ENHANCED PERF AND THROUGHPUT OF AUTOMATED DNA SEQUENCE

该方案的研究目标是增强性能 并提高了基于凝胶的自动DNA测序的吞吐量 基因组测序实验室中的仪器。 我们建议将我们已建立的基本呼叫系统与 上游数据采集硬件和软件，以及 DNA序列的下游处理和分析。我们 最近确定了新ABI的CD-Camera探测器 377 DNA测序仪可以外部驱动，绕过其默认设置 横向扫描分辨率和光谱带宽的限制。我们 建议将扫描速度从每1.5秒194个像素增加到600个像素 遍历凝胶，并将采样从4次增加到 每像素的波长间隔(滤光片)。吞吐量将会增加 从默认的36条到96条或更多可区分的样本车道 凝胶。增加探测器带宽将改善去卷积 适用于多种染料组。这将通过以下方式邀请申请 超过标准的四种染料标签，包括替代 荧光染料标记。我们将调查反卷积和 模式识别多路策略，以确定有利 多个DNA样本同时进行序列分析的条件 莱恩。我们将评估和进一步开发车道跟踪软件， 在样本数量显著增加的情况下分析凝胶图像 台词。我们将使用上下文模式识别方法来 以自动编辑初级DNA序列为引擎生成 贝叶斯基本呼叫置信度指标。这将支持自动 对下游多个项目中的基准计算差异进行对账 序列比对，从而促进共识编辑作为 顺序完成任务。这些基于ABI 377的研究将是有用的 采用新测序平台的应用模型 发展。毛细管和微通道硬件将面临挑战 现代基本编队系统，原始数据流量增加 监控其加速分离所需的映像数据 以及密集的排序梯子阵列。 这项研究有助于实现高性价比和精确的大规模 DNA测序--人类的一个重要技术目标 基因组计划。从长远来看，这项技术是必不可少的 调查和批判性地了解结构、功能、 以及医学上重要基因的序列多样性。

The research objectives of this proposal are enhanced performance and increased throughput for gel-based automated DNA sequencing instruments in genome sequencing laboratories. We propose to integrate our established basecalling system with upstream data acquisition hardware and software, and with downstream processing and analysis of DNA sequences. We recently determined that the CCD-camera detector of the new ABI 377 DNA sequencer can be externally driven, to bypass its default limits on lateral scanning resolution and spectral bandwidth. We propose to increase scanning from 194 to 600 pixels per 1.5 second traverse of the gel, and to increase sampling from 4 to 64 wavelength intervals (filters) per pixel. Throughput would increase from the default 36 to 96 or more distinguishable sample lanes per gel. Increased detector bandwidth will improve the deconvolution performance for multiple dye sets. This invites applications with more than the standard four dye labels, including alternative fluorescent dye markers. We will investigate deconvolution and pattern recognition multiplex strategies, to determine favorable conditions for sequence analysis with multiple DNA samples per lane. We will evaluate and further develop lane tracking software, to analyze gel images with significantly increased numbers of sample lines. We will use our contextual pattern recognition approach to auto-editing of primary DNA sequence as an engine to generate Bayesian basecall confidence metrics. This will support automated reconciliation of basecalling discrepancies in downstream multiple sequence alignments, and thus facilitate consensus editing as a sequence finishing task. These ABI 377-based studies will be useful models for applications with new sequencing platforms under development. Capillary and microchannel hardware will challenge contemporary basecalling systems, with increased flow of raw imaging data that is required to monitor their accelerated separations and dense arrays of sequencing ladders. This research contributes to cost-effective and accurate large scale DNA sequencing, a significant technical objective of the Human Genome Initiative. This technology is essential in the long term for investigation and critical understanding of the structure, function, and sequence diversity of medically important genes.