2019
DOI: 10.1101/697243
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Machine-learning classification suggests that many alphaproteobacterial prophages may instead be gene transfer agents

Abstract: 21Many of the sequenced bacterial and archaeal genomes encode regions of viral provenance. Yet, not all of 22 these regions encode bona fide viruses. Gene transfer agents (GTAs) are thought to be former viruses that 23 are now maintained in genomes of some bacteria and archaea and are hypothesized to enable exchange of 24 DNA within bacterial populations. In Alphaproteobacteria, genes homologous to the 'head-tail' gene 25 cluster that encodes structural components of the Rhodobacter capsulatus GTA (RcGTA) are … Show more

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Cited by 7 publications
(30 citation statements)
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“…In the phylogenetic tree of TerLs (Figure 1), a group of 616 TerLs was labeled as the "RcGTA-like containing group." This group includes 507 TerLs of the 526 RcGTA-like TerLs that were identified and curated by Kogay et al (2019). Nineteen RcGTA-like TerLs from the dataset of Kogay et al (2019) are absent in our dataset because they were not in GenBank at the time of our data collection (December 2018).…”
Section: Identification Of Rcgta-like Large Terminasesmentioning
confidence: 99%
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“…In the phylogenetic tree of TerLs (Figure 1), a group of 616 TerLs was labeled as the "RcGTA-like containing group." This group includes 507 TerLs of the 526 RcGTA-like TerLs that were identified and curated by Kogay et al (2019). Nineteen RcGTA-like TerLs from the dataset of Kogay et al (2019) are absent in our dataset because they were not in GenBank at the time of our data collection (December 2018).…”
Section: Identification Of Rcgta-like Large Terminasesmentioning
confidence: 99%
“…This group includes 507 TerLs of the 526 RcGTA-like TerLs that were identified and curated by Kogay et al (2019). Nineteen RcGTA-like TerLs from the dataset of Kogay et al (2019) are absent in our dataset because they were not in GenBank at the time of our data collection (December 2018). The 616 TerLs were classified as either "RcGTAlike" or "virus-like" using a machine learning approach implemented in the GTA-Hunter program (Kogay et al, 2019).…”
Section: Identification Of Rcgta-like Large Terminasesmentioning
confidence: 99%
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