The construction and utility of reference pan-genome graphs

参考泛基因组图的构建和利用

• 批准号: 10112282
• 负责人: Heng Li
• 金额: $ 80万
• 依托单位: DANA-FARBER CANCER INST
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-03-01 至 2023-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10112282
• 关键词: Address; Adoption; Algorithms; Awareness; Back; Base Sequence; Biological Assay; Biomedical Research; Companions; Complement; Complex; Computer software; Data; Data Analyses; Diagnostic; Disease; Ecosystem; Frequencies; Future; Genetic Research; Genetic Variation; Genome; Genotype; Graph; Haplotypes; Heart; Human; Human Resources; Individual; Informatics; Libraries; Mainstreaming; Maps; Medical; Methods; Modeling; Morphologic artifacts; Mosaicism; Phenotype; Play; Population; Population Genetics; Population Heterogeneity; Problem Solving; Research; Research Personnel; Role; Sequence Alignment; Speed; Structure; System; Time; Update; Variant; Work; base; bioinformatics tool; cancer genomics; design; experience; human population genetics; human reference genome; indexing; linear transformation; pan-genome; programs; reference genome; success; support tools; tool; user-friendly

PROJECT SUMMARY The current human reference genome, GRCh38, plays a central role in medical and population human genetics. It primarily models a single human individual and is missing hundreds of thousands of large structural variations segregating in the population. This underrepresentation of genetic diversity leads to various artifacts in data analysis and significantly hampers our understanding of the functional and medical relevance of these large human variations, which may collectively have pervasive impact. To address this issue, we will extend our previous work on sequence graphs and alignment algorithms and construct a pan-genome reference graph from hundreds of long-read human assemblies that more completely represent genetic diversity. Specifically, we will (1) design a reference graph model with a stable coordinate system compatible with GRCh38 and develop toolkits and libraries to interact with this model; (2) develop minimizer-based sequence-to-graph alignment algorithms for short and long sequences; (3) incrementally construct a reference graph by mapping assemblies to an existing graph and updating the graph; and (4) develop a graph-based genotyping algorithm and apply it to short-read based projects to call structural variations missed by the current pipelines. Upon completion, the proposed project could replace the current practices based on a linear genome and will enable the profiling and study of complex human variations missed in most current research.

项目总结