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115 results for “Multi-locus”
Data from: Comparative multi-locus phylogeography of two Palaearctic spruce bark beetles: influence of contrasting ecological strategies on genetic variation
While phylogeographic patterns of organisms are often interpreted through past environmental disturbances, mediated by climate changes, and geographic barriers, they may also be strongly influenced by species-specific traits. To investigate the impact of such traits, we focused on two Eurasian spruce bark beetles that share a similar geographic distribution, but differ in their ecology and reproduction. Ips typographus is an aggressive tree-killing species characterized by strong dispersal, whereas Dendroctonus micans is a discrete inbreeding species (sib mating is the rule), parasite of living trees and a poor disperser. We compared genetic variation between the two species over both beetles' entire range in Eurasia with five independent gene fragments, to evaluate whether their intrinsic differences could have an influence over their phylogeographic patterns. We highlighted widely divergent patterns of genetic variation for the two species and argue that the difference is indeed largely compatible with their contrasting dispersal strategies and modes of reproduction. In addition, genetic structure in I. typographus divides European populations in a northern and a southern group, as was previously observed for its host plant, and suggests past allopatric divergence. A long divergence time was estimated between East Asian and other populations of both species, indicating their long-standing presence in Eurasia, prior to the last glacial maximum. Finally, the strong population structure observed in D. micans for the mitochondrial locus provides insights into the recent colonization history of this species, from its native European range to regions where it was recently introduced.
Data from: Understanding the mechanisms of anti-tropical divergence in the seabird White-faced Storm-petrel (Procellariiformes: Pelagodroma marina) using a multi-locus approach
Analytical methods that apply coalescent theory to multilocus data have improved inferences of demographic parameters that are critical to understanding population divergence and speciation. In particular, at the early stages of speciation, it is important to implement models that accommodate conflicting gene trees, and benefit from the presence of shared polymorphisms. Here, we employ eleven nuclear loci and the mitochondrial control region to investigate the phylogeography and historical demography of the pelagic seabird White-faced Storm-petrel (Pelagodroma marina) by sampling subspecies across its antitropical distribution. Groups are all highly differentiated: global mitochondrial ΦST = 0.89 (P < 0.01) and global nuclear ΦST varies between 0.22 and 0.83 (all P < 0.01). The complete lineage sorting of the mitochondrial locus between hemispheres is corroborated by approximately half of the nuclear genealogies, suggesting a long-term antitropical divergence in isolation. Coalescent-based estimates of demographic parameters suggest that hemispheric divergence of P. marina occurred approximately 840 000 ya (95% HPD 582 000–1 170 000), in the absence of gene flow, and divergence within the Southern Hemisphere occurred 190 000 ya (95% HPD 96 000–600 000), both probably associated with the profound palaeo-oceanographic changes of the Pleistocene. A fledgling sampled in St Helena (tropical South Atlantic) suggests recent colonization from the Northern Hemisphere. Despite the great potential for long-distance dispersal, P. marina antitropical groups have been evolving as independent, allopatric lineages, and divergence is probably maintained by philopatry coupled with asynchronous reproductive phenology and local adaptation.
Data from: Multi-locus sequence data reveal a new species of coral reef goby (Teleostei: Gobiidae: Eviota), and evidence of Pliocene vicariance across the Coral Triangle
Here, multi-locus sequence data are coupled with observations of live colouration to recognize a new species, Eviota punyit from the Coral Triangle, Indian Ocean and Red Sea. Relaxed molecular clock divergence time estimation indicates a Pliocene origin for the new species, and the current distribution of the new species and its sister species Eviota sebreei supports a scenario of vicariance across the Indo-Pacific Barrier, followed by subsequent range expansion and overlap in the Coral Triangle. These results are consistent with the 'centre of overlap' hypothesis, which states that the increased diversity in the Coral Triangle is due in part to the overlapping ranges of Indian Ocean and Pacific Ocean faunas. These findings are discussed in the context of other geminate pairs of coral reef fishes separated by the Indo-Pacific Barrier.
Data from: An integrative approach to phylogeography: investigating the effects of ancient seaways, climate, and historical geology on multi-locus phylogeographic boundaries of the arboreal salamander (Aneides lugubris)
Background: Phylogeography is an important tool that can be used to reveal cryptic biodiversity and to better understand the processes that promote lineage diversification. We studied the phylogeographic history of the Arboreal Salamander (Aneides lugubris), a wide-ranging species endemic to the California floristic province. We used multi-locus data to reconstruct the evolutionary history of A. lugubris and to discover the geographic location of major genetic breaks within the species. We also used species distribution modeling and comparative phylogeography to better understand the environmental factors that have shaped the genetic history of A. lugubris. Results: We found six major mitochondrial clades in A. lugubris. Nuclear loci supported the existence of at least three genetically distinct groups, corresponding to populations north of the San Francisco Bay and in the Sierra Nevada, in the Santa Cruz Mountains, and in the central coast and southern California. All of the genetic breaks in mitochondrial and nuclear loci corresponded to regions where historical barriers to dispersal have been observed in other species. Geologic or water barriers likely were the most important factors restricting gene flow among clades. Climatic unsuitability during glacial maximum may have contributed to the isolation of the mitochondrial clades in the central coast and southern California. A projection of our species distribution model to a future scenario with a moderate amount of climate change suggests that most of the range of A. lugubris will remain climatically suitable, but climatic conditions in the Sierra Nevada and low elevation areas in Southern California are likely to deteriorate. Conclusions: Aneides lugubris contains substantial cryptic genetic diversity as a result of historical isolation of populations. At least two (and perhaps three) evolutionarily significant units in A. lugubris merit protection; all six mitochondrial clades should be considered as management units within the species.
Data from: Deciphering the genomic architecture of the stickleback brain with a novel multi-locus gene-mapping approach
Quantitative traits important to organismal function and fitness, such as brain size, are presumably controlled by many small-effect loci. Deciphering the genetic architecture of such traits with traditional quantitative trait locus (QTL) mapping methods is challenging. Here, we investigated the genetic architecture of brain size (and the size of five different brain parts) in nine-spined sticklebacks (Pungitius pungitius) with the aid of novel multi-locus QTL mapping approaches based on a de-biased LASSO method. Apart from having more statistical power to detect QTL and reduced rate of false positives than conventional QTL mapping approaches, the developed methods can handle large marker panels and provide estimates of genomic heritability. Single-locus analyses of an F2-interpopulation cross with 239 individuals and 15 198 fully informative single nucleotide polymorphisms (SNPs) uncovered 79 QTL associated with variation in stickleback brain size traits. Many of these loci were in strong linkage disequilibrium (LD) with each other, and consequently, a multi-locus mapping of individual SNPs, accounting for LD structure in the data, recovered only four significant QTL. However, a multi-locus mapping of SNPs grouped by linkage group (LG) identified 14 LGs (1-6 depending on the trait) that influence variation in brain traits. For instance, 17.6% of the variation in relative brain size was explainable by cumulative effects of SNPs distributed over six LGs, whereas 42% of the variation was accounted for by all 21 LGs. Hence, the results suggest that variation in stickleback brain traits is influenced by many small-effect loci. Apart from suggesting moderately heritable (h2 ≈ 0.15-0.42) multifactorial genetic architecture of brain traits, the results highlight the challenges in identifying the loci contributing to variation in quantitative traits. Nevertheless, the results demonstrate that the novel QTL mapping approach developed here has distinctive advantages over the traditional QTL mapping methods in analyses of dense marker panels.
FIGURE 9 in Multi-locus phylogeny and taxonomic revision of Uperoleia toadlets (Anura: Myobatrachidae) from the western arid zone of Australia, with a description of a new species
FIGURE 9. Photos in life (dorsolateral and dorsal views) and after preservation (ventral view) of U. saxatilis sp. nov. holotype (WAM R162877) from Turee Creek, Western Australia. Photos by P. Doughty.
FIGURE 5 in Multi-locus phylogeny and taxonomic revision of Uperoleia toadlets (Anura: Myobatrachidae) from the western arid zone of Australia, with a description of a new species
FIGURE 5. Plot showing results of Principle Components Analysis (top) and Discriminant Function Analysis (bottom) on body proportion variables only, see text for details. Uperoleia micromeles is the most distinct and U. russelli and U. saxatilis sp. nov. are indistinguishable based on these characters, but each is distinct based on genetic, call and other morphological characters.
FIGURE 6 in Multi-locus phylogeny and taxonomic revision of Uperoleia toadlets (Anura: Myobatrachidae) from the western arid zone of Australia, with a description of a new species
FIGURE 6. Oscillographs and spectrograms of (a) U. glandulosa, U. russelli (b) long call and (c) short call, U. talpa (d) long call and (e) short call, and U. saxatilis sp. nov. (f) long call and (g) short call.
FIGURE 1 in Multi-locus phylogeny and taxonomic revision of Uperoleia toadlets (Anura: Myobatrachidae) from the western arid zone of Australia, with a description of a new species
FIGURE 1. Geological regions of the western arid zone of Australia. Solid lines denote geological boundaries and dotted lines represent rivers. Modified from Beard & Webb (1974), Beard (1975, 1979), and Interim Biogeographic Regions of Australia version 6.1 (Commonwealth of Australia 2005).
FIGURE 4 in Multi-locus phylogeny and taxonomic revision of Uperoleia toadlets (Anura: Myobatrachidae) from the western arid zone of Australia, with a description of a new species
FIGURE 4. Molecular phylogeny of the genus Uperoleia based on a combined analysis of five genes including the mtDNA genes 16S and ND2 and the nuclear loci RAG-1, POMC, and BNDF (total 4,152 bp). The phylogeny shown is based on a partitioned Bayesian analysis, see text for details. Values above the branches are Bayesian posterior probabilities and values below are the parsimony bootstrap values.
FIGURE 3 in Multi-locus phylogeny and taxonomic revision of Uperoleia toadlets (Anura: Myobatrachidae) from the western arid zone of Australia, with a description of a new species
FIGURE 3. Molecular phylogeny of the genus Uperoleia based on the mtDNA genes 16S and ND2 (total 2,047 bp), including all tissues available for sequencing from the western arid zone. The phylogeny shown is based on a partitioned Bayesian analysis where each gene represents one partition. Values above the branches are Bayesian posterior probabilities and values below are the parsimony bootstrap values.
FIGURE 2 in Multi-locus phylogeny and taxonomic revision of Uperoleia toadlets (Anura: Myobatrachidae) from the western arid zone of Australia, with a description of a new species
FIGURE 2. Extent of webbing relative to tubercle position on the fourth toe. a) basal webbing, b) webbing extends to the first proximal tubercle, c) webbing extends to halfway between the first and second proximal tubercles, d) webbing extends to the second proximal tubercle.
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 (A) Distribution ranges (colored shading) provided by the Giraffe Conservation Foundation [7], plotted on a map of Africa (http://www.naturalearthdata. com/). Circles represent sampling locations; for coding, see Figure 2. (B) Enlarged view of the South Sudan region. Note that the samples of the putative Nubian giraffe were taken west and east of the Nile River. See also Table S1.
Supplementary material 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 S1 : Explanation note: Phylogenetic trees from the nuDNA matrix and each of the nuclear introns.
FIGURE 2 in Multi-locus phylogeny of southern African Acontias aurantiacus (Peters) subspecies (Scincidae: Acontinae) confirms the presence of three genetically, geographically and morphologically discrete taxa
FIGURE 2. Haplotype phylogeny of the South African and nominate subspecies of Acontias aurantiacus inferred from a concatenated cyt b, 16S and RAG1 dataset comprising of 3,159 nucleotides (cyt b = 1,045, 16S = 526 and RAG1 = 1,588 nt) using a Maximum Likelihood algorithm. Maximum Likelihood (ML) bootstrap values ḵ70% (upper) and Bayesian posterior probability (BPP, lower) support values ḵ0.95 are indicated, while nodes with statistical support below these thresholds have no associated support values. Melanistic specimens are indicated with an asterisk and the mottled specimen with a cross.
FIGURE 1 in Multi-locus phylogeny of southern African Acontias aurantiacus (Peters) subspecies (Scincidae: Acontinae) confirms the presence of three genetically, geographically and morphologically discrete taxa
FIGURE 1. Molecular phylogeny of the genus Acontias inferred using a Maximum Likelihood algorithm and a concatenated cyt b, 16S and RAG1 dataset comprising of 2,244 nt. Maximum Likelihood (ML) bootstrap values ḵ70% and Bayesian posterior probability (BPP) support values ḵ0.95 are shown above and below each of the supported nodes, respectively, while unsupported nodes have no associated values. Taxa marked with an asterisk were sourced from GenBank.
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 (A) Distribution ranges (colored shading) provided by the Giraffe Conservation Foundation [7], plotted on a map of Africa (http://www.naturalearthdata. com/). Circles represent sampling locations; for coding, see Figure 2. (B) Enlarged view of the South Sudan region. Note that the samples of the putative Nubian giraffe were taken west and east of the Nile River. See also Table S1.
Figure S3 in Multi-locus analyses reveal four giraffe species instead of one
Figure S3. Additional Structure and PCA analyses. Related to Figure 3. A) Structure analysis for all subspecies for K=2 to K=6. K=4 has the highest delta K and from K=5 increasing admixtures is evident. B) A separate Structure analysis for the subspecies of the northern giraffe reveals evidence for additional cluster of West African (WA) and Nubian (former Rothschild's, MF) giraffe. However, in this data set haplotypes sharing with other subspecies is evident and these are not distinct in other analyses. C) Southern giraffe do not show additional clustering when analyzed separately. This is in contrast the the clear separation of the subspecies by mtDNA sequences. Abbreviations for the geographic origin are explained in Table S1. D) PCAs of giraffe haplotypes with grouping according to traditional nine subspecies classification 1 - G. c. angolensis, 2 - G. c. antiquorum, 3 – G. c. thornicrofti, 4 - G. c.
Figure S1 in Multi-locus analyses reveal four giraffe species instead of one
Figure S1. Haplotype networks of seven intron sequences. Related to Figure 2 and 3. The networks for 105 giraffe show that numerous single alleles are shared and that for most loci subspecies cannot be easily distinguished. Notable exceptions are intron 52 and 930 that are exclusive for Masai (tippelskirchi, including the formerly recognized Thornicroft's giraffe) and 241 that is nearly exclusive for the West African giraffe (peralta). Furthermore, a southern clade (angolensis plus giraffa) and northern clade (antiquorum, peralta, rothschildi) are prominent for most loci. The lack of further resolution is possibly a consequence of insufficient data and gene flow remains uncertain.
Figure S2 in Multi-locus analyses reveal four giraffe species instead of one
Figure S2. Evolutionary trees with details on the individual IDs. Related to Figure 2. A) ASTRAL tree from individual nuclear loci with ML branch lengths. While analysis of concatenated sequences is problematic [S1] a ML tree based on concatenated sequences, which shows the West African Giraffe separate can be found in doi:10.5061/dryad.h3tc2. B) BEAST mtDNA tree with details for accession numbers and individual IDs and their location. Note – the okapi branch (root) is not to scale in both figures to allow for better resolution among giraffe branches. Genbank accession numbers for published data are shown and are detailed in [S2] and individual ID and sample location can be found in doi:10.5061/dryad.h3tc2.
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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)
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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.