Phylogeographic Approaches to Characterize the Emergence of Plant Pathogens

2020 ◽  
pp. PHYTO-07-20-031
Author(s):  
David A. Rasmussen ◽  
Niklaus J. Grünwald

Phylogeography combines geographic information with phylogenetic and population genomic approaches to infer the evolutionary history of a species or population in a geographic context. This approach has been instrumental in understanding the emergence, spread, and evolution of a range of plant pathogens. In particular, phylogeography can address questions about where a pathogen originated, whether it is native or introduced, and when and how often introductions occurred. We review the theory, methods, and approaches underpinning phylogeographic inference and highlight applications providing novel insights into the emergence and spread of select pathogens. We hope that this review will be useful in assessing the power, pitfalls, and opportunities presented by various phylogeographic approaches.

mBio ◽  
2018 ◽  
Vol 9 (3) ◽  
Author(s):  
Pierre Gladieux

ABSTRACTIn a recent article, Sepúlveda et al. (mBio 8:e01339-17, 2017, https://doi.org/10.1128/mBio.01339-17) investigated the genetic structure and evolutionary history of the human pathogenHistoplasma. Using whole-genome resequencing data, Sepúlveda et al. found that theHistoplasmagenus is composed of at least four strongly differentiated lineages. Their tour de force is to use a smart combination of population genomic approaches to show that the advanced stage of intraspecific divergence observed withinHistoplasmadoes not simply reflect population structure, but instead results from previously unidentified speciation events. The four independently evolvingHistoplasmalineages are elevated to the species status and assigned names. The newly described species exhibit medically important differences in phenotype, and these findings, therefore, have important epidemiological implications. This work provides a blueprint for phylogenomic species recognition in fungi, opening the way for a new age of enlightenment in which fungal species are diagnosed using highly discriminatory tools within a hypothesis-testing framework.


2020 ◽  
Author(s):  
Jonás A. Aguirre-Liguori ◽  
Javier A. Luna-Sánchez ◽  
Jaime Gasca-Pineda ◽  
Luis E. Eguiarte

ABSTRACTMassive parallel sequencing is revolutionizing the field of molecular ecology by allowing to understand better the evolutionary history of populations and species, and to detect genomic regions that could be under selection. However, the needed economic and computational resources generate a tradeoff between the amount of loci that can be obtained and the number of populations or individuals that can be sequenced. In this work, we analyzed and compared two extensive genomic and one large microsatellite datasets consisting of empirical data. We generated different subsampling designs by changing the number of loci, individuals, populations and individuals per population to test for deviations in classic population genetics parameters (HS, FIS, FST) and landscape genetic tests (isolation by distance and environment, central abundance hypothesis). We also tested the effect of sampling different number of populations in the detection of outlier SNPs. We found that the microsatellite dataset is very sensitive to the number of individuals sampled when obtaining summary statistics. FIS was particularly sensitive to a low sampling of individuals in the genomic and microsatellite datasets. For the genomic datasets, we found that as long as many populations are sampled, few individuals and loci are needed. For all datasets we found that increasing the number of population sampled is important to obtain precise landscape genetic estimates. Finally, we corroborated that outlier tests are sensitive to the number of populations sampled. We conclude by proposing different sampling designs depending on the objectives.


Author(s):  
Dave Lutgen ◽  
Raphael Ritter ◽  
Remi-André Olsen ◽  
Holger Schielzeth ◽  
Joel Gruselius ◽  
...  

AbstractThe feasibility to sequence entire genomes of virtually any organism provides unprecedented insights into the evolutionary history of populations and species. Nevertheless, many population genomic inferences – including the quantification and dating of admixture, introgression and demographic events, and the inference of selective sweeps – are still limited by the lack of high-quality haplotype information. In this respect, the newest generation of sequencing technology now promises significant progress. To establish the feasibility of haplotype-resolved genome resequencing at population scale, we investigated properties of linked-read sequencing data of songbirds of the genus Oenanthe across a range of sequencing depths. Our results based on the comparison of downsampled (25x, 20x, 15x, 10x, 7x, and 5x) with high-coverage data (46-68x) of seven bird genomes suggest that phasing contiguities and accuracies adequate for most population genomic analyses can be reached already with moderate sequencing effort. At 15x coverage, phased haplotypes span about 90% of the genome assembly, with 50 and 90 percent of the phased sequence located in phase blocks longer than 1.25-4.6 Mb (N50) and 0.27-0.72 Mb (N90), respectively. Phasing accuracy reaches beyond 99% starting from 15x coverage. Higher coverages yielded higher contiguities (up to about 7 Mb/1Mb (N50/N90) at 25x coverage), but only marginally improved phasing accuracy. Finally, phasing contiguity improved with input DNA molecule length; thus, higher-quality DNA may help keeping sequencing costs at bay. In conclusion, even for organisms with gigabase-sized genomes like birds, linked-read sequencing at moderate depth opens an affordable avenue towards haplotype-resolved genome resequencing data at population scale.


Author(s):  
Olga Kozhar ◽  
Mee-Sook Kim ◽  
Jorge Ibarra Caballero ◽  
Ned Klopfenstein ◽  
Phil Cannon ◽  
...  

Emerging plant pathogens have been increasing exponentially over the last century. To address this issue, it is critical to determine whether these pathogens are native to ecosystems or have been recently introduced. Understanding the ecological and evolutionary processes fostering emergence can help to manage their spread and predict epidemics/epiphytotics. Using restriction site-associated DNA sequencing data, we studied genetic relationships, pathways of spread, and evolutionary history of Phellinus noxius, an emerging root-rotting fungus of unknown origin, in eastern Asia, Australia, and the Pacific Islands. We analyzed patterns of genetic variation using Bayesian inference, maximum likelihood phylogeny, populations splits and mixtures measuring correlations in allele frequencies and genetic drift, and finally applied coalescent based theory using Approximate Bayesian computation (ABC) with supervised machine learning. Population structure analyses revealed five genetic groups with signatures of complex recent and ancient migration histories. The most probable scenario of ancient pathogen spread is movement from ghost population to Malaysia and the Pacific Islands, with subsequent spread to Taiwan and Australia. Furthermore, ABC analyses indicate that P. noxius spread occurred thousands of generations ago, contradicting previous assumptions that this pathogen was recently introduced to multiple geographic regions. Our results suggest that recent emergence of P. noxius in eastern Asia, Australia, and the Pacific Islands is likely driven by anthropogenic and natural disturbances, such as deforestation, land-use change, severe weather events, and/or introduction of exotic plants. This study provides a novel example of applying genome-wide allele frequency data to unravel dynamics of pathogen emergence under changing ecosystem conditions.


eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Daniel B Weissman ◽  
Oskar Hallatschek

Samples of multiple complete genome sequences contain vast amounts of information about the evolutionary history of populations, much of it in the associations among polymorphisms at different loci. We introduce a method, Minimal-Assumption Genomic Inference of Coalescence (MAGIC), that reconstructs key features of the evolutionary history, including the distribution of coalescence times, by integrating information across genomic length scales without using an explicit model of coalescence or recombination, allowing it to analyze arbitrarily large samples without phasing while making no assumptions about ancestral structure, linked selection, or gene conversion. Using simulated data, we show that the performance of MAGIC is comparable to that of PSMC’ even on single diploid samples generated with standard coalescent and recombination models. Applying MAGIC to a sample of human genomes reveals evidence of non-demographic factors driving coalescence.


Author(s):  
Mireia Coscolla ◽  
Daniela Brites ◽  
Fabrizio Menardo ◽  
Chloe Loiseau ◽  
Sonia Borrell ◽  
...  

AbstractHuman tuberculosis is caused by members of the Mycobacterium tuberculosis Complex (MTBC). The MTBC comprises several human-adapted lineages known as M. tuberculosis sensu stricto as well as two lineages (L5 and L6) traditionally referred to as M. africanum. Strains of L5 and L6 are largely limited to West Africa for reasons unknown, and little is known on their genomic diversity, phylogeography and evolution. Here, we analyzed the genomes of 365 L5 and 326 L6 strains, plus five related genomes that had not been classified into any of the known MTBC lineages, isolated from patients from 21 African countries.Our population genomic and phylogeographical analyses show that the unclassified genomes belonged to a new group that we propose to name MTBC Lineage 9 (L9). While the most likely ancestral distribution of L9 was predicted to be East Africa, the most likely ancestral distribution for both L5 and L6 was the Eastern part of West Africa. Moreover, we found important differences between L5 and L6 strains with respect to their phylogeographical substructure, genetic diversity and association with drug resistance. In conclusion, our study sheds new light onto the genomic diversity and evolutionary history of M. africanum, and highlights the need to consider the particularities of each MTBC lineage for understanding the ecology and epidemiology of tuberculosis in Africa and globally.


2018 ◽  
Vol 41 ◽  
Author(s):  
Kevin Arceneaux

AbstractIntuitions guide decision-making, and looking to the evolutionary history of humans illuminates why some behavioral responses are more intuitive than others. Yet a place remains for cognitive processes to second-guess intuitive responses – that is, to be reflective – and individual differences abound in automatic, intuitive processing as well.


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