Methods

Our Approach

Target sequence capture uses RNA probes to enrich sequencing libraries for targeted orthologous genes (Dodsworth et al. 2019; Faircloth et al., 2012; Lemmon et al., 2012). In effect, the RNA probes “fish out” a specific set of genes of interest. Angiosperms353 (Johnson et al., 2019) is a universal probe set that targets 353 single-copy loci, derived from a broader set of orthologous loci identified by the One Thousand Plants (OneKP) project (Leebens-Mack et al., 2019). The Angiosperms353 probe set recovers a median of 161 kbp of coding region per sample across the diversity of angiosperms (Baker et al., 2022). The probe set works efficiently from poor quality DNA, including DNA extracted from herbarium material (Brewer et al., 2019). The Angiosperms353 probe set and loci have been extensively explored in special issues of American Journal of Botany, Applications in Plant Sciences and other scientific papers.

The full workflow for the generation of data and computation of trees is described in detail by Baker et al. (2022), with updates documented in release notes available via our secure FTP (SFTP) site. A summary of these methods [and updates] is given below.

Sampling

Our goal is to sample at least one species of each of the ca. 13,700 genera of flowering plants. To guide the selection of samples, we follow the global list of plant names in the World Checklist of Vascular Plants (Govaerts et al., 2021) available via the Plants of the World Online.

DNA was obtained from a wide variety of sources, including PAFTOL’s network of collaborators and partners. In most cases, samples were sourced from the collections of the Royal Botanic Gardens, Kew (Herbarium, DNA Bank, Tissue Bank, Living Collections and Millennium Seed Bank). To be included, the sample must be 1) legally available for use in phylogenomic studies, 2) verified by a relevant expert, and 3) ideally collected in the wild. The identifications of samples were substantiated by voucher specimens deposited in herbaria, as far as was practically achievable. All voucher specimen information, including links to specimen images where available, is provided in the Kew Tree of Life Explorer.

DNA Extraction

DNA was extracted from 20 mg of silica dried material (Chase & Hills, 1991) or 40 mg herbarium material using a modified CTAB extraction method (Doyle & Doyle, 1987), followed by magnetic bead clean-up.

Target Sequence Capture

Libraries were prepared using a standard library preparation kit. Depending on DNA quality, total DNA was sonicated before library preparation, aiming for fragment sizes between 350 and 450 bp. After pooling, libraries were hybridised with the Angiosperms353 probe kit following the manufacturer’s protocol. DNA sequencing was performed using Illumina MiSeq, HiSeq and NovaSeq platforms.

Additional Data Sources

In addition to data generated by target sequence capture, we retrieved the Angiosperms353 loci from publicly available genomic data and from genomic data shared with us by our collaborators (see Data Sources page). These datasets included annotated and unannotated genomes, assembled transcriptomes, and raw sequencing reads.

Gene Recovery

Up to 353 genes were recovered from each sample by searching for sequences matching the Angiosperms353 genes (Johnson et al., 2019). For raw reads (e.g. target sequence capture data, other raw read data), HybPiper2 (Johnson et al., 2016) was used to assemble Illumina reads and identify gene orthologues corresponding to the Angiosperms353 target gene set. For assembled sequences (e.g. annotated and unannotated genomes, assembled transcriptomes), Captus (Ortiz et al., 2023) was used for gene recovery. Family identification for each sample was validated using DNA barcode and phylogenetics tests as described by Baker et al. (2022).

Tree of Life Reconstruction

Following the approach of Zuntini, Carruthers et al. (2024), we first produced 'backbone' gene alignments and trees from a small subset of the best quality samples available, distributed across all angiosperm families, two samples per family or proportionally more for larger families. Next, sequences from each of the remaining samples in the dataset were aligned with EMMA (Shen et al., 2023), using the "backbone" gene alignments and trees as guides for the overall alignments. Each gene tree was built with a divide-and-conquer approach using FastTree (Price et al., 2010) to create an initial guide tree, IQ-TREE 2 (Minh et al., 2020) to build subset trees and Guide Tree Merger (Smirnov & Warnow, 2020) to combine the subset trees into a final gene tree. The navigable tree of life presented here was estimated with weighted ASTRAL (Zhang & Mirarab, 2022; Zhang et al., 2025) from all the gene trees and rooted with a set of gymnosperm species. The tree is annotated with local posterior probabilities as indicators of branch support.

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