Fine Mapping and Candidate Gene Prediction of a Pleiotropic Quantitative Trait Locus for Yield-Related Trait in Zea mays

The yield of maize grain is a highly complex quantitative trait that is controlled by multiple quantitative trait loci (QTLs) with small effects, and is frequently influenced by multiple genetic and environmental factors. Thus, it is challenging to clone a QTL for grain yield in the maize genome. Previously, we identified a major QTL, qKNPR6, for kernel number per row (KNPR) across multiple environments, and developed two nearly isogenic lines, SL57-6 and Ye478, which differ only in the allelic constitution at the short segment harboring the QTL. Recently, qKNPR6 was re-evaluated in segregating populations derived from SL57-6×Ye478, and was narrowed down to a 2.8 cM interval, which explained 56.3% of the phenotypic variance of KNPR in 201 F_2∶3 families. The QTL simultaneously affected ear length, kernel weight and grain yield. Furthermore, a large F₂ population with more than 12,800 plants, 191 recombinant chromosomes and 10 overlapping recombinant lines placed qKNPR6 into a 0.91 cM interval corresponding to 198Kb of the B73 reference genome. In this region, six genes with expressed sequence tag (EST) evidence were annotated. The expression pattern and DNA diversity of the six genes were assayed in Ye478 and SL57-6. The possible candidate gene and the pathway involved in inflorescence development were discussed.     

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.     

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.     

Identification of Quantitative Trait Loci for ABA Sensitivity at Seed Germination and Seedling Stages in Rice

Abscisic acid (ABA) is one of the important plant hormones, which plays a critical role in seed development and adaptation to abiotic stresses. The sensitivity of rice (Oryza sativa L.) to exogenous ABA at seed germination and seedling stages was investigated in the recombinant inbred line (RIL) population derived from a cross between irrigated rice Zhenshan 97 and upland rice IRAT109, using relative germination vigor (RGV), relative germination rate (RGR) and leaf rolling scores of spraying (LRS) or culturing (LRC) with ABA as sensitivity indexes. The phenotypic correlation analysis revealed that only RGV at germination stage was positively correlated to ABA sensitivity at seedling stage. QTL detection using composite interval mapping (CIM) and mixed linear model was conducted to dissect the genetic basis of ABA sensitivity, and the single-locus QTLS detected by both methods are in good agreement with each other. Five single QTLs and six pairs of epistatic QTLs were detected for ABA sensitivity at germination stage. Eight single QTLs and five pairs of epistatic QTLs were detected for ABA sensitivity at seedling stage. Two QTLs were common between LRS and LRC; and one common QTL was detected for RGV, LRS and LRC simultaneously. These results indicated that both single and epistatic loci were involved in the ABA sensitivity in rice, and the genetic basis of ABA sensitivity at seed germination and seedling stage was largely different.     

不同发育阶段水稻苗高的QTL分析

分析了不同发育阶段控制水稻苗高的QTL,用5个阶段和4个净增长量的数据共检测到9个QTL,分别位于染色体1,4,6,7,8,11,和12号上。SH－4是主基因,它在各个阶段都表达,对苗高的贡献率在20％以上。结果表明,数量性状的发育或形态建成是由数量性状位点基因选择性表达的结果。     

不同发育阶段水稻苗高的QTL分析

分析了不同发育阶段控制水稻苗高的QTL, 用5个阶段和4个净增长量的数据共检测到9个QTL,分别位于染色体1,4,6,7,8,11,和12号上。SH-4 是主基因,它在各个阶段都表达,对苗高的贡献率在20%以上。结果表明, 数量性状的发育或形态建成是由数量性状位点基因选择性表达的结果。 Abstract:QTLs conferring rice seedling height at different developmental stages were analyzed in this paper using a DH population with 122 lines deriving from a cross between indica variety Zai-Ye-Qing 8 and japonica variety Jing-Xi 17. A total of nine QTLs were identified with the data of five stages and four sets of net increase data between two successive stages. Of all the QTLs, Sh-4was a major gene, it expressed at all stages and accounted for more than 20% of the variance. The results revealed that the development of the quantitative trait was controlled by the selective expression of the genes at quantitative trait loci.     

Mapping of Quantitative Trait Loci Underlying Cold Tolerance in Rice Seedlings via High-Throughput Sequencing of Pooled Extremes

Low temperature is a major limiting factor in rice growth and development. Mapping of quantitative trait loci (QTLs) controlling cold tolerance is important for rice breeding. Recent studies have suggested that bulked segregant analysis (BSA) combined with next-generation sequencing (NGS) can be an efficient and cost-effective way for QTL mapping. In this study, we employed NGS-assisted BSA to map QTLs conferring cold tolerance at the seedling stage in rice. By deep sequencing of a pair of large DNA pools acquired from a very large F₃ population (10,800 individuals), we obtained ∼450,000 single nucleotide polymorphisms (SNPs) after strict screening. We employed two statistical methods for QTL analysis based on these SNPs, which yielded consistent results. Six QTLs were mapped on chromosomes 1, 2, 5, 8 and 10. The three most significant QTLs on chromosomes 1, 2 and 8 were validated by comparison with previous studies. Two QTLs on chromosomes 2 and 5 were also identified previously, but at the booting stage rather than the seedling stage, suggesting that some QTLs may function at different developmental stages, which would be useful for cold tolerance breeding in rice. Compared with previously reported QTL mapping studies for cold tolerance in rice based on the traditional approaches, the results of this study demonstrated the advantages of NGS-assisted BSA in both efficiency and statistical power.     

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RIL群体芽期耐冷性基因的分子标记定位

水稻芽期冷害是我国长江中下游的早稻种植区和东北、西北稻区及云贵高原的一季稻区水稻生产中的重要限制因子之一。研究中利用纸卷法测定1个水稻重组自交系群体对10℃低温的芽期耐冷性,结合1张高密度分子遗传图谱,进行QTL定位分析。检测到控制水稻芽期耐冷性的4个QTL,分别位于1、3、7和11号染色体上。其中,位于11号染色体上的QTL qSCT-11的效应最大,在10℃低温处理13d时,对性状的贡献率达26％～30％,被检测到的LOD值也高达16～19,其加性效应值为正,增效等位基因存在于亲本Lemont中,RM202为与QTL qSCT-11紧密连锁的SSR标记。该主效QTL的增效基因,可作为分子标记辅助选择的操作对象用于水稻芽期耐冷性的遗传改良。     

水稻幼苗活力性状的低温反应数量性状基因座检测

以籼粳交“密阳23/吉冷1号”的F2：3代200个家系作为作图群体,在12℃冷水胁迫下,进行苗高、苗鲜重和苗干重等水稻幼苗活力性状的低温反应鉴定,并利用由SSR标记构建的分子连锁图谱为基础,对冷水胁迫下苗高、苗鲜重和苗干重以及它们的低温反应指数进行了数量性状基因座（QTLs）检测。研究结果表明,低温胁迫下上述幼苗活力性状在F3家系群中均表现为接近正态的连续分布,表现为由多基因控制的数量性状;在第1、2、7、8和12染色体上,检测到与幼苗活力性状的低温反应相关的QTL共12个,对表型变异的贡献率范围为5．2％-17．9％,其中位于第2染色体RM262-RM263区间和第12染色体RM270-RM17区间的与低温下苗高相关的qCSH2和qCSH12,以及位于第12染色体RM19-RM270区间和第1染色体RM129-RM9区间的分别控制低温下苗干重及其低温反应指数的qSDW12和qCSDW1对表型变异的贡献率较大,分别为16．6％、17．9％、15．9％和16．2％。其增效等位基因均来自吉冷1号,前两者均表现为加性效应,后两者分别表现为显性和超显性。     

Whole-Genome Quantitative Trait Locus Mapping Reveals Major Role of Epistasis on Yield of Rice

Although rice yield has been doubled in most parts of the world since 1960s, thanks to the advancements in breeding technologies, the biological mechanisms controlling yield are largely unknown. To understand the genetic basis of rice yield, a number of quantitative trait locus (QTL) mapping studies have been carried out, but whole-genome QTL mapping incorporating all interaction effects is still lacking. In this paper, we exploited whole-genome markers of an immortalized F₂ population derived from an elite rice hybrid to perform QTL mapping for rice yield characterized by yield per plant and three yield component traits. Our QTL model includes additive and dominance main effects of 1,619 markers and all pair-wise interactions, with a total of more than 5 million possible effects. The QTL mapping identified 54, 5, 28 and 4 significant effects involving 103, 9, 52 and 7 QTLs for the four traits, namely the number of panicles per plant, the number of grains per panicle, grain weight, and yield per plant. Most identified QTLs are involved in digenic interactions. An extensive literature survey of experimentally characterized genes related to crop yield shows that 19 of 54 effects, 4 of 5 effects, 12 of 28 effects and 2 of 4 effects for the four traits, respectively, involve at least one QTL that locates within 2 cM distance to at least one yield-related gene. This study not only reveals the major role of epistasis influencing rice yield, but also provides a set of candidate genetic loci for further experimental investigation.     

Correlation of Cold Tolerance at Different Growth Stages in Rice

Cold injury which influence rice production in different rice growing countries occurs at various growth stages. The degree of cold injury depends on the air or water temperature, the cropping pattern, the growth stage of the rice and other factors. It is generally accepted that cold tolerance of rice at one stage is different from another stage. However, Okabe and Toriyama reported that varieties seem to respond similarly to cold temperature at different growth stages. Some varieties have been found to be tolerant at different growth stages. The purpose of this experiment is to find whether cold tolerance scores at different growth stages of different kinds of rice are correlated or not.     

Quantitative Trait Locus Mapping for Yield-Associated Agronomic Traits in a BC2F6 Population of Japonica Hybrid Rice Liaoyou 5218

Journal of Plant Growth Regulation - RAD-seq method is a recently developed, cost-effective, and high-throughput approach for detecting genetic variability based on single-nucleotide polymorphisms...     

水稻芽期耐冷性的QTL分析

本研究以98个Nipponbare/Kasalath//Nipponbare回交重组自交家系(backcross-inbred lines,BILs)组成的群体为材料,进行水稻芽期耐冷性数量性状基因座的检测和遗传效应分析.25℃正常条件下水稻发芽7 d,芽长5～10 cm,5℃低温处理10d,之后升温至25℃,缓苗10d,调查活苗率,并以活苗率作为芽期耐冷性的表型值,分析亲本和98个BILs的芽期耐冷性表现.采用Windows QTL Cartographer 1.13a软件的复合区间作图法,共检测到4个苗期耐冷性数量性状基因座(quantative trait locus,QTL),分别位于第3、第7和第12染色体上,命名为qSCT-3-1、qSCT-3-2、qSCT-7和qSCT-12.4个QTL的加性效应分别为11.16、11.14、-8.8和-14.59,可解释表型变异的12.11%,12.66%,6.82%和15.86%.     

茶陵野生稻苗期耐冷性研究

以耐冷性强弱不同的栽培稻为参比,通过自然冷胁迫与(或)人工冷处理,比较了茶陵野生稻与不同类型栽培稻经冷胁迫后的秧苗成活率、净光合速率和光系统Ⅱ光化学量子效率的变化,对茶陵野生稻苗期耐冷性作出评估.结果表明:经冷胁迫后,茶陵野生稻上述指标值的变化小于典型籼稻和爪哇稻,大于典型粳稻.说明茶陵野生稻苗期耐冷性强于籼稻和爪哇稻,但弱于粳稻.     

A Hidden Markov Model Combining Linkage and Linkage Disequilibrium Information for Haplotype Reconstruction and Quantitative Trait Locus Fine Mapping

Faithful reconstruction of haplotypes from diploid marker data (phasing) is important for many kinds of genetic analyses, including mapping of trait loci, prediction of genomic breeding values, and identification of signatures of selection. In human genetics, phasing most often exploits population information (linkage disequilibrium), while in animal genetics the primary source of information is familial (Mendelian segregation and linkage). We herein develop and evaluate a method that simultaneously exploits both sources of information. It builds on hidden Markov models that were initially developed to exploit population information only. We demonstrate that the approach improves the accuracy of allele phasing as well as imputation of missing genotypes. Reconstructed haplotypes are assigned to hidden states that are shown to correspond to clusters of genealogically related chromosomes. We show that these cluster states can directly be used to fine map QTL. The method is computationally effective at handling large data sets based on high-density SNP panels.ARRAY technology now allows genotyping of large cohorts for thousands to millions of single nucleotide polymorphisms (SNPs), which are becoming available for a growing list of organisms including human and domestic animals. Among other applications, these advances permit systematic scanning of the genome to map trait loci by association (e.g., Wellcome Trust Case Control Consortium 2007; Charlier et al. 2008), to predict genomic breeding values for complex traits (Meuwissen et al. 2001; Goddard and Hayes 2009), or to identify signatures of selection (e.g., Voight et al. 2006).Present-day genotyping platforms do not directly provide information about linkage phase; i.e., co-inherited alleles at adjacent heterozygous markers (haplotypes) are not identified as such. As haplotype information may considerably empower genetic analyses, indirect phasing strategies have been devised: haplotypes can be reconstructed from unphased genotypes using either familial information (Mendelian segregation and linkage) and/or population information (linkage disequilibrium, LD, and surrogate parents) (e.g., Windig and Meuwissen 2004; Scheet and Stephens 2006; Kong et al. 2008).Haplotype-based approaches are routinely applied in animal genetics for combined linkage and LD mapping of QTL (e.g., Meuwissen and Goddard 2000; Blott et al. 2003). In these studies, phasing has so far relied on familial information provided by the extended pedigrees typical of livestock (e.g., Windig and Meuwissen 2004). This approach, however, leaves a nonnegligible proportion of genotypes unphased, especially for the less connected individuals. After phasing, identity-by-descent (IBD) probabilities conditional on haplotype data—needed for QTL mapping—are computed for all chromosome pairs, using familial as well as population information (hence combined linkage and LD mapping – L + LD) (e.g., Meuwissen and Goddard 2001). However, the use of high-density SNP chips and the analysis of ever larger cohorts render the computation of pairwise IBD probabilities a bottleneck.We herein propose a more efficient, heuristic approach based on hidden Markov models (HMM). It simultaneously phases and sorts haplotypes in clusters that can be used directly for mapping or other purposes. The proposed method exploits familial as well as population information, and imputes missing genotypes. We herein describe the accuracy of the proposed method and its use for L + LD mapping of QTL.     

利用染色体单片段代换系定位水稻芽期耐冷QTL

水稻(Oryza sativa)芽期耐冷性是其生长发育过程中不可忽视的重要数量性状,易受遗传背景的干扰和环境因素的影响;利用单片段代换系(SSSL.s)能减少遗传背景的干扰。该研究以85个单片段代换系为材料,其受体亲本为广陆矮4号,供体亲本为日本晴。通过单因素方差分析和Dun netts多重比较,分析单片段代换系与受体亲本之间芽期耐冷性的差异,并对代换片段上的芽期耐冷QTL进行鉴定。以F≤0.001为闽值共检测到8个芽期耐冷QTL,分别分布在第1、6、8、9和10号染色体上,其中4个QTL通过代换作图被初步定位。这些QTL加性效应均表现为增效作用,在2个年度间其加性效应值的变化范围分别为14%-44%和10%-45%,加性效应百分率的变化范围分别为700%-2 200%和500%-2 250%,其中qCTPg-2在2个年度间的加性效应均最高,分别为44%和45%。研究结果对进一步发掘和利用新的水稻芽期耐冷QTL具有重要意义。     

Quantitative Trait Locus Mapping and Candidate Gene Analysis for Plant Architecture Traits Using Whole Genome Re-Sequencing in Rice

Plant breeders have focused on improving plant architecture as an effective means to increase crop yield. Here, we identify the main-effect quantitative trait loci (QTLs) for plant shape-related traits in rice (Oryza sativa) and find candidate genes by applying whole genome re-sequencing of two parental cultivars using next-generation sequencing. To identify QTLs influencing plant shape, we analyzed six traits: plant height, tiller number, panicle diameter, panicle length, flag leaf length, and flag leaf width. We performed QTL analysis with 178 F₇ recombinant in-bred lines (RILs) from a cross of japonica rice line ‘SNUSG1’ and indica rice line ‘Milyang23’. Using 131 molecular markers, including 28 insertion/deletion markers, we identified 11 main- and 16 minor-effect QTLs for the six traits with a threshold LOD value > 2.8. Our sequence analysis identified fifty-four candidate genes for the main-effect QTLs. By further comparison of coding sequences and meta-expression profiles between japonica and indica rice varieties, we finally chose 15 strong candidate genes for the 11 main-effect QTLs. Our study shows that the whole-genome sequence data substantially enhanced the efficiency of polymorphic marker development for QTL fine-mapping and the identification of possible candidate genes. This yields useful genetic resources for breeding high-yielding rice cultivars with improved plant architecture.