Drivers and dynamics of a massive adaptive radiation in cichlid fishes

Subjects

Abstract

Adaptive radiation is the likely source of much of the ecological and morphological diversity of life1,2,3,4. How adaptive radiations proceed and what determines their extent remains unclear in most cases1,4. Here we report the in-depth examination of the spectacular adaptive radiation of cichlid fishes in Lake Tanganyika. On the basis of whole-genome phylogenetic analyses, multivariate morphological measurements of three ecologically relevant trait complexes (body shape, upper oral jaw morphology and lower pharyngeal jaw shape), scoring of pigmentation patterns and approximations of the ecology of nearly all of the approximately 240 cichlid species endemic to Lake Tanganyika, we show that the radiation occurred within the confines of the lake and that morphological diversification proceeded in consecutive trait-specific pulses of rapid morphospace expansion. We provide empirical support for two theoretical predictions of how adaptive radiations proceed, the ‘early-burst’ scenario1,5 (for body shape) and the stages model1,6,7 (for all traits investigated). Through the analysis of two genomes per species and by taking advantage of the uneven distribution of species in subclades of the radiation, we further show that species richness scales positively with per-individual heterozygosity, but is not correlated with transposable element content, number of gene duplications or genome-wide levels of selection in coding sequences.

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Fig. 1: Time-calibrated species tree of the cichlid fishes of African Lake Tanganyika.
Fig. 2: Morphospace and ecospace occupation of the cichlid fishes of Lake Tanganyika.
Fig. 3: Temporal dynamics of morphological diversification in the adaptive radiation of cichlid fishes in Lake Tanganyika.
Fig. 4: Association between genomic features and species richness across the cichlid tribes in Lake Tanganyika.

Data availability

All newly sequenced genomes for this study and their raw reads are available from NCBI under the BioProject accession number PRJNA550295 (https://www.ncbi.nlm.nih.gov/bioproject/). The VCF file, tree files, summary statistics of the assembled genomes and phenotypic datasets generated and analysed during this study are available as downloadable files on Dryad (https://doi.org/10.5061/dryad.9w0vt4bbf). The Nile tilapia reference genome used is available under RefSeq accession GCF_001858045.1. All X-ray data are available on MorphoSource under the project number P1093. Source data are provided with this paper.

Code availability

Code used to analyse the data is available on GitHub (https://github.com/cichlidx/ronco_et_al), except for analyses where single commands from publicly available software were used and where all settings are fully reported in the Methods and/or Supplementary Methods.

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Acknowledgements

We thank the University of Burundi, the Ministère de l'Eau, de l'Environnement, de l'Amenagement du Territoire et de l'Urbanisme, Republic of Burundi, the Centre de Recherche en Hydrobiologie (CRH), Uvira, DR Congo, the Tanzania Commission for Science and Technology (COSTECH), the Tanzania Fisheries Research Institute (TAFIRI), the Tanzania National Parks Authority (TANAPA), the Tanzania Wildlife Research Institute (TAWIRI), the Lake Tanganyika Research Unit, Department of Fisheries, Republic of Zambia, and the Zambian Department for Immigration for research permits; G. Banyankimbona, H. Mwima, G. Hakizimana, N. Muderhwa, P. Masilya, I. Kimirei, M. Mukuli Wa-Teba, G. Moshi, A. Mwakatobe, C. Katongo, T. Banda and L. Makasa for assistance with obtaining research permits; the boat crews of the Chomba (D. Mwanakulya, J. Sichilima, H. D. Sichilima Jr and G. Katai) and the Maji Makubwa II (G. Kazumbe and family) for navigation, guidance and company; the boat drivers M. Katumba and T. Musisha; the car drivers A. Irakoze and J. Leonard; M. Schreyen-Brichard, M. Mukuli Wa-Teba, G. Kazumbe, I. Kimirei, D. Schlatter, R. Schlatter, M. K. Dominico, H. Sichilima Sr, C. Zytkow, P. Lassen and V. Huwiler for logistic support; G. Banyankimbona, N. Boileau, B. Egger, Y. Fermon, G. Kazumbe, G. Katai, R. Lusoma, K. Smailus, L. Widmer and numerous fishermen at Lake Tanganyika for help during sampling; V. Huwiler, Charity, O. Mangwangwa and the Zytkow family for lodging; people of innumerable villages on the shores of Lake Tanganyika for providing workspace, shelter for night-camps and access to village infrastructure; M. Barluenga, H. Gante, Z. Musilová, F. Schedel, J. Snoeks, M. Stiassny, H. Tanaka, G. Turner and M. Van Steenberge for providing additional samples and/or specimens; M. Sánchez, A. Schweizer and A. Wegmann for assistance with the μCT scanning of large specimens; C. Moes for help with radiographs; V. Evrard for help with stable isotopes; I. Nissen and E. Burcklen for assistance with DNA shearing; M. Conte and T. D. Kocher for sharing the RepeatMasker annotations for Nile tilapia; C. Klingenberg and M. Sánchez for discussions on the morphometric approach; A. Tooming-Klunderud and team at the Norwegian Sequencing Centre and C. Beisel and team at the Genomics Facility Basel at the ETH Zurich Department of Biosystems Science and Engineering (D-BSSE), Basel, for assistance with next-generation sequencing; M. Jacquot, E. Pujades and T. Sengstag for the setup and assistance with the collection database system (LabKey); and J. Johnson and A. Viertler for fish illustrations in Fig. 1 and Extended Data Fig. 5, respectively. Calculations were performed at sciCORE (http://scicore.unibas.ch/) scientific computing centre at University of Basel (with support by the SIB/Swiss Institute of Bioinformatics) and the Abel computer cluster, University of Oslo. This work was funded by the European Research Council (ERC, Consolidator Grant Nr. 617585 ‘CICHLID~X’ jointly hosted by the University of Basel and the University of Oslo) and the Swiss National Science Foundation (SNSF, grants 156405 and 176039) to W.S. A. Böhne was supported by the SNSF (Ambizione grant 161462).

Author information

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Authors

Contributions

F.R., A.I. and W.S. designed this study (with input from H.H.B., A.K. and S.J.). F.R., A.I., H.H.B. and W.S. collected the specimens in the field. F.R. and A. Böhne extracted DNA and prepared the libraries for sequencing. S.J. coordinated sequencing. M. Matschiner performed the mapping, variant calling, phylogenetic analyses and coalescent simulations. M. Malinsky contributed to the variant calling pipelines and performed the f4-ratio statistics. A. Böhne assembled the genomes and quantified gene duplications, A.E.T. conducted the dN/dS analyses and V.R. analysed transposable elements. A. Boila assessed stable-isotope compositions, H.H.B. radiographed the specimens and W.S. scored pigmentation patterns. F.R. curated the samples and performed μCT scanning, geometric morphometric analyses, and all analyses incorporating morphological and ecological data as well as correlations with species richness. F.R. and W.S. wrote the manuscript with contributions and/or feedback from all authors. All authors read and approved the final version of the manuscript.

Corresponding authors

Correspondence to Fabrizia Ronco or Walter Salzburger.

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The authors declare no competing interests.

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Extended data figures and tables

Extended Data Fig. 1 Age of the adaptive radiation of cichlid fishes in African Lake Tanganyika.

Time-calibrated species tree of species representing divergent tribes and subfamilies within cichlids as well as closely-related non-cichlid outgroups, generated with the multi-species coalescent model in StarBEAST2. Nodes marked with a black dot were constrained according to species-tree analyses with ASTRAL. Node bars indicate 95% highest-posterior density age intervals. Outgroup divergence times are not drawn to scale. Insets visualize the prior distribution applied for the age of African cichlids according to Matschiner et al.18, as well as posterior age estimates for Oreochromini and the cichlid adaptive radiation in Lake Tanganyika (LT).

Extended Data Fig. 2 Time-calibrated species tree of the cichlid adaptive radiation in Lake Tanganyika.

The species tree is based on the maximum-likelihood topology estimated with RAxML (Fig. 1) and was time-calibrated using a relaxed-clock model in BEAST2, applied to a selected set of alignments.

Extended Data Fig. 3 Alternative time-calibrated species tree of the cichlid adaptive radiation in Lake Tanganyika.

The species tree is based on the topology estimated with ASTRAL and was time-calibrated using a relaxed-clock model in BEAST2, applied to a selected set of alignments.

Extended Data Fig. 4 Alternative time-calibrated species tree of the cichlid adaptive radiation in Lake Tanganyika.

The species tree is based on the topology estimated with SNAPP and was time-calibrated using a relaxed-clock model in BEAST2, applied to a selected set of alignments.

Extended Data Fig. 5 Phenotyping of the specimens.

a, Two-dimensional landmarks placed on X-ray images of the specimens. To quantify overall body shape we excluded landmark 16 (to minimise the effect of the orientation of the oral jaw). To analyse upper oral jaw morphology we used landmarks 1, 2, 16 and 21. b, Three-dimensional landmarks used to analyse lower pharyngeal jaw shape on μCT scans of the heads. True landmarks are indicated in red, sliding semi-landmarks are indicated in blue. c, Body regions scored for presence/absence of pigmentation patterns.

Extended Data Fig. 6 Ecospace and morphospace occupation of the cichlid adaptive radiation in Lake Tanganyika.

Scatter plots for each focal tribe (indicated with colours, see Fig. 1 for colour key) against the total eco-and morphospace (grey). Species ranges are indicated with convex hulls. a, Stable N and C isotope compositions (δ15N and δ13C values). The additional plot shows δ15N and δ13C values of a baseline dataset which confirms the interpretability of the stable N and C isotope composition in Lake Tanganyika (see Supplementary Methods and Discussion). b, PC1 and PC2 of body shape (for shape changes associated with the PC axes see Fig. 2). The last plot for each trait shows the size of the traitspace per tribe in relation to species numbers (stable isotopes: Pearson’s r = 0.88, d.f. = 9, P = 0.0004; body shape: Pearson’s r = 0.91, d.f. = 9, P = 0.0001). Traitspace size was calculated as the square root of the convex hull area spanned by species means.

Extended Data Fig. 7 Morphospace occupation of the cichlid adaptive radiation in Lake Tanganyika.

a, b, Scatter plots of PC1 and PC2 for upper oral jaw morphology (a) and lower pharyngeal jaw shape per tribe (b) (indicated with colours, see Fig. 1 for colour key) against the total morphospace (grey). Species ranges are indicated with convex hulls. For shape changes associated with the respective PC-axis see Fig. 2. The last plot for each trait shows the size of the morphospace per tribe in relation to species numbers (upper oral jaw morphology: Pearson’s r = 0.88, d.f. = 9, P = 0.0003; lower pharyngeal jaw shape: Pearson’s r = 0.83, d.f. = 9, P = 0.0017). Morphospace size was calculated as the square root of the convex hull area spanned by species means.

Extended Data Fig. 8 PLS fit for each multivariate trait against the stable N and C isotope compositions (δ15N and δ13C values) and models of trait evolution.

ac, PLS fits for body shape (a), upper oral jaw morphology (b) and lower pharyngeal jaw shape (c). Associated shape changes and loadings of the respective stable isotope projection are indicated next to the axes. Data points represent species means and are coloured according to tribe. d, Comparison of model fits for different models of trait evolution and phylogenetic signal for each trait complex using three time-calibrated species trees with alternative topologies. e, Overview of the model fits and phylogenetic signal inferred using 100 trees sampled from the posterior distributions of the time calibrations for each of the three alternative tree topologies.

Extended Data Fig. 9 Genome-wide statistical analyses.

a, Proportion of the different classes of transposable elements (TE) among all TE for each tribe (one genome per species, n = 245). b, Species means of dN (left) and dS (right) values over alignment length for each tribe (n = 243 taxa, 471 genomes). The boxes’ centre lines show median, box limits show first and third quartiles, and whiskers show the 1.5 × interquartile ranges. c, f4-ratio statistics among species within each tribe in simulated data (tribe means are based on the mean across 20 simulations of each species triplet). Data points are coloured according to tribes; large points are tribe means shown with 95% confidence intervals, small points represent species means and are only shown for group sizes <40 species. To test for a correlation with species richness per tribe (log-transformed), we calculated phylogenetic independent contrasts for each variable and inferred Pearson’s r through the origin.

Extended Data Fig. 10 Signals of introgression among Lake Tanganyika cichlid species.

Upper matrix: maximum values of the f4-ratio statistics between all pairs of species, derived from calculations across all combinations of species trios with T. sparrmanii fixed as the outgroup. The f4-ratio estimates the proportion of the genome affected by gene flow, all presented values are statistically significant (one-sided block-jackknife tests: P < 5 × 10−5 after Benjamini–Hochberg correction for multiple testing). Lower matrix: Dtree-statistics (hue) with corresponding P-value (two-tailed binomial test, not adjusted for multiple testing; log-transformed; saturation) based on a phylogenetic approach testing for asymmetry in the relationships of species trios in 1,272 local maximum-likelihood trees (see Supplementary Methods). The two different approaches uncovered little gene flow among the tribes (see Supplementary Discussion).

Supplementary information

Supplementary Information

This file contains Supplementary Methods with a detailed description of methods used to collect and analyse the data presented in the manuscript, and a Supplementary Discussion, and Supplementary Figures 1 and 2.

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Supplementary Tables

This file contains Supplementary Tables 1 and 2 with sample size information per species for each data set, read depth of the genomes, and information on each of the specimens used in the study, including taxonomic information and sampling locations. The title and caption of each Supplementary Table can be found in the Supplementary Information file.

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Ronco, F., Matschiner, M., Böhne, A. et al. Drivers and dynamics of a massive adaptive radiation in cichlid fishes. Nature (2020). https://doi.org/10.1038/s41586-020-2930-4

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