QTL mapping for the tocopherols at milk stage of kernel development in sweet corn

Tocopherols have several beneficial effects in plants, and are indispensable micronutrients for humans. Sweet corn is a major source of tocopherols in high concentrations. In this investigation, tocopherol compounds in sweet corn were analyzed by high performance liquid chromatography. To detect quantitative trait loci (QTL) controlling accumulation of tocopherols at the milk stage in sweet corn, a F₂ population consisting of 229 F_2:3 lines was created from the cross between a high-total tocopherols line (A6) and a low-total tocopherols line (A57). A genetic map was constructed using 136 polymorphic molecular markers including one gene-targeted marker based on the tocopherol biosynthesis pathway (HPPD). Eleven putative QTLs for tocopherol content and composition were detected by composite interval mapping and located on Chr. 1, Chr. 2, Chr. 5, Chr. 6 and Chr. 10. Phenotypic variance explained by each QTL ranged from 4.74 to 41.16 %. Eight mapped QTLs were co-localized, suggesting that the same QTL affected the amounts of more than one tocopherol compound. One candidate gene-targeted marker (HPPD) showed co-localization with the major QTL for γ-tocopherol and total tocopherols. Only one interval (umc1177–bnlg1429) on chromosome one exhibited a QTL for α, δ, γ, and total tocopherols with high LOD and R² values. The primary conclusion of this work is that two major QTLs located on Chr. 1 and Chr. 5 can be used for improvement of sweet corn nutrition quality by marker-assisted selection.     

大豆籽粒硬实加性和上位性QTL定位

硬实是植物种子的普遍特性, 是影响大豆种子发芽率、生存能力及储存期的重要数量性状, 同时影响着大豆的加工品质。本实验通过对大豆籽粒硬实性状的加性和上位性互作QTL (quantitative trait locus)分析, 明确控制大豆籽粒硬实的重要位点及效应, 旨在为进一步解析硬实性状复杂的遗传机制提供理论依据。以冀豆12和地方品种黑豆(ZDD03651)杂交构建的包含186个家系的F_6:8和F_6:9重组自交系群体为材料, 采用WinQTL Cartographer V. 2.5的复合区间作图法(composite interval mapping, CIM)定位不同年份的籽粒硬实性状相关的加性QTL, 同时采用IciMapping 4.1软件中的完备区间作图法(inclusive composite interval mapping, ICIM)检测籽粒硬实性状的加性及上位性QTL。共检测到3个籽粒硬实性状相关的加性QTL, 分别位于第2、第6和第14染色体, 遗传贡献率范围为5.54%~12.94%。同时检测到4对上位性互作QTL, 分别位于第2、第6、第9、第12和第14染色体, 可解释的表型变异率为2.53%~3.47%。同时检测到籽粒硬实性状加性及上位性互作QTL, 且上位性互作多发生在主效QTL间或主效QTL与非主效QTL间, 表明上位性互作效应在大豆籽粒硬实性状的遗传基础中具有重要的作用。     

大豆籽粒维生素E含量的QTL分析

维生素E(VE)具有提高人体免疫力、抗癌、预防心血管疾病等保健作用,从大豆中提取的VE安全性更高。本研究采用高效液相色谱技术(HPLC)检测大豆BIEX群体(Essex×ZDD2315)维生素E的α-生育酚、γ-生育酚和δ-生育酚含量。应用QTLNetwork 2.1软件分别检测到8个和12对控制大豆维生素E及组分含量的加性和互作QTL。α-生育酚含量加性和互作QTL累计贡献值分别为8.68%(2个)和15.57%(4对),γ-生育酚含量加性和互作QTL累计贡献值分别为8.59%(2个)和11.57%(2对),δ-生育酚含量加性和互作QTL累计贡献值分别为5.44%(1个)和17.61%(3对),维生素E总含量的加性和互作QTL累计贡献值分别为11.39%(3个)和9.48%(3对)。未检测到维生素E及组分含量和环境互作的QTL。未定位到的微效QTL累计贡献值为66.16%~75.32%,说明未定位到的微效基因的变异占2/3以上。各性状的遗传构成中,未检测出的微效QTL份额最大,加性QTL和互作QTL贡献相差不大。在育种中应考虑常规方法聚合微效QTL与标记辅助方法聚合主要QTL相结合。     

Genetic dissection of vitamin E content in rice (Oryza sativa) grains using recombinant inbred lines derived from a cross between 'Zhenshan97B' and 'Nanyangzhan'

Vitamin E (VE) is an important nutritional trait in rice grains. In order to dissect the genetic basis underlying VE content, a recombinant inbred lines population derived from 'Zhenshan 97B' and 'Nanyangzhan' was used for quantitative trait locus (QTL) analysis. Totally, 29 QTLs for six VE traits were identified in 2 consecutive years. Among those, five QTLs repeatedly detected in two years formed a cluster on chromosome 2, which was responsible for all five VE isomers. OsγTMT, the gene encoding γ‐tocopherol methyltransferase in rice, was located to the same region and treated as the candidate gene. Sequence analysis of alleles from two parents revealed many polymorphisms, including 19 single nucleotide polymorphisms (SNPs) and two insert/deletions (Indels) in the promoter region, two nonsynonymous SNPs in exons, and 25 SNPs and an Indel in introns. Besides, a QTL for δ‐tocotrienol and two QTLs for α‐tocopherol were repeatedly detected on chromosome 5 and 8, respectively, all three regions carrying no homologous genes involved in VE biosynthesis. These results could be useful in development of rice lines displaying desirable VE content.     

Identification of drought responsive QTLs during vegetative growth stage of rice using a saturated GBS-based SNP linkage map

Drought is a major abiotic constraint for rice production worldwide. The quantitative trait loci (QTLs) for drought tolerance traits identified in earlier studies have large confidence intervals due to low density linkage maps. Further, these studies largely focused on the above ground traits. Therefore, this study aims to identify QTLs for root and shoot traits at the vegetative growth stage using a genotyping by sequencing (GBS) based saturated SNP linkage map. A recombinant inbred line (RIL) population from a cross between Cocodrie and N-22 was evaluated for eight morphological traits under drought stress. Drought was imposed to plants grown in 75 cm long plastic pots at the vegetative growth stage. Using a saturated SNP linkage map, 14 additive QTLs were identified for root length, shoot length, fresh root mass, fresh shoot mass, number of tillers, dry root mass, dry shoot mass, and root-shoot ratio. Majority of the drought responsive QTLs were located on chromosome 1. The expression of QTLs varied under stress and irrigated condition. Shoot length QTLs qSL1.38 and qSL1.11 were congruent to dry shoot mass QTL qDSM1.38 and dry root mass QTL qDRM1.11, respectively. Analysis of genes present within QTL confidence intervals revealed many potential candidate genes such as laccase, Calvin cycle protein, serine threonine protein kinase, heat shock protein, and WRKY protein. Another important gene, Brevis radix, present in the root length QTL region, was known to modulate root growth through cell proliferation and elongation. The candidate genes and the QTL information will be helpful for marker-assisted pyramiding to improve drought tolerance in rice.     

不同统计遗传模型QTL定位方法应用效果的模拟比较

分子遗传和数量遗传的结合,发展了QTL定位研究。随着定位方法与软件的建立和完善,QTL定位的研究越来越多。准确定位的QTL可用于分子标记辅助选择和图位克隆,而假阳性QTL将误导定位信息的应用。本文分析了迄今主要定位方法(软件)对于各种遗传模型数据的适用性。应用计算机模拟4类遗传模型不同的重组自交系群体(RIL),第一类只包含加性QTL;第二类包含加性和上位性互作QTL;第三类包含加性QTL和QTL与环境互作效应;第四类包含加性、上位性互作QTL和QTL与环境互作效应。每类按模拟QTL个数不同设两种情况,共分为8种数据模型(下称M-1～M-8)。选用WinQTLCart 2.5的复合区间作图(下称CIM)、多区间作图前进搜索(MIMF)、多区间作图回归前进选择(MIMR)、IciMapping 2.0的完备复合区间作图(ICIM)、MapQTL 5.0的多QTL模型(MQM)以及QTLnetwork 2.0的区间作图(MCIM)6种程序对8种不同遗传模型的RIL进行QTL检测。结果表明,不同程序适用的遗传模型范围不同。CIM和MQM只适于检测第一类模型;MIMR、MIMF和ICIM只适于检测第一类和第二类模型;只有MCIM适于检测所有4类遗传模型;因而不同遗传模型数据的最适合检测程序不同。由于未知实际数据的遗传模型,应采用在复杂模型程序,如QTLnetwork 2.0,扫描基础上的多模型QTL定位策略,对所获模型用相应模型软件进行验证。     

甘蓝型油菜株高、第一分枝高和分枝数的QTL检测及候选基因筛选

株高、分枝数及第1分枝高是油菜重要的农艺性状。本研究利用甘蓝型油菜GH06和P174杂交,F2通过单粒法连续自交至F11构建重组自交系群体,利用油菜60K芯片对该群体进行基因分型,构建高密度遗传连锁图谱。结果表明,该图谱包含2795个SNP多态性标记位点,总长1832.9 c M,相邻标记间平均距离为0.66 c M。在此图谱基础上采用复合区间作图法(CIM),检测到3个农艺性状的24个QTL。其中11个株高QTL分别位于A01、A06、A07、A08、A10和C06染色体,单个QTL解释5.00%~15.26%的表型变异;7个第1分枝高QTL分别位于A06、C05和C06染色体,单个QTL解释5.04%~12.99%的表型变异;6个分枝数QTL分别位于A03、A07、C01、C04和C06染色体,单个QTL解释5.95%~8.14%的表型变异。将156个拟南芥株高相关基因、10个拟南芥第1分枝高相关基因和148个拟南芥分枝数相关基因与QTL对应置信区间序列进行同源比较分析(E1E–20),分别找出了20个株高候选基因、3个第1分枝高候选基因以及12个分枝数候选基因。2个环境中在A07染色体上重复检测到的QTL置信区间检测到与株高相关的候选基因ATGID1B/GID1B和WRI1,A08染色体上重复检测到的QTL置信区间检测到SLR/IAA14和AXR2/IAA72个与株高相关的候选基因。在具有部分置信区间重叠的q2013FBH-C05-1和q2014FBH-C05-2区间均检测到第1分枝高候选基因PHT1;8,在A03和C06染色体上的QTL置信区间内,分别检测到4个分枝数候选基因,匹配E值介于0~3E–56之间。     

Validating a segment on the short arm of chromosome 6 responsible for genetic variation in the hull silicon content and yield traits of rice

Rice is a typical silicon-accumulating plant and the beneficial effect of silicon on rice has long been recognized. In a previous study using 244 recombinant inbred lines (RILs) of an indica rice cross, Zhenshan 97B/Milyang 46 grown in 2003, four QTLs were detected for hull silicon content. QTL qHUS-6 had the largest effect among these, and the same interval also had significant effects on yield traits in the same population. The primary objective of this study was to validate the QTL effect in this region on HUS and yield traits. The same RIL population and another RIL population of lower heterogeneity were grown in 2004. QTL qHUS-6 was found to have significant additive effects on hull silicon content with a consistent direction in the two populations. From a residual heterozygous line selected from RILs of the same cross, 15 F_2:3 lines that differed only in a 2.15-Mb segment extending from RM587 to RM6119 on the short arm of chromosome 6 were derived. In these lines, qHUS-6 displayed a major effect, so did QTLs for yield traits previously detected in the same region. Two more QTLs for HUS detected in 2003, qHUS-1-1 and qHUS-1-2, also had consistent effects in the Zhenshan 97B/Milyang 46 RIL population in 2004. Thus this study verified three candidate regions for fine mapping HUS QTLs and determining the genetic relationship between silicon content and yield traits in rice.     

基于高密度Bin图谱的水稻抽穗期QTL定位

以粳稻品种02428和籼稻品种玉针香进行杂交, 按单粒传法连续自交10代, 得到包含192个株系的重组自交系(RIL)作图群体。通过对两亲本重测序及RIL群体简化基因组测序, 构建了包含2711个Bin标记的高密度遗传图谱。该图谱各染色体标记数在162~311个之间, 标记间平均物理距离为137.68 kb。将亲本及192个株系分别于4个环境下采用随机区组种植, 并记录抽穗期。使用WinQTL Cartographer 2.5软件的CIM分析方法, 进行抽穗期相关QTL检测及定位。在4个环境下定位到影响抽穗期的QTL共14个, 分布于第1、第2、第3、第7、第8、第9和第10染色体。其中, qHD2.2和qHD10.2能在3个环境中被重复检测到, 表型贡献率分别为5.14%~11.15%和5.35%~16.97%, 分别能缩短抽穗期1.66 d和1.56 d, 具有聚合育种的应用价值。通过物理位置比对, 14个QTL中有11个与前人定位在相同或邻近区域, qHD1.1、qHD2.2和qHD9.1尚未见报道。经对qHD2.2详细分析, 在其染色体区间内找到3个与抽穗期相关的注释基因LOC_Os02g46450、LOC_Os02g46710和LOC_Os02g46940, 其中LOC_Os02g46450已被克隆。测序分析发现, 这3个基因在两亲本间都存在差异, 可作为候选基因。     

QTL mapping of sheath blight resistance in a deep-water rice cultivar

Sheath blight, caused by the pathogen Rhizoctonia solani Kühn, is one of the most serious diseases of rice and leads to severe yield loss worldwide. A recombinant inbred line (RIL) population consisting of 121 lines was constructed from a cross between HH1B and RSB03, the latter of which is a deep-water rice variety. Five traits were used to evaluate sheath blight resistance, namely disease rating (DR), lesion length (LL), lesion height (LH), relative lesion length [RLL, the ratio of LL to plant height (PH)], and relative LH (RLH, the ratio of LH to PH). Using the RIL population and 123 molecular markers, we identified 28 quantitative trait loci (QTLs) for the five traits in two environments. These QTLs are located on nine chromosomes and most of them are environment specific. A major QTL for DR (qSBR1) on chromosome 1 was identified with contributions of 12.7% at Shanghai and 42.6% at Hainan, and it collocated with a QTL for PH. The allele at this locus from RSB03 enhances sheath blight resistance and increases PH. Another QTL for DR on chromosome 7 was adjacent to QTLs for heading date (HD) and four other disease traits. RSB03 also carries the resistant allele at this locus and shortens HD. The susceptible parent, HH1B, provides the resistance allele at the locus qSBR8, where QTLs for four other disease traits were identified. QTL mapping results showed that most QTLs for LL, LH, RLL, and RLH are collocated with QTLs for DR. Three QTLs for DR are independent from HD, PH, and four other disease traits, while four QTLs are closely related to HD and PH. Four QTLs for LL, LH, RLL, and RLH are independent from DR, HD, and PH, while there is only one region harboring QTLs for these four traits and HD. Correlation analysis and QTL mapping results indicated that LL, LH, RLL, and RLH might be important indices, like DR, for evaluating the level of resistance to rice sheath blight.     

Soybean plant height QTL mapping and meta‐analysis for mining candidate genes

Plant height is closely related to seed yield of soybean. The goal of this study was to identify important loci affecting soybean plant height using meta‐analysis based on a reference physical map. Plant height related to QTLs was mapped across eight years with a RIL population by WinQTLCart v2.5. 182 QTLs related to plant height of soybean from database and our research were collected, and each QTL was projected onto the soybean physical map by software BioMercator v2.1. The confidence interval of meta‐QTL ranged from 0.09 to 5.07 Mb, and the mean phenotypic variance ranged from 4.9% to 73.0%. Furthermore, 4,259 candidate genes were located in these consensus QTLs, and 40 of them were involved in the plant growth and stem elongation and annotated as plant hormone signal transduction (pathway ID ko04075) in KEGG pathway. These results would lay a foundation for fine mapping of QTLs/genes related to plant height and marker‐assisted selection for breeding in soybean.     

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.     

基于QTL定位和全基因组关联分析筛选甘蓝型油菜株高和一次有效分枝高度的候选基因

株高和一次有效分枝高度是与甘蓝型油菜结荚层厚度、收获指数紧密关联的重要农艺性状,有关株高的数量性状位点(quantitative trait locus,QTL)和全基因组关联分析(genome-wide association study,GWAS)已有很多报道,但对一次有效分枝高度的QTL和GWAS定位以及候选基因筛选的研究报道较少。本研究利用已构建的高密度遗传连锁图对2016和2017年2个环境的186个株系组成的重组自交系群体株高和一次有效分枝高度及其最佳线性无偏预测(best linear unbiased prediction,BLUP)值进行QTL定位共检测到8个株高的QTL,分别位于A03、A04和A09染色体,单个QTL解释4.60%~13.29%的表型变异,其中位于A04染色体上的QTL(q-2017PH-A04-2和q-BLUP-PH-A04-2)在2017年和BLUP中均被检测到;检测到9个一次有效分枝高度QTL,分别位于A01、A02、A05、A09、C01和C05染色体上,单个QTL解释5.12%~19.10%的表型变异,其中q-2017BH-A09-1、q-BLUP-BH-A09-2和q-BLUP-BH-A09-3有重叠区段。同时,利用课题组前期完成的588份重测序自然群体进行全基因组关联分析,2年共检测到与株高显著关联的50个SNP位点和与一次有效分枝高度显著关联的12个SNP位点;根据SNP的物理位置,筛选出参与细胞增殖、细胞扩增、细胞周期和细胞壁活动的13个株高候选基因,以及参与赤霉素、亚精胺等合成代谢途径、核糖体组成和在光合、萌发等过程中有一定作用的一次分枝高度的11个候选基因,并利用荧光定量PCR技术验证候选基因在极端材料中的表达情况。本研究结果将为油菜株型改良及后续基因的功能研究提供理论依据。     

Mapping of QTLs in tomato line FLA456 associated with resistance to a virus causing tomato yellow leaf curl disease

Tomato (yellow) leaf curl disease (TYLCD) is a serious threat to tomato production in the tropics and subtropics. The genetics of resistance to Tomato yellow leaf curl Thailand virus Taiwan strain (TYLCTHV-[TW]) in a highly resistant tomato line FLA456 was studied through quantitative trait loci (QTL) analysis. Four QTLs named qTy4.1, qTy6.1, qTy10.1 and qTy11.1 were detected on chromosomes 4, 6, 10, and 11, respectively, through evaluation of an F₆ recombinant inbred line (RIL) population derived from a cross between FLA456 (resistant) and CLN1621L (susceptible). Gene action of all QTLs was recessive based on disease reaction of the F₁. The markers SINAC1 and SLM4-34 flanked qTy4.1 on chromosome 4, and SLM11-12 and SLM11-17 defined qTy11.1, which co-located with the previously identified Ty-5 and Ty-2 loci, respectively. qTy6.1 was flanked by the markers SLM6-55 and TES-0014, and qTy10.1 by the markers SLM10-80-SLM10-46 on chromosomes 6 and 10. The LOD values of the putative QTLs ranged from 2.79 to 13.76. The phenotypic variance explained by each QTL ranged from 7.1 to 31.9 %. The four QTLs collectively contributed about 60.5 % of the phenotypic variation in resistance against TYLCTHV-[TW]. Group mean severity scores of those RILs possessing three or four qTy were generally lower than RIL groups with only one or no qTy. Given the diversity of begomoviruses that cause TYLCD across the regions, the new QTLs from FLA456 would be valuable in tomato breeding for developing varieties with durable resistance. Two QTL intervals (qTy4.1 and qTy10.1) contained virus resistance candidate genes such as CTV.22 and eukaryotic translation initiation factor 4E.     

基于侯选基因标记的四倍体马铃薯休眠QTL关联分析

休眠期是马铃薯(SolanumtuberosumL.)重要的块茎性状之一,寻找调控马铃薯块茎休眠的关键基因,揭示其分子机制以选育具有适宜休眠期长度的马铃薯品种,对于解决当前马铃薯产业中过长或过短休眠期带来的经济损失和食品安全隐患等问题十分关键。前期研究在二倍体马铃薯连锁群体中定位了6个加性休眠QTL,本研究拟在四倍体马铃薯育种材料中验证这些休眠QTL。基于休眠QTL连锁的候选基因标记,采用混合线性模型(MLM),模型中考虑群体结构和亲缘关系(Q+K),在四倍体马铃薯自然群体St-hzau中对马铃薯块茎休眠期进行了关联分析。5号染色体上休眠QTL DorB5.3连锁的候选基因标记S199_300和GWD (根据葡聚糖水双激酶α-glucan water dikinase基因设计)与马铃薯块茎休眠期具有显著的关联(P0.05),分别解释了休眠期表型变异的7.8%和3.2%,分别能增加休眠期7.1 d和4.5 d,即在二倍体马铃薯连锁群体中定位的稳定主效休眠QTL DorB5.3在四倍体马铃薯关联群体St-hzau中也表现显著, DorB5.3的稳定性在关联分析结果中得到了验证,表明候选基因标记策略在马铃薯块茎休眠QTL关联分析中是一种有效的策略。本研究所验证的主效休眠QTL DorB5.3及相应连锁标记可以直接用于马铃薯休眠育种。据此可以推测GWD可能在控制还原糖含量和块茎休眠2个方面均发挥作用,马铃薯块茎休眠机制与还原糖含量变化机制可能存在着部分交叉。     

水稻粒型和粒重的QTL定位分析

利用以两个籼稻品种H359和Acc8558为亲本杂交建立的重组自交系群体及相应的分子标记连锁图，对水稻粒长、粒宽和粒重进行了QTL定位分析。检测到15个与粒长有关的QTL、17个与粒宽有关的QTL及16个与粒重有关的QTL，它们可分别解释75．91％、76．20％和81．40％的表型变异。其中在5号染色体上检测到1个控制粒宽的主效QTL，可解释26．65％的表型变异。粒长和粒宽之间虽然相关显著，但相关系数很小(r=0．180)。而QTL分析结果也显示，两者的QTL位置很少相同。这说明粒长和粒宽有不同的遗传基础。粒长和粒宽与粒重的相关系数分别为0．781和0．461，直接通径系数分别为0．7220和0．3299。QTL定位结果也显示，粒长与粒重的QTL位置相近或重叠的较多。因此，粒长对粒重的贡献较大。     

Analysis of quantitative trait loci underlying the period of reproductive growth stages in soybean (<Emphasis Type="Italic">Glycine max</Emphasis> [L.] Merr.)

Quantitative trait loci (QTLs) underlying reproductive growth stages are important for molecular breeding of soybeans [Glycine max (L.) Merr.]. Most of these QTLs identified so far derived from a single environment, and thus may be influenced by specific environmental conditions. In this study (from 2004 to 2005), analysis of QTLs underlying the period to reach a given reproductive growth stage was performed in three different environments (Harbin, Heilongjiang Province, China). QTL analysis was achieved with a recombination inbred line (RIL) population consisting of 153 lines. The RIL population derived from a cross between an American semi-dwarf cultivar (cv. Charleston) and a Chinese line with a short growth stage (cv. Dongnong 594). The growth stage data of soybean was recorded for each day. QTLs for all eight reproductive growth stages of soybean (R1 to R8) were analyzed by a composite interval mapping method combined with a mixed genetic model. Fifty-four QTLs displayed main effects and 56 QTL pairs showed epistatic effects. Two marker intervals (Satt173–Satt581, Satt402–Satt267), located on the linkage group O and D1a respectively, strongly influenced plant developmental processes during reproductive growth stages. The findings of this study open the possibility to modulate the structure of soybean growth stages by marker-assisted selection and pyramiding QTL analysis. H.-M. Qiu and D.-W. Xin contributed equally to this work.     

不同环境基于高密度遗传图谱的稻米外观品质QTL定位

为解析稻米外观品质遗传基础, 挖掘稳定存在的控制稻米外观品质性状的QTL, 本研究以籼稻品种V20B和爪哇稻品种CPSLO17作为亲本, 构建包含150个重组自交家系(recombinantion inbred line, RIL)的RIL作图群体, 进行外观品质性状QTL定位分析。利用特定位点扩增长度测序(SLAF-seq)技术, 构建了一个由12个连锁群包含8602个标记, 平均间距为0.29 cM的高密度遗传图谱。采用IciMapping 4.0软件的ICIM-ADD方法在3种环境(贵阳、贵定、三亚)对4个外观品质性状(粒长、粒宽、垩白度和垩白粒率)进行QTL (quantitative trait locus)定位分析。结果表明: 3种环境共检测到9个粒长QTL、6个粒宽QTL、3个垩白度QTL和4个垩白粒率QTL; 有5个QTL在多个环境被重复检测到, 其中3种环境都定位到的粒宽QTL qGW5-1和垩白度QTL qCha5-1为同一定位区间(第5染色体的Marker1642127-Marker1514505); 此外, 垩白度QTL qCha5-2的定位区间(Marker1554573-Marker1554589)和垩白粒率QTL qCGP5-2也是一样的。序列比对发现QTL qCha5-1定位区间仅51.5 kb, 是新的垩白性状主效QTL。本研究结果不仅为挖掘新的外观品质性状基因奠定基础, 也有助于开发新的分子标记进行水稻外观品质性状遗传改良。     

Quantitative trait locus mapping for seed artificial aging traits using an F2:3 population and a recombinant inbred line population crossed from two highly related maize inbreds

Quantitative trait locus (QTL) mapping for seed longevity is essential for breeding modern cultivars with resistance to deterioration during postharvest storage. The inbred lines X178 and I178 showed large differences in seed vigour after artificial aging treatment, while they had similar performances in terms of most agronomic traits. An F_2:3 population and a recombinant inbred line (RIL) population were generated to map QTL after 5 days under artificial aging conditions. Positive correlations were observed among all investigated traits including the aging germination rate, relative aging germination rate, aging simple vigour index, aging primary root length, aging shoot length and aging total length. Thirteen QTL were identified to locate on five chromosome regions: Chr.1:297 Mb (chromosome 1 region 297 Mb), Chr.3:205 Mb, Chr.4:240 Mb, Chr.5:205 Mb and Chr.7:155 Mb, with 2 to 4 QTL co‐located on a region. In each region, 3–8 previously identified aging‐related QTL were located, confirming the importance of these regions for controlling seed longevity in different maize populations. Taken together, the results of this work provide a foundation for further QTL fine mapping and the molecular‐assisted breeding of aging tolerant maize.     

QTL for maize grain yield identified by QTL mapping in six environments and consensus loci for grain weight detected by meta‐analysis

Grain yield is the most important and complicated trait in maize. In this study, a total of 498 recombinant inbred lines (RIL) derived from a biparental cross of two elite inbred lines, 178 and P53, were grown in six different environments. Quantitative trait locus (QTL) mapping was conducted for three grain yield component traits (100 grain weight, ear weight and kernel weight per plant). Subsequently, meta‐analysis was performed after a comprehensive review of the research on QTL mapping for grain weight (100, 300 and 1000) using BioMercator V4.2. In total, 62 QTLs were identified for 100 grain weight, ear weight and kernel weight per plant in six environments. Forty‐three meta‐QTLs (MQTLs) were detected by meta‐analysis. A total of 13 candidate genes homologous to eight functionally characterized rice genes were found, and four candidate genes were located in the two hot spot regions of MQTL1.5 and MQTL2.3. Our results suggest that the combination of literature collection, meta‐analysis and homologous blast searches can offer abundant information for further fine mapping, marker‐assisted selection (MAS) breeding and map‐based cloning for maize.