基于元分析的抗玉米丝黑穗病QTL比较定位

以玉米遗传连锁图谱IBM2 2005 Neighbors为参考图谱,通过映射整合不同试验中的抗玉米丝黑穗病QTL,构建QTL综合图谱。在国内外种质中,共发现22个抗病QTL,分布在除第7染色体外的9条玉米染色体上。采用元分析技术,获得2个“一致性”抗病QTL,图距分别为8.79 cM和18.92cM。从MaizeGDB网站下载“一致性”QTL区间内基因和标记的原始序列;采用NCBI网站在线软件BLASTx通过同源比对在2个“一致性”QTL区间内初步获得4个抗病位置候选基因。借助比较基因电子定位策略,将69个水稻和玉米抗性基因定位于玉米IBM2图谱上,在2个“一致性”QTL区间内分别发现1个水稻抗性基因,初步推断为抗病位置候选基因。本文结果为抗玉米丝黑穗病QTL精细定位和分子育种提供了基础。     

The Genetic Architecture of Flowering Time and Photoperiod Sensitivity in Maize as Revealed by QTL Review and Meta Analysis

The control of flowering is not only important for reproduction,but also plays a key role in the processes of domestication and adaptation.To reveal the genetic architecture for flowering time and photoperiod sensitivity,a comprehensive evaluation of the relevant literature was performed and followed by meta analysis.A total of 25 synthetic consensus quantitative trait loci(QTL)and four hot-spot genomic regions were identified for photoperiod sensitivity including 11 genes related to photoperiod response or flower morphogenesis and development.Besides,a comparative analysis of the QTL for flowering time and photoperiod sensitivity highlighted the regions containing shared and unique QTL for the two traits.Candidate genes associated with maize flowering were identified through integrated analysis of the homologous genes for flowering time in plants and the consensus QTL regions for photoperiod sensitivity in maize(Zea mays L.).Our results suggest that the combination of literature review,meta-analysis and homologous blast is an efficient approach to identify new candidate genes and create a global view of the genetic architecture for maize photoperiodic flowering.Sequences of candidate genes can be used to develop molecular markers for various models of marker-assisted selection,such as marker-assisted recurrent selection and genomic selection that can contribute significantly to crop environmental adaptation.     

玉米抗甘蔗花叶病毒基因的比较定位

收集了玉米抗甘蔗花叶病毒基因/QTL定位信息, 借助玉米遗传图谱IBM2 2005 Neighbors进行了整合。在国内外研究中, 累计报道81个抗病毒基因位点, 分布在玉米7条染色体上, 比较定位发现这些位点集中分布于第3和6染色体。采用元分析技术, 确定3个“一致性”抗病毒QTL, 其中1个位于第3染色体, 在遗传图谱IBM2 2005 Neighbors上覆盖的范围为6.44 cM; 2个位于第6染色体, 覆盖范围分别为6.16 cM和27.48 cM。借助比较基因组学策略, 在第3染色体“一致性”QTL区间内筛选出4个抗病位置候选基因。该研究结果为确定和克隆抗病主效基因提供了基础。     

玉米叶形相关性状的Meta-QTL及候选基因分析

叶长、叶宽、叶面积及叶夹角不仅影响玉米(Zea mays)光合效率, 也是株型的重要构成因素。通过对620个叶形QTL进行整合, 构建不同遗传背景下的叶形QTL整合图谱, 利用元分析发掘出22个叶长、22个叶宽、12个叶面积以及17个叶夹角mQTL; 进一步运用生物信息学手段, 确定44个与叶片发育密切相关的候选基因。分析发现, 仅有NAL7-like、YABBY6- like和GRF2等13个基因位于mQTL区间内, 而玉米中已克隆的KNOTTED1、AN3/GIF1、rgd1/lbl1、mwp1及SRL2-like、HYL1-like和CYCB2;4-like等水稻(Oryza sativa)和拟南芥(Arabidopsis thaliana)叶形同源基因位于未被整合的QTL内; 对44个候选基因在叶片长、宽、厚发育过程中基部-末端、中央-边缘、远轴-近轴的调控机理进行归纳分析, 发现玉米中仅有少数几个候选基因被报道, 揭示了叶形发育的部分分子机理。因此, 对玉米叶形相关mQTL/QTL及基因进行全面深入的分析, 不仅有助于增加对其遗传结构的了解, 发掘更多候选基因, 阐明叶形发育和形成的分子机制, 还可为耐密理想株型的分子标记辅助选择提供依据。     

Meta-Analysis of Flowering-Related Traits and Mining of Candidate Genes in Maize

Maize flowering is an important agronomic character, which is controlled by quantitative trait loci (QTL). Over the years, a large number of flowering-related QTL have been found in maize and exist in public databases. However, combining these data, re-analyzing and mining candidate loci and fine mapping of flowering-related traits to reduce confidence intervals has become a hot issue in maize. In this study, the QTL of 6 important agronomic traits of maize flowering were collected from 15 published articles, including flowering period (DA), Days to tasseling (DTT), Days to silking (DS), Days to pollen shedding (DTP), anthesis-silking interval (ASI) and the photosensitive (PS). Through meta-analysis, 622 QTL were integrated into 26 meta-QTLs (MQTL). Finally, the candidate genes related to maize flowering (Gene IDs: ZM00001D005791, ZM00001D019045, ZM00001D050697, ZM00001D011139) were identified by Gene Ontology (GO) enrichment and hierarchical cluster analysis of expression profile. Based on the results of this study, the genetic characteristics of maize flowering traits will be further analyzed, which is of great significance to guide the improvement of important agronomic characters and improve the efficiency of breeding.     

Meta-analysis of QTL involved in silage quality of maize and comparison with the position of candidate genes

A meta-analysis of quantitative trait loci (QTL) associated with plant digestibility and cell wall composition in maize was carried out using results from 11 different mapping experiments. Statistical methods implemented in “MetaQTL” software were used to build a consensus map, project QTL positions and perform meta-analysis. Fifty-nine QTL for traits associated with digestibility and 150 QTL for traits associated with cell wall composition were included in the analysis. We identified 26 and 42 metaQTL for digestibility and cell wall composition traits, respectively. Fifteen metaQTL with confidence interval (CI) smaller than 10 cM were identified. As expected from trait correlations, 42% of metaQTL for digestibility displayed overlapping CIs with metaQTL for cell wall composition traits. Coincidences were particularly strong on chromosomes 1 and 3. In a second step, 356 genes selected from the MAIZEWALL database as candidates for the cell wall biosynthesis pathway were positioned on our consensus map. Colocalizations between candidate genes and metaQTL positions appeared globally significant based on χ² tests. This study contributed in identifying key chromosomal regions involved in silage quality and potentially associated genes for most of these regions. These genes deserve further investigation, in particular through association mapping.     

Meta-analysis combined with syntenic metaQTL mining dissects candidate loci for maize yield

Yield potential and stability improvement with the goal of ensuring global food security is an important priority. Yield has a quantitative nature and is controlled by quantitative trait loci (QTL) and environmental factors. An increasingly large number of maize yield QTL have been identified, and how to integrate and re-analyze them is challenging. To this end, we tried to combine QTL meta-analysis with homology-based cloning techniques to dissect candidate loci/genes for maize yield. We first collected maize yield-related QTL from public resources. Then, 351 collected QTL were iteratively projected and meta-analyzed to obtain metaQTL (MQTL). A total of 54 MQTL were identified and tended to cluster in the maize genome. Seven MQTL containing ten maize orthologs of rice yield genes were dissected and temporarily termed syntenic MQTL. Maize orthologs of three functionally-characterized rice yield genes, GIF1, WFP/IPA1, and DEP1, were specially selected to undergo phylogenetic, proliferation, and selective pattern analysis. The results showed that maize orthologs were closely related to rice yield genes and subjected to mixed selective pressures, including positive selection during selective sweeps. The power of the combined techniques reported here was primarily validated not only by the congruency of MQTL and recently reported maize yield QTL but also by mined syntenic MQTL containing the well-characterized Miniature1 (Mn1) gene for maize kernel size and weight determination. Maize MQTL, especially syntenic MQTL regions, could serve not only for QTL fine-mapping and cloning but also for the marker-assisted selection breeding program. The maize yield candidate loci/genes presented here also deserve further investigation and will provide clues to the molecular bases of grain yield. Additionally, the combined technique described here will find its way into further quantitative trait research.     

Exploration and mapping of microsatellite markers from subtracted drought stress ESTs in Sorghum bicolor (L.) Moench

Molecular variation within defined genes underlying specific biochemical or physiological functions provide candidate gene-based markers which show very close association with the trait of interest and thus should enable to design superior genotypes. We explored microsatellite loci in a total of 9,892 subtracted drought stress ESTs of sorghum (6,295 after flowering ESTs and 3,597 before flowering ESTs) available in the NCBI dbEST database. Analysis of 9,892 ESTs identified 221 non-redundant ESTs with SSRs, from which 109 functional SSRs were developed. Among them 62 EST-microsatellites (56.8%) exhibited polymorphism for at least one sorghum genotype among the five tested and yielded a total of 161 alleles, with an average of 2.59 alleles per marker. We present a microsatellite linkage map using a RIL population derived from the cross 296B and IS18551. The map contains 128 microsatellite loci distributed over 15 linkage groups, and spanning a genetic distance of 1,074.5 cM. The map includes map positions of 28 drought EST-microsatellites developed and seven new genomic-SSRs, and are distributed throughout the map. The developed EST markers include genes coding for important regulatory proteins and functional proteins that are involved in stress related metabolism. The drought EST-microsatellites will have applications in functional diversity studies, association studies, QTL studies for drought, and other agronomically important traits in sorghum, and comparative genomics studies between sorghum and other members of the Poaceae family.     

Genetic and physical mapping of flowering time loci in canola (Brassica napus L.)

We identified quantitative trait loci (QTL) underlying variation for flowering time in a doubled haploid (DH) population of vernalisation—responsive canola (Brassica napus L.) cultivars Skipton and Ag-Spectrum and aligned them with physical map positions of predicted flowering genes from the Brassica rapa genome. Significant genetic variation in flowering time and response to vernalisation were observed among the DH lines from Skipton/Ag-Spectrum. A molecular linkage map was generated comprising 674 simple sequence repeat, sequence-related amplified polymorphism, sequence characterised amplified region, Diversity Array Technology, and candidate gene based markers loci. QTL analysis indicated that flowering time is a complex trait and is controlled by at least 20 loci, localised on ten different chromosomes. These loci each accounted for between 2.4 and 28.6 % of the total genotypic variation for first flowering and response to vernalisation. However, identification of consistent QTL was found to be dependant upon growing environments. We compared the locations of QTL with the physical positions of predicted flowering time genes located on the sequenced genome of B. rapa. Some QTL associated with flowering time on A02, A03, A07, and C06 may represent homologues of known flowering time genes in Arabidopsis; VERNALISATION INSENSITIVE 3, APETALA1, CAULIFLOWER, FLOWERING LOCUS C, FLOWERING LOCUS T, CURLY LEAF, SHORT VEGETATIVE PHASE, GA3 OXIDASE, and LEAFY. Identification of the chromosomal location and effect of the genes influencing flowering time may hasten the development of canola varieties having an optimal time for flowering in target environments such as for low rainfall areas, via marker-assisted selection.     

A gene regulatory network model for floral transition of the shoot apex in maize and its dynamic modeling

The transition from the vegetative to reproductive development is a critical event in the plant life cycle. The accurate prediction of flowering time in elite germplasm is important for decisions in maize breeding programs and best agronomic practices. The understanding of the genetic control of flowering time in maize has significantly advanced in the past decade. Through comparative genomics, mutant analysis, genetic analysis and QTL cloning, and transgenic approaches, more than 30 flowering time candidate genes in maize have been revealed and the relationships among these genes have been partially uncovered. Based on the knowledge of the flowering time candidate genes, a conceptual gene regulatory network model for the genetic control of flowering time in maize is proposed. To demonstrate the potential of the proposed gene regulatory network model, a first attempt was made to develop a dynamic gene network model to predict flowering time of maize genotypes varying for specific genes. The dynamic gene network model is composed of four genes and was built on the basis of gene expression dynamics of the two late flowering id1 and dlf1 mutants, the early flowering landrace Gaspe Flint and the temperate inbred B73. The model was evaluated against the phenotypic data of the id1 dlf1 double mutant and the ZMM4 overexpressed transgenic lines. The model provides a working example that leverages knowledge from model organisms for the utilization of maize genomic information to predict a whole plant trait phenotype, flowering time, of maize genotypes.     

Combined genetic and physiological analysis of a locus contributing to quantitative variation

The natural variation of many traits is controlled by multiple genes, individually referred to as quantitative trait loci (QTL), that interact with the environment to determine the ultimate phenotype of any individual. A QTL has yet to be described molecularly, in part because strategies to systematically identify them are underdeveloped and because the subtle nature of QTLs prevents the application of standard methods of gene identification. Therefore, it will be necessary to develop a systematic approach(es) for the identification of QTLs based upon the numerous positional data now being accumulated through molecular marker analyses. We have characterized a QTL by the following three-step approach: (1) identification of a QTL in complex populations, (2) isolation and genetic mapping of this QTL in near-isogenic lines, and (3) identification of a candidate gene using map position and physiological criteria. Using this approach we have characterized a plant height QTL in maize that maps to chromosome 9 near the centromere. Both map position and physiological criteria suggest the gibberillin biosynthesis gene dwarf3 as a candidate gene for this QTL.     

Quantitative genetic analysis of flowering time in tomato.

Artificial selection of cultivated tomato (Solanum lycopersicum L.) has resulted in the generation of early-flowering, day-length-insensitive cultivars, despite its close relationship to other Solanum species that need more time and specific photoperiods to flower. To investigate the genetic mechanisms controlling flowering time in tomato and related species, we performed a quantitative trait locus (QTL) analysis for flowering time in an F2 mapping population derived from S. lycopersicum and its late-flowering wild relative S. chmielewskii. Flowering time was scored as the number of days from sowing to the opening of the first flower (days to flowering), and as the number of leaves under the first inflorescence (leaf number). QTL analyses detected 2 QTLs affecting days to flowering, which explained 55.3% of the total phenotypic variance, and 6 QTLs for leaf number, accounting for 66.7% of the corresponding phenotypic variance. Four of the leaf number QTLs had not previously been detected for this trait in tomato. Colocation of some QTLs with flowering-time genes included in the genetic map suggests PHYB2, FALSIFLORA, and a tomato FLC-like sequence as candidate genes that might have been targets of selection during the domestication of tomato.     

Detection of QTL for flowering time in multiple families of elite maize

Flowering time is a fundamental quantitative trait in maize that has played a key role in the postdomestication process and the adaptation to a wide range of climatic conditions. Flowering time has been intensively studied and recent QTL mapping results based on diverse founders suggest that the genetic architecture underlying this trait is mainly based on numerous small-effect QTL. Here, we used a population of 684 progenies from five connected families to investigate the genetic architecture of flowering time in elite maize. We used a joint analysis and identified nine main effect QTL explaining approximately 50?% of the genotypic variation of the trait. The QTL effects were small compared with the observed phenotypic variation and showed strong differences between families. We detected no epistasis with the genetic background but four digenic epistatic interactions in a full 2-dimensional genome scan. Our results suggest that flowering time in elite maize is mainly controlled by main effect QTL with rather small effects but that epistasis may also contribute to the genetic architecture of the trait.     

Effect of genotype and environment on branching in weedy green millet (Setaria viridis) and domesticated foxtail millet (Setaria italica) (Poaceae)

Many domesticated crops are derived from species whose life history includes weedy characteristics, such as the ability to vary branching patterns in response to environmental conditions. However, domesticated crop plants are characterized by less variable plant architecture, as well as by a general reduction in vegetative branching compared to their progenitor species. Here we examine weedy green millet and its domesticate foxtail millet that differ in the number of tillers (basal branches) and axillary branches along each tiller. Branch number in F(2:3) progeny of a cross between the two species varies with genotype, planting density, and other environmental variables, with significant genotype-environment interactions (GEI). This is shown by a complex pattern of reaction norms and by variation in the pattern of significant quantitative trait loci (QTL) amongst trials. Individual and joint analyses of high and low density trials indicate that most QTL have significant GEI. Dominance and epistasis also explain some variation in branching. Likely candidate genes underlying the QTL (based on map position and phenotypic effect) include teosinte branched1 and barren stalk1. Phytochrome B, which has been found to affect response to shading in other plants, explains little or no variation. Much variation in branching is explained by QTL that do not have obvious candidate genes from maize or rice.     

Mapping quantitative trait loci using naturally occurring genetic variance among commercial inbred lines of maize (Zea mays L.)

Many commercial inbred lines are available in crops. A large amount of genetic variation is preserved among these lines. The genealogical history of the inbred lines is usually well documented. However, quantitative trait loci (QTL) responsible for the genetic variances among the lines are largely unexplored due to lack of statistical methods. In this study, we show that the pedigree information of the lines along with the trait values and marker information can be used to map QTL without the need of further crossing experiments. We develop a Monte Carlo method to estimate locus-specific identity-by-descent (IBD) matrices. These IBD matrices are further incorporated into a mixed-model equation for variance component analysis. QTL variance is estimated and tested at every putative position of the genome. The actual QTL are detected by scanning the entire genome. Applying this new method to a well-documented pedigree of maize (Zea mays L.) that consists of 404 inbred lines, we mapped eight QTL for the maize male flowering trait, growing degree day heat units to pollen shedding (GDUSHD). These detected QTL contributed >80% of the variance observed among the inbred lines. The QTL were then used to evaluate all the inbred lines using the best linear unbiased prediction (BLUP) technique. Superior lines were selected according to the estimated QTL allelic values, a technique called marker-assisted selection (MAS). The MAS procedure implemented via BLUP may be routinely used by breeders to select superior lines and line combinations for development of new cultivars.     

水稻资源开花期耐热性的全基因组关联分析

水稻在开花期对高温非常敏感,挖掘耐热种质并解析耐热性的遗传机制,有助于水稻的耐热性遗传改良。本研究选取205份国内外种质资源,在抽穗开花期对遇高温的稻穗进行标记,以高温下标记穗的结实率作为耐热指标,结合高密度SNP标记进行全基因组关联分析并初步预测候选基因。结果表明:不同水稻种质的耐热性差异明显,高温下的结实率最低为19.0%,平均值为64.0%,中位值为65.9%,最高值为86.6%,其中06-32、剪刀齐、娄早籼5号等17份种质的耐热性较强;全基因组关联分析共筛选到130个与耐热性显著关联的SNP标记,并鉴定到18个耐热QTL,其中6个QTL与已报道的耐热相关QTL共定位;qHT4-6与耐热性的关联度最高,根据该区间lead SNP的单倍型分类,G单倍型材料的开花期耐热性显著强于A单倍型材料,该区间附近有7个基因可能受高温调控。     

玉米和水稻重要性状QTL的比较研究

在构建玉米分子标记连锁图和对重要性状进行QTL定位的基础上,以玉米和水稻的分子标记比较图谱为桥梁,分析了控制玉米和水稻F2：3群体重要农艺和产量性状QTL的共线性关系。研究结果表明：在玉米和水稻共线性的染色体区段,控制玉米株高、行数和行粒数的QTL与控制水稻株高、单株有效穗和每穗实粒数的QTL存在广泛的对应关系;在已定位的影响玉米株高等5个性状的45个QTL中,有16个与水稻“汕优63”群体中5个相同或相似性状所定位的38个QTL中的12个具有共线性关系。这一结果为利用水稻的基因组数据来定位、分离和克隆玉米重要性状的QTL提供了有益信息。同时发现,控制水稻某一个性状的QTL常常与控制玉米同一性状的两个QTL相对应,这一结果为玉米染色体是由水稻染色体加倍而来的理论假设提供了支持。研究还发现,不管是玉米还是水稻在染色体上都存在QTL的富集区域,而这些富集区域常常存在于相同的共线性区域,暗示着玉米和水稻控制相同或相似性状的QTL可能有着相同的起源。基于性状的比较基因组研究不但有助于新基因或QTL的发现、克隆和利用,同时还有助于研究不同物种间染色体的演变和进化规律。     

Quantitative trait loci affecting amylose,amylopectin and starch content in maize recombinant inbred lines

The loci explaining the variability of quantitative traits related to starch content and composition (amylose, amylopectin and water soluble fraction) were searched for in maize kernels. Multifactorial genetic methods were used to detect and locate QTLs (quantitative trait loci) on a genetic map consisting mainly of RFLP markers for genes with known function. The genetic material was recombinant inbred lines originating from parents differing in starch structure (dent vs. flint). Kernels were harvested from field grown plants for two successive years and under two pollination systems. Main effect and epistasis QTLs were detected using two methods, composite interval mapping (MQTL) and ANOVA. Despite large year-to-year differences, physiologically meaningful co-locations were observed between trait QTLs. Moreover, the number of expressed sequences on our map allowed the search for co-locations between QTLs and genes involved in carbohydrate metabolism. The main co-location was between an amylose QTL and Shrunken 2 (SH2) locus, on chromosome 3 (SH2 encoding for the large subunit of ADPglucose pyrophosphorylase). The importance of this locus as a candidate gene for a starch QTL is in agreement with previous studies based either on QTL co-locations or on revertant analysis. Other co-locations were observed between amylose and amylopectin QTLs and the two loci of IVR1 invertase genes on chromosomes 2 and 10. Further comparison with previously detected QTLs for carbohydrate metabolism in maize leaves showed consistent co-location in map regions devoid of candidate genes, such as near chromosome 1S telomere. The possible contribution of regulatory genes in this region is discussed.     

Rapid establishment of introgression lines using cytoplasmic male sterility and a restorer gene in Oryza sativa cv. Nipponbare

Quantitative trait locus (QTL) analyses have greatly enhanced our understanding of complex traits in rice (Oryza sativa). In parallel, the development of introgression lines has provided a powerful tool for elucidation of complicated genetic networks and identification of QTL. We recently developed a biotron breeding system that allows rapid indoor cultivation of rice plants. The system, however, has two relatively weak points in its application to marker-assisted breeding in rice: first, variation in generation times among cultivars; second, the low number of seeds produced by crosses. To compensate for these weaknesses, we propose utilizing cytoplasmic male sterility (CMS) and restorer (Rf) lines with a cv. Nipponbare genetic background. Through use of the Nipponbare genetic background, rice generation times of 2 months can be achieved regardless of any differences in the genetic background of the donor rice plant. This CMS–Rf system confers a high yield of hybrid seeds, avoids the need for emasculation and precludes accidental crosses. Our results demonstrate that this new methodology can markedly accelerate many different aspects of rice research, especially in functional genomics. The combination of biotron breeding system, early flowering habit and CMS will be of great value for screening candidate genes associated with QTL and for introducing useful QTL into elite cultivars.