Other Open Access

WEBINAR: Conflict in multi-gene datasets: why it happens and what to do about it - deep coalescence, paralogy and reticulation

Schmidt-Lebuhn, Alexander

This record includes training materials associated with the Australian BioCommons webinar ‘Conflict in multi-gene datasets: why it happens and what to do about it - deep coalescence, paralogy and reticulation’. This webinar took place on 20 May 2021.

Multi-gene datasets used in phylogenetic analyses, such as those produced by the sequence capture or target enrichment used in the Genomics for Australian Plants: Australian Angiosperm Tree of Life project, often show discordance between individual gene trees and between gene and species trees. This webinar explores three different forms of discordance: deep coalescence, paralogy, and reticulation. In each case, it considers underlying biological processes, how discordance presents in the data, and what bioinformatic or phylogenetic approaches and tools are available to address these challenges. It covers Yang and Smith paralogy resolution and general information on options for phylogenetic analysis.

This webinar is part of a series of webinars and workshops developed by the Genomics for Australian Plants (GAP) Initiative that focused on the analysis of target capture sequence data. In addition to two public webinars, the GAP bioinformatics working group is offering training workshops in the use of newly developed and existing scripts in an integrated workflow to participants in the 2021 virtual Australasian Systematic Botany Society Conference.

The materials are shared under a Creative Commons 4.0 International agreement unless otherwise specified and were current at the time of the event.

Files and materials included in this record:

  • Event metadata (PDF): Information about the event including, description, event URL, learning objectives, prerequisites, technical requirements etc.

  • Index of training materials (PDF): List and description of all materials associated with this event including the name, format, location and a brief description of each file.

  • Schmidt-Lebuhn - paralogy lineage sorting reticulation - slides (PDF): Slides presented during the webinar


Materials shared elsewhere:

A recording of the webinar is available on the Australian BioCommons YouTube Channel: https://youtu.be/1bw81q898z8

Files (9.2 MB)
Name Size
Event metadata.pdf
105.4 kB Download
Index of training materials.pdf
90.9 kB Download
Schmidt-Lebuhn - paralogy lineage sorting reticulation-slides.pdf
9.0 MB Download
  • Altenhoff AM, Dessimoz C, 2012. Inferring Orthology and Paralogy, pp. 259-279 in: Maria Anisimova (ed.), Evolutionary Genomics: Statistical and Computational Methods, Volume 1,Methods in Molecular Biology, vol. 855, Springer. https://people.inf.ethz.ch/adriaal/orthology-bookchapter.pdf

  • Barker MS, Arrigo N, Baniaga AE, Li Z, Levin DA, 2016. On the relative abundance of autopolyploids and allopolyploids. New Phytologist 210: 391–398. https://doi.org/10.1111/nph.13698

  • Folk RA, Soltis PS, Soltis DE, Guralnick R, 2018. New prospects in the detection and comparative analysis of hybridization in the tree of life. Amer. J. Bot. 105: 364-375. https://doi.org/10.1002/ajb2.1018

  • Maddison WP, 1997. Gene trees in species trees. Syst. Biol. 46: 523-536. https://doi.org/10.1093/sysbio/46.3.523

  • Nakhleh L, 2013. Computational approaches to species phylogeny inference and gene tree reconciliation. Trends in Ecology & Evolution 28: 719-728. https://doi.org/10.1016/j.tree.2013.09.004

  • Payseur, B. A., and L. H. Rieseberg. 2016. A genomic perspective on hybridization and speciation. Molecular Ecology 25: 2337–2360. https://doi.org/10.1111/mec.13557

  • Peer YV de, Mizrachi E, Marchal K. 2017. The evolutionary significance of polyploidy. Nature Reviews Genetics 18: 411–424. http://dx.doi.org/10.1038/nrg.2017.26

  • Smith ML, Hahn MW, 2020. New approaches for inferring phylogenies in the presence of paralogs. Trends in Genetics 1721. https://doi.org/10.1016/j.tig.2020.08.012

  • Stegemann S, Keuthe M, Greiner S, Bock R, 2012. Horizontal transfer of chloroplast genomes between plant species. Proc. Natl. Acad. Sci. 109: 2434–2438. https://doi.org/10.1073/pnas.1114076109

  • Flouri T, Jiao X, Rannala B, Yang Z, 2020. A Bayesian implementation of the multispecies coalescent model with introgression for phylogenomic analysis. Mol. Biol. Evol. 37: 1211-1223. https://doi.org/10.1093/molbev/msz296

  • Heled J, Drummond AJ, 2010. Bayesian inference of species trees from multilocus data. Mol. Biol. Evol. 27: 570-580. https://doi.org/10.1093/molbev/msp274

  • Johnson MG, et al., 2019. A universal probe set for targeted sequencing of 353 nuclear genes from any flowering plant designed using k-medoids clustering. Syst. Biol. 68: 594-606. https://doi.org/10.1093/sysbio/syy086

  • Joly S, McLenachan PA, Lockhart PJ, 2009. A statistical approach for distinguishing hybridization and incomplete lineage sorting. Amer. Nat. 174: E54-E70. https://doi.org/10.1086/600082

  • Morel B, Schade P, Lutteropp S, Williams TA, Sz llősi GJ, Stamatakis A, 2021. SpeciesRax: A tool for maximum likelihood species tree inference from gene family trees under duplication, transfer, and loss. https://doi.org/10.1101/2021.03.29.437460

  • Nauheimer L, Weigner N, Joyce E, Crayn D, Clarke C, Nargar K, 2020. HybPhaser: a workflow for the detection and phasing of hybrids in target capture datasets. BioRxiv. https://doi.org/10.1101/2020.10.27.354589

  • Sol s-Lemus C, An  C, 2016. Inferring phylogenetic networks with maximum pseudolikelihood under incomplete lineage sorting. PLoS Genetics 12: e1005896. https://doi.org/10.1371/journal.pgen.1005896

  • Yang Y, Smith SA, 2014. Orthology inference in nonmodel organisms using transcriptomes and low-coverage genomes: improving accuracy and matrix occupancy for phylogenomics. Mol. Biol. Evol. 31: 3081–3092. https://doi.org/10.1093/molbev/msu245

  • Zhang C, Rabiee M, Sayyari E, Mirarab S, 2018. ASTRAL-III: polynomial time species tree reconstruction from partially resolved gene trees. BMC Bioinformatics 19: 153. https://doi.org/10.1186/s12859-018-2129-y

All versions This version
Views 189189
Downloads 4242
Data volume 66.6 MB66.6 MB
Unique views 184184
Unique downloads 2727


Cite as