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Perfect Match Genomic Landscape strategy: Refinement and customization of reference genomes
- Source :
- Proceedings of the National Academy of Sciences of the United States of America
- Publication Year :
- 2021
- Publisher :
- National Academy of Sciences, 2021.
-
Abstract
- Significance The accuracy of the nucleotide sequence of genomes is of utmost importance. The Perfect Match Genomic Landscape (PMGL) is a precise, sensitive, and nonstatistical strategy to detect genome variation. We used this strategy to refine reference genomes from microorganisms belonging to the three domains of life. Our studies show as well that the PMGL can be useful to detect variants in pathogen agents during a pandemic, and to isolate mutations generated during any desired stage of experimental evolution studies. We propose that the PMGL strategy could be the final step in the refinement of any haploid genome, independently of the methodology and algorithms used for its assembly.<br />When addressing a genomic question, having a reliable and adequate reference genome is of utmost importance. This drives the necessity to refine and customize reference genomes (RGs). Our laboratory has recently developed a strategy, the Perfect Match Genomic Landscape (PMGL), to detect variation between genomes [K. Palacios-Flores et al.. Genetics 208, 1631–1641 (2018)]. The PMGL is precise and sensitive and, in contrast to most currently used algorithms, is nonstatistical in nature. Here we demonstrate the power of PMGL to refine and customize RGs. As a proof-of-concept, we refined different versions of the Saccharomyces cerevisiae RG. We applied the automatic PMGL pipeline to refine the genomes of microorganisms belonging to the three domains of life: the archaea Methanococcus maripaludis and Pyrococcus furiosus; the bacteria Escherichia coli, Staphylococcus aureus, and Bacillus subtilis; and the eukarya Schizosaccharomyces pombe, Aspergillus oryzae, and several strains of Saccharomyces paradoxus. We analyzed the reference genome of the virus SARS-CoV-2 and previously published viral genomes from patients’ samples with COVID-19. We performed a mutation-accumulation experiment in E. coli and show that the PMGL strategy can detect specific mutations generated at any desired step of the whole procedure. We propose that PMGL can be used as a final step for the refinement and customization of any haploid genome, independently of the strategies and algorithms used in its assembly.
- Subjects :
- Saccharomyces cerevisiae
Computational biology
Genome
Proof of Concept Study
Mutation Accumulation
Genetics
Saccharomyces paradoxus
experimental evolution
Experimental evolution
microbial genomes
Multidisciplinary
biology
SARS-CoV-2
fungi
Genetic Variation
Methanococcus maripaludis
Genomics
Biological Sciences
biology.organism_classification
genome variation
mutation-accumulation experiments
Genome, Microbial
Schizosaccharomyces pombe
Pyrococcus furiosus
Algorithms
Reference genome
Subjects
Details
- Language :
- English
- ISSN :
- 10916490 and 00278424
- Volume :
- 118
- Issue :
- 14
- Database :
- OpenAIRE
- Journal :
- Proceedings of the National Academy of Sciences of the United States of America
- Accession number :
- edsair.doi.dedup.....727b7996c8595f72206c9f4658cfbbeb