Linked-read sequencing enables haplotype-resolved resequencing at population scale

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.

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Updates in the Language ofHistoplasmaBiodiversity

mBio ◽

10.1128/mbio.00181-18 ◽

2018 ◽

Vol 9 (3) ◽

Author(s):

Pierre Gladieux

Keyword(s):

Evolutionary History ◽

Species Recognition ◽

Fungal Species ◽

Species Status ◽

Genome Resequencing ◽

Intraspecific Divergence ◽

Testing Framework ◽

Population Genomic ◽

History Of ◽

Whole Genome Resequencing

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.

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The Aquilegia genome: adaptive radiation and an extraordinarily polymorphic chromosome with a unique history

10.1101/264101 ◽

2018 ◽

Cited By ~ 3

Author(s):

Danièle Filiault ◽

Evangeline S. Ballerini ◽

Terezie Mandáková ◽

Gökçe Aköz ◽

Nathan Derieg ◽

...

Keyword(s):

Adaptive Radiation ◽

Evolutionary History ◽

Wide Distribution ◽

Allele Sharing ◽

Sequencing Data ◽

High Coverage ◽

The World ◽

Entire Chromosome ◽

Evolutionary Context ◽

History Of

AbstractThe columbine genus Aquilegia is a classic example of an adaptive radiation, involving a wide variety of pollinators and habitats. Here we present the genome assembly of A. coerulea ‘Goldsmith’, complemented by high-coverage sequencing data from 10 wild species covering the world-wide distribution. Our analyses reveal extensive allele sharing among species and demonstrate that introgression and selection played a role in the Aquilegia radiation. We also present the remarkable discovery that the evolutionary history of an entire chromosome differs from that of the rest of the genome – a phenomenon which we do not fully understand, but which highlights the need to consider chromosomes in an evolutionary context.

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The Aquilegia genome provides insight into adaptive radiation and reveals an extraordinarily polymorphic chromosome with a unique history

eLife ◽

10.7554/elife.36426 ◽

2018 ◽

Vol 7 ◽

Cited By ~ 29

Author(s):

Danièle L Filiault ◽

Evangeline S Ballerini ◽

Terezie Mandáková ◽

Gökçe Aköz ◽

Nathan J Derieg ◽

...

Keyword(s):

Adaptive Radiation ◽

Evolutionary History ◽

Wide Distribution ◽

Allele Sharing ◽

Sequencing Data ◽

High Coverage ◽

Entire Chromosome ◽

Evolutionary Context ◽

History Of ◽

Insight Into

The columbine genus Aquilegia is a classic example of an adaptive radiation, involving a wide variety of pollinators and habitats. Here we present the genome assembly of A. coerulea ‘Goldsmith’, complemented by high-coverage sequencing data from 10 wild species covering the world-wide distribution. Our analyses reveal extensive allele sharing among species and demonstrate that introgression and selection played a role in the Aquilegia radiation. We also present the remarkable discovery that the evolutionary history of an entire chromosome differs from that of the rest of the genome – a phenomenon that we do not fully understand, but which highlights the need to consider chromosomes in an evolutionary context.

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Pathogen emergence in changing ecosystems: RAD-seq reveals long evolutionary history of Phellinus noxius in east Asia, Australia, and the Pacific Islands

10.22541/au.162670289.98665561/v1 ◽

2021 ◽

Author(s):

Olga Kozhar ◽

Mee-Sook Kim ◽

Jorge Ibarra Caballero ◽

Ned Klopfenstein ◽

Phil Cannon ◽

...

Keyword(s):

East Asia ◽

Evolutionary History ◽

Pacific Islands ◽

Genetic Relationships ◽

Supervised Machine Learning ◽

Sequencing Data ◽

The Pacific ◽

Recent Emergence ◽

History Of ◽

Phellinus Noxius

Emerging pathogens have been increasing exponentially over the last century. The knowledge on whether these organisms are native to ecosystems or have been recently introduced is often of great importance. Understanding the ecological and evolutionary processes promoting emergence can help to control their spread and forecast epidemics. 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 west to east: from Malaysia to 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 it was recently introduced in multiple areas. Our results suggest that recent emergence of P. noxius in east Asia, Australia, and the Pacific Islands is likely driven by anthropogenic and natural disturbances, including deforestation, land-use change, severe weather events, and introduction of exotic plants. This study provides a novel example of utilization of genome wide allele frequency data to unravel dynamics of pathogen emergence under conditions of changing ecosystems.

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Population genomic analyses reveal a history of range expansion and trait evolution across the native and invaded range of yellow starthistle (Centaurea solstitialis)

Molecular Ecology ◽

10.1111/mec.13998 ◽

2017 ◽

Vol 26 (4) ◽

pp. 1131-1147 ◽

Cited By ~ 35

Author(s):

Brittany S. Barker ◽

Krikor Andonian ◽

Sarah M. Swope ◽

Douglas G. Luster ◽

Katrina M. Dlugosch

Keyword(s):

Range Expansion ◽

Centaurea Solstitialis ◽

Yellow Starthistle ◽

Trait Evolution ◽

Population Genomic ◽

Genomic Analyses ◽

History Of

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Evaluation of the minimum sampling design for population genomic and microsatellite studies. An analysis based on wild maize

10.1101/2020.03.06.980888 ◽

2020 ◽

Author(s):

Jonás A. Aguirre-Liguori ◽

Javier A. Luna-Sánchez ◽

Jaime Gasca-Pineda ◽

Luis E. Eguiarte

Keyword(s):

Evolutionary History ◽

Isolation By Distance ◽

Molecular Ecology ◽

Population Genomic ◽

History Of ◽

Outlier Tests ◽

Landscape Genetic ◽

Genomic Regions ◽

Computational Resources ◽

Number Of Individuals

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.

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Long evolutionary history of an emerging fungal pathogen of diverse tree species in eastern Asia, Australia, and the Pacific Islands

10.22541/au.164079355.56023358/v1 ◽

2021 ◽

Author(s):

Olga Kozhar ◽

Mee-Sook Kim ◽

Jorge Ibarra Caballero ◽

Ned Klopfenstein ◽

Phil Cannon ◽

...

Keyword(s):

Evolutionary History ◽

Plant Pathogens ◽

Pacific Islands ◽

Genetic Relationships ◽

Supervised Machine Learning ◽

Sequencing Data ◽

Eastern Asia ◽

The Pacific ◽

Recent Emergence ◽

History Of

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.

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Phylogeographic Approaches to Characterize the Emergence of Plant Pathogens

Phytopathology ◽

10.1094/phyto-07-20-0319-fi ◽

2020 ◽

pp. PHYTO-07-20-031

Author(s):

David A. Rasmussen ◽

Niklaus J. Grünwald

Keyword(s):

Evolutionary History ◽

Plant Pathogens ◽

Geographic Information ◽

Geographic Context ◽

Population Genomic ◽

History Of

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.

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Minimal-assumption inference from population-genomic data

eLife ◽

10.7554/elife.24836 ◽

2017 ◽

Vol 6 ◽

Cited By ~ 15

Author(s):

Daniel B Weissman ◽

Oskar Hallatschek

Keyword(s):

Evolutionary History ◽

Simulated Data ◽

Large Samples ◽

Minimal Assumption ◽

Population Genomic ◽

Human Genomes ◽

History Of ◽

Or Gene ◽

Linked Selection ◽

Genomic Length

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.

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Iroki: automatic customization and visualization of phylogenetic trees

10.1101/106138 ◽

2017 ◽

Cited By ~ 7

Author(s):

Ryan M. Moore ◽

Amelia O. Harrison ◽

Sean M. McAllister ◽

Shawn W. Polson ◽

K. Eric Wommack

Keyword(s):

Web Application ◽

Phylogenetic Trees ◽

Evolutionary History ◽

Phylogenetic Analyses ◽

Community Diversity ◽

Sequencing Data ◽

Link Type ◽

Large Trees ◽

History Of ◽

Microbial Groups

ABSTRACTPhylogenetic trees are an important analytical tool for evaluating community diversity and evolutionary history. In the case of microorganisms, the decreasing cost of sequencing has enabled researchers to generate ever-larger sequence datasets, which in turn have begun to fill gaps in the evolutionary history of microbial groups. However, phylogenetic analyses of these types of datasets create complex trees that can be challenging to interpret. Scientific inferences made by visual inspection of phylogenetic trees can be simplified and enhanced by customizing various parts of the tree. Yet, manual customization is time-consuming and error prone, and programs designed to assist in batch tree customization often require programming experience or complicated file formats for annotation. Iroki, a user-friendly web interface for tree visualization, addresses these issues by providing automatic customization of large trees based on metadata contained in tab-separated text files. Iroki’s utility for exploring biological and ecological trends in sequencing data was demonstrated through a variety of microbial ecology applications in which trees with hundreds to thousands of leaf nodes were customized according to extensive collections of metadata. The Iroki web application and documentation are available at https://www.iroki.net or through the VIROME portal (http://virome.dbi.udel.edu). Iroki’s source code is released under the MIT license and is available at https://github.com/mooreryan/iroki.

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