Tackling Rapid Radiations With Targeted Sequencing

In phylogenetic studies across angiosperms, at various taxonomic levels, polytomies have persisted despite efforts to resolve them by increasing sampling of taxa and loci. The large amount of genomic data now available and statistical tools to analyze them provide unprecedented power for phylogenetic inference. Targeted sequencing has emerged as a strong tool for estimating species trees in the face of rapid radiations, lineage sorting, and introgression. Evolutionary relationships in Cyperaceae have been studied mostly using Sanger sequencing until recently. Despite ample taxon sampling, relationships in many genera remain poorly understood, hampered by diversification rates that outpace mutation rates in the loci used. The C4 Cyperus clade of the genus Cyperus has been particularly difficult to resolve. Previous studies based on a limited set of markers resolved relationships among Cyperus species using the C3 photosynthetic pathway, but not among C4 Cyperus clade taxa. We test the ability of two targeted sequencing kits to resolve relationships in the C4 Cyperus clade, the universal Angiosperms-353 kit and a Cyperaceae-specific kit. Sequences of the targeted loci were recovered from data generated with both kits and used to investigate overlap in data between kits and relative efficiency of the general and custom approaches. The power to resolve shallow-level relationships was tested using a summary species tree method and a concatenated maximum likelihood approach. High resolution and support are obtained using both approaches, but high levels of missing data disproportionately impact the latter. Targeted sequencing provides new insights into the evolution of morphology in the C4 Cyperus clade, demonstrating for example that the former segregate genus Alinula is polyphyletic despite its seeming morphological integrity. An unexpected result is that the Cyperus margaritaceus-Cyperus niveus complex comprises a clade separate from and sister to the core C4 Cyperus clade. Our results demonstrate that data generated with a family-specific kit do not necessarily have more power than those obtained with a universal kit, but that data generated with different targeted sequencing kits can often be merged for downstream analyses. Moreover, our study contributes to the growing consensus that targeted sequencing data are a powerful tool in resolving rapid radiationsEspaña Ministry of Economy and Competitiveness (project CGL2016- 77401-P

Phylogenomic analysis reveals extensive phylogenetic mosaicism in the Human GPCR Superfamily

A novel high throughput phylogenomic analysis (HTP) was applied to the rhodopsin G-protein coupled receptor (GPCR) family. Instances of phylogenetic mosaicism between receptors were found to be frequent, often as instances of correlated mosaicism and repeated mosaicism. A null data set was constructed with the same phylogenetic topology as the rhodopsin GPCRs. Comparison of the two data sets revealed that mosaicism was found in GPCRs in a higher frequency than would be expected by homoplasy or the effects of topology alone. Various evolutionary models of differential conservation, recombination and homoplasy are explored which could result in the patterns observed in this analysis. We find that the results are most consistent with frequent recombination events. A complex evolutionary history is illustrated in which it is likely frequent recombination has endowed GPCRs with new functions. The pattern of mosaicism is shown to be informative for functional prediction for orphan receptors. HTP analysis is complementary to conventional phylogenomic analyses revealing mosaicism that would not otherwise have been detectable through conventional phylogenetics

Phylogenomics of plant genomes: a methodology for genome-wide searches for orthologs in plants

<p>Abstract</p> <p>Background</p> <p>Gene ortholog identification is now a major objective for mining the increasing amount of sequence data generated by complete or partial genome sequencing projects. Comparative and functional genomics urgently need a method for ortholog detection to reduce gene function inference and to aid in the identification of conserved or divergent genetic pathways between several species. As gene functions change during evolution, reconstructing the evolutionary history of genes should be a more accurate way to differentiate orthologs from paralogs. Phylogenomics takes into account phylogenetic information from high-throughput genome annotation and is the most straightforward way to infer orthologs. However, procedures for automatic detection of orthologs are still scarce and suffer from several limitations.</p> <p>Results</p> <p>We developed a procedure for ortholog prediction between <it>Oryza sativa </it>and <it>Arabidopsis thaliana</it>. Firstly, we established an efficient method to cluster <it>A. thaliana </it>and <it>O. sativa </it>full proteomes into gene families. Then, we developed an optimized phylogenomics pipeline for ortholog inference. We validated the full procedure using test sets of orthologs and paralogs to demonstrate that our method outperforms pairwise methods for ortholog predictions.</p> <p>Conclusion</p> <p>Our procedure achieved a high level of accuracy in predicting ortholog and paralog relationships. Phylogenomic predictions for all validated gene families in both species were easily achieved and we can conclude that our methodology outperforms similarly based methods.</p

Molecular Evolution and Gene Function

One of the basic questions of phylogenomics is how gene function evolves, whether among species or inside gene families. In this chapter, we provide a brief overview of the problems associated with defining gene function in a manner which allows comparisons which are both large scale and evolutionarily relevant. The main source of functional data, despite its limitations, is transcrip-tomics. Functional data provides information on evolutionary mechanisms primarily by showing which functional classes of genes evolve under stronger or weaker purifying or adaptive selection, and on which classes of mutations (e.g., substitutions or duplications). However, the example of the "ortholog conjecture" shows that we are still not at a point where we can confidently study phylogenomically the evolution of gene function at a precise scale

HMMER cut-off threshold tool (HMMERCTTER): Supervised classification of superfamily protein sequences with a reliable cut-off threshold

Background: Protein superfamilies can be divided into subfamilies of proteins with different functional characteristics. Their sequences can be classified hierarchically, which is part of sequence function assignation. Typically, there are no clear subfamily hallmarks that would allow pattern-based function assignation by which this task is mostly achieved based on the similarity principle. This is hampered by the lack of a score cut-off that is both sensitive and specific. Results: HMMER Cut-off Threshold Tool (HMMERCTTER) adds a reliable cut-off threshold to the popular HMMER. Using a high quality superfamily phylogeny, it clusters a set of training sequences such that the cluster-specific HMMER profiles show cluster or subfamily member detection with 100% precision and recall (P&R), thereby generating a specific threshold as inclusion cut-off. Profiles and thresholds are then used as classifiers to screen a target dataset. Iterative inclusion of novel sequences to groups and the corresponding HMMER profiles results in high sensitivity while specificity is maintained by imposing 100% P&R self detection. In three presented case studies of protein superfamilies, classification of large datasets with 100% precision was achieved with over 95% recall. Limits and caveats are presented and explained. Conclusions: HMMERCTTER is a promising protein superfamily sequence classifier provided high quality training datasets are used. It provides a decision support system that aids in the difficult task of sequence function assignation in the twilight zone of sequence similarity. All relevant data and source codes are available from the Github repository at the following.Fil: Pagnuco, Inti Anabela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Científicas y Tecnológicas en Electrónica. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Instituto de Investigaciones Científicas y Tecnológicas en Electrónica; ArgentinaFil: Revuelta, María Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Biológicas. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Biológicas; ArgentinaFil: Bondino, Hernán Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Biológicas. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Biológicas; ArgentinaFil: Brun, Marcel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Científicas y Tecnológicas en Electrónica. Universidad Nacional de Mar del Plata. Facultad de Ingeniería. Instituto de Investigaciones Científicas y Tecnológicas en Electrónica; ArgentinaFil: Ten Have, Arjen. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Biológicas. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Biológicas; Argentin

GreenPhylDB: a database for plant comparative genomics

GreenPhylDB (http://greenphyl.cirad.fr) is a comprehensive platform designed to facilitate comparative functional genomics in Oryza sativa and Arabidopsis thaliana genomes. The main functions of GreenPhylDB are to assign O. sativa and A. thaliana sequences to gene families using a semi-automatic clustering procedure and to create ‘orthologous’ groups using a phylogenomic approach. To date, GreenPhylDB comprises the most complete list of plant gene families, which have been manually curated (6421 families). GreenPhylDB also contains all of the phylogenomic relationships computed for 4375 families. A total of 492 TAIR, 1903 InterPro and 981 KEGG families and subfamilies were manually curated using the clusters created with the TribeMCL software. GreenPhylDB integrates information from several other databases including UniProt, KEGG, InterPro, TAIR and TIGR. Several entry points can be used to display phylogenomic relationships for A. thaliana or O. sativa sequences, using TAIR, TIGR gene ID, family name, InterPro, gene alias, UniProt or protein/nucleic sequence. Finally, a powerful phylogenomics tool, GreenPhyl Ortholog Search Tool (GOST), was incorporated into GreenPhylDB to predict orthologous relationships between O. sativa/A. thaliana protein(s) and sequences from other plant species