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
这个子项目是许多研究子项目中利用
资源由NIH/NCRR资助的中心拨款提供。子项目和
调查员(PI)可能从NIH的另一个来源获得了主要资金,
并因此可以在其他清晰的条目中表示。列出的机构是
该中心不一定是调查人员的机构。
表征Alu元件在大规模DNA碱基上的插入位点偏好是灵长类特异信息学中的一个重要问题。这个问题具有挑战性和趣味性的主要特征包括: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进行生物学洞察?2)如何在搜索空间达到4200或10120的情况下获得紧凑但本质上具有区别性的模式?为了成功地完成上述任务,本研究提出了一种基于分治和聚合的综合算法。与现有最先进的生物学研究相比,我们对8400多个Alu前插入序列的结果进一步精细地分析了Alu插入机制中涉及的特征模式。在生物学上最重要的是,我们获得了一个围绕Alu插入的200nt预测图谱,它不仅包含了广泛接受的信号共识,而且还暗示了一个更长的模式(T)7AA[AG]AATAA。其生物学意义在于,这种模式提供了更多关于启动插入过程所涉及的L1 ORF2核酸内切酶优先结合和切割的有利序列变异的洞察力。将相应地进行全基因组搜索,以寻找所发现的模式的分布。获得的模式的全基因组位置将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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