Diversity and Evolution of Frog Visual Opsins: Spectral Tuning and Adaptation to Distinct Light Environments.

Visual systems adapt to different light environments through several avenues including optical changes to the eye and neurological changes in how light signals are processed and interpreted. Spectral sensitivity can evolve via changes to visual pigments housed in the retinal photoreceptors through gene duplication and loss, differential and coexpression, and sequence evolution. Frogs provide an excellent, yet understudied, system for visual evolution research due to their diversity of ecologies (including biphasic aquatic-terrestrial life cycles) that we hypothesize imposed different selective pressures leading to adaptive evolution of the visual system, notably the opsins that encode the protein component of the visual pigments responsible for the first step in visual perception. Here, we analyze the diversity and evolution of visual opsin genes from 93 new eye transcriptomes plus published data for a combined dataset spanning 122 frog species and 34 families. We find that most species express the four visual opsins previously identified in frogs but show evidence for gene loss in two lineages. Further, we present evidence of positive selection in three opsins and shifts in selective pressures associated with differences in habitat and life history, but not activity pattern. We identify substantial novel variation in the visual opsins and, using microspectrophotometry, find highly variable spectral sensitivities, expanding known ranges for all frog visual pigments. Mutations at spectral-tuning sites only partially account for this variation, suggesting that frogs have used tuning pathways that are unique among vertebrates. These results support the hypothesis of adaptive evolution in photoreceptor physiology across the frog tree of life in response to varying environmental and ecological factors and further our growing understanding of vertebrate visual evolution.

Professional development through mentoring: Final evaluation of the pilot mentoring programme of the European society of radiotherapy and oncology.

The European SocieTy for Radiotherapy and Oncology (ESTRO) organized a one-year pilot mentoring programme. At evaluation after one year, both mentors and mentees scored the programme with a median score of 9 on a scale of 10. All of the mentors indicated that they wanted to participate again as mentors.

Knowledge-based versus deep learning based treatment planning for breast radiotherapy.

Background and Purpose: To improve radiotherapy (RT) planning efficiency and plan quality, knowledge-based planning (KBP) and deep learning (DL) solutions have been developed. We aimed to make a direct comparison of these models for breast cancer planning using the same training, validation, and testing sets. Materials and Methods: Two KBP models were trained and validated with 90 RT plans for left-sided breast cancer with 15 fractions of 2.6 Gy. The versions either used the full dataset (non-clean model) or a cleaned dataset (clean model), thus eliminating geometric and dosimetric outliers. Results were compared with a DL U-net model (previously trained and validated with the same 90 RT plans) and manually produced RT plans, for the same independent dataset of 15 patients. Clinically relevant dose volume histogram parameters were evaluated according to established consensus criteria. Results: Both KBP models underestimated the mean heart and lung dose equally 0.4 Gy (0.3-1.1 Gy) and 1.4 Gy (1.1-2.8 Gy) compared to the clinical plans 0.8 Gy (0.5-1.8 Gy) and 1.7 Gy (1.3-3.2 Gy) while in the final calculations the mean lung dose was higher 1.9-2.0 Gy (1.5-3.5 Gy) for both KPB models. The U-Net model resulted in a mean planning target volume dose of 40.7 Gy (40.4-41.3 Gy), slightly higher than the clinical plans 40.5 Gy (40.1-41.0 Gy). Conclusions: Only small differences were observed between the estimated and final dose calculation and the clinical results for both KPB models and the DL model. With a good set of breast plans, the data cleaning module is not needed and both KPB and DL models lead to clinically acceptable results.

Frog phylogeny: A time-calibrated, species-level tree based on hundreds of loci and 5,242 species.

Large-scale, time-calibrated phylogenies from supermatrix studies have become crucial for evolutionary and ecological studies in many groups of organisms. However, in frogs (anuran amphibians), there is a serious problem with existing supermatrix estimates. Specifically, these trees are based on a limited number of loci (15 or fewer), and the higher-level relationships estimated are discordant with recent phylogenomic estimates based on much larger numbers of loci. Here, we attempted to rectify this problem by generating an expanded supermatrix and combining this with data from phylogenomic studies. To assist in aligning ribosomal sequences for this supermatrix, we developed a new program (TaxonomyAlign) to help perform taxonomy-guided alignments. The new combined matrix contained 5,242 anuran species with data from 307 markers, but with 95% missing data overall. This dataset represented a 71% increase in species sampled relative to the previous largest supermatrix analysis of anurans (adding 2,175 species). Maximum-likelihood analyses generated a tree in which higher-level relationships (and estimated clade ages) were generally concordant with those from phylogenomic analyses but were more discordant with the previous largest supermatrix analysis. We found few obvious problems arising from the extensive missing data in most species. We also generated a set of 100 time-calibrated trees for use in comparative analyses. Overall, we provide an improved estimate of anuran phylogeny based on the largest number of combined taxa and markers to date. More broadly, we demonstrate the potential to combine phylogenomic and supermatrix analyses in other groups of organisms.

Direct haplotype-resolved 5-base HiFi sequencing for genome-wide profiling of hypermethylation outliers in a rare disease cohort.

Long-read HiFi genome sequencing allows for accurate detection and direct phasing of single nucleotide variants, indels, and structural variants. Recent algorithmic development enables simultaneous detection of CpG methylation for analysis of regulatory element activity directly in HiFi reads. We present a comprehensive haplotype resolved 5-base HiFi genome sequencing dataset from a rare disease cohort of 276 samples in 152 families to identify rare (~0.5%) hypermethylation events. We find that 80% of these events are allele-specific and predicted to cause loss of regulatory element activity. We demonstrate heritability of extreme hypermethylation including rare cis variants associated with short (~200 bp) and large hypermethylation events (>1 kb), respectively. We identify repeat expansions in proximal promoters predicting allelic gene silencing via hypermethylation and demonstrate allelic transcriptional events downstream. On average 30-40 rare hypermethylation tiles overlap rare disease genes per patient, providing indications for variation prioritization including a previously undiagnosed pathogenic allele in DIP2B causing global developmental delay. We propose that use of HiFi genome sequencing in unsolved rare disease cases will allow detection of unconventional diseases alleles due to loss of regulatory element activity.

Redefining Possible: Combining Phylogenomic and Supersparse Data in Frogs.

The data available for reconstructing molecular phylogenies have become wildly disparate. Phylogenomic studies can generate data for thousands of genetic markers for dozens of species, but for hundreds of other taxa, data may be available from only a few genes. Can these two types of data be integrated to combine the advantages of both, addressing the relationships of hundreds of species with thousands of genes? Here, we show that this is possible, using data from frogs. We generated a phylogenomic data set for 138 ingroup species and 3,784 nuclear markers (ultraconserved elements [UCEs]), including new UCE data from 70 species. We also assembled a supermatrix data set, including data from 97% of frog genera (441 total), with 1-307 genes per taxon. We then produced a combined phylogenomic-supermatrix data set (a "gigamatrix") containing 441 ingroup taxa and 4,091 markers but with 86% missing data overall. Likelihood analysis of the gigamatrix yielded a generally well-supported tree among families, largely consistent with trees from the phylogenomic data alone. All terminal taxa were placed in the expected families, even though 42.5% of these taxa each had >99.5% missing data and 70.2% had >90% missing data. Our results show that missing data need not be an impediment to successfully combining very large phylogenomic and supermatrix data sets, and they open the door to new studies that simultaneously maximize sampling of genes and taxa.

A high-quality Ixodes scapularis genome advances tick science.

Ixodes spp. and related ticks transmit prevalent infections, although knowledge of their biology and development of anti-tick measures have been hindered by the lack of a high-quality genome. In the present study, we present the assembly of a 2.23-Gb Ixodes scapularis genome by sequencing two haplotypes within one individual, complemented by chromosome-level scaffolding and full-length RNA isoform sequencing, yielding a fully reannotated genome featuring thousands of new protein-coding genes and various RNA species. Analyses of the repetitive DNA identified transposable elements, whereas the examination of tick-associated bacterial sequences yielded an improved Rickettsia buchneri genome. We demonstrate how the Ixodes genome advances tick science by contributing to new annotations, gene models and epigenetic functions, expansion of gene families, development of in-depth proteome catalogs and deciphering of genetic variations in wild ticks. Overall, we report critical genetic resources and biological insights impacting our understanding of tick biology and future interventions against tick-transmitted infections.

Longitudinal, Multi-Platform Metagenomics Yields a High-Quality Genomic Catalog and Guides an In Vitro Model for Cheese Communities.

Microbiomes are intricately intertwined with human health, geochemical cycles, and food production. While many microbiomes of interest are highly complex and experimentally intractable, cheese rind microbiomes have proven to be powerful model systems for the study of microbial interactions. To provide a more comprehensive view of the genomic potential and temporal dynamics of cheese rind communities, we combined longitudinal, multi-platform metagenomics of three ripening washed-rind cheeses with whole-genome sequencing of community isolates. Sequencing-based approaches revealed a highly reproducible microbial succession in each cheese and the coexistence of closely related Psychrobacter species and enabled the prediction of plasmid and phage diversity and their host associations. In combination with culture-based approaches, we established a genomic catalog and a paired 16-member in vitro washed-rind cheese system. The combination of multi-platform metagenomic time-series data and an in vitro model provides a rich resource for further investigation of cheese rind microbiomes both computationally and experimentally. IMPORTANCE Metagenome sequencing can provide great insights into microbiome composition and function and help researchers develop testable hypotheses. Model microbiomes, such as those composed of cheese rind bacteria and fungi, allow the testing of these hypotheses in a controlled manner. Here, we first generated an extensive longitudinal metagenomic data set. This data set reveals successional dynamics, yields a phyla-spanning bacterial genomic catalog, associates mobile genetic elements with their hosts, and provides insights into functional enrichment of Psychrobacter in the cheese environment. Next, we show that members of the washed-rind cheese microbiome lend themselves to in vitro community reconstruction. This paired metagenomic data and in vitro system can thus be used as a platform for generating and testing hypotheses related to the dynamics within, and the functions associated with, cheese rind microbiomes.

Evaluation of taxonomic classification and profiling methods for long-read shotgun metagenomic sequencing datasets.

BACKGROUND: Long-read shotgun metagenomic sequencing is gaining in popularity and offers many advantages over short-read sequencing. The higher information content in long reads is useful for a variety of metagenomics analyses, including taxonomic classification and profiling. The development of long-read specific tools for taxonomic classification is accelerating, yet there is a lack of information regarding their relative performance. Here, we perform a critical benchmarking study using 11 methods, including five methods designed specifically for long reads. We applied these tools to several mock community datasets generated using Pacific Biosciences (PacBio) HiFi or Oxford Nanopore Technology sequencing, and evaluated their performance based on read utilization, detection metrics, and relative abundance estimates. RESULTS: Our results show that long-read classifiers generally performed best. Several short-read classification and profiling methods produced many false positives (particularly at lower abundances), required heavy filtering to achieve acceptable precision (at the cost of reduced recall), and produced inaccurate abundance estimates. By contrast, two long-read methods (BugSeq, MEGAN-LR & DIAMOND) and one generalized method (sourmash) displayed high precision and recall without any filtering required. Furthermore, in the PacBio HiFi datasets these methods detected all species down to the 0.1% abundance level with high precision. Some long-read methods, such as MetaMaps and MMseqs2, required moderate filtering to reduce false positives to resemble the precision and recall of the top-performing methods. We found read quality affected performance for methods relying on protein prediction or exact k-mer matching, and these methods performed better with PacBio HiFi datasets. We also found that long-read datasets with a large proportion of shorter reads (< 2 kb length) resulted in lower precision and worse abundance estimates, relative to length-filtered datasets. Finally, for classification methods, we found that the long-read datasets produced significantly better results than short-read datasets, demonstrating clear advantages for long-read metagenomic sequencing. CONCLUSIONS: Our critical assessment of available methods provides best-practice recommendations for current research using long reads and establishes a baseline for future benchmarking studies.

Systematics of the Central African Spiny Reed Frog Afrixalus laevis (Anura: Hyperoliidae), with the description of two new species from the Albertine Rift.

The geographically widespread species Afrixalus laevis (Anura: Hyperoliidae) currently has a disjunct distribution in western Central Africa (Cameroon, Equatorial Guinea, Gabon, and possibly adjacent countries) and the area in and near the Albertine Rift in eastern Democratic Republic of the Congo and neighboring countries. At least two herpetologists have previously suggested that these disjunct populations represent distinct species, and herein, we utilize an integrative taxonomic approach with molecular and morphological data to reconcile the taxonomy of these spiny reed frogs. We sequenced 1554 base pairs of the 16S and RAG1 genes from 34 samples of A. laevis and one sample of A. orophilus (sympatric with eastern populations of A. laevis), and combined these data with previously sequenced GenBank Afrixalus samples via the bioinformatics toolkit SuperCRUNCH. Phylogenetic trees, dated phylogenetic analyses, and species-delimitation analyses were generated with RAxML, BEAST, and BPP, respectively. Eleven mensural characters were taken from multiple specimens of A. laevis and A. orophilus, and compared with paired t-tests and analyses of covariance. These combined results suggested populations of A. laevis in western Central Africa (Cameroon and Bioko Island, Equatorial Guinea) represent one species, whereas populations from the Albertine Rift and nearby forests represent two undescribed taxa that are sister to A. dorsimaculatus. The two new species (A. lacustris sp. nov. and A. phantasma sp. nov.) are distinguished by our phylogenetic and species-delimitation analyses, significant differences in several mensural characters, qualitative morphological differences, and by their non-overlapping elevational distribution.

Phylogeography and population genetics of a widespread cold-adapted ant, Prenolepis imparis.

As species arise, evolve and diverge, they are shaped by forces that unfold across short and long timescales and at both local and vast geographical scales. It is rare, however, to be able document this history across broad sweeps of time and space in a single species. Here, we report the results of a continental-scale phylogenomic analysis across the entire range of a widespread species. We analysed sequences of 1402 orthologous ultraconserved element (UCE) loci from 75 individuals to identify population genetic structure and historical demographic patterns across the continent-wide range of a cold-adapted ant, the winter ant, Prenolepis imparis. We recovered five well-supported, genetically isolated clades representing lineages that diverged from 8.2-2.2 million years ago. These include: (i) an early diverging lineage located in Florida, (ii) a lineage that spans the southern United States, (iii) populations that extend across the midwestern and northeastern United States, (iv) populations from the western United States and (v) populations in southwestern Arizona and Mexico. Population genetic analyses revealed little or no gene flow among these lineages, but patterns consistent with more recent gene flow among populations within lineages, and localized structure with migration in the western United States. High support for five major geographical lineages and lack of evidence of contemporary gene flow indicate in situ diversification across the species' range, producing relatively ancient lineages that persisted through subsequent climate change and glaciation during the Quaternary.

Metagenome assembly of high-fidelity long reads with hifiasm-meta.

De novo assembly of metagenome samples is a common approach to the study of microbial communities. Current metagenome assemblers developed for short sequence reads or noisy long reads were not optimized for accurate long reads. We thus developed hifiasm-meta, a metagenome assembler that exploits the high accuracy of recent data. Evaluated on seven empirical datasets, hifiasm-meta reconstructed tens to hundreds of complete circular bacterial genomes per dataset, consistently outperforming other metagenome assemblers.

Finding the right fit: evaluation of short-read and long-read sequencing approaches to maximize the utility of clinical microbiome data.

A long-standing challenge in human microbiome research is achieving the taxonomic and functional resolution needed to generate testable hypotheses about the gut microbiota's impact on health and disease. With a growing number of live microbial interventions in clinical development, this challenge is renewed by a need to understand the pharmacokinetics and pharmacodynamics of therapeutic candidates. While short-read sequencing of the bacterial 16S rRNA gene has been the standard for microbiota profiling, recent improvements in the fidelity of long-read sequencing underscores the need for a re-evaluation of the value of distinct microbiome-sequencing approaches. We leveraged samples from participants enrolled in a phase 1b clinical trial of a novel live biotherapeutic product to perform a comparative analysis of short-read and long-read amplicon and metagenomic sequencing approaches to assess their utility for generating clinical microbiome data. Across all methods, overall community taxonomic profiles were comparable and relationships between samples were conserved. Comparison of ubiquitous short-read 16S rRNA amplicon profiling to long-read profiling of the 16S-ITS-23S rRNA amplicon showed that only the latter provided strain-level community resolution and insight into novel taxa. All methods identified an active ingredient strain in treated study participants, though detection confidence was higher for long-read methods. Read coverage from both metagenomic methods provided evidence of active-ingredient strain replication in some treated participants. Compared to short-read metagenomics, approximately twice the proportion of long reads were assigned functional annotations. Finally, compositionally similar bacterial metagenome-assembled genomes (MAGs) were recovered from short-read and long-read metagenomic methods, although a greater number and more complete MAGs were recovered from long reads. Despite higher costs, both amplicon and metagenomic long-read approaches yielded added microbiome data value in the form of higher confidence taxonomic and functional resolution and improved recovery of microbial genomes compared to traditional short-read methodologies.

Generating lineage-resolved, complete metagenome-assembled genomes from complex microbial communities.

Microbial communities might include distinct lineages of closely related organisms that complicate metagenomic assembly and prevent the generation of complete metagenome-assembled genomes (MAGs). Here we show that deep sequencing using long (HiFi) reads combined with Hi-C binning can address this challenge even for complex microbial communities. Using existing methods, we sequenced the sheep fecal metagenome and identified 428 MAGs with more than 90% completeness, including 44 MAGs in single circular contigs. To resolve closely related strains (lineages), we developed MAGPhase, which separates lineages of related organisms by discriminating variant haplotypes across hundreds of kilobases of genomic sequence. MAGPhase identified 220 lineage-resolved MAGs in our dataset. The ability to resolve closely related microbes in complex microbial communities improves the identification of biosynthetic gene clusters and the precision of assigning mobile genetic elements to host genomes. We identified 1,400 complete and 350 partial biosynthetic gene clusters, most of which are novel, as well as 424 (298) potential host-viral (host-plasmid) associations using Hi-C data.

FrogCap: A modular sequence capture probe-set for phylogenomics and population genetics for all frogs, assessed across multiple phylogenetic scales.

Despite the prevalence of high-throughput sequencing in phylogenetics, many relationships remain difficult to resolve because of conflicting signal among genomic regions. Selection of different types of molecular markers from different genomic regions is required to overcome these challenges. For evolutionary studies in frogs, we introduce the publicly available FrogCap suite of genomic resources, which is a large collection of ~15,000 markers that unifies previous genetic sequencing efforts. FrogCap is designed to be modular, such that subsets of markers and SNPs can be selected based on the desired phylogenetic scale. FrogCap uses a variety of marker types that include exons and introns, ultraconserved elements, and previously sequenced Sanger markers, which span up to 10,000 bp in alignment lengths; in addition, we demonstrate potential for SNP-based analyses. We tested FrogCap using 121 samples distributed across five phylogenetic scales, comparing probes designed using a consensus- or exemplar genome-based approach. Using the consensus design is more resilient to issues with sensitivity, specificity, and missing data than picking an exemplar genome sequence. We also tested the impact of different bait kit sizes (20,020 vs. 40,040) on depth of coverage and found triple the depth for the 20,020 bait  kit. We observed sequence capture success (i.e., missing data, sequenced markers/bases, marker length, and informative sites) across phylogenetic scales. The incorporation of different marker types is effective for deep phylogenetic relationships and shallow population genetics studies. Having demonstrated FrogCap's utility and modularity, we conclude that these new resources are efficacious for high-throughput sequencing projects across variable timescales.

Giant Tree Frog diversification in West and Central Africa: Isolation by physical barriers, climate, and reproductive traits.

Secondary sympatry amongst sister lineages is strongly associated with genetic and ecological divergence. This pattern suggests that for closely related species to coexist in secondary sympatry, they must accumulate differences in traits that mediate ecological and/or reproductive isolation. Here, we characterized inter- and intraspecific divergence in three giant tree frog species whose distributions stretch across West and Central Africa. Using genome-wide single-nucleotide polymorphism data, we demonstrated that species-level divergence coincides temporally and geographically with a period of large-scale forest fragmentation during the late Pliocene. Our environmental niche models further supported a dynamic history of climatic suitability and stability, and indicated that all three species occupy distinct environmental niches. We found modest morphological differentiation amongst the species with significant divergence in tympanum diameter and male advertisement call. In addition, we confirmed that two species occur in secondary sympatry in Central Africa but found no evidence of hybridization. These patterns support the hypothesis that cycles of genetic exchange and isolation across West and Central Africa have contributed to globally significant biodiversity. Furthermore, divergence in both ecology and reproductive traits appear to have played important roles in maintaining distinct lineages. At the intraspecific level, we found that climatic refugia, precipitation gradients, marine incursions, and potentially riverine barriers generated phylogeographic structure throughout the Pleistocene and into the Holocene. Further studies examining phenotypic divergence and secondary contact amongst these geographically structured populations may demonstrate how smaller scale and more recent biogeographic barriers contribute to regional diversification.

La sympatrie secondaire parmi les espèces sœurs est fortement associée à la divergence génétique et écologique. Ce modèle suggère que pour que des espèces étroitement liées coexistent en sympatrie secondaire, elles doivent accumuler des différences dans les traits qui contribuent à l'isolement écologique ou reproductif. Ici, nous avons caractérisé la divergence inter- et intra-spécifique chez trois espèces de grenouilles arboricoles géantes dont les distributions s'étendent à travers l'Afrique de l'Ouest et Centrale. Avec des données génétiques, nous avons démontré que la divergence au niveau des espèces coïncide temporellement et géographiquement avec une période de fragmentation forestière à la fin du Pliocène. Nos modèles de niches environnementales ont soutenu une histoire dynamique de stabilité climatique, et ont indiqué que les trois espèces occupent des niches environnementales distinctes. Nous avons trouvé une différenciation morphologique modeste parmi les trois espèces mais une divergence significative dans le diamètre du tympan et les cris des mâles. De plus, nous avons confirmé que deux espèces sont présentes en sympatrie secondaire en Afrique Centrale mais n'avons trouvé aucune preuve d'hybridation. Ces résultats soutiennent l'hypothèse que les cycles d'échange génétique et d'isolement à travers l'Afrique de l'Ouest et Centrale ont contribué à une profonde concentration de biodiversité dans la région. De plus, la divergence des traits écologiques et reproducteurs semble avoir joué un rôle important dans le maintien de lignées distinctes. Au niveau intra-spécifique, nous avons constaté que les refuges climatiques, les gradients de précipitation, les incursions marines et potentiellement les barrières fluviales ont généré une structure phylogéographique pendant le Pléistocène et jusqu'à l'Holocène. Des études examinant la divergence phénotypique et le contact secondaire entre ces populations géographiquement structurées pourraient démontrer comment des barrières biogéographiques à échelle plus petite et plus récentes contribuent à la diversification régionale.

Phylogenomics of Monitor Lizards and the Role of Competition in Dictating Body Size Disparity.

Organismal interactions drive the accumulation of diversity by influencing species ranges, morphology, and behavior. Interactions vary from agonistic to cooperative and should result in predictable patterns in trait and range evolution. However, despite a conceptual understanding of these processes, they have been difficult to model, particularly on macroevolutionary timescales and across broad geographic spaces. Here, we investigate the influence of biotic interactions on trait evolution and community assembly in monitor lizards (Varanus). Monitors are an iconic radiation with a cosmopolitan distribution and the greatest size disparity of any living terrestrial vertebrate genus. Between the colossal Komodo dragon Varanus komodoensis and the smallest Australian dwarf goannas, Varanus length and mass vary by multiple orders of magnitude. To test the hypothesis that size variation in this genus was driven by character displacement, we extended existing phylogenetic comparative methods which consider lineage interactions to account for dynamic biogeographic history and apply these methods to Australian monitors and marsupial predators. Incorporating both exon-capture molecular and morphological data sets we use a combined evidence approach to estimate the relationships among living and extinct varaniform lizards. Our results suggest that communities of Australian Varanus show high functional diversity as a result of continent-wide interspecific competition among monitors but not with faunivorous marsupials. We demonstrate that patterns of trait evolution resulting from character displacement on continental scales are recoverable from comparative data and highlight that these macroevolutionary patterns may develop in parallel across widely distributed sympatric groups.[Character displacement; comparative methods; phylogenetics; trait evolution; Varanus.].

Do Alignment and Trimming Methods Matter for Phylogenomic (UCE) Analyses?

Alignment is a crucial issue in molecular phylogenetics because different alignment methods can potentially yield very different topologies for individual genes. But it is unclear if the choice of alignment methods remains important in phylogenomic analyses, which incorporate data from hundreds or thousands of genes. For example, problematic biases in alignment might be multiplied across many loci, whereas alignment errors in individual genes might become irrelevant. The issue of alignment trimming (i.e., removing poorly aligned regions or missing data from individual genes) is also poorly explored. Here, we test the impact of 12 different combinations of alignment and trimming methods on phylogenomic analyses. We compare these methods using published phylogenomic data from ultraconserved elements (UCEs) from squamate reptiles (lizards and snakes), birds, and tetrapods. We compare the properties of alignments generated by different alignment and trimming methods (e.g., length, informative sites, missing data). We also test whether these data sets can recover well-established clades when analyzed with concatenated (RAxML) and species-tree methods (ASTRAL-III), using the full data ($\sim $5000 loci) and subsampled data sets (10% and 1% of loci). We show that different alignment and trimming methods can significantly impact various aspects of phylogenomic data sets (e.g., length, informative sites). However, these different methods generally had little impact on the recovery and support values for well-established clades, even across very different numbers of loci. Nevertheless, our results suggest several "best practices" for alignment and trimming. Intriguingly, the choice of phylogenetic methods impacted the phylogenetic results most strongly, with concatenated analyses recovering significantly more well-established clades (with stronger support) than the species-tree analyses. [Alignment; concatenated analysis; phylogenomics; sequence length heterogeneity; species-tree analysis; trimming].

Finding complexity in complexes: Assessing the causes of mitonuclear discordance in a problematic species complex of Mesoamerican toads.

Mitonuclear discordance is a frequently encountered pattern in phylogeographic studies and occurs when mitochondrial and nuclear DNA display conflicting signals. Discordance among these genetic markers can be caused by several factors including confounded taxonomies, gene flow, and incomplete lineage sorting. In this study, we present a strong case of mitonuclear discordance in a species complex of toads (Bufonidae: Incilius coccifer complex) found in the Chortís Block of Central America. To determine the cause of mitonuclear discordance in this complex, we used spatially explicit genetic data to test species limits and relationships, characterize demographic history, and quantify gene flow. We found extensive mitonuclear discordance among the three recognized species within this group, especially in populations within the Chortís Highlands of Honduras. Our data reveal nuclear introgression within the Chortís Highlands populations that was most probably driven by cyclical range expansions due to climatic fluctuations. Though we determined introgression occurred within the nuclear genome, our data suggest that it is not the key factor in driving mitonuclear discordance in the entire species complex. Rather, due to a lack of discernible geographic pattern between mitochondrial and nuclear DNA, as well as a relatively recent divergence time of this complex, we concluded that mitonuclear discordance has been caused by incomplete lineage sorting. Our study provides a framework to test sources of mitonuclear discordance and highlights the importance of using multiple marker types to test species boundaries in cryptic species.

Macroevolutionary Patterns of Sexual Size Dimorphism Among African Tree Frogs (Family: Hyperoliidae).

Sexual size dimorphism (SSD) is shaped by multiple selective forces that drive the evolution of sex-specific body size, resulting in male or female-biased SSD. Stronger selection on one sex can result in an allometric body size scaling relationship consistent with Rensch's rule or its converse. Anurans (frogs and toads) generally display female-biased SSD, but there is variation across clades and the mechanisms driving the evolution of SSD remain poorly understood. We investigated these topics in a diverse family of African treefrogs (Hyperoliidae). Hyperoliids display traits considered rare among amphibians, including sexual dichromatism and protogynous sex change. Using phylogenetic comparative methods, we tested if adult ecology, sexual dichromatism, and sex change were predictors of body size or SSD. We also tested whether hyperoliids displayed allometric interspecific body size scaling relationships. We found a majority of hyperoliid taxa display female-biased SSD, but that adult ecology and sexual dichromatism are poor predictors of sex-specific body size and SSD. Regardless of the groupings analyzed (partitioned by clades or traits), we found support for isometric body size scaling. However, we found that sex change is a significant predictor of SSD variation. Species in the Hyperolius viridiflavus complex, which putatively display this trait, show a significant reduction in SSD and are frequently sexually monomorphic in size. Although protogynous sex change needs to be validated for several of these species, we tentatively propose this trait is a novel mechanism influencing anuran body size evolution. Beyond this association, additional factors that shape the evolution of anuran body size and SSD remain elusive.