利用三个重叠重组自交系精细定位棉花染色体24部分区段的纤维品质及产量性状QTL
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摘要
棉花是重要的纺织工业原料。棉花工作者长期以来面对的挑战是产量和纤维品质的同步提高以满足棉花生产者和纺织工业的要求。随着纺织技术的不断发展,对棉纤维品质提出了更高的要求,从而更多地要求更强、更细和更整齐的棉纤维。然而,由于纤维品质性状的复杂性,加上纤维品质检测的费用高和选择效率低,棉纤维品质的改良虽经过几十年的艰苦努力,纤维品质与产量的负相关依然存在,传统育种在进一步改良棉纤维品质上显然存在相当的困难。发展与棉纤维品质和产量性状连锁的DNA标记使得育种者在棉花生长的早期阶段或早期分离世代就能追踪这个重要的性状,从而提高选择效率。
然而目前有关棉纤维品质和产量QTLs的筛选方面存在以下问题：(1)使用的群体多为海陆种间群体,用于陆地棉品质改良难度大；(2)使用的群体大多为F2暂时性群体,无法进行多年多点重复试验,难以获得稳定的QTLs。本研究在(7235×TM-1)RIL、(7235×TM-1)F2以及F2：3群体与纤维品质及产量性状相关的QTL定位研究结果的基础,利用(7235×TM-1)RIL中三个互相重叠而且是高强纤维的家系7TR-133,7TR-132和7TR-214再与TM-1回交,构建三个F2及F2：3群体,开展两年两点的重复试验,用基于PCR的SSR标记筛选不同环境中稳定表达的主效QTLs,为优质高产棉基因的利用提供理论依据。进行(7235×TM-1)重组自交系(RILs)三个家系(7TR-133,7TR-132和7TR-214)回交F2：3群体棉纤维品质与产量性状相关性以及F2和F2：3遗传性分析,以便从分子水平上揭示主要品质性状与主要产量构成因子性状相关性,进一步明确了棉花纤维品质与产量性状的遗传特性。主要研究结果如下：
1.主要纤维品质性状及产量性状相关性分析
纤维品质性状长度与强度正相关,细度与伸长率正相关,铃数与衣分正相关,长度性状与铃重正相关；纤维强度和细度与伸长率负相关,长度性状与铃数和衣分性状负相关,强度性状与产量性状铃数、铃重、衣分负相关,细度性状与铃数和铃重性状负相关,伸长率与铃数、铃重负相关,产量性状铃数与铃重负相关,铃重与衣分负相关。
2.主要纤维品质性状及产量性状遗传分析
主要纤维品质性状(纤维长度、纤维强度、麦克隆值、伸长率)及产量构成因子单株铃数、铃重、衣分的最佳遗传模式为两对主基因控制的遗传模型,其中加性效应在F2以及新疆和江浦两地的F2：3世代中能够稳定表达。在不同群体和世代中,品质和产量性状主基因遗传率不同可能由于控制数量性状的基因间互作以及基因与环境间互作的结果。
3.遗传连锁图普的构建
本研究利用6123对SSR引物进行三个群体四个亲本(7TR-133,7TR-132,7TR-214和TM-1)多态性筛选,构建(7TR-133×TM-1)F2,(7TR-132×TM-1)F2和(7TR-214×TM-1)F2分子遗传图谱,构建遗传图谱的群体大小分别是907,670和940,所构建的(7TR-133×TM-1)群体遗传图谱具有22个标记位点,长度为13.7cM,占Chro.24染色体遗传图谱111.7cM的12.3%；(7TR-132×TM-1)群体遗传图谱具有11个标记位点,长度为19.1cM,占Chro.24染色体遗传图谱111.7cM的17.1%；(7TR-214×TM-1)群体遗传图谱具有18个标记位点,长度为10.1cM,占Chro.24染色体遗传图谱111.7cM的9.4%。在构建图谱的22,11和18个标记中分别有16,7和10个偏分离标记,其偏分离位点的百分率分别是72.7%,63.6%和55.6%,由此可见,(7TR-132xTM-1)F2,(7TR-133×TM-1)F2和(7TR-214×TM-1)F2偏分离位点比(7235xTM-1)RIL的100%偏分离明显下降。
4.纤维品质性状QTL定位分析
PopA(7TR-133×TM-1)、PopB(7TR-132×TM-1)和PopC(7TR-214×TM-1)三个群体中检测到与纤维品质性状相关的QTLs共17个,其中,与纤维长度性状相关的5个QTLs,具有20.1-32.7%贡献率；与强度性状相关的5个QTLs,具有28.8-59.6%贡献率；与细度相关的4个QTLs,具有17.9-41.5%贡献率；与伸长率相关的3个QTLs,具有18.0-26.2%贡献率。与品质性状相关的QTL的增效基因在三个作图群体中具有较好的一致性，其中纤维强度、纤维长度以及纤维细度性状来自母本(7235×TM-1)RIL的家系7TR-133,7TR-132和7TR-214(纤维长度和强度增加,纤维细度降低),纤维伸长率来自父本TM-1(伸长率增加)。
5.产量性状QTL的定位
PopA(7TR-133×TM-1)、PopB(7TR-132xTM-1)和PopC(7TR-214×TM-1)三个群体中检测到与产量性状相关的QTLs共6个,其中,与铃数性状相关的1个QTL,具有5.6-9.4%贡献率；与铃重性状相关的3个QTLs,具有15.0-35.5%贡献率；与衣分性状相关的2个QTLs,具有10.9-19.3%。产量性状铃数、铃重增效基因来自父本TM-1(铃数和铃重增加),衣分性状增效基因来自母本(7235xTM-1)RIL家系7TR-133、7TR-132和7TR-214(衣分增加)。
本实验研究在(7235×TM-1)RIL群体棉花染色体24上与纤维强度性状相关的QTL的置信区间内,在三个互相重叠(7235×TM-1)RIL家系7TR-133,7TR-132,7TR-214与TM-1回交群体中共检测到五个紧密连锁的强度性状QTL,其原因可能与进一步进行了回交以及使用了较大的研究群体有关。在本研究中的两个回交群体中检测到与铃数性状相关的QTL,即q-BN-D08,与Shen et al.在(7235×TM-1)RIL检测到的与铃数性状相关的QTL为同一个,由此可见该QTL是一个较为稳定的QTL。
纤维品质及产量性状的遗传分析结果,主要品质及产量性状由两对主基因控制,并且以加性效应为主。纤维品质性状和产量性状相关性分析结果,主要品质性状与主要产量性状呈负相关,QTL定位分析结果,主要优质性状基因来自母本(7235×TM-1)RIL家系7TR-133,7TR-132和7TR-214,主要高产基因来自父本TM-1,因此,在棉花品种的培育与改良中,同步提高纤维品质及产量具有一定的难度。
Cotton is an important cash crop in the world. A long-term challenge facing cotton breeder is the simultaneous improvement of yield and fiber quality to meet the demands of the cotton producer as well as the textile industry. In the recent years, improvement of cotton fiber quality has been extremely important because of changes in spinning technology. However, a negative association between lint yield and fiber quality are still presented after over dozens years of exhausting breeding for improved fiber properties due to the genetic complexity of fiber quality properties. Conventional breeding procedures exist difficulty in further improving fiber quality because of its high costs, long duration, and low selective efficiency. The development of DNA markers linked to the fiber quality QTL would allow cotton breeders to trace this very important trait in early plant-growing stage or early segregating generations. The use of these DNA markers is increasing the prospect for streamlining the cotton breeding programs for improving fiber quality while maintaining fiber yield.
However, QTL analysis for fiber properties is problematic:(1) QTLs obtained from interspecies population of Sealand cotton and Upland cotton showed less valuable in improving fiber quality of Upland cotton; (2) In previous reports, population constructed were all F2 population. Replicated experiment couldn't be carried out and common QTLs couldn't be got. Considering of these problems above, the objective of this research is to develop three F2 and F2:3 populations, by using 7TR-133,7TR-132,7TR-214, which derived from a cross between 7235 and TM-1 using a bulk-selfing technique, as female parent, backcrossed with TM-1 to identify fine located of common QTL associated with fiber quality and yield component traits across different background and different generations by PCR to screen SSR markers. Second, in order to provide theory for employing super quality and high yield, replicated experiment of two years and two locations in the present were used to identify stable major QTLs of fiber quality and yield component traits. The present result as following:
1. Correlation analysis for fiber quality and yield traits
Positive correlation was observed between fiber length and fiber strength, between fineness and elongation, between bolls per plant and lint percentage, between fiber length and boll size, and negative correlations between strength and fineness, strength and fiber elongation, between bolls per plant and boll size, boll size and lint percentage, between fiber length and bolls per plant and lint percentage, between fiber strength and bolls per plant, fiber strength and boll size, fiber strength and lint percentage, between fiber fineness and bolls per plant, fineness and boll size, between fiber elongation and bolls per plant, elongation and boll size.
2. Genetic analysis for fiber quality and yield components
Fiber quality (fiber length, fiber strength, fiber fineness and fiber elongation) and yield components genetic model was controlled by more than one major gene. Additive effect was stably exhibited in F2 and F2:3 generations and different locations (Xinjiang and Jiangpu). In the present research, the herelicity for fiber quality and yield component was different in different generations and locations. It was the reason that the genes for these traits were influenced by themselves and surroundings.
3. Construction of genetic linkage map
Of the 6123 SSR markers employed in this study, polymorphic SSR markers were detected in three populations (between 7TR-133 and TM-1,7TR-132 and TM-1,7TR-214 and TM-1). The three genetic maps for (7TR-133×TM-1) F2, (7TR-132×TM-1) F2, and (7TR-214×TM-1) F2 were generated. The SSR genetic map was constructed using 907 individuals in (7TR-133×TM-1)F2 and included 22 loci covering 13.7 cM, which represented approximately 12.3% of the total 111.7 cM recombinational length of cotton Chro.24. The map constructed from 670 individuals in (7TR-132×TM-1) F2 included 11 loci covering 19.1 cM, approximately 17.1% of the recombinational length of cotton Chro. 24, and the map constructed using 940 individuals in (214-RIL×TM-1) F2 included 18 loci covering 10.1 cM, approximately 9.4% of the recombinational length of cotton Chro.24. Sixteen,7 and 10 distorted SSR loci were detected in (7TR-133×TM-1) F2, (7TR-132×TM-1) F2 and (7TR-214×TM-1) F2. The percent skewed segregation ratios were 72.7%, 63.6%, and 55.6%, respectively, a great deal of decrease from 100% in (7235×TM-1)RIL.
4. QTL tagging for fiber quality
17 QTLs of fiber quality were identified in Pop A (7TR-133×TM-1), Pop B(7TR-132 ×TM-1) and Pop C (7TR-214×TM-1) three populations. Of these QTLs, there were 5 QTLs for fiber length, which exhibited a total phenotypic variance (PV) of 20.1%-32.7%,5 QTLs for fiber strength, which exhibited a total phenotypic variance (PV) of 28.8%-59.6%, 4 QTLs for fiber fineness, which exhibited a total phenotypic variance (PV) of 17.9%-41.5%, and 3 QTLs for fiber elongation, which exhibited a total phenotypic variance (PV) of 18.0%-26.2%. The QTLs for fiber length, fiber strength and fiber fineness were conferred by female parents 7TR-133,7TR-132 and 7TR-214 (increased fiber length and strength, decrease fiber fineness), and the QTL for elongation was conferred by male parent TM-1 (increased fiber elongation).
5. QTL tagging for yield traits
6 QTLs of yield trait were identified in (7TR-133×TM-1) Pop A, (7TR-132×TM-1) Pop B and (7TR-214×TM-1) Pop C populations. Of these QTLs, there were 1 QTLs for bolls per plant, which exhibited a phenotypic variance (PV) of 5.6%-9.4%,3 QTLs for boll size, which exhibited a total phenotypic variance (PV) of 15.0%-35.5%, and 2 QTLs for lint percentage, which exhibited a total phenotypic variance (PV) of 10.9%-19.3%. The QTLs for bolls per plant and boll size were conferred by male parent TM-1 (increased bolls per plant and boll size), and the QTL for lint percentage was conferred by female parent 7TR-133,7TR-132 and 7TR-214(increased lint percentage).
In the present,5 clustered QTL for fiber strength were detected in the three backcross populations among the confidence interval of q-FS-D08 identified by Shen et al. The q-BN-D08 was identified in the three backcross populations and (7235×TM-1) RIL population. It showed that the QTL for bolls per plant was stable and common. There was consistent with the result of genetic analysis and QTL mapping. Fiber quality and yield components were controlled by more than one main gene, and additive effect was mainly. It was difficult to breed and improve fiber quality and yield at same time because there was negative correlation between fiber quality and yield components.
然而目前有关棉纤维品质和产量QTLs的筛选方面存在以下问题：(1)使用的群体多为海陆种间群体,用于陆地棉品质改良难度大；(2)使用的群体大多为F2暂时性群体,无法进行多年多点重复试验,难以获得稳定的QTLs。本研究在(7235×TM-1)RIL、(7235×TM-1)F2以及F2：3群体与纤维品质及产量性状相关的QTL定位研究结果的基础,利用(7235×TM-1)RIL中三个互相重叠而且是高强纤维的家系7TR-133,7TR-132和7TR-214再与TM-1回交,构建三个F2及F2：3群体,开展两年两点的重复试验,用基于PCR的SSR标记筛选不同环境中稳定表达的主效QTLs,为优质高产棉基因的利用提供理论依据。进行(7235×TM-1)重组自交系(RILs)三个家系(7TR-133,7TR-132和7TR-214)回交F2：3群体棉纤维品质与产量性状相关性以及F2和F2：3遗传性分析,以便从分子水平上揭示主要品质性状与主要产量构成因子性状相关性,进一步明确了棉花纤维品质与产量性状的遗传特性。主要研究结果如下：
1.主要纤维品质性状及产量性状相关性分析
纤维品质性状长度与强度正相关,细度与伸长率正相关,铃数与衣分正相关,长度性状与铃重正相关；纤维强度和细度与伸长率负相关,长度性状与铃数和衣分性状负相关,强度性状与产量性状铃数、铃重、衣分负相关,细度性状与铃数和铃重性状负相关,伸长率与铃数、铃重负相关,产量性状铃数与铃重负相关,铃重与衣分负相关。
2.主要纤维品质性状及产量性状遗传分析
主要纤维品质性状(纤维长度、纤维强度、麦克隆值、伸长率)及产量构成因子单株铃数、铃重、衣分的最佳遗传模式为两对主基因控制的遗传模型,其中加性效应在F2以及新疆和江浦两地的F2：3世代中能够稳定表达。在不同群体和世代中,品质和产量性状主基因遗传率不同可能由于控制数量性状的基因间互作以及基因与环境间互作的结果。
3.遗传连锁图普的构建
本研究利用6123对SSR引物进行三个群体四个亲本(7TR-133,7TR-132,7TR-214和TM-1)多态性筛选,构建(7TR-133×TM-1)F2,(7TR-132×TM-1)F2和(7TR-214×TM-1)F2分子遗传图谱,构建遗传图谱的群体大小分别是907,670和940,所构建的(7TR-133×TM-1)群体遗传图谱具有22个标记位点,长度为13.7cM,占Chro.24染色体遗传图谱111.7cM的12.3%；(7TR-132×TM-1)群体遗传图谱具有11个标记位点,长度为19.1cM,占Chro.24染色体遗传图谱111.7cM的17.1%；(7TR-214×TM-1)群体遗传图谱具有18个标记位点,长度为10.1cM,占Chro.24染色体遗传图谱111.7cM的9.4%。在构建图谱的22,11和18个标记中分别有16,7和10个偏分离标记,其偏分离位点的百分率分别是72.7%,63.6%和55.6%,由此可见,(7TR-132xTM-1)F2,(7TR-133×TM-1)F2和(7TR-214×TM-1)F2偏分离位点比(7235xTM-1)RIL的100%偏分离明显下降。
4.纤维品质性状QTL定位分析
PopA(7TR-133×TM-1)、PopB(7TR-132×TM-1)和PopC(7TR-214×TM-1)三个群体中检测到与纤维品质性状相关的QTLs共17个,其中,与纤维长度性状相关的5个QTLs,具有20.1-32.7%贡献率；与强度性状相关的5个QTLs,具有28.8-59.6%贡献率；与细度相关的4个QTLs,具有17.9-41.5%贡献率；与伸长率相关的3个QTLs,具有18.0-26.2%贡献率。与品质性状相关的QTL的增效基因在三个作图群体中具有较好的一致性，其中纤维强度、纤维长度以及纤维细度性状来自母本(7235×TM-1)RIL的家系7TR-133,7TR-132和7TR-214(纤维长度和强度增加,纤维细度降低),纤维伸长率来自父本TM-1(伸长率增加)。
5.产量性状QTL的定位
PopA(7TR-133×TM-1)、PopB(7TR-132xTM-1)和PopC(7TR-214×TM-1)三个群体中检测到与产量性状相关的QTLs共6个,其中,与铃数性状相关的1个QTL,具有5.6-9.4%贡献率；与铃重性状相关的3个QTLs,具有15.0-35.5%贡献率；与衣分性状相关的2个QTLs,具有10.9-19.3%。产量性状铃数、铃重增效基因来自父本TM-1(铃数和铃重增加),衣分性状增效基因来自母本(7235xTM-1)RIL家系7TR-133、7TR-132和7TR-214(衣分增加)。
本实验研究在(7235×TM-1)RIL群体棉花染色体24上与纤维强度性状相关的QTL的置信区间内,在三个互相重叠(7235×TM-1)RIL家系7TR-133,7TR-132,7TR-214与TM-1回交群体中共检测到五个紧密连锁的强度性状QTL,其原因可能与进一步进行了回交以及使用了较大的研究群体有关。在本研究中的两个回交群体中检测到与铃数性状相关的QTL,即q-BN-D08,与Shen et al.在(7235×TM-1)RIL检测到的与铃数性状相关的QTL为同一个,由此可见该QTL是一个较为稳定的QTL。
纤维品质及产量性状的遗传分析结果,主要品质及产量性状由两对主基因控制,并且以加性效应为主。纤维品质性状和产量性状相关性分析结果,主要品质性状与主要产量性状呈负相关,QTL定位分析结果,主要优质性状基因来自母本(7235×TM-1)RIL家系7TR-133,7TR-132和7TR-214,主要高产基因来自父本TM-1,因此,在棉花品种的培育与改良中,同步提高纤维品质及产量具有一定的难度。
Cotton is an important cash crop in the world. A long-term challenge facing cotton breeder is the simultaneous improvement of yield and fiber quality to meet the demands of the cotton producer as well as the textile industry. In the recent years, improvement of cotton fiber quality has been extremely important because of changes in spinning technology. However, a negative association between lint yield and fiber quality are still presented after over dozens years of exhausting breeding for improved fiber properties due to the genetic complexity of fiber quality properties. Conventional breeding procedures exist difficulty in further improving fiber quality because of its high costs, long duration, and low selective efficiency. The development of DNA markers linked to the fiber quality QTL would allow cotton breeders to trace this very important trait in early plant-growing stage or early segregating generations. The use of these DNA markers is increasing the prospect for streamlining the cotton breeding programs for improving fiber quality while maintaining fiber yield.
However, QTL analysis for fiber properties is problematic:(1) QTLs obtained from interspecies population of Sealand cotton and Upland cotton showed less valuable in improving fiber quality of Upland cotton; (2) In previous reports, population constructed were all F2 population. Replicated experiment couldn't be carried out and common QTLs couldn't be got. Considering of these problems above, the objective of this research is to develop three F2 and F2:3 populations, by using 7TR-133,7TR-132,7TR-214, which derived from a cross between 7235 and TM-1 using a bulk-selfing technique, as female parent, backcrossed with TM-1 to identify fine located of common QTL associated with fiber quality and yield component traits across different background and different generations by PCR to screen SSR markers. Second, in order to provide theory for employing super quality and high yield, replicated experiment of two years and two locations in the present were used to identify stable major QTLs of fiber quality and yield component traits. The present result as following:
1. Correlation analysis for fiber quality and yield traits
Positive correlation was observed between fiber length and fiber strength, between fineness and elongation, between bolls per plant and lint percentage, between fiber length and boll size, and negative correlations between strength and fineness, strength and fiber elongation, between bolls per plant and boll size, boll size and lint percentage, between fiber length and bolls per plant and lint percentage, between fiber strength and bolls per plant, fiber strength and boll size, fiber strength and lint percentage, between fiber fineness and bolls per plant, fineness and boll size, between fiber elongation and bolls per plant, elongation and boll size.
2. Genetic analysis for fiber quality and yield components
Fiber quality (fiber length, fiber strength, fiber fineness and fiber elongation) and yield components genetic model was controlled by more than one major gene. Additive effect was stably exhibited in F2 and F2:3 generations and different locations (Xinjiang and Jiangpu). In the present research, the herelicity for fiber quality and yield component was different in different generations and locations. It was the reason that the genes for these traits were influenced by themselves and surroundings.
3. Construction of genetic linkage map
Of the 6123 SSR markers employed in this study, polymorphic SSR markers were detected in three populations (between 7TR-133 and TM-1,7TR-132 and TM-1,7TR-214 and TM-1). The three genetic maps for (7TR-133×TM-1) F2, (7TR-132×TM-1) F2, and (7TR-214×TM-1) F2 were generated. The SSR genetic map was constructed using 907 individuals in (7TR-133×TM-1)F2 and included 22 loci covering 13.7 cM, which represented approximately 12.3% of the total 111.7 cM recombinational length of cotton Chro.24. The map constructed from 670 individuals in (7TR-132×TM-1) F2 included 11 loci covering 19.1 cM, approximately 17.1% of the recombinational length of cotton Chro. 24, and the map constructed using 940 individuals in (214-RIL×TM-1) F2 included 18 loci covering 10.1 cM, approximately 9.4% of the recombinational length of cotton Chro.24. Sixteen,7 and 10 distorted SSR loci were detected in (7TR-133×TM-1) F2, (7TR-132×TM-1) F2 and (7TR-214×TM-1) F2. The percent skewed segregation ratios were 72.7%, 63.6%, and 55.6%, respectively, a great deal of decrease from 100% in (7235×TM-1)RIL.
4. QTL tagging for fiber quality
17 QTLs of fiber quality were identified in Pop A (7TR-133×TM-1), Pop B(7TR-132 ×TM-1) and Pop C (7TR-214×TM-1) three populations. Of these QTLs, there were 5 QTLs for fiber length, which exhibited a total phenotypic variance (PV) of 20.1%-32.7%,5 QTLs for fiber strength, which exhibited a total phenotypic variance (PV) of 28.8%-59.6%, 4 QTLs for fiber fineness, which exhibited a total phenotypic variance (PV) of 17.9%-41.5%, and 3 QTLs for fiber elongation, which exhibited a total phenotypic variance (PV) of 18.0%-26.2%. The QTLs for fiber length, fiber strength and fiber fineness were conferred by female parents 7TR-133,7TR-132 and 7TR-214 (increased fiber length and strength, decrease fiber fineness), and the QTL for elongation was conferred by male parent TM-1 (increased fiber elongation).
5. QTL tagging for yield traits
6 QTLs of yield trait were identified in (7TR-133×TM-1) Pop A, (7TR-132×TM-1) Pop B and (7TR-214×TM-1) Pop C populations. Of these QTLs, there were 1 QTLs for bolls per plant, which exhibited a phenotypic variance (PV) of 5.6%-9.4%,3 QTLs for boll size, which exhibited a total phenotypic variance (PV) of 15.0%-35.5%, and 2 QTLs for lint percentage, which exhibited a total phenotypic variance (PV) of 10.9%-19.3%. The QTLs for bolls per plant and boll size were conferred by male parent TM-1 (increased bolls per plant and boll size), and the QTL for lint percentage was conferred by female parent 7TR-133,7TR-132 and 7TR-214(increased lint percentage).
In the present,5 clustered QTL for fiber strength were detected in the three backcross populations among the confidence interval of q-FS-D08 identified by Shen et al. The q-BN-D08 was identified in the three backcross populations and (7235×TM-1) RIL population. It showed that the QTL for bolls per plant was stable and common. There was consistent with the result of genetic analysis and QTL mapping. Fiber quality and yield components were controlled by more than one main gene, and additive effect was mainly. It was difficult to breed and improve fiber quality and yield at same time because there was negative correlation between fiber quality and yield components.
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