Intron evolution: automated phylogentic analysis system

描述（由申请人提供）：比较序列分析在基因组注释、药物靶点发现、生物分子工程和医学遗传学中发挥着越来越突出的作用。比较序列分析的金标准是基于序列家族成员的多重比对（MSA）的系统发育特征分析，从MSA推断系统发育树，以及分析感兴趣的序列特征（活性位点残基，剪接点等）的重建变化。在这个项目中，一个自动化的系统，以促进进化分析将被开发，测试，并应用于剪接体内含子的进化中尚未解决的问题。将开发和测试用于组装真核细胞核蛋白编码基因的序列家族数据集（序列、MSA、内含子位点、树）的软件管道。以基于NEXUS的标准交换格式产生的数据集将被载入SPAN，SPAN是一个数据库/分析系统，将提供i）适合于存储序列家族数据集的关系模式; ii）基于综合分类层次的分类查询功能; iii）进化变化的重建; iv）基于树拓扑、分支长度和重建的查询和检索; v）明确处理序列注释和进化推断中的质量或不确定性。使用软件管道和SPAN，将使用具有20-200个序列家族的一系列数据库来评估靶向内含子获得的作用，以及更一般地，内含子获得和丢失的近期事件在解释基因和基因组中内含子分布的非随机性中的作用。在使用进化重建获得内含子增益的核苷酸偏好的精细估计之后，将针对内含子相位频率、内含子位点附近的氨基酸组成和内含子位点附近的蛋白质结构偏差中的偏差来评估靶向增益的影响。拟议的研究将解决有关分裂基因进化历史的长期问题，开发的软件系统将代表一个重大的方法学进步，对生物信息学具有广泛的影响。

DESCRIPTION (provided by applicant): Comparative sequence analysis plays an increasingly prominent role in genome annotation, drug target discovery, biomolecule engineering, and medical genetics. The gold standard of comparative sequence analysis is phylogenetic character analysis based on a multiple alignment (MSA) of sequence family members, inference of a phylogenetic tree from the MSA, and analysis of reconstructed changes in sequence features of interest (active site residues, splice junctions, and so on). In this project, an automated system to facilitate evolutionary analysis will be developed, tested, and applied to unresolved issues in the evolution of spliceosomal introns. A software pipeline to assemble sequence family data sets (sequences, MSAs, intron sites, trees) for eukaryotic nuclear protein-coding genes will be developed and tested. Data sets produced in a NEXUS-based standard exchange format will be loaded into SPAN, a database/analysis system that will provide i) a relational schema suitable for storing sequence family data sets; ii) taxonomic query functions based on a comprehensive taxonomic hierarchy; iii) reconstruction of evolutionary changes; iv) query and retrieval based on tree topology, branch lengths, and reconstructions; v) explicit treatment of quality or uncertainty in sequence annotations and evolutionary inferences. Using the software pipeline and SPAN, a series of databases with 20-200 sequence families will be used to evaluate the role of targeted intron gain, and more generally the role of recent events of intron gain and loss, in accounting for non-randomness in the distribution of introns in genes and genomes. After obtaining a refined estimate of the nucleotide preferences of intron gain using evolutionary reconstructions, the implications of targeted gain will be evaluated with respect to biases in intron phase frequencies, amino acid composition near intron sites, and protein structure biases near intron sites. The proposed research will resolve long-standing issues concerning the evolutionary history of split genes, and the software systems developed will represent a major methodological advance with broad implications for bioinformatics.