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植物基因相关SSR序列调控及位点多态性研究
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摘要
简单重复序列(Simple Sequence Repeat, SSR)作为一类短串联重复序列广泛分布于植物基因组。传统观点认为SSR序列倾向存在于植物基因组重复区域,但随着大量植物基因组及其表达序列的测定,发现SSR的分布情况比原先认识的要复杂得多,SSR序列在植物基因组中并非集中于基因组重复区域,而是更倾向分布在基因组单拷贝或低拷贝区域,尤其在基因上游调控区大量出现。出于对SSR序列属于基因组的“垃圾”DNA,并不具备重要生物学功能的片面认识,长时间以来SSR序列的生物学功能未引起重视,但SSR序列在植物基因调控区超乎寻常的积累应该具备环境适应优势。开展植物基因组调控区大量SSR序列的功能研究,对于突破SSR序列只作为一种优良分子标记的认识局限,加深理解SSR序列在植物基因组中的生物学功能具有重要意义。
     分布于拟南芥基因组调控区的SSR序列主要由GA/CT和GAA/CTT重复类型组成,约占调控区SSR位点总数的60%。一些SSR位点作为重要的功能元件涉及基因调控,这些功能位点在进化过程中应该具有不同程度的序列保守性。本研究采用系统发生足迹技术对拟南芥基因组内同源基因调控区、拟南芥基因组与甘蓝基因组的同源基因调控区CT/GA和CTT/GAA重复类型的SSR序列进行保守性分析,试图发掘具有调控功能的非编码保守SSR序列或非编码保守微卫星序列(Conserved Noncoding Microsatellite Sequence, CNMS)。结果发现在拟南芥和甘蓝基因组分化过程中247个SSR位点呈现位点保守性,包括182个CT/GA和65个CTT/GAA重复序列位点。同样,分析拟南芥旁系同源基因,发现位于基因调控区的122个CNMS位点,包括78个CT/GA和44个CTT/GAA重复序列位点。总计491个CT/GA和CTT/GAA重复序列位于拟南芥基因组调控区存在保守性,占整个拟南芥基因组上游调控区500 bp区域同类型SSR序列的10.6%。比较分析3组不同类型随机数据,排除了CNMS位点出现在同源基因调控区的偶然性,进一步确认位于拟南芥同源基因调控区的部分SSR序列起源于同一祖先位点,在进化过程中具有很高的序列保守性。
     为深入了解拟南芥CNMS的进化起源,本研究通过计算相关同源基因的同义替换率估算CNMS位点的进化关系。结果表明拟南芥-甘蓝直系CNMS位点在15百万年(Million years, Myr)前起源于同一祖先位点;大部分拟南芥旁系CNMS位点起源于28 Myr前拟南芥基因组大规模的重复事件,而少部分旁系CNMS位点则起源于42 Myr前十字花科的共同祖先序列。基于计算结果推测:一些古老的拟南芥旁系同源CNMS位点在甘蓝基因组中应该存在相应直系同源位点。进一步比较拟南芥-甘蓝和拟南芥-拟南芥调控区保守SSR序列,发现18个拟南芥旁系同源CNMS在甘蓝基因组中至少存在一个保守等位位点。这些同时出现在拟南芥-甘蓝直系同源和拟南芥-旁系同源基因调控区的Ultra-CNMS位点在其它进化关系较远的植物基因组中同样存在序列保守性。
     根据Gene Ontology的功能注释,206个拟南芥-甘蓝CNMS相关基因以及194个拟南芥-拟南芥CNMS相关基因具有较为明确的功能。功能分析表明CNMS相关基因的功能与转录因子活性和转录调控显著相关。生物信息学预测显示CT/GA和CTT/GAA保守重复序列分别与响应光信号和水杨酸信号的已知功能顺式作用元件相似。本研究通过分析拟南芥CNMS (CTT)n/(GAA)n相关基因在水杨酸处理后的表达模式来验证计算机预测结果。根据拟南芥MPSS表达数据显示约70%-80%的拟南芥CNMS (CTT)n/(GAA)n相关基因在叶片中的表达丰度明显受水杨酸调控。采用半定量RT-PCR分析其中7个CNMS (CTT)n/(GAA)n相关基因的表达谱,目标基因在水杨酸处理后的表达模式与拟南芥MPSS数据所反映的基因表达谱基本一致。
     为进一步研究CTT/GAA类型SSR序列与水杨酸诱导之间的联系,采用缺失方法对包含CTT重复位点且受水杨酸诱导的拟南芥AtHip1基因启动子进行水杨酸调控元件分析。4个不同缺失体与gus基因融合构建植物表达载体,利用农杆菌介导法转化拟南芥。转基因植株经报告基因gus蛋白活性测定及定量PCR分析,发现AtHip1启动子-399至-184的216 bp区域是启动子转录调控的核心区域,该区域缺失导致启动子水杨酸诱导功能丧失。生物信息学分析发现AtHip1启动子-399至-184的216 bp的序列除潜在响应水杨酸信号的CTT重复元件外,并未发现其它参与水杨酸信号应答的功能元件,说明存在于调控区域内的CTT重复序列为水杨酸信号应答的顺式作用元件。
     来源于表达序列标签(Expressed Sequence Tag, EST)的SSR标记,不仅具备传统基因组来源的SSR标记所有优势,还反映出基因转录区的差异,其多态性可能与所在基因的功能直接相关,具有很高的实际应用价值。随着EST测序的快速发展,尤其是同一基因来自不同亚种或品种的EST序列的大量重复测定,使同一物种中许多基因的EST序列存在大量的冗余信息,其中一些冗余序列包含SSR位点长度多态性信息。本研究以此为基础发展了EST-SSR多态性位点大规模发掘的计算机方法。利用该方法对公共序列数据库中玉米、大豆、水稻、小麦、油菜、大麦、棉花、西红柿、马铃薯及高梁10个主要作物的EST序列进行分析,共检测到15,640个等位位点存在长度多态性的SSR位点。10种作物中,EST-SSR多态性位点占被检测SSR位点的比率介于0.7%至2.61%,其中玉米EST-SSR多态性比率最高,西红柿EST-SSR位点多态性最低。这些EST-SSR多态性位点主要集中于二、三核苷酸重复类型,约占所有发掘位点的84%。分析发掘的EST-SSR等位位点长度变异,发现EST-SSR因突变而导致重复单元增加的等位位点明显多于重复单元减少的等位位点,表明EST-SSR突变倾向于增加位点长度。
     EST-SSR多态性位点来源于基因转录区,物种间存在很高通用性。对所发掘的15,640个具有长度多态性的EST-SSR进行通用性分析,EST-SSR多态性位点的通用性比率在14.1%至45.9%之间,高粱(45.9%)、小麦(39.1%)和大麦(38.2%)的EST-SSR多态性位点在相关作物间的通用性最高,油菜(14.1%)EST-SSR多态性位点在相关作物间的通用性较低。作物EST-SSR标记通用性表明:对于缺乏标记资源的作物,可利用其它作物已有的EST-SSR标记来开发相应的标记,不失为一种有效的替代方法。
     根据Gene ontology的植物代表性GO slims,对14,084个具有EST-SSR多态性位点的基因进行功能分类,8,952基因序列涉及108,601个GO功能注释。对包含SSR多态性位点的相关植物基因按GO生物学过程(biological process)分类,主要涉及蛋白质代谢、转运、转录、逆境应激、发育、信号转导等过程;分子功能(molecularfunction)主要包括蛋白结合、DNA或RNA结合(包括转录调控活性、转录因子活性)、水解酶活性、转移酶活性等。
     为方便查询相关EST-SSR多态性位点信息,以MySQL数据库管理系统构建了EST-SSR多态性位点数据库。EST-SSR多态性位点数据库包括重复单元、等位位点长度、品种来源、相关基因功能以及相关候选扩增引物等信息。用户通过网络游览器查看有关信息以及EST序列簇的详细拼接结果。用户还可以通过BLAST程序与包含SSR多态性位点的EST序列进行同源比较分析。网站同时提供相关数据下载服务。
Simple Sequence Repeats (SSRs), as short tandem repeated sequences, are extremely common in plant genomes. SSRs are generally thought to originate from genomic repetitive DNA and regarded as“junk”DNA without any apparent function. With the advantage of genome sequencing, the recent investigation showed SSRs are preferentially associated with nonrepetitive DNA in plant genomes. They can be found abundantly within or near plant genes, and in particular, some types are significantly enriched within the 5’regulatory regions. It implies SSR within the regulatory regions may play vital roles in gene expression or function in plants. Thus, investigation of these over-represented SSRs will help to understand their function in gene regulation in plants.
     SSRs are significantly enriched in the regulatory regions of Arabidopsis genome, and this feature is mostly attributable to the over-representation of CT/GA and CTT/GAA repeats which account for about 60% of all SSR in the regions. Given these SSRs are important for regulating gene expression and they should be conserved in homologous promoters due to functional constraints during plant evolution. To address the question of SSR associated with gene regulation, we used inter- and intra-genomic phylogenetic footprinting to analyze the dominant SSRs in the 5’noncoding regions of Arabidopsis and Brassica oleracea genes for conserved noncoding SSRs, or conserved noncoding microsatellite sequences (CNMSs). We identified 247 Arabidopsis-Brassica orthologous and 122 Arabidopsis paralogous CNMSs, representing 491 CT/GA and CTT/GAA repeats, which accounted for 10.6% of these types located in the 500 bp regions upstream of coding sequences in the Arabidopsis genome. In order to ensure that the observation of CNMSs was not simply due to its over-representation in plant genomes, a similar analysis carried out based on three different random datasets, and it indicated that some SSRs in regulatory regions were conserved from common ancestors during plant evolution.
     To gain further insight into the evolutionary relationship of Arabidopsis-Brassica and Arabidopsis-Arabidopsis CNMSs, the synonymous substitution rate (Ks) was calculated for the corresponding gene pairs. The frequency distribution of Ks suggested that the Arabidopsis-Brassica orthologous CNMSs were conserved from a common ancestor over a 15 million years (Myr) period, while most of the paralogous CNMSs were originated from large scale gene duplication over 28 Myr ago and others were duplicated from the common ancestor of brassicaceae family over 42 Myr ago. The results from the evolutionary relationships of Arabidopsis-Brassica and Arabidopsis-Arabidopsis CNMSs suggested that most paralogous CNMSs pre-dated the divergence of the two species. Further comparisons of paralogous and orthologous genes from Arabidopsis and Brassica were made for common CNMSs. With the same criteria, we identified 18 Ultra-CNMSs found in Arabidopsis paralogous pairs that also were coincident with CNMSs from at least one orthologs in Brassica and many Ultra-CNMSs were conserved across a number of more distantly homologous genes in Brassicaceae species and other plants.
     Function annotations based on Gene Ontology showed that there were 206 Arabidopsis–Brassica and 194 Arabidopsis–Arabidopsis CNMS associated genes with known function and their function were significantly enriched for transcription factor activity and transcription regulation. These findings suggested that CNMSs might be specifically associated with regulation of transcription. Computational prediction of cis-acting elements revealed that CNMS (CT)n/(GA)n were similar to the known motif involved in light responsiveness and CNMS (CTT)n/(GAA)n were involved in salicylic acid responsiveness. The abundance of gene transcripts evaluated by the MPSS showed about 70%-80% of CNMS (CTT)n/(GAA)n associated genes in Arabidopsis leaves were regulated by salicylic acid. Seven CNMS (CTT)n/(GAA)n associated genes were additionally analyzed for expression patterns after salicylic acid treatment with RT-PCR. The results showed that expression of these investigated genes were consistent with the patterns of gene expression from the Arabidopsis MPSS database.
     In order to validate the CTT/GAA repeats as salicylic acid-responsive elements, four 5' deletions of the salicylic acid induced CTT repeat-containing AtHip1 promoter were fused to theβ-glucronidase (GUS) gene and introduced into Arabidopsis plants. The histochemcal assays of GUS activity and the expression level investigation of gus gene by real-time PCR on promoter transformant plants revealed that the AtHip1 promoter from -399 to -184 region (216 bp) relative to transcription start site is core promoter for gene transcription regulation. Deletion of this region led to the AtHip1 promoter lacking the salicylic acid-responsive function. Bioinformatics analysis revealed there was no known salicylic acid induced elements but the CTT repeated element in this region. Taken together, these results demonstrate that the CTT tandem repeated sequences within 5’regions as cis-acting elements play important roles in the salicylic acid regulation.
     Expressed Sequence Tag (EST) derived SSRs as genetic markers are specific associated with gene expression and fucntion. The large number of ESTs in databases is a valuable resource to develop SSR markers. EST databases may contain redundancy in sequences of a particular gene, such as different alleles derived from heterozygous individuals or from different genotypes. Some redundant ESTs can contain information on length-polymorphisms in SSRs. We developed an in silico tool for identification of polymorphic SSRs based on EST sequence redundancy. Using this tool, we identified 15,640 polymorphic EST-derived SSRs from maize, soybean, rice, wheat, rape, barley, cotton, tomato, potato and sorghum. The percentage of polymorphic SSRs ranged from 0.7% for tomato to 2.61% for maize. The EST-derived SSRs mainly consist of dinucleotide and trinucleotide repeats, accounting for 84% in all identified polymorphic EST-SSRs. Length polymorphism of all identified 15,640 EST-SSRs revealed a mutational bias of EST-SSRs that alleles tend to increase in size.
     EST-SSRs are derived from transcripts. Homologous analysis on indentified 15,640 plolymorphic EST-SSRs indicated the in silico EST-SSRs had a high level of transferability across crop species and the percentage of transferability ranged from 14.1% for rape to 45.9% for grass species such as sorghum (45.9%), wheat (39.1%) and barley (38.2%). Large-scale identification of polymorphic EST-SSRs by in silico approach greatly improves the efficiency of marker development. It is practicable to develop new molecular markers based on EST-SSRs transferability for those poor informative plants.
     Each of unique ESTs with polymorphic SSRs was searched against the uniprot/swiss-prot database by BLAST and the assigned uniprot/swiss-prot IDs were classified according to the GO terms using Plant GO-Slims into categories. The results showed that 8,952 out of 14,084 unique ESTs were associated with 108,601 GO annotations. Functional categories revealed ESTs with polymorphic SSRs were mainly involved in biological process such as protein metabolism, transport, transcription, response to stresses, developmental processes and signal transduction, while their molecular functions were preferentially associated with protein binding, DNA or RNA binding, hydrolase activity and transferase activity.
     To facilitate access this resource of polymorphic EST-SSRs from crops, we developed a database providing the detailed information of these EST-SSRs such as SSR motif, allele length, cultivar, gene function and primers. The database also provided a viewing of EST assembly and a homologous analysis of SSR-containing ESTs among the related species by BLAST. The online service of EST-SSR database was implemented in Perl + MySQL, and the data is available for download.
引文
[1]. Miesfeld R, Krystal M, Arnheim N. A member of a new repeated sequence family which is conserved throughout eucaryotic evolution is found between the human delta and beta globin genes. Nucleic Acids Res, 1981, 9 (22): 5931-5947.
    [2]. Weber JL. Informativeness of human (dC-dA)n.(dG-dT)n polymorphisms. Genomics, 1990, 7 (4): 524-530.
    [3]. Weber JL, May PE. Abundant class of human DNA polymorphisms which can be typed using the polymerase chain reaction. Am J Hum Genet, 1989, 44 (3): 388-396.
    [4]. Litt M, Luty JA. A hypervariable microsatellite revealed by in vitro amplification of a dinucleotide repeat within the cardiac muscle actin gene. Am J Hum Genet, 1989, 44 (3): 397-401.
    [5]. Lander ES, Linton LM, Birren B, et al. Initial sequencing and analysis of the human genome. Nature, 2001, 409 (6822): 860-921.
    [6]. Zhang L, Yuan D, Yu S, et al. Preference of simple sequence repeats in coding and non-coding regions of Arabidopsis thaliana. Bioinformatics, 2004, 20 (7): 1081-1086.
    [7]. Lawson MJ, Zhang L. Distinct patterns of SSR distribution in the Arabidopsis thaliana and rice genomes. Genome Biol, 2006, 7 (2): R14.
    [8]. Zhang Z, Deng Y, Tan J, et al. A genome-wide microsatellite polymorphism database for the indica and japonica rice. DNA Res, 2007, 14 (1): 37-45.
    [9]. Katti MV, Ranjekar PK, Gupta VS. Differential distribution of simple sequence repeats in eukaryotic genome sequences. Mol Biol Evol, 2001, 18 (7): 1161-1167.
    [10]. Toth G, Gaspari Z, Jurka J. Microsatellites in different eukaryotic genomes: survey and analysis. Genome Res, 2000, 10 (7): 967-981.
    [11]. Sharma PC, Grover A, Kahl G. Mining microsatellites in eukaryotic genomes. Trends Biotechnol, 2007, 25 (11): 490-498.
    [12]. Morgante M, Hanafey M, Powell W. Microsatellites are preferentially associated with nonrepetitive DNA in plant genomes. Nat Genet, 2002, 30 (2): 194-200.
    [13]. Henderson ST, Petes TD. Instability of simple sequence DNA in Saccharomyces cerevisiae. Mol Cell Biol, 1992, 12 (6): 2749-2757.
    [14]. Marriage TN, Hudman S, Mort ME, et al. Direct estimation of the mutation rate at dinucleotide microsatellite loci in Arabidopsis thaliana (Brassicaceae). Heredity, 2009, 103 (4): 310-317.
    [15]. Ellegren H. Microsatellite mutations in the germline: implications for evolutionary inference. Trends Genet, 2000, 16 (12): 551-558.
    [16]. Schug MD, Mackay TF, Aquadro CF. Low mutation rates of microsatellite loci in Drosophila melanogaster. Nat Genet, 1997, 15 (1): 99-102.
    [17]. Schlotterer C. Genome evolution: are microsatellites really simple sequences? Curr Biol, 1998, 8 (4): R132- R134.
    [18]. Xu X, Peng M, Fang Z. The direction of microsatellite mutations is dependent upon allele length. Nat Genet, 2000, 24 (4): 396-399.
    [19]. Kelkar YD, Tyekucheva S, Chiaromonte F, et al. The genome-wide determinants of human and chimpanzee microsatellite evolution. Genome Res, 2008, 18 (1): 30-38.
    [20]. Huang Q, Xu F, Shen H, et al. Mutation patterns at dinucleotide microsatellite loci in humans. Am J Hum Genet, 2002, 70 (3): 625-634.
    [21]. Schlotterer C, Tautz D. Slippage synthesis of simple sequence DNA. Nucleic Acids Res, 1992, 20 (2): 211-215.
    [22]. Shinde D, Lai Y, Sun F, et al. Taq DNA polymerase slippage mutation rates measured by PCR and quasi-likelihood analysis: (CA/GT)n and (A/T)n microsatellites. Nucleic Acids Res, 2003, 31 (3): 974-980.
    [23]. Lee JS, Hanford MG, Genova JL, et al. Relative stabilities of dinucleotide and tetranucleotide repeats in cultured mammalian cells. Hum Mol Genet, 1999, 8 (13): 2567-2572.
    [24]. Ellegren H. Microsatellites: simple sequences with complex evolution. Nat Rev Genet, 2004, 5 (6): 435-445.
    [25]. Bachtrog D, Agis M, Imhof M, et al. Microsatellite variability differs between dinucleotide repeat motifs-evidence from Drosophila melanogaster. Mol Biol Evol, 2000, 17 (9): 1277-1285.
    [26]. Levinson G, Gutman GA. High frequencies of short frameshifts in poly-CA/TG tandem repeats borne by bacteriophage M13 in Escherichia coli K-12. Nucleic Acids Res, 1987, 15 (13): 5323-5338.
    [27]. Walsh PS, Fildes NJ, Reynolds R. Sequence analysis and characterization of stutter products at the tetranucleotide repeat locus vWA. Nucleic Acids Res, 1996, 24 (14): 2807-2812.
    [28]. Richard GF, Paques F. Mini- and microsatellite expansions: the recombination connection. EMBO Rep, 2000, 1 (2): 122-126.
    [29]. Ota T, Kimura M. A model of mutation appropriate to estimate the number of electrophoretically detectable alleles in a finite population. Genet Res, 1973, 22 (2): 201-204.
    [30]. Amos W, Sawcer SJ, Feakes RW, et al. Microsatellites show mutational bias and heterozygote instability. Nat Genet, 1996, 13 (4): 390-391.
    [31]. Brinkmann B, Klintschar M, Neuhuber F, et al. Mutation rate in human microsatellites: influence of the structure and length of the tandem repeat. Am J Hum Genet, 1998, 62 (6): 1408-1415.
    [32]. Dupuy BM, Stenersen M, Egeland T, et al. Y-chromosomal microsatellite mutation rates: differences in mutation rate between and within loci. Hum Mutat, 2004, 23 (2): 117-124.
    [33]. Shimoda N, Knapik EW, Ziniti J, et al. Zebrafish genetic map with 2000 microsatellite markers. Genomics, 1999, 58 (3): 219-232.
    [34]. Primmer CR, Saino N, Moller AP, et al. Unraveling the processes of microsatellite evolution through analysis of germ line mutations in barn swallows Hirundo rustica. Mol Biol Evol, 1998, 15 (8):1047-1054.
    [35]. Beck NR, Double MC, Cockburn A. Microsatellite evolution at two hypervariable loci revealed by extensive avian pedigrees. Mol Biol Evol, 2003, 20 (1): 54-61.
    [36]. Primmer CR, Saino N, Moller AP, et al. Directional evolution in germline microsatellite mutations. Nat Genet, 1996, 13 (4): 391-393.
    [37]. Ellegren H. Heterogeneous mutation processes in human microsatellite DNA sequences. Nat Genet, 2000, 24 (4): 400-402.
    [38]. Harr B, Schlotterer C. Long microsatellite alleles in Drosophila melanogaster have a downward mutation bias and short persistence times, which cause their genome-wide underrepresentation. Genetics, 2000, 155 (3): 1213-1220.
    [39]. Bell GI, Jurka J. The length distribution of perfect dimer repetitive DNA is consistentwith its evolution by an unbiased single-step mutation process. J Mol Evol, 1997, 44 (4): 414-421.
    [40]. Kruglyak S, Durrett RT, Schug MD, et al. Equilibrium distributions of microsatellite repeat length resulting from a balance between slippage events and point mutations. Proc Natl Acad Sci U S A, 1998, 95 (18): 10774-10778.
    [41]. Calabrese PP, Durrett RT, Aquadro CF. Dynamics of microsatellite divergence under stepwise mutation and proportional slippage/point mutation models. Genetics, 2001, 159 (2): 839-852.
    [42]. Dieringer D, Schlotterer C. Two distinct modes of microsatellite mutation processes: evidence from the complete genomic sequences of nine species. Genome Res, 2003, 13 (10): 2242-2251.
    [43]. Brouwer JR, Willemsen R, Oostra BA. Microsatellite repeat instability and neurological disease. Bioessays, 2009, 31 (1): 71-83.
    [44]. Pearson CE, Nichol EK, Cleary JD. Repeat instability: mechanisms of dynamic mutations. Nat Rev Genet, 2005, 6 (10): 729-742.
    [45]. The Huntington's Disease Collaborative Research Group. A novel gene containing a trinucleotide repeat that is expanded and unstable on Huntington's disease chromosomes. Cell, 1993, 72 (6): 971-983.
    [46]. La Spada AR, Wilson EM, Lubahn DB, et al. Androgen receptor gene mutations in X-linked spinal and bulbar muscular atrophy. Nature, 1991, 352 (6330): 77-79.
    [47]. Brais B, Bouchard JP, Xie YG, et al. Short GCG expansions in the PABP2 gene cause oculopharyngeal muscular dystrophy. Nat Genet, 1998, 18 (2): 164-167.
    [48]. Iglesias AR, Kindlund E, Tammi M, et al. Some microsatellites may act as novel polymorphic cis-regulatory elements through transcription factor binding. Gene, 2004, 341: 1491-1465.
    [49]. Vinces MD, Legendre M, Caldara M, et al. Unstable tandem repeats in promoters confer transcriptional evolvability. Science, 2009, 324 (5931): 1213-1216.
    [50]. Albanese V, Biguet NF, Kiefer H, et al. Quantitative effects on gene silencing by allelic variation at a tetranucleotide microsatellite. Hum Mol Genet, 2001, 10 (17): 1785-1792.
    [51]. Chen YH, Chau LY, Lin MW, et al. Heme oxygenase-1 gene promotor microsatellitepolymorphism is associated with angiographic restenosis after coronary stenting. Eur Heart J, 2004, 25 (1): 39-47.
    [52]. Martin P, Makepeace K, Hill SA, et al. Microsatellite instability regulates transcription factor binding and gene expression. Proc Natl Acad Sci U S A, 2005, 102 (10): 3800-3804.
    [53]. Gangwal K, Sankar S, Hollenhorst PC, et al. Microsatellites as EWS/FLI response elements in Ewing's sarcoma. Proc Natl Acad Sci U S A, 2008, 105 (29): 10149-10154.
    [54]. Guillon N, Tirode F, Boeva V, et al. The oncogenic EWS-FLI1 protein binds in vivo GGAA microsatellite sequences with potential transcriptional activation function. PLoS One, 2009, 4 (3): e4932.
    [55]. Van Steensel B, Delrow J, Bussemaker HJ. Genomewide analysis of Drosophila GAGA factor target genes reveals context-dependent DNA binding. Proc Natl Acad Sci U S A, 2003, 100 (5): 2580-2585.
    [56]. Lehmann M. Anything else but GAGA: a nonhistone protein complex reshapes chromatin structure. Trends Genet, 2004, 20 (1): 15-22.
    [57]. Santi L, Wang Y, Stile MR, et al. The GA octodinucleotide repeat binding factor BBR participates in the transcriptional regulation of the homeobox gene Bkn3. Plant J, 2003, 34 (6): 813-826.
    [58]. Sangwan I, O'Brian MR. Identification of a soybean protein that interacts with GAGA element dinucleotide repeat DNA. Plant Physiol, 2002, 129 (4): 1788-1794.
    [59]. Meister RJ, Williams LA, Monfared MM, et al. Definition and interactions of a positive regulatory element of the Arabidopsis INNER NO OUTER promoter. Plant J, 2004, 37 (3): 426-438.
    [60]. Shivaswamy S, Bhinge A, Zhao Y, et al. Dynamic remodeling of individual nucleosomes across a eukaryotic genome in response to transcriptional perturbation. PLoS Biol, 2008, 6 (3): e65.
    [61]. Field Y, Fondufe-Mittendorf Y, Moore IK, et al. Gene expression divergence in yeast is coupled to evolution of DNA-encoded nucleosome organization. Nat Genet, 2009, 41 (4): 438-445.
    [62]. Boeger H, Griesenbeck J, Strattan JS, et al. Nucleosomes unfold completely at a transcriptionally active promoter. Mol Cell, 2003, 11 (6): 1587-1598.
    [63]. Lee CK, Shibata Y, Rao B, et al. Evidence for nucleosome depletion at active regulatory regions genome-wide. Nat Genet, 2004, 36 (8): 900-905.
    [64]. Yuan GC, Liu YJ, Dion MF, et al. Genome-scale identification of nucleosome positions in S. cerevisiae. Science, 2005, 309 (5734): 626-630.
    [65]. Albert I, Mavrich TN, Tomsho LP, et al. Translational and rotational settings of H2A.Z nucleosomes across the Saccharomyces cerevisiae genome. Nature, 2007, 446 (7135): 572-576.
    [66]. Lee W, Tillo D, Bray N, et al. A high-resolution atlas of nucleosome occupancy in yeast. Nat Genet, 2007, 39 (10): 1235-1244.
    [67]. Kaplan N, Moore IK, Fondufe-Mittendorf Y, et al. The DNA-encoded nucleosome organization of a eukaryotic genome. Nature, 2009, 458 (7236): 362-366.
    [68]. Lam FH, Steger DJ, O'Shea EK. Chromatin decouples promoter threshold from dynamic range. Nature, 2008, 453 (7192): 246-250.
    [69]. Hulzink RJ, de Groot PF, Croes AF, et al. The 5'-untranslated region of the ntp303 gene strongly enhances translation during pollen tube growth, but not during pollen maturation. Plant Physiol, 2002, 129 (1): 342-353.
    [70]. Bao S, Corke H, Sun M. Microsatellites in starch-synthesizing genes in relation to starch physicochemical properties in waxy rice (Oryza sativa L.). Theor Appl Genet, 2002, 105 (6-7): 898-905.
    [71]. Pauli S, Rothnie HM, Chen G, et al. The cauliflower mosaic virus 35S promoter extends into the transcribed region. J Virol, 2004, 78 (22): 12120-12128.
    [72]. Attia AS, Hansen EJ. A conserved tetranucleotide repeat is necessary for wild-type expression of the Moraxella catarrhalis UspA2 protein. J Bacteriol, 2006, 188 (22): 7840-7852.
    [73]. Powell W, Morgante M, Andre C, et al. The comparison of RFLP, RAPD, AFLP and SSR (microsatellite) markers for germplasm analysis. Mol Breeding, 1996, 2 (3): 225-238.
    [74]. Adams MD, Kelley JM, Gocayne JD, et al. Complementary DNA sequencing: expressed sequence tags and human genome project. Science, 1991, 252 (5013): 1651-1656.
    [75]. Kantety RV, La Rota M, Matthews DE, et al. Data mining for simple sequence repeats in expressed sequence tags from barley, maize, rice, sorghum and wheat. PlantMol Biol, 2002, 48 (5-6): 501-510.
    [76]. Varshney RK, Graner A, Sorrells M. E. Genic microsatellite markers in plants: features and applications. Trends Biotechnol, 2005, 23 (1): 48-55.
    [77]. Schuler GD. Pieces of the puzzle: expressed sequence tags and the catalog of human genes. J Mol Med, 1997, 75 (10): 694-698.
    [78]. Pertea G, Huang X, Liang F, et al. TIGR Gene Indices clustering tools (TGICL): a software system for fast clustering of large EST datasets. Bioinformatics, 2003, 19 (5): 651-652.
    [79]. Hazelhurst S, Hide W, Liptak Z, et al. An overview of the wcd EST clustering tool. Bioinformatics, 2008, 24 (13): 1542-1546.
    [80]. Zhang Z, Schwartz S, Wagner L, et al. A greedy algorithm for aligning DNA sequences. J Comput Biol, 2000, 7 (1-2): 203-214.
    [81]. Burke J, Davison D, Hide W. d2_cluster: a validated method for clustering EST and full-length cDNAsequences. Genome Res, 1999, 9 (11): 1135-1142.
    [82]. Abajian C. Sputnik: C program to search DNA sequence for microsatellite repeats. http://espressosoftware.com/sputnik/index.html, 1994.
    [83]. Benson G. Tandem repeats finder: a program to analyze DNA sequences. Nucleic Acids Res, 1999, 27 (2): 573-780.
    [84]. Gao L, Tang J, Li H, et al. Analysis of microsatellites in major crops assessed by computational and experimental approaches. Mol Breeding, 2003, 12 (3): 245-261.
    [85]. Thiel T, Michalek W, Varshney RK, et al. Exploiting EST databases for the development and characterization of gene-derived SSR-markers in barley (Hordeum vulgare L.). Theor Appl Genet, 2003, 106 (3): 411-422.
    [86]. Kofler R, Schlotterer C, Lelley T. SciRoKo: a new tool for whole genome microsatellite search and investigation. Bioinformatics, 2007, 23 (13): 1683-1685.
    [87]. Fujimori S., Washio T., Higo K., et al. A novel feature of microsatellites in plants: a distribution gradient along the direction of transcription. FEBS Lett, 2003, 554 (1-2): 17-22.
    [88]. Cardle L, Ramsay L, Milbourne D, et al. Computational and experimental characterization of physically clustered simple sequence repeats in plants. Genetics, 2000, 156 (2): 847-854.
    [89]. Ellis JR, Burke JM. EST-SSRs as a resource for population genetic analyses. Heredity, 2007, 99 (2): 125-132.
    [90]. Guo W, Wang W, Zhou B, et al. Cross-species transferability of G. arboreum-derived EST-SSRs in the diploid species of Gossypium. Theor Appl Genet, 2006, 112 (8): 1573-1581.
    [91]. Eujayl I, Sledge MK, Wang L, et al. Medicago truncatula EST-SSRs reveal cross-species genetic markers for Medicago spp. Theor Appl Genet, 2004, 108 (3): 414-422.
    [92]. Saha MC, Mian MA, Eujayl I, et al. Tall fescue EST-SSR markers with transferability across several grass species. Theor Appl Genet, 2004, 109 (4): 783-791.
    [93]. Varshney RK, Sigmund R, Borner A, et al. Interspecific transferability and comparative mapping of barley EST-SSR markers in wheat, rye and rice. Plant Sci, 2005, 168 (1): 195-202.
    [94]. Sim SC, Yu JK, Jo YK, et al. Transferability of cereal EST-SSR markers to ryegrass. Genome, 2009, 52 (5): 431-437.
    [95]. Yu JK, La Rota M, Kantety RV, et al. EST derived SSR markers for comparative mapping in wheat and rice. Mol Genet Genomics, 2004, 271 (6): 742-751.
    [96].赵岩,孔凡美,丁承强,等. EST-SSR标记在结缕草中的通用性.中国草地学报, 2008, 30 (3): 69-73.
    [97]. Pashley CH, Ellis JR, McCauley DE, et al. EST databases as a source for molecular markers: lessons from Helianthus. J Hered, 2006, 97 (4): 381-388.
    [98]. Bandopadhyay R, Sharma S, Rustgi S, et al. DNA polymorphism among 18 species of Triticum- Aegilops complex using wheat EST-SSRs. Plant Sci, 2004, 166 (2): 349-356.
    [99]. Rungis D, Berube Y, Zhang J, et al. Robust simple sequence repeat markers for spruce (Picea spp.) from expressed sequence tags. Theor Appl Genet, 2004, 109 (6): 1283-1294.
    [100]. Bhat PR, Krishnakumar V, Hendre PS, et al. Identification and characterization of expressed sequence tags-derived simple sequence repeats, markers from robusta coffee variety 'CxR' (an interspecific hybrid of Coffea canephora×Coffea congensis). Mol Ecol Notes, 2005, 5 (1): 80-83.
    [101]. Gutierrez MV, Vaz Patto MC, Huguet T, et al. Cross-species amplification ofMedicago truncatula microsatellites across three major pulse crops. Theor Appl Genet, 2005, 110 (7): 1210-1217.
    [102]. Gupta PK, Rustgi S, Sharma S, et al. Transferable EST-SSR markers for the study of polymorphism and genetic diversity in bread wheat. Mol Genet Genomics, 2003, 270 (4): 315-323.
    [103]. Andersen JR, Lubberstedt T. Functional markers in plants. Trends Plant Sci, 2003, 8 (11): 554-560.
    [104]. Varshney RK, Grosse I, Hahnel U, et al. Genetic mapping and BAC assignment of EST-derived SSR markers shows non-uniform distribution of genes in the barley genome. Theor Appl Genet, 2006, 113 (2): 239-250.
    [105]. Han ZG, Guo WZ, Song XL, et al. Genetic mapping of EST-derived microsatellites from the diploid Gossypium arboreum in allotetraploid cotton. Mol Genet Genomics, 2004, 272 (3): 308-327.
    [106]. Zhang Y, Lin Z, Xia Q, et al. Characteristics and analysis of simple sequence repeats in the cotton genome based on a linkage map constructed from a BC1 population between Gossypium hirsutum and G. barbadense. Genome, 2008, 51 (7): 534-546.
    [107]. Yu JK, Dake TM, Singh S, et al. Development and mapping of EST-derived simple sequence repeat markers for hexaploid wheat. Genome, 2004, 47 (5): 805-818.
    [108]. Nicot N, Chiquet V, Gandon B, et al. Study of simple sequence repeat (SSR) markers from wheat expressed sequence tags (ESTs). Theor Appl Genet, 2004, 109 (4): 800-805.
    [109]. Gao LF, Jing RL, Huo NX, et al. One hundred and one new microsatellite loci derived from ESTs (EST-SSRs) in bread wheat. Theor Appl Genet, 2004, 108 (7): 1392-1400.
    [110]. Gadaleta A, Giancaspro A, Giove SL, et al. Genetic and physical mapping of new EST-derived SSRs on the A and B genome chromosomes of wheat. Theor Appl Genet, 2009, 118 (5): 1015-1025.
    [111]. Fraser LG, Harvey CF, Crowhurst RN, et al. EST-derived microsatellites from Actinidia species and their potential for mapping. Theor Appl Genet, 2004, 108 (6): 1010-1016.
    [112]. Nguyen TT, Koizumi S, La TN, et al. Pi35(t), a new gene conferring partialresistance to leaf blast in the rice cultivar Hokkai 188. Theor Appl Genet, 2006, 113 (4): 697-704.
    [113]. Khlestkina EK, Than MH, Pestsova EG, et al. Mapping of 99 new microsatellite-derived loci in rye (Secale cereale L.) including 39 expressed sequence tags. Theor Appl Genet, 2004, 109 (4): 725-732.
    [114]. Warnke SE, Barker RE, Jung G, et al. Genetic linkage mapping of an annual×perennial ryegrass population. Theor Appl Genet, 2004, 109 (2): 294-304.
    [115]. Saha MC, Mian R, Zwonitzer JC, et al. An SSR- and AFLP-based genetic linkage map of tall fescue (Festuca arundinacea Schreb.). Theor Appl Genet, 2005, 110 (2): 323-336.
    [116]. Barrett B, Griffiths A, Schreiber M, et al. A microsatellite map of white clover. Theor Appl Genet, 2004, 109 (3): 596-608.
    [117]. Yi G, Lee JM, Lee S, et al. Exploitation of pepper EST-SSRs and an SSR-based linkage map. Theor Appl Genet, 2006, 114 (1): 113-130.
    [118]. Ramu P, Kassahun B, Senthilvel S, et al. Exploiting rice-sorghum synteny for targeted development of EST-SSRs to enrich the sorghum genetic linkage map. Theor Appl Genet, 2009, 119 (7): 1193-1204.
    [119]. Xia Z, Tsubokura Y, Hoshi M, et al. An integrated high-density linkage map of soybean with RFLP, SSR, STS, and AFLP markers using A single F2 population. DNA Res, 2007, 14 (6): 257-269.
    [120]. Sledge MK, Ray IM, Jiang G. An expressed sequence tag SSR map of tetraploid alfalfa (Medicago sativa L.). Theor Appl Genet, 2005, 111 (5): 980-992.
    [121].杨新泉,刘鹏,韩宗福,等.普通小麦、斯卑尔脱小麦和密穗小麦基因组中SSR和EST-SSR分子标记的遗传差异研究.自然科学进展, 2004, 14 (9): 989-998.
    [122]. Eujayl I, Sorrells ME, Baum M, et al. Isolation of EST-derived microsatellite markers for genotyping the A and B genomes of wheat. Theor Appl Genet, 2002, 104 (2-3): 399-407.
    [123]. Caruso M, Federici CT, Roose ML. EST-SSR markers for asparagus genetic diversity evaluation and cultivar identification. Mol Breeding, 2008, 21 (2): 195-204.
    [124]. Feingold S, Lloyd J, Norero N, et al. Mapping and characterization of new EST-derived microsatellites for potato (Solanum tuberosum L.). Theor Appl Genet, 2005,111 (3): 456-466.
    [125]. Tang J, Baldwin SJ, Jacobs JM, et al. Large-scale identification of polymorphic microsatellites using an in silico approach. BMC Bioinformatics, 2008, 9: 374.
    [126]. Hardison RC. Conserved noncoding sequences are reliable guides to regulatory elements. Trends Genet, 2000, 16 (9): 369-372.
    [127]. Guo H, Moose SP. Conserved noncoding sequences among cultivated cereal genomes identify candidate regulatory sequence elements and patterns of promoter evolution. Plant Cell, 2003, 15 (5): 1143-1158.
    [128]. Inada DC, Bashir A, Lee C, et al. Conserved noncoding sequences in the grasses. Genome Res, 2003, 13 (9): 2030-2041.
    [129]. Hong RL, Hamaguchi L, Busch MA, et al. Regulatory elements of the floral homeotic gene AGAMOUS identified by phylogenetic footprinting and shadowing. Plant Cell, 2003, 15 (6): 1296-1309.
    [130]. Colinas J, Birnbaum K, Benfey PN. Using cauliflower to find conserved non-coding regions in Arabidopsis. Plant Physiol, 2002, 129 (2): 451-454.
    [131]. The Arabidopsis Genome Initiative. Analysis of the genome sequence of the flowering plant Arabidopsis thaliana. Nature, 2000, 408 (6814): 796-815.
    [132]. Altschul SF, Madden TL, Schaffer AA, et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res, 1997, 25 (17): 3389-3402.
    [133]. Huang X, Madan A. CAP3: A DNA sequence assembly program. Genome Res, 1999, 9 (9): 868-877.
    [134]. Morgenstern B. DIALIGN 2: improvement of the segment-to-segment approach to multiple sequence alignment. Bioinformatics, 1999, 15 (3): 211-218.
    [135]. Thompson JD, Higgins DG, Gibson TJ. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res, 1994, 22 (22): 4673-4680.
    [136]. Yang YW, Lai KN, Tai PY, et al. Rates of nucleotide substitution in angiosperm mitochondrial DNA sequences and dates of divergence between Brassica and other angiosperm lineages. J Mol Evol, 1999, 48 (5): 597-604.
    [137]. Koch M, Haubold B, Mitchell-Olds T. Molecular systematics of the Brassicaceae:evidence from coding plastidic matK and nuclear Chs sequences. Am J Bot, 2001, 88 (3): 534-544.
    [138]. Ashburner M, Ball CA, Blake JA, et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet, 2000, 25 (1): 25-29.
    [139]. Martin D, Brun C, Remy E, et al. GOToolBox: functional analysis of gene datasets based on Gene Ontology. Genome Biol, 2004, 5 (12): R101.
    [140]. Meyers BC, Lee DK, Vu TH, et al. Arabidopsis MPSS. An online resource for quantitative expression analysis. Plant Physiol, 2004, 135 (2): 801-813.
    [141]. Blanc G, Hokamp K, Wolfe KH. A recent polyploidy superimposed on older large-scale duplications in the Arabidopsis genome. Genome Res, 2003, 13 (2): 137-144.
    [142]. Koch MA, Haubold B, Mitchell-Olds T. Comparative evolutionary analysis of chalcone synthase and alcohol dehydrogenase loci in Arabidopsis, Arabis, and related genera (Brassicaceae). Mol Biol Evol, 2000, 17 (10): 1483-1498.
    [143]. Reyes JC, Muro-Pastor MI, Florencio FJ. The GATA family of transcription factors in Arabidopsis and rice. Plant Physiol, 2004, 134 (4): 1718-1732.
    [144]. Soltis PS, Soltis DE, Chase MW. Angiosperm phylogeny inferred from multiple genes as a tool for comparative biology. Nature, 1999, 402 (6760): 402-404.
    [145]. Lescot M, Dehais P, Thijs G, et al. PlantCARE, a database of plant cis-acting regulatory elements and a portal to tools for in silico analysis of promoter sequences. Nucleic Acids Res, 2002, 30 (1): 325-327.
    [146]. Higo K, Ugawa Y, Iwamoto M, et al. PLACE: a database of plant cis-acting regulatory DNA elements. Nucleic Acids Res, 1998, 26 (1): 358-359.
    [147]. Bolle C, Kusnetsov VV, Herrmann RG, et al. The spinach AtpC and AtpD genes contain elements for light-regulated, plastid-dependent and organ-specific expression in the vicinity of the transcription start sites. Plant J, 1996, 9 (1): 21-30.
    [148]. Arguello-Astorga GR, Herrera-Estrella LR. Ancestral multipartite units in light-responsive plant promoters have structural features correlating with specific phototransduction pathways. Plant Physiol, 1996, 112 (3): 1151-1166.
    [149]. Orozco BM, Ogren WL. Localization of light-inducible and tissue-specific regions of the spinach ribulose bisphosphate carboxylase/oxygenase (rubisco) activase promoter in transgenic tobacco plants. Plant Mol Biol, 1993, 23 (6): 1129-1138.
    [150]. Goldsbrough AP, Albrecht H, Stratford R. Salicylic acid-inducible binding of a tobacco nuclear protein to a 10 bp sequence which is highly conserved amongst stress-inducible genes. Plant J, 1993, 3 (4): 563-571.
    [151]. Pastuglia M, Roby D, Dumas C, et al. Rapid induction by wounding and bacterial infection of an S gene family receptor-like kinase gene in Brassica oleracea. Plant Cell, 1997, 9 (1): 49-60.
    [152]. Haberer G, Hindemitt T, Meyers BC, et al. Transcriptional similarities, dissimilarities, and conservation of cis-elements in duplicated genes of Arabidopsis. Plant Physiol, 2004, 136 (2): 3009-3022.
    [153]. Bevilacqua A, Fiorenza MT, Mangia F. A developmentally regulated GAGA box-binding factor and Sp1 are required for transcription of the hsp70.1 gene at the onset of mouse zygotic genome activation. Development, 2000, 127 (7): 1541-1551.
    [154]. Busturia A, Lloyd A, Bejarano F, et al. The MCP silencer of the Drosophila Abd-B gene requires both Pleiohomeotic and GAGA factor for the maintenance of repression. Development, 2001, 128 (11): 2163-2173.
    [155]. Teakle GR, Manfield IW, Graham JF, et al. Arabidopsis thaliana GATA factors: organisation, expression and DNA-binding characteristics. Plant Mol Biol, 2002, 50 (1): 43-57.
    [156]. Ryals JA, Neuenschwander UH, Willits M. G., et al. Systemic Acquired Resistance. Plant Cell, 1996, 8 (10): 1809-1819.
    [157]. Clough SJ, Bent AF. Floral dip: a simplified method for Agrobacterium-mediated transformation of Arabidopsis thaliana. Plant J, 1998, 16 (6): 735-743.
    [158]. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods, 2001, 25 (4): 402-408.
    [159]. Jefferson RA, Kavanagh TA, Bevan MW. GUS fusions: beta-glucuronidase as a sensitive and versatile gene fusion marker in higher plants. EMBO J, 1987, 6 (13): 3901-3907.
    [160]. Margulies M, Egholm M, Altman WE, et al. Genome sequencing in microfabricated high-density picolitre reactors. Nature, 2005, 437 (7057): 376-380.
    [161]. Shendure J, Porreca GJ, Reppas NB, et al. Accurate multiplex polony sequencing of an evolved bacterial genome. Science, 2005, 309 (5741): 1728-1732.

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