TRANSLATION OF AUTOMATED SEQUENCER DATA TO DNA SEQUENCES

该提案的目标是显著提高自动化程度 DNA序列的测定。 确定了自动DNA测序仪的实际性能极限 聚丙烯酰胺凝胶对寡核苷酸的分离作用 电泳法。现代乐器的设计基本上是 很相似。当DNA测序梯子中的低聚物通过检测器时(S)， 多组分分析确定了放射性或荧光标记 与每个齐聚物相关联。在理想条件下，测定 末端核苷酸的序列很简单。什么时候 低聚物或信号水平的分离不是最佳的，模棱两可 或者，可能会出现错误。这些都是错误的碱基，额外的或缺失的碱基， 或DNA序列文件中的未知碱基，通常约为1到 每100个垒有3个错误。 接近1%的错误率是DNA测序性能的常见目标， 因为与互补链序列数据比较应该 将错误减少到每10,000个碱基对中约1个。这是唯一可能的 如果识别出序列及其补体的每个不匹配，并且 已正确调和。即使这样，错误率也在0.01%到0.1%之间 基因库中等位基因之间的近似变异：一些这样的等位基因 可能与遗传性病理的严重负担相关。小的 单链错误率的提高将对以下方面产生重大影响 完成序列的质量从1/10,000个核苷酸到1/1,000,000个核苷酸。 如果自动化系统要提供更长的跨度，就需要改进 错误更少的DNA序列。这项建议的重点是 原始数据获取和将原始数据转换为 完成的DNA序列。 将开发一个专家系统，基于规则的方法来加强 将原始数据转换为DNA序列的传统方法。一个独立的， 还将开发和测试模式识别系统，使用 神经网络的构建和训练技术。我们还将 评估利用单标签、单数据通道的两种新方法 以便更有效地确定DNA序列。备择 用于序列分析的寡核苷酸分离方法也将 被调查。为了追求这些具体目标，我们将采取 连续波的相对间隔和强度的优势 DNA测序梯形图中的寡聚体作为DNA的独立决定因素 特定于序列的数据流模式。

The objective of this proposal is to significantly improve automated determination of DNA sequences. Practical performance limits of automated DNA sequencers are determined by the separation of oligonucleotides effected by polyacrylamide gel electrophoresis. Designs of contemporary instruments are basically similar. As oligomers in a DNA sequencing ladder pass the detector(s), multi-component analysis specifies the radioactive or fluorescent label associated with each oligomer. Under ideal conditions, determination of the sequence of terminal nucleotides is straightforward. When separations of oligomers or signal levels are not optimal, ambiguities or errors are likely. These are miscalled bases, extra or missing bases, or unidentified bases in the DNA sequence file, typically at about 1 to 3 errors per 100 bases. An error rate near 1% is a common target for DNA sequencing performance, since comparison with complementary strand sequence data should then reduce errors to about 1 per 10,000 base pairs. This is only possible if every mismatch of the sequence and its complement is identified and correctly reconciled. Even then, error rates from 0.01% to 0.1% approximate the variation among alleles in a gene pool: some such alleles can correlate with severe burdens of inherited pathology. Small improvements in single strand error rate will have substantial impact on quality of finished sequences from 1/10,000 bp to 1/1,000,000 bp. Improvements are needed if automated systems are to provide longer spans of DNA sequences with fewer errors. The emphasis of this proposal is on raw data acquisition and new methods for translation of the raw data to finished DNA sequences. An expert system, rule-based method will be developed to reinforce conventional translation of raw data to DNA sequences. An independent, pattern-recognition system will also be developed and tested, using techniques for construction and training of neural nets. We will also evaluate two new approaches to utilize single label, single data channels for more efficient determination of DNA sequences. Alternative approaches to oligonucleotide separation for sequence analysis will also be investigated. In pursuit of these specific aims we will take advantage of the relative separations and intensities of successive oligomers in DNA sequencing ladders, as independent determinants of DNA sequence-specific data stream patterns.