The impact of gene sequence alignment and gene tree estimation error on summary-based species network estimation

The impact of gene sequence alignment and gene tree estimation error on summary-based species network estimation
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基因序列比对和基因树估计误差对基于摘要的物种网络估计的影响

DOI:
10.1145/3535508.3545559
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发表时间:
2022
期刊:
and Health Informatics (BCB ’22
影响因子:
--
通讯作者:
Liu, Kevin J.
Liu, Kevin J.
中科院分区:
--
文献类型:
--
作者:
Gao, Meijun;Wang, Wei;Liu, Kevin J.

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部分得益于下一代测序技术的快速进步,最近的系统基因组学研究证明了非树状进化在生命树的许多部分--地球上所有生命的进化史--中发挥的关键作用。因此,生命之树根本不一定是一棵树,但可以用更一般的图形结构来更好地描述,比如系统发育网络。这些进展的另一个关键因素是从大规模基因组序列数据重建系统发育网络所需的计算方法。但几乎所有这些方法要么需要多个序列比对(MSA)作为输入,要么使用基因树或使用MSA计算的其他输入。所有输入的MSA和基因树都必须基于经验数据进行估计。这些方法本身并不直接考虑上游的估计误差,除了前人对系统发育树重建和轶事证据的研究外,对估计的MSA和基因树误差对下游物种网络重建的影响了解很少,因此我们开展了一项性能研究,以量化MSA误差和基因树误差对最新系统发育网络推断方法的影响。我们的研究利用了人工基准数据以及蚊子和酵母的基因组序列数据。我们发现,上游MSA和基因树估计误差会对下游网络重构的精度产生一阶影响,但对其计算时间的影响较小。这种影响在更具挑战性的数据集上变得更加明显,这些数据集具有更大的进化分歧和更多采样的分类群。我们的发现突出了计算方法开发的一个重要需求:即,当使用未比对的生物分子序列数据重建系统发育网络时,需要可扩展的方法来考虑估计的MSA和基因树误差。
Thanks in part to rapid advances in next-generation sequencing technologies, recent phylogenomic studies have demonstrated the pivotal role that non-tree-like evolution plays in many parts of the Tree of Life - the evolutionary history of all life on Earth. As such, the Tree of Life is not necessarily a tree at all, but is better described by more general graph structures such as a phylogenetic network. Another key ingredient in these advances consists of the computational methods needed for reconstructing phylogenetic networks from large-scale genomic sequence data. But virtually all of these methods either require multiple sequence alignments (MSAs) as input or utilize gene trees or other inputs that are computed using MSAs. All of the input MSAs and gene trees must be estimated on empirical data. The methods themselves do not directly account for upstream estimation error, and, apart from prior studies of phylogenetic tree reconstruction and anecdotal evidence, little is understood about the impact of estimated MSA and gene tree error on downstream species network reconstruction.We therefore undertake a performance study to quantify the impact of MSA error and gene tree error on state-of-the-art phylogenetic network inference methods. Our study utilizes synthetic benchmarking data as well as genomic sequence data from mosquito and yeast. We find that upstream MSA and gene tree estimation error can have first-order effects on the accuracy of downstream network reconstruction and, to a lesser extent, its computational runtime. The effects become more pronounced on more challenging datasets with greater evolutionary divergence and more sampled taxa. Our findings highlight an important need for computational methods development: namely, scalable methods are needed to account for estimated MSA and gene tree error when reconstructing phylogenetic networks using unaligned biomolecular sequence data.
书评:人类进化遗传学:起源、民族和疾病以及基因谱系、变异和进化:合并理论入门
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