b,2:153-163
Shaver T N, R H Dilday. Measurement of and correlations among selected seed quality actors for 36 Texas race stock s of cotton. Crop Sci,1982,22:779-781
Shen X L, Guo W Z, Zhu X, Yuan Y L, Yu J Z, Kohel R J, Zhang T Z. Molecular mapping of QTLs for fiber qualities in three diverse lines in Upland cotton using SSR markers. Molecular Breeding,2005, 15:169-181
Shen X, Zhang T, Guo W, Zhu X, Zhang X. Mapping fiber and yield QTL with main, epistatic, and QTL×environment interaction effects in recombinant inbred lines of upland cotton. Crop Sci,2006,46: 61
Shen X, Guo W, Lu Q, Zhu X, Yuan Y, Zhang T. Genetic mapping of quantitative trait loci for fiber quality and yield trait by RIL approach in upland cotton. Euphytica,2007,155:371-380
Singh M, Singh TH, Chahal GS. Genetics analysis of some seed quality characters in upland cotton (G. hirsutum L.).TAG,1985,71:126-128
Song XL, Zhang TZ. Identification of quantitative trait loci controlling seed physical and nutrient traits in cotton. Seed Science Research,2007,17:243-251
Speed TR, Kzieg D.R, Jividen G. Relationship between cotton seedling cold tolerance and physical and chemical properties. Proceedings Beltwide Cotton Conferences,1996,2:1170-1171
Turner JH, Ramey HH, Jr. and Smith Worley Jr.. Relationship of yield, seed quality and fiber properties in upland cotton. Crop Sci,1976,16:578-580
Ulloa M, Meredith WR, Shappley ZW, Kahler AL. RFLP genetic linkage maps from four F_(2-3) populations and a joinmap of Gossypium hirsutum L. Theor Appl Genet,2002,104:200-208
Ulloa M, Meredith WR. Genetic linkage map and QTL analysis of agronomic and fiber quality traits in an intraspecific population. Cotton Science,2000a,4:161-171.
Ulloa M, Cantrell RG, Percy RG, Zeiger E, Lu Z. QTL analysis of stomatal conductance and relationship to lint yield in an interspecific cotton. J Cotton Sci,2000b,4:10-18
Van Ooijen JW. MapQTL5.0 software for the maping of quantitative trait loci in experimental population. Plant Research International BV, Wageningen,2002. The Netherlands Arailable at http://www.intl-pag.org
Voorrips RE. MapChart:Software for the graphical presentation of linkage maps and QTL. J. Hered,2002, 93:77-78, Available at hattp://www.biometris.nl
Wan Q, Zhang ZS, Hu MC, Chen L, Liu DJ, Chen X, Wang W, Zheng J. T, locus in cotton is the candidate gene affecting lint percentage, fiber quality and spiny bollworm(Earias spp.) resistance. Euphytica, 2007,158:241-247
Wang B, Guo W, Zhu X, Wu Y, Huang N, Zhang T. QTL mapping of fiber quality in an elite hybrid derived-RIL population of upland cotton. Euphytica,2006,152:367-378
Wendel J F, Brubaker C L, Percival E. Genetic diversity in Gossypim hirsutum and the origin of Upland cotton. Am J Bot,1992,79:1291-1310
Williams GK, Kubelik AR, Livak KJ, Rafalski JA, Tingey SV. DNA polymorphisms amplified by arbitrary primers are useful as genetic markers. Nucleic Acid res,1990,18:6531-6534
Willson FD,Lee JA. Interralationships among gland density, gossypol content and lint and seed characters in cotton. Crop Sci,1976,16:860-861
Wright RJ, Thaxton PM, El-Zik KM, Paterson AH. D-sub-genome bias of Xcm resistance genes in tetraploid Gossypium(cotton) suggests that polyploid formation has created novel avenues for evolution. Genetics,1998,149:1987-1996
Wright RJ, Thaxton PM, El-Zik KM, Paterson AH. Molecular mapping of genes affecting pubescence of cotton. J Hered,1999,90:215-219
Wu MQ, Zhang XL, Nie YC, He DH. Localization of QTLs for yield and fiber quality traits of tetraploid cotton cultivar. Acta Genetica Scinica,2003,30:443-452.
Young ND, Tanksley SD. RFLP analysis of the size of chromosomal segments retained around the Tm-2 locus of tomato during backross breeding. Theor Appl Genet,1989,77:353-359
Yu ZH, Park YH, Lazo GR, Wolff NC, Kohel RJ. Molecular map-ping of cotton genome and its application to cotton improvement. Proc Belt Cotton Pro Res Conf,1996:636-637
Zabeau M, Vos P. Selective restriction fragment amplification:a general method for DNA fingerprinting. European Patent Application.1993, Publication No.0 534 858 A1
Zietkiewicz E, Rafalski A, Labuda D. Genome fingerprinting by simple sequence repeat (SSR)-auchored polymerase chain reaction amplification. Genomics,1994,20:176-183
Zhang TZ, Yuan YL, Yu J, Guo WZ, Kohel RJ. Molecular tagging of a major QTL for fiber strength in Upland cotton. Theor. Appl. Genet.,2003,106:262-268
Zhang Z, Xiao Y, Luo M, Li X, Luo X, Hou L, Li D & Pei Y. Construction of a genetic linkage map and QTL analysis of fiber-related traits in upland cotton (Gossypium hirsutum L.). Euphytica,2005,144: 91-99
Zhang ZS, Hu MC, Zhang J, Liu DJ, Zheng J, Zhang Ke, Wang W, Wan Q. Construction of a comprehensive PCR-based marker linkage map and QTL mapping for fiber quality traits in (Gossypium hirsutum L.).Molecular Breeding,2009,24:49-61
Zhu J, Weir BS. Analysis of cytoplasmic and maternal effects:I, a genetic model for diaploid plant seeds and animals. Theoretical and Applted Genetics,1994,89:153-159