How Important Is Sexual Isolation to Speciation?

A central role for sexual isolation in the formation of new species and establishment of species boundaries has been noticed since Darwin and is frequently emphasized in the modern literature on speciation. However, an objective evaluation of when and how sexual isolation plays a role in speciation has been carried out in few taxa. We discuss three approaches for assessing the importance of sexual isolation relative to other reproductive barriers, including the relative evolutionary rate of sexual trait differentiation, the relative strength of sexual isolation in sympatry, and the role of sexual isolation in the long-term persistence of diverging forms. First, we evaluate evidence as to whether sexual isolation evolves faster than other reproductive barriers during the early stages of divergence. Second, we discuss available evidence as to whether sexual isolation is as strong or stronger than other barriers between closely related sympatric species. Finally, we consider the effect of sexual isolation on long-term species persistence, relative to other reproductive barriers. We highlight challenges to our knowledge of and opportunities to improve upon our understanding of sexual isolation from different phases of the speciation process.

The role of microbial biofilms in range shifts of marine habitat-forming organisms.

Marine species, such as corals and kelp, are responding to climate change by altering their distributions. Microbial biofilms underpin key processes that affect the establishment, maintenance, and function of these dominant habitat-formers. Climate-mediated changes to microbial biofilms can therefore strongly influence species' range shifts. Here, we review emerging research on the interactions between benthic biofilms and habitat-formers and identify two key areas of interaction where climate change can impact this dynamic: (i) via direct effects on biofilm composition, and (ii) via impacts on the complex feedback loops which exist between the biofilm microbes and habitat-forming organisms. We propose that these key interactions will be fundamental in driving the speed and extent of tropicalisation of coastal ecosystems under climate change.

Innovation and elaboration on the avian tree of life.

Widely documented, megaevolutionary jumps in phenotypic diversity continue to perplex researchers because it remains unclear whether these marked changes can emerge from microevolutionary processes. Here, we tackle this question using new approaches for modeling multivariate traits to evaluate the magnitude and distribution of elaboration and innovation in the evolution of bird beaks. We find that elaboration, evolution along the major axis of phenotypic change, is common at both macro- and megaevolutionary scales, whereas innovation, evolution away from the major axis of phenotypic change, is more prominent at megaevolutionary scales. The major axis of phenotypic change among species beak shapes at megaevolutionary scales is an emergent property of innovation across clades. Our analyses suggest that the reorientation of phenotypes via innovation is a ubiquitous route for divergence that can arise through gradual change alone, opening up further avenues for evolution to explore.

Clinical Evaluation of the XDR-LFC Assay for the Molecular Detection of Isoniazid, Rifampin, Fluoroquinolone, Kanamycin, Capreomycin, and Amikacin Drug Resistance in a Prospective Cohort.

While the goal of universal drug susceptibility testing has been a key component of the WHO End TB Strategy, in practice, this remains inaccessible to many. Rapid molecular tests for tuberculosis (TB) and antituberculosis drug resistance could significantly improve access to testing. In this study, we evaluated the accuracy of the Akonni Biosystems XDR-TB (extensively drug-resistant TB) TruArray and lateral-flow-cell (XDR-LFC) assay (Akonni Biosystems, Inc., Frederick, MD, USA), a novel assay that detects mutations in seven genes associated with resistance to antituberculosis drugs: katG, the inhA promoter, and the ahpC promoter for isoniazid; rpoB for rifampin; gyrA for fluoroquinolones; rrs and the eis promoter for kanamycin; and rrs for capreomycin and amikacin. We evaluated assay performance using direct sputum samples from 566 participants recruited in a prospective cohort in Moldova over 2 years. The sensitivity and specificity against the phenotypic reference were both 100% for isoniazid, 99.2% and 97.9% for rifampin, 84.8% and 99.1% for fluoroquinolones, 87.0% and 84.1% for kanamycin, 54.3% and 100% for capreomycin, and 79.2% and 100% for amikacin, respectively. Whole-genome sequencing data for a subsample of 272 isolates showed 95 to 99% concordance with the XDR-LFC-reported suspected mutations. The XDR-LFC assay demonstrated a high level of accuracy for multiple drugs and met the WHO's minimum target product profile criteria for isoniazid and rifampin, while the sensitivity for fluoroquinolones and amikacin fell below target thresholds, likely due to the absence of a gyrB target in the assay. With optimization, the XDR-LFC shows promise as a novel near-patient technology to rapidly diagnose drug-resistant tuberculosis.

Using pose estimation to identify regions and points on natural history specimens.

A key challenge in mobilising growing numbers of digitised biological specimens for scientific research is finding high-throughput methods to extract phenotypic measurements on these datasets. In this paper, we test a pose estimation approach based on Deep Learning capable of accurately placing point labels to identify key locations on specimen images. We then apply the approach to two distinct challenges that each requires identification of key features in a 2D image: (i) identifying body region-specific plumage colouration on avian specimens and (ii) measuring morphometric shape variation in Littorina snail shells. For the avian dataset, 95% of images are correctly labelled and colour measurements derived from these predicted points are highly correlated with human-based measurements. For the Littorina dataset, more than 95% of landmarks were accurately placed relative to expert-labelled landmarks and predicted landmarks reliably captured shape variation between two distinct shell ecotypes ('crab' vs 'wave'). Overall, our study shows that pose estimation based on Deep Learning can generate high-quality and high-throughput point-based measurements for digitised image-based biodiversity datasets and could mark a step change in the mobilisation of such data. We also provide general guidelines for using pose estimation methods on large-scale biological datasets.

Sociality, ecology and developmental constraints predict variation in brain size across birds.

Conflicting theories have been proposed to explain variation in relative brain size across the animal kingdom. Ecological theories argue that the cognitive demands of seasonal or unpredictable environments have selected for increases in relative brain size, whereas the 'social brain hypothesis' argues that social complexity is the primary driver of brain size evolution. Here, we use a comparative approach to test the relative importance of ecology (diet, foraging niche and migration), sociality (social bond, cooperative breeding and territoriality) and developmental mode in shaping brain size across 1886 bird species. Across all birds, we find a highly significant effect of developmental mode and foraging niche on brain size, suggesting that developmental constraints and selection for complex motor skills whilst foraging generally imposes important selection on brain size in birds. We also find effects of social bonding and territoriality on brain size, but the direction of these effects do not support the social brain hypothesis. At the same time, we find extensive heterogeneity among major avian clades in the relative importance of different variables, implying that the significance of particular ecological and social factors for driving brain size evolution is often clade- and context-specific. Overall, our results reveal the important and complex ways in which ecological and social selection pressures and developmental constraints shape brain size evolution across birds.

Deep learning image segmentation reveals patterns of UV reflectance evolution in passerine birds.

Ultraviolet colouration is thought to be an important form of signalling in many bird species, yet broad insights regarding the prevalence of ultraviolet plumage colouration and the factors promoting its evolution are currently lacking. In this paper, we develop a image segmentation pipeline based on deep learning that considerably outperforms classical (i.e. non deep learning) segmentation methods, and use this to extract accurate information on whole-body plumage colouration from photographs of >24,000 museum specimens covering >4500 species of passerine birds. Our results demonstrate that ultraviolet reflectance, particularly as a component of other colours, is widespread across the passerine radiation but is strongly phylogenetically conserved. We also find clear evidence in support of the role of light environment in promoting the evolution of ultraviolet plumage colouration, and a weak trend towards higher ultraviolet plumage reflectance among bird species with ultraviolet rather than violet-sensitive visual systems. Overall, our study provides important broad-scale insight into an enigmatic component of avian colouration, as well as demonstrating that deep learning has considerable promise for allowing new data to be brought to bear on long-standing questions in ecology and evolution.

Detecting signatures of selection on gene expression.

A substantial amount of phenotypic diversity results from changes in gene expression levels and patterns. Understanding how the transcriptome evolves is therefore a key priority in identifying mechanisms of adaptive change. However, in contrast to powerful models of sequence evolution, we lack a consensus model of gene expression evolution. Furthermore, recent work has shown that many of the comparative approaches used to study gene expression are subject to biases that can lead to false signatures of selection. Here we first outline the main approaches for describing expression evolution and their inherent biases. Next, we bridge the gap between the fields of phylogenetic comparative methods and transcriptomics to reinforce the main pitfalls of inferring selection on expression patterns and use simulation studies to show that shifts in tissue composition can heavily bias inferences of selection. We close by highlighting the multi-dimensional nature of transcriptional variation and identifying major unanswered questions in disentangling how selection acts on the transcriptome.

Latitudinal gradients in avian colourfulness.

It has long been suggested that tropical species are generally more colourful than temperate species, but whether latitudinal gradients in organismal colourfulness exist remains controversial. Here we quantify global latitudinal trends in colourfulness (within-individual colour diversity) by collating and analysing a photographic dataset of whole-body plumage reflectance information for >4,500 species of passerine birds. We show that male and female birds of tropical passerine species are generally more colourful than their temperate counterparts, both on average and in the extreme. We also show that these geographic gradients can be explained in part by the effects of several latitude-related factors related to classic hypotheses for climatic and ecological determinants of organismal colourfulness. Taken together, our results reveal that species' colourfulness peaks in the tropics for passerine birds, confirming the existence of a long-suspected yet hitherto elusive trend in the distribution of global biodiversity.