The inference of evolutionary relationships in the species-rich family Orchidaceae has hitherto relied heavily on plastid DNA sequences and limited taxon sampling. Previous studies have provided a robust plastid phylogenetic framework, which was used to classify orchids and investigate the drivers of orchid diversification. However, the extent to which phylogenetic inference based on the plastid genome is congruent with the nuclear genome has been only poorly assessed. METHODS:We inferred higher-level phylogenetic relationships of orchids based on likelihood and ASTRAL analyses of 294 low-copy nuclear genes sequenced using the Angiosperms353 universal probe set for 75 species (representing 69 genera, 16 tribes, 24 subtribes) and a concatenated analysis of 78 plastid genes for 264 species (117 genera, 18 tribes, 28 subtribes). We compared phylogenetic informativeness and support for the nuclear and plastid phylogenetic hypotheses.RESULTS: Phylogenetic inference using nuclear data sets provides well-supported orchid relationships that are highly congruent between analyses. Comparisons of nuclear gene trees and a plastid supermatrix tree showed that the trees are mostly congruent, but revealed instances of strongly supported phylogenetic incongruence in both shallow and deep time. The phylogenetic informativeness of individual Angiosperms353 genes is in general better than that of most plastid genes. CONCLUSIONS:Our study provides the first robust nuclear phylogenomic framework for Orchidaceae and an assessment of intragenomic nuclear discordance, plastid-nuclear tree incongruence, and phylogenetic informativeness across the family. Our results also demonstrate what has long been known but rarely thoroughly documented: nuclear and plastid phylogenetic trees can contain strongly supported discordances, and this incongruence must be reconciled prior to interpretation in evolutionary studies, such as taxonomy, biogeography, and character evolution.

High-throughput DNA sequencing techniques enable time-and cost-effective sequencing of large portions of the genome. Instead of sequencing and annotating whole genomes, many phylogenetic studies focus sequencing effort on large sets of pre-selected loci, which further reduces costs and bioinformatic challenges while increasing coverage. One common approach that enriches loci before sequencing is often referred to as target sequence capture. This technique has been shown to be applicable to phylogenetic studies of greatly varying evolutionary depth. Moreover, it has proven to produce powerful, large multi-locus DNA sequence datasets suitable for phylogenetic analyses. However, target capture requires careful considerations, which may greatly affect the success of experiments. Here we provide a simple flowchart for designing phylogenomic target capture experiments. We discuss necessary decisions from the identification of target loci to the final bioinformatic processing of sequence data. We outline challenges and solutions related to the taxonomic scope, sample quality, and available genomic resources of target capture projects. We hope this review will serve as a useful roadmap for designing and carrying out successful phylogenetic target capture studies.

High-throughput DNA sequencing techniques enable time- and cost-effective sequencing of large portions of the genome. Instead of sequencing and annotating whole genomes, many phylogenetic studies focus sequencing efforts on large sets of pre-selected loci, which further reduces costs and bioinformatic challenges while increasing sequencing depth. One common approach that enriches loci before sequencing is often referred to as target sequence capture. This technique has been shown to be applicable to phylogenetic studies of greatly varying evolutionary depth and has proven to produce powerful, large multi-locus DNA sequence datasets of selected loci, suitable for phylogenetic analyses. However, target capture requires careful theoretical and practical considerations, which will greatly affect the success of the experiment. Here we provide an easy-to-follow flowchart for adequately designing phylogenomic target capture experiments, and we discuss necessary considerations and decisions from the first steps in the lab to the final bioinformatic processing of the sequence data. We particularly discuss issues and challenges related to the taxonomic scope, sample quality, and available genomic resources of target capture projects and how these issues affect all steps from bait design to the bioinformatic processing of the data. Altogether this review outlines a roadmap for future target capture experiments and is intended to assist researchers with making informed decisions for designing and carrying out successful phylogenetic target capture studies

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Madagascar’s unique biota is heavily affected by human activity and is under intense threat. Here, we review the current state of knowledge on the conservation status of Madagascar’s terrestrial and freshwater biodiversity by presenting data and analyses on documented and predicted species-level conservation statuses, the most prevalent and relevant threats, ex situ collections and programs, and the coverage and comprehensiveness of protected areas. The existing terrestrial protected area network in Madagascar covers 10.4% of its land area and includes at least part of the range of the majority of described native species of vertebrates with known distributions (97.1% of freshwater fishes, amphibians, reptiles, birds, and mammals combined) and plants (67.7%). The overall figures are higher for threatened species (97.7% of threatened vertebrates and 79.6% of threatened plants occurring within at least one protected area). International Union for Conservation of Nature (IUCN) Red List assessments and Bayesian neural network analyses for plants identify overexploitation of biological resources and unsustainable agriculture as the most prominent threats to biodiversity. We highlight five opportunities for action at multiple levels to ensure that conservation and ecological restoration objectives, programs, and activities take account of complex underlying and interacting factors and produce tangible benefits for the biodiversity and people of Madagascar.

Madagascar’s biota is hyperdiverse and includes exceptional levels of endemicity. We review the current state of knowledge on Madagascar’s past and current terrestrial and freshwater biodiversity by compiling and presenting comprehensive data on species diversity, endemism, and rates of species description and human uses, in addition to presenting an updated and simplified map of vegetation types. We report a substantial increase of records and species new to science in recent years; however, the diversity and evolution of many groups remain practically unknown (e.g., fungi and most invertebrates). Digitization efforts are increasing the resolution of species richness patterns and we highlight the crucial role of field- and collections-based research for advancing biodiversity knowledge and identifying gaps in our understanding, particularly as species richness corresponds closely to collection effort. Phylogenetic diversity patterns mirror that of species richness and endemism in most of the analyzed groups. We highlight humid forests as centers of diversity and endemism because of their role as refugia and centers of recent and rapid radiations. However, the distinct endemism of other areas, such as the grassland-woodland mosaic of the Central Highlands and the spiny forest of the southwest, is also biologically important despite lower species richness. The documented uses of Malagasy biodiversity are manifold, with much potential for the uncovering of new useful traits for food, medicine, and climate mitigation. The data presented here showcase Madagascar as a unique “living laboratory” for our understanding of evolution and the complex interactions between people and nature. The gathering and analysis of biodiversity data must continue and accelerate if we are to fully understand and safeguard this unique subset of Earth’s biodiversity.

AimDifferent fruit colours are associated with dispersal by different frugivores, largely based on colour vision type. Frugivore mobility affects overall range size for the plant being dispersed. Here we determine the interaction between different fruit colours, range sizes, and diversification rates by testing two hypotheses: That (1) fruit colours attractive to birds have larger range sizes due to their higher dispersal ability, and that (2) different frugivore disperser groups, bird or mammal, leads to different diversification rate at different range size, where intermediate range size leads to the highest diversification rate.LocationGlobal.Time periodContemporary (or present)Major taxa studiedPalms (Arecaceae)MethodsUsing model selection, we identified three groups of colours with similar diversification rate and likely disperser. Range sizes were estimated and categorized species as small, intermediate, or large-ranged. For model selection and to determine the relationship beween fruit color, range size and diversification rate we used Multi-State Speciation and Extinction (MuSSE) models.ResultsSpecies with intermediate range size had the highest net diversification for all three fruit colour groups. Bird-dispersed palms more likely diversified at small than at large range size while mammal-dispersed palms more likely diversified at larger range size than small. Fruit colours associated with mammal dispersal had more large-ranged species than colours associated with bird dispersal.Main conclusionsThe associated between intermediate range size and higher diversification rate indicates that spatial factors that affect diversification at small and large range sizes result in higher diversification at intermediate ranges. We find striking differences in diversification rate within each range size category between fruit color groups. This suggests that the relationship between diversification rate and range size depends on the specific frugivorous dispersers and their dispersal patterns. This study reveals how fruit traits alter dispersal patterns and how that, in turn, influences diversification.

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