Testing for genetic assimilation with phylogenetic comparative analysis: Conceptual, methodological, and statistical considerations

Genetic assimilation is a process that leads to reduced phenotypic plasticity during adaptation to novel conditions, a potentially important phenomenon under global environmental change. Null expectations when testing for genetic assimilation, however, are not always clear. For instance, the statistical artifact of regression to the mean could bias us towards detecting genetic assimilation when it has not occurred. Likewise, the specific mechanism underlying plasticity expression may affect null expectations under neutral evolution. We used macroevolutionary numerical simulations to examine both of these important issues and their interaction, varying whether or not plasticity evolves, the evolutionary mechanism, trait measurement error, and experimental design. We also modified an existing reaction norm correction method to account for phylogenetic non-independence. We found: 1) regression to the mean is pervasive and can generate spurious support for genetic assimilation; 2) experimental design and post-hoc correction can minimize this spurious effect; and 3) neutral evolution can produce patterns consistent with genetic assimilation without constraint or selection, depending on the mechanism of plasticity expression. Additionally, we re-analyzed published macroevolutionary data supporting genetic assimilation, and found that support was lost after proper correction. Considerable caution is thus required whenever investigating genetic assimilation and reaction norm evolution at macroevolutionary scales.

Spatial structure governs the mode of tumour evolution

Characterizing the mode—the way, manner or pattern—of evolution in tumours is important for clinical forecasting and optimizing cancer treatment. Sequencing studies have inferred various modes, including branching, punctuated and neutral evolution, but it is unclear why a particular pattern predominates in any given tumour. Here we propose that tumour architecture is key to explaining the variety of observed genetic patterns. We examine this hypothesis using spatially explicit population genetics models and demonstrate that, within biologically relevant parameter ranges, different spatial structures can generate four tumour evolutionary modes: rapid clonal expansion, progressive diversification, branching evolution and effectively almost neutral evolution. Quantitative indices for describing and classifying these evolutionary modes are presented. Using these indices, we show that our model predictions are consistent with empirical observations for cancer types with corresponding spatial structures. The manner of cell dispersal and the range of cell–cell interactions are found to be essential factors in accurately characterizing, forecasting and controlling tumour evolution.

Mixture Density Regression reveals frequent recent adaptation in the human genome

How much genome differences between species reflect neutral or adaptive evolution is a central question in evolutionary genomics. In humans and other mammals, the prevalence of adaptive versus neutral genomic evolution has proven particularly difficult to quantify. The difficulty notably stems from the highly heterogenous organization of mammalian genomes at multiple levels (functional sequence density, recombination, etc.) that complicates the interpretation and distinction of adaptive vs. neutral evolution signals. Here, we introduce Mixture Density Regressions (MDRs) for the study of the determinants of recent adaptation in the human genome. MDRs provide a flexible regression model based on multiple Gaussian distributions. We use MDRs to model the association between recent selection signals and multiple genomic factors likely to affect positive selection, if the latter was common enough in the first place to generate these associations. We find that a MDR model with two Gaussian distributions provides an excellent fit to the genome-wide distribution of a common sweep summary statistic (iHS), with one of the two distributions likely capturing the positively selected component of the genome. We further find several factors associated with recent adaptation, including the recombination rate, the density of regulatory elements in immune cells and testis, GC-content, gene expression in immune cells, the density of mammal-wide conserved elements, and the distance to the nearest virus-interacting gene. These results support that strong positive selection was relatively common in recent human evolution and highlight MDRs as a powerful tool to make sense of signals of recent genomic adaptation.

Balancing Selection in Structured Populations of Three-Spined Sticklebacks

Balancing selection describes evolutionary processes that maintain genetic diversity. To date, the number of impacted genes and underlying biological functions remain elusive. Using 60 three-spined stickleback genomes (Gasterosteus aculeatus) from five recently diverged lake-river population-pairs, we performed genome-wide scans across two levels of organization: population-pairs and populations. We overlapped Tajima’s D and Watterson’s estimator metrics and verified signals with additional summary statistics, and evaluated alternative explanations: neutral evolution, population structure, associated overdominance, or demographic change. Candidate windows exhibiting signals of balancing selection spanned 2.31% (population-pair) and 3.10% (population) of the autosomes. These candidate windows had extended linkage disequilibrium and were enriched in intergenic and non-synonymous SNPs. We identified 715 (population-pair) and 1,010 (population) candidate genes under balancing selection. Importantly, using conservative thresholds, we found a small proportion of candidate genes overlapped with highly differentiated loci or regions of potential associated overdominance. There was little evidence of confounding effects originating from demographic change. Overall, candidate genes under balancing selection were associated with functions related to interactions with the environment (olfaction and receptor signalling pathways). Our results demonstrate selection that maintains standing genetic variation is common and evolves in response to local environmental pressures, playing an important role in adaptation.

Maintenance of copy number variation at the human salivary agglutinin gene (DMBT1) by balancing selection driven by host-microbe interactions

Most genetic variation in humans occurs in a pattern consistent with neutral evolution, but a small subset is maintained by balancing selection. Identifying loci under balancing selection is important not only for understanding the processes explaining variation in the genome, but also to identify loci with alleles that affect response to the environment and disease. Several genome scans using genetic variation data have identified the 5-prime end of the DMBT1 gene as a region undergoing balancing selection. DMBT1 encodes the pattern-recognition glycoprotein DMBT1, also known as SALSA, gp340 or salivary agglutinin. It binds to a wide variety of pathogens through a tandemly-arranged scavenger receptor cysteine-rich (SRCR) domain, with the number of SRCR domains varying in humans. Here we use expression analysis, linkage in pedigrees, and long range single transcript sequencing, to show that the signal of balancing selection is driven by one haplotype usually carrying shorter SRCR repeats, and another usually carrying a longer SRCR repeat, within the coding region of DMBT1. The DMBT1 protein size isoform encoded by a shorter SRCR domain repeat allele showed complete loss of binding of a cariogenic and invasive Streptococcus mutans strain in contrast to the long SRCR allele. Taken together, our results suggest that balancing selection at DMBT1 is due to host-microbe interactions of encoded SRCR tandem repeat alleles.

The length scale of multivalent interactions is evolutionarily conserved in fungal and vertebrate phase-separating proteins

One key feature of proteins that form liquid droplets by phase separation inside a cell is multivalency—the presence of multiple sites that mediate interactions with other proteins. We know little about the variation of multivalency on evolutionary time scales. Here, we investigated the long-term evolution (∼600 million years) of multivalency in fungal mRNA decapping subunit 2 protein (Dcp2), and in the FET protein family. We found that multivalency varies substantially among the orthologs of these proteins. However, evolution has maintained the length scale at which sequence motifs that enable protein-protein interactions occur. That is, the total number of such motifs per hundred amino acids is higher and less variable than expected by neutral evolution. To help explain this evolutionary conservation, we developed a conformation classifier using machine-learning algorithms. This classifier demonstrates that disordered segments in Dcp2 and FET proteins tend to adopt compact conformations, which is necessary for phase separation. Thus, the evolutionary conservation we detected may help proteins preserve the ability to undergo phase separation. Altogether, our study reveals that the length scale of multivalent interactions is an evolutionarily conserved feature of two classes of phase-separating proteins in fungi and vertebrates.

Pig genome functional annotation enhances the biological interpretation of complex traits and human disease

The functional annotation of livestock genomes is crucial for understanding the molecular mechanisms that underpin complex traits of economic importance, adaptive evolution and comparative genomics. Here, we provide the most comprehensive catalogue to date of regulatory elements in the pig (Sus scrofa) by integrating 223 epigenomic and transcriptomic data sets, representing 14 biologically important tissues. We systematically describe the dynamic epigenetic landscape across tissues by functionally annotating 15 different chromatin states and defining their tissue-specific regulatory activities. We demonstrate that genomic variants associated with complex traits and adaptive evolution in pig are significantly enriched in active promoters and enhancers. Furthermore, we reveal distinct tissue-specific regulatory selection between Asian and European pig domestication processes. Compared with human and mouse epigenomes, we show that porcine regulatory elements are more conserved in DNA sequence, under both rapid and slow evolution, than those under neutral evolution across pig, mouse, and human. Finally, we provide biological insights on tissue-specific regulatory conservation, and by integrating 47 human genome-wide association studies, we demonstrate that, depending on the traits, mouse or pig might be more appropriate biomedical models for different complex traits and diseases.

Insertions and deletions in the RNA sequence–structure map

Genotype–phenotype maps link genetic changes to their fitness effect and are thus an essential component of evolutionary models. The map between RNA sequences and their secondary structures is a key example and has applications in functional RNA evolution. For this map, the structural effect of substitutions is well understood, but models usually assume a constant sequence length and do not consider insertions or deletions. Here, we expand the sequence–structure map to include single nucleotide insertions and deletions by using the RNAshapes concept. To quantify the structural effect of insertions and deletions, we generalize existing definitions for robustness and non-neutral mutation probabilities. We find striking similarities between substitutions, deletions and insertions: robustness to substitutions is correlated with robustness to insertions and, for most structures, to deletions. In addition, frequent structural changes after substitutions also tend to be common for insertions and deletions. This is consistent with the connection between energetically suboptimal folds and possible structural transitions. The similarities observed hold both for genotypic and phenotypic robustness and mutation probabilities, i.e. for individual sequences and for averages over sequences with the same structure. Our results could have implications for the rate of neutral and non-neutral evolution.