Biology subjects

Pentinsaari, M.

Publications and source records attributed to Pentinsaari, M..

4 recordsLinked to original sources

bioRxiv2026

Time-calibrated phylogenomics reveals relationships and parallel evolution of neoteny within Elateriformia (Coleoptera) despite pervasive homoplasy

The controversy over Elateriformia relationships hampers understanding of the evolution of disparate soft-bodied and fully sclerotized phenotypes, bioluminescence, and the ontogenetic reprogramming that leads to larviform females. Elateriformia contains >50,000 species in 34 families, including fireflies, jewel, and click beetles. We sample 31 families and 195 ingroup taxa, each with up to 4,224 orthologs. Through explicit hypothesis testing, coalescent-based approaches, and evaluation of dataset properties, we resolve backbone relationships. We reconfirm the monophyly of Byrrhoidea sensu lato, rejecting the recent resurrection of Dryopoidea, and verify the reciprocally monophyletic lampyroid and elaterid clades. We characterize short internodes and gene-tree discordance, both of which are indicative of ancient rapid radiations. Counterintuitively, signals from moderately variable genes are crucial for resolving certain splits, suggesting that even subtle rate differences distinguish phylogenetically informative loci from overly conserved, less informative markers. Time-calibrated phylogenies indicate the early origin of Elateriformia (281-287 Mya), with superfamilies diverging at the Permian-Triassic boundary and diversifying throughout the Jurassic. We identify 15 independent origins of soft-bodiedness and neotenic modifications spanning the Mid Jurassic to the present. Our hypothesis provides a foundation for investigating the genetic mechanisms underlying ontogenetic reprogramming and bioluminescence.

evolutionary biology↗

bioRxiv2024

Common to rare transfer learning (CORAL) enables inference and prediction for a quarter million rare Malagasy arthropods

Modern DNA-based biodiversity surveys result in massive-scale data, including up to millions of species - of which most are rare. Making the most of such data for inference and prediction requires modelling approaches that can relate species occurrences to environmental and spatial predictors, while incorporating information about their taxonomic or phylogenetic placement. Even if the scalability of joint species distribution models to large communities has greatly advanced, incorporating hundreds of thousands of species has not been feasible to date, leading to compromised analyses. Here we present a novel "common to rare transfer learning" approach (CORAL), based on borrowing information from the common species to enable statistically and computationally efficient modelling of both common and rare species. We illustrate that CORAL leads to much improved prediction and inference in the context of DNA metabarcoding data from Madagascar, comprising 255,188 arthropod species detected in 2874 samples.

ecology↗

bioRxiv2019

Forensics and DNA Barcodes - Do Identification Errors Arise in the Lab or in the Sequence Libraries?

Forensic studies often require the determination of biological materials to a species level. As such, DNA-based approaches to identification, particularly DNA barcoding, are attracting increased interest. The capacity of DNA barcodes to assign newly encountered specimens to a species relies upon access to informatics platforms, such as BOLD and GenBank, which host libraries of reference sequences and support the comparison of new sequences to them. As parameterization of these libraries expands, DNA barcoding has the potential to make valuable contributions in diverse forensic contexts. However, a recent publication called for caution after finding that both platforms performed poorly in identifying specimens of 17 common insect species. This study follows up on this concern by asking if the misidentifications reflected problems in the reference libraries or in the query sequences used to test them. Because this reanalysis revealed that missteps in acquiring and analyzing the query sequences were responsible for the misidentifications, a workflow is described to minimize such errors in future investigations. The present study also revealed the limitations imposed by the lack of a polished species-level taxonomy for many groups. In such cases, forensic applications can be strengthened by mapping the geographic distributions of sequence-based species proxies rather than waiting for the maturation of formal taxonomic systems based on morphology.

genetics↗

bioRxiv2019

A reference library for the identification of Canadian invertebrates: 1.5 million DNA barcodes, voucher specimens, and genomic samples

The reliable taxonomic identification of organisms through DNA sequence data requires a well parameterized library of curated reference sequences. However, it is estimated that just 15% of described animal species are represented in public sequence repositories. To begin to address this deficiency, we provide DNA barcodes for 1,500,003 animal specimens collected from 23 terrestrial and aquatic ecozones at sites across Canada, a nation that comprises 7% of the planets land surface. In total, 14 phyla, 43 classes, 163 orders, 1123 families, 6186 genera, and 64,264 Barcode Index Numbers (BINs; a proxy for species) are represented. Species-level taxonomy was available for 38% of the specimens, but higher proportions were assigned to a genus (69.5%) and a family (99.9%). Voucher specimens and DNA extracts are archived at the Centre for Biodiversity Genomics where they are available for further research. The corresponding sequence and taxonomic data can be accessed through the Barcode of Life Data System, GenBank, the Global Biodiversity Information Facility, and the Global Genome Biodiversity Network Data Portal.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=61 SRC=\"FIGDIR/small/701805v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (17K):\norg.highwire.dtl.DTLVardef@5c6449org.highwire.dtl.DTLVardef@1bc0224org.highwire.dtl.DTLVardef@309dddorg.highwire.dtl.DTLVardef@1cc2cc8_HPS_FORMAT_FIGEXP M_FIG C_FIG

ecology↗