Editing Plasmid (section)

===Sequence-based plasmid typing===
With the wider availability of whole genome sequencing which is able to capture the genetic sequence of plasmids, methods have been developed to cluster or type plasmids based on their sequence content. Plasmid multi-locus sequence typing (pMLST) is based on chromosomal [[Multilocus sequence typing]] by matching the sequence of replication machinery genes to databases of previously classified sequences. If the sequence [[allele]] matches the database, this is used as the plasmid classification, and therefore has higher sensitivity than a simple presence or absence test of these genes.<ref name="Carattoli_2014" />

A related method is to use [[average nucleotide identity]] between plasmids to find close genetic neighbours. Tools which use this approach include COPLA<ref name="RedondoSalvo_2021">{{cite journal | vauthors = Redondo-Salvo S, Bartomeus-Peñalver R, Vielva L, Tagg KA, Webb HE, Fernández-López R, de la Cruz F | title = COPLA, a taxonomic classifier of plasmids | journal = BMC Bioinformatics | volume = 22 | issue = 1 | pages = 390 | date = 2021 | doi = 10.1186/s12859-021-04299-x | doi-access = free | pmid = 34332528 | pmc = 8325299 }}</ref> and MOB-cluster.<ref name="Robertson_2018">{{cite journal | vauthors = Robertson J, Nash J | title = MOB-suite: software tools for clustering, reconstruction and typing of plasmids from draft assemblies | journal = Microbial Genomics | volume = 4 | issue = 8 | date = 2018 | doi = 10.1099/mgen.0.000206 | doi-access = free | pmid = 30052170 | pmc = 6159552 }}</ref>

Creating typing classifications using [[unsupervised learning]], that is without a pre-existing database or 'reference-free', has been shown to be useful in grouping plasmids in new datasets without biasing or being limited to representations in a pre-built database—tools to do this include mge-cluster.<ref name="ArredondoAlonso_2023">{{cite journal | vauthors = Arredondo-Alonso S, Gladstone RA, Pöntinen AK, Gama JA, Schürch AC, Lanza VF, Johnsen PJ, Samuelsen Ø, Tonkin-Hill G, Corander J | title = Mge-cluster: a reference-free approach for typing bacterial plasmids | journal = NAR Genomics and Bioinformatics | volume = 5 | issue = 3 | pages = lqad066 | date = 2023 | doi = 10.1093/nargab/lqad066 | pmid = 37435357 | pmc = 10331934 }}</ref> As plasmid frequently change their gene content and order, modelling genetic distances between them using methods designed for point mutations can lead to poor estimates of the true evolutionary distance between plasmids. Tools such as pling find homologous sequence regions between plasmids, and more accurately reconstruct the number of evolutionary events ([[structural variants]]) between each pair, then use unsupervised clustering apporaches to group plasmids.<ref name="Frolova_2024">{{cite journal | vauthors = Frolova D, Lima L, Roberts LW, Bohnenkämper L, Wittler R, Stoye J, Iqbal Z | title = Applying rearrangement distances to enable plasmid epidemiology with pling | journal = Microbial Genomics | volume = 10 | issue = 10 | pages = 001300 | date = 2024 | doi = 10.1099/mgen.0.001300 | doi-access = free | pmid = 39401066 | pmc = 11472880 }}</ref>