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70 results for “divergence time estimation”
The implications of lineage-specific rates for divergence time estimation
<p>Rate variation adds considerable complexity to divergence time estimation in molecular phylogenies. Here, we evaluate the impact of lineage-specific rates—which we define as among-branch-rate-variation that acts consistently across the entire genome. We compare its impact to residual rates—defined as among-branch-rate-variation that shows a different pattern of rate variation at each sampled locus, and gene-specific rates—defined as variation in the average rate across all branches at each sampled locus. We show that lineage-specific rates lead to erroneous divergence time estimates, regardless of how many loci are sampled. Further, we show that stronger lineage-specific rates lead to increasing error. This contrasts to residual rates and gene-specific rates, where sampling more loci significantly reduces error. If divergence times are inferred in a Bayesian framework, we highlight that error caused by lineage-specific rates significantly reduces the probability that the 95% highest posterior density includes the correct value, and leads to sensitivity to the prior. Use of a more complex rate prior—which has recently been proposed to model rate variation more accurately—does not affect these conclusions. Finally, we show that the scale of lineage-specific rates used in our simulation experiments is comparable to that of an empirical data set for the angiosperm genus Ipomoea. Taken together, our findings demonstrate that lineage-specific rates cause error in divergence time estimates, and that this error is not overcome by analyzing genomic scale multilocus data sets.</p>
FIGURE 1 in Molecular phylogeny and divergence time estimates of Penaeid Shrimp Lineages (Decapoda: Penaeidae)
FIGURE 1. ML phylogeny for penaeidae family, reconstructed using 16S, COI and concatenated sequences. For 16S and COI phylogenies only ML bootstrap values are shown. For the concatenated sequence tree bootstrap support values for ML, BI, and NJ are shown near interior branches. Bootstrap values lower than 50 are not shown. Species with circles, triangles and squares belong respectively to Penaeini, Trachypenaeini, and Parapenaeini clades, following Burkenroad's (1953) traditional classification. The Penaeini clade (bold branches) was used in divergence times estimates. Letters A, B and C are references for the nodes where time constrains were set.
Data from: Fossils matter: improved estimates of divergence times in Pinus reveal older diversification
Background: The taxonomy of pines (genus Pinus) is widely accepted and a robust gene tree based on entire plastome sequences exists. However, there is a large discrepancy in estimated divergence times of major pine clades among existing studies, mainly due to differences in fossil placement and dating methods used. We currently lack a dated molecular phylogeny that makes use of the rich pine fossil record, and this study is the first to estimate the divergence dates of pines based on a large number of fossils (21) evenly distributed across all major clades, in combination with applying both node and tip dating methods. Results: We present a range of molecular phylogenetic trees of Pinus generated within a Bayesian framework. We find the origin of pines is likely up to 30 Myr older (Early Cretaceous) than inferred in most previous studies (Late Cretaceous) and propose generally older divergence times for major clades within Pinus than previously thought. Our age estimates vary significantly between the different dating approaches, but the results generally agree on older divergence times. We present a revised list of 21 fossils that are suitable to use in dating or comparative analyses of pines. Conclusions: Reliable estimates of divergence times in pines are essential if we are to link diversification processes and functional adaptation of this genus to geological events or to changing climates. In addition to older divergence times in Pinus, our results also indicate that node age estimates in pines depend on dating approaches and the specific fossil sets used, reflecting inherent differences in various dating approaches. The sets of dated phylogenetic trees of pines presented here provide a way to account for uncertainties in age estimations when applying comparative phylogenetic methods.
Figure 6 in A phylogeny with divergence-time estimation of planthoppers (Hemiptera: Fulgoroidea) based on mitochondrial sequences
Figure 6. Chronogram of Fulgoroidea estimated using the Bayesian phylogenetic by MCMCTREE in paml. Time units are in millions of years. Estimated divergence times are shown near nodes.
Figure 5 in A phylogeny with divergence-time estimation of planthoppers (Hemiptera: Fulgoroidea) based on mitochondrial sequences
Figure 5. BI analysis (PhyloBayes) based on PCG12R–ATP8. Numerals at nodes are Bayesian posterior probabilities (PP). '–' indicates different clades.
Figure 1 in A phylogeny with divergence-time estimation of planthoppers (Hemiptera: Fulgoroidea) based on mitochondrial sequences
Figure 1. Sliding window analysis. The red curve shows the value of nucleotide diversity (Pi). Pi value of each PCG is shown below the arrows.
Figure 4 in A phylogeny with divergence-time estimation of planthoppers (Hemiptera: Fulgoroidea) based on mitochondrial sequences
Figure 4. BI analysis (MrBayes) based on PCG12R–ATP8. Numerals at nodes are Bayesian posterior probabilities (PP). '–' indicates different clades.
Figure 2 in A phylogeny with divergence-time estimation of planthoppers (Hemiptera: Fulgoroidea) based on mitochondrial sequences
Figure 2. Genetic distance (on average) and ratio of non-synonymous (Ka) to synonymous (Ks) substitution rates.
Figure 3 in A phylogeny with divergence-time estimation of planthoppers (Hemiptera: Fulgoroidea) based on mitochondrial sequences
Figure 3. ML analysis based on PCG12R–ATP8. Numerals at nodes are bootstrap values (BS). '–' indicates different clades.
Fig. 3 Chronogram showing the relationships and divergence times for 80 bears, estimated from a concatenated mitochondrial dataset comprising all 13 protein coding and 2 in Examining the sensitivity of molecular species delimitations to the choice of mitochondrial marker
Fig. 3 Chronogram showing the relationships and divergence times for 80 bears, estimated from a concatenated mitochondrial dataset comprising all 13 protein coding and 2 ribosomal RNA genes. Groups delimited as species by the GMYC analysis are shown as triangles. The horizontal axis shows the timescale, measured in millions of years.
Fig. 2 Chronogram showing the relationships and divergence times for 357 cetaceans, estimated from a concatenated mitochondrial dataset comprising all 13 protein coding and 2 in Examining the sensitivity of molecular species delimitations to the choice of mitochondrial marker
Fig. 2 Chronogram showing the relationships and divergence times for 357 cetaceans, estimated from a concatenated mitochondrial dataset comprising all 13 protein coding and 2 ribosomal RNA genes. Groups delimited as species by the GMYC analysis are shown as triangles. The horizontal axis shows the timescale, measured in millions of years.
Fig. 2 in Divergence time estimation in Cichorieae (Asteraceae) using a fossil-calibrated relaxed molecular clock
Fig. 2 Chronogram of Cichorieae produced by the program BEAST based on ITS1 and ITS2 sequences (unconstrained topology; maximum clade credibility tree with mean node heights obtained by stem group node calibration). Posterior probabilities of nodes are shown
FIGURE 3 in Review of the systematic status of Sceloporus arenicolus Degenhardt and Jones, 1972 with an estimate of divergence time
FIGURE 3. Consensus tree from Bayesian phylogenetic analysis. Bayesian posterior probabilities (PP) and ML bootstrap support (BS) are noted at nodes with high support (> 95% PP and 75 BS) and at basal nodes. Nodal support of PP = 1 and BS = 100 are indicated with a solid circle at the branch. Shaded symbols correspond to collection localities on Figure 1.
FIGURE 2. Minimum spanning haplotype networks for all S in Review of the systematic status of Sceloporus arenicolus Degenhardt and Jones, 1972 with an estimate of divergence time
FIGURE 2. Minimum spanning haplotype networks for all S. graciosus group samples sequenced at each of three nuclear loci. Size of each circle corresponds to the frequency of that haplotype. Shading corresponds to clade membership in Figure 3.
FIGURE 1 in Review of the systematic status of Sceloporus arenicolus Degenhardt and Jones, 1972 with an estimate of divergence time
FIGURE 1. Collection localities for samples from the Sceloporus graciosus group included in this study. Colored symbols correspond to clade membership on Figure 3; three individuals for which we only have sequence data at R35 are indicated with stars. Putative species and subspecies boundaries are shaded for the members of the Sceloporus graciosus group. Sceloporus graciosus graciosus: dark gray distribution, S. g. gracilis: light gray distribution, S. g. vandenburgianus: brown distribution, and S. arenicolus: black distribution.
FIGURE 5 in Biogeography and divergence time estimation of the relict Cape dragonfly genus Syncordulia: global significance and implications for conservation
FIGURE 5. Present distributions of Syncordulia species in South Africa. Uppermost box shows the distributions of all Syncordulia species, lower boxes show individual species distributions: S. gracilis (top and top left); S. legator (top right); S. serendipator (bottom left); S. venator (bottom right).
FIGURE 3. R8S in Biogeography and divergence time estimation of the relict Cape dragonfly genus Syncordulia: global significance and implications for conservation
FIGURE 3. R8S analysis on a 26-taxon tree; Geological maps adapted from figures on rst.gsfc.nasa.gov.
FIGURE 4 in Biogeography and divergence time estimation of the relict Cape dragonfly genus Syncordulia: global significance and implications for conservation
FIGURE 4. Ancestral distributions; DIVA analysis optimized with 2 regions; larger letters indicate the scenarios discussed in the text
FIGURE 1. Strict consensus tree from a in Biogeography and divergence time estimation of the relict Cape dragonfly genus Syncordulia: global significance and implications for conservation
FIGURE 1. Strict consensus tree from a PAUP parsimony heuristic search; 10,000 addition sequence replicates; bootstrap support shown above branches
FIGURE 2. Consensus tree from a in Biogeography and divergence time estimation of the relict Cape dragonfly genus Syncordulia: global significance and implications for conservation
FIGURE 2. Consensus tree from a PHASE analysis; 10 million generations. Posterior probabilities shown above branches
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