Good from far,but far from good: The impact of a reference genome on evolutionary inference

Genomic diversity and past population histories are key considerations in the fields of conservation and evolutionary biology. In this issue of Molecular Ecology Resources, Prasad et al. (Mol. Ecol. Resour., 2021) examine how the quality and phylogenetic divergence of reference genomes influences the outcomes of downstream analyses such as diversity and demographic history inference. Using the beluga whale and rowi kiwi as examples (Figure 1), they systematically estimate heterozygosity, runs of homozygosity (ROH), and demographic history (PSMC) using reference genomes of varying quality and phylogenetic divergence from the target species. They show that demographic history analyses are impacted by phylogenetic distance, although this is not pronounced until divergence exceeds 3% from the target species. Similarly, their results imply that heterozygosity estimates are dependent on phylogenetic distance and the method used to perform the estimates, and ROHs are potentially undetectable when a nonconspecific reference is used. This investigation into the role of divergence and quality of reference genomes highlights the impact and potential biases generated by genome selection on downstream analyses, and provides a possible alternative in cross-species scaffolding in instances where a conspecific reference genome is not available.     

Links between genetic and functional diversity – a bridge too far?

The view that nutrient acquisition by most plants growing in natural ecosystems is mediated by mycorrhiza-forming symbiotic fungi is now largely accepted. With this perception comes the need to learn more about the identity of the organisms responsible for these key processes. Herein lies a challenge taken up by Vrålstad et al . on pp. 549–563 in this issue.     

Temporal regulation in the early embryo: is MBT too good to be true?

The question of how early embryonic events are temporally regulated has traditionally been tied to the mid-blastula transition (MBT). This concept has directed the studies in Xenopus and influenced the studies in other organisms. By examining the weaknesses in the concept of MBT, we hope to refocus the study of temporal regulation on the many developmental transitions that do exist and to clear the way for an alternative viewpoint that emphasizes the similarities between developmental processes in different organisms.     

Taxonomic and sensory biases in the mate-choice literature: there are far too few studies of chemical and multimodal communication

The sexual selection literature has grown rapidly in recent years. In an effort to elucidate biases in the focus of current mate-choice research here, I review 297 studies among 230 species. Among taxa, studies of birds were most common (40% of all studies), with insects, fishes, and anurans less well represented (20%, 18%, 14%, respectively). All other taxa were poorly represented in the literature (<3%). Across sensory modalities, studies of visual and acoustic signals were most common (46%, 30%, respectively), with relatively few studies investigating chemical, tactile, and electrical signals in mate choice (3%, 3%, <1%, respectively). Most mate-choice studies of birds and fishes investigated visual signals, while the majority of insect and anuran studies investigated acoustic signals. While these associations may reflect biological realities—birds and anurans tend not to emphasize chemical cues in mate choice; electric communication may indeed be quite uncommon—they may also be grossly misleading: chemical cues are likely critical for mate choice in millions of insect species. Moreover, I suggest that the particularly high vulnerability of chemical communication networks to anthropogenic fouling should provide immediate motivation for many more studies of chemical signals in mate choice. Finally, I find that despite widespread acceptance that male displays are often comprised of multiple elements produced across sensory modalities, studies simultaneously investigating the use of multiple cues in mate choice are rare. While not exhaustive, this review identifies biases in the focus of mate-choice studies, and should serve to identify fruitful directions for future mate-choice research.     

Allocating individuals to avoid inbreeding in ex situ conservation plantations: so far, so good

The only cost-effective way to control inbreeding in ex situ forest tree plantations is often to allocate trees in such a way that the possibility of close relatives mating is small and, consequently, inbreeding does not increase too much over time. The classical permutated neighbourhood methods look for the configuration in which no ramets of the same genet are planted in the surroundings (neighbourhoods) of a particular tree but deny the influence of more distant trees. Another limitation of these methods is that they cannot incorporate any other genetic (e.g. kinship) or ecological (e.g. phenology) information. We have developed a new method based on the minimisation of the global probability of generating inbred offspring for the whole population. Improvements of this method from the classical ones are: (i) it takes into account all the trees (whether near or far) and not only the neighbours; (ii) different pollen dispersal functions can be implemented, fitting the particularities of each species and population; (iii) it allows for the integration of all available information about the genetic relationship between trees; and (iv) it is flexible allowing for particular crosses to be banned or encouraged. The novel method showed a better performance than classical ones both for simulated data and a case study under a broad range of scenarios. Magnitude of the benefit depends on the actual and assumed parameters for the pollen dispersal function and the relationship between trees, but even in the simple case where only clone identity is considered some advantage can be obtained by implementing the new algorithm.     

The ACR20 and defining a threshold for response in rheumatic diseases: too much of a good thing

In the past 20 years great progress has been made in the development of multidimensional outcome measures (such as the Disease Activity Score and ACR20) to evaluate treatments in rheumatoid arthritis, a process disseminated throughout rheumatic diseases. These outcome measures have standardized the assessment of outcomes in trials, making it possible to evaluate and compare the efficacy of treatments. The methodologic advances have included the selection of pre-existing outcome measures that detected change in a sensitive fashion (in rheumatoid arthritis, this was the Core Set Measures). These measures were then combined into a single multidimensional outcome measure and such outcome measures have been widely adopted in trials and endorsed by the American College of Rheumatology (ACR) and the European League Against Rheumatism (EULAR) and regulatory agencies. The secular improvement in treatment for patients with rheumatoid arthritis has been facilitated in part by these major methodologic advancements. The one element of this effort that has not optimized measurement of outcomes nor made it easier to detect the effect of treatments is the dichotomization of continuous measures of response, creating responders and non-responder definitions (for example, ACR20 responders; EULAR good responders). Dichotomizing response sacrifices statistical power and eliminates variability in response. Future methodologic work will need to focus on improving multidimensional outcome measurement without arbitrarily characterizing some patients as responders while labeling others as non-responders.     

Evolution: sperm ejection near and far

In promiscuous fruit flies, the last male to inseminate a female has a fertilising advantage. Recent evidence indicates that this happens because females eject previously stored semen after a new copulation, revealing female bias in sperm use and the resulting battle of the sexes over fertilisation.     

Simplivariate models: ideas and first examples

One of the new expanding areas in functional genomics is metabolomics: measuring the metabolome of an organism. Data being generated in metabolomics studies are very diverse in nature depending on the design underlying the experiment. Traditionally, variation in measurements is conceptually broken down in systematic variation and noise where the latter contains, e.g. technical variation. There is increasing evidence that this distinction does not hold (or is too simple) for metabolomics data. A more useful distinction is in terms of informative and non-informative variation where informative relates to the problem being studied. In most common methods for analyzing metabolomics (or any other high-dimensional x-omics) data this distinction is ignored thereby severely hampering the results of the analysis. This leads to poorly interpretable models and may even obscure the relevant biological information. We developed a framework from first data analysis principles by explicitly formulating the problem of analyzing metabolomics data in terms of informative and non-informative parts. This framework allows for flexible interactions with the biologists involved in formulating prior knowledge of underlying structures. The basic idea is that the informative parts of the complex metabolomics data are approximated by simple components with a biological meaning, e.g. in terms of metabolic pathways or their regulation. Hence, we termed the framework 'simplivariate models' which constitutes a new way of looking at metabolomics data. The framework is given in its full generality and exemplified with two methods, IDR analysis and plaid modeling, that fit into the framework. Using this strategy of 'divide and conquer', we show that meaningful simplivariate models can be obtained using a real-life microbial metabolomics data set. For instance, one of the simple components contained all the measured intermediates of the Krebs cycle of E. coli. Moreover, these simplivariate models were able to uncover regulatory mechanisms present in the phenylalanine biosynthesis route of E. coli.