Paul B. Frandsen

PartitionFinder 2: New Methods for Selecting Partitioned Models of Evolution for Molecular and Morphological Phylogenetic Analyses

PartitionFinder 2 is a program for automatically selecting best-fit partitioning schemes and models of evolution for phylogenetic analyses. PartitionFinder 2 is substantially faster and more efficient than version 1, and incorporates many new methods and features. These include the ability to analyze morphological datasets, new methods to analyze genome-scale datasets, new output formats to facilitate interoperability with downstream software, and many new models of molecular evolution. PartitionFinder 2 is freely available under an open source license and works on Windows, OSX, and Linux operating systems. It can be downloaded from www.robertlanfear.com/partitionfinder. The source code is available at https://github.com/brettc/partitionfinder.

Automatic selection of partitioning schemes for phylogenetic analyses using iterative k-means clustering of site rates

BackgroundModel selection is a vital part of most phylogenetic analyses, and accounting for the heterogeneity in evolutionary patterns across sites is particularly important. Mixture models and partitioning are commonly used to account for this variation, and partitioning is the most popular approach. Most current partitioning methods require some a priori partitioning scheme to be defined, typically guided by known structural features of the sequences, such as gene boundaries or codon positions. Recent evidence suggests that these a priori boundaries often fail to adequately account for variation in rates and patterns of evolution among sites. Furthermore, new phylogenomic datasets such as those assembled from ultra-conserved elements lack obvious structural features on which to define a priori partitioning schemes. The upshot is that, for many phylogenetic datasets, partitioned models of molecular evolution may be inadequate, thus limiting the accuracy of downstream phylogenetic analyses.ResultsWe present a new algorithm that automatically selects a partitioning scheme via the iterative division of the alignment into subsets of similar sites based on their rates of evolution. We compare this method to existing approaches using a wide range of empirical datasets, and show that it consistently leads to large increases in the fit of partitioned models of molecular evolution when measured using AICc and BIC scores. In doing so, we demonstrate that some related approaches to solving this problem may have been associated with a small but important bias.ConclusionsOur method provides an alternative to traditional approaches to partitioning, such as dividing alignments by gene and codon position. Because our method is data-driven, it can be used to estimate partitioned models for all types of alignments, including those that are not amenable to traditional approaches to partitioning.

The Trichoptera barcode initiative: a strategy for generating a species-level Tree of Life.

DNA barcoding was intended as a means to provide species-level identifications through associating DNA sequences from unknown specimens to those from curated reference specimens. Although barcodes were not designed for phylogenetics, they can be beneficial to the completion of the Tree of Life. The barcode database for Trichoptera is relatively comprehensive, with data from every family, approximately two-thirds of the genera, and one-third of the described species. Most Trichoptera, as with most of lifes species, have never been subjected to any formal phylogenetic analysis. Here, we present a phylogeny with over 16 000 unique haplotypes as a working hypothesis that can be updated as our estimates improve. We suggest a strategy of implementing constrained tree searches, which allow larger datasets to dictate the backbone phylogeny, while the barcode data fill out the tips of the tree. We also discuss how this phylogeny could be used to focus taxonomic attention on ambiguous species boundaries and hidden biodiversity. We suggest that systematists continue to differentiate between ‘Barcode Index Numbers’ (BINs) and ‘species’ that have been formally described. Each has utility, but they are not synonyms. We highlight examples of integrative taxonomy, using both barcodes and morphology for species description. This article is part of the themed issue ‘From DNA barcodes to biomes’.

Response to Comment on “Phylogenomics resolves the timing and pattern of insect evolution”

Tong et al. comment on the accuracy of the dating analysis presented in our work on the phylogeny of insects and provide a reanalysis of our data. They replace log-normal priors with uniform priors and add a “roachoid” fossil as a calibration point. Although the reanalysis provides an interesting alternative viewpoint, we maintain that our choices were appropriate.

Applications of deep convolutional neural networks to digitized natural history collections

Abstract Natural history collections contain data that are critical for many scientific endeavors. Recent efforts in mass digitization are generating large datasets from these collections that can provide unprecedented insight. Here, we present examples of how deep convolutional neural networks can be applied in analyses of imaged herbarium specimens. We first demonstrate that a convolutional neural network can detect mercury-stained specimens across a collection with 90% accuracy. We then show that such a network can correctly distinguish two morphologically similar plant families 96% of the time. Discarding the most challenging specimen images increases accuracy to 94% and 99%, respectively. These results highlight the importance of mass digitization and deep learning approaches and reveal how they can together deliver powerful new investigative tools.

Genomic and transcriptomic resources for assassin flies including the complete genome sequence of Proctacanthus coquilletti (Insecta: Diptera: Asilidae) and 16 representative transcriptomes

A high-quality draft genome for Proctacanthus coquilletti (Insecta: Diptera: Asilidae) is presented along with transcriptomes for 16 Diptera species from five families: Asilidae, Apioceridae, Bombyliidae, Mydidae, and Tabanidae. Genome sequencing reveals that P. coquilletti has a genome size of approximately 210 Mbp and remarkably low heterozygosity (0.47%) and few repeats (15%). These characteristics helped produce a highly contiguous (N50 = 862 kbp) assembly, particularly given that only a single 2 × 250 bp PCR-free Illumina library was sequenced. A phylogenomic hypothesis is presented based on thousands of putative orthologs across the 16 transcriptomes. Phylogenetic relationships support the sister group relationship of Apioceridae + Mydidae to Asilidae. A time-calibrated phylogeny is also presented, with seven fossil calibration points, which suggests an older age of the split among Apioceridae, Asilidae, and Mydidae (158 mya) and Apioceridae and Mydidae (135 mya) than proposed in the AToL FlyTree project. Future studies will be able to take advantage of the resources presented here in order to produce large scale phylogenomic and evolutionary studies of assassin fly phylogeny, life histories, or venom. The bioinformatics tools and workflow presented here will be useful to others wishing to generate de novo genomic resources in species-rich taxa without a closely-related reference genome.

Advances using molecular data in insect systematics

The size of molecular datasets has been growing exponentially since the mid 1980s, and new technologies have now dramatically increased the slope of this increase. New datasets include genomes, transcriptomes, and hybrid capture data, producing hundreds or thousands of loci. With these datasets, we are approaching a consensus on the higher level insect phylogeny. Huge datasets can produce new challenges in interpreting branch support, and new opportunities in developing better models and more sophisticated partitioning schemes. Dating analyses are improving as we recognize the importance of careful fossil calibration selection. With thousands of genes now available, coalescent methods have come of age. Barcode libraries continue to expand, and new methods are being developed for incorporating them into phylogenies with tens of thousands of individuals.

Fly family diversity shows evidence of livestock grazing pressure in Mongolia (Insecta: Diptera)

Members of the insect order Diptera respond differentially to environmental changes and may play an important role in understanding the effects that livestock grazing disturbances have on biodiversity. Here we examine how increasing grazing pressures on the Mongolian steppe affect Diptera diversity and abundance. Using 2334 yellow pan traps, we sampled a total of 132 sites over four years to collect 17,348 flies. We compared fly diversity and abundance at five levels of livestock grazing. We observed that fly family diversity decreased in heavily grazed sites and that diptera communities at sites with intense grazing have proportionally higher prevalence of taxa from the families Muscidae, Sepsidae, Ephydridae, Chloropidae, and Tachinidae, two of which are often associated with animal waste. Chironomidae, Ceratopogonidae, Sarcophagidae, and Sciaridae are most prevalent at sites with very little or no grazing, and Anthomyiidae, Calliphoridae, Carnidae, Cecidomyiidae, Dolichopodidae, Empididae, Scatopsidae and Sphaeroceridae are most often encountered at sites with intermediate amounts of grazing. Observing changes in a few guilds of fly families at different grazing levels is beneficial in understanding human effects on fly diversity.