Institut de Biologia Evolutiva (CSIC-Universitat Pompeu Fabra), Passeig Marítim de la Barceloneta 37-49, 08003, Barcelona, Catalonia, Spain.
Departament de Genètica, Microbiologia i Estadística, Universitat de Barcelona, Barcelona, Catalonia, Spain.
Sci Rep. 2017 Sep 8;7(1):11025. doi: 10.1038/s41598-017-11466-9.
Single-cell genomics (SCG) appeared as a powerful technique to get genomic information from uncultured organisms. However, SCG techniques suffer from biases at the whole genome amplification step that can lead to extremely variable numbers of genome recovery (5-100%). Thus, it is unclear how useful can SCG be to address evolutionary questions on uncultured microbial eukaryotes. To provide some insights into this, we here analysed 3 single-cell amplified genomes (SAGs) of the choanoflagellate Monosiga brevicollis, whose genome is known. Our results show that each SAG has a different, independent bias, yielding different levels of genome recovery for each cell (6-36%). Genes often appear fragmented and are split into more genes during annotation. Thus, analyses of gene gain and losses, gene architectures, synteny and other genomic features can not be addressed with a single SAG. However, the recovery of phylogenetically-informative protein domains can be up to 55%. This means SAG data can be used to perform accurate phylogenomic analyses. Finally, we also confirm that the co-assembly of several SAGs improves the general genomic recovery. Overall, our data show that, besides important current limitations, SAGs can still provide interesting and novel insights from poorly-known, uncultured organisms.
单细胞基因组学(SCG)作为一种从未培养的生物体中获取基因组信息的强大技术出现。然而,SCG 技术在全基因组扩增步骤中存在偏差,这可能导致基因组回收率极不稳定(5-100%)。因此,单细胞基因组学对于解决未培养微生物真核生物的进化问题有多大作用尚不清楚。为了对此提供一些见解,我们在此分析了已知基因组的领鞭虫 Monosiga brevicollis 的 3 个单细胞扩增基因组(SAG)。我们的结果表明,每个 SAG 都有不同的、独立的偏差,导致每个细胞的基因组回收率不同(6-36%)。在注释过程中,基因经常出现碎片化,并分裂成更多的基因。因此,对基因获得和丢失、基因结构、基因同线性和其他基因组特征的分析不能仅通过单个 SAG 来进行。然而,系统发育信息丰富的蛋白质结构域的回收率最高可达 55%。这意味着 SAG 数据可用于进行准确的系统基因组分析。最后,我们还证实了多个 SAG 的共组装可以提高整体基因组回收率。总体而言,我们的数据表明,除了当前的重要限制外,SAG 仍然可以为了解甚少的未培养生物提供有趣和新颖的见解。