Putting the ‘bio’ into bioinformatics

Bioinformatic analyses have grown rapidly in sophistication and efficiency to accommodate the vast increase in available data. One of the major challenges has been to incorporate the growing appreciation of the complexity of molecular evolution into new analytical methods. As the reliance on molecular data in biology and medicine increases, we need to be confident that these methods adequately reflect the underlying processes of genome change. This special issue focuses on the way that patterns and processes of molecular evolution are influenced by features of populations of whole organisms, such as selection pressure, population size and life history. The advantage of this approach to molecular evolution is that it views genomic change not simply as a biochemical or stochastic process, but as the result of a complex series of interactions that shape the kinds of genomic changes that can and do happen.     

Putting the genes into community genetics

As part of the long‐term fusion of evolutionary biology and ecology (Ford, 1964), the field of community genetics has made tremendous progress in describing the impacts of plant genetic variation on community and ecosystem processes. In the “genes‐to‐ecosystems” framework (Whitham et al., 2003), genetically based traits of plant species have ecological consequences, but previous studies have not identified specific plant genes responsible for community phenotypes. The study by Barker et al. (2019) in this issue of Molecular Ecology uses an impressive common garden experiment of trembling aspen (Figure 1) to test for the genetic basis of tree traits that shape the insect community composition. Using a Genome‐Wide Association Study (GWAS), they found that genomic regions associated with phytochemical traits best explain variation in herbivore community composition, and identified specific genes associated with different types of leaf‐modifying herbivores and ants. This is one of the first studies to identify candidate genes underlying the heritable plant traits that explain patterns of insect biodiversity.     

Putting pharmacogenetics into practice

Genetics is slowly explaining variations in drug response, but applying this knowledge depends on implementation of a host of policies that provide long-term support to the field, from translational research and regulation to professional education.     

Putting the systems back into systems biology

In recent years the term "systems biology" has become widespread in the biological literature, but most of the papers in which these words appear have surprisingly little to do with older notions of biological systems: they often seem to imply little more than reductionist biology applied on a large scale, with a little attention to interactions between some of the components, but with minimal attention to the kinetic properties of enzymes, which supplied much of the reductionist foundation of biochemistry. A systemic approach to biology ought to put the emphasis on the entire system; insofar as it is concerned with components at all, it is to explain their roles in meeting the needs of the system as a whole. Genuinely systemic thinking allows us to understand how biochemical systems are regulated, and why clumsy attempts to manipulate them for biotechnological purposes may fail. At a more abstract level, it is necessary for understanding the nature of life, because as long as an organism is treated as no more than a collection of components, one cannot ask the right questions, and certainly cannot answer them.     

Putting the pH into phosphatidic acid signaling

Background

Camouflage patterns that hinder detection and/or recognition by antagonists are widely studied in both human and animal contexts. Patterns of contrasting stripes that purportedly degrade an observer's ability to judge the speed and direction of moving prey ('motion dazzle') are, however, rarely investigated. This is despite motion dazzle having been fundamental to the appearance of warships in both world wars and often postulated as the selective agent leading to repeated patterns on many animals (such as zebra and many fish, snake, and invertebrate species). Such patterns often appear conspicuous, suggesting that protection while moving by motion dazzle might impair camouflage when stationary. However, the relationship between motion dazzle and camouflage is unclear because disruptive camouflage relies on high-contrast markings. In this study, we used a computer game with human subjects detecting and capturing either moving or stationary targets with different patterns, in order to provide the first empirical exploration of the interaction of these two protective coloration mechanisms.

Results

Moving targets with stripes were caught significantly less often and missed more often than targets with camouflage patterns. However, when stationary, targets with camouflage markings were captured less often and caused more false detections than those with striped patterns, which were readily detected.

Conclusions

Our study provides the clearest evidence to date that some patterns inhibit the capture of moving targets, but that camouflage and motion dazzle are not complementary strategies. Therefore, the specific coloration that evolves in animals will depend on how the life history and ontogeny of each species influence the trade-off between the costs and benefits of motion dazzle and camouflage.     

Putting epigenome comparison into practice

Comparative analysis of epigenomes offers new opportunities to understand cellular differentiation, mutation effects and disease processes. But the scale and heterogeneity of epigenetic data present numerous computational challenges.