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

项目总结/摘要 完成人类基因组的方法将受益于谨慎的、基准化的进展 证明了完全组装和定相二倍体染色体的能力。的 在我们的高分辨率基因组图谱中，已知剩余的未解决区域包含长 重复的片段。我们研究的长期目标是开发新的实验性 完成染色体规模组装以研究序列组织的方法， 这些新序列的结构多样性和疾病影响。本提案的目的是 开发测序方法，以提高数百个读数的序列通量， 在长度上缩短，以提高共识基础的准确性，必要的一步，以推进 组装工作进入剩余的空白区域。在我们的第一个目标中，我们展示了 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至关重要， 参考程序集。在我们的第二个目标中，我们提出了一种新的方法来瞄准和丰富 重复DNA中的长读段，以前在 以前的参考组件。这种方法有望提供一种新的具有成本效益的 一种研究这些高度可变区域的遗传变异的方法， 个体这项研究还有一个额外的好处，它将为人类增加新的序列， 基因组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.