SMS: Smart Model Selection in PhyML

Lefort, Vincent; Longueville, Jean-Emmanuel; Gascuel, Olivier

doi:10.1093/molbev/msx149

Cited by 1,562 publications

(1,165 citation statements)

References 8 publications

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“…To reconstruct the species tree and calculate the divergence time, single‐copy gene families were extracted and the protein sequences were aligned with MUSCLE. The phylogenetic analysis of the superalignments was performed using a maximum‐likelihood algorithm implemented in the PhyML (Guindon et al., 2010) package with the JTT+G+F model calculated using the Smart Model Selection (Lefort, Longueville, & Gascuel, 2017) (SMS, http://www.atgc-montpellier.fr/sms/), and a Bayesian inference method implemented in the MrBayes package (Ronquist & Huelsenbeck, 2003) with the model used to PhyML. The divergence time was calculated using MCMCtree with the approximate likelihood method (Yang & Rannala, 2006).…”

Section: Methodsmentioning

confidence: 99%

De novo assembly and characterization of the Hucho taimen transcriptome

Tong

Xü

Zhang

et al. 2017

Ecology and Evolution

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Taimen (Hucho taimen) is an important ecological and economic species that is classified as vulnerable by the IUCN Red List of Threatened Species; however, limited genomic information is available on this species. RNA‐Seq is a useful tool for obtaining genetic information and developing genetic markers for nonmodel species in addition to its application in gene expression profiling. In this study, we performed a comprehensive RNA‐Seq analysis of taimen. We obtained 157 M clean reads (14.7 Gb) and used them to de novo assemble a high‐quality transcriptome with a N50 size of 1,060 bp. In the assembly, 82% of the transcripts were annotated using several databases, and 14,666 of the transcripts contained a full open reading frame. The assembly covered 75% of the transcripts of Atlantic salmon and 57.3% of the protein‐coding genes of rainbow trout. To learn about the genome evolution, we performed a systematic comparative analysis across 11 teleosts including eight salmonids and found 313 unique gene families in taimen. Using Atlantic salmon and rainbow trout transcriptomes as the background, we identified 250 positive selection transcripts. The pathway enrichment analysis revealed a unique characteristic of taimen: It possesses more immune‐related genes than Atlantic salmon and rainbow trout; moreover, some genes have undergone strong positive selection. We also developed a pipeline for identifying microsatellite marker genotypes in samples and successfully identified 24 polymorphic microsatellite markers for taimen. These data and tools are useful for studying conservation genetics, phylogenetics, evolution among salmonids, and selective breeding for threatened taimen.

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Section: Methodsmentioning

confidence: 99%

De novo assembly and characterization of the Hucho taimen transcriptome

Tong

Xü

Zhang

et al. 2017

Ecology and Evolution

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“…Phylogenetic relationships for both serotypes were analyzed using a maximum‐likelihood (ML) tree inferred with PhyML,10 under the TN93+G+Г4 model of nucleotide substitution as determined by automatic model selection by SMS: Smart Model Selecion in PhyML11 and the SPR branch‐swapping heuristic tree search algorithm. The reliability of the phylogenies was estimated with the approximate likelihood‐ratio (aLRT) SH‐like test12 and trees were visualized with FigTree v1.4.2 program 13.…”

Section: Methodsmentioning

confidence: 99%

First detection and molecular characterization of a DENV‐1/DENV‐4 co‐infection during an epidemic in Rio de Janeiro, Brazil

Bruycker-Nogueira

Faria

Nunes

et al. 2018

Clinical Case Reports

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Key Clinical MessageIn the 80s, dengue viruses type 1 and 4 (DENV‐1 and 4) were isolated in North region of Brazil. However, it was only after the DENV‐1 introduction in the state of Rio de Janeiro (RJ) in mid‐1980s, that dengue became a nationwide public health problem. In 2009, this serotype re‐emerged causing an explosive epidemic in the country. DENV‐4 was first detected in RJ in 2011 and in 2012, and DENV‐1 and 4 were co‐circulating and responsible for a high number of cases notifications. Here, we describe the detection and molecular characterization of a DENV‐1/4 co‐infection in sample of 2012 in RJ.

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“…24, 2018; reconstruction is essential here to not introduce artefactual frameshifts in ancestral iORFs, see below, which depends on the conservation of the same reading frame between the start and the stop codon. Historian was run with a Jukes-Cantor model and using a phylogenetic tree inferred from aligned intergenic sequences by PhyML version 3.0 (Guindon et al 2010) with the Smart Model Selection (Lefort et al 2017) and YPS128 as outgroup.…”

Section: Ancestral Reconstructions Of Intergenic Sequencesmentioning

confidence: 99%

The high turnover of ribosome-associated transcripts fromde novoORFs produces gene-like characteristics available forde novogene emergence in wild yeast populations

Durand

Gagnon‐Arsenault

Hatin

et al. 2018

Preprint

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Little is known about the rate of emergence of genes de novo, how they spread in populations and what their initial properties are. We examined wild Saccharomyces paradoxus populations to characterize the diversity and turnover of intergenic ORFs over short evolutionary time-scales. We identified ~34,000 intergenic ORFs per individual genome for a total of ~64,000 orthogroups, which resulted from an estimated turnover rate relatively smaller than the rate of gene duplication in yeast. Hundreds of intergenic ORFs show translation signatures, similar to canonical genes, but lower translation efficiency, which could reduce their potential production cost or simply reflect a lack of optimization. Translated intergenic ORFs tend to display low expression levels with sequence properties that are on average closer to expectations based on intergenic sequences.However, some predicted de novo polypeptides with gene-like properties emerged from ancient as well as recent birth events, illustrating that the raw material for functional innovations may appear even over short evolutionary time-scales. Our results suggest that variation in the mutation rate along the genome impacts the turnover of random polypeptides, which may in turn influence their early evolutionary trajectory. Whereas low mutation rate regions allow more time for random intergenic ORFs to evolve and become functional before being lost, mutation hotspots allow for the rapid exploration of the molecular landscape, thereby increasing the probability to acquire a polypeptide with immediate gene-like properties and thus functional potential.

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SMS: Smart Model Selection in PhyML

Cited by 1,562 publications

References 8 publications

De novo assembly and characterization of the Hucho taimen transcriptome

De novo assembly and characterization of the Hucho taimen transcriptome

First detection and molecular characterization of a DENV‐1/DENV‐4 co‐infection during an epidemic in Rio de Janeiro, Brazil

The high turnover of ribosome-associated transcripts fromde novoORFs produces gene-like characteristics available forde novogene emergence in wild yeast populations

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