利用MR1523/苏御糯F_(2:3)群体定位水稻抗灰飞虱QTL

灰飞虱是我国水稻生产的主要害虫之一,不仅直接取食危害水稻,还是水稻主要病毒病的传播介体,严重制约水稻生产。籼稻品种MR1523对灰飞虱表现较强的排趋性。为发掘抗灰飞虱新基因,本研究利用MR1523与感虫粳稻品种苏御糯构建了一个包含200个家系的F2:3分离群体,进行灰飞虱抗性鉴定。并利用120对均匀分布在水稻12条染色体的多态性SSR标记,构建了全基因组连锁图谱,进行抗灰飞虱QTL定位。结果分别在水稻第2、第5和第6染色体上检测到Qsbph2、Qsbph5a、Qsbph5b和Qsbph6 4个抗灰飞虱QTLs,分别位于分子标记RM526–RM3763、RM17804–RM13、RM574–RM169和RM190–RM510之间,LOD值分别为2.14、3.13、3.23和2.35,贡献率分别为12.0%、14.7%、17.4%和14.1%,各QTL的抗性等位基因效应均来自抗虫亲本MR1523。该结果为后续抗灰飞虱基因的精细定位及通过分子标记辅助选择培育抗灰飞虱水稻新品种奠定了基础。     

利用Mudgo/武育粳3号F2群体分析水稻抗灰飞虱QTL

灰飞虱是我国水稻生产上的重要害虫。Mudgo是一个高抗灰飞虱的籼稻品种,对灰飞虱具有强的排驱性和抗生性抗性。利用Mudgo/武育粳3号F₂群体,构建了含有177个单株的F₂群体的遗传连锁图谱。该连锁图包含104个SSR标记和3个Indel标记,覆盖整个水稻基因组1 409.9 cM,每两个标记之间的平均距离为13.2 cM。采用改进的苗期集团筛选法对177个F_2:3家系进行了抗性鉴定,通过Windows QTL Cartographer 2.5进行复合区间作图分析,在第2、3、12染色体上分别检测到抗灰飞虱QTL Qsbph2b、Qsbph3d和Qsbph12a,分别位于标记RM5791~RM29、RM3199~RM5442和I12-17~RM333 1之间,单个LOD值分别为3.25、3.11和6.82,贡献率分别为17.3%、15.6%和35.8%,各QTL增强抗性的等位基因效应均来自Mudgo。其中Qsbph12a与标记RM3331和I12-17紧密连锁。结合表型鉴定的结果,Qsbph12a应为抗灰飞虱主效QTL,与该位点紧密连锁的标记可用于抗灰飞虱快速选择辅助育种。     

玉米抗穗粒腐病QTL定位

用已构建的包括88个AFLP标记和151个SSR标记的遗传图谱和230个F₂植株用于抗病QTL定位研究,在四川雅安、绵阳对F2株系进行抗病性鉴定,采用复合区间定位法进行抗病QTL检测。在雅安检测到位于第2、3、4、6和9染色体上的抗病QTL 6个,解释表型变异的8.3%~25.7%;在绵阳检测到位于第1、6、7和9染色体上的抗病QTL 4个,解释表型变异的11.3%~26.4%。在10个抗病QTL中,位于第6和第9染色体上的2个同时在两点被检测到,贡献率均超过15%,表明玉米穗粒腐病确实存在遗传抗病性。利用2个环境抗病指数的平均值进行抗性QTL检测,共检测到位于第1、6和7连锁群上的3个抗性QTL,单个QTL的贡献率在8.9%~17.2%之间。结果有助于了解玉米穗粒腐病的抗性机制,并为分子标记辅助选择提供理论支撑。     

QTLs conferring FOV 7 resistance detected by linkage and association mapping in Upland cotton

Fusarium wilt is a worldwide disease that affects cotton production. Molecular markers tightly linked to resistance genes can be used for marker-assisted and/or genomic selection. We performed both family-based linkage mapping and population-based association mapping (AM) to detect quantitative trait loci (QTLs) conferring resistance against Fusarium oxysporum f. sp. vasinfectum race 7 (FOV 7) in Upland cotton. To identify QTLs underlying FOV 7 resistance by linkage mapping, three Upland cotton cultivars/lines, Xuzhou 142, Yumian 21 and Shang 9901, were used to obtain the composite cross population, designated as Xuzhou 142/Yumian 21//Xuzhou 142/Shang 9901. A linkage map containing 185 simple sequence repeat loci and 40 linkage groups was constructed with an average distance of 7.5 cM between adjacent markers. Seven QTLs were detected by linkage mapping, explaining 2.9–6.6 % of the total phenotypic variance. We also performed marker–trait AM with the MLM model (Q + K) in a panel composed of 356 Upland cotton cultivars. In total, 27 loci were significantly associated with FOV 7 resistance at the α = 0.01 level (?log₁₀ P ≥ 2), which were distributed on 16 chromosomes and explained 1.48–12.99 % of phenotypic variation. Three of the 7 QTLs identified by linkage mapping could be detected in AM. We identified the favorable allele for each of the 27 associated loci and investigated the number of favorable alleles in each accession. The results should increase our understanding of the genetic basis of FOV resistance and facilitate future resistance breeding in Upland cotton.     

QTLs for black-point resistance in wheat and the identification of potential markers for use in breeding programmes

Quantitative trait loci (QTLs) for black‐point resistance have been mapped in two doubled haploid‐derived wheat populations, each thought to contain unrelated sources of resistance. In the ‘Sunco’בTasman’‐derived population, QTLs were located on chromosomes 1D, 2B, 3D, 4A, 5A and 7A with each QTL explaining between 4 and 15% of the observed phenotypic variance. QTLs were contributed by both parents. In the ‘Cascades’בAUS1408’‐derived population, QTLs from ‘Cascades’ were identified on chromosomes 2A, 2D and 7A with each QTL explaining between 12 and 18% of the phenotypic variance. Several markers were identified which are promising candidates for use in marker‐assisted selection programmes. If one, two or three of these markers would have been used to select for black‐point resistance in the ‘Sunco’בTasman’ population, then with one marker 34 of 39 resistant lines, with two markers 23 of 32 and with three markers 17 of 32 would have been selected. At the same time, 67 false positives obtained by selecting with one marker are reduced to 24 by selection with two markers and to 11 by selection with three markers. Similarly, if one, two or three markers are used to select for black‐point resistance in the ‘Cascades’בAUS1408’ populations, then with one marker 25 of 31 resistant lines, with two markers 26 of 31 and with three markers 10 of 31 are selected. At the same time, 14 false positives are obtained with one marker are reduced to six by selection with two markers and no false positives are selected using three markers.     

Tagging quantitative trait loci for dormancy, tuber shape, regularity of tuber shape, eye depth and flesh colour in diploid potato originated from six Solanum species

Potato breeding aims at breeding diversified cultivars not only suitable for different purposes, but also resistant to diseases, such as late blight caused by Phytophthora infestans , which is a major constraint in potato production. Resistance to P. infestans has been previously introduced into the diploid hybrid population 98-21 from Solanum verrucosum and Solanum microdontum . In the present study, we assessed the segregation of tuber dormancy, tuber shape, regularity of tuber shape, eye depth and flesh colour in this population. Quantitative Trait Loci (QTLs) affecting these important quality traits were tagged using the genetic map developed for this population to locate QTLs for late blight resistance. The most prominent QTL for dormancy was detected on chromosome II and explained 7.1% of the variance. The most important QTLs for tuber eye depth, flesh colour, shape and shape regularity were identified on chromosomes X ( R ² = 14.7%), IV ( R ² = 5.8%), II ( R ² = 8.0%) and III ( R ² = 10.4%) respectively. All traits were also affected by minor QTLs. The obtained results improve our understanding of the inheritance of traits relevant for variety development in potato.     

Quantitative Traits Locus Meta-analysis of Fiber Quality Traits in Cotton

Using bioinformatics methods and meta-analysis with BC₁ map as reference, 92 cotton fiber quality QTL collected from both BC₁ and BC₁F₂ populations constructed previously were used to construct a QTL integrated map for QTL analysis in this study. The five hundred ninety-nine loci were mapped into 26 chromosomes with an average distance between adjacent markers of 5.96 cM and covered 3,571.9 cM. Sixty-three QTL of fiber qualities related were integrated into the new reference map. The fifteen meta-QTL were mapped on 12 chromosomes by the meta-analysis method and also QTL clusters have been discovered on chromosome 9, 16 and 24. The major meta-QTL of Meta-QTL9-1 derived from five QTL on chromosome 9, could explain 17.16% of phenotypic variance. The meta-QTL16-1 derived from ten QTL on chromosome 16, could explain 12.28% of phenotypic variance. And three meta-QTL derived from nine QTLs on chromosome 24, could explain 16.12%,16.69% and 18.27% of phenotypic variance, respectively. On average, one meta-QTL derived from two QTLs on the other chromosomes. The results indicated that these meta-QTL could be used in improving fine QTL mapping and molecular-assisted selection of cotton fiber qualities in breeding.     

越冬栽培稻产量性状相关QTL定位

越冬栽培稻是一类能越过自然冷冬季节并在第2年春季萌芽、正常开花结实、收获稻谷的水稻品种。本文通过对越冬栽培稻产量性状QTL分析,明确产量相关性状的遗传规律,旨在进一步解析越冬栽培稻产量性状的遗传机制,为育种创新利用提供理论依据。以3份越冬栽培稻构建的3个半同胞F2群体为材料。各考察15个产量相关性状,利用Excel 2003、GraphPad Prism 5.0和QTL IciMapping 4.10软件分析数据、绘制遗传图谱、定位QTL和联合分析。结果表明,产量性状表型值在3群体中呈连续正态分布,表现为数量性状遗传。共检测到37个QTL和26对上位性QTL,贡献率分别介于2.32%～36.31%和1.04%～2.05%;检测到9个同时影响2个及以上产量性状(一因多效)QTL标记区间;以联合分析检测到13个产量性状相关QTL,其中4个QTL区间与单群体检测QTL区间重叠;越冬栽培稻产量相关性状QTL以加–显性效应遗传为主、上位性遗传效应为辅。本研究将为越冬栽培稻产量相关基因挖掘及育种创新利用奠定基础。     

水稻条纹病毒和介体灰飞虱抗性的QTL分析

水稻品种Kasalath高抗条纹病毒和介体灰飞虱。为剖析不同抗性类型基因之间的关系，利用回交重组自交系群体Nipponbare/Kasalath//Nipponbare分析了对条纹病毒和介体灰飞虱抗性的数量性状基因座。结果在第11染色体S2260–G257标记区间检测到1个与条纹病毒抗性相关的QTL（qSTV11），LOD值为9.2, 贡献率为35.79%；在第3染色体R1618–C595 和R2170–C1135标记区间各检测到1个与介体灰飞虱抗性相关的QTL (qSBPH3-a, qSBPH3-b)，LOD值和贡献率分别为3.12和2.96, 11.69% 和11.36%,表明条纹病毒和介体灰飞虱抗性由不同基因所控制,而且两者之间不相关。此外，还分别检测到两对与条纹病毒和介体灰飞虱抗性相关的上位性QTL，暗示水稻对条纹病毒和介体灰飞虱的抗性受主效和上位性QTL的共同影响。进一步分析发现SSR标记BJ11-8与qSTV11紧密连锁, 为分子标记辅助选择高抗条纹叶枯病水稻品种提供了基础。     

Mapping the QTLs underlying drought stress at developmental stage of sorghum (Sorghum bicolor (L.) Moench) by association analysis

This study was conducted to identify quantitative trait loci (QTLs) for drought tolerance in sorghum (Sorghum bicolor (L.) Moench) by association mapping using a simple sequence repeat (SSR)-marker-based diversity research set. Genotypic data for 98 SSR marker loci on ten chromosomes were used for the association analysis. The experiment was conducted under control (well-watered) and drought stress conditions, and the phenotypic values of 23 morphological traits were recorded. Drought tolerance was assessed by using a leaf drying score as a parameter of the tolerance/susceptibility: scores were assigned on a scale from 1 (most tolerant) to 9 (most susceptible). Under the control conditions, 17 QTLs associated with 12 traits were identified on chromosomes 1, 2, 4, 8, 9, and 10, with ?Log₁₀ (P) ranging from 2.5 to 7.6 and explaining 9.5–57.5 % of the total phenotypic variance for the traits. Under the drought stress conditions, nine QTLs associated with 8 traits were identified on chromosomes 1, 2, 3, and 10 that explained 9–61.2 % of the total phenotypic variance for the traits, with ?Log₁₀ (P) ranging from 2.5 to 3.5. QTLs for some traits were detected only under the drought stress condition, suggesting that these traits are important in drought tolerance. These QTLs could be used to further dissect the genetic and physiological basis of drought tolerance in sorghum.     

Identification of QTLs for rice grain size and shape of Iranian cultivars using SSR markers

Grain size is a main component of rice appearance quality. In this study, we performed the SSR mapping of quantitative trait loci (QTLs) controlling grain size (grain length and breadth) and shape (length/breadth ratio) using an F₂ population of a cross between two Iranian cultivars, Domsephid and Gerdeh, comprising of 192 individuals. A linkage map with 88 markers was constructed, which covered 1367.9 cM of the rice genome with an average distance of 18 cM between markers. Interval mapping procedure was used to identify the QTLs controlling three grain traits, and QTLs detected were further confirmed using composite interval mapping. A total of 11 intervals carrying 18 QTLs for three traits were identifed, that included five QTLs for grain length, seven QTLs for grain breadth, and six QTLs for grain shape. A major QTL for grain length was detected on chromosome 3, that explained 19.3% of the phenotypic variation. Two major QTLs for grain breadth were mapped on chromosomes 3 and 8, which explained 34.1% and 20% of the phenotypic variation, respectively. Another two major QTLs were identified for grain shape on chromosomes 3 and 8, which accounted for 27.1% and 20.5% of the phenotypic variance, respectively. The two QTLs that were mapped for grain shape coincided with the major QTLs detected for grain length and grain breadth. Intrestingly, gs2 QTL specific to grain shape was detected on chromosome 2 that explained 15% of the phenotypic variation.     

Identification of quantitative trait loci controlling soybean seed weight in recombinant inbred lines derived from PI 483463 (Glycine soja) × ‘Hutcheson’ (G. max)

The objective of this study was to identify quantitative trait loci (QTLs) controlling 100‐seed weight in soybean using 188 recombinant inbred lines (RIL) derived from a cross of PI 483463 and ‘Hutcheson’. The parents and RILs were grown for 4 years (2010–2013), and mature, dry seeds were used for 100‐seed weight measurement. The variance components of genotype (a), environment (e) and a × e interactions for seed weight were highly significant. The QTL analysis identified 14 QTLs explaining 3.83–12.23% of the total phenotypic variation. One of the QTLs, qSW17‐2, was found to be the stable QTL, being identified in all the environments with high phenotypic variation as compared to the other QTLs. Of the 14 QTLs, 10 QTLs showed colocalization with the seed weight QTLs identified in earlier reports, and four QTLs, qSW5‐1, qSW14‐1, qSW15‐1 and qSW15‐2, found to be the novel QTLs. A two‐dimensional genome scan revealed 11 pairs of epistatic QTLs across 11 chromosomes. The QTLs identified in this study may be useful in genetic improvement of soybean seed weight.     

CIMMYT小麦种质C615抗叶锈病QTL分析

由Puccinia triticina引起的叶锈病是小麦主要病害之一, 引进种质C615具有叶锈病成株期抗性, 但其抗病性遗传机制尚不清楚。本研究以抗病亲本C615与高感叶锈病亲本宁麦18构建的F_2:7代重组自交系群体为材料, 利用337对多态性SSR标记构建遗传连锁图谱, 结合2016、2017连续两年的叶锈病鉴定结果进行复合区间作图, 结果在1BL、2DS、3BS、4DL和6BS染色体上共发现了5个抗性QTL, 暂命名为QLr.njau-1BL、QLr.njau-2DS、QLr.njau-3BS、QLr.njau-4DL和QLr.njau-6BS。其中, QLr.njau-1BL、QLr.njau-3BS和QLr.njau-4DL在两年均被检测到, 分别解释10.1%~15.7%、10.9%~13.5%和8.2%~9.0%的表型变异; 另2个QTL只在一年被检测到, 解释6.2%和9.2%的表型变异。除QLr.njau-2DS外的4个抗性QTL均来源于抗病亲本C615。QLr.njau-1BL和QLr.njau-4DL分别与已报道的慢病性基因Lr46、Lr67在同一区域, QLr.njau-3B可能为一个新的抗叶锈病QTL。此外, 本研究在C615/扬麦13 (轮回亲本)BC₄F₅回交群体中选出了15个农艺性状优良且抗叶锈病的株系, 利用与C615所含抗性QTL紧密连锁的7个SSR标记对其进行基因型检测, 结果显示所有这15个株系均含有来自C615的抗性QTL, 且有3个株系聚合了全部抗性位点, 表明C615可作为抗源亲本用于高产、抗病育种。本研究结果将为分子标记选育抗叶锈品种提供材料和技术支撑。     

利用DH和IF_2群体检测油菜籽粒油酸、亚油酸、亚麻酸含量QTL

以德国冬性甘蓝型油菜Express和中国半冬性甘蓝型油菜SWU07为亲本构建包含261个株系的DH群体和包含234个株系的IF2群体,检测不同年份条件下油菜籽粒油酸、亚油酸、亚麻酸含量相关的QTL。在DH群体4年环境下共检测出71个QTL,在IF2群体2年环境下共检测出4个QTL。去掉在不同年份和群体中置信区间相互重叠的QTL之后,共得到3个品质性状的51个QTL,其中有15个在2年以上环境中被检测到。这些QTL分别分布在13个连锁群上,其中与油酸含量相关的18个,分布于A01、A02、A04、A05、A07、A09、C01连锁群,揭示3.44%～13.97%的表型变异;与亚油酸相关的12个,分布于A02、A06、A09、C01、C02连锁群,揭示3.84%～19.51%的表型变异;与亚麻酸相关的21个,分布于A01、A02、A03、A04、A05、A08、A09、C01、C02、C03、C06连锁群,揭示2.86%～11.91%的表型变异。这些结果将为油菜脂肪酸品质改良提供更多遗传信息。     

普通小麦‘Holdfast’条锈病成株抗性QTL定位

Holdfast是来自英国的小麦品种,多年来一直保持良好的条锈病持久抗性。本研究目的是发掘Holdfast的条锈病成株抗性基因及其紧密连锁的分子标记,为小麦持久抗性品种选育提供材料和方法。利用铭贤169和Holdfast杂交后代重组自交系(recombinant inbred lines, RIL)群体,于2014—2015和2015—2016年度在甘肃甘谷、甘肃中梁和四川成都进行条锈病成株抗性鉴定,并统计最大严重度(maximum disease severity, MDS)。基于小麦660K SNP芯片和BSA(bulkedsegregantanalysis)技术初步确定抗病基因所在的染色体后,将目标区域的SNP标记转化为KASP(KompetitiveallelespecificPCR)标记,检测整个RIL群体,进行基因型分析。最后进行RIL群体条锈病成株抗性的QTL分析,在5AL和7AL染色体上发现了2个成株抗性QTL。5A染色体长臂上1个条锈病成株抗性QTL QYr.gaas-5AL,在所有环境下均存在,可解释6.5%～9.3%的表型变异; QYr.gaas-5AL位于标记Ax-109948955和Ax-108798241之间,连锁距离分别为0.5 cM和1.1 cM。在7A染色体长臂上定位到1个条锈病成株抗性QTL QYr.gaas-7AL,在2015年和2016年甘谷环境中均稳定存在,分别解释6.2%和7.3%的表型变异;QYr.gaas-7AL位于标记Ax-110361069和Ax-108759561之间,连锁距离分别为0.5 cM和0.7 cM。携带QYr.gaas-5AL和QYr.gaas-7AL抗病等位基因家系的MDS显著低于感病等位基因家系的MDS,表明QYr.gaas-5AL和QYr.gaas-7AL可有效降低条锈病严重度,可应用于小麦抗条锈育种。     

Development of molecular markers for crown rot resistance in wheat: mapping of QTLs for seedling resistance in a '2-49' × 'Janz' population

Crown rot, caused by Fusarium pseudograminearum, is an important disease of wheat in Australia and elsewhere. In order to identify molecular markers associated with partial seedling resistance to this disease, bulked segregant analysis and quantitative trait loci (QTL) mapping approaches were undertaken using a population of 145 doubled haploid lines constructed from ‘2‐49’ (partially resistant) × ‘Janz’ (susceptible) parents. Phenotypic data indicated that the trait is quantitatively inherited. The largest QTLs were located on chromosomes 1D and 1A, and explained 21% and 9% of the phenotypic variance, respectively. Using the best markers associated with five QTLs identified by composite interval mapping, the combined effect of the QTLs explained 40.6% of the phenotypic variance. All resistance alleles were inherited from ‘2‐49’ with the exception of a QTL on 2B, which was inherited from ‘Janz’. A minor QTL on 4B was loosely linked (19.8 cM) to the Rht1 locus in repulsion. None of the QTLs identified in this study were located in the same region as resistance QTLs identified in other populations segregating for Fusarium head blight, caused by Fusarium graminearum.     

Mapping of quantitative trait loci associated with rice black‐streaked dwarf virus disease and its insect vector in rice (Oryza sativa L.)

Rice black‐streaked dwarf virus disease (RBSDVD), transmitted by small brown planthopper (SBPH, Laodelphax striatellus), causes serious loss in rice production. Breeding resistant cultivars are one of the most effective strategies to control the virus disease and its vector. By both natural inoculations in the field and modified seedling‐box screening test in the glasshouse, an indica variety WR24 showed high resistance to RBSDVD and SBPH. An F_2:3 population consisting of 153 lines derived from a cross between WR24 and a susceptible japonica variety Suyunuo was used for quantitative trait loci (QTL) analysis of RBSDVD and SBPH resistance. The linkage map consisting of 130 SSR markers was constructed with an average marker interval of 13.90 cM, spanning a total of 1890.9 cM. Totally, five QTLs for RBSDV resistance, viz. qRBSDV3^WR24, qRBSDV6^WR24, qRBSDV7^WR24, qRBSDV9^WR24 and qRBSDV11^WR24, were detected on chromosomes 3, 6, 7, 9 and 11, with LOD scores of 2.7, 3.08, 3.13, 5.28 and 3.7, respectively. Meanwhile, three QTLs for SBPH resistance, including qSBPH5^WR24, qSBPH7^WR24 and qSBPH10^WR24, were mapped on chromosomes 5, 7 and 10, with LOD scores of 2.18, 3.5 and 3.57, respectively. All resistant alleles were from WR24. Among these QTLs, qRBSDV7^WR24, qSBPH5^WR24 and qSBPH10^WR24 were newly reported, and qSBPH10^WR24 showed major effect that explained 17.9% of total phenotypic variance. The RBSDVD and SBPH resistance QTLs and the tightly linked DNA markers can be utilized in RBSDV and SBPH resistance breeding in rice.     

QTL analysis for wheat falling number in a recombinant inbred line population segregated with 1BL/1RS translocation in a rainfed agricultural area of China

Falling number (FN) is an inner quality trait in wheat (Triticum aestivum L.) ultimately determining the end use of wheat kernels. In this 3-year study, 171 recombinant inbred lines derived from Chuannong17 (a 1BL/1RS tranlocation parent) × Mianyang11 were planted in the Sichuan Basin, a rainfed agricultural area in southwestern China. In this climate, we found that FN had significant differences between 1BL/1RS translocation lines and non-1BL/1RS translocation lines in two of the 3 years and the heavy fluctuation of rainfall and temperature resulted in decreasing FN in grain filling period. We used 191 simple sequence repeats markers to construct a genetic linkage map and then detected 11 additive effect FN quantitative trait loci (QTL) on chromosomes 2B, 3D, 4A, 4D, 6B and 7D, explaining 5.48–31.91% of the phenotypic variance. The FN QTL on chromosomes 4A, 4D and 6B were major or stable and detected at least in 2 years, whereas the Qfn.sicau-3D.1 in 2015 year explained the maximum phenotypic variation (about 31.91%). Furthermore, FN QTLs additive and epistatic effects as well as their interactions with environment were estimated by a mixed linear model approach. We found that the additive effect QTLs had no significant additive × environment interaction, while the paired QTLs had significant additive × additive epistatic effects however none had a significant additive × additive epistasis × environment interaction effect, excluding the paired QTLs Qfn.sicau-3B/Qfn.sicau-5B.     

小麦品种扬麦16赤霉病抗扩展QTL定位及分析

扬麦系列品种赤霉病抗性在世界范围内得到重视,但其抗性遗传机制尚不清楚。扬麦16是近年来大面积推广的抗赤霉病品种,本研究以扬麦16与中麦895杂交构建的174个双单倍体(doublehaploidlines,DH)系为材料,于2017—2019年连续3年对该群体采用单花滴注进行赤霉病抗扩展鉴定。利用660KSNP芯片构建高密度遗传图谱,共检测到6个抗性QTL,分别位于2DL、3BL、4BS、4DS、5BL和6AS染色体上。除4BS位点外,其他5个抗性等位基因均来源于扬麦16。QFhb.yaas-4DS和QFhb.yaas-6AS均在多年被检测到,可解释8.8%～15.0%的表型变异;QFhb.yaas-2DL、QFhb.yaas-3BL仅在1年被检测到,分别解释10.5%和14.7%的表型变异;QFhb.yaas-5BL和来源于中麦895的QFhb.yaas-4BS仅在1年被检测到且效应仅为6.4%和8.3%。QTL效应分析结果表明,相较于单个位点,多个抗性QTL的聚合可显著降低赤霉病严重度。扬麦16抗赤霉病QTL将为揭示扬麦品种抗性遗传机制及开发相应分子标记奠定基础。     

QTL mapping for chromium-induced growth and zinc, and chromium distribution in seedlings of a rice DH population

Chromium contamination in soil has become a severe threat to crop production and food safety. The experiment was conducted using a rice DH population to detect the QTLs associated with Cr tolerance. Seventeen putative QTLs associated with growth traits included three additive loci and fourteen epistatic loci. These loci were distributed on 11 rice chromosomes, and their contribution to the phenotypic variation ranged from 2.44 to 10.08%. Two QTLs located at the similar genetic region on chromosome ten were associated with shoot Cr concentration and translocation from roots to shoots, respectively; and they accounted for 11.65 and 11.22% of the phenotypic variation. In addition, six QTLs related to Zn concentration and translocation was found on chromosomes 1, 2, 4, 5, 7 and 12. Meanwhile epistatic effect existed in the two additive QTLs of qRZC1 and qRZC7. Most of QTLs controlling Zn concentration had small genotypic variance and qSRZ4 related to Zn translocation showed growth condition-dependent expression.