Strange RN, Scott PR. Plant disease: a threat to global food security. Annu Rev Phytopathol. 2005;43:83–116.
Google Scholar
Savary S, Willocquet L, Pethybridge SJ, Esker P, McRoberts N, Nelson A. The global burden of pathogens and pests on major food crops. Nat Ecol Evol. 2019;3:430–9.
Google Scholar
Savary S, Bregaglio S, Willocquet L, Gustafson D, Mason D’Croz D, Sparks A, et al. Crop health and its global impacts on the components of food security. Food Secur. 2017;9:311–27.
Google Scholar
Garrett KA, Alcalá-Briseño RI, Andersen KF, Buddenhagen CE, Choudhury RA, Fulton JC, et al. Network analysis: a systems framework to address grand challenges in plant pathology. Annu Rev Phytopathol. 2018;56:559–80.
Google Scholar
Pautasso M, Xu X, Jeger MJ, Harwood TD, Moslonka-Lefebvre M, Pellis L. Disease spread in small-size directed trade networks: the role of hierarchical categories. J Appl Ecol. 2010;47:1300–9.
Google Scholar
Bryant JM, Grogono DM, Rodriguez-Rincon D, Everall I, Brown KP, Moreno P, et al. Emergence and spread of a human-transmissible multidrug-resistant nontuberculous mycobacterium. Science. 2016;354:751–7.
Google Scholar
Yang C, Zhang X, Fan H, Li Y, Hu Q, Yang R, et al. Genetic diversity, virulence factors and farm-to-table spread pattern of Vibrio parahaemolyticus food-associated isolates. Food Microbiol. 2019;84:103270.
Google Scholar
Dallman TJ, Byrne L, Ashton PM, Cowley LA, Perry NT, Adak G, et al. Whole-genome sequencing for national surveillance of Shiga toxin-producing Escherichia coli O157. Clin Infect Dis. 2015;61:305–12.
Google Scholar
Kwong JC, Mercoulia K, Tomita T, Easton M, Li HY, Bulach DM, et al. Prospective whole-genome sequencing enhances national surveillance of Listeria monocytogenes. J Clin Microbiol. 2016;54:333–42.
Google Scholar
Mather AE, Reid SW, Maskell DJ, Parkhill J, Fookes MC, Harris SR, et al. Distinguishable epidemics of multidrug-resistant Salmonella Typhimurium DT104 in different hosts. Science. 2013;341:1514–7.
Google Scholar
Richards VP, Velsko IM, Alam T, Zadoks RN, Manning SD, Pavinski Bitar PD, et al. Population gene introgression and high genome plasticity for the zoonotic pathogen Streptococcus agalactiae. Mol Biol Evol. 2019;36:2572–90.
Google Scholar
Mellor KC, Petrovska L, Thomson NR, Harris K, Reid SWJ, Mather AE. Antimicrobial resistance diversity suggestive of distinct Salmonella Typhimurium sources or selective pressures in food-production animals. Front Microbiol. 2019;10:708.
Google Scholar
Monteil CL, Yahara K, Studholme DJ, Mageiros L, Méric G, Swingle B, et al. Population-genomic insights into emergence, crop adaptation and dissemination of Pseudomonas syringae pathogens. Micro Genom. 2016;2:e000089.
Perez-Quintero AL, Ortiz-Castro M, Lang JM, Rieux A, Wu G, Liu S, et al. Genomic acquisitions in emerging populations of Xanthomonas vasicola pv. vasculorum infecting corn in the United States and Argentina. Phytopathology. 2020;110:1161–73.
Google Scholar
McCann HC, Li L, Liu Y, Li D, Pan H, Zhong C, et al. Origin and evolution of the kiwifruit canker pandemic. Genome Biol Evol. 2017;9:932–44.
Google Scholar
Quibod IL, Atieza-Grande G, Oreiro EG, Palmos D, Nguyen MH, Coronejo ST, et al. The Green Revolution shaped the population structure of the rice pathogen Xanthomonas oryzae pv. oryzae. ISME J. 2020;14:492–505.
Google Scholar
Straub C, Colombi E, McCann H. Population genomics of bacterial plant pathogens. Phytopathology. 2021. https://doi.org/10.1094/PHYTO-09-20-0412-RVW.
Vinatzer BA, Monteil CL, Clarke CR. Harnessing population genomics to understand how bacterial pathogens emerge, adapt to crop hosts, and disseminate. Ann Rev Phytopathol. 2014;52:19–43.
Google Scholar
Weisberg AJ, Davis EW, Tabima JF, Belcher MS, Miller M, Kuo C, et al. Unexpected conservation and global transmission of agrobacterial virulence plasmids. Science. 2020;368:eaba5256.
Google Scholar
Jones JB, Lacy GH, Bouzar H, Stall RE, Schaad NW. Reclassification of the xanthomonads associated with bacterial spot disease of tomato and pepper. Syst Appl Microbiol. 2004;27:755–62.
Google Scholar
Potnis N, Timilsina S, Strayer A, Shantharaj D, Barak JD, Paret ML, et al. Bacterial spot of tomato and pepper: diverse Xanthomonas species with a wide variety of virulence factors posing a worldwide challenge. Mol Plant Pathol. 2015;16:907–20.
Google Scholar
VanSickle J, Weldon R. The economic impact of bacterial leaf spot on the tomato industry. Tomato Inst Proc. 2009:30–31 https://plantpath.ifas.ufl.edu/rsol/RalstoniaPublications_PDF/Tomato_Institute_Proceedings_09.pdf.
Horvath DM, Stall RE, Jones JB, Pauly MH, Vallad GE, Dahlbeck D, et al. Transgenic resistance confers effective field level control of bacterial spot disease in tomato. PLOS One. 2012;7:e42036.
Google Scholar
Kunwar S, Iriarte F, Fan Q, Evaristo da Silva E, Ritchie L, Nguyen NS, et al. Transgenic expression of EFR and Bs2 genes for field management of bacterial wilt and bacterial spot of tomato. Phytopathology. 2018;108:1402–11.
Google Scholar
Jones JB, Bouzar H, Somodi GC, Stall RE, Pernezny K, El-Morsy G, et al. Evidence for the preemptive nature of tomato race 3 of Xanthomonas campestris pv. vesicatoria in Florida. Phytopathology. 1998;88:33–38.
Google Scholar
Timilsina S, Jibrin MO, Potnis N, Minsavage GV, Kebede M, Schwartz A, et al. Multilocus sequence analysis of xanthomonads causing bacterial spot of tomato and pepper plants reveals strains generated by recombination among species and recent global spread of Xanthomonas gardneri. Appl Environ Microbiol. 2015;81:1520–9.
Google Scholar
United States Department of Agriculture. National Agricultural Statistics Service. Washington, DC: United States Department of Agriculture; 2019.
Klein-Gordon JM, Xing Y, Garrett KA, Abrahamian P, Paret ML, Minsavage GV, et al. Assessing changes and associations in the Xanthomonas perforans population across Florida commercial tomato fields via a state-wide survey. Phytopathology. 2021;111:1029–1041.
Vallad GE, Timilsina S, Adkison H, Potnis N, Minsavage G, Jones J, et al. A recent survey of xanthomonads causing bacterial spot of tomato in Florida provides insights into management strategies. Tomato Inst Proc. 2013:25–27 https://swfrec.ifas.ufl.edu/docs/pdf/veghort/tomato-institute/proceedings/ti13_proceedings.pdf.
Timilsina S, Pereira-Martin JA, Minsavage GV, Iruegas-Bocardo F, Abrahamian P, Potnis N, et al. Multiple recombination events drive the current genetic structure of Xanthomonas perforans in Florida. Front Microbiol. 2019;10:448.
Google Scholar
Burlakoti R, Hsu C, Chen J, Wang J. Population dynamics of Xanthomonads associated with bacterial spot of tomato and pepper during twenty-seven years across Taiwan. Plant Dis. 2018;102:1348–56.
Google Scholar
Araújo ER, Costa JR, Ferreira MASV, Quezada-Duval AM. Widespread distribution of Xanthomonas perforans and limited presence of X. gardneri in Brazil. Plant Pathol. 2017;66:159–68.
Google Scholar
Jones JB, Pohronezny KL, Stall RE, Jones JP. Survival of Xanthomonas campestris pv. vesicatoria in Florida on tomato crop residue, weeds, seeds, and volunteer tomato plants. Phytopathology. 1986;76:430–4.
Google Scholar
Sijam K, Chang CJ, Gitaitis RD. An agar medium for the isolation and identification of Xanthomonas campestris pv. vesicatoria from seed. Phytopathology. 1991;81:831–4.
Google Scholar
Abrahamian P, Timilsina S, Minsavage GV, Potnis N, Jones JB, Goss EM, et al. Molecular epidemiology of Xanthomonas perforans outbreaks in tomato plants from transplant to field as determined by single-nucleotide polymorphism analysis. Appl Environ Microbiol. 2019;85:e01220–01219.
Google Scholar
Abrahamian P, Sharma A, Jones J, Vallad GE. Dynamics and spread of bacterial spot epidemics in tomato transplants grown for field production. Plant Dis. 2021 in press.
Baym M, Kryazhimskiy S, Lieberman TD, Chung H, Desai MM, Kishony R. Inexpensive multiplexed library preparation for megabase-sized genomes. PLOS One. 2015;10:e0128036.
Google Scholar
Tudor-Nelson SM, Minsavage GV, Stall RE, Jones JB. Bacteriocin-like substances from tomato race 3 strains of Xanthomonas campestris pv. vesicatoria. Bacteriology. 2003;93:1415–21.
Google Scholar
Schwartz A, Potnis N, Timilsina S, Wilson M, Patane J, Martins J, et al. Phylogenomics of Xanthomonas field strains infecting pepper and tomato reveals diversity in effector repertoires and identifies determinants of host specificity. Front Microbiol. 2015;6:535.
Google Scholar
Nurk S, Bankevich A, Antipov D, Gurevich AA, Korobeynikov A, Lapidus A, et al. Assembling single-cell genomes and mini-metagenomes from chimeric MDA products. J Comput Biol. 2013;20:714–37.
Google Scholar
Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9:357–9.
Google Scholar
Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The sequence alignment/map format and SAMtools. Bioinform. 2009;25:2078–9.
Google Scholar
Walker BJ, Abeel T, Shea T, Priest M, Abouelliel A, Sakthikumar S, et al. Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLOS One. 2014;9:e112963.
Google Scholar
Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 2015;25:1043–55.
Google Scholar
Chen IA, Chu K, Palaniappan K, Pillay M, Ratner A, Huang J, et al. IMG/M v.5.0: an integrated data management and comparative analysis system for microbial genomes and microbiomes. Nucleic Acids Res. 2019;47:D666–d677. D1
Google Scholar
Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014;30:2068–9.
Google Scholar
Katoh K, Standley DM. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol. 2013;30:772–80.
Google Scholar
Rice P, Longden I, Bleasby A. EMBOSS: the European molecular biology open software suite. Trends Genet. 2000;16:276–7.
Google Scholar
Darriba D, Posada D, Kozlov AM, Stamatakis A, Morel B, Flouri T. ModelTest-NG: a new and scalable tool for the selection of DNA and protein evolutionary models. Mol Biol Evol. 2019;37:291–4.
Google Scholar
Stamatakis A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics. 2014;30:1312–3.
Google Scholar
Stamatakis A, Hoover P, Rougemont J. A rapid bootstrap algorithm for the RAxML web servers. Syst Biol. 2008;57:758–71.
Google Scholar
Didelot X, Wilson DJ. ClonalFrameML: efficient inference of recombination in whole bacterial genomes. PLOS Comput Biol. 2015;11:e1004041.
Google Scholar
Tonkin-Hill G, Lees JA, Bentley SD, Frost SDW, Corander J. RhierBAPS: an R implementation of the population clustering algorithm hierBAPS. Wellcome Open Res. 2018;3:93.
Google Scholar
Cheng L, Connor TR, Sirén J, Aanensen DM, Corander J. Hierarchical and spatially explicit clustering of DNA sequences with BAPS software. Mol Biol Evol. 2013;30:1224–8.
Google Scholar
Letunic I, Bork P. Interactive Tree Of Life (iTOL): an online tool for phylogenetic tree display and annotation. Bioinformatics. 2007;23:127–8.
Google Scholar
Csardi G, Nepusz T. The igraph software package for complex network research. 2006; InterJ., Complex Systems:1695.
R Core Team. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2020.
Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009;25:1754–60.
Google Scholar
Canteros BI, Minsavage GV, Jones JB, Stall RE. Diversity of plasmids in Xanthomonas campestris pv. vesicatoria. Phytopathology. 1995;85:1482–6.
Google Scholar
Li H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv. 2013. https://arxiv.org/abs/1303.3997.
Broad Institute: Picard. http://broadinstitute.github.io/picard/ 2019.
Garrison E, Marth G. Haplotype-based variant detection from short-read sequencing. arXiv. 2012. https://arxiv.org/abs/1207.3907.
Garrison, E, Kronenberg, ZN, Dawson, ET, Pedersen, BS, Prins, P. Vcflib and tools for processing the VCF variant call format. BioRxiv. 2021.
Li H. Tabix: fast retrieval of sequence features from generic TAB-delimited files. Bioinformatics. 2011;27:718–9.
Google Scholar
Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, et al. The variant call format and VCFtools. Bioinformatics. 2011;27:2156–8.
Google Scholar
Cingolani P, Platts A, Wang LL, Coon M, Nguyen T, Wang L, et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff. Fly. 2012;6:80–92.
Google Scholar
R Core Team. A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2019.
RStudio Team. RStudio: Integrated Development for R. Boston, MA: RStudio Inc.; 2016.
Knaus B, Grünwald NJ. vcfR: a package to manipulate and visualize variant call format data in R. Mol Ecol Res. 2017;17:44–53.
Google Scholar
Jombart T. adegenet: a R package for the multivariate analysis of genetic markers. Bioinform. 2008;24:1403–5.
Google Scholar
Kamvar ZN, Tabima JF, Grünwald NJ. Poppr: an R package for genetic analysis of populations with clonal, partially clonal, and/or sexual reproduction. PeerJ. 2014;2:e281.
Google Scholar
Grünwald NJ, Kamvar ZN, Everhart SE. Population genetics and genomics in R: Discriminant analysis of principal components (DAPC). 2020. https://grunwaldlab.github.io/Population_Genetics_in_R/DAPC.html.
Wickham H. ggplot2: elegant graphics for data analysis. New York: Springer-Verlag; 2016.
Tabima JF, Knaus B, Grünwald NJ. Population genetics and genomics in R: GBS analysis. 2020. https://grunwaldlab.github.io/Population_Genetics_in_R/gbs_analysis.html.
Dray S, Dufour A. The ade4 package: implementing the duality diagram for ecologists. J Stat Softw. 2007;22:1–20.
Google Scholar
Kamvar ZN, Everhart SE, Grünwald NJ. Population genetics and genomics in R: AMOVA. 2020. https://grunwaldlab.github.io/Population_Genetics_in_R/AMOVA.html.
Rozas J, Ferrer-Mata A, Sanchez-DelBarrio JC, Guirao-Rico S, Librado P, Ramos-Onsins SE, et al. DnaSP 6: DNA sequence polymorphism analysis of large data sets. Mol Biol Evol. 2017;34:3299–302.
Google Scholar
Lischer HE, Excoffier L. PGDSpider: an automated data conversion tool for connecting population genetics and genomics programs. Bioinformatics. 2012;28:298–9.
Google Scholar
Excoffier L, Lischer HEL. Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Mol Ecol Resour. 2010;10:564–7.
Google Scholar
Newberry EA, Bhandari R, Minsavage GV, Timilsina S, Jibrin MO, Kemble J, et al. Independent evolution with the gene flux originating from multiple Xanthomonas species explains genomic heterogeneity in Xanthomonas perforans. Appl Environ Microbiol. 2019;85:e00885–19.
Jibrin MO, Potnis N, Timilsina S, Minsavage GV, Vallad GE, Roberts PD, et al. Genomic inference of recombination-mediated evolution in Xanthomonas euvesicatoria and X. perforans. Appl Environ Microbiol. 2018; 84:e00136–18.
Source: Ecology - nature.com