中国主要花生品种品质性状关联分析

以来自全国的136个花生主要育成品种及育种骨干亲本作为供试群体,测定其蛋白质含量、脂肪及油酸含量等性状。选用64个均匀分布在复合遗传图谱不同遗传连锁群上多态性较好的SSR标记进行多位点扫描。通过标记的基因型值,利用Structure软件对群体进行结构划分并得到结构划分的矫正Q值,采用Tassel 软件中GLM（Q）方法将供试花生品种连续3年的品质性状与SSR标记进行关联分析。结果表明：①依据基因型数据对材料群的结构划分,供试群体最终可被划分为5个亚群,依据群体特点和结构分析可以表明供试的花生材料是适合关联分析的;②通过关联分析,共发掘与2010年、2011年、2012年品质性状显著关联的SSR位点分别有18个、31个、26个;③通过综合分析,能够连续3年重复检测出与品质性状关联的SSR位点4个,共计等位变异位点40个。     

陆地棉主要产量相关性状的SSR标记关联分析

高产优质育种是我国棉花育种的主要目标。寻找与目标性状关联的分子标记,可克服常规育种的盲目性,提高分子标记辅助选择育种的准确性。本研究对118份陆地棉种质资源的衣分、单铃重、单株铃数及子指等4个产量相关性状进行2年2点的表型鉴定,并利用覆盖全基因组的、有多态性的214对SSR标记进行标记与性状的关联分析。结果表明:118份材料的4个产量相关性状表型变异丰富,平均变异系数的变幅在6.1%~19.1%之间,且在各环境中表现较为稳定;基因型分析表明,214对标记共检测到460个等位变异,基因多样性指数平均为0.5151,PIC值平均为0.4587,表明该批标记具有较多的等位变异数和较高的基因多样性;群体结构分析表明该批材料可分为4个亚群,且各类群中材料与地理来源无对应关系;关联分析结果显示,在显著条件下(-log10P1.3,P0.05),共有39个标记位点能够在2个及2个以上的环境中同时检测到,其中有4个标记位点同时与2个以上性状相关联,进一步比较发现,有7个位点与前人研究结果一致,其余32个位点为新发现的位点。研究结果可为陆地棉产量性状遗传改良的分子标记辅助选择提供理论依据。     

小麦全基因组抗赤霉病QTL关联位点特异性SSR标记的筛选、等位变异及效应解析

赤霉病是小麦主要的流行病害之一。借助标记辅助选择将不同数量性状基因座（quantitative trait loci，QTL）聚合是防治赤霉病有效且环保的方法，可以从源头上控制赤霉病并降低籽粒中毒素含量。抗赤霉病QTL在小麦全基因组均有分布，但除了Fhb1、Fhb2等少数位点有比较可靠的鉴别标记，绝大部分位点缺乏有效的位点特异性鉴别标记。简单重复序列（simple sequence repeat，SSR）标记多态性丰富，可以区分自然群体中不同等位变异，方便用于标记辅助育种。基于此，搜集了不同文献中报道的与赤霉病关联的SSR标记386个，并用这些标记构建全基因组赤霉病抗性QTL一致性图谱，接着对这些关联标记进行拷贝数分析，进而选择位点内的单拷贝SSR标记，将这些单拷贝标记在156个品种组成的自然群体中进行扩增，并与三季大田和三季温室环境下赤霉病抗性进行关联，筛选与赤霉病抗性关联的单拷贝SSR标记，明确这些标记在自然群体中的有效等位变异和效应。结果表明，共8个单拷贝SSR标记至少在两季试验中与表型显著关联(P<0.05)，涉及2B、2D、3B、5A、5B、6A、6D、7A染色体，有5个单拷贝标记位点存在有效等位变异。中国地方品种和日本品种携带更多的有利变异，且有利等位变异数目越多的品种赤霉病抗性越好。研究分析的QTL位点及其关联的单拷贝SSR标记可用于赤霉病抗病育种，有利于提高品种赤霉病抗性水平和育种效率。     

烤烟SSR标记多样性及与致香物质的关联分析

了解烤烟品种的遗传多样性,寻找与烤烟致香物质含量关联的分子标记,挖掘高致香物质含量的优异等位变异与种质,对香气品质分子标记辅助育种具有重要意义。本研究检测了山东和四川2个生态区60份烤烟种质中76种致香物质的含量;筛选覆盖全基因组的1914个SSR标记,利用得到的390对多态性引物扩增供试群体。用基于Nei's(1983)遗传距离的邻接法(Neighor-joining,NJ)进行聚类分析。在分析群体结构的基础上,利用混合线性模型进行关联分析,并进一步发掘极显著关联标记的优异等位变异和种质。结果检测到928个等位变异,平均每个位点2.38个等位变异,变化范围为2~5个。PIC值的变化范围分别为0.141~0.733,平均值0.332。这说明供试群体遗传多样性较丰富。聚类分析将该群体划分为2个亚群,划分结果体现了烤烟品种间的亲缘关系;群体结构分析与聚类结果基本一致。关联分析结果显示:共有56个SSR标记位点与41种致香物质同时在2个生态区显著关联(P0.05)。共5个标记与6个性状在2个生态区极显著关联(P0.01),6种致香物质为草酸、肉豆蔻酸、2,4-庚二烯醛、芳樟醇、a-松油醇和gamma-壬内酯,关联标记分别为PT50662、PT60191、PT52263、PT60597、PT60597和PT52722。关联位点表型解释率为12.54%~42.20%。进一步分析发掘了14种致香物质的优异等位变异,并筛选出含增效等位变异较多的种质:净叶黄、抗9201、单育二号、满屋香、金星6007、秦烟95等。这对香气品质分子标记辅助选择育种以及亲本材料选配等奠定了基础。     

绿豆5个产量相关性状的QTL分析

利用绿豆(Vigna radiata)品种苏绿16-10和潍绿11杂交构建的F₂和F₃群体发掘调控绿豆产量相关性状的遗传位点。同时对绿豆产量相关性状进行表型鉴定和相关性分析, 并利用构建的遗传连锁图谱进行QTL定位。结果表明, 单株产量与单株荚数、单荚粒数、百粒重和分枝数均呈正相关。单株产量与单株荚数的相关性最高, 这2个性状在F₂和F₃群体中的相关系数分别为0.950和0.914。在F₂群体中, 共检测到8个与产量性状相关的QTL位点, 其中与单株荚数、单荚粒数和单株产量相关的QTL位点各1个, 分别解释11.09% (qNPP3)、17.93% (qNSP3)和14.18% (qYP3)的表型变异; 2个与分枝数相关的QTL位点qBMS3和qBMS11, 分别解释18.51%和7.06%的表型变异; 3个与百粒重相关的QTL位点qHSW3、qHSW7和qHSW10, 分别解释5.33%、46.07%和4.24%的表型变异。在F₃群体中, qNSP3和qHSW7再次被检测到, 表明这2个QTLs有较好的遗传稳定性。同时, 开发了1个与百粒重主效QTL qHSW7紧密连锁的InDel标记R7-13.4, 并利用自然群体对该分子标记辅助筛选的有效性进行了验证。研究结果可为绿豆产量相关性状基因的定位、克隆及分子标记辅助育种提供参考。     

辣椒疫病抗性关联分析及优异等位变异挖掘

基于SSR标记技术,对194份辣椒核心种质疫病抗性进行关联分析。58对SSR标记共检测到178个等位变异,Shannon指数平均值为0.6732,多态信息量(PIC)平均值为0.3859,基因多样性平均值为0.4400,说明供试材料具有较高的遗传多样性。群体结构分析将194份材料划分为两个亚群,亚群1的疫病抗性水平高于亚群2。关联分析结果表明,共有12个SSR位点与辣椒疫病病情指数显著关联(P0.05),表型贡献率为2.98%～16.05%,15个SSR位点与辣椒病株率显著关联,表型贡献率为2.95%～21.29%;表型贡献率最大的位点为CM0005,位于第7号染色体,其余位点分布于第2、3、5、7、8、9和11号染色体,与已有报道有所差异,说明供试种质可能含有新的疫病抗性基因。根据关联位点表型效应值,发掘出CM0005c、ge35-141pmH0135Cd和Hpms1-139c等12个疫病抗性优异等位变异及种质171、55、161、65、132、128、91、106、125、127、169等优良抗性载体材料。本研究结果为辣椒疫病抗性基因发掘和分子标记辅助选择抗性育种提供了理论指导和材料基础。     

陆地棉纤维品质性状关联分析及优异等位基因挖掘

本研究检测了214个陆地棉材料在多环境下的纤维品质指标(上半部平均长度、断裂比强度、马克隆值、伸长率和整齐度),选用在棉花基因组上均匀分布多态性较好的259个SSR标记对供试群体进行基因型检测,利用Tassel软件中的GLM(Q)方法挖掘与纤维品质指标相关的QTLs,依据表型效应值鉴别优异等位变异位点及典型材料。结果显示:同一纤维品质性状在3个地点2~3年内变化趋势相对稳定,纤维上半部平均长度、断裂比强度和整齐度三者之间呈正相关(P<0.01),纤维上半部平均长度/断裂比强度均和马克隆值/伸长率负相关。259个SSR标记共检测到309个等位基因,涉及774个基因型,多态性信息含量(PIC,polymorphic information content)平均为0.2688,基因多样性指数平均为0.2239。按照基因型数据可将该群体划分为2个亚群。通过关联分析获得与纤维品质相关的等位变异位点134个(P<0.01),在3个及以上环境中均可检测到的位点有30个,有3个位点(NAU6177、DPL0886、NAU3607)在7个环境中分别与断裂比强度、马克隆值、伸长率显著关联(P<0.01),最高表型变异解释率分别为11.14%、5.74%和13.99%。31个位点同时与2个及以上纤维品质指标相关,其中,NAU 6177与5个纤维品质指标均显著关联(P<0.01)。与已发表结果比对,17个QTL已被报道与纤维品质性状相关,10个QTL与前人关联指标相同。分析多环境纤维品质关联位点的表型效应,获得72个等位变异位点,5份携带优异等位基因载体材料。本研究在多环境下挖掘与陆地棉纤维品质指标关联的分子标记,同时鉴别携带优异等位变异基因的典型载体材料,为棉花纤维品质分子标记辅助选择及目标基因定位提供有益信息。     

小麦骨干亲本阿夫衍生系赤霉病抗性的关联分析

赤霉病是影响小麦产量和品质的重要病害,发掘抗性遗传变异、培育抗病品种是防治小麦赤霉病最安全、经济的根本途径。本研究在5个环境中对阿夫及其264份衍生品种(系)进行了赤霉病抗扩展性鉴定,利用分布于19条染色体上的52个标记进行遗传多样性分析、群体结构分析以及关联分析,共检测到19个与赤霉病抗性相关的位点。其中,分布在2B、2D、3A、3B和5A染色体上的5个位点能够在至少5个环境中的2个且在5年平均值中检测到。3B上的赤霉病抗性位点Xgwm493与Fhb1连锁;5A上的赤霉病抗性位点Xbarc117与Fhb5紧密连锁。标记位点的等位变异表型效应值检测结果显示11个等位变异与赤霉病抗性关联,其中3个等位变异具有减效效应,减效效应值最大的是Xgwm493-180;7个等位变异具有增效效应,增效效应值最大的是Xbarc117-225,1个等位变异为无效等位变异。同时发现材料的赤霉病病小穗数与其携带优异等位变异数目呈线性负相关。     

豌豆种质表型性状SSR标记关联分析

关联分析是以连锁不平衡原理为基础,鉴定某一群体内表型性状与遗传标记或候选基因间关系的遗传分析方法。本研究利用59个多态性SSR标记,对192份豌豆种质进行全基因组扫描,以分析SSR位点遗传多样性,寻找其连锁不平衡位点;采用TASSEL软件的一般线性模型,利用59个SSR标记对19个形态性状进行关联分析。结果显示SSR位点间有较高的多态性和一定程度的连锁不平衡,共检测出32个SSR标记位点与14个表形性状相关联,一些SSR标记与2个或多个形态性状相关联。     

小麦耐低磷相关性状的全基因组关联分析

通过对小麦耐低磷相关性状进行全基因组关联分析(GWAS,genome-wide association study),挖掘与小麦耐低磷性显著相关的单核苷酸多态性标记(SNP,single nucleotide polymorphism)位点及候选基因,为小麦耐低磷性状的遗传基础和分子机制研究提供理论参考。本试验以198份黄淮麦区小麦品种(系)为试验材料,设置低磷和正常磷营养液水培试验,利用小麦35K芯片对分布于小麦全基因组的11896个SNP,采用Q+K关联模型对小麦耐低磷性相关性状进行关联分析。结果表明,小麦耐低磷性状表现出广泛的表型变异,变异系数为15.65%~26.59%,多态性信息含量(PIC,polymorphic information content)为0.095~0.500。群体结构分析表明,试验所用自然群体可分为2个亚群,GWAS共检测到67个与小麦耐低磷相关性状显著关联的SNP位点(P≤0.001),这些位点分布在除3A、3B和3D以外的18条染色体上,单个SNP位点可解释5.826%~9.552%的表型变异。在这些显著位点中有4个SNP位点同时关联到了2个不同的耐低磷性状。对67个SNP位点进行发掘,筛选到7个可能与小麦耐低磷性有关的候选基因。TraesCS6A02G001000和TraesCS6A02G001100在锌指合成中有重要作用;TraesCS6A02G118100可能为低磷胁迫诱导基因;TraesCS5D02G536400、TraesCS1B02G154200和TraesCS5D02G536500与低磷胁迫相关酶类基因家族有关;TraesCS1D02G231200与植物DUF 538结构域蛋白有关,是植物胁迫相关调控蛋白候选基因。     

Diversity characterization and association analysis of agronomic traits in a Chinese peanut (Arachis hypogaea L.) mini-core collection

Association mapping is a powerful approach for exploring the molecular basis of phenotypic variations in plants.A peanut(Arachis hypogaea L.)mini-core collection in China comprising 298 accessions was genotyped using 109 simple sequence repeat(SSR)markers,which identified 554 SSR alleles and phenotyped for 15 agronomic traits in three different environments,exhibiting abundant genetic and phenotypic diversity within the panel.A model-based structure analysis assigned all accessions to three groups.Most of the accessions had the relative kinship of less than 0.05,indicating that there were no or weak relationships between accessions of the mini-core collection.For 15 agronomic traits in the peanut panel,generally the Q t K model exhibited the best performance to eliminate the false associated positives compared to the Q model and the general linear model-simple model.In total,89SSR alleles were identified to be associated with 15 agronomic traits of three environments by the Q t K model-based association analysis.Of these,eight alleles were repeatedly detected in two or three environments,and 15 alleles were commonly detected to be associated with multiple agronomic traits.Simple sequence repeat allelic effects confirmed significant differences between different genotypes of these repeatedly detected markers.Our results demonstrate the great potential of integrating the association analysis and marker-assisted breeding by utilizing the peanut mini-core collection.     

Diversity characterization and association analysis of agronomic traits in a Chinese peanut （Arachis hypogaea L.） mini-core collection

Association mapping is a powerful approach for exploring the molecular basis of phenotypic variations in plants. A peanut （Arachis hypogaea L.） mini-core collection in China comprising 298 accessions was genotyped using lo9 simple sequence repeat （SSR） markers, which identified 554 SSR alleles and phenotyped for 15 agronomic traits in three different environments, exhibiting abundant genetic and phenotypic diversity within the panel. A model-based structure analysis assigned all accessions to three groups. Most of the accessions had the relative kinship of less than o.05, indicating that there were no or weak relationships between accessions of the mini- core collection. For 15 agronomic traits in the peanut panel, generally the Q ＋ K model exhibited the best performance to eliminate the false associated positives compared to the Q model and the general linear model-simple model. In total, 89 SSR alleles were identified to be associated with 15 agronomic traits of three environments by the Q＋K model-based association analysis. Of these, eight alleles were repeatedly detected in two or three environments, and 15 alleles were commonly detected to be associated with multiple agronomic traits. Simple sequence repeat allelic effects confirmed significant differences between different genotypes of these repeatedly detected markers. Our results demonstrate the great potential of integrating the association analysis and marker-assisted breeding by utilizing the peanut mini-core collection.     

Genomic regions underlying agronomic traits in linseed （Linum usitatissimum L.） as revealed by association mapping

The extreme climate of the Canadian Prairies poses a major chal enge to improve yield. Although it is possible to breed for yield per se, focusing on yield-related traits could be advantageous because of their simpler genetic architecture. The Canadian flax core col ection of 390 accessions was genotyped with 464 simple sequence repeat markers, and phenotypic data for nine agronomic traits including yield, bol s per area, 1,000 seed weight, seeds per bol , start of flowering, end of flowering, plant height, plant branching, and lodging col ected from up to eight environments was used for association mapping. Based on a mixed model （principal component analysis （PCA） t kinship matrix （K））, 12 significant marker-trait associations for six agronomic traits were identi-fied. Most of the associations were stable across environments as revealed by multivariate analyses. Statistical simulation for five markers associated with 1000 seed weight indicated that the favorable al eles have additive effects. None of the modern cultivars carried the five favorable al eles and the maximum number of four observed in any accessions was mostly in＆amp;nbsp;breeding lines. Our results confirmed the complex genetic architecture of yield-related traits and the inherent difficulties associated with their identification while il ustrating the potential for improvement through marker-assisted selection.     

Genetic analysis of maize germplasm in the Korean Genebank and association with agronomic traits and simple sequence repeat markers

We assessed genetic and phenotypic variation in 105 maize germplasm accessions from RDA-Genebank of Korea and performed association analyses for 11 agronomical traits and 100 simple sequence repeats (SSR). Genetic diversity (GD) analysis revealed a total of 1104 alleles at the 100 SSR loci. The average number of alleles per locus was 11.0. The average GD and polymorphic information content values were 0.73 and 0.70, respectively. The average major allele frequency was 0.41. Population structure analysis indicated that these maize accessions comprised two major groups and one admixed group based on a membership probability threshold of 0.80. The two major groups contained 35 and 46 maize accessions. A mixed linear model of association analysis revealed five marker-trait associations with a significance level of P?≤?0.01 involving five SSR markers. A general linear model showed 72 marker-trait associations involving 42 SSR markers. We confirmed the presence in the general linear model associations of the five significant marker-trait associations (SMTAs) identified in the mixed linear model. For these SMTAs, two loci were associated with stem diameter and one locus each was associated with ear row number, leaf width, and leaf length. These results should prove useful for breeding new inbred lines by selecting parental lines using molecular markers and will help to preserve maize genetic resources in Korea.     

Genomic regions for yield and yield parameters in Chinese winter wheat (Triticum aestivum L.) genotypes tested under varying environments correspond to QTL in widely different wheat materials

Field trials with a population of 108 doubled haploid (DH) lines of bread wheat (Triticum aestivum L.) derived from a cross between the Chinese winter wheat cultivars CA9613 and H1488 were carried out at Beijing (China) in 2000/2001 and 2001/2002. In addition, a field trial and a pot experiment were carried out at the experimental field stations of Giessen University (Germany) in the vegetation periods 2004/2005 and 2006/2007. Phenotypic data for major agronomic yield-related traits, i.e. grain weight per ear (GWE), grain number per ear (GNE), plant height and thousand-grain weight (TGW), were recorded in all experiments. In addition, biomass weight per tiller and ear weight were evaluated in the two field trials at Beijing. Based on the phenotypic data and a genetic map comprising 168 SSR markers, an analysis of quantitative trait loci (QTL) was carried out for yield and yield parameters using the composite interval mapping (CIM) approach. A total of 30 QTL were detected for these traits across four environments. Five of these QTL located on chromosomes 1A, 1B, 2B, 2D and 7D exhibited pleiotropic effects. Such pleiotropic gene loci will be very useful for understanding the homologous/homeologous relationships among QTL and designing an appropriate marker-assisted breeding programme including multi-trait selection in order to accumulate (“pyramide”) favorable alleles at different genetic loci.     

Association and Validation of Yield-Favored Alleles in Chinese Cultivars of Common Wheat (Triticumaestivum L.)

Common wheat is one of the most important crops in China, which is the largest producer in the world. A set of 230 cultivars was used to identify yield-related loci by association mapping. This set was tested for seven yield-related traits, viz. plant height (PH), spike length (SL), spikelet number per spike (SNPS), kernel number per spike (KNPS), thousand-kernel weight (TKW), kernel weight per spike (KWPS), and sterile spikelet number (SSN) per plant in four environments. A total of 106 simple sequence repeat (SSR) markers distributed on all 21 chromosomes were used to screen the set. Twenty-one and 19 of them were associated with KNPS and TKW, respectively. Association mapping detected 73 significant associations across 50 SSRs, and the phenotypic variation explained (R²) by the associations ranged from 1.54 to 23.93%. The associated loci were distributed on all chromosomes except 4A, 7A, and 7D. Significant and potentially new alleles were present on 8 chromosomes, namely1A, 1D, 2A, 2D, 3D, 4B, 5B, and 6B. Further analysis showed that genetic effects of associated loci were greatly influenced by association panels, and the R² of crucial loci were lower in modern cultivars than in the mini core collection, probably caused by strong selection in wheat breeding. In order to confirm the results of association analysis, yield-related favorable alleles Xgwm135-1A₁₃₈, Xgwm337-1D₁₈₆, Xgwm102-2D₁₄₄, and Xgwm132-6B₁₂₈ were evaluated in a double haploid (DH) population derived from Hanxuan10 xLumai14.These favorable alleles that were validated in various populations might be valuable in breeding for high-yield.     

Association between SSR markers and fibre traits in sea island cotton (<Emphasis Type="BoldItalic">Gossypium barbadense</Emphasis>) germplasm resources

Identification of molecular markers associated with fibre traits can accelerate cotton marker-assisted selection (MAS) programmes. In this study, Gossypium barbadense germplasm accessions with diverse origins (\(n = 123\)) were used to perform association analysis of fibre traits with 120 polymorphic simple sequence repeat (SSR) markers. In total, 120 polymorphic primer pairs amplified 258 loci with a mean of 2.15 loci per primer. Population structure analysis identified three main clusters for the accessions, which indicated agreement of genetic and predefined populations. Marker–trait associations (\(n= 58\)) were detected for 10 fibre traits with 26 SSR markers located on 15 chromosomes. The \(R^{2}\) (phenotypic variation explained) ranged from 3.19 to 15.21%. Two markers (NAU5465 and NAU3013) were found to be stably associated with boll number per plant (BNP) and fibre uniformity (UI), respectively. Four markers (BNL252, NAU3424, NAU3324 and CGR5202) associated with fibre quality traits preferentially clustered on the D8 chromosome, which was thus identified as an important candidate region for study molecular mechanisms underlying fibre quality and for use in breeding cotton cultivars for improving fibre quality. This study generated molecular data with a potential for better understanding of the genetic basis of the fibre traits and provided new markers for MAS in G. barbadense breeding programmes.     

Association mapping of agronomic traits on chromosome 2A of wheat

Association mapping is a method to test the association between molecular markers and quantitative trait loci (QTL) based on linkage disequilibrium (LD). In this study, the collection of 108 wheat germplasm accessions form China were evaluated for their plant heights, spike length, spikelets per spike, grains per spike, thousand kernel weight and spikelets density in 3 years at three locations. And they were genotyped with 85 SSR markers and 40 EST-SSR markers. The population structure was inferred on the basis of unlinked 48 SSR markers and 40 EST-SSR markers. The extent of LD on chromosome 2A was 2.3 cM. Association of 37 SSR loci on chromosomes 2A with six agronomic traits was analysed with a mixed linear model. A total of 14 SSR loci were significantly associated with agronomic traits. Some of the associated markers were located in the QTL region detected in previous linkage mapping analysis. Our results demonstrated that association mapping can enhance QTL information and achieves higher resolution with short LD extent.     

棉花耐盐相关种质资源遗传多样性分析

为了解我国棉花耐盐相关种质资源的遗传变异,利用88对SSR引物对23份棉花耐盐材料和24份盐敏感材料进行遗传多样性分析。88个SSR位点在47份材料中共检测出338个等位基因变异,平均每个位点有3.841个;其中耐盐材料中检测出333个,盐敏感材料中检测出312个。耐盐材料的位点多态信息含量(PIC)、每个位点的有效等位基因数(Ne)、基因型多样性(H′)分别为0.613、2.929和1.083,盐敏感材料的PIC、Ne、H′分别为0.605、2.883和1.071。耐盐材料和盐敏感材料的Jaccard相似性系数分别在0.530–0.979和0.525–0.878之间,遗传相似性系数总体平均值接近,但耐盐材料的变化幅度更大。用类平均法(UPGMA)聚类将47份材料分成3个类群。总体而言,大多数材料之间的遗传相似性系数较高,表明我国陆地棉耐盐相关种质资源遗传基础狭窄。本结果为棉花耐盐育种中亲本的选配和优势组合的预测以及耐盐资源的合理利用等提供了基础资料。