The phylogenomics and evolutionary dynamics of the organellar genomes in carnivorous Utricularia and Genlisea species (Lentibulariaceae).

Utricularia and Genlisea are highly specialized carnivorous plants whose phylogenetic history has been poorly explored using phylogenomic methods. Additional sampling and genomic data are needed to advance our phylogenetic and taxonomic knowledge of this group of plants. Within a comparative framework, we present a characterization of plastome (PT) and mitochondrial (MT) genes of 26 Utricularia and six Genlisea species, with representatives of all subgenera and growth habits. All PT genomes maintain similar gene content, showing minor variation across the genes located between the PT junctions. One exception is a major variation related to different patterns in the presence and absence of ndh genes in the small single copy region, which appears to follow the phylogenetic history of the species rather than their lifestyle. All MT genomes exhibit similar gene content, with most differences related to a lineage-specific pseudogenes. We find evidence for episodic positive diversifying selection in PT and for most of the Utricularia MT genes that may be related to the current hypothesis that bladderworts' nuclear DNA is under constant ROS oxidative DNA damage and unusual DNA repair mechanisms, or even low fidelity polymerase that bypass lesions which could also be affecting the organellar genomes. Finally, both PT and MT phylogenetic trees were well resolved and highly supported, providing a congruent phylogenomic hypothesis for Utricularia and Genlisea clade given the study sampling.

TopHap: rapid inference of key phylogenetic structures from common haplotypes in large genome collections with limited diversity.

MOTIVATION: Building reliable phylogenies from very large collections of sequences with a limited number of phylogenetically informative sites is challenging because sequencing errors and recurrent/backward mutations interfere with the phylogenetic signal, confounding true evolutionary relationships. Massive global efforts of sequencing genomes and reconstructing the phylogeny of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains exemplify these difficulties since there are only hundreds of phylogenetically informative sites but millions of genomes. For such datasets, we set out to develop a method for building the phylogenetic tree of genomic haplotypes consisting of positions harboring common variants to improve the signal-to-noise ratio for more accurate and fast phylogenetic inference of resolvable phylogenetic features. RESULTS: We present the TopHap approach that determines spatiotemporally common haplotypes of common variants and builds their phylogeny at a fraction of the computational time of traditional methods. We develop a bootstrap strategy that resamples genomes spatiotemporally to assess topological robustness. The application of TopHap to build a phylogeny of 68 057 SARS-CoV-2 genomes (68KG) from the first year of the pandemic produced an evolutionary tree of major SARS-CoV-2 haplotypes. This phylogeny is concordant with the mutation tree inferred using the co-occurrence pattern of mutations and recovers key phylogenetic relationships from more traditional analyses. We also evaluated alternative roots of the SARS-CoV-2 phylogeny and found that the earliest sampled genomes in 2019 likely evolved by four mutations of the most recent common ancestor of all SARS-CoV-2 genomes. An application of TopHap to more than 1 million SARS-CoV-2 genomes reconstructed the most comprehensive evolutionary relationships of major variants, which confirmed the 68KG phylogeny and provided evolutionary origins of major and recent variants of concern. AVAILABILITY AND IMPLEMENTATION: TopHap is available at https://github.com/SayakaMiura/TopHap. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

TopHap: Rapid inference of key phylogenetic structures from common haplotypes in large genome collections with limited diversity.

MOTIVATION: Building reliable phylogenies from very large collections of sequences with a limited number of phylogenetically informative sites is challenging because sequencing errors and recurrent/backward mutations interfere with the phylogenetic signal, confounding true evolutionary relationships. Massive global efforts of sequencing genomes and reconstructing the phylogeny of SARS-CoV-2 strains exemplify these difficulties since there are only hundreds of phylogenetically informative sites and millions of genomes. For such datasets, we set out to develop a method for building the phylogenetic tree of genomic haplotypes consisting of positions harboring common variants to improve the signal-to-noise ratio for more accurate phylogenetic inference of resolvable phylogenetic features. RESULTS: We present the TopHap approach that determines spatiotemporally common haplotypes of common variants and builds their phylogeny at a fraction of the computational time of traditional methods. To assess topological robustness, we develop a bootstrap resampling strategy that resamples genomes spatiotemporally. The application of TopHap to build a phylogeny of 68,057 genomes (68KG) produced an evolutionary tree of major SARS-CoV-2 haplotypes. This phylogeny is concordant with the mutation tree inferred using the co-occurrence pattern of mutations and recovers key phylogenetic relationships from more traditional analyses. We also evaluated alternative roots of the SARS-CoV-2 phylogeny and found that the earliest sampled genomes in 2019 likely evolved by four mutations of the most recent common ancestor of all SARS-CoV-2 genomes. An application of TopHap to more than 1 million genomes reconstructed the most comprehensive evolutionary relationships of major variants, which confirmed the 68KG phylogeny and provided evolutionary origins of major variants of concern. AVAILABILITY: TopHap is available on the web at https://github.com/SayakaMiura/TopHap . CONTACT: s.kumar@temple.edu.

An Evolutionary Portrait of the Progenitor SARS-CoV-2 and Its Dominant Offshoots in COVID-19 Pandemic.

Global sequencing of genomes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has continued to reveal new genetic variants that are the key to unraveling its early evolutionary history and tracking its global spread over time. Here we present the heretofore cryptic mutational history and spatiotemporal dynamics of SARS-CoV-2 from an analysis of thousands of high-quality genomes. We report the likely most recent common ancestor of SARS-CoV-2, reconstructed through a novel application and advancement of computational methods initially developed to infer the mutational history of tumor cells in a patient. This progenitor genome differs from genomes of the first coronaviruses sampled in China by three variants, implying that none of the earliest patients represent the index case or gave rise to all the human infections. However, multiple coronavirus infections in China and the United States harbored the progenitor genetic fingerprint in January 2020 and later, suggesting that the progenitor was spreading worldwide months before and after the first reported cases of COVID-19 in China. Mutations of the progenitor and its offshoots have produced many dominant coronavirus strains that have spread episodically over time. Fingerprinting based on common mutations reveals that the same coronavirus lineage has dominated North America for most of the pandemic in 2020. There have been multiple replacements of predominant coronavirus strains in Europe and Asia as well as continued presence of multiple high-frequency strains in Asia and North America. We have developed a continually updating dashboard of global evolution and spatiotemporal trends of SARS-CoV-2 spread (http://sars2evo.datamonkey.org/).

An evolutionary portrait of the progenitor SARS-CoV-2 and its dominant offshoots in COVID-19 pandemic.

We report the likely most recent common ancestor of SARS-CoV-2 - the coronavirus that causes COVID-19. This progenitor SARS-CoV-2 genome was recovered through a novel application and advancement of computational methods initially developed to reconstruct the mutational history of tumor cells in a patient. The progenitor differs from the earliest coronaviruses sampled in China by three variants, implying that none of the earliest patients represent the index case or gave rise to all the human infections. However, multiple coronavirus infections in China and the USA harbored the progenitor genetic fingerprint in January 2020 and later, suggesting that the progenitor was spreading worldwide as soon as weeks after the first reported cases of COVID-19. Mutations of the progenitor and its offshoots have produced many dominant coronavirus strains, which have spread episodically over time. Fingerprinting based on common mutations reveals that the same coronavirus lineage has dominated North America for most of the pandemic. There have been multiple replacements of predominant coronavirus strains in Europe and Asia and the continued presence of multiple high-frequency strains in Asia and North America. We provide a continually updating dashboard of global evolution and spatiotemporal trends of SARS-CoV-2 spread (http://sars2evo.datamonkey.org/).

Transmitted HIV type 1 drug resistance among individuals with recent HIV infection in East and Southern Africa.

To characterize WHO-defined transmitted HIV drug resistance mutation (TDRM) data from recently HIV-infected African volunteers, we sequenced HIV (pol) and evaluated for TDRM the earliest available specimens from ARV-naive volunteers diagnosed within 1 year of their estimated date of infection at eight research centers in sub-Saharan Africa. TDRMs were detected in 19/408 (5%) volunteers. The prevalence of TDRMs varied by research center, from 5/26 (19%) in Entebbe, 6/78 (8%) in Kigali, 2/49 (4%) in Kilifi, to 3/106 (3%) in Lusaka. One of five volunteers from Cape Town (20%) had TDRMs. Despite small numbers, our data suggest an increase in DRMs by year of infection in Zambia (p = 0.004). The prevalence observed in Entebbe was high across the entire study. ARV history data from 12 (63%) HIV-infected sexual partners were available; 3 reported ARV use prior to transmission. Among four partners with sequence data available, transmission linkage was confirmed and two had the same TDRMs as the newly infected volunteer (both K103N). As ARV therapy continues to increase in availability throughout Africa, monitoring incident virus strains for the presence of TDRMs should be a priority. Early HIV infection cohorts provide an excellent and important platform to monitor the development of TDRMs to inform treatment guidelines, drug choices, and strategies for secondary prevention of TDRM transmission.