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Supplementary material 1 from: Leite BR, Vieira PE, Troncoso JS, Costa FO (2021) Comparing species detection success between molecular markers in DNA metabarcoding of coastal macroinvertebrates. Metabarcoding and Metagenomics 5: e70063. https://doi.org/10.3897/mbmg.5.70063
Table S1, Figures S1–S5
Supplementary material 2 from: Leite BR, Vieira PE, Troncoso JS, Costa FO (2021) Comparing species detection success between molecular markers in DNA metabarcoding of coastal macroinvertebrates. Metabarcoding and Metagenomics 5: e70063. https://doi.org/10.3897/mbmg.5.70063
Tables S2, S3
FIGURE 1 in Comparing genetic markers' efficiencies for discrimination between two commercially important holothuroids in the Mediterranean Sea, Holothuria polii and Holothuria sanctori
FIGURE 1. Whole mount, fresh samples of Holothuria sanctori (1,2) and Holothuria polii (3,4).
Spatial and temporal genetic variation in Ethiopian barley (Hordeum vulgare L.) landraces as revealed by simple sequence repeat (SSR) markers
<p>Ethiopia is a center of diversity for barley (<i>Hordeum vulgare </i>L.) and it is grown across different agro-ecologies of the country. Unraveling population structure and gene flow status on temporal scales assists an evaluation of the consequences of physical, demographic as well as overall environmental changes on the stability and persistence of populations. Here, we examine spatial and temporal genetic variation within and among barley landrace samples collected over a period of four decades (1976-2017), using simple sequence repeat (SSR) markers. Our objective was to evaluate spatial and temporal changes in barley population connectivity associated with the closure of geographic origin and time periods. Low to strong genetic diversity was observed among the landraces and STRUCTURE, Neighbour joining tree and Discriminant Analysis of Principal Component analysis revealed three clusters. The cluster analysis revealed a close relationship between landraces along geographic proximity with genetic distance increases along with geographic distance. The grouping of landraces based on altitudinal classes was influenced by geographic proximity. From AMOVA year categories, it was observed that within population genetic diversity much higher than between population genetic diversity and that the temporal differentiation is considerably smaller. The low to strong genetic differentiation between landraces from various geographic origins could be attributed to gene flow across the region as a consequence of seed exchange among farmers. Nevertheless, we found some connectivity between changes in population dynamics as well as contemporary gene flow. The results demonstrate that this set of SSRs was highly informative and was useful in generating a meaningful classification of barley germplasms. Furthermore, our data also suggest that landraces are a source of valuable germplasm for sustainable agriculture in the context of future climate change, and that <i>in-situ</i> conservation strategies based on farmers use can conserve the genetic identity of landraces while allowing adaptation to local-environments.</p>
FIGURE 1 in Assessment of SCoT and ISSR molecular markers in genetic diversity of rigid ryegrass (Lolium rigidum Gaud.) in Iran
FIGURE 1. Geographical distribution of the studied Lolium rigidum populations.
Figure 4 from: Ceballos-Escalera A, Richards J, Arias MB, Inward DJG, Vogler AP (2022) Metabarcoding of insect-associated fungal communities: a comparison of internal transcribed spacer (ITS) and large-subunit (LSU) rRNA markers. MycoKeys 88: 1-33. https://doi.org/10.3897/mycokeys.88.77106
Figure 4 Heatmap using Pearson's correlation coefficient between the OTUs generated from the ITS2 and LSU D1-D2 metabarcodes and the analysed beetle species and forest types. Rectangles indicate the strength of association between an OTU and beetle/forest (strongly negative, grey, to strongly positive, red). Fungal OTUs (on the horizontal axis) were classified to genus or species level where possible; they are shown in random order and cannot be linked taxonomically between both markers.
Supplementary material 1 from: Ceballos-Escalera A, Richards J, Arias MB, Inward DJG, Vogler AP (2022) Metabarcoding of insect-associated fungal communities: a comparison of internal transcribed spacer (ITS) and large-subunit (LSU) rRNA markers. MycoKeys 88: 1-33. https://doi.org/10.3897/mycokeys.88.77106
Figure S1. Length distribution of the ITS (grey) and LSU (orange) OTUs
Figure 7 from: Ceballos-Escalera A, Richards J, Arias MB, Inward DJG, Vogler AP (2022) Metabarcoding of insect-associated fungal communities: a comparison of internal transcribed spacer (ITS) and large-subunit (LSU) rRNA markers. MycoKeys 88: 1-33. https://doi.org/10.3897/mycokeys.88.77106
Figure 7 Closed reference clustering of OTUs and phylogenetic trees at different thresholds A results from the closed reference clustering of OTUs at each clustering threshold against composite LSU/ITS2 reference sequences. LSU matches in green, ITS2 matches in blue, linked matches (for which both an ITS2 and LSUOTU were matched to a reference sequence of the same species) in yellow. Underlined taxa indicate new matches at each clustering threshold B phylogenetic tree of LSUOTUs under increasingly stringent clustering thresholds, with arrows marking newly added taxa as threshold values are increased.
Figure 3 from: Ceballos-Escalera A, Richards J, Arias MB, Inward DJG, Vogler AP (2022) Metabarcoding of insect-associated fungal communities: a comparison of internal transcribed spacer (ITS) and large-subunit (LSU) rRNA markers. MycoKeys 88: 1-33. https://doi.org/10.3897/mycokeys.88.77106
Figure 3 NMDS ordination plot of all specimens sampled with ITS2 and LSU D1-D2, based on the fungal community composition of the individual beetles. Shapes represent forest types and colours represent beetle species. Stress for this graph fell within acceptable ranges (<0.2).
Figure 2 from: Ceballos-Escalera A, Richards J, Arias MB, Inward DJG, Vogler AP (2022) Metabarcoding of insect-associated fungal communities: a comparison of internal transcribed spacer (ITS) and large-subunit (LSU) rRNA markers. MycoKeys 88: 1-33. https://doi.org/10.3897/mycokeys.88.77106
Figure 2 Top panel: The proportion of OTUs identified as members of a fungal Class determined by the ITS2 and LSU D1-D2 regions. For the spruce forest, only nine X. germanus and four X. saxesenii specimens were retained after rarefaction. Lower panel: The number of fungal OTUs per beetle specimen, separate for each beetle species and forest type, for ITS2 and LSU.
Figure 6 from: Ceballos-Escalera A, Richards J, Arias MB, Inward DJG, Vogler AP (2022) Metabarcoding of insect-associated fungal communities: a comparison of internal transcribed spacer (ITS) and large-subunit (LSU) rRNA markers. MycoKeys 88: 1-33. https://doi.org/10.3897/mycokeys.88.77106
Figure 6 Order-level trees and splitting/lumping of OTUs at clustering A order-level ML trees with mixed OTU clustering thresholds (99% LSU D1-D2, 98% ITS2). Full tree in supplementary materials. Leotia lubrica was used as the outgroup (not pictured). Brackets indicate reference taxa linked to an ITS2 and/or LSUOTU, with colours indicating potential splitting/lumping (blue, splitting; green, lumping; orange, 1:1) B diagram illustrating the effects of splitting and lumping of an OTU in the fungal community on the tree inference. Four hypothetical species (A to D) in a community are treated under uniform clustering thresholds for ITS2 and LSU. This may result in deviation from the 1:1 ratio of OTUs expected if each species in the community is represented equally by both markers (species A). Threshold values may be too high, resulting in splitting of species into multiples OTUs, which is likely to affect the more variable ITS2 region (species B) or may be too low, resulting in lumping of multiple species into a single OTU, likely to affect the conservative LSU region (species C and D).
Supplementary material 4 from: Ceballos-Escalera A, Richards J, Arias MB, Inward DJG, Vogler AP (2022) Metabarcoding of insect-associated fungal communities: a comparison of internal transcribed spacer (ITS) and large-subunit (LSU) rRNA markers. MycoKeys 88: 1-33. https://doi.org/10.3897/mycokeys.88.77106
Figure S4. Binding site of ITS86 primer showing mismatched base pairs in Ophiostomatales
Figure 1 from: Ceballos-Escalera A, Richards J, Arias MB, Inward DJG, Vogler AP (2022) Metabarcoding of insect-associated fungal communities: a comparison of internal transcribed spacer (ITS) and large-subunit (LSU) rRNA markers. MycoKeys 88: 1-33. https://doi.org/10.3897/mycokeys.88.77106
Figure 1 The proportion of fungi classified with IDTAXA, Protax-fungi and RDP from class to species level. "All" refers to the proportion of OTUs for which the three classifiers agreed in their classification.
Supplementary material 7 from: Ceballos-Escalera A, Richards J, Arias MB, Inward DJG, Vogler AP (2022) Metabarcoding of insect-associated fungal communities: a comparison of internal transcribed spacer (ITS) and large-subunit (LSU) rRNA markers. MycoKeys 88: 1-33. https://doi.org/10.3897/mycokeys.88.77106
Table S3. Number of OTUs assigned to each order based on RDP Bayesian classifier
Figure 5 from: Ceballos-Escalera A, Richards J, Arias MB, Inward DJG, Vogler AP (2022) Metabarcoding of insect-associated fungal communities: a comparison of internal transcribed spacer (ITS) and large-subunit (LSU) rRNA markers. MycoKeys 88: 1-33. https://doi.org/10.3897/mycokeys.88.77106
Figure 5 ML tree of Sordariomycetes constructed from the reference sequence alignments and OTUs for both markers (clustering thresholds: 98% ITS2, 99% LSU D1-D2). Leotia lubrica (Leotiomycetes) was specified as the outgroup. The assignment of OTUs by each of the three classifiers (RDP, IDTAXA, Protax-fungi) is shown by coloured boxes. Terminals missing these boxes are the reference sequences. Coloured dots on the nodes of the tree indicate the hypothetical ancestor defining monophyletic groups corresponding to the various orders of Sordariomycetes. The extent of each order is indicated by the coloured inner ring. Note that the ancestor of an order is defined by the youngest node from which all reference sequences are descended; OTUs falling outside of the resulting clades appear as 'unassigned' by the phylogenetic analysis approach. The distribution of ITS2 (red squares) and LSU D1-D2 (blue bullets) relative to the reference set (yellow stars) on each of the tips of the tree. Note the limited presence of ITS sequences in the Ophiostomatales (in top right quadrant).
Figure 8 from: Ceballos-Escalera A, Richards J, Arias MB, Inward DJG, Vogler AP (2022) Metabarcoding of insect-associated fungal communities: a comparison of internal transcribed spacer (ITS) and large-subunit (LSU) rRNA markers. MycoKeys 88: 1-33. https://doi.org/10.3897/mycokeys.88.77106
Figure 8 Proportion of OTUs assigned to each Order from metabarcoding with LSU (left panel) and ITS (right panel) markers based on the RDP classifier and the phylogenetic tree, under increasing threshold values.
FIGURE 1 in Comparative study and genetic diversity of Salicornia persica (Chenopodiaceae) using SCOT molecular markers
FIGURE 1. Distribution map of the studied populations.
Data for "Quantifying Discourse Marker Usage in Oral and Literary Discourse"
<p>Anonymized data for the paper "Quantifying Discourse Marker Usage in Oral and Literary Discourse" (currently under blind review)</p>
Phenotypic and marker data for statistical genetic analysis of Minnesota maize lines
<p>Publicly available maize lines are a resource for studying quantitative genetic variation in plants. This dataset includes cluster or subpopulation information, phenotypic data, and single nucleotide polymorphism (SNP) data for 272 maize lines developed by the University of Minnesota, other universities, and seed companies. The lines were evaluated at multiple locations in Minnesota in 2011 and 2012 for different phenological, morphological, and kernel composition traits. The lines were genotyped for 56,110 SNP loci on the Maize SNP50 Beadchip (Illumina). Filtering for SNP data quality led to data for 28,626 SNP loci for the 272 maize lines. Population structure analysis showed that the maize lines clustered into five subpopulations (A321 or Minnesota 13, B73, Mo17, Oh43, and PH207 or Iodent) that represented most of the U.S. Corn Belt diversity (Schaefer and Bernardo 2013a, Crop Science 53:1529-1536). Genomewide association mapping revealed marker-trait associations for male flowering date, female flowering date, plant height, ear height, and kernel concentration for oil, protein, and starch (Schaefer and Bernardo 2013b, Crop Science 53:2518-2529). The covariance between relatives is a tenet in quantitative genetics, but such classical theory has ignored any resemblance between individuals unrelated by pedigree. Analysis of this maize dataset showed that a covariance between nonrelatives in maize is not ubiquitous but it is sometimes rpesent for specific traits and for certain groups of unrelated individuals (Bernardo 2022, Heredity).</p>
Data from: Ultraconserved elements anchor thousands of genetic markers for target enrichment spanning multiple evolutionary timescales
Although massively parallel sequencing has facilitated large-scale DNA sequencing, comparisons among distantly related species rely upon small portions of the genome that are easily aligned. Methods are needed to efficiently obtain comparable DNA fragments prior to massively parallel sequencing, particularly for biologists working with non-model organisms. We introduce a new class of molecular marker, anchored by ultraconserved genomic elements (UCEs), that universally enable target enrichment and sequencing of thousands of orthologous loci across species separated by hundreds of millions of years of evolution. Our analyses here focus on use of UCE markers in Amniota, because UCEs and phylogenetic relationships are well known in some amniotes. We perform an in silico experiment to demonstrate that sequence flanking 2,030 UCEs contains information sufficient to enable unambiguous recovery of the established primate phylogeny. We extend this experiment by performing an in vitro enrichment of 2,386 UCE-anchored loci from nine, non-model avian species. We then use alignments of 854 of these loci to unambiguously recover the established evolutionary relationships within and among three ancient bird lineages. Because many organismal lineages have UCEs, this type of genetic marker and the analytical framework we outline can be applied across the tree of life, potentially reshaping our understanding of phylogeny at many taxonomic levels.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.