Pan-African genome demonstrates how population-specific genome graphs improve high-throughput sequencing data analysis.
Pan-African genome demonstrates how population-specific genome graphs improve high-throughput sequencing data analysis.
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泛非基因组展示了群体特异性基因组图如何改善高通量测序数据分析。
DOI：
10.1038/s41467-022-31724-3
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发表时间：
2022-08-04
影响因子：
16.6
通讯作者：
中科院分区：
文献类型：
--
作者：
基于图的基因组参考表示已经看到了显著的发展，其动机是当前人类基因组参考不足以表示来自不同人类群体的多样遗传信息，并且其无法对非欧洲祖先保持相同的准确性水平。虽然已经做出了许多努力来开发用于NGS读段比对和变体调用的计算高效的基于图的工具包，但是管理基因组变体并随后构建基因组图的方法仍然是一个未充分研究的问题，其不可避免地决定了整个生物信息学管道的有效性。在这项研究中，我们讨论了在图的建设过程中遇到的障碍，并提出了基于人口多样性的样本选择方法，图增强结构变量和信息过载引起的图参考歧义的决议。此外，我们提出的情况下，迭代扩增定制的基因组图为目标人群，并证明这种方法对非洲血统的全基因组样本。我们的研究结果表明，群体特异性图，作为线性或通用图参考的更有代表性的替代品，可以实现显着降低读取映射错误和增强的变异调用灵敏度，除了提供联合变异调用的改进，而不需要计算密集的后处理步骤。基于图的基因组参考表示已经看到了显著的发展，其动机是当前人类基因组参考不足以表示来自不同人类群体的多样遗传信息，并且其无法对非欧洲祖先保持相同的准确性水平。在这里，作者提出了迭代增强针对目标人群的定制基因组图的案例，并在非洲血统的全基因组样本上演示了这种方法。
Graph-based genome reference representations have seen significant development, motivated by the inadequacy of the current human genome reference to represent the diverse genetic information from different human populations and its inability to maintain the same level of accuracy for non-European ancestries. While there have been many efforts to develop computationally efficient graph-based toolkits for NGS read alignment and variant calling, methods to curate genomic variants and subsequently construct genome graphs remain an understudied problem that inevitably determines the effectiveness of the overall bioinformatics pipeline. In this study, we discuss obstacles encountered during graph construction and propose methods for sample selection based on population diversity, graph augmentation with structural variants and resolution of graph reference ambiguity caused by information overload. Moreover, we present the case for iteratively augmenting tailored genome graphs for targeted populations and demonstrate this approach on the whole-genome samples of African ancestry. Our results show that population-specific graphs, as more representative alternatives to linear or generic graph references, can achieve significantly lower read mapping errors and enhanced variant calling sensitivity, in addition to providing the improvements of joint variant calling without the need of computationally intensive post-processing steps. Graph-based genome reference representations have seen significant development, motivated by the inadequacy of the current human genome reference to represent the diverse genetic information from different human populations and its inability to maintain the same level of accuracy for non-European ancestries. Here the authors present the case for iteratively augmenting tailored genome graphs for targeted populations and demonstrate this approach on the whole-genome samples of African ancestry.
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影响因子：
64.8
作者：
Bycroft C;Freeman C;Petkova D;Band G;Elliott LT;Sharp K;Motyer A;Vukcevic D;Delaneau O;O'Connell J;Cortes A;Welsh S;Young A;Effingham M;McVean G;Leslie S;Allen N;Donnelly P;Marchini J
通讯作者：
Marchini J
影响因子：
16.6
作者：
Duncan, L.;Shen, H.;Domingue, B.
通讯作者：
Domingue, B.
影响因子：
12.3
作者：
Ballouz, Sara;Dobin, Alexander;Gillis, Jesse A.
通讯作者：
Gillis, Jesse A.
影响因子：
64.8
作者：
Karczewski, Konrad J;Francioli, Laurent C;MacArthur, Daniel G
通讯作者：
MacArthur, Daniel G
影响因子：
12.3
作者：
Jain M;Olsen HE;Paten B;Akeson M
通讯作者：
Akeson M