Molecular and automated identification of the diatom genus<i>Frustulia</i>in northern Europe

Urbánková, Pavla; Scharfen, Vojtěch; Kulichová, Jana

doi:10.1080/0269249x.2016.1224780

Cited by 10 publications

(8 citation statements)

References 41 publications

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“…We examined 15 monoclonal strains representing 12 phylogenetic lineages of the genus Frustulia (three lineages were represented by two strains and nine by one strain). Since not all strains were represented by a unique morphotype, their names are composed of two species names (F. crassinervia-saxonica: F. crassinervia (Brebisson) Lange-Bertalot & Krammer, and F. saxonica Rabenhorts) with lineage attribute (III-VII) sensu [25,26]. All of the strains, which were mounted onto permanent slides using a Naphrax (Brunel Microscopes Ltd., Wiltshire, UK), originated from our previous research [25,28].…”

Section: Characteristics Of Strains and Data Acquisitionmentioning

confidence: 99%

“…All of the strains, which were mounted onto permanent slides using a Naphrax (Brunel Microscopes Ltd., Wiltshire, UK), originated from our previous research [25,28]. The treatment of strains was similar: slightly acidic, oligotrophic liquid medium (OGM) enriched with sodium metasilicate; 18 • C temperature and continuous lighting; harvesting of cells in the exponential phase of the growth; and cleaning of frustules by the incineration method (for details of the culture conditions, see [25,26]). We selected lineages on the basis of three criteria: a monophyletic origin [27][28][29], availability of more than 50 frustules or valves per strain, and a cell size above the minimum of their known size range (Table S1).…”

Section: Characteristics Of Strains and Data Acquisitionmentioning

confidence: 99%

“…All available sequences were downloaded from the GenBank database. Sequences of psbA were sequenced following reference [26] using primers psbA-F and psbA-R1 [42] with the MyTaq™ polymerase and the following PCR settings: initial denaturation at 94 • C for 1 min; 35 cycles of 94 • C for 15 s, 55 • C for 15 s, and 74 • C for 10 s; and final extension at 72 • C for 7 min. To reduce missing data in the alignment, we imputed missing sequences from strains which belonged to the same species based on the more divergent markers (rbcL or LSU).…”

Section: Reconstruction Of Phylogeny and Trait Mappingmentioning

confidence: 99%

“…A characteristic morphological feature of this raphid pennate diatom is a specific structure running centrally along the apical axis (longitudinal rib) and a linear-lanceolate-rhomboidal valve shape with rounded, rostrate, or capitate apices (Figure 1, [1,23]). Morphometric and phylogenetic studies showed that not all Frustulia morphospecies can be unambiguously identified: some morphospecies show overlapping morphological variability, and some phylogenetic lineages do not share unique morphology [25][26][27]. Despite the symmetric appearance of the valves, the internal valve structures of several Frustulia lineages can be asymmetric (e.g., longitudinal rib in Figure 1a,b).…”

Section: Introductionmentioning

confidence: 99%

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Symmetric and Asymmetric Components of Shape Variation in the Diatom Genus Frustulia (Bacillariophyta)

Kulichová

Urbánková

2020

Symmetry

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Irregularities in cell division can produce asymmetry in symmetric structures, such as outlines of diatom cells, which can reflect genetic, environmental, or random variability in developmental processes. This study examined 12 phylogenetic lineages of the diatom genus Frustulia using landmark-based geometric morphometrics to assess the variation between cell segments separated by apical and transapical axes. Although asymmetric variation within cells differed in some lineages, these irregularities most likely did not reflect the evolutionary history of the lineages. The intraclonal phenotypic plasticity of diatom frustules was induced rather by nongenetic factors, i.e., inherited valve abnormalities, constraints of siliceous cell walls, and random developmental instability during morphogenesis. The positive correlations between the symmetric and asymmetric components of shape variation indicated that the morphogenesis of diatom cell walls affected irregularities within cells and variability among the symmetrized cells to a similar extent.

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Section: Characteristics Of Strains and Data Acquisitionmentioning

confidence: 99%

Section: Characteristics Of Strains and Data Acquisitionmentioning

confidence: 99%

Section: Reconstruction Of Phylogeny and Trait Mappingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Symmetric and Asymmetric Components of Shape Variation in the Diatom Genus Frustulia (Bacillariophyta)

Kulichová

Urbánková

2020

Symmetry

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“…We then use supervised machine learning techniques to automate the identification of species from images. Supervised machine learning methods have previously been used to automate species identification for several microscopic taxa, including coccoliths (Beaufort & Dollfus, ), pollen grains (Gonçalves et al, ; Rodriguez‐Damian et al, ), phytoplankton (Sosik & Olson, ), hymenopterans (Rodner et al, ), diatoms (Urbánková et al, ), and dipterans and coleopterans (Valan et al, ). However, these techniques have only been applied in a limited way (i.e., few species, low sampling, limited image variability, and scope) to modern planktonic foraminifera (Macleod et al, ; Mitra et al, ; Ranaweera et al, ; Zhong et al, ), preventing their use as a general tool in this field.…”

Section: Introductionmentioning

confidence: 99%

Endless Forams: >34,000 Modern Planktonic Foraminiferal Images for Taxonomic Training and Automated Species Recognition Using Convolutional Neural Networks

Hsiang

Brombacher

Rillo

et al. 2019

Paleoceanog and Paleoclimatol

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Planktonic foraminiferal species identification is central to many paleoceanographic studies, from selecting species for geochemical research to elucidating the biotic dynamics of microfossil communities relevant to physical oceanographic processes and interconnected phenomena such as climate change. However, few resources exist to train students in the difficult task of discerning amongst closely related species, resulting in diverging taxonomic schools that differ in species concepts and boundaries. This problem is exacerbated by the limited number of taxonomic experts. Here we document our initial progress toward removing these confounding and/or rate-limiting factors by generating the first extensive image library of modern planktonic foraminifera, providing digital taxonomic training tools and resources, and automating species-level taxonomic identification of planktonic foraminifera via machine learning using convolution neural networks. Experts identified 34,640 images of modern (extant) planktonic foraminifera to the species level. These images are served as species exemplars through the online portal Endless Forams (endlessforams.org) and a taxonomic training portal hosted on the citizen science platform Zooniverse (zooniverse.org/projects/ahsiang/ endless-forams/). A supervised machine learning classifier was then trained with~27,000 images of these identified planktonic foraminifera. The best-performing model provided the correct species name for an image in the validation set 87.4% of the time and included the correct name in its top three guesses 97.7% of the time. Together, these resources provide a rigorous set of training tools in modern planktonic foraminiferal taxonomy and a means of rapidly generating assemblage data via machine learning in future studies for applications such as paleotemperature reconstruction.

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Mini review: Diatom species as seen through a molecular window

Medlin

2018

Braz. J. Bot

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It has been accepted that we know less than 10% of the identified diversity in the marine microbial world and the diatoms are no exception. Even the species that we think we can easily recognize are often cryptic species, and even less is known of their life histories and spatial and temporal trends in their abundance and distribution. With new molecular and analytical techniques, we can advance our knowledge of a species to understand its morphological range, biogeographies and reproductive isolation. Moreover, some of molecular techniques are very sensitive. Depending on the species-level question(s) being asked, the molecular tools appropriate to answer them differ greatly.

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Molecular and automated identification of the diatom genusFrustuliain northern Europe

Cited by 10 publications

References 41 publications

Symmetric and Asymmetric Components of Shape Variation in the Diatom Genus Frustulia (Bacillariophyta)

Symmetric and Asymmetric Components of Shape Variation in the Diatom Genus Frustulia (Bacillariophyta)

Endless Forams: >34,000 Modern Planktonic Foraminiferal Images for Taxonomic Training and Automated Species Recognition Using Convolutional Neural Networks

Mini review: Diatom species as seen through a molecular window

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