基因芯片的研制、应用和开发(张济、王侃侃)
发布日期:2010-04-03 浏览次数:238

急性髓性白血病(Acute myeloid leukemia, AML)中转录调控的异常是其发生的重要机制。AML常是由于染色体易位产生融合基因(如PML-RARA、AML1-ETO等),最终导致转录调控网络的异常。因此如何利用高通量组学技术平台,从全基因组水平揭示白血病发生过程中异常转录调控机制是当今这一研究领域的前沿。
本课题组适应当前前沿技术发展趋势,结合前期利用高通量组学技术研究的丰富经验,建立并完善以下平台技术:1)ChIP-on-chip (Chromatin Immunoprecipitation on chip)及ChIP-Seq(ChIP Sequencing)技术平台。2)高通量组学数据挖掘平台:针对生物组学数据的特点,本课题组自行开发了基于基因的数据整合框架(Framework for knowledge-based integrative analysis of microarray data, KIAM)、基于序列的整合方法(Knowledge-based integrative analysis for genomic data, GIS)以及适用于各种物种的de novo motif查找工具(An Improved motif discovery Tool, IMD),使各种数据之间的整合成为可能。
在上述平台的基础上,本课题组遵循系统生物学的研究思路,以急性早幼粒细胞白血病(Acute promyelocytic leukemia, APL)中异常转录因子PML-RARA为研究对象,从全基因组水平分析了PML-RARA的靶基因,发现了PML-RARA在介导APL发生过程中的新的转录调控模式。通过生物信息学分析本课题组发现PML-RARA的靶基因调控区域显著性富集转录因子PU.1结合位点,PU.1作为髓系造血细胞分化的关键转录因子,逻辑上提示了PML-RARA选择性的靶向抑制了PU.1下游调控靶基因。通过各种功能性分子生物学技术实验证实了这种组成性的调控模式促进了APL发生的作用,从而为揭示白血病的发生机制提供了新的理论依据。该原创性研究成果发表在Cancer Cell上(In Press)。
同时,本课题组也在生物信息学领域取得了一定的进展:(1) 基于基因的数据整合系统:KIAM,其原理主要是利用基因组序列的唯一性以及基因ID的非重复性,同时采用了不同的统计检验方法。(2) 基于序列的数据整合系统:KIAM,主要是利用了基因序列的唯一性,通过Z-score进行统计学检验。(3) De novo motif 分析工具:其特点是准确度高,适用简便,速度快,并且能适用于不同物种不同平台的数据。(4) Web sever:主要实现下面这些功能:①数据展示方面,SOM-CPP/SVD/NMF,主要应用于表达谱数据分析;②数据整合方面:实现了基于基因 (Gene-based) 和序列 (Sequence-based)的整合方式,适用于各种不同类型数据之间的交叉验证;③数据信息挖掘方面,主要实现了序列的Motif分析,包括IMD和KMD两种不同理念的方法。

Ⅻ. Research, application and development of gene chips (Ji Zhang & Kan-Kan Wang)
Acute myeloid leukemia (AML) is genetically characterized by aberrant transcription regulation. Specifically, chromosomal translocation involving differentiation-related transcription factors produces oncogenic fusion proteins (e.g., PML-RARA, AML1-ETO) and perturbs regulatory networks, eventually contributing to the AML genesis. Nowadays, how to understand the transcription dysregulation at the whole-genome wide has become the focus of leukemogenesis.
Accordingly, we have developed several high throughput platforms. We better up the platforms of ChIP-on-chip (Chromatin Immunoprecipitation on chip) and ChIP-Seq (ChIP Sequencing) for transcription regulation and epigenetic research. In addition, we have proposed bioinformatics platform for in-depth data mining.  We have developed several computational pipelines, namely, gene-based integrative analysis tools (KIAM), sequence-based integrative analysis tools (GIS) and a de novo motif discovery tool (IMD).
Through the wet and dry platforms above, we chose abnormal oncogenic transcription factor PML-RARα as a subject for the genome-wide location analysis, revealing a novel regulatory mode. More than 62% of PML-RARα binding sites contained canonical PU.1 motifs; as high as 84% of PU.1 motifs coexisted with RAREh binding sites. Further analysis indicated that promoters with such PU.1-RAREh binding sites were transactivated by PU.1. Moreover, PU.1-mediated transactivation was repressed by PML/RARA and restored by the addition of retinoic acid (ATRA). Genes containing such promoters were significantly represented by genes transcriptionally suppressed in APL and/or reactivated upon treatment with ATRA. Thus, selective targeting of PU.1-regulated genes by PML/RARA is a critical mechanism for the pathogenesis of APL. Collectively, this study not only provides a global view of PML-RARA target genes and the mechanism underlying the cross-talk between PML-RARA and PU.1, but also supplies a more comprehensive understanding of APL and a theoretical roadmap to future work. Notably, this study comprehensively presented a new study pattern to reveal other serious diseases at the -omics level.
 Accompanying the progress made in the AML, we also achieve a significant outcome in the field of bioinformatics. (1) Gene-based data integration system  KIAM is in principle to use unique genome sequence and the non-recurring genetically ID, while using different statistical test ways. (2) Sequence data-based on integration system KIAM mainly uses the sequences of unique genes with Z-score as the statistical tests value. (3) De novo motif analysis tool can be applied to various data of different species with high accuracy. (4) Web server incorporates ① data visualization, as highlighted by SOM-CPP/SVD/NMF of microarray expression data, ② data integration including gene-based and sequence-based  integration methods for the cross-validation of data of different types, ③ data mining, as highlighted by IMD and KMD of motif analysis.

年度发表论文:
国家重点实验室第一作者单位文章:
1. Wang KK, Wang P, Shi JT, Zhu XH, He MM, Jia XH, Yang XW, Qiu F, Jin W, Qian MX, Fang H, Mi JQ, Yang XZ, Xiao HS, Mark Minden, Du YZ, Chen Z, Zhang J. PML/RAR Targets Promoter Regions Containing PU.1 Consensus and RARE Half Sites in Acute Promyelocytic Leukemia. Cancer Cell 2010; 17: 186-197.
2. Wang KK, Fang H, Xiao DK, Zhu XH, He MM, Pan XL, Shi JT, Zhang H, Jia XH, Du YZ, Zhang J. Converting Redox Signaling to Apoptotic Activities by Stress-Responsive Regulators HSF1 and NRF2 in Fenretinide Treated Cancer Cells. PLOS One. 2009; 4: e7538
合作文章:
1. Xie ZQ, Liang G, Zhang L, Wang Q, Qu Y, Gao Y, Lin LB, Ye S, Zhang J, Wang H, Zhao GP, Zhang QH. Molecular mechanisms underlying the cholesterollowering effect of Ginkgo biloba extract in hepatocytes: a comparative study with lovastatin. Acta Pharmacologica Sinica 2009; 30: 1262-1275.