Zeng Jiaqi, Wang Yuxiao, Wu Ziyao, Zhou Yizhuang
Institute of Pathogeny Biology, School of Basic Medicine, Guilin Medical University, Guilin, China.
Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Health, School of Public Health, Guilin Medical University, Guilin, China.
Front Microbiol. 2022 May 18;13:847439. doi: 10.3389/fmicb.2022.847439. eCollection 2022.
We previously reported on FRAGTE (hereafter termed FRAGTE1), a promising algorithm for sieving (pre-selecting genome pairs for whole-genome species demarcation). However, the overall amount of pairs sieved by FRAGTE1 is still large, requiring seriously unaffordable computing cost, especially for large datasets. Here, we present FRAGTE2. Tests on simulated genomes, real genomes, and metagenome-assembled genomes revealed that () FRAGTE2 outstandingly reduces ~50-60.10% of the overall amount of pairs sieved by FRAGTE1, dramatically decreasing the computing cost required for whole-genome species demarcation afterward; () FRAGTE2 shows superior sensitivity than FRAGTE1; ( FRAGTE2 shows higher specificity than FRAGTE1; and () FRAGTE2 is faster than or comparable with FRAGTE1. Besides, FRAGTE2 is independent of genome completeness, the same as FRAGTE1. We therefore recommend FRAGTE2 tailored for sieving to facilitate species demarcation in prokaryotes.
我们之前报道过FRAGTE（以下简称FRAGTE1），这是一种用于筛选（为全基因组物种划分预先选择基因组对）的很有前景的算法。然而，FRAGTE1筛选出的基因组对总数仍然很大，需要高昂到令人难以承受的计算成本，尤其是对于大型数据集而言。在此，我们推出FRAGTE2。对模拟基因组、真实基因组和宏基因组组装基因组的测试表明：（）FRAGTE2显著减少了FRAGTE1筛选出的基因组对总数的约50 - 60.10%，极大地降低了后续全基因组物种划分所需的计算成本；（）FRAGTE2比FRAGTE1具有更高的灵敏度；（）FRAGTE2比FRAGTE1具有更高的特异性；以及（）FRAGTE2比FRAGTE1更快或与之相当。此外，与FRAGTE1一样，FRAGTE2不依赖于基因组的完整性。因此，我们推荐专门用于筛选的FRAGTE2，以促进原核生物的物种划分。
