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Vahtera, Varpu

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Vahtera

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Varpu

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Vahtera, Varpu
Author's Publications: search.filters.isAuthorOfPublication.93153305-7a90-4d10-8ef2-401791bed94a

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    Running WILD: the case for exploring mixed parameter sets in sensitivity analysis
    (Wiley-Blackwell, 2010) Sharma, Prashant Pradeep; Vahtera, Varpu; Kawauchi, Gisele Y.; Giribet, Gonzalo
    The robustness of clades to parameter variation may be a desirable quality or even a goal in phylogenetic analyses. Sensitivity analyses used to assess clade stability have invoked the incongruence length difference (ILD or \(_WILD\)) metric, a measure of congruence among datasets, to compare a series of most-parsimonious results from re-running analyses under different analytical conditions. It is also common practice to select a single “optimal” parameter set that minimizes \(_WILD\) across all parameter sets. However, the divergent molecular evolution of ribosomal genes and protein-encoding genes—specifically the bias against transversion events in coding genes of conserved function—suggests that deployment of multiple parameter sets could outperform the use of a single parameter set applied to all molecules. We explored congruence in five published datasets by including mixed parameter sets in our sensitivity analysis. In four cases, mixed parameter sets outperformed the previously reported, single optimal parameter set. Conversely, multiple parameter sets did not outperform a single optimal parameter set in a case in which actual strong topological conflict exists between data partitions. Exploration of mixed parameter sets may prove useful when combining ribosomal and protein-encoding genes, due to the relatively higher frequency of single- and double-base pair indel events in the former, and the relatively lower frequency of transversions in the latter.
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    Evolution of blindness in scolopendromorph centipedes (Chilopoda: Scolopendromorpha): insight from an expanded sampling of molecular data
    (Wiley-Blackwell, 2011) Vahtera, Varpu; Edgecombe, Gregory; Giribet, Gonzalo
    Relative to its diversity (34 genera, 700 species), Scolopendromorpha has been undersampled in molecular phylogenetic analyses compared with the other chilopod orders. Previous analyses based on morphology have not resolved several key controversies in systematics and evolutionary morphology unambiguously. Here we apply new molecular and morphological data to scolopendromorph phylogenetics, with a focus on the evolution of blindness. The taxonomic sample includes 19 genera, many lacking previous molecular data, and diverse, cosmopolitan genera of Scolopendridae are sampled by multiple species. Phylogenetic analysis with Direct Optimization used 94 morphological characters and ca. 4.5 kb of sequence data from two nuclear (18S and 28S rRNA) and two mitochondrial (16S rRNA and COI) loci. A single most-parsimonious cladogram selected after sensitivity analyses resolves Scolopendromorpha as monophyletic, and divides it into a blind clade of three families (Plutoniumidae, Cryptopidae, Scolopocryptopidae) and its ocellate sister group, Scolopendridae. Some species-rich, cosmopolitan genera (Cormocephalus, Otostigmus, Scolopendra) in Scolopendridae are non-monophyletic, and in several instances (e.g. New and Old World Scolopendra) relationships are more congruent with geographical distributions than with traditional classifications. The tribe Asanadini is particularly subject to parameter-sensitivity, nesting in the combined analysis within Scolopendrini but as sister to all other Scolopendrinae for molecular data alone. The total-evidence tree unambiguously optimizes trunk segmentation: a 23-segmented trunk has a single origin in the blind clade.
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    Comparative description of ten transcriptomes of newly sequenced invertebrates and efficiency estimation of genomic sampling in non-model taxa
    (BioMed Central, 2012) Riesgo, Ana; Da Silva Andrade, Sonia; Sharma, Prashant Pradeep; Novo, Marta; Rodriguez Perez-Porro, Alicia R.; Vahtera, Varpu; Gonzalez, Vanessa Liz; Kawauchi, Gisele Y.; Giribet, Gonzalo
    Introduction: Traditionally, genomic or transcriptomic data have been restricted to a few model or emerging model organisms, and to a handful of species of medical and/or environmental importance. Next-generation sequencing techniques have the capability of yielding massive amounts of gene sequence data for virtually any species at a modest cost. Here we provide a comparative analysis of de novo assembled transcriptomic data for ten non-model species of previously understudied animal taxa. Results: cDNA libraries of ten species belonging to five animal phyla (2 Annelida [including Sipuncula], 2 Arthropoda, 2 Mollusca, 2 Nemertea, and 2 Porifera) were sequenced in different batches with an Illumina Genome Analyzer II (read length 100 or 150 bp), rendering between ca. 25 and 52 million reads per species. Read thinning, trimming, and de novo assembly were performed under different parameters to optimize output. Between 67,423 and 207,559 contigs were obtained across the ten species, post-optimization. Of those, 9,069 to 25,681 contigs retrieved blast hits against the NCBI non-redundant database, and approximately 50% of these were assigned with Gene Ontology terms, covering all major categories, and with similar percentages in all species. Local blasts against our datasets, using selected genes from major signaling pathways and housekeeping genes, revealed high efficiency in gene recovery compared to available genomes of closely related species. Intriguingly, our transcriptomic datasets detected multiple paralogues in all phyla and in nearly all gene pathways, including housekeeping genes that are traditionally used in phylogenetic applications for their purported single-copy nature. Conclusions: We generated the first study of comparative transcriptomics across multiple animal phyla (comparing two species per phylum in most cases), established the first Illumina-based transcriptomic datasets for sponge, nemertean, and sipunculan species, and generated a tractable catalogue of annotated genes (or gene fragments) and protein families for ten newly sequenced non-model organisms, some of commercial importance (i.e., Octopus vulgaris). These comprehensive sets of genes can be readily used for phylogenetic analysis, gene expression profiling, developmental analysis, and can also be a powerful resource for gene discovery. The characterization of the transcriptomes of such a diverse array of animal species permitted the comparison of sequencing depth, functional annotation, and efficiency of genomic sampling using the same pipelines, which proved to be similar for all considered species. In addition, the datasets revealed their potential as a resource for paralogue detection, a recurrent concern in various aspects of biological inquiry, including phylogenetics, molecular evolution, development, and cellular biochemistry.