Wu Hao, Wang Dan, Gao Feng
Department of Physics, School of Science, Tianjin University.
Department of Physics, School of Science, and the Frontier Science Center of Synthetic Biology (MOE), Key Laboratory of Systems Bioengineering (MOE), Tianjin University.
Brief Bioinform. 2021 Mar 22;22(2):1951-1971. doi: 10.1093/bib/bbaa013.
Pan-genome analysis is widely used to study the evolution and genetic diversity of species, particularly in bacteria. However, the impact of strain selection on the outcome of pan-genome analysis is poorly understood. Furthermore, a standard protocol to ensure high-quality pan-genome results is lacking. In this study, we carried out a series of pan-genome analyses of different strain sets of Bacillus subtilis to understand the impact of various strains on the performance and output quality of pan-genome analyses. Consequently, we found that the results obtained by pan-genome analyses of B. subtilis can be influenced by the inclusion of incorrectly classified Bacillus subspecies strains, phylogenetically distinct strains, engineered genome-reduced strains, chimeric strains, strains with a large number of unique genes or a large proportion of pseudogenes, and multiple clonal strains. Since the presence of these confounding strains can seriously affect the quality and true landscape of the pan-genome, we should remove these deviations in the process of pan-genome analyses. Our study provides new insights into the removal of biases from confounding strains in pan-genome analyses at the beginning of data processing, which enables the achievement of a closer representation of a high-quality pan-genome landscape of B. subtilis that better reflects the performance and credibility of the B. subtilis pan-genome. This procedure could be added as an important quality control step in pan-genome analyses for improving the efficiency of analyses, and ultimately contributing to a better understanding of genome function, evolution and genome-reduction strategies for B. subtilis in the future.
泛基因组分析被广泛用于研究物种的进化和遗传多样性，尤其是在细菌中。然而，菌株选择对泛基因组分析结果的影响却鲜为人知。此外，目前还缺乏确保高质量泛基因组结果的标准方案。在本研究中，我们对枯草芽孢杆菌的不同菌株集进行了一系列泛基因组分析，以了解各种菌株对泛基因组分析性能和输出质量的影响。结果发现，枯草芽孢杆菌泛基因组分析所获得的结果可能会受到以下因素的影响：错误分类的芽孢杆菌亚种菌株、系统发育上不同的菌株、工程化的基因组精简菌株、嵌合菌株、具有大量独特基因或大量假基因的菌株以及多个克隆菌株。由于这些混杂菌株的存在会严重影响泛基因组的质量和真实情况，因此我们在泛基因组分析过程中应消除这些偏差。我们的研究为在数据处理开始时从泛基因组分析中的混杂菌株中消除偏差提供了新的见解，这使得能够更接近地呈现枯草芽孢杆菌高质量泛基因组的情况，从而更好地反映枯草芽孢杆菌泛基因组的性能和可信度。这一程序可以作为泛基因组分析中的一个重要质量控制步骤添加进去，以提高分析效率，并最终有助于未来更好地理解枯草芽孢杆菌的基因组功能、进化和基因组精简策略。
