Predicting the direction of phenotypic difference.

Predicting phenotypes from genomic data is a key goal in genetics, but for most complex phenotypes, predictions are hampered by incomplete genotype-to-phenotype mapping. Here, we describe a more attainable approach than quantitative predictions, which is aimed at qualitatively predicting phenotypic differences. Despite incomplete genotype-to-phenotype mapping, we show that it is relatively easy to determine which of two individuals has a greater phenotypic value. This question is central in many scenarios, e.g., comparing disease risk between individuals, the yield of crop strains, or the anatomy of extinct vs extant species. To evaluate prediction accuracy, i.e., the probability that the individual with the greater predicted phenotype indeed has a greater phenotypic value, we developed an estimator of the ratio between known and unknown effects on the phenotype. We evaluated prediction accuracy using human data from tens of thousands of individuals from either the same family or the same population, as well as data from different species. We found that, in many cases, even when only a small fraction of the loci affecting a phenotype is known, the individual with the greater phenotypic value can be identified with over 90% accuracy. Our approach also circumvents some of the limitations in transferring genetic association results across populations. Overall, we introduce an approach that enables accurate predictions of key information on phenotypes - the direction of phenotypic difference - and suggest that more phenotypic information can be extracted from genomic data than previously appreciated.

The determinants of proxy treadmilling in evolutionary models of reliable signals.

Identifying the conditions of proxy treadmilling is crucial for determining whether reliable signals can persist over time. I present a framework that maps evolutionary models of reliable signals according to their assumptions regarding the effects of Goodhart's law. This framework can explain the contrasting outcomes of different modelling approaches, and identify in which models proxy treadmilling is expected to occur.

DORA: an interactive map for the visualization and analysis of ancient human DNA and associated data.

The ability to sequence ancient genomes has revolutionized the way we study evolutionary history by providing access to the most important aspect of evolution-time. Until recently, studying human demography, ecology, biology, and history using population genomic inference relied on contemporary genomic datasets. Over the past decade, the availability of human ancient DNA (aDNA) has increased rapidly, almost doubling every year, opening the way for spatiotemporal studies of ancient human populations. However, the multidimensionality of aDNA, with genotypes having temporal, spatial and genomic coordinates, and integrating multiple sources of data, poses a challenge for developing meta-analyses pipelines. To address this challenge, we developed a publicly-available interactive tool, DORA, which integrates multiple data types, genomic and non-genomic, in a unified interface. This web-based tool enables browsing sample metadata alongside additional layers of information, such as population structure, climatic data, and unpublished samples. Users can perform analyses on genotypes of these samples, or export sample subsets for external analyses. DORA integrates analyses and visualizations in a single intuitive interface, resolving the technical issues of combining datasets from different sources and formats, and allowing researchers to focus on the scientific questions that can be addressed through analysis of aDNA datasets.

Rescue by gene swamping as a gene drive deployment strategy.

Gene drives are genetic constructs that can spread deleterious alleles with potential application to population suppression of harmful species. As gene drives can potentially spill over to other populations or species, control measures and fail-safe strategies must be considered. Gene drives can generate a rapid change in the population's genetic composition, leading to substantial demographic decline, processes that are expected to occur at a similar timescale during gene drive spread. We developed a gene drive model that combines evolutionary and demographic dynamics in a two-population setting. The model demonstrates how feedback between these dynamics generates additional outcomes to those generated by the evolutionary dynamics alone. We identify an outcome of particular interest where short-term suppression of the target population is followed by gene swamping and loss of the gene drive. This outcome can prevent spillover and is robust to the evolution of resistance, suggesting it may be suitable as a fail-safe strategy for gene drive deployment.

Incorporating ecology into gene drive modelling.

Gene drive technology, in which fast-spreading engineered drive alleles are introduced into wild populations, represents a promising new tool in the fight against vector-borne diseases, agricultural pests and invasive species. Due to the risks involved, gene drives have so far only been tested in laboratory settings while their population-level behaviour is mainly studied using mathematical and computational models. The spread of a gene drive is a rapid evolutionary process that occurs over timescales similar to many ecological processes. This can potentially generate strong eco-evolutionary feedback that could profoundly affect the dynamics and outcome of a gene drive release. We, therefore, argue for the importance of incorporating ecological features into gene drive models. We describe the key ecological features that could affect gene drive behaviour, such as population structure, life-history, environmental variation and mode of selection. We review previous gene drive modelling efforts and identify areas where further research is needed. As gene drive technology approaches the level of field experimentation, it is crucial to evaluate gene drive dynamics, potential outcomes, and risks realistically by including ecological processes.

Knockout of DDM1 in Physcomitrium patens disrupts DNA methylation with a minute effect on transposon regulation and development.

The Snf2 chromatin remodeler, DECREASE IN DNA METHYLATION 1 (DDM1) facilitates DNA methylation. In flowering plants, DDM1 mediates methylation in heterochromatin, which is targeted primarily by MET1 and CMT methylases and is necessary for silencing transposons and for proper development. DNA methylation mechanisms evolved throughout plant evolution, whereas the role of DDM1 in early terrestrial plants remains elusive. Here, we studied the function of DDM1 in the moss, Physcomitrium (Physcomitrella) patens, which has robust DNA methylation that suppresses transposons and is mediated by a MET1, a CMT, and a DNMT3 methylases. To elucidate the role of DDM1 in P. patens, we have generated a knockout mutant and found DNA methylation to be strongly disrupted at any of its sequence contexts. Symmetric CG and CHG sequences were affected stronger than asymmetric CHH sites. Furthermore, despite their separate targeting mechanisms, CG (MET) and CHG (CMT) methylation were similarly depleted by about 75%. CHH (DNMT3) methylation was overall reduced by about 25%, with an evident hyper-methylation activity within lowly-methylated euchromatic transposon sequences. Despite the strong hypomethylation effect, only a minute number of transposons were transcriptionally activated in Ppddm1. Finally, Ppddm1 was found to develop normally throughout the plant life cycle. These results demonstrate that DNA methylation is strongly dependent on DDM1 in a non-flowering plant; that DDM1 is required for plant-DNMT3 (CHH) methylases, though to a lower extent than for MET1 and CMT enzymes; and that distinct and separate methylation pathways (e.g. MET1-CG and CMT-CHG), can be equally regulated by the chromatin and that DDM1 plays a role in it. Finally, our data suggest that the biological significance of DDM1 in terms of transposon regulation and plant development, is species dependent.

DNA methylation mutants in Physcomitrella patens elucidate individual roles of CG and non-CG methylation in genome regulation.

Cytosine (DNA) methylation in plants regulates the expression of genes and transposons. While methylation in plant genomes occurs at CG, CHG, and CHH sequence contexts, the comparative roles of the individual methylation contexts remain elusive. Here, we present Physcomitrella patens as the second plant system, besides Arabidopsis thaliana, with viable mutants with an essentially complete loss of methylation in the CG and non-CG contexts. In contrast to A. thaliana, P. patens has more robust CHH methylation, similar CG and CHG methylation levels, and minimal cross-talk between CG and non-CG methylation, making it possible to study context-specific effects independently. Our data found CHH methylation to act in redundancy with symmetric methylation in silencing transposons and to regulate the expression of CG/CHG-depleted transposons. Specific elimination of CG methylation did not dysregulate transposons or genes. In contrast, exclusive removal of non-CG methylation massively up-regulated transposons and genes. In addition, comparing two exclusively but equally CG- or CHG-methylated genomes, we show that CHG methylation acts as a greater transcriptional regulator than CG methylation. These results disentangle the transcriptional roles of CG and non-CG, as well as symmetric and asymmetric methylation in a plant genome, and point to the crucial role of non-CG methylation in genome regulation.

Contiguous and stochastic CHH methylation patterns of plant DRM2 and CMT2 revealed by single-read methylome analysis.

Cytosine methylome data is commonly generated through next-generation sequencing, with analyses averaging methylation states of individual reads. We propose an alternative method of analysing single-read methylome data. Using this method, we identify patterns relating to the mechanism of two plant non-CG-methylating enzymes, CMT2 and DRM2. CMT2-methylated regions show higher stochasticity, while DRM2-methylated regions have higher variation among cells. Based on these patterns, we develop a classifier that predicts enzyme activity in different species and tissues. To facilitate further single-read analyses, we develop a genome browser, SRBrowse, optimised for visualising and analysing sequencing data at single-read resolution.

DNA methylation is maintained with high fidelity in the honey bee germline and exhibits global non-functional fluctuations during somatic development.

BACKGROUND: DNA methylation of active genes, also known as gene body methylation, is found in many animal and plant genomes. Despite this, the transcriptional and developmental role of such methylation remains poorly understood. Here, we explore the dynamic range of DNA methylation in honey bee, a model organism for gene body methylation. RESULTS: Our data show that CG methylation in gene bodies globally fluctuates during honey bee development. However, these changes cause no gene expression alterations. Intriguingly, despite the global alterations, tissue-specific CG methylation patterns of complete genes or exons are rare, implying robust maintenance of genic methylation during development. Additionally, we show that CG methylation maintenance fluctuates in somatic cells, while reaching maximum fidelity in sperm cells. Finally, unlike universally present CG methylation, we discovered non-CG methylation specifically in bee heads that resembles such methylation in mammalian brain tissue. CONCLUSIONS: Based on these results, we propose that gene body CG methylation can oscillate during development if it is kept to a level adequate to preserve function. Additionally, our data suggest that heightened non-CG methylation is a conserved regulator of animal nervous systems.

Publisher Correction: RdDM-independent de novo and heterochromatin DNA methylation by plant CMT and DNMT3 orthologs.

The original version of this Article contained an error in Fig. 5, in which the evolutionary origin of DRM2 was incorrectly placed prior to the divergence between gymnosperms and angiosperms . The correct evolutionary origin of DRM2 should be in angiosperms. In addition, in the "Percent methylation change" section of the Methods, Equation 1 was incorrect. This has been corrected in both the PDF and HTML versions of the Article.An amendment to this paper has been published and can be accessed via a link at the top of the paper.

RdDM-independent de novo and heterochromatin DNA methylation by plant CMT and DNMT3 orthologs.

To properly regulate the genome, cytosine methylation is established by animal DNA methyltransferase 3 s (DNMT3s). While altered DNMT3 homologs, Domains rearranged methyltransferases (DRMs), have been shown to establish methylation via the RNA directed DNA methylation (RdDM) pathway, the role of true-plant DNMT3 orthologs remains elusive. Here, we profile de novo (RPS transgene) and genomic methylation in the basal plant, Physcomitrella patens, mutated in each of its PpDNMTs. We show that PpDNMT3b mediates CG and CHH de novo methylation, independently of PpDRMs. Complementary de novo CHG methylation is specifically mediated by the CHROMOMETHYLASE, PpCMT. Intragenomically, PpDNMT3b functions preferentially within heterochromatin and is affected by PpCMT. In comparison, PpDRMs target active-euchromatic transposons. Overall, our data resolve how DNA methylation in plants can be established in heterochromatin independently of RdDM; suggest that DRMs have emerged to target euchromatin; and link DNMT3 loss in angiosperms to the initiation of heterochromatic CHH methylation by CMT2.

Applying the handicap principle to biofilms: condition-dependent signalling in Bacillus subtilis microbial communities.

Bacteria in nature often reside in differentiated communities termed biofilms. These communities, which are composed of a number of functionally-distinct cell types, are an interesting example of division of labour in microbes, and as such have been used as a system to study the evolution of cooperation. The structured population of the biofilm also plays a critical role in the persistence of infections, and biofouling of medical and industrial devices. Biofilm formation involves several stages of differentiation, which are mediated by extracellular factors secreted by cells composing the biofilm. The developmental model of biofilm formation describes this process mechanistically: specific subpopulations of cells synthesize signals within the biofilm, and promote the differentiation of other subpopulations. The handicap principle suggests that signals function because they provide reliable information regarding the state of the signaller; here, we apply the handicap principle to signalling among cells composing Bacillus subtilis biofilms, emphasizing the perspective of secreted factors as sources of information rather than solely as mediators of development. Such information could facilitate competition among phenotypically-similar cells composing the biofilm, affecting local organizational patterns within defined subpopulations.

An individual-level selection model for the apparent altruism exhibited by cellular slime moulds.

In Dictyostelium discoideum, cells that become part of the stalk or basal disc display behaviour that can be interpreted as altruistic. Atzmony et al. (Curr Sci 72:142-145, 1997) had hypothesised that this behaviour could be the outcome of an adaptive strategy based on differing intrinsic quality as reflected by phenotypes that indicate differences in potential for survival and reproduction, followed by intercellular competition among amoebae of differing qualities. Low-quality amoebae would have a poor chance of succeeding in the competition to form spores; they could enhance their chances of survival by adopting a presumptive stalk strategy. Here we extend the hypothesis by making use of recent findings. Our approach is based on the view that an evolutionary explanation for the apparent altruism of stalk cells in D. discoideum must apply broadly to other cellular slime moulds (CSMs) that exhibit stalk cell death. Further, it must be capable of being modified to cover social behaviour in CSMs with an extracellular stalk, as well as in sorocarpic amoebae whose stalk cells are viable. With regard to D. discoideum, we suggest that (a) differentiation-inducing factor, thought of as a signal that inhibits amoebae from forming spores and induces them to differentiate into basal disc cells, is better viewed as a mediator of competition among post-aggregation amoebae and (b) the products of the 'recognition genes', tgrB and tgrC, allow an amoeba to assess its quality relative to that of its neighbours and move to a position within the aggregate that optimises its reproductive fitness. From this perspective, all cells behave in a manner that is 'selfish' rather than 'altruistic', albeit with different expectations of success.

Why are neurotransmitters neurotoxic? An evolutionary perspective.

In the CNS, minor changes in the concentration of neurotransmitters such as glutamate or dopamine can lead to neurodegenerative diseases. We present an evolutionary perspective on the function of neurotransmitter toxicity in the CNS. We hypothesize that neurotransmitters are selected because of their toxicity, which serves as a test of neuron quality and facilitates the selection of neuronal pathways. This perspective may offer additional explanations for the reduction of neurotransmitter concentration in the CNS with age, and suggest an additional role for the blood-brain barrier. It may also suggest a connection between the specific toxicity of the neurotransmitters released in a specific region of the CNS, and elucidate their role as chemicals that are optimal for testing the quality of cells in that region.