Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
115
datasets available to search
ShareScore release 0.9.0
Dataset results
115 results for “Multi-locus”
Data from: Resolving ambiguity of concatenation in multi-locus sequence data for the construction of phylogenetic supermatrices
The construction of supermatrices from mining of DNA metadata is problematic due to incomplete species identification and incongruence of gene trees that hamper sequence concatenation based on Linnaean binomials. We applied methods from graph theory to minimize ambiguity of concatenation globally over a large data set. An initial step establishes sequence clusters for each locus that broadly correspond to Linnaean species. These clusters frequently are not consistent with binomials and specimen identifiers, which greatly complicates the concatenation of clusters across multiple loci. A multipartite heuristic algorithm is used to match clusters across loci and to generate a global set of concatenates that minimizes conflict of taxonomic names. The procedure was applied to all available data on GenBank for the Coleoptera (beetles) including >10500 taxon labels for >23500 sequences of four loci. The BlastClust algorithm was used in the initial clustering step, resulting in 11241 clusters or divergent singletons. Clusters were first used for name assignment of unidentified sequences resulting in 510 new identifications (13.9% of total unidentified sequences) of which nearly half were by clustering of a specimen at a secondary locus. Concatenation was straightforward only for 12.8% of all binomials represented by a singleton sequence at each locus with an available entry, while the majority of binomials were associated to multi-sequence clusters in at least one locus. Concatenation of clusters is particularly problematic where limits of DNA-based clusters are inconsistent with the Linnaean binomials, either containing more than one binomial or splitting a binomial among multiple clusters. The current data set contained 1518 such clusters (13.5% of total). By applying a scoring scheme for full and partial name matches in pairs of clusters, the maximum weight set of concatenates produced a matrix of minimally 7366 terminals. Varying the match weights for partial matches had little effect on the number of terminals, although if partial matches were disallowed, the number of terminals increased greatly. Trees from the resulting supermatrices generally produced tree topologies in good agreement with the Linnaean taxonomy, with fewer terminals compared to trees generated according to standard species labels. The study illustrates a strategy for assembling the Tree-of-Life from an ever more complex primary database.
Data from: Multi-locus phylogeny of lethal amanitas: implications for species diversity and historical biogeography
Background: Lethal amanitas (Amanita section Phalloideae) are a group of wild, fatal mushrooms causing many poisoning cases worldwide. However, the diversity and evolutionary history of these lethal mushrooms remain poorly known due to the limited sampling and insufficient gene fragments employed for phylogenetic analyses. In this study, five gene loci (nrLSU, ITS, rpb2, ef1-α and β-tubulin) with a widely geographic sampling from East and South Asia, Europe, North and Central America, South Africa and Australia were analysed with maximum-likelihood, maximum-parsimony and Bayesian inference methods. Biochemical analyses were also conducted with intention to detect amatoxins and phalloidin in 14 representative samples. Result: Lethal amanitas were robustly supported to be a monophyletic group after excluding five species that were provisionally defined as lethal amanitas based on morphological studies. In lethal amanitas, 28 phylogenetic species were recognised by integrating molecular phylogenetic analyses with morphological studies, and 14 of them represented putatively new species. The biochemical analyses indicated a single origin of cyclic peptide toxins (amatoxins and phalloidin) within Amanita and suggested that this kind of toxins seemed to be a synapomorphy of lethal amanitas. Molecular dating through BEAST and biogeographic analyses with LAGRANGE and RASP indicated that lethal amanitas most likely originated in the Palaeotropics with the present crown group dated around 64.92 Mya in the early Paleocene, and the East Asia–eastern North America or Eurasia–North America–Central America disjunct distribution patterns were primarily established during the middle Oligocene to Miocene. Conclusion: The cryptic diversity found in this study indicates that the species diversity of lethal amanitas is strongly underestimated under the current taxonomy. The intercontinental sister species or sister groups relationships among East Asia and eastern North America or Eurasia–North America–Central America within lethal amanitas are best explained by the diversification model of Palaeotropical origin, dispersal via the Bering Land Bridge, followed by regional vicariance speciation resulting from climate change during the middle Oligocene to the present. These findings indicate the importance of both dispersal and vicariance in shaping the intercontinental distributions of these ectomycorrhizal fungi.
Data from: Multi-locus analyses indicate that Melastoma dendrisetosum, an endemic and endangered shrub in Hainan, is a distinct species
Melastoma dendrisetosum is an extremely narrowly distributed taxon endemic to the Diaoluo Mountain region in Hainan, China, and was recently taxonomically incorporated under a widespread species, M. sanguineum. Based on its distinct morphological traits, especially the indumentum on the hypanthium, we propose that it should represent a distinct species. In this study, we sequenced six partial nuclear genes and two chloroplast intergenic spacers of M. dendrisetosum and three other morphologically similar species, M. sanguineum, M. penicillatum, and M. normale, to clarify its taxonomic status. M. dendrisetosum exhibited an extremely low level of genetic diversity, and was well-separated from the three other species with no shared haplotypes at all six nuclear genes, supporting the hypothesis that it is a distinct species. This finding was also supported by the Bayesian clustering-based STRUCTURE analysis, phylogenetic analysis, and Bayesian species delimitation analysis. We further propose that M. dendrisetosum be categorized as 'Critically Endangered' under the IUCN criteria, due to its extremely small population and declining habitat quality. We suggest that the conservation of M. dendrisetosum be prioritized, and road construction in its range should be avoided, to protect this distinct and critically endangered species.
Figure 1 in Multi-locus analyses reveal four giraffe species instead of one
Figure 1. Distribution and Sampling Locations of Different Giraffe Subspecies in Africa
(legend on next page) in Multi-locus analyses reveal four giraffe species instead of one
(legend on next page)
Supplementary material 1 from: Chen D, Liu Q, Chang J, Jiang A, Zhou F, Zhang Y, Zhang Z (2016) Multi-locus analysis supports the taxonomic validity of Arborophila gingica guangxiensis Fang Zhou & Aiwu Jiang, 2008. ZooKeys 555: 125-136. https://doi.org/10.3897/zookeys.555.6814
Table S1 : Explanation note: Primers used for PCR amplification and sequencing in this study.
Figure 3 in Multi-locus analyses reveal four giraffe species instead of one
Figure 3. Population Structuring and Giraffe Divergence Times
Figure S3 in Multi-locus analyses reveal four giraffe species instead of one
Figure S3. Additional Structure and PCA analyses. Related to Figure 3.
(legend on next page) in Multi-locus analyses reveal four giraffe species instead of one
(legend on next page)
Figure 1 in Multi-locus analyses reveal four giraffe species instead of one
Figure 1. Distribution and Sampling Locations of Different Giraffe Subspecies in Africa
Figure 2 from: Chen D, Liu Q, Chang J, Jiang A, Zhou F, Zhang Y, Zhang Z (2016) Multi-locus analysis supports the taxonomic validity of Arborophila gingica guangxiensis Fang Zhou & Aiwu Jiang, 2008. ZooKeys 555: 125-136. https://doi.org/10.3897/zookeys.555.6814
Figure 2 - Phylogenetic consensus trees from the mtDNA matrix and complete data matrix. Node values above the branches represented the BI posterior probability and ML bootstrap support. Values below the branches represent the divergence times (median) and 95% highest posterior density (HPD) between lineage groups, note that the divergence times in the multi-locus tree were estimated by species tree analysis. The last number in tip labels in the multi-locus tree represent the two haplotypes phased from diploid nuclear sequences.
Figure 1 from: Chen D, Liu Q, Chang J, Jiang A, Zhou F, Zhang Y, Zhang Z (2016) Multi-locus analysis supports the taxonomic validity of Arborophila gingica guangxiensis Fang Zhou & Aiwu Jiang, 2008. ZooKeys 555: 125-136. https://doi.org/10.3897/zookeys.555.6814
Figure 1 - Map of southeast China showing the distribution area of Arborophila gingica. The purple area represents the distribution of the nominate subspecies Arborophila gingica gingica according to del Hoyo and Collar (2014), with the dark blue dot indicating the sampling site in Wuyishan Mountain. The orange dots represent the three isolated populations of Arborophila gingica guangxiensis (Zhou and Jiang 2008), with the sampling site in Jiuwanshan Mountain.
Data from: Evaluating summary methods for multi-locus species tree estimation in the presence of incomplete lineage sorting
Open the record for dataset details and reuse information.
Data from: Multi-locus phylogeny of the Afrotropical freshwater crab fauna reveals historical drainage connectivity and transoceanic dispersal since the Eocene
Open the record for dataset details and reuse information.
Data from: Multi-locus phylogeny of lethal amanitas: implications for species diversity and historical biogeography
Open the record for dataset details and reuse information.
Data from: Multi-locus analyses indicate that Melastoma dendrisetosum, an endemic and endangered shrub in Hainan, is a distinct species
Open the record for dataset details and reuse information.
Data from: Addressing gene tree discordance and non-stationarity to resolve a multi-locus phylogeny of the flatfishes (Teleostei: Pleuronectiformes)
Open the record for dataset details and reuse information.
Data from: Multi-locus phylogenetic analysis reveals the pattern and tempo of bony fish evolution
Open the record for dataset details and reuse information.
Data from: Resolving ambiguity of concatenation in multi-locus sequence data for the construction of phylogenetic supermatrices
Open the record for dataset details and reuse information.
Multi-locus microsatellite genotypes of Pocillopora acuta (Scleractinia: Pocilloporidae) in the Bolinao-Anda Reef Complex, Philippines
Open the record for dataset details and reuse information.
ScienceDex guides
Understand access before you commit
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.