DIVIDE-CONQUER & AGGREGATE BASED APPROACH FOR EFFICIENT CHARACTERIZATION OF ALU
DIVIDE-CONQUER & AGGREGATE BASED APPROACH FOR EFFICIENT CHARACTERIZATION OF ALU
批准号:
8168136
负责人:
Kun Zhang
金额:
$0.96万
依托单位国家:
美国
项目类别:
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-07-15 至 2011-04-30
关键词:
AlgorithmsAlu ElementsArtsBindingBiologicalBiologyCharacteristicsComputer Retrieval of Information on Scientific Projects DatabaseConsensusDNADNA Insertion ElementsFundingGenesGenomeGrantHuman GenomeInformaticsInsertion MutationInstitutionKnowledgeLocationPatternPrimatesProcessResearchResearch PersonnelResourcesSignal TransductionSiteSourceUnited States National Institutes of HealthVariantbaseendonucleasegenome-wideinsightinterestpreference
中文摘要
该子项目是利用该技术的众多研究子项目之一
资源由 NIH/NCRR 资助的中心拨款提供。子项目和
研究者 (PI) 可能已从 NIH 的另一个来源获得主要资金,
因此可以在其他 CRISP 条目中表示。列出的机构是
对于中心来说,它不一定是研究者的机构。
表征大规模 DNA 碱基上 Alu 元件的插入位点偏好是灵长类动物特异性信息学中的一个重要问题。这个问题具有挑战性和有趣的关键特征包括:1)在没有任何先验知识的情况下,我们能否发现可能存在的一般模式并得出生物学见解? 2)在搜索空间达到4200或10120的情况下,如何获得紧凑但重要的判别模式?本研究提出了一种基于分治和聚合的集成算法来成功完成上述任务。与现有最先进的生物学研究相比,我们对超过 8400 个 Alu 前插入序列的结果证明了对 Alu 插入机制所涉及的特征模式的进一步精细分析。最重要的是,在生物学中,我们获得了围绕 Alu 插入的 200nt 预测图谱,它不仅包含广泛接受的信号共识,而且还表明了更长的模式 (T)7AA[AG]AATAA。生物学意义在于,这种模式提供了对参与启动插入过程的 L1 ORF2 核酸内切酶优先结合和切割的有利序列变异的更深入了解。将相应地对所发现的模式的分布进行全基因组搜索。将获得的模式的全基因组位置与人类基因组上的基因分布进行比较,以确定哪些基因可能特别容易受到 Alu 插入突变的影响。
英文摘要
This subproject is one of many research subprojects utilizing the
resources provided by a Center grant funded by NIH/NCRR. The subproject and
investigator (PI) may have received primary funding from another NIH source,
and thus could be represented in other CRISP entries. The institution listed is
for the Center, which is not necessarily the institution for the investigator.
Characterizing the insertion site preference of Alu elements on a large scale DNA bases is an important problem in primate-specific informatics. Key characteristics of this problem that are challenging and interesting include: 1) Without any prior knowledge, can we discover the general patterns that could exist and also make biological insights? 2) How to obtain the compact yet essential discriminative patterns given a search space up of 4200 or 10120? This research proposes an integrated divide-conquer and aggregate based algorithm for successfully fulfilling the above task. Compared to the existing state-of-the-art biological study, our results on over 8400 pre-Alu insertion sequences demonstrate a further refined analysis of the characteristic patterns involved in the mechanism of Alu insertion. Most importantly in biology, we acquire a 200nt predictive profile around the Alu insertion which not only contains the widely accepted signal consensus, but also suggests a longer pattern (T)7AA[AG]AATAA. The biological significance is that this pattern provides more insight into the favored sequence variations allowed for preferred binding and cleavage by the L1 ORF2 endonuclease that is involved in initiating the insertion process. Whole-genome search for the distribution of the discovered pattern will be conducted accordingly. The obtained genome-wide locations of the pattern will be compared to gene distributions on the human genome to identify which genes might be especially susceptible to the Alu insertion mutations.
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