利用选择导入系分析大豆芽期和苗期耐旱性的遗传重叠

以黑龙江主栽品种红丰11为母本, 与美国品种Clark杂交, 再以红丰11为轮回亲本, 对回交后代的芽期和苗期的耐旱性进行筛选。结果获得芽期耐旱导入系44个,采用单项方差分析检测到10个控制芽期耐旱性的QTL;获得苗期耐旱导入系46个,检测到影响苗期叶片相对含水量、叶片持水能力、胁迫期间株高变化量的21个QTL。大多数位点的遗传是相互独立的,只有分布于A1、K、I和H连锁群上的Satt449、Satt499、Satt440和Sat_180位点是在芽期、苗期干旱条件下共同检测到的,表明芽期和苗期的耐旱性存在部分的遗传重叠。以上结果为深入研究大豆耐旱性以及进行分子设计育种以累加芽期苗期重要耐旱QTL奠定了基础。     

大豆耐旱选择群体叶片持水能力QTL定位

大豆耐旱性是重要的农艺性状,直接影响大豆产量,近年来有关报道不断增多。此研究以‘红丰11’为轮回亲本、Clark为供体亲本构建回交群体进行耐旱性鉴定及叶片持水能力QTL定位。利用单向方差分析法检测到8个QTL位点分布于A1、B1、C2、E、L和N 6条连锁群,其中Satt316、Satt457和Satt694位点贡献率较高,可能是控制大豆耐旱性的重要位点。     

大豆荚粒相关性状的QTL分析

利用Harosoy和Clark导入到红丰11为背景的初级回交导入系定位了大豆荚粒相关性状的QTL。在两套导入系群体中,对13个荚粒性状共检测到37个相关的QTL位点,分布在18个连锁群上。根据不同群体QTL检测情况,可将其分为3类：第1类为在两套群体同时检测到的QTL,共有23个,分布在13个连锁群上;第2类为只在Clark为供体亲本的群体中检测到的QTL,共有7个,分布在4个连锁群上;第3类为只在Harosoy为供体亲本的群体中被检测到的QTL,共有7个,分布在7个连锁群上。两套群体均检测到的23个QTL,并且有7个QTL与前人研究结果较一致,这些QTL位点为稳定主效的QTL,对荚粒性状贡献较大。本研究所构建的两套大豆回交导入系群体都是以红丰11作为轮回亲本,由于遗传背景较为一致,减小了其对QTL定位的干扰,排除了由于基因累赘所造成的偏差。因此QTL一致性较高,为标记辅助选择培育高产品种奠定了基础。     

利用选择导入系QTL聚合设计方法改良水稻产量相关性状

培育和种植高产水稻品种是解决粮食短缺危机最有效的方法之一。利用轮回亲本明恢86和供体亲本ZDZ057、辐恢838和特青构建了3个BC2F4高产选择导入系群体,从中选择5个稳定的高产导入系培育了4个聚合群体WD135/WD190、WD190/WD250、WD208/WD258、WD135/WD258。通过对4个F4聚合群体进行大田表型鉴定,考察产量及其相关性状。选取55个SSR多态性标记对聚合群体进行基因型鉴定,并利用性状-标记间的单项方差分析进行产量及相关性状的QTL检测和根据遗传搭车理论对增产的聚合系基因型的分析结果进行卡方检测。方差分析结果表明,穗长和单株产量在所有4个聚合群体中都存在显著或者极显著基因型差异,抽穗期没有差异,其余性状在不同群体中表现不尽一致。在4个聚合群体中,一共有57个聚合系产量高于轮回亲本,增产幅度从0.36%～72.7%,其中有40个聚合系高于其各自的聚合亲本。与轮回亲本和导入系亲本相比,高产聚合系的单株有效穗数、每穗实粒数和每穗颖花数有了一定程度的提高。高产聚合系增产的主要原因是由于单株有效穗数、每穗实粒数和每穗颖花数得到了改良。利用卡方检验和单项方差分析分别检测到22和20个与产量及相关性状有关的QTLs,其中10个QTL与前人定位的结果一致。聚合亲本携带的QTL在聚合群体的效应与导入系群体估算的不完全一致。说明利用选择回交导入系进行复杂性状聚合改良虽然可以部分消除QTL与遗传背景的互作,但是QTL之间的上位性互作可能仍然起着一定的作用。本研究采取的产量聚合系定位方法可靠性较好,为复杂性状的聚合系定位提供了一个新途径。     

利用双向导入群体检测遗传背景对耐盐QTL定位的影响

以优质粳稻品种Lemont与高产籼稻品种特青为亲本培育的高代双向回交导入系为材料,在温室140 mmol L^-1 NaCl胁迫条件下定位影响苗期叶片盐害级别(SST)、幼苗存活天数(SDS)、地上部K⁺浓度(SKC)和地上部Na⁺浓度(SNC)及人工气候室条件下影响地上部K⁺、Na⁺浓度的QTL。双向导入系的大部分遗传背景与各自的受体亲本相同,其中Lemont背景导入系中轮回亲本Lemont的基因组平均占83.8%,特青背景导入系中轮回亲本特青基因组平均占88.9%。各耐盐相关性状在两个背景群体中均出现超亲分离,多数性状的频率分布呈相互重叠状态,表明双亲作为供体相互导入各耐盐性状基因的效应大致相当。两个背景导入系群体中分别检测到影响上述耐盐相关性状的QTL各18个,同一性状在两个背景导入系中未能检测到任何相同表达的QTL,表明耐盐QTL表达具有很强的遗传背景效应,同时也说明这些耐盐QTL的效应可能较小。温室和人工气候室两种环境下仅在特青背景导入系中检测到1个影响SKC的相同QTL,表明耐盐QTL与环境的互作非常明显。虽然双亲均表现中等感盐,但QTL定位结果表明双亲中都存在一些提高耐盐相关性状的有利等位基因。研究认为,利用分子标记技术挖掘“隐蔽”于育成品种中的耐盐基因,进一步利用分子标记辅助选择技术对这些非等位耐盐基因进行聚合,完全有可能提高育成品种的耐盐水平。     

利用双向导入系群体检测遗传背景对耐盐QTL定位的影响

以优质粳稻品种Lemont与高产籼稻品种特青为亲本培育的高代双向同交导入系为材料,在温室140 mmolL-1 NaCl胁迫条件下定位影响苗期叶片盐害级别(SST)、幼苗存活天数(SDS)、地上部K+浓度(SKC)和地上部Na+浓度(SNC)及人工气候室条件下影响地上部K+、Na+浓度的QTL.双向导入系的大部分遗传背景与各自的受体亲本相同,其中Lemont背景导入系中轮回亲本Lemont的基因组平均占83.8%,特青背景导入系中轮回亲本特青基因组平均占88.9%.各耐盐相关性状在两个背景群体中均出现超亲分离,多数性状的频率分布呈相互重叠状态,表明双亲作为供体相互导入各耐盐性状基因的效应大致相当.两个背景导入系群体中分别检测到影响上述耐盐相火性状的QTL各18个,同一性状在两个背景导入系中未能检测到任何相同表达的QTL,表明耐盐QTL表达具有很强的遗传背景效应,同时也说明这些耐盐QTL的效应可能较小.温室和人工气候室两种环境下仅在特青背景导入系中检测到1个影响SKC的相同QTL,表明耐盐QTL与环境的互作非常明显.虽然双亲均表现中等感盐,但QTL定位结果表明双亲中都存在一些提高耐盐相关性状的有利等佗基因.研究认为,利用分子标记技术挖掘"隐蔽"于育成品种中的耐盐基因,进一步利用分子标记辅助选择技术对这些非等位耐盐基因进行聚合,完全有可能提高育成品种的耐盐水平.     

应用导入系群体进行水稻产量相关性状的遗传剖析

以优质高产水稻品种丰矮占为轮回亲本, 以Khazar和IR64作供体亲本, 经连续回交分别构建了2套导入系(introgression lines)群体。对导入系后代分别在广州早造和晚造两种环境下进行重复产量鉴定。对两环境下产量及其组分性状的相关分析表明, 在广州早造和晚造环境下水稻产量构成因素存在很大差异。在早造, 每穗实粒数对产量供献最大, 而在晚造, 单株有效穗数对产量供献最大。应用SSR分子标记对这些导入系的供体片段进行全基因组扫描并应用单向方差分析(one-way ANOVA)剖析了导入系基因型与其产量及其组分的关系, 共检测到27个染色体区段与产量及组分性状相关, 包括10个产量QTL、9个单株穗数QTL、9个每穗实粒数QTL和14个千粒重QTL。大多数QTL只在一个环境条件下表达。在第3、7和9染色体上有3个QTL区域与产量及其两个组分有较大的效应, 值得关注。最终, 本研究在同步进行复杂农艺性状的改良和遗传剖析的研究上做出了有益的尝试。     

利用耐低磷选择回交导入系群体定位水稻产量性状QTL

水稻磷素利用率低是影响水稻产量的重要因素之一。为了发掘水稻耐低磷有利基因、培育磷高效品种,选用生产上大面积推广应用的恢复系‘蜀恢527’、‘明恢86’作为轮回亲本,以‘爷驼崽’为供体亲本,构建了2个BC2F4耐低磷选择回交导入系群体。分别在正常施肥量条件下和低磷条件下对2个群体进行产量性状鉴定和分析,同时对2个群体进行了分子标记检测,利用性状-标记间的单向方差分析,对耐低磷选择回交导入系群体的产量性状进行QTL定位。分析结果表明：在不同环境、不同遗传背景下单株有效穗数、每穗实粒数与单株产量之间呈极显著正相关;产量构成因素中,单株有效穗数受低磷胁迫影响较大,是造成低磷条件下减产的主要原因。2个群体在正常条件和低磷条件下共检测到控制单株有效穗数QTL 11个,控制每穗实粒数QTL 10个,控制结实率QTL 10个,控制千粒重QTL 9个,控制单株产量QTL 13个;检测到一因多效的位点12个。研究结果对低磷品种的选育、相关有利基因的发掘利用和分子标记辅助选择有重要参考作用,选择导入系也为耐低磷育种提供了材料。     

作物染色体导入系的构建及其应用

染色体导入系,也称染色体片段代换系、回交重组自交系或近等基因系,是借助分子辅助选择方法,通过回交和自交,从供体中导入一个或几个小的染色体片段进入轮回亲本.相对于传统的遗传群体,导入系群体大大降低了供体材料的遗传背景的干扰,提高了QTL分析的灵敏度和准确性,是QTL鉴定、精细定位、互作分析、图位克隆、性状改良及杂种优势利用和基因表达分析的理想的实验材料.本文就染色体导入系的研究情况进行了详细的综述.     

籼稻开花期耐热性鉴定与QTL定位分析

高温热害是水稻生产的重要制约因素之一。本研究利用籼稻恢复系蜀恢527为轮回亲本,以来自不同来源的6个籼稻品种为供体亲本构建了131个BC2F3:4选择导入系群体,在正常大田和温室大棚高温胁迫条件下进行连续两年(2011年和2012年)的耐热性鉴定,并结合基因型分析进行产量相关性状和耐热性QTL定位。耐热表型分析结果表明,尽管轮回亲本和供体本身不具备很强的耐热性,但绝大多数导入系后代出现了耐热性的超亲分离。本研究通过分子标记基因型和表型分析的单向方差分析进行产量相关性状(每穗总粒数,结实率,千粒重,单株产量)和耐热性(热胁迫指数)QTL发掘,共定位的到39个产量相关性状QTL,贡献率为7.3%~39.7%和12个耐热性QTL,贡献率为14.7%~30.2%。12个耐热性QTL中,有9个也在产量相关性状中检测到。40例QTL有利等位基因来自供体亲本,61.5%的QTL能在不同群体或环境中被重复检测到。产量性状和耐热性QTL在染色体上大多成簇分布,每个簇往往同时影响几个性状(多效性)。其中,第2染色体上RM341(Bin2.8)对每穗总粒数、千粒重和单株产量影响较大;第7染色体RM051(Bin7.1)则是主要控制结实率、单株产量和耐热指数等性状。第10染色体RM258(Bin10.5)则是主要控制每穗总粒数和耐热指数等性状。研究结果将为水稻耐热性改良及其分子标记辅助育种提供有益信息。     

大豆耐旱选择群体QTL定位

以红丰11为轮回亲本、Clark为供体亲本构建回交群体进行耐旱性鉴定,对获得选择群体进行全基因组SSR标记扫描,计算供体基因型导入频率,利用卡方测验检测偏分离SSR位点,并结合GGT软件对各连锁群分析, 对5个耐旱相关性状进行QTL定位。以卡方测验检测到23个SSR偏分离位点(超导入),分布于10条连锁群。方差分析表明,8个叶片持水能力QTL分布于A₁、B₁、C₂、E、L和N连锁群;9个根长QTL分布于C₂、F、G和I连锁群;11个根干重QTL分布于A₂、B₁、B₂、E、F、K、L、M和O连锁群;12个产量QTL分布于B₁、D₁a、E、F、G、I、L、M和O连锁群;7个生物量QTL分布于E、F、G、K、L和N连锁群。在E连锁群的Sat_136位点,对于叶片持水能力、根干重、产量和生物量具有一致性;在F连锁群的GMRUBP位点,对于根干重和生物量具有一致性,Satt586位点,对于根长、根干重和产量具有一致性;在K连锁群的Satt167位点,对于根干重和生物量具有一致性,SOYPRP1位点,对于根长和生物量具有一致性;在L连锁群的Satt398位点,对于根长和产量具有一致性,Satt694位点对于叶片持水能力和生物量具有一致性;在M连锁群的GMSL514位点,对于根干重和产量具有一致性;以上位点均与卡方测验检测到的“超导入”位点具有一致性。经过供体等位基因卡方测验和耐旱QTL定位,共检测到33个QTL,其中有17个同时被检测到。这些位点可能是控制大豆耐旱性的重要位点。     

Quantitative trait loci for agronomic traits in soybean

There continues to be improvement in seed yields of soybean by conventional breeding, but molecular techniques may provide faster genetic gains. The objective of this study was to identify quantitative trait loci (QTL) associated with the agronomic traits seed yield, lodging, plant height, seed filling period and plant maturity in soybean. To achieve this objective, 101 F₆‐derived recombinant inbred lines (RIL) from a population developed from a cross of N87‐984‐16 × TN93‐99 were used. Experiments were conducted in six environments during 2002–2003. Heritability estimates on an entry mean basis from data combined across environments ranged from 0.12 to 0.65 for seed yield and seed filling period, respectively. Composite interval mapping detected one QTL for yield (near Satt076), two for lodging (near Satt225 and Satt593) and four for maturity (near Satt263, Satt292, Satt293 and Satt591) in this population. Additional environmentally sensitive QTL for these traits, and for seed filling period and plant height are also reported. The QTL associated with agronomic traits that we report and the recently released germplasm (PI 636460) from this population may be useful in soybean breeding programmes.     

A quantitative trait locus influencing tolerance to Phytophthora root rot in the soybean cultivar ‘Conrad’

‘Conrad’, a soybean cultivar tolerant to Phytophthora root rot (PRR), and ‘OX760-6-1’, a breeding line with low tolerance to PRR, were crossed. F₂ derived recombinant inbred lines were advanced to F₆ to generate a population through single-seed descent. This population was used to identify quantitative trait loci (QTLs) influencing PRR tolerance in ‘Conrad’. A total of 99 simple sequence repeat (SSR), or microsatellite, markers that were polymorphic and clearly segregated in the F₆ mapping population were used for QTL detection. Based on the data of PRR in the field at two planting locations, Woodslee and Weaver, for the years 2000 and 2001, one putative QTL, designated as Qsatt414-596, was detected using MapMaker/QTL. Qsatt414-596 was flanked by two SSR markers from the linkage group MLG J, Satt414 and Satt596. Satt414 and Satt596 were also detected to be significantly (P < 0.005) associated with PRR using the SAS GLM procedure and were estimated to explain 13.7% and 21.5% of the total phenotypic variance, respectively.     

大豆主茎节数数量性状座定位及遗传效应分析

为了定位控制主茎节数的QTL并明确其遗传效应,利用100对SSR引物,并采用Mapmaker Exp 3.0和复合区间法,研究构建了一张包括3个连锁群的连锁图谱。以‘黑农37’（栽培大豆）×ZYD581（野生大豆）组合的亲本、F₂、F₃为试材,分别在chr1连锁群上定位了一个影响大豆主茎节数的QTL,2007年QTL位于Satt238—Satt242这个区间内,与Satt238的遗传距离是0.01 cM,与Satt242的遗传距离是24.69 cM,其遗传贡献率为17.22%,加性效应为-3.2608;2008年QTL位于Satt238—Satt240之间,与Satt238的遗传距离为0.59 cM,与Satt240的遗传距离为6.01 cM,其遗传贡献率为6.68%,加性效应为-1.4965。2年大豆主茎节数QTL分析表明,在chr1连锁群上Satt238附近确定了1个控制大豆主茎节数QTL位点。     

Molecular loci associated with seed isoflavone content may underlie resistance to soybean pod borer (Leguminivora glycinivorella)

Soybean pod borer (SPB) (Leguminivora glycinivorella (Mats.) Obraztsov) causes severe loss of soybean (Glycine max L. Merr.) seed yield and quality in some regions of the world, especially in north‐eastern China, Japan and Russia. Isoflavones in soybean seed play a crucial role in plant resistance to diseases and pests. The aim of this study was to find whether SPB resistance QTL are associated with soybean seed isoflavone content. A cross was made between ‘Zhongdou 27’ (higher isoflavone content) and ‘Jiunong 20’ (lower isoflavone content). One hundred and twelve F_5:10 recombinant inbred lines were derived through single‐seed descent. A plastic‐net cabinet was used to cover the plants in early August, and thirty SPB moths per square metre were put in to infest the soybean green pods. The results indicated that the percentage of seeds damaged by SPB was positively correlated with glycitein content (GC), whereas it was negatively correlated with genistein (GT), daidzein (DZ) and total isoflavone content (TI). Four QTL underlying SPB damage to seeds were identified and the phenotypic variation for SPB resistance explained by the four QTL ranged from 2% to 14% on chromosomes Gm7, 10, 13 and 17. Moreover, eleven QTL underlying isoflavone content were identified, and ten of them were encompassed within the same four marker intervals as the SPB QTL (BARC‐Satt208‐Sat292, Satt144‐Sat074, Satt540‐Sat244 and Satt345‐Satt592). These QTL could be useful in marker‐assisted selection for breeding soybean cultivars with both SPB resistance and high seed isoflavone content.     

Modifier QTL for fatty acid composition in soybean oil

Soybean [Glycine max (L.) Merr.] is the principal oilseed crop in the world. Soybean oil has various industrial and food applications. The quality of soybean oil is determined by its fatty acid composition. Palmitic, stearic, oleic, linoleic and linolenic are the predominant fatty acids in soybean oil. The objective of this study was to determine the associations of simple sequence repeat (SSR) molecular markers with minor differences in fatty acids in soybean oil thereby detecting modifier quantitative trait loci (QTL) which could further improve soybean oil quality. To achieve this objective, 101 F₆-derived recombinant inbred lines (RIL) from a population whose parents did not contain major mutant fatty acid alleles were developed from a cross of N87-984-16 × TN93-99. Fatty acids were determined by gas chromatography. Heritability estimates on an entry mean basis for fatty acids ranged from 65.8 to 77.3% for palmitic and linoleic acids, respectively. Molecular marker Satt537 located on molecular linkage group (MLG) D1b was associated with palmitic acid and Satt168 and Satt249 located on MLG B2 and J, respectively were associated with stearic acid. Molecular markers Satt185 or Satt268 (which are within 0.6 cM of each other) located on MLG E were consistently associated with oleic and linoleic acid, and Satt263 and Satt235 located on MLG E and G, respectively were associated with linolenic acid. The lack of markers associated with multiple fatty acids suggests the possibility of independently changing fatty acid levels to achieve a desirable composition, except for regions common to all saturated fatty acids. Phenotypic variation explained by the fatty acids modifier QTL ranged from 10 to 22.5%. These modifier QTL may be useful in making minor improvements to further enhance the quality of soybean oil.     

Development of a chromosome segment substitution line population with wild soybean (Glycine soja Sieb. et Zucc.) as donor parent

Chromosome segment substitution line (CSSL) population is potential in precisely detecting and pyramiding genes/QTL/segments due to the genetic background noise removed. To exploit and utilize the favorable wild alleles, a CSSL population with 151 lines (SojaCSSLP1) was generated using a wild soybean (Glycine soja Sieb. et Zucc.) N24852 as donor parent and the elite cultivar NN1138-2 as its genetic background. An improved CSSL construction strategy was used, i.e. continuous backcross after initial crossing followed with alternation of backcross and selfing combined with marker-assisted selection based on pedigree DNA pools and phenotypic differences among pedigrees. The SojaCSSLP1 with an average recovery ratio of 95.7?% of the NN1138-2 genome could cover the entire genome of wild soybean. Four wild alleles/segments for each of the two wild characteristics, longer plant height (PH) and more number of nodes on main stem (NN), in a total of six segments, were detected with additive effects all positive. Among them, Satt243 on Chr.10 and Sat_286 on Chr.19 associated with both PH and NN while Satt338 and SOYGPATR on Chr.4 and Satt314 neighboring with Satt192 on Chr.12 had the former and latter on each chromosome associated with PH and NN, respectively. That could explain the high positive correlation between the two traits (r?=?0.88). Compared with those in the literature, three QTL/segments for PH and one for NN were detected also among cultivated soybeans, indicating allele differentiation happened not only between wild and cultivated but also among cultivated soybeans. Therefore these QTL/segments might be the key ones to explain the domestication and evolution of soybean. In addition, SojaCSSLP1 should be also potential in studies for multiple wild traits due to its broad variation.     

Quantitative trait loci for agronomic and seed quality traits in an F2 and F4:6 soybean population

Molecular breeding is becoming more practical as better technology emerges. The use of molecular markers in plant breeding for indirect selection of important traits can favorably impact breeding efficiency. The purpose of this research is to identify quantitative trait loci (QTL) on molecular linkage groups (MLG) which are associated with seed protein concentration, seed oil concentration, seed size, plant height, lodging, and maturity, in a population from a cross between the soybean cultivars ‘Essex’ and ‘Williams.’ DNA was extracted from F₂ generation soybean leaves and amplified via polymerase chain reaction (PCR) using simple sequence repeat (SSR) markers. Markers that were polymorphic between the parents were analyzed against phenotypic trait data from the F₂ and F_4:6 generation. For the F₂ population, significant additive QTL were Satt540 (MLG M, maturity, r² = 0.11; height, r² = 0.04, seed size, r²= 0.06], Satt373 (MLG L, seed size, r² = 0.04; height, r² = 0.14), Satt50 (MLG A1, maturity r² = 0.07), Satt14 (MLG D2, oil, r² = 0.05), and Satt251 (protein r² = 0.03, oil, r² =0.04). Significant dominant QTL for the F₂ population were Satt540 (MLG M,height, r² = 0.04; seed size, r² = 0.06) and Satt14 (MLG D2, oil, r² = 0.05). In the F_4:6 generation significant additive QTL were Satt239 (MLGI, height, r² = 0.02 at Knoxville, TN and r² = 0.03 at Springfield, TN), Satt14 (MLG D2, seed size, r² = 0.14 at Knoxville, TN), Satt373 (MLG L, protein, r² = 0.04 at Knoxville, TN) and Satt251 (MLG B1, lodging r² = 0.04 at Springfield, TN). Averaged over both environments in the F_4:6 generation, significant additive QTL were identified as Satt251 (MLG B1, protein, r² = 0.03), and Satt239 (MLG I, height, r² = 0.03). The results found in this study indicate that selections based solely on these QTL would produce limited gains (based on low r² values). Few QTL were detected to be stable across environments. Further research to identify stable QTL over environments is needed to make marker-assisted approaches more widely adopted by soybean breeders. This revised version was published online in July 2006 with corrections to the Cover Date.