水稻种子萌发和苗期ABA敏感性的QTL定位分析

植物激素ABA参与不同的生理过程,尤其是在种子发育和非生物逆境的适应都需要ABA的调控.以水稻珍汕97和旱稻IRAT109为亲本的重组自交系群体为材料,分别调查种子发芽和苗期对ABA的敏感程度.种子发芽阶段以ABA处理下的相对发芽势（Relative germination vigor,RGV）和相对发芽率（Relative germination rate,RGR）为指标,苗期以ABA喷施处理下的卷叶程度（Leaf rolling scores by ABA spaying,LRS）和含ABA水培条件下的卷叶程度（Leaf rolling scores by ABA culturing,LRC）为指标.性状相关分析表明发芽阶段的相对发芽势与苗期卷叶程度呈显著正相关.用复合区间作图法和混合线性模型对ABA敏感性QTL定位和上位性效应分析.两种软件检测到的主效QTL位点大致相同.共检测到5个单位点QTL和6对上位性QTL与发芽阶段的ABA敏感性有关;8个单位点QTL和5对上位性QTL与水稻苗期对ABA的敏感性有关;在苗期,两种ABA处理条件下共检测到两个共同的QTL;仅一个共同的QTL同时控制发芽阶段和苗期对ABA的敏感性.这些研究结果说明,水稻对ABA的敏感性同时受单位点的多基因和上位性基因控制;而且控制种子萌发阶段发芽势和苗期对ABA敏感性的遗传基础有很大的不同.     

Dynamic Quantitative Trait Loci Analysis of Seed Reserve Utilization during Three Germination Stages in Rice

In this study, one rice population of recombinant inbred lines (RILs) was used to determine the genetic characteristics of seed reserve utilization during the early (day 6), middle (day 10) and late (day 14) germination stages. The seedling dry weight (SDW) and weight of the mobilized seed reserve (WMSR) were increased, while the seed reserve utilization efficiency (SRUE) decreased, during the process of seed germination. The SDW and WMSR were affected by the seed weight, while the SRUE was not affected by the seed weight. A total of twenty unconditional and twenty-one conditional additive QTLs and eight epistatic QTLs were identified at three germination stages, and the more QTLs were expressed at the late germination stage. Among them, twelve additive and three epistatic QTLs for SDW, eight additive and three epistatic QTLs for WMSR and thirteen additive and two epistatic QTLs for SRUE were identified, respectively. The phenotypic variation explained by each additive QTL, epistatic QTL and QTL × development interaction ranged from 6.10 to 23.91%, 1.79 to 6.88% and 0.22 to 2.86%, respectively. Two major additive QTLs qWMSR7.1 and qSRUE4.3 were identified, and each QTL could explain more than 20% of the total phenotypic variance. By comparing the chromosomal positions of these additive QTLs with those previously identified, eleven QTLs might represent novel genes. The best four cross combinations of each trait for the development of RIL populations were selected. The selected RILs and the identified QTLs might be applicable to improve rice seed reserve utilization by the marker-assisted selection approach.     

Dynamic Quantitative Trait Locus Analysis of Seed Vigor at Three Maturity Stages in Rice

Seed vigor is an important characteristic of seed quality. In this study, one rice population of recombinant inbred lines (RILs) was used to determine the genetic characteristics of seed vigor, including the germination potential, germination rate, germination index and time for 50% of germination, at 4 (early), 5 (middle) and 6 weeks (late) after heading in two years. A total of 24 additive and 9 epistatic quantitative trait loci (QTL) for seed vigor were identified using QTL Cartographer and QTLNetwork program respectively in 2012; while 32 simple sequence repeat (SSR) markers associated with seed vigor were detected using bulked segregant analysis (BSA) in 2013. The additive, epistatic and QTL × development interaction effects regulated the dry maturity developmental process to improve seed vigor in rice. The phenotypic variation explained by each additive, epistatic QTL and QTL × development interaction ranged from 5.86 to 40.67%, 4.64 to 11.28% and 0.01 to 1.17%, respectively. The QTLs were rarely co-localized among the different maturity stages; more QTLs were expressed at the early maturity stage followed by the late and middle stages. Twenty additive QTLs were stably expressed in two years which might play important roles in establishment of seed vigor in different environments. By comparing chromosomal positions of these stably expressed additive QTLs with those previously identified, the regions of QTL for seed vigor are likely to coincide with QTL for grain size, low temperature germinability and seed dormancy; while 5 additive QTL might represent novel genes. Using four selected RILs, three cross combinations of seed vigor for the development of RIL populations were predicted; 19 elite alleles could be pyramided by each combination.     

Identification of QTLs with Additive,Epistatic, and QTL × Seed Maturity Interaction Effects for Seed Vigor in Rice

Seed maturity is a critical process of seed vigor establishment. In this study, one rice population of recombinant inbred lines (RILs) was used to determine the genetic characteristics of seed vigor, including the germination potential (GP), germination rate (GR), germination index (GI), and time for 50 % of germination (T₅₀), at 4, 5, and 6 weeks after heading in 2 years. Significant differences of seed vigor were observed among two parents and RIL population; the heritability of four traits was more than 90 % at three maturity stages. A total of 19 additive and 2 epistatic quantitative trait loci (QTL) for seed vigor were identified using QTL Cartographer and QTLNetwork program, respectively, in 2012, while 16 simple sequence repeat (SSR) markers associated with seed vigor were detected using bulked segregant analysis (BSA) in 2013. The phenotypic variation explained by each additive, epistatic QTL, and QTL × seed maturity interaction ranged from 9.19 to 22.94 %, 7.23 to 7.75 %, and 0.05 to 0.63 %, respectively. Ten additive QTLs were stably expressed in 2 years which might play important roles in establishment of seed vigor in different environments. By comparing chromosomal positions of ten stably expressed additive QTLs with those previously identified, they might be true QTLs for seed vigor; the regions of QTLs for seed vigor are likely to coincide with QTLs for seed dormancy, seed reserve mobilization, low-temperature germinability, and seedling growth. Using four selected RILs, three cross-combinations were predicted to improve seed vigor; 9 to 10 elite alleles could be pyramided by each combination. The selected RILs and the identified QTLs might be applicable for the improvement of seed vigor by marker-assisted selection (MAS) in rice.     

水稻耐储藏特性三年动态鉴定与QTL分析

种子耐储藏特性是粮食作物的特殊农艺性状之一, 耐储藏性能对种子生产和种质资源保存有重要意义。以粳型超级稻龙稻5 (LD5)和高产籼稻中优早8 (ZYZ8)杂交衍生的重组自交系(RILs)群体(共180个株系)为实验材料, 自然高温高湿条件下放置1年、2年和3年后, 对不同储藏时段种子发芽率进行比较, 并利用223个分子标记的遗传图谱进行动态QTL鉴定。结果表明, 不同储藏时段龙稻5的发芽率均显著低于中优早8, 株系间耐储性存在较大差异; 不同储藏时段发芽率显著相关, 相邻存储时段发芽率关系紧密。共检测到17个耐储性相关的QTLs, 3个老化时段分别检测到5、4和3个, 检测到5个动态条件QTLs, 单一QTL解释5.60%-32.76%的表型变异, 加性效应在-16.78%-16.95%范围内。主效QTL簇qSSC2、qSSC6、qSSC7和qSSC8能调控不同储藏时段的发芽率, qSSC6具有明显降低发芽率的效应。共检测到26对上位性互作位点, 主效QTL qSS1和qSS4参与上位性互作, 这表明上位性互作是调控耐储藏性状的重要遗传组成。研究结果为水稻(Oryza sativa)耐储性相关QTL的精细定位奠定基础, 同时丰富了耐储性分子标记辅助选择育种的基因资源。     

水稻耐储藏特性三年动态鉴定与QTL分析

种子耐储藏特性是粮食作物的特殊农艺性状之一, 耐储藏性能对种子生产和种质资源保存有重要意义。以粳型超级稻龙稻5 (LD5)和高产籼稻中优早8 (ZYZ8)杂交衍生的重组自交系(RILs)群体(共180个株系)为实验材料, 自然高温高湿条件下放置1年、2年和3年后, 对不同储藏时段种子发芽率进行比较, 并利用223个分子标记的遗传图谱进行动态QTL鉴定。结果表明, 不同储藏时段龙稻5的发芽率均显著低于中优早8, 株系间耐储性存在较大差异; 不同储藏时段发芽率显著相关, 相邻存储时段发芽率关系紧密。共检测到17个耐储性相关的QTLs, 3个老化时段分别检测到5、4和3个, 检测到5个动态条件QTLs, 单一QTL解释5.60%-32.76%的表型变异, 加性效应在-16.78%-16.95%范围内。主效QTL簇qSSC2、qSSC6、qSSC7和qSSC8能调控不同储藏时段的发芽率, qSSC6具有明显降低发芽率的效应。共检测到26对上位性互作位点, 主效QTL qSS1和qSS4参与上位性互作, 这表明上位性互作是调控耐储藏性状的重要遗传组成。研究结果为水稻(Oryza sativa)耐储性相关QTL的精细定位奠定基础, 同时丰富了耐储性分子标记辅助选择育种的基因资源。     

Dynamic analysis of QTLs on tiller number in rice (Oryza sativa L.) with single segment substitution lines

Twelve single segment substitution lines (SSSLs) in rice, which contain quantitative trait loci (QTLs) for tiller number detected previously, were used to study dynamic expression of the QTLs in this study. These SSSLs and their recipient, Hua-Jing-Xian 74 (HJX74), were used to produce 78 crossing combinations first, and then these combinations and their parents were grown in two planting seasons with three cropping densities. Tiller number was measured at seven developmental stages. QTL effects including main effects (additive, dominance and epistasis), QTL?×?season and QTL?×?density interaction effects were analyzed at each measured stage. The additive, dominant and epistatic effects of the 12 QTLs as well as their interaction effects with the seasons and with the densities all display dynamic changes with the development. Eight QTLs are detected with significant additive effects and/or additive?×?season and/or additive?×?density interaction effects at least at one developmental stage, and all QTLs have significant dominant and epistatic effects and/or interaction effects involved in. For most of the QTLs dominant effects are much bigger than additive effects, showing overdominance. Each QTL interacts at least with eight other QTLs. Additive and dominant effects of these QTLs are mostly positive while epistatic effects are negative and minor. Most of the QTLs show significant interactions with planting seasons and cropping densities, but the additive effects of QTLs Tn3-1 and Tn3-2, the dominant effects of QTL Tn7 and Tn8, and the epistatic effects of 14 pairs of QTLs are stable across seasons and the dominant effect of QTL Tn3-3 and the epistatic effects of QTL pairs Tn2-1/Tn6-2, Tn2-1/Tn9 and Tn3-3/Tn6-3 are nearly consistent across cropping densities. This paper is the first report of dynamics on dominances and epistasis of QTLs for tiller number in rice and provides abundant information, which is useful to improve rice tiller number via heterosis and/or QTL pyramiding.     

Dynamic quantitative trait locus analysis of seed dormancy at three development stages in rice

In this study, a rice population of recombinant inbred lines (RILs) was used to determine the genetic characteristics of seed dormancy (SD) at 4 (early), 5 (middle) and 6 (late) weeks after heading stages. Dynamic analysis showed that the indica IR28 variety tended to have deeper dormancy than the japonica Daguandao at the middle and late development stages. The level of SD decreased with the process of seed development. The significant interaction between heading date (HD) and SD occurred only in those seeds collected at the early development stage. A total of nine additive quantitative trait loci (QTLs) and eight epistatic QTLs for SD were identified at three seed development stages. Of them, one additive and four epistatic QTLs were identified for the early stage, six additive and one epistatic QTL for the middle stage and two additive and three epistatic QTLs for the late stage. The phenotypic variation explained by each additive and epistatic QTL ranged from 5.8 to 30.6 % and from 3.8 to 13.1 %, respectively. Compared with the additive QTLs, epistatic interactions were much more important for SD at the early and late development stages. Two major additive QTLs, qSD3.1 and qSD4.1, were identified; each QTL could explain more than 20 % of the total phenotypic variance and each dormancy-enhancing allele could decrease the germination percentage by about 10 %. By comparing the chromosomal positions of these additive QTLs with those previously identified, five additive QTLs, qSD1.2, qSD2.1, qSD3.2, qSD4.1 and qSD9.1, might represent novel genes. One QTL identified here, qHD1, and nine QTLs identified in previous studies for HD were co-located with our QTLs for SD, which indicated that the significant correlation between SD and HD might be due to the linkage of QTLs for SD and HD. Four RILs with deep dormancy at development stages but non-dormancy after post-ripening under different germination conditions were selected. Using the selected RILs, three cross combinations of SD for the development of RIL populations were predicted. The selected RILs and the identified QTLs might be applicable for the improvement of pre-harvest sprouting tolerance by marker-assisted selection in rice.     

小麦幼苗耐热性的QTL定位分析

以小麦DH群体(‘旱选10号’ב鲁麦14’)为材料,在高温(热胁迫)及常温(对照)两种条件下考察小麦幼苗的根干重、苗干重、幼苗生物量、叶片叶绿素含量、叶绿素荧光参数及其耐热指数,并应用基于混合线性模型的复合区间作图法分析幼苗性状及其耐热指数QTL的数量、染色体分布及表达情况,以及QTL与环境的互作效应。结果显示:(1)亲本‘旱选10号’的耐热性明显优于‘鲁麦14’,且杂交后代的耐热性出现超亲分离。(2)控制幼苗耐热相关性状的QTL位点在染色体2D、6B、3A、4A、5A和7A上分布较多,而控制幼苗性状耐热指数的QTL在染色体6A、6B、3A、2D、5A和7A上分布较多,QTL位点在染色体上的分布有区域化的趋势。(3)控制幼苗性状的单个加性QTL和上位性QTL解释的表型变异分别平均为2.48%和2.65%;而控制耐热指数的单个加性QTL和上位性QTL解释的表型变异分别平均为8.84%和1.98%。(4)在热胁迫和对照条件下共检测到与幼苗性状及其耐热指数有关的加性效应QTL 13个和上位性效应QTL 28对,分布在除4D和6D以外的19条染色体上。研究表明,控制幼苗性状的QTL以上位性效应为主,而其耐热指数的QTL以加性效应为主。     

水稻种子活力QTL定位及上位性分析

利用1个粳／籼交来源(Lemont／Teqing)、包含264个重组自交系的作图群体,采用纸卷法在18℃培养箱中进行2次重复的发芽实验,考察了种子发芽7d、9d和1ld的发芽率,种子发芽15d后的芽长及干重等种子活力的相关性状。结合一张含有198个DNA标记的连锁图谱,用作图软件QTLMapper1．0定位与种子活力相关的QTL。共检测到13个主效应QTL,这些QTL对性状的贡献率为2．9％～12．7％,平均贡献率为6．2％。同时检测到18对贡献率≥5％的互作位点,其贡献率为5．1％～11．8％,平均贡献率为6．9％,比检测到的主效应QTL的平均贡献率稍大。种子活力相关性状的大多数主效应和互作QTL成串分布于少数几个染色体区段(Chromosome Regions,CRs),并且成串分布在同一染色体区段的QTL效应的方向总是一致,该结果与这些性状在表型上的正相关相一致。若将成串分布有3个及3个以上种子活力相关性状QTL的CRs视为与种子活力高度相关的CRs,则共检测到7个上述与种子活力高度相关的CRs,分别分布在水稻12条染色体中的7条染色体上。根据所含QTL的种类(主效应QTL或／和上位性QTL)可将这些CRs分成以下3种：1)M-CRs：只含有主效应QTL,如CR^sv-7;2)E-CRs：所含位点没有主效应,但与其他位点发生互作,如CR^sv-1、CR^sv-6和CR^sv-12;3)ME-CRs：既含有主效应QTL、也含有与其他位点产生互作的互作位点,如CR^sv-2、CR^sv-5和CR^sv-8。另外还发现,有的CR上的位点同时与多个不同CR上的位点互作,影响种子活力的相关性状。与前入的研究结果相比较,发现有些与种子活力高度相关的CR可在不同研究者所用的不同定位群体中被检测到,而有的CR只在特定的定位群体中被检测到。由此表明,水稻种子活力具有丰富的遗传多样性和复杂的遗传基础,其主效QTL和互作位点可能基于遗传背景的不同而相互转化。     

Identification of QTLs for seed germination capability after various storage periods using two RIL populations in rice

Seed germination capability of rice is one of the important traits in the production and storage of seeds. Quantitative trait loci (QTL) associated with seed germination capability in various storage periods was identified using two sets of recombinant inbred lines (RILs) which derived from crosses between Milyang 23 and Tong 88-7 (MT-RILs) and between Dasanbyeo and TR22183 (DT-RILs). A total of five and three main additive effects (QTLs) associated with seed germination capability were identified in MT-RILs and DT-RILs, respectively. Among them, six QTLs were identified repeatedly in various seed storage periods designated as qMT-SGC5.1, qMT-SGC7.2, and qMT-SGC9.1 on chromosomes 5, 7, and 9 in MT-RILs, and qDT-SGC2.1, qDT-SGC3.1, and qDT-SGC9.1 on chromosomes 2, 3, and 9 in DT-RILs, respectively. The QTL on chromosome 9 was identified in both RIL populations under all three storage periods, explaining up to 40% of the phenotypic variation. Eight and eighteen pairs additive × additive epistatic effect (epistatic QTL) were identified in MT-RILs and DT-RILs, respectively. In addition, several near isogenic lines (NILs) were developed to confirm six repeatable QTL effects using controlled deterioration test (CDT). The identified QTLs will be further studied to elucidate the mechanisms controlling seed germination capability, which have important implications for long-term seed storage.     

Natural variation in Arabidopsis thaliana revealed a genetic network controlling germination under salt stress

Plant responses to environmental stresses are polygenic and complex traits. In this study quantitative genetics using natural variation in Arabidopsis thaliana was used to investigate the genetic architecture of plant responses to salt stress. Eighty seven A. thaliana accessions were screened and showed a large variation for root development and seed germination under 125 and 200 mM NaCl, respectively. Twenty two quantitative trait loci for these traits have been detected by phenotyping two recombinants inbred line populations, Sha x Col and Sha x Ler. Four QTLs controlling germination under salt were detected in the Sha x Col population. Interestingly, only one allelic combination at these four QTLs inhibits germination under salt stress, implying strong epistatic interactions between them. In this interacting context, we confirmed the effect of one QTL by phenotyping selected heterozygous inbred families. We also showed that this QTL is involved in the control of germination under other stress conditions such as KCl, mannitol, cold, glucose and ABA. Our data highlights the presence of a genetic network which consists of four interacting QTLs and controls germination under limiting environmental conditions.     

水稻萌发耐淹性的遗传分析

水稻(Oryza sativa)萌发耐淹性受到复杂的网络调控, 其分子机制不同于苗期耐淹性的相关机制, 萌发耐淹性的强弱影响着直播稻的成苗率。通过对256份水稻核心种质的萌发耐淹性评估, 发现粳稻和籼稻之间的萌发耐淹性差异并不显著, 都存在广泛的遗传变异。利用以粳稻R0380为供体亲本, 籼稻RP2334为轮回亲本的170个高代回交自交系构建含146个分子标记的连锁图谱, 以低氧胚芽鞘长度为性状指标, 通过复合区间作图法检测到影响萌发耐淹性的4个QTLs(quantitative trait loci), 分别定位于第2(2个)、3(1个)和8号(1个)染色体。贡献率最大的QTL为qGS2.2, 其值为17.34%, 增效等位基因来自轮回亲本籼稻RP2334; 其余3个QTLs的增效等位基因均来自供体亲本粳稻R0380, 贡献率分别为12.86%、9.37%和14.60%。     

Genetic Analysis of Cold Tolerance at the Germination and Booting Stages in Rice by Association Mapping

Low temperature affects the rice plants at all stages of growth. It can cause severe seedling injury and male sterility resulting in severe yield losses. Using a mini core collection of 174 Chinese rice accessions and 273 SSR markers we investigated cold tolerance at the germination and booting stages, as well as the underlying genetic bases, by association mapping. Two distinct populations, corresponding to subspecies indica and japonica showed evident differences in cold tolerance and its genetic basis. Both subspecies were sensitive to cold stress at both growth stages. However, japonica was more tolerant than indica at all stages as measured by seedling survival and seed setting. There was a low correlation in cold tolerance between the germination and booting stages. Fifty one quantitative trait loci (QTLs) for cold tolerance were dispersed across all 12 chromosomes; 22 detected at the germination stage and 33 at the booting stage. Eight QTLs were identified by at least two of four measures. About 46% of the QTLs represented new loci. The only QTL shared between indica and japonica for the same measure was qLTSSvR6-2 for SSvR. This implied a complicated mechanism of old tolerance between the two subspecies. According to the relative genotypic effect (RGE) of each genotype for each QTL, we detected 18 positive genotypes and 21 negative genotypes in indica, and 19 positive genotypes and 24 negative genotypes in japonica. In general, the negative effects were much stronger than the positive effects in both subspecies. Markers for QTL with positive effects in one subspecies were shown to be effective for selection of cold tolerance in that subspecies, but not in the other subspecies. QTL with strong negative effects on cold tolerance should be avoided during MAS breeding so as to not cancel the effect of favorable QTL at other loci.     

水稻株高构成因素的QTL剖析

利用水稻籼粳杂交 (圭 6 30× 0 2 42 8) F1 的花药离体培养建立的一个含 81个 DH家系的作图群体 ,对水稻株高构成因素 (穗长、第 1节间长、……、第 5节间长 )进行基因定位。DH群体中株高构成因素均呈正态分布。相邻的构成因素间呈极显著的正相关 ,而相距较远的构成因素间的相关较弱或不显著。采用 QTL(Quantitative trait lo-cus)分析 ,定位了影响株高构成因素的 6个 QTL:qtl7同时影响穗长和第 1、2、3节间长 ,qtl1 和 qtl2 同时影响第 4和第 5节间长 ,qtl1 0 a和 qtl1 0 b仅影响第 1节间长 ,qtl3 仅影响第 3节间长。采用 QTL 互作分析 ,检测到 19对显著的互作 ,每个构成因素受 2个或 2个以上的 QTL 互作对的影响。并且还发现 ,同一个 QTL 互作对可能影响不同的性状 ,以及一个 QTL 可以分别与不同的 QTL 产生互作而影响同一个性状或影响不同的性状 ,但总的看来 ,加性效应是主要的。这些结果揭示了株高构成因素间相关的遗传基础 ,在水稻育种中运用这些 QTL 将有助于对株高 ,以及对穗长和上部节间长度进行精细的遗传调控。     

A quantitative trait locus,qSE3, promotes seed germination and seedling establishment under salinity stress in rice

Seed germination is a complex trait determined by both quantitative trait loci (QTLs) and environmental factors and also their interactions. In this study, we mapped one major QTLqSE3 for seed germination and seedling establishment under salinity stress in rice. To understand the molecular basis of this QTL, we isolated qSE3 by map‐based cloning and found that it encodes a K⁺ transporter gene, OsHAK21. The expression of qSE3 was significantly upregulated by salinity stress in germinating seeds. Physiological analysis suggested that qSE3 significantly increased K⁺ and Na⁺ uptake in germinating seeds under salinity stress, resulting in increased abscisic acid (ABA) biosynthesis and activated ABA signaling responses. Furthermore, qSE3 significantly decreased the H₂O₂ level in germinating seeds under salinity stress. All of these seed physiological changes modulated by qSE3 might contribute to seed germination and seedling establishment under salinity stress. Based on analysis of single‐nucleotide polymorphism data of rice accessions, we identified a HAP3 haplotype of qSE3 that was positively correlated with seed germination under salinity stress. This study provides important insights into the roles of qSE3 in seed germination and seedling establishment under salinity stress and facilitates the practical use of qSE3 in rice breeding.     

Genetic effects of major QTLs controlling low-temperature germinability in different genetic backgrounds in rice (Oryza sativa L.)

The effects of QTLs are demonstrated basically within the population used in the original QTL analysis as the difference between the alleles of the parental varieties. For the efficient use of QTLs in breeding programs, it is necessary to assess whether the QTL exhibits its genetic effect when it is introgressed into different genetic backgrounds. Extensive studies of tolerance to low temperature at the seed germination stage (called low-temperature germinability) in rice revealed that 2 major QTLs on chromosomes 3 and 11, qLTG3-1 and qLTG11, have large effects. This study assessed the effects of these 2 QTLs from an aus variety, Kasalath, in different genetic backgrounds of 3 japonica varieties, Hoshinoyume, Hayamasari, and Koshihikari. Backcrossed progenies and chromosome segment substitution lines showed that both qLTG3-1 and qLTG11 were effective in the Hoshinoyume and Koshihikari backgrounds, while only qLTG3-1 was effective in the Hayamasari background. The results in this study demonstrated that these 2 QTLs are useful for the improvement of low-temperature germinability in rice breeding programs. The results also indicated that low-temperature germinability in rice is governed by an epistatic interaction of qLTG11.     

Use of randomization testing to detect multiple epistatic QTLs

Here, we describe a randomization testing strategy for mapping interacting quantitative trait loci (QTLs). In a forward selection strategy, non-interacting QTLs and simultaneously mapped interacting QTL pairs are added to a total genetic model. Simultaneous mapping of epistatic QTLs increases the power of the mapping strategy by allowing detection of interacting QTL pairs where none of the QTL can be detected by their marginal additive and dominance effects. Randomization testing is used to derive empirical significance thresholds for every model selection step in the procedure. A simulation study was used to evaluate the statistical properties of the proposed randomization tests and for which types of epistasis simultaneous mapping of epistatic QTLs adds power. Least squares regression was used for QTL parameter estimation but any other QTL mapping method can be used. A genetic algorithm was used to search for interacting QTL pairs, which makes the proposed strategy feasible for single processor computers. We believe that this method will facilitate the evaluation of the importance at epistatic interaction among QTLs controlling multifactorial traits and disorders.     

Quantitative trait loci associated with seed and seedling traits in Lactuca

Seed and seedling traits related to germination and stand establishment are important in the production of cultivated lettuce (Lactuca sativa L.). Six seed and seedling traits segregating in a L. sativa cv. Salinas x L. serriola recombinant inbred line population consisting of 103 F8 families revealed a total of 17 significant quantitative trait loci (QTL) resulting from three seed production environments. Significant QTL were identified for germination in darkness, germination at 25 and 35°C, median maximum temperature of germination, hypocotyl length at 72 h post-imbibition, and plant (seedling) quality. Some QTL for germination and early seedling growth characteristics were co-located, suggestive of pleiotropic loci regulating these traits. A single QTL (Htg6.1) described 25 and 23% of the total phenotypic variation for high temperature germination in California- and Netherlands-grown populations, respectively, and was significant between 33 and 37°C. Additionally, Htg6.1 showed significant epistatic interactions with other Htg QTL and a consistent effect across all the three seed production environments. L. serriola alleles increased germination at these QTL. The estimate of narrow-sense heritability (h²) of Htg6.1 was 0.84, indicating potential for L. serriola as a source of germination thermotolerance for lettuce introgression programs.     

Mapping QTLs of root morphological traits at different growth stages in rice

Roots are a vital organ for absorbing soil moisture and nutrients and influence drought resistance. The identification of quantitative trait loci (QTLs) with molecular markers may allow the estimation of parameters of genetic architecture and improve root traits by molecular marker-assisted selection (MAS). A mapping population of 120 recombinant inbred lines (RILs) derived from a cross between japonica upland rice 'IRAT109' and paddy rice 'Yuefu' was used for mapping QTLs of developmental root traits. All plant material was grown in PVC-pipe. Basal root thickness (BRT), root number (RN), maximum root length (MRL), root fresh weight (RFW), root dry weight (RDW) and root volume (RV) were phenotyped at the seedling (I), tillering (II), heading (III), grain filling (IV) and mature (V) stages, respectively. Phenotypic correlations showed that BRT was positively correlated to MRL at the majority of stages, but not correlated with RN. MRL was not correlated to RN except at the seedling stage. BRT, MRL and RN were positively correlated to RFW, RDW and RV at all growth stages. QTL analysis was performed using QTLMapper 1.6 to partition the genetic components into additive-effect QTLs, epistatic QTLs and QTL-by-year interactions (Q x E) effect. The results indicated that the additive effects played a major role for BRT, RN and MRL, while for RFW, RDW and RV the epistatic effects showed an important action and Q x E effect also played important roles in controlling root traits. A total of 84 additive-effect QTLs and 86 pairs of epistatic QTLs were detected for the six root traits at five stages. Only 12 additive QTLs were expressed in at least two stages. This indicated that the majority of QTLs were developmental stage specific. Two main effect QTLs, brt9a and brt9b, were detected at the heading stage and explained 19% and 10% of the total phenotypic variation in BRT without any influence from the environment. These QTLs can be used in breeding programs for improving root traits.