与骨纤维异常增殖症相关的MicroRNA分析
摘要
1.研究背景
骨纤维异常增殖症为骨内纤维组织代替骨组织的增生过程。多见于儿童及青少年时期发病。女性多见,男女比例约为1:2。患者颌骨呈进行性肿大,青春期后可停止发展或速度减慢。多见于上颌骨及颧骨。可为单骨性,也可为多骨性。多骨性最常见于颅骨、颌骨,还可累及肋骨、骨盆及长骨。后期常引起颌面畸形及咬合功能障碍或眼球移位、鼻塞等症状。
目前对于骨纤维异常增殖症的基础研究集中在:骨形成蛋白基因等少数已经报道的致病基因和突变位点,发现更多骨纤维异常增殖症致病基因及深入探索其致病机制是骨纤维异常增殖症基础研究的重要方向。本课题拟采用MicroRNA芯片探索与骨纤维异常增殖症相关的基因,为后续研究提供科学依据。
MicroRNA是一种21-25nt长的单链小分子RNA。它广泛存在于真核生物中,是一组不编码蛋白质的短序列RNA,其本身不具有开放阅读框(ORF)。成熟的miRNA,5′端有一个磷酸基团,3′端为羟基。miRNA 5′端第一个碱基对U(尿苷)有强烈的倾向性,而对G却排斥,但第二到第四个碱基缺乏U。一般来讲,除第四个碱基外,其他位置碱基通常都缺乏C。这些分子能够与那些和它的序列互补的mRNA分子相结合,有时候甚至可以与特定的DNA片断结合。这种结合的结果就是导致基因的沉默。这种方式是机体调节基因表达的一个重要策略。据推测,miRNA调节着人类三分之一的基因。
2.研究方法和研究结果:
本课题收集骨纤维异常增殖症临床病例共4例,同时选取2例正常对照。在基因芯片实验中,我们将4例患者患病组织中提取的RNA进行等量混合,2例正常对照也进行同样处理。通过microRNA芯片,发现患者与正常对照之间存在的基因表达差异,然后讨论这些存在差异表达的microRNA的潜在意义。
芯片用LuxScan 10K/A双通道激光扫描仪(CapitalBio公司)进行扫描。之后利用LuxScan3.0图像分析软件(CapitalBio公司)对芯片图像进行分析,把图像信号转化为数字信号,再利用SAM软件进行统计比较,我们发现,在A1样品中有22个microRNA表达明显上调,17个microRNA表达明显下调。在所有表达上调的microRNA中,mir-34a/b在病例中表达上调最为明显。而在表达下调的microRNA中,mir-1和mir-133a/b是下调最明显的3个microRNA。
获得以上基因芯片数据以后,再次提取正常对照及患者组织的RNA,并对提取的RNA进行定性、定量分析,采用Northern blot方法对芯片结果进行验证。结果表明,mir-34a/b、mir-181b和mir-20b在病例样本中表达上调明显;mir-1和mir-133a/b在病例样本中下凋显著,与芯片结果相符。
在证实上述结果以后,对表达改变显著的microRNA进行生物信息学分析,相关数据和资料显示,mir-34a/b可以通过影响细胞周期来抑制细胞的增殖,但是软件提示的相关基因与骨形成关系不明显。mir-181b和mir-20b均与VEGF表达相关,VEGF全称是血管内皮生长因子(Vascular endothelial growth factor),是PDGF/VEGF生长因子家族的成员之一,主要在内皮细胞中发挥功能,其作用包括间接增加血管渗透性;诱导血管新生、血管发生和内皮细胞生长;促进细胞迁移、抑制细胞凋亡。在对骨纤维异常增殖症患者的手术中,有一个显著特点:患病组织局部出血显著多于正常组织,提示患者的基因表达异常中,可能存在与血管生成、发育相关的异常。VEGF是目前发现的作用最强、特异性最高的促血管生成因子。所以在后续实验中,选取VEGF作为研究靶点。
实验选取4位患者的组织和血清,通过Western Blot、RT-PCR和ELISA实验验证了患者VEGF的表达水平,结果发现:患者VEGF水平在蛋白质水平和mRNA水平均显著升高。这一点改变可以解释目前在手术中发现的患者手术局部血管丰富、出血较多的表现。
3.结论:
实验首先通过microRNA基因芯片确定了骨纤维异常增殖症患者与正常对照之间microRNA的表达差别,之后应用Northern blot方法对实验结果进行验证。结果发现mir-34a/b、mir-181b和mir-20b在病例样本中表达上调明显;mir-1和mir-133a/b在病例样本中下调明显,这些特异改变可以作为以后基因诊断和基因治疗的研究靶点。
在确定表达改变显著的microRNA以后,对这些microRNA进行生物信息学分析,发现mir-181b和mir-20b均与VEGF表达相关,实验从组织水平、血清水平验证了患者组织中和血液中均存在VEGF表达增高的改变。
1. Background:
Fibrous dysplasia can affect many bone in your body. Most people with the disorder have only one affected bone—a form called monostotic fibrous dysplasia—and develop no signs or symptoms. When the condition affects more than one bone, it's known as polyostotic fibrous dysplasia. Fibrous dysplasia may cause few or no signs and symptoms, particularly if the condition is mild. Signs and symptoms may develop during childhood, adolescence or adulthood. If you have the polyostotic form, you're more likely to develop signs and symptoms, usually by age 10. More severe fibrous dysplasia may cause: Bone pain. Difficulty walking, Bone deformities, Fractures.
MicroRNAs (miRNAs) are endogenously expressed non-coding RNAs of 21-25 nucleotides, which post-transcriptionally regulate gene expression in plants and animals. Recently it has been recognized that miRNAs comprise one of the abundant gene families in multicellular species, and their regulatory functions in various biological processes are widely spread. There has been a surge in the research activities in this field in the past few years. From the very beginning, computational methods have been utilized as indispensable tools, and many discoveries have been obtained through combination of experimental and computational approaches. In this review, both biological and computational aspects of miRNA will be discussed. A brief history of the discovery of miRNA and discussion of microarray applications in miRNA research are also included.
2. Methods and results:
Four patients and two normal control were enrolled in our study. After RNA was distilled by TRI_(ZOL), microRNA hybridization was carried out. The chips were scanned with LuxScan 10K/A dual channels laser scanner of CapitalBio Company to look for the information of differently expressed genes.
By contrast with normal control, we find that the expression of 22 microRNAs were enhanced and he expression of other 17 microRNAs were declined. In these microRNAs, the most prominence microRNAs changed in our results were mir-34a/b and mir-133a/b. Via pictar assay, we find that the target genes of mir-34a/b were related to major gene which influenced development and proliferation of bone. The target gene of mir-133a/b was related to muscle maturation.
In addition, the change of mir-181b and mir-20b were two important microRNAs in our results. Based on our analysis and previous reports, mir-181b and mir-20b may be related to the expression of VEGF. So we investiged the expression of VEGF in patients tissue and serum by western blot, RT-PCR and ELISA.
The results of western blot, RT-PCR and ELISA showed that the expression of VEGF in patients was markedly increased. This result could explain the phenomenon that patients with Fibrous dysplasia have the tendency of haemorrhage in the course of operation.
骨纤维异常增殖症为骨内纤维组织代替骨组织的增生过程。多见于儿童及青少年时期发病。女性多见,男女比例约为1:2。患者颌骨呈进行性肿大,青春期后可停止发展或速度减慢。多见于上颌骨及颧骨。可为单骨性,也可为多骨性。多骨性最常见于颅骨、颌骨,还可累及肋骨、骨盆及长骨。后期常引起颌面畸形及咬合功能障碍或眼球移位、鼻塞等症状。
目前对于骨纤维异常增殖症的基础研究集中在:骨形成蛋白基因等少数已经报道的致病基因和突变位点,发现更多骨纤维异常增殖症致病基因及深入探索其致病机制是骨纤维异常增殖症基础研究的重要方向。本课题拟采用MicroRNA芯片探索与骨纤维异常增殖症相关的基因,为后续研究提供科学依据。
MicroRNA是一种21-25nt长的单链小分子RNA。它广泛存在于真核生物中,是一组不编码蛋白质的短序列RNA,其本身不具有开放阅读框(ORF)。成熟的miRNA,5′端有一个磷酸基团,3′端为羟基。miRNA 5′端第一个碱基对U(尿苷)有强烈的倾向性,而对G却排斥,但第二到第四个碱基缺乏U。一般来讲,除第四个碱基外,其他位置碱基通常都缺乏C。这些分子能够与那些和它的序列互补的mRNA分子相结合,有时候甚至可以与特定的DNA片断结合。这种结合的结果就是导致基因的沉默。这种方式是机体调节基因表达的一个重要策略。据推测,miRNA调节着人类三分之一的基因。
2.研究方法和研究结果:
本课题收集骨纤维异常增殖症临床病例共4例,同时选取2例正常对照。在基因芯片实验中,我们将4例患者患病组织中提取的RNA进行等量混合,2例正常对照也进行同样处理。通过microRNA芯片,发现患者与正常对照之间存在的基因表达差异,然后讨论这些存在差异表达的microRNA的潜在意义。
芯片用LuxScan 10K/A双通道激光扫描仪(CapitalBio公司)进行扫描。之后利用LuxScan3.0图像分析软件(CapitalBio公司)对芯片图像进行分析,把图像信号转化为数字信号,再利用SAM软件进行统计比较,我们发现,在A1样品中有22个microRNA表达明显上调,17个microRNA表达明显下调。在所有表达上调的microRNA中,mir-34a/b在病例中表达上调最为明显。而在表达下调的microRNA中,mir-1和mir-133a/b是下调最明显的3个microRNA。
获得以上基因芯片数据以后,再次提取正常对照及患者组织的RNA,并对提取的RNA进行定性、定量分析,采用Northern blot方法对芯片结果进行验证。结果表明,mir-34a/b、mir-181b和mir-20b在病例样本中表达上调明显;mir-1和mir-133a/b在病例样本中下凋显著,与芯片结果相符。
在证实上述结果以后,对表达改变显著的microRNA进行生物信息学分析,相关数据和资料显示,mir-34a/b可以通过影响细胞周期来抑制细胞的增殖,但是软件提示的相关基因与骨形成关系不明显。mir-181b和mir-20b均与VEGF表达相关,VEGF全称是血管内皮生长因子(Vascular endothelial growth factor),是PDGF/VEGF生长因子家族的成员之一,主要在内皮细胞中发挥功能,其作用包括间接增加血管渗透性;诱导血管新生、血管发生和内皮细胞生长;促进细胞迁移、抑制细胞凋亡。在对骨纤维异常增殖症患者的手术中,有一个显著特点:患病组织局部出血显著多于正常组织,提示患者的基因表达异常中,可能存在与血管生成、发育相关的异常。VEGF是目前发现的作用最强、特异性最高的促血管生成因子。所以在后续实验中,选取VEGF作为研究靶点。
实验选取4位患者的组织和血清,通过Western Blot、RT-PCR和ELISA实验验证了患者VEGF的表达水平,结果发现:患者VEGF水平在蛋白质水平和mRNA水平均显著升高。这一点改变可以解释目前在手术中发现的患者手术局部血管丰富、出血较多的表现。
3.结论:
实验首先通过microRNA基因芯片确定了骨纤维异常增殖症患者与正常对照之间microRNA的表达差别,之后应用Northern blot方法对实验结果进行验证。结果发现mir-34a/b、mir-181b和mir-20b在病例样本中表达上调明显;mir-1和mir-133a/b在病例样本中下调明显,这些特异改变可以作为以后基因诊断和基因治疗的研究靶点。
在确定表达改变显著的microRNA以后,对这些microRNA进行生物信息学分析,发现mir-181b和mir-20b均与VEGF表达相关,实验从组织水平、血清水平验证了患者组织中和血液中均存在VEGF表达增高的改变。
1. Background:
Fibrous dysplasia can affect many bone in your body. Most people with the disorder have only one affected bone—a form called monostotic fibrous dysplasia—and develop no signs or symptoms. When the condition affects more than one bone, it's known as polyostotic fibrous dysplasia. Fibrous dysplasia may cause few or no signs and symptoms, particularly if the condition is mild. Signs and symptoms may develop during childhood, adolescence or adulthood. If you have the polyostotic form, you're more likely to develop signs and symptoms, usually by age 10. More severe fibrous dysplasia may cause: Bone pain. Difficulty walking, Bone deformities, Fractures.
MicroRNAs (miRNAs) are endogenously expressed non-coding RNAs of 21-25 nucleotides, which post-transcriptionally regulate gene expression in plants and animals. Recently it has been recognized that miRNAs comprise one of the abundant gene families in multicellular species, and their regulatory functions in various biological processes are widely spread. There has been a surge in the research activities in this field in the past few years. From the very beginning, computational methods have been utilized as indispensable tools, and many discoveries have been obtained through combination of experimental and computational approaches. In this review, both biological and computational aspects of miRNA will be discussed. A brief history of the discovery of miRNA and discussion of microarray applications in miRNA research are also included.
2. Methods and results:
Four patients and two normal control were enrolled in our study. After RNA was distilled by TRI_(ZOL), microRNA hybridization was carried out. The chips were scanned with LuxScan 10K/A dual channels laser scanner of CapitalBio Company to look for the information of differently expressed genes.
By contrast with normal control, we find that the expression of 22 microRNAs were enhanced and he expression of other 17 microRNAs were declined. In these microRNAs, the most prominence microRNAs changed in our results were mir-34a/b and mir-133a/b. Via pictar assay, we find that the target genes of mir-34a/b were related to major gene which influenced development and proliferation of bone. The target gene of mir-133a/b was related to muscle maturation.
In addition, the change of mir-181b and mir-20b were two important microRNAs in our results. Based on our analysis and previous reports, mir-181b and mir-20b may be related to the expression of VEGF. So we investiged the expression of VEGF in patients tissue and serum by western blot, RT-PCR and ELISA.
The results of western blot, RT-PCR and ELISA showed that the expression of VEGF in patients was markedly increased. This result could explain the phenomenon that patients with Fibrous dysplasia have the tendency of haemorrhage in the course of operation.
引文
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19. Sempere L, Sokol N, Dubrovsky E, Berger E, Ambros V. Temporal regulation of microRNA expression in Drosophila melanogaster mediated by hormonal signals and broad-Complex gene activity. Dev Biol. 2003;259:9-18.
20. Lee Y, Kim M, Han J, Yeom K, Lee S, et al. MicroRNA genes are transcribed by RNA polymerase II. EMBO J. 2004;23:4051-4060.
21. Houbaviy H, Dennis L, Jaenisch R, Sharp P. Characterization of a highly variable eutherian microRNA gene. RNA. 2005;11:1245-1257.
22. Xie Z, Allen E, Fahlgren N, Calamar A, Givan S, et al. Expression of Arabidopsis miRNA genes. Plant Physiol. 2005; 138:2145-2154.
23. Smale S, Kadonaga J. The RNA polymerase II core promoter. Annu Rev Biochem. 2003;72:449-479.
24. Weis L, Reinberg D. Transcription by RNA polymerase II: Initiator-directed formation of transcription-competent complexes. FASEB J. 1992;6:3300-3309.
25. Ohler U, Yekta S, Lim L, Bartel D, Burge C. Patterns of flanking sequence conservation and a characteristic upstream motif for microRNA gene identification. RNA. 2004;10:1309—1322.
26. Wang G, Yu T. Zhang W. WordSpy: Identifying transcription factor binding motifs by building a dictionary and learning a grammar. Nucleic Acids Res. 2005;33:W412-W416.
27. Wang G, Zhang W. A steganalysis-based approach to comprehensive identification and characterization of functional regulatory elements. Genome Biol. 2006;7:R49.
28. Quinlan, J. C4.5: Programs for machine learning. San Francisco: Morgan Kaufmann Publisher; 1993. 302p.
29. Schlkopf, B.; Smola, A. Learning with kernels: Support vector machines, regularization, optimization, and beyond. Cambridge: MIT Press; 2001. 644 p.
30. Witten, IH.; Frank, E. Data mining: Practical machine learning tools and techniques with Java implementations. San Francisco: Morgan Kaufmann Publisher; 1999. 416 p.
31. Bailey, T.; Elkan, C. Fitting a mixture model by expectation maximization to discover motifs in biopolymers. In: Russ A, Brutlag D, Karp P, Lathrop R, Searls D., editors. Proceedings of the Second International Conference on Intelligent Systems for Molecular Biology; 14-17 August 1994;; Stanford, California.. United States: AAAI Press; 1994. pp. 28-36.
32. Yamashita R, Suzuki Y, Wakaguri H, Tsuritani K, Nakai K, et al. DBTSS: DataBase of Human Transcription Start Sites, Progress Report 2006. Nucleic Acids Res. 2006;34:D86-D89.
33. Fujimori S, Washio T, Higo K, Ohtomo Y, Murakami K, et al. A novel feature of microsatellites in plants: A distribution gradient along the direction of transcription. FEBS Lett. 2003;554:17-22.
34. Leibovitch B, Lu Q, Benjamin L, Liu Y, Gilmour D, et al. GAGA factor and the TFIID complex collaborate in generating an open chromatin structure at the Drosophila melanogaster hsp26 promoter. Mol Cell Biol. 2002;22:6148-6157.
35. Morgante M, Hanafey M, Powell W. Microsatellites are preferentially associated with nonrepetitive DNA in plant genomes. Nat Genet. 2002;30:194-200.
36. Molina C, Grotewold E. Genome wide analysis of Arabidopsis core promoters. BMC Genomics. 2005;6:25.
37. Hoffman E, Trusko S, Murphy M, George D. An S1 nuclease-sensitive homopurine/homopyrimidine domain in the c-Ki-ras promoter interacts with a nuclear factor. Proc Natl Acad Sci U S A. 1990;87:2705-2709.
38. Johnson A, Jinno Y, Merlino G. Modulation of epidermal growth factor receptor proto-oncogene transcription by a promoter site sensitive to S1 nuclease. Mol Cell Biol. 1988;8:4174-4184.
39. Mavrothalassitis G, Watson D, Papas T. Molecular and functional characterization of the promoter of ETS2, the human c-ets-2 gene. Proc Natl Acad Sci U SA. 1990;87:1047-1051.
40. Yao X, Hu J, Li T, Yang Y, Sun Z, et al. Epigenetic regulation of the taxol resistance-associated gene TRAG-3 in human tumors. Cancer Genet Cytogenet. 2004;151:1-13.
41. Xu G, Goodridge A. Characterization of a polypyrimidine/polypurine tract in the promoter of the gene for chicken malic enzyme. J Biol Chem. 1996;271:16008—16019.
42. Xu G, Goodridge A. A CT repeat in the promoter of the chicken malic enzyme gene is essential for function at an alternative transcription start site. Arch Biochem Biophys. 1998;358:83-91.
43. Xu G, Goodridge A. Function of a C-rich sequence in the polypyrimidine/polypurine tract of the promoter of the chicken malic enzyme gene depends on promoter context. Arch Biochem Biophys. 1999;363:202-212.
44. Lu Q, Wallrath L, Allan B, Glaser R, Lis J, et al. Promoter sequence containing (CT)n.(GA)n repeats is critical for the formation of the DNase I hypersensitive sites in the Drosophila hsp26 gene. J Mol Biol. 1992;225:985-998.
45. Yu M, Yang X, Schmidt T, Chinenov Y, Wang R, et al. GA-binding protein-dependent transcription initiator elements. Effect of helical spacing between polyomavirus enhancer a factor 3(PEA3)/Ets-binding sites on initiator activity. J Biol Chem. 1997;272:29060-29067.
46. Frank-Kamenetskii M, Mirkin S. Triplex DNA structures. Annu Rev Biochem. 1995;64:65-95.
47. Htun H, Dahlberg J. Topology and formation of triple-stranded H-DNA. Science. 1989;243:1571-1576.
48. Ponger L, Mouchiroud D. CpGProD: Identifying CpG islands associated with transcription start sites in large genomic mammalian sequences. Bioinformatics. 2002; 18:631-633.
49. Baumlein H, Nagy I, Villarroel R, Inze D, Wobus U. Cis-analysis of a seed protein gene promoter: The conservative RY repeat CATGCATG within the legumin box is essential for tissue-specific expression of a legumin gene. Plant J. 1992;2:233—239.
50. Fujiwara T, Beachy R. Tissue-specific and temporal regulation of a beta-conglycinin gene: Roles of the RY repeat and other cis-acting elements. Plant Mol Biol. 1994;24:261-272.
51. Xue Z, Xu M, Shen W, Zhuang N, Hu W, et al. Characterization of a Gy4 glycinin gene from soybean Glycine max cv. forrest. Plant Mol Biol. 1992;18:897-908.
52. Mohanty B, Krishnan S, Swarup S, Bajic V. Detection and preliminary analysis of motifs in promoters of anaerobically induced genes of different plant species. Ann Bot. 2005;96:669-681.
53. Macisaac K, Gordon D, Nekludova L, Odom D, Schreiber J, et al. A hypothesis-based approach for identifying the binding specificity of regulatory proteins from chromatin immunoprecipitation data. Bioinformatics. 2006;22:423-429.
54.Olefsky J.Nuclear receptor minireview series.J Biol Chem.2001;276:36863-36864.
55.Wang Y,Hindemitt T,Mayer K.Signifi microRNAs.Bioinformatics.2006;22:2585-2589.
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18. Johnson S, Lin S, Slack F. The time of appearance of the C. elegans let-7 microRNA is transcnptionally controlled utilizing a temporal regulatory element in its promoter. Dev Biol. 2003;259:364-379.
19. Sempere L, Sokol N, Dubrovsky E, Berger E, Ambros V. Temporal regulation of microRNA expression in Drosophila melanogaster mediated by hormonal signals and broad-Complex gene activity. Dev Biol. 2003;259:9-18.
20. Lee Y, Kim M, Han J, Yeom K, Lee S, et al. MicroRNA genes are transcribed by RNA polymerase II. EMBO J. 2004;23:4051-4060.
21. Houbaviy H, Dennis L, Jaenisch R, Sharp P. Characterization of a highly variable eutherian microRNA gene. RNA. 2005;11:1245-1257.
22. Xie Z, Allen E, Fahlgren N, Calamar A, Givan S, et al. Expression of Arabidopsis miRNA genes. Plant Physiol. 2005; 138:2145-2154.
23. Smale S, Kadonaga J. The RNA polymerase II core promoter. Annu Rev Biochem. 2003;72:449-479.
24. Weis L, Reinberg D. Transcription by RNA polymerase II: Initiator-directed formation of transcription-competent complexes. FASEB J. 1992;6:3300-3309.
25. Ohler U, Yekta S, Lim L, Bartel D, Burge C. Patterns of flanking sequence conservation and a characteristic upstream motif for microRNA gene identification. RNA. 2004;10:1309—1322.
26. Wang G, Yu T. Zhang W. WordSpy: Identifying transcription factor binding motifs by building a dictionary and learning a grammar. Nucleic Acids Res. 2005;33:W412-W416.
27. Wang G, Zhang W. A steganalysis-based approach to comprehensive identification and characterization of functional regulatory elements. Genome Biol. 2006;7:R49.
28. Quinlan, J. C4.5: Programs for machine learning. San Francisco: Morgan Kaufmann Publisher; 1993. 302p.
29. Schlkopf, B.; Smola, A. Learning with kernels: Support vector machines, regularization, optimization, and beyond. Cambridge: MIT Press; 2001. 644 p.
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31. Bailey, T.; Elkan, C. Fitting a mixture model by expectation maximization to discover motifs in biopolymers. In: Russ A, Brutlag D, Karp P, Lathrop R, Searls D., editors. Proceedings of the Second International Conference on Intelligent Systems for Molecular Biology; 14-17 August 1994;; Stanford, California.. United States: AAAI Press; 1994. pp. 28-36.
32. Yamashita R, Suzuki Y, Wakaguri H, Tsuritani K, Nakai K, et al. DBTSS: DataBase of Human Transcription Start Sites, Progress Report 2006. Nucleic Acids Res. 2006;34:D86-D89.
33. Fujimori S, Washio T, Higo K, Ohtomo Y, Murakami K, et al. A novel feature of microsatellites in plants: A distribution gradient along the direction of transcription. FEBS Lett. 2003;554:17-22.
34. Leibovitch B, Lu Q, Benjamin L, Liu Y, Gilmour D, et al. GAGA factor and the TFIID complex collaborate in generating an open chromatin structure at the Drosophila melanogaster hsp26 promoter. Mol Cell Biol. 2002;22:6148-6157.
35. Morgante M, Hanafey M, Powell W. Microsatellites are preferentially associated with nonrepetitive DNA in plant genomes. Nat Genet. 2002;30:194-200.
36. Molina C, Grotewold E. Genome wide analysis of Arabidopsis core promoters. BMC Genomics. 2005;6:25.
37. Hoffman E, Trusko S, Murphy M, George D. An S1 nuclease-sensitive homopurine/homopyrimidine domain in the c-Ki-ras promoter interacts with a nuclear factor. Proc Natl Acad Sci U S A. 1990;87:2705-2709.
38. Johnson A, Jinno Y, Merlino G. Modulation of epidermal growth factor receptor proto-oncogene transcription by a promoter site sensitive to S1 nuclease. Mol Cell Biol. 1988;8:4174-4184.
39. Mavrothalassitis G, Watson D, Papas T. Molecular and functional characterization of the promoter of ETS2, the human c-ets-2 gene. Proc Natl Acad Sci U SA. 1990;87:1047-1051.
40. Yao X, Hu J, Li T, Yang Y, Sun Z, et al. Epigenetic regulation of the taxol resistance-associated gene TRAG-3 in human tumors. Cancer Genet Cytogenet. 2004;151:1-13.
41. Xu G, Goodridge A. Characterization of a polypyrimidine/polypurine tract in the promoter of the gene for chicken malic enzyme. J Biol Chem. 1996;271:16008—16019.
42. Xu G, Goodridge A. A CT repeat in the promoter of the chicken malic enzyme gene is essential for function at an alternative transcription start site. Arch Biochem Biophys. 1998;358:83-91.
43. Xu G, Goodridge A. Function of a C-rich sequence in the polypyrimidine/polypurine tract of the promoter of the chicken malic enzyme gene depends on promoter context. Arch Biochem Biophys. 1999;363:202-212.
44. Lu Q, Wallrath L, Allan B, Glaser R, Lis J, et al. Promoter sequence containing (CT)n.(GA)n repeats is critical for the formation of the DNase I hypersensitive sites in the Drosophila hsp26 gene. J Mol Biol. 1992;225:985-998.
45. Yu M, Yang X, Schmidt T, Chinenov Y, Wang R, et al. GA-binding protein-dependent transcription initiator elements. Effect of helical spacing between polyomavirus enhancer a factor 3(PEA3)/Ets-binding sites on initiator activity. J Biol Chem. 1997;272:29060-29067.
46. Frank-Kamenetskii M, Mirkin S. Triplex DNA structures. Annu Rev Biochem. 1995;64:65-95.
47. Htun H, Dahlberg J. Topology and formation of triple-stranded H-DNA. Science. 1989;243:1571-1576.
48. Ponger L, Mouchiroud D. CpGProD: Identifying CpG islands associated with transcription start sites in large genomic mammalian sequences. Bioinformatics. 2002; 18:631-633.
49. Baumlein H, Nagy I, Villarroel R, Inze D, Wobus U. Cis-analysis of a seed protein gene promoter: The conservative RY repeat CATGCATG within the legumin box is essential for tissue-specific expression of a legumin gene. Plant J. 1992;2:233—239.
50. Fujiwara T, Beachy R. Tissue-specific and temporal regulation of a beta-conglycinin gene: Roles of the RY repeat and other cis-acting elements. Plant Mol Biol. 1994;24:261-272.
51. Xue Z, Xu M, Shen W, Zhuang N, Hu W, et al. Characterization of a Gy4 glycinin gene from soybean Glycine max cv. forrest. Plant Mol Biol. 1992;18:897-908.
52. Mohanty B, Krishnan S, Swarup S, Bajic V. Detection and preliminary analysis of motifs in promoters of anaerobically induced genes of different plant species. Ann Bot. 2005;96:669-681.
53. Macisaac K, Gordon D, Nekludova L, Odom D, Schreiber J, et al. A hypothesis-based approach for identifying the binding specificity of regulatory proteins from chromatin immunoprecipitation data. Bioinformatics. 2006;22:423-429.
54.Olefsky J.Nuclear receptor minireview series.J Biol Chem.2001;276:36863-36864.
55.Wang Y,Hindemitt T,Mayer K.Signifi microRNAs.Bioinformatics.2006;22:2585-2589.