2019
DOI: 10.1016/j.ijfoodmicro.2018.11.028
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Insights from genome-wide approaches to identify variants associated to phenotypes at pan-genome scale: Application to L. monocytogenes' ability to grow in cold conditions

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Cited by 43 publications
(32 citation statements)
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“…genes in 0% ≤ strains < 15%). These observations are consistent with previous comparative genomics studies unravelling the L. monocytogenes pangenome [48,49,54,55]. From the Phandango interactive visualization of the accessory genes based distance tree, associated metadata and the pangenome matrix (Additional file 6), five major clusters representing the CCs of L. monocytogenes genomes were identified.…”
Section: Pangenomic Extraction and Clustering Of Accessory Genes Revesupporting
confidence: 88%
“…genes in 0% ≤ strains < 15%). These observations are consistent with previous comparative genomics studies unravelling the L. monocytogenes pangenome [48,49,54,55]. From the Phandango interactive visualization of the accessory genes based distance tree, associated metadata and the pangenome matrix (Additional file 6), five major clusters representing the CCs of L. monocytogenes genomes were identified.…”
Section: Pangenomic Extraction and Clustering Of Accessory Genes Revesupporting
confidence: 88%
“…Within a range from 51 Listeria monocytogenes [29] to 3701 Streptococcus pneumoniae strains [35] and without consensus on the appropriated size of genome dataset, most of the microbial GWAS includes around 500 samples under clonal and/or panmictic status (Table 6) [43]. Contrary to human GWAS focusing on the effects of individual SNPs, microbial GWAS has also to access phenotype associations based on presence/absence of genes alongside SNPs [43].…”
Section: Methodsmentioning
confidence: 99%
“…Following the first tool computing GWAS with a correction of Eukaryotic population structure based on SNPs (PLINK) [27], combinations of different methods have been implemented in the recently developed microbial GWAS. Over the last 10 years, microbial GWAS was implemented to explore a diversity of biological problems: genetic backgrounds of microbial origin [28], persistence [29], host preference [30], virulence [31, 32], and antibiotic resistance [3342]. In comparison to human GWAS, the confounding factors of the microbial GWAS include genome selection, homologous recombination events, population structure, as well as genome wide significance [43].…”
Section: Introductionmentioning
confidence: 99%
“…The IT-OTH-CP-36 genome was compared to all the CC121 genomes available from the ANSES Laboratory for Food Safety database, including 107 genomes described by Félix et al [ 27 ], 54 genomes described by Henri et al [ 18 ], 6 by Fritsch et al [ 61 ], 29 by Palma et al [ 25 ], 143 genomes from the Liseq collection [ 17 ] and 21 new genomes specifically sequenced in the framework of this study. These genomes included 11 genomes of strains from Ireland, four from Republic of North Macedonia, four from France and two from Czech Republic.…”
Section: Methodsmentioning
confidence: 99%