Biology subjects

Somervuo, P.

Publications and source records attributed to Somervuo, P..

5 recordsLinked to original sources

bioRxiv2025

Discovering the unseen: a performance comparison of taxonomic classification methods under unknown DNA barcodes

O_LIDNA barcoding and metabarcoding have emerged as cost-efficient, standardized methods for characterizing local biodiversity. Based on the sequencing of a small targeted gene fragment, it is theoretically possible to identify a wide diversity of taxa by comparing them with reference sequence databases. However, a key challenge for accurate taxonomic classification is the incompleteness of such databases, leading to most query sequences lacking species-level matches. C_LIO_LIWhere species-level matches are missing, it may be possible to classify query sequences to a higher taxonomic level, such as genus or family, based on the similarity of related reference taxa. The challenge then lies in confidently recognizing whether the sequence belongs to an unobserved (here, "novel") taxon on a given taxonomic level. C_LIO_LIIn this study, we evaluated the performance and utility of several methods for taxonomic classification. Methods were assessed based on the classification accuracy of both observed and novel taxa, training time, space requirements, and run time. We did this for two cases: the COI barcode for arthropods, and the ITS barcode for fungi, with the latter representing an instance with substantially greater sequence similarity variation within classes. To test classification of novel taxa, we used well-curated datasets with partially distinct taxonomic distribution between the training and test set. Novel taxa occurred at all evaluated taxonomic levels, such as novel species in observed genera and novel genera in observed families. We further assessed the effect on performance when shifting from full-length barcodes to shorter sequences as generated through metabarcoding in the testing dataset. C_LIO_LIThis study sheds light on the strengths and limitations of different classification algorithms across varied ecological contexts and provides guidance for researchers in selecting suitable algorithms for DNA barcoding and metabarcoding applications. In particular, it demonstrates the supreme performance of phylogenetic placement methods such as EPA-ng for classification of arthropod COI barcodes, and composition-based classifiers such as SINTAX, RDP-NBC, and IDTAXA for fungal ITS. C_LI

bioinformatics↗

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↗

bioRxiv2022

Spatial cumulant models enable spatially informed treatment strategies and analysis of local interactions in cancer systems

Theoretical and applied cancer studies that use individual-based models (IBMs) have been limited by the lack of a mathematical formulation that enables rigorous analysis of these models. However, spatial cumulant models (SCMs), which have arisen from theoretical ecology, describe population dynamics generated by a specific family of IBMs, namely spatio-temporal point processes (STPPs). SCMs are spatially resolved population models formulated by a system of differential equations that approximate the dynamics of two STPP-generated summary statistics: first-order spatial cumulants (densities), and second-order spatial cumulants (spatial covariances). We exemplify how SCMs can be used in mathematical oncology by modelling theoretical cancer cell populations comprising interacting growth factor-producing and non-producing cells. To formulate model equations, we use computational tools that enable the generation of STPPs, SCMs and mean-field population models (MFPMs) from user-defined model descriptions (Cornell et al., 2019). To calculate and compare STPP, SCM and MFPM-generated summary statistics, we develop an application-agnostic computational pipeline. Our results demonstrate that SCMs can capture STPP-generated population density dynamics, even when MFPMs fail to do so. From both MFPM and SCM equations, we derive treatment-induced death rates required to achieve non-growing cell populations. When testing these treatment strategies in STPP-generated cell populations, our results demonstrate that SCM-informed strategies outperform MFPM-informed strategies in terms of inhibiting population growths. We thus demonstrate that SCMs provide a new framework in which to study cell-cell interactions, and can be used to describe and perturb STPP-generated cell population dynamics. We, therefore, argue that SCMs can be used to increase IBMs applicability in cancer research. Statements and DeclarationsThe authors have no competing interests to declare that are relevant to the content of this article.

cancer biology↗

bioRxiv2021

Alternative developmental and transcriptomic responses to host plant water limitation in a butterfly metapopulation

Predicting how climate change affects biotic interactions and their evolution poses a challenge. Plant-insect herbivore interactions are particularly sensitive to climate change, as climate-induced changes in plant quality cascade into the performance of insect herbivores. Whereas the immediate survival of herbivore individuals depends on plastic responses to climate change induced nutritional stress, long-term population persistence via evolutionary adaptation requires genetic variation for these responses. In order to assess the prospects for population persistence under climate change, it is therefore crucial to characterise response mechanisms to climate change induced stressors, and quantify their variability in natural populations. Here, we test developmental and transcriptomic responses to water limitation induced host plant quality change in a Glanville fritillary butterfly (Melitaea cinxia) metapopulation. We combine nuclear magnetic resonance spectroscopy on the plant metabolome, larval developmental assays and an RNA seq analysis of the larval transcriptome. We observed that responses to feeding on water limited plants, in which amino acids and aromatic compounds are enriched, showed marked intrapopulation variation, with individuals of some families performing better on control and others on water limited plants. The transcriptomic responses were concordant with the developmental responses: Families exhibiting opposite developmental responses also produced opposite transcriptomic responses, e.g. in growth associated intracellular signalling. The opposite developmental and transcriptomic responses are associated with between families differences in organic compound catabolism and storage protein production. The results reveal heritable intrapopulation variability in plasticity, suggesting potential for evolutionary responses to drought-induced changes in host plant quality in the Finnish M. cinxia metapopulation.

ecology↗

bioRxiv2017

Carrion Fly-Derived DNA Metabarcoding Is An Effective Tool For Mammal Surveys: Evidence From A Known Tropical Mammal Community

Metabarcoding of vertebrate DNA derived from carrion flies has been proposed as a promising tool for biodiversity monitoring. To evaluate its efficacy, we conducted metabarcoding surveys of carrion flies on Barro Colorado Island (BCI), Panama, which has a well-known mammal community, and compared our results against diurnal transect counts and camera-trapping. We collected 1084 flies in 29 sampling days, which were pooled into 102 DNA extractions. We then conducted metabarcoding with mammal-specific (16S) and vertebrate-specific (12S) primers targeting mtDNA, and sequenced these amplicons on Illumina MiSeq. For taxonomic assignment, we compared BLAST with the new program PROTAX, and we found PROTAX significantly improved species identifications. We detected 20 mammal, four bird, and one lizard species from carrion fly metabarcoding, all but one of which were previously known from BCI. Fly metabarcoding detected more mammal species than concurrent transect counts (29 sampling days, 13 species) and concurrent camera-trapping (84 sampling days, 17 species), and detected 67% of the number of mammal species documented by 8 years of transect counts and camera-trapping combined, although fly metabarcoding missed several abundant species. This study demonstrates that carrion fly metabarcoding is a powerful tool for mammal biodiversity surveys, and has the potential to detect a broader range of species than more commonly used methods.

zoology↗