Population identification and genetic diversity analysis of Fritillaria ussuriensis (Fritillaria) based on chloroplast genes atpF and petB

The chloroplast genomes of five Fritillaria ussuriensis materials from different production areas were comparatively analyzed, atpF and petB were screened as specific DNA barcodes, and the population identification and genetic diversity of F. ussuriensis were analyzed based on them. The F. ussuriensis chloroplast genome showed a total length of 151 515-151 548 bp with a typical tetrad structure and encoded 130 genes. atpF and petB were used to amplify 183 samples from 13 populations, and they could identify 6 and 9 haplotypes, respectively. Joint analysis of the two sequences revealed 18 haplotypes, named H1-H18, with the most widely distributed and most abundant being H4. Ten haplotypes were unique for 7 populations that they could be used to distinguish from others. Haplotype diversity and nucleotide diversity were 0.99 and 2.09 × 10-3, respectively, indicating the genetic diversity was relatively rich. The results of the intermediary adjacency network showed that H5 was the oldest haplotype, and stellate radiation was centered around it, indicating that population expansion occurred in genuine production areas. This study lays a theoretical foundation for the population identification, genetic evolution, and breed selection of F. ussuriensis.

Assessing the emergence time of SARS-CoV-2 zoonotic spillover

Understanding the evolution of Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) and its relationship to other coronaviruses in the wild is crucial for preventing future virus outbreaks. While the origin of the SARS-CoV-2 pandemic remains uncertain, mounting evidence suggests the direct involvement of the bat and pangolin coronaviruses in the evolution of the SARS-CoV-2 genome. To unravel the early days of a probable zoonotic spillover event, we analyzed genomic data from various coronavirus strains from both human and wild hosts. Bayesian phylogenetic analysis was performed using multiple datasets, using strict and relaxed clock evolutionary models to estimate the occurrence times of key speciation, gene transfer, and recombination events affecting the evolution of SARS-CoV-2 and its closest relatives. We found strong evidence supporting the presence of temporal structure in datasets containing SARS-CoV-2 variants, enabling us to estimate the time of SARS-CoV-2 zoonotic spillover between August and early October 2019. In contrast, datasets without SARS-CoV-2 variants provided mixed results in terms of temporal structure. However, they allowed us to establish that the presence of a statistically robust clade in the phylogenies of gene S and its receptor-binding (RBD) domain, including two bat (BANAL) and two Guangdong pangolin coronaviruses (CoVs), is due to the horizontal gene transfer of this gene from the bat CoV to the pangolin CoV that occurred in the middle of 2018. Importantly, this clade is closely located to SARS-CoV-2 in both phylogenies. This phylogenetic proximity had been explained by an RBD gene transfer from the Guangdong pangolin CoV to a very recent ancestor of SARS-CoV-2 in some earlier works in the field before the BANAL coronaviruses were discovered. Overall, our study provides valuable insights into the timeline and evolutionary dynamics of the SARS-CoV-2 pandemic.

SimPlot ++: a Python application for representing sequence similarity and detecting recombination

MOTIVATION

Accurate detection of sequence similarity and homologous recombination are essential parts of many evolutionary analyses.

RESULTS

We have developed SimPlot ++, an open-source multiplatform application implemented in Python, which can be used to produce publication quality sequence similarity plots using 63 nucleotide and 20 amino acid distance models, to detect intergenic and intragenic recombination events using Φ, Max-χ2, NSS or proportion tests, and to generate and analyze interactive sequence similarity networks. SimPlot ++ supports multicore data processing and provides useful distance calculability diagnostics.

AVAILABILITY

SimPlot ++ is freely available on GitHub at: https://github.com/Stephane-S/Simplot_PlusPlus, as both an executable file (for Windows) and Python scripts (for Windows/Linux/MacOS).

Horizontal gene transfer and recombination analysis of SARS-CoV-2 genes helps discover its close relatives and shed light on its origin

BACKGROUND

The SARS-CoV-2 pandemic is one of  the greatest  global medical and social challenges that have emerged in recent history. Human coronavirus strains discovered during previous SARS outbreaks have been hypothesized to pass from bats to humans using intermediate hosts, e.g. civets for SARS-CoV and camels for MERS-CoV. The discovery of an intermediate host of SARS-CoV-2 and the identification of specific mechanism of its emergence in humans are topics of primary evolutionary importance. In this study we investigate the evolutionary patterns of 11 main genes of SARS-CoV-2. Previous studies suggested that the genome of SARS-CoV-2 is highly similar to the horseshoe bat coronavirus RaTG13 for most of the genes and to some Malayan pangolin coronavirus (CoV) strains for the receptor binding (RB) domain of the spike protein.

RESULTS

We provide a detailed list of statistically significant horizontal gene transfer and recombination events (both intergenic and intragenic) inferred for each of 11 main genes of the SARS-CoV-2 genome. Our analysis reveals that two continuous regions of genes S and N of SARS-CoV-2 may result from intragenic recombination between RaTG13 and Guangdong (GD) Pangolin CoVs. Statistically significant gene transfer-recombination events between RaTG13 and GD Pangolin CoV have been identified in region [1215-1425] of gene S and region [534-727] of gene N. Moreover, some statistically significant recombination events between the ancestors of SARS-CoV-2, RaTG13, GD Pangolin CoV and bat CoV ZC45-ZXC21 coronaviruses have been identified in genes ORF1ab, S, ORF3a, ORF7a, ORF8 and N. Furthermore, topology-based clustering of gene trees inferred for 25 CoV organisms revealed a three-way evolution of coronavirus genes, with gene phylogenies of ORF1ab, S and N forming the first cluster, gene phylogenies of ORF3a, E, M, ORF6, ORF7a, ORF7b and ORF8 forming the second cluster, and phylogeny of gene ORF10 forming the third cluster.

CONCLUSIONS

The results of our horizontal gene transfer and recombination analysis suggest that SARS-CoV-2 could not only be a chimera virus resulting from recombination of the bat RaTG13 and Guangdong pangolin coronaviruses but also a close relative of the bat CoV ZC45 and ZXC21 strains. They also indicate that a GD pangolin may be an intermediate host of this dangerous virus.

Inferring explicit weighted consensus networks to represent alternative evolutionary histories

BACKGROUND

The advent of molecular biology techniques and constant increase in availability of genetic material have triggered the development of many phylogenetic tree inference methods. However, several reticulate evolution processes, such as horizontal gene transfer and hybridization, have been shown to blur the species evolutionary history by causing discordance among phylogenies inferred from different genes.

METHODS

To tackle this problem, we hereby describe a new method for inferring and representing alternative (reticulate) evolutionary histories of species as an explicit weighted consensus network which can be constructed from a collection of gene trees with or without prior knowledge of the species phylogeny.

RESULTS

We provide a way of building a weighted phylogenetic network for each of the following reticulation mechanisms: diploid hybridization, intragenic recombination and complete or partial horizontal gene transfer. We successfully tested our method on some synthetic and real datasets to infer the above-mentioned evolutionary events which may have influenced the evolution of many species.

CONCLUSIONS

Our weighted consensus network inference method allows one to infer, visualize and validate statistically major conflicting signals induced by the mechanisms of reticulate evolution. The results provided by the new method can be used to represent the inferred conflicting signals by means of explicit and easy-to-interpret phylogenetic networks.

On the origin of Solanum nigrum: can networks help?

Black nightshades are a group of species best known for their 'poisonous' or noxious weedy reputation. It is not so well known that species of this group serve as emerging food source in many countries worldwide especially in the African continent. Despite the fact that the section has recently been studied extensively, taxonomy is still unsettled and debated because of inter- and intraspecific hybridization, phenotypic plasticity and polyploidization. In this study we analyze the genetic relationships among diploid, tetraploid and hexaploid species of sect. Solanum, which have possibly taken part in the formation of Solanum nigrum, utilizing multi-locus (SCoT, ISSR) markers combined with chloroplast trnL-F sequence data and morphological characters. We scored 51 morphological characters united with SCoT (171), ISSR (224) and trnL-F (1042), for simultaneous analysis of 49 terminals and 1488 characters. The topology of the tree is concordant with the results of the network analysis. In the phylogenetic networks, all the accessions of the diploid species shared a split with all of the polyploid species. This reflected a high portion of shared ISSR and SCoT bands between diploids and polyploids. In addition, a strong split divided the diploid species. The history of S. nigrum might be reticulate with hybrid speciation playing an important rule. Genetically differentiated diploids in few combinations have created a series of genetically distinct polyploid populations. The insufficient isolation that permitted further recombination between ancient polyploids and diploids have resulted in high level of genotypic and phenotypic polymorphism. This high level of novel genomic variability obviously enabled species to succeed in their new environment.

Novel methodology for construction and pruning of quasi-median networks

Background

Visualising the evolutionary history of a set of sequences is a challenge for molecular phylogenetics. One approach is to use undirected graphs, such as median networks, to visualise phylogenies where reticulate relationships such as recombination or homoplasy are displayed as cycles. Median networks contain binary representations of sequences as nodes, with edges connecting those sequences differing at one character; hypothetical ancestral nodes are invoked to generate a connected network which contains all most parsimonious trees. Quasi-median networks are a generalisation of median networks which are not restricted to binary data, although phylogenetic information contained within the multistate positions can be lost during the preprocessing of data. Where the history of a set of samples contain frequent homoplasies or recombination events quasi-median networks will have a complex topology. Graph reduction or pruning methods have been used to reduce network complexity but some of these methods are inapplicable to datasets in which recombination has occurred and others are procedurally complex and/or result in disconnected networks.

Results

We address the problems inherent in construction and reduction of quasi-median networks. We describe a novel method of generating quasi-median networks that uses all characters, both binary and multistate, without imposing an arbitrary ordering of the multistate partitions. We also describe a pruning mechanism which maintains at least one shortest path between observed sequences, displaying the underlying relations between all pairs of sequences while maintaining a connected graph.

Conclusion

Application of this approach to 5S rDNA sequence data from sea beet produced a pruned network within which genetic isolation between populations by distance was evident, demonstrating the value of this approach for exploration of evolutionary relationships.