IMPROVING THROUGHPUT OF LONG READS WITH HIGH CONSENSUS BASE ACCURACY TO RESOLVE REPETITIVE DNAS

项目摘要/摘要 完成人类基因组的方法将受益于仔细的、有基准的进展 证明了完全组装二倍体染色体并使其成熟的能力。这个 我们的高分辨率基因组图中剩余的未分辨区域已知包含长的 一连串的重复。我们研究的长期目标是开发新的实验 方法完成染色体标尺组装，研究序列组织， 这些新序列的结构多样性和疾病影响。这项提议的目标是 开发测序方法以提高数百个读数的序列吞吐量 千碱基的长度以提高共识基础的准确性，这是推进的必要步骤 大会努力将这些努力转移到剩余的空白地区。在我们的第一个目标中，我们演示如何使用 我们的方法产生了第一个人类端粒到端粒的阶段性组装 染色体。我们假设这项工作对完成其他染色体是至关重要的 引用程序集。在我们的第二个目标中，我们提出了一种新的方法来针对和丰富 对重复DNA的长时间读取，这些重复DNA之前被错误陈述或完全丢失 以前的引用程序集。这种方法有望提供一种新的成本效益 研究这些高变异区的遗传变异的方法 个人。这项研究还有一个额外的好处，那就是它将为人类增加新的序列 基因组来系统地探索经常被忽视的区域的遗传变异 疾病关联研究。

Project Summary/Abstract Approaches to complete the human genome will benefit from careful, benchmarked advances that demonstrate the capability to fully assemble and phase diploid chromosomes. The remaining unresolved regions in our high-resolution genomic maps are known to contain long tracts of repeats. The long-term objective of our research is to develop new experimental methods to complete chromosome scale assemblies to study the sequence organization, structural diversity, and disease impact of these novel sequences. The goal of this proposal is to develop sequencing methods to improve the sequence throughput of reads that are hundreds of kilobases in length to improve consensus base accuracy, a necessary step to advance assembly efforts into the remaining gapped regions. In our first aim, we demonstrate the use of our approach to generate the first telomere-to-telomere phased assembly of a human chromosome. We hypothesize that this work will be critical to complete other chromosome reference assemblies. In our second aim we present a new approach to target and enrich for long-reads in repetitive DNAs that were previously misrepresented or missing completely in previous reference assemblies. This approach is expected to provide a new cost-effective method of studying genetic variation in these highly variable regions from a large number of individuals. This research has the additional benefit that it will add new sequence to the human genome to systematically explore genetic variation of regions frequently overlooked as part of disease-association studies.