裸燕麦子粒性状的QTL研究

以六倍体裸燕麦578(大粒品种)和三分三(小粒品种)为亲本进行杂交,构建包含202个家系的F2遗传作图群体。由172个SSR标记构建出包含21个连锁群的遗传连锁图谱。采用复合区间作图对子粒性状进行QTL定位,共检测到17个控制子粒长度、宽度、千粒重的QTL位点。其中,6个与子粒长度相关的QTL位点表型的贡献率为0.70%~12.83%,5个与子粒宽度相关的QTL位点表型的贡献率为0.77%~12.92%,6个与子粒千粒重相关的QTL位点表型的贡献率为0.58%~10.64%。在这些QTLs中有4个的贡献率达到了10%以上,分别是与子粒长有关的qGL-2(12.83%)、与子粒宽有关的qGW-5(12.92%)以及与千粒重有关的qTGW-3(10.64%)和qTGW-4(10.05%),被认为是主效基因所在位点。而且qGL-2和qTGW-4位于连锁群的相同位置上。还发现第3号连锁群上AM1089~AM1512区段分别与子粒长度、宽度和千粒重相关,同时3号连锁群AM86-2~AM1044区间分别与子粒长度和千粒重相关,而位于第21号连锁群AM3217~AM965区段分别与子粒宽度和千粒重相关。这一研究为燕麦子粒性状的深入研究和相关标记开发以及分子辅助选择研究奠定了基础。     

水稻子粒硒含量的遗传及QTL检测

富硒功能水稻具有富硒、优质、保健、防病、安全等特点,已成为当前研究的热点。子粒硒含量的QTL定位对研究富硒功能水稻的遗传育种具有重要的意义。以籼稻亲本奉新红米和明恢100杂交的145个株系的F2群体构建遗传连锁图谱,图谱拟合92个SSR标记位点,覆盖水稻基因组2187.5 cM,标记间平均遗传距离为23.7 cM,占水稻全基因组的49.2%。采用复合区间作图法,对水稻子粒硒含量进行QTL分析,在第5染色体上共检测到2个新的水稻子粒硒的QTL,对表型变异的贡献率分别为6.39%、8.01%。     

基于染色体片段置换系的野生稻粒宽QTL-qGW8.1的精细定位

利用以栽培稻9311为受体、普通野生稻为供体的染色体单片段置换系CSSL182,检测到一个与粒宽相关的QTL。CSSL182与受体亲本9311粒型性状差异显著,且只在8号染色体有一个野生稻导入片段。构建CSSL182/9311的F_2次级分离群体,将粒宽QTL初定位在8号染色体的标记RM447和RM264之间,贡献率达22.49%,将该QTL命名为qGW8.1。随后进一步设计区间内多态性分子标记引物,检测F_2群体的2000株分离个体以及F_(2∶3)群体交换单株,结合后代表型验证,最终将qGW8.1精细定位到8号染色体10 kb区间内。该区间内含有3个候选基因,基因测序发现这3个基因在双亲之间均含有丰富的变异。对双亲子粒颖壳细胞电镜扫描观察发现,CSSL182的颖壳细胞宽度比9311减少16.7%。这一结果表明qGW8.1中来自野生稻的等位基因通过改变颖壳细胞形状影响粒型。     

水稻籽粒锌含量的QTL 定位

锌元素的营养失衡已成为影响人类健康的最重要因素之一, 籽粒锌含量的QTL(quantitative trait loci)定位对研究富锌水稻的遗传育种具有重要的意义。以水稻(Oryza sativa L.)亲本奉新红米和明恢100杂交的145个株系的F2群体为实验材料, 利用92个SSR(simple sequence repeat)标记对水稻籽粒锌含量进行了QTL定位, 共检测到3个QTLs , 分别定位于第3、6和11染色体上, 对表型变异的贡献率分别为4.97%、12.75%和7.74%。其中位于第3染色体上的分子标记RM186和RM168之间的QZN3对表型变异的贡献率最大, 其增效等位基因来自亲本明恢100, 表现为部分显性。3个QTLs 的联合贡献率为25.46%, 具有基因累加效应。该研究结果有利于深入理解水稻锌含量的遗传基础, 为锌含量的QTL精细定位、基因克隆和分子标记辅助选择提供依据。     

南瓜遗传连锁图谱的构建及粒宽性状的QTL定位

以印度南瓜纯系大粒材料‘0515-1’和小粒材料‘0460-1-1’为亲本,获得193个南瓜F2单株群体,应用AFLP和SSR分子标记技术进行多态性筛选,构建了含84个标记位点的遗传连锁图谱。结果表明,整个图谱包含12个连锁群,全长683.50cM,标记平均间距为8.13cM。采用复合区间定位分析,共检测到控制南瓜籽粒宽度的4个数量性状位点(QTL),分别位于3个连锁群上,各QTL的贡献率在2.87%～29.68%之间。     

水稻叶片性状和根系活力的QTL定位

应用由247个株系组成的珍汕97B/密阳46重组自交系(RIL)群体及其分子标记连锁图谱,检测控制剑叶、倒二叶、倒三叶的5个形态性状和控制根系伤流量性状的数量性状座位(QTL)。在9个标记区间检测到控制叶片形态性状的24个QTL,LOD值为2．9～11．8,单个QTL的表型变异贡献率为4．0％～32．5％;分别检测到56对和4对控制叶片形态和根系活力的上位性互作,绝大多数互作发生在2个不表现加性效应的座位之间。与该群体产量性状QTL的研究结果相比较,发现控制叶片性状和根系活力的QTL与产量性状QTL往往处于相似的染色体区间。     

水、旱条件下水稻茎秆主要抗倒伏性状的QTL分析

以粳型旱稻IRAT109和粳型水稻越富杂交的116个DH株系的群体为材料,利用已构建的分子标记连锁图(包括94个RFLP标记和71个SSR标记),定位了水稻茎秆主要抗倒伏性状的QTL。在水田、旱田栽培条件下,考查了乳熟期DH系及其亲本的茎基粗、茎秆长及茎秆强度等性状。相关分析表明,茎基粗与茎秆长、茎基粗与茎秆强度及茎秆长与茎秆强度间均呈极显著正相关。利用QTLMAPPER进行水、旱田单环境定位分析及水、旱田联合定位分析定位了控制这些性状的QTL。水、旱田单环境定位分析结果表明：3个性状共检测到9个加性QTL和5对上位性QTL;联合定位分析表明：茎基粗、茎秆长共检测到6个加性QTL和6对上位性QTL,其中6个加性QTL和1对上位性QTL在两种方法下都检测到。旱田条件下检测到2个加性及2对上位性QTL(bctla、ct9、c16a-c16c和cs5-cs12)对表型变异的贡献率(简称贡献率)大于30％。这些高贡献率QTL可能对旱田条件下旱稻抗倒伏分子育种有重要意义。     

利用染色体片段置换系定位水稻落粒性主效QTL

水稻落粒性是与其生产密切相关的重要性状之一。以7个染色体片段置换系为材料, 采用重叠群代换作图法对控制落粒性的2个主效QTL进行定位。结果表明, 104个SSR标记在亲本间具有多态性, 多态率为68.0%; 4个置换系的落粒性与亲本日本晴的落粒性相似, 表现难落粒。3个置换系与亲本93-11的落粒性相似, 表现易落粒; 7个染色体片段置换系在第1和第6染色体上检出7个置换片段, 其长度分别为23.6、16.5、 6.6、 9.9、 10.4、 20.2和7.1 cM; qSH-1-1被定位在第1染色体RM472－RM1387之间, 遗传距离约为6.6 cM。qSH-6-1为新发现的落粒性主效QTL, 被定位在第6染色体RM6782－RM3430之间,遗传距离约为4.2 cM。利用染色体片段置换系能准确地定位水稻落粒性QTL, qSH-1-1与qSH-6-1的鉴定和初步定位为其进一步的精细定位、图位克隆及分子标记辅助选择奠定了基础。     

利用染色体片段置换系定位水稻落粒性主效QTL

水稻落粒性是与其生产密切相关的重要性状之一。以7个染色体片段置换系为材料,采用重叠群代换作图法对控制落粒性的2个主效QTL进行定位。结果表明,104个SSR标记在亲本间具有多态性,多态率为68.0%;4个置换系的落粒性与亲本日本晴的落粒性相似,表现难落粒。3个置换系与亲本93-11的落粒性相似,表现易落粒;7个染色体片段置换系在第1和第6染色体上检出7个置换片段,其长度分别为23.6、16.5、6.6、9.9、10.4、20.2和7.1 cM;qSH-1-1被定位在第1染色体RM472-RM1387之间,遗传距离约为6.6 cM。qSH-6-1为新发现的落粒性主效QTL,被定位在第6染色体RM6782-RM3430之间,遗传距离约为4.2 cM。利用染色体片段置换系能准确地定位水稻落粒性QTL,qSH-1-1与qSH-6-1的鉴定和初步定位为其进一步的精细定位、图位克隆及分子标记辅助选择奠定了基础。     

籼粳稻杂交后代花时性状的QTL分析

研究典型籼稻品种‘七山占’和典型粳稻品种‘秋光’杂交衍生的重组自交系群体及其双亲的花时性状,并用该群体的分子连锁图谱进行QTL分析,共检测到6个与水稻花时性状相关的QTL,包括1个始花时QTL、3个盛花时QTL和2个终花时QTL,分别位于第1、2、7、8、10和12染色体,单个QTL的贡献率在7.08%～26.95%之间。有4个增效等位基因来源于粳型亲本‘秋光’,2个来源于籼型亲本‘七山占’。     

Mapping and characterisation of QTL × E interactions for traits determining grain and stover yield in pearl millet

A mapping population of 104 F(3) lines of pearl millet, derived from a cross between two inbred lines H 77/833-2 x PRLT 2/89-33, was evaluated, as testcrosses on a common tester, for traits determining grain and stover yield in seven different field trials, distributed over 3 years and two seasons. The total genetic variation was partitioned into effects due to season (S), genotype (G), genotype x season interaction (G x S), and genotype x environment-within-season interaction [G x E(S)]. QTLs were determined for traits for their G, G x S, and G x E(S) effects, to assess the magnitude and the nature (cross over/non-crossover) of environmental interaction effects on individual QTLs. QTLs for some traits were associated with G effects only, while others were associated with the effects of both G and G x S and/or G, G x S and G x E(S) effects. The major G x S QTLs detected were for flowering time (on LG 4 and LG 6), and mapped to the same intervals as G x S QTLs for several other traits (including stover yield, harvest index, biomass yield and panicle number m(-2)). All three QTLs detected for grain yield were unaffected by G x S interaction however. All three QTLs for stover yield (mapping on LG 2, LG 4 and LG 6) and one of the three QTLs for grain yield (mapping on LG 4) were also free of QTL x E(S) interactions. The grain yield QTLs that were affected by QTL x E(S) interactions (mapping on LG 2 and LG 6), appeared to be linked to parallel QTL x E(S) interactions of the QTLs for panicle number m(-2) on (LG 2) and of QTLs for both panicle number m(-2) and harvest index (LG 6). In general, QTL x E(S) interactions were more frequently observed for component traits of grain and stover yield, than for grain or stover yield per se.     

High-Density Genetic Linkage Map Construction and QTL Mapping of Grain Shape and Size in the Wheat Population Yanda1817 × Beinong6

High-density genetic linkage maps are necessary for precisely mapping quantitative trait loci (QTLs) controlling grain shape and size in wheat. By applying the Infinium iSelect 9K SNP assay, we have constructed a high-density genetic linkage map with 269 F ₈ recombinant inbred lines (RILs) developed between a Chinese cornerstone wheat breeding parental line Yanda1817 and a high-yielding line Beinong6. The map contains 2431 SNPs and 128 SSR & EST-SSR markers in a total coverage of 3213.2 cM with an average interval of 1.26 cM per marker. Eighty-eight QTLs for thousand-grain weight (TGW), grain length (GL), grain width (GW) and grain thickness (GT) were detected in nine ecological environments (Beijing, Shijiazhuang and Kaifeng) during five years between 2010–2014 by inclusive composite interval mapping (ICIM) (LOD≥2.5). Among which, 17 QTLs for TGW were mapped on chromosomes 1A, 1B, 2A, 2B, 3A, 3B, 3D, 4A, 4D, 5A, 5B and 6B with phenotypic variations ranging from 2.62% to 12.08%. Four stable QTLs for TGW could be detected in five and seven environments, respectively. Thirty-two QTLs for GL were mapped on chromosomes 1B, 1D, 2A, 2B, 2D, 3B, 3D, 4A, 4B, 4D, 5A, 5B, 6B, 7A and 7B, with phenotypic variations ranging from 2.62% to 44.39%. QGl.cau-2A.2 can be detected in all the environments with the largest phenotypic variations, indicating that it is a major and stable QTL. For GW, 12 QTLs were identified with phenotypic variations range from 3.69% to 12.30%. We found 27 QTLs for GT with phenotypic variations ranged from 2.55% to 36.42%. In particular, QTL QGt.cau-5A.1 with phenotypic variations of 6.82–23.59% was detected in all the nine environments. Moreover, pleiotropic effects were detected for several QTL loci responsible for grain shape and size that could serve as target regions for fine mapping and marker assisted selection in wheat breeding programs.     

Identification of QTLs for Yield and Associated Traits in F₂ Population of Rice

Identification of quantitative trait loci (QTLs) controlling yield and yield-related traits in rice was performed in the F₂ mapping population derived from parental rice genotypes DHMAS and K343. A total of 30 QTLs governing nine different traits were identified using the composite interval mapping (CIM) method. Four QTLs were mapped for number of tillers per plant on chromosomes 1 (2 QTLs), 2 and 3; three QTLs for panicle number per plant on chromosomes 1 (2 QTLs) and 3; four QTLs for plant height on chromosomes 2, 4, 5 and 6; one QTL for spikelet density on chromosome 5; four QTLs for spikelet fertility percentage (SFP) on chromosomes 2, 3 and 5 (2 QTLs); two QTLs for grain length on chromosomes 1 and 8; three QTLs for grain width on chromosomes1, 3 and 8; three QTLs for 1000-grain weight (TGW) on chromosomes 1, 4 and 8 and six QTLs for yield per plant (YPP) on chromosomes 2 (3 QTLs), 4, 6 and 8. Most of the QTLs were detected on chromosome 2, so further studies on chromosome 2 could help unlock some new chapters of QTL for this cross of rice variety. Identified QTLs elucidating high phenotypic variance can be used for marker-assisted selection (MAS) breeding. Further, the exploitation of information regarding molecular markers tightly linked to QTLs governing these traits will facilitate future crop improvement strategies in rice.     

Molecular mapping in tropical maize (Zea mays L.) using microsatellite markers. 2. Quantitative trait loci (QTL) for grain yield, plant height, ear height and grain moisture

A previous genetic map containing 117 microsatellite loci and 400 F(2) plants was used for quantitative trait loci (QTL) mapping in tropical maize. QTL were characterized in a population of 400 F(2:3) lines, derived from selfing the F(2) plants, and were evaluated with two replications in five environments. QTL determinations were made from the mean of these five environments. Grain yield (GY), plant height (PH), ear height (EH) and grain moisture (GM) were measured. Variance components for genotypes (G), environments (E) and GxE interaction were highly significant for all traits. Heritability was 0.69 for GY, 0.66 for PH, 0.67 for EH and 0.23 for GM. Using composite interval mapping (CIM), a total of 13 distinct QTLs were identified: four for GY, four for PH and five for EH. No QTL was detected for GM. The QTL explained 32.73 % of the phenotypic variance of GY, 24.76 % of PH and 20.91 % of EH. The 13 QTLs displayed mostly partial dominance or overdominance gene action and mapped to chromosomes 1, 2, 7, 8 and 9. Most QTL alleles conferring high values for the traits came from line L-14-4B. Mapping analysis identified genomic regions associated with two or more traits in a manner that was consistent with correlation among traits, supporting either pleiotropy or tight linkage among QTL. The low number of QTLs found, can be due to the great variation that exists among tropical environments.     

QTL analysis for grain quality traits in 2 BC2F2 populations derived from crosses between Oryza sativa cv Swarna and 2 accessions of O. nivara

The appearance and cooking quality of rice determine its acceptability and price to a large extent. Quantitative trait loci (QTLs) for 12 grain quality traits were mapped in 2 mapping populations derived from Oryza sativa cv Swarna × O. nivara. The BC(2)F(2) population of the cross Swarna × O. nivara IRGC81848 (population 1) was evaluated during 2005 and that from Swarna × O. nivara IRGC81832 (population 2) was evaluated during 2006. Linkage maps were constructed using 100 simple sequence repeat (SSR) markers in population 1 and 75 SSR markers in population 2. In all, 21 QTLs were identified in population 1 (43% from O. nivara) and 37 in population 2 (38% QTLs from O. nivara). The location of O. nivara-derived QTLs mp1.2 for milling percent, kw6.1 for kernel width, and klac12.1 for kernel length after cooking coincided in the 2 populations and appear to be useful for Marker Assisted Selection (MAS). Four QTLs for milling percent, 1 QTL each for amylose content, water uptake, elongation ratio, 2 QTLs for kernel width, and 3 QTLs for gel consistency, each explained more than 20% phenotypic variance. Three QTL clusters for grain quality traits were close to the genes/QTLs for shattering and seed dormancy. QTLs for 4 quality traits were associated with 5 of the 7 major yield QTLs reported in the same 2 mapping populations. Useful introgression lines have been developed for several agronomic traits. It emerges that 40% O. nivara alleles were trait enhancing in both populations, and QTLs for grain quality overlapped with yield meta-QTLs and QTLs for dormancy and seed shattering.     

Development of Chromosome Segment Substitution Lines Derived from Backcross between Two Sequenced Rice Cultivars, <Emphasis Type="Italic">Indica</Emphasis> Recipient 93-11 and <Emphasis Type="Italic">Japonica</Emphasis> Donor Nipponbare

Chromosome segment substitution lines (CSSLs) are powerful tools for detecting and precisely mapping quantitative trait loci (QTLs) and evaluating gene action as a single factor. In this study, 103 CSSLs were produced using two sequenced rice cultivars: 93-11, an elite restorer indica cultivar as recipient, and Nipponbare, a japonica cultivar, as donor. Each CSSL carried a single chromosome substituted segment. The total length of the substituted segments in the CSSLs was 2,590.6 cM, which was 1.7 times of the rice genome. To evaluate the potential application of these CSSLs for QTL detection, phenotypic variations of seed shattering, grain length and grain width in 10 CSSLs were observed. Two QTLs for seed shattering and three for grain length and grain width were identified and mapped on rice chromosomes. The results demonstrate that CSSLs are excellent genetic materials for dissecting complex traits into a set of monogenic loci. These CSSLs are of great potential value for QTL mapping and plant marker-assisted breeding (MAB).     

QTL mapping for some grain traits in bread wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.)

Grain traits are important agronomic attributes with the market value as well as milling yield of bread wheat. In the present study, quantitative trait loci (QTL) regulating grain traits in wheat were identified. Data for grain area size (GAS), grain width (GWid), factor form density (FFD), grain length-width ratio (GLWR), thousand grain weight (TGW), grain perimeter length (GPL) and grain length (GL) were recorded on a recombinant inbred line derived from the cross of NW1014?×?HUW468 at Meerut and Varanasi locations. A linkage map of 55 simple sequence repeat markers for 8 wheat chromosomes was used for QTL analysis by Composite interval mapping. Eighteen QTLs distributed on 8 chromosomes were identified for seven grain traits. Of these, five QTLs for GLWR were found on chromosomes 1A, 6A, 2B, and 7B, three QTLs for GPL were located on chromosomes 4A, 5A and 7B and three QTLs for GAS were mapped on 5D and 7D. Two QTLs were identified on chromosomes 4A and 5A for GL and two QTLs for GWid were identified on chromosomes 7D and 6A. Similarly, two QTLs for FFD were found on chromosomes 1A and 5D. A solitary QTL for TGW was identified on chromosome 2B. For several traits, QTLs were also co-localized on chromosomes 2B, 4A, 5A, 6A, 5D, 7B and 7D. The QTLs detected in the present study may be validated for specific crosses and then used for marker-assisted selection to improve grain quality in bread wheat.     

Quantitative trait loci mapping of dark-induced senescence in winter wheat (Triticum aestivum)

In order to explore the genetics of dark-induced senescence in winter wheat(Triticum aestivum L.),a quantitative trait loci(QTL)analysis was carried out in a doubled haploid population developed from a cross between the varieties Hanxuan 10(HX)and Lumai 14(LM).The senescence parameters chlorophyll content(Chl a+b,Chl a,and Chl b),original fluorescence(Fo),maximum fluorescence level(Fm),maximum photochemical efficiency(Fv/Fm),and ratio of variable fluorescence to original fluorescence(Fv/Fo)were evaluated in the second leaf of whole three-leaf seedlings subjected to 7 d of darkness.A total of 43 QTLs were identified that were associated with dark-induced senescence using composite interval mapping.These QTLs were mapped to 20 loci distributed on 11 chromosomes:1B,1D,2A,2B,3B,3D,5D,6A,6B,7A,and 7B.The phenotypic variation explained by each QTL ranged from 7.5% to 19.4%.Eleven loci coincided with two or more of the analyzed parameters.In addition,14 loci co-located or were linked with previously reported QTLs regulating flag leaf senescence,tolerance to high light stress,and grain protein content(Gpc),separately.     

Multi-Environmental Genetic Analysis of Grain Size Traits Based on Chromosome Segment Substitution Line in Rice (<i>Oryza sativa</i> L.)

Grain size traits are critical agronomic traits which directly determine grain yield, but the genetic bases of these traits are still not well understood. In this study, a total of 154 chromosome segment substitution lines (CSSLs) population derived from a cross between a japonica variety Koshihikari and an indica variety Nona Bokra was used to investigate grain length (GL), grain width (GW), length-width ratio (LWR), grain perimeter (GP), grain area (GA), and thousand grain weight (TGW) under four environments. QTL mapping analysis of six grain size traits was performed by QTL IciMapping 4.2 with an inclusive composite interval mapping (ICIM) model. A total of 64 QTLs were identified for these traits, which mapped to chromosomes 1, 2, 3, 4, 6, 7, 8, 10, 11, and 12 and accounted for 1.6%–27.1% of the total phenotypic variations. Among these QTLs, thirty-six loci were novel and seven QTLs were identified under four environments. One locus containing the known grain size gene, qGL3/GL3.1/OsPPKL1, also have been found. Moreover, five pairs of digenic epistatic interactions were identified except for GL and GP. These findings will facilitate fine mapping of the candidate gene and QTL pyramiding to genetically improve grain yield in rice.     

大豆油份含量QTL的定位

以大豆杂交组合皖82-178×通山薄皮黄豆甲衍生的重组自交系群体(RIL)为材料, 以该群体所构建的遗传连锁图谱为基础, 以2004和2005年油份含量为指标, 利用软件Cartgrapher(V. 2.0)采用复合区间作图法进行了QTL分析, 结果表明, 利用两年资料对油份含量QTL的定位结果基本一致。两年资料所检测到的QTL均位于wt-11连锁群的satt331附近, 分别可以解释13.95%和15.01%遗传变异。此外, 利用软件QTL Mapper 1.6, 采用复合区间作图法直接对两年的油份含量进行QTL联合分析, 结果表明, 控制油份的QTL也位于wt-11连锁群的satt331附近。