The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
A genome-scale phylogeny of the kingdom Fungi
Open accessAbstract
Summary Phylogenomic studies using genome-scale amounts of data have greatly improved understanding of the tree of life. Despite the diversity, ecological significance, and biomedical and industrial importance of fungi, evolutionary relationships among several major lineages remain poorly resolved, especially those near the base of the fungal phylogeny. To examine poorly resolved relationships and assess progress toward a genome-scale phylogeny of the fungal kingdom, we compiled a phylogenomic data matrix of 290 genes from the genomes of 1,644 species that includes representatives from most major fungal lineages. We also compiled 11 data matrices by subsampling genes or taxa from the full data matrix based on filtering criteria previously shown to improve phylogenomic inference. Analyses of these 12 data matrices using concatenation- and coalescent-based approaches yielded a robust phylogeny of the fungal kingdom in which ~85% of internal branches were congruent across data matrices and approaches used. We found support for several historically poorly resolved relationships as well as evidence for polytomies likely stemming from episodes of ancient diversification. By examining the relative evolutionary divergence of taxonomic groups of equivalent rank, we found that fungal taxonomy is broadly aligned with both genome sequence divergence and divergence time, but also identified lineages where current taxonomic circumscription does not reflect their levels of evolutionary divergence. Our results provide a robust phylogenomic framework to explore the tempo and mode of fungal evolution and offer directions for future fungal phylogenetic and taxonomic studies. In brief Li et al. analyze 290 genes from 1,644 species to infer a genome-scale phylogeny of the fungal kingdom. Analyses using different approaches and data matrices show that 85% of inferred relationships among fungi are robustly supported. The results provide a robust phylogenomic framework to explore the tempo and mode of fungal evolution.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability
Katoh, K., & Standley, D. M. (2013) · Molecular Biology and Evolution · doi:10.1093/molbev/mst010 · Cited by 46,209
ModelFinder: fast model selection for accurate phylogenetic estimates
Kalyaanamoorthy, S., Minh, B. Q., Wong, T. K. F., von Haeseler, A., & Jermiin, L. S. (2017) · Nature Methods · doi:10.1038/nmeth.4285 · Cited by 18,449
IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era
Minh, B. Q., Schmidt, H. A., Chernomor, O., Schrempf, D., Woodhams, M. D., von Haeseler, A., & Lanfear, R. (2020) · Molecular Biology and Evolution · doi:10.1093/molbev/msaa015 · Cited by 16,873
Genome-scale approaches to resolving incongruence in molecular phylogenies.
Rokas, A., Williams, B. L., King, N., & Carroll, S. B. (2003) · Nature · doi:10.1038/nature02053 · Cited by 1,512
Self-citationTempo and Mode of Genome Evolution in the Budding Yeast Subphylum
Shen, X.-X., Opulente, D. A., Kominek, J., Zhou, X., Steenwyk, J. L., Buh, K. V., Haase, M. A. B., Wisecaver, J. H., Wang, M., Doering, D. T., et al. (2018) · Cell · doi:10.1016/j.cell.2018.10.023 · Cited by 619
Self-citationInferring ancient divergences requires genes with strong phylogenetic signals
Salichos, L., & Rokas, A. (2013) · Nature · doi:10.1038/nature12130 · Cited by 616
Self-citationContentious relationships in phylogenomic studies can be driven by a handful of genes
Shen, X.-X., Hittinger, C. T., & Rokas, A. (2017) · Nature Ecology & Evolution · doi:10.1038/s41559-017-0126 · Cited by 520
Self-citationError, signal, and the placement of Ctenophora sister to all other animals
Whelan, N. V., Kocot, K. M., Moroz, L. L., & Halanych, K. M. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1503453112 · Cited by 331 · cited 1×
“Top100_slow-evolving – data matrix #8 This data matrix was constructed by retaining the 100 BUSCO genes with the lowest values of average pairwise patristic distance, which has previously been used to evaluate if fast-evolving genes bias phylogenetic inference 29,79 .”
Torruella, G., Derelle, R., Paps, J., Lang, B. F., Roger, A. J., Shalchian-Tabrizi, K., & Ruiz-Trillo, I. (2012) · Molecular Biology and Evolution · doi:10.1093/molbev/msr185 · Cited by 169
Rooting the Animal Tree of Life
Li, Y., Shen, X.-X., Evans, B., Dunn, C. W., & Rokas, A. (2021) · Molecular Biology and Evolution · doi:10.1093/molbev/msab170 · Cited by 146
Self-citationTreSpEx-detection of misleading signal in phylogenetic reconstructions based on tree information
Struck, T. H. (2014) · Evolutionary Bioinformatics · doi:10.4137/ebo.s14239 · Cited by 128
Cited by
Genomic factors shape carbon and nitrogen metabolic niche breadth across Saccharomycotina yeasts
Opulente, D. A., LaBella, A. L., Harrison, M.-C., Wolters, J. F., Liu, C., Li, Y., Kominek, J., Steenwyk, J. L., Stoneman, H. R., VanDenAvond, J., et al. (2024) · Science · doi:10.1126/science.adj4503 · Cited by 121
Self-citationGenomic and phenotypic evolution of nematode-infecting microsporidia
Wadi, L., El Jarkass, H. T., Tran, T. D., Islah, N., Luallen, R. J., & Reinke, A. W. (2023) · PLOS Pathogens · doi:10.1371/journal.ppat.1011510 · Cited by 32
Kress, A., Poch, O., Lecompte, O., & Thompson, J. D. (2023) · Frontiers in Bioinformatics · doi:10.3389/fbinf.2023.1178926 · Cited by 21
15 years of introgression studies: quantifying gene flow across Eukaryotes
Dagilis, A. J., Peede, D., Coughlan, J. M., Jofre, G. I., D’Agostino, E. R. R., Mavengere, H., Tate, A. D., & Matute, D. R. (2021) · doi:10.1101/2021.06.15.448399 · Cited by 14
Gonçalves, C., Steenwyk, J. L., Rinker, D. C., Opulente, D. A., LaBella, A. L., Harrison, M.-C., Wolters, J. F., Zhou, X., Shen, X.-X., Covo, S., et al. (2025) · Molecular Biology and Evolution · doi:10.1093/molbev/msaf285 · Cited by 4
Self-citation
Metadata
- Authors
- Li, Y., Steenwyk, J. L., Chang, Y., Wang, Y., James, T. Y., Stajich, J. E., Spatafora, J. W., Groenewald, M., Dunn, C. W., Hittinger, C. T., Shen, X.-X., & Rokas, A.
- Venue
- Current Biology
- Publisher
- Elsevier BV
- Published
- 2021-04
- Volume
- 31
- Issue
- 8
- Pages
- 1653-1665.e5
- ISSN
- 0960-9822 (ISSN-L)
- OpenAlex
- W3130851577
- Cited by
- 365
- References
- 11
- FWCI
- 17.44
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
