Evaluation of single-cell genomics to address evolutionary questions using three SAGs of the choanoflagellate Monosiga brevicollis. Lopez-Escardo, D., Grau-Bove, X., Guillaumet-Adkins, A., Gut, M., Sieracki, M. E., & Ruiz-Trillo, I. Sci Rep, 7(1):11025, 2017. Lopez-Escardo, David Grau-Bove, Xavier Guillaumet-Adkins, Amy Gut, Marta Sieracki, Michael E Ruiz-Trillo, Inaki eng Evaluation Study Research Support, Non-U.S. Gov't England Sci Rep. 2017 Sep 8;7(1):11025. doi: 10.1038/s41598-017-11466-9.![Evaluation of single-cell genomics to address evolutionary questions using three SAGs of the choanoflagellate Monosiga brevicollis [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex 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.
@article{RN89,
author = {Lopez-Escardo, D. and Grau-Bove, X. and Guillaumet-Adkins, A. and Gut, M. and Sieracki, M. E. and Ruiz-Trillo, I.},
title = {Evaluation of single-cell genomics to address evolutionary questions using three SAGs of the choanoflagellate Monosiga brevicollis},
journal = {Sci Rep},
volume = {7},
number = {1},
pages = {11025},
note = {Lopez-Escardo, David
Grau-Bove, Xavier
Guillaumet-Adkins, Amy
Gut, Marta
Sieracki, Michael E
Ruiz-Trillo, Inaki
eng
Evaluation Study
Research Support, Non-U.S. Gov't
England
Sci Rep. 2017 Sep 8;7(1):11025. doi: 10.1038/s41598-017-11466-9.},
abstract = {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.},
keywords = {Choanoflagellata/classification/*genetics/*isolation & purification
Computational Biology
DNA, Protozoan/*genetics/*isolation & purification
Genomics/*methods
Single-Cell Analysis/*methods
Whole Genome Sequencing},
ISSN = {2045-2322 (Electronic)
2045-2322 (Linking)},
DOI = {10.1038/s41598-017-11466-9},
url = {https://www.ncbi.nlm.nih.gov/pubmed/28887541},
year = {2017},
type = {Journal Article}
}
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