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Figure 6 in Phylogenetic biome conservatism as a key concept for an integrative understanding of evolutionary history: Galliformes and Falconiformes as study cases
Figure 6. Colonization dynamics of Falconiformes. Each graph represents the rate of colonization by new lineages for each biome throughout the Cenozoic.
Figure 4 in Phylogenetic biome conservatism as a key concept for an integrative understanding of evolutionary history: Galliformes and Falconiformes as study cases
Figure 4. Biome transitions in Galliformes. The number of recent species is indicated inside the circles. Arrow thickness is proportional to the number of colonizations. The dashed lines indicate only one colonization event. The number of transitions that did not imply colonization (niche conservatism) is indicated as different areas of the circles, classified in five categories. For more details about absolute scores, see Table 2.
Figure 2 in Phylogenetic biome conservatism as a key concept for an integrative understanding of evolutionary history: Galliformes and Falconiformes as study cases
Figure 2. Ancestral biome reconstruction for Galliformes. Coloured circles represent the ten different biomes implemented in the model (Walter, 1970; Hernández Fernández, 2001); those at the nodes represent the inferred ancestral biome(s) occupancy; those at the tips correspond to the recent biome distribution of species. Along the time scale, geological and climatic histories are shown, in addition to intercontinental biotic interchanges. Abbreviations: Af, Africa; Au, Australia; EAs, Eurasia; LB, land bridge; NA, North America; SA, South America.
Figure 3 in Phylogenetic biome conservatism as a key concept for an integrative understanding of evolutionary history: Galliformes and Falconiformes as study cases
Figure 3. Colonization dynamics of Galliformes. Each graph represents the rate of colonization by new lineages for each biome throughout the Cenozoic.
Figure 1 in Phylogenetic biome conservatism as a key concept for an integrative understanding of evolutionary history: Galliformes and Falconiformes as study cases
Figure 1. Schematic explanatory example for transition categories considered in this study: transition with biome conservatism; transition with colonization; and transition with loss of ancestral biome occupation. Note that ancestral biome occupation (for node A) is the same above and below, whereas biome occupations for derived nodes B (above) and C (below) differ.
Figure 1. A in Evolutionary History of the Subgenus Mus in Eurasia with Special Emphasis on the House Mouse Mus musculus
Figure 1. A sketch of the evolutionary patterns of lineage differentiation among species in the genus Mus based on molecular phylogenetic analysis of nuclear gene sequences (Suzuki et al., 2004; Shimada et al., 2010). The tree shows the four subgenera of the genus Mus and the four species groups (SGs) of the subgenus Mus: M. musculus, M. booduga, M. lepidoides, and M. caroli (previously termed as M. cervicolor SG), representing four geographic regions of the Palaearctic region, Indian subcontinent, Myanmar, and Southeast Asia, respectively. The taxon previously regarded as "M. cervicolor" in Thailand is here referred to as "M. sp.", due to uncertainty regarding the taxonomic status of the sampled specimens (see main text). The estimated divergence times for the subgenera and species groups are approximately 5 and 2.5 million years ago, respectively (Shimada et al., 2010). Specific habitat transitions from grasslands to forests and arid areas are marked for the species lineages of M. cookii and M. lepidoides. Predicted dispersal events between geographic regions are indicated with dotted arrows.
Figures 2–4 in Evolutionary History of the Subgenus Mus in Eurasia with Special Emphasis on the House Mouse Mus musculus
Figures 2–4. Assessment of population genetic structure using concatenated sequences (4302 bp) of seven nuclear genes. (2) Positions of the analysed regions (open triangles) in seven genes on murine chromosome 8 (Nunome et al., 2010; Kodama et al., 2013). (3) Neighbour- Net network based on concatenated sequences from 98 Mus musculus, showing haplogroups representing the subspecies groups Mus musculus domesticus (DOM), Mus musculus castaneus (CAS), and Mus musculus musculus (MUS) as well as recombinant haplotypes (Re) (Kodama et al., 2013). In the network, the level of diversity of CAS is markedly higher than those of DOM and MUS, yielding five distinct phylogroups A–E. Scale bar indicates genetic divergence. (4) Approximate geographic ranges of the five subclusters of CAS. Localities where samples used in this analysis were collected are marked with open and filled circles, representing the mitochondrial haplogroup CAS-1 and all other types, respectively (Kodama et al., 2013). The phylogroups A–E of CAS showed rough geographical distributions and one of them, phylogroup D, comprised the haplotypes recovered from a large geographical area of Southeast Asia, south China, and Indonesia and can be characterized as the lineage dispersed with prehistoric human movement (arrow; Kodama et al., 2015). Note that subcluster D (arrow in Fig. 3) shows a broad distribution range in Southeast Asia and the southern part of East Asia. In the Neighbor-Net network, this subcluster exhibits limited divergence among haplotypes.
Data from: Rtapas: An R package to assess cophylogenetic signal between two evolutionary histories
<p class="MsoNormal"><span>Cophylogeny represents a framework to understand how ecological and evolutionary process influence lineage diversification. The recently developed algorithm Random Tanglegram Partitions provides a directly interpretable statistic to quantify the strength of cophylogenetic signal and incorporates phylogenetic uncertainty into its estimation, and maps onto a tanglegram the contribution to cophylogenetic signal of individual host-symbiont associations. We introduce </span><span>Rtapas</span><span>, an R package to perform Random Tanglegram Partitions. </span><span>Rtapas</span><span> </span><span>applies a given global-fit method to random partial tanglegrams of a fixed size to identify the associations, terminals, and internal nodes that maximize phylogenetic congruence. This new package extends the original implementation with a new algorithm that examines the contribution to phylogenetic incongruence of each host-symbiont association and adds ParaFit, a method designed to test for topological congruence between two phylogenies, to the list of global-fit methods than can be applied. </span><span>Rtapas</span><span> </span><span>facilitates and speeds up cophylogenetic analysis, as it can handle large phylogenies (100+ terminals) in affordable computational time as illustrated with two real-world examples. </span><span>Rtapas</span><span> </span><span>can particularly cater for the need for causal inference in cophylogeny in two domains: (i) Analysis of complex and intricate host-symbiont evolutionary histories and (ii) assessment of topological (in)congruence between phylogenies produced with different DNA markers and specifically identify subsets of loci for phylogenetic analysis that are most likely to reflect gene-tree evolutionary histories.</span></p>
Fig.3 in A global phylogeny of butterflies reveals their evolutionary history, ancestral hosts and biogeographic origins
Fig.3 | Relativemeandispersalratesofbutterfliesbetweenbioregions. Numbersbesideeacharrowareaverageratesfrom 1,000 simulationsusing biogeographicstochasticmappingin BioGeoBEARS. Thesenumbersweredividedby 100 foreaseof comparison (rawvaluescanbefoundin Supplementary Data 5). E., Eastern;W., Western.
Fig. 1 in A global phylogeny of butterflies reveals their evolutionary history, ancestral hosts and biogeographic origins
Fig. 1 | Evolutionaryrelationshipsanddiversificationpatternsofbutterflies. Time-calibratedtreeof 2,244 butterflyspeciesbasedon 391 loci and 150 amino acidpartitions.Branchesshowdistinctchangesindiversification (circles) asestimatedbyclade-specificmodels.Lettersatnodesrefertocladeswith significantrateshifts (seesection 6 of Supplementary Results).Colouredlines intheouterringbesidetipsindicateassociationwithoneof the 13 hostmodules (seesection 17 of Extended Online Methods).Blacklinesinthehostassociation ringindicatespecieswithoutdata,andasterisksdenotenon-monophyletic subfamilies.Supplementary Fig. 1 showsthistreewithvisiblespeciesnamesand agesforallnodes.
Fig. 2 in A global phylogeny of butterflies reveals their evolutionary history, ancestral hosts and biogeographic origins
Fig. 2 | Distributionofbutterfliesovertime. Bioregionshadingindicatesthenumberofbutterflylineagesthatwereassociatedwiththatbioregionduringthattime period,asdeterminedby BioGeoBEARSancestralstatereconstruction.Eachmapcorrespondstoa 15-Maintervalofbutterfly evolution.Resultsarebasedon data fromthisstudy.
A new molecular phylogeny of salps (Tunicata: Thalicea: Salpida) and the evolutionary history of their colonial architecture
<p>Salps are marine pelagic urochordates with a complex life cycle including a solitary and colonial stage composed of asexually-budded individuals. These colonies develop into species-specific architectures with distinct zooid orientations, including transversal, oblique, linear, helical, and bipinnate chains; as well as whorls, and clusters. The evolutionary history of salp colony architecture has remained obscured due to the lack of a homology-based ontology to characterize architectures, as well as a lack of phylogenetic taxon sampling and resolution of critical nodes. We (1) collected and first-time sequenced eight species of salps, (2) inferred the phylogenetic relationships among salps, and (3) reconstructed the evolutionary history of salp colony architecture. We collected salp specimens via offshore SCUBA diving, dissected tissue samples, extracted their DNA, amplified their 18S gene, and sequenced them using Sanger technology. We inferred a new molecular phylogeny using both Maximum Likelihood and Bayesian approaches. Using this phylogeny, we reconstructed the ancestral states of colony architecture using a Bayesian ordered Markov model informed by the presence and absence of specific developmental mechanisms that lead to each architecture. We find that the ancestral salp architecture is either oblique or linear, with every other state being derived. Moreover, linear chains have evolved independently at least three times. While transversal chains are developmentally basal and hypothesized to be ancestral, our phylogenetic topology and reconstructions strongly indicate that they are evolutionarily derived through the loss of zooid torsion. These traits are likely critical to multijet locomotory performance and evolving under natural selection. Our work showcases the need to study the broader diversity of salp species in order to gain a comprehensive understanding of their organismal biology, evolutionary history, and ecological roles in pelagic ecosystems.</p>
Population demographic history and evolutionary rescue: Influence of a bottleneck event
<p class="p1">Rapid environmental change presents a significant challenge to the persistence of natural populations. Rapid adaptation that increases population growth, enabling populations that declined following severe environmental change to grow and avoid extinction, is called evolutionary rescue. Numerous studies have shown that evolutionary rescue can indeed prevent extinction. Here, we extend those results by considering the demographic history of populations. To evaluate how demographic history influences evolutionary rescue, we created 80 populations of red flour beetle, <em>Tribolium castaneum</em>, with three classes of demographic history: diverse populations that did not experience a bottleneck, and populations that experienced either an intermediate or a strong bottleneck. We subjected these populations to a new and challenging environment for six discrete generations and tracked extinction and population size. Populations that did not experience a bottleneck in their demographic history avoided extinction entirely, while more than 20% of populations that experienced an intermediate or strong bottleneck went extinct. Similarly, among the extant populations at the end of the experiment, adaptation increased the growth rate in the novel environment the most for populations that had not experienced a bottleneck in their history. Taken together, these results highlight the importance of considering the demographic history of populations to make useful and effective conservation decisions and management strategies for populations experiencing environmental change that pushes them toward extinction.</p>
FIGURE 5 A in The evolutionary history of the white wagtail species complex, (Passeriformes: Motacillidae: Motacilla alba)
FIGURE 5 A) Geographical distribution of haplotypes based on clades. B) Geographical distribution of haplotypes based on haplotypes diversity in PopART 1.7.
FIGURE 4 in The evolutionary history of the white wagtail species complex, (Passeriformes: Motacillidae: Motacilla alba)
FIGURE 4 Estimates of phylogenetic tree, divergence times and LAGRANGE ancestral area reconstructions of the M. alba complex. The chronogram tree is based on BEAST analysis of the combined dataset. Colour pies indicate the origin of a given node based on four zoogeographical areas followed by LAGRANGE analysis.
FIGURE 2 in The evolutionary history of the white wagtail species complex, (Passeriformes: Motacillidae: Motacilla alba)
FIGURE 2 Ecological niche modelling pattern of white wagtail during the present, Holocene, and LGM. Red, orange and yellow colours represent more suitable areas for the species; green indicates less suitable areas.
Fig. 7 in Reconstruction of Evolutionary History of Pleurostomatid Ciliates (Ciliophora, Litostomatea, Haptoria): Interplay of Morphology and Molecules
Fig. 7. Reconstruction of ancestral morphologies in pleurostomatids. Schematic drawings are based on the results of the likelihood method in combination with the Markov evolutionary model implemented in the computer program Mesquite. aE – apical group of oral extrusomes, B – dorsal brush, CV – contractile vacuoles, MA – macronucleus, MI – micronucleus, oE – extrusomes attached along the whole length of the oral bulge, PeK1–3 – preoral kineties 1–3, sE – extrusomes attached to the somatic cortex.
Fig. 3 in Reconstruction of Evolutionary History of Pleurostomatid Ciliates (Ciliophora, Litostomatea, Haptoria): Interplay of Morphology and Molecules
Fig. 3. Phylogenetic analysis of the combined molecular and morphological dataset comprising 26 haptorian taxa and 1492 characters. The tree was constructed with Bayesian inference using mixed models and with the maximum parsimony analysis implemented in PAUP*. Nodal support is indicated by posterior probabilities for Bayesian inference and the bootstrap values for the maximum parsimony. A dash indicates MP bootstraps below 50%. The scale bar indicates two changes per one hundred characters.
Fig. 5. Split support spectrum for the 18S in Reconstruction of Evolutionary History of Pleurostomatid Ciliates (Ciliophora, Litostomatea, Haptoria): Interplay of Morphology and Molecules
Fig. 5. Split support spectrum for the 18S rRNA gene alignment used to construct the phylogenetic network in Fig. 4. Column height represents the number of clade-supporting positions, i.e., putative primary homologies. Column parts above the y-axis represent the in-group partition, while those below the axis correspond to the out-group partition.
Fig. 2 in Reconstruction of Evolutionary History of Pleurostomatid Ciliates (Ciliophora, Litostomatea, Haptoria): Interplay of Morphology and Molecules
Fig. 2. Small subunit rRNA gene phylogeny based on 1462 nucleotide characters from 26 haptorian taxa. The tree was constructed using three methods (Bayesian inference, maximum likelihood, and maximum parsimony) with the GTR + I + Γ evolutionary model and the gamma shape parameter at 0.4970, the proportion of invariable sites at 0.6150, and a rate matrix for the model as suggested by jModeltest. Nodal supports are indicated as follows: posterior probabilities for the Bayesian inference / bootstrap values for maximum likelihood / bootstrap values for maximum parsimony. A dash indicates MP bootstraps below 50%. The scale bar indicates two substitutions per one hundred nucleotide positions. Sequences in bold were obtained during this study.
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Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
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