The Effects of Demography and Long-Term Selection on the Accuracy of Genomic Prediction with Sequence Data

The use of dense SNPs to predict the genetic value of an individual for a complex trait is often referred to as “genomic selection” in livestock and crops, but is also relevant to human genetics to predict, for example, complex genetic disease risk. The accuracy of prediction depends on the strength of linkage disequilibrium (LD) between SNPs and causal mutations. If sequence data were used instead of dense SNPs, accuracy should increase because causal mutations are present, but demographic history and long-term negative selection also influence accuracy. We therefore evaluated genomic prediction, using simulated sequence in two contrasting populations: one reducing from an ancestrally large effective population size (N_e) to a small one, with high LD common in domestic livestock, while the second had a large constant-sized N_e with low LD similar to that in some human or outbred plant populations. There were two scenarios in each population; causal variants were either neutral or under long-term negative selection. For large N_e, sequence data led to a 22% increase in accuracy relative to ∼600K SNP chip data with a Bayesian analysis and a more modest advantage with a BLUP analysis. This advantage increased when causal variants were influenced by negative selection, and accuracy persisted when 10 generations separated reference and validation populations. However, in the reducing N_e population, there was little advantage for sequence even with negative selection. This study demonstrates the joint influence of demography and selection on accuracy of prediction and improves our understanding of how best to exploit sequence for genomic prediction.     

Non‐zero‐sum neutrality test for the tropical rain forest community using long‐term between‐census data

For community ecologists, “neutral or not?” is a fundamental question, and thus, rejecting neutrality is an important first step before investigating the deterministic processes underlying community dynamics. Hubbell''s neutral model is an important contribution to the exploration of community dynamics, both technically and philosophically. However, the neutrality tests for this model are limited by a lack of statistical power, partly because the zero‐sum assumption of the model is unrealistic. In this study, we developed a neutrality test for local communities that implements non‐zero‐sum community dynamics and determines the number of new species (N _sp) between observations. For the non‐zero‐sum neutrality test, the model distributed the expected N _sp, as calculated by extensive simulations, which allowed us to investigate the neutrality of the observed community by comparing the observed N _sp with distributions of the expected N _sp derived from the simulations. For this comparison, we developed a new “non‐zero‐sum N _sp test,” which we validated by running multiple neutral simulations using different parameter settings. We found that the non‐zero‐sum N _sp test rejected neutrality at a near‐significance level, which justified the validity of our approach. For an empirical test, the non‐zero‐sum N _sp test was applied to real tropical tree communities in Panama and Malaysia. The non‐zero‐sum N _sp test rejected neutrality in both communities when the observation interval was long and N _sp was large. Hence, the non‐zero‐sum N _sp test is an effective way to examine neutrality and has reasonable statistical power to reject the neutral model, especially when the observed N _sp is large. This unique and simple approach is statistically powerful, even though it only employs two temporal sequences of community data. Thus, this test can be easily applied to existing datasets. In addition, application of the test will provide significant benefits for detecting changing biodiversity under climate change and anthropogenic disturbance.     

Unusual mammalian usage of TGA stop codons reveals that sequence conservation need not imply purifying selection

The assumption that conservation of sequence implies the action of purifying selection is central to diverse methodologies to infer functional importance. GC-biased gene conversion (gBGC), a meiotic mismatch repair bias strongly favouring GC over AT, can in principle mimic the action of selection, this being thought to be especially important in mammals. As mutation is GC→AT biased, to demonstrate that gBGC does indeed cause false signals requires evidence that an AT-rich residue is selectively optimal compared to its more GC-rich allele, while showing also that the GC-rich alternative is conserved. We propose that mammalian stop codon evolution provides a robust test case. Although in most taxa TAA is the optimal stop codon, TGA is both abundant and conserved in mammalian genomes. We show that this mammalian exceptionalism is well explained by gBGC mimicking purifying selection and that TAA is the selectively optimal codon. Supportive of gBGC, we observe (i) TGA usage trends are consistent at the focal stop codon and elsewhere (in UTR sequences); (ii) that higher TGA usage and higher TAA→TGA substitution rates are predicted by a high recombination rate; and (iii) across species the difference in TAA <-> TGA substitution rates between GC-rich and GC-poor genes is largest in genomes that possess higher between-gene GC variation. TAA optimality is supported both by enrichment in highly expressed genes and trends associated with effective population size. High TGA usage and high TAA→TGA rates in mammals are thus consistent with gBGC’s predicted ability to “drive” deleterious mutations and supports the hypothesis that sequence conservation need not be indicative of purifying selection. A general trend for GC-rich trinucleotides to reside at frequencies far above their mutational equilibrium in high recombining domains supports the generality of these results.

Is sequence conservation a sign of purifying selection and hence functional importance? This analysis of why mammals use and conserve the most error-prone stop codon suggests not, consistent with GC-biased gene conversion’s predicted ability to “drive” deleterious mutations and supporting the hypothesis that sequence conservation need not be indicative of purifying selection.     

Significance of Population Size on the Fixation of Nonsynonymous Mutations in Genes Under Varying Levels of Selection Pressure

Previous studies observed a higher ratio of divergences at nonsynonymous and synonymous sites (ω = d_N/d_S) in species with a small population size compared to that estimated for those with a large population size. Here we examined the theoretical relationship between ω, effective population size (N_e), and selection coefficient (s). Our analysis revealed that when purifying selection is high, ω of species with small N_e is much higher than that of species with large N_e. However the difference between the two ω reduces with the decline in selection pressure (s → 0). We examined this relationship using primate and rodent genes and found that the ω estimated for highly constrained genes of primates was up to 2.9 times higher than that obtained for their orthologous rodent genes. Conversely, for genes under weak purifying selection the ω of primates was only 17% higher than that of rodents. When tissue specificity was used as a proxy for selection pressure we found that the ω of broadly expressed genes of primates was up to 2.1-fold higher than that of their rodent counterparts and this difference was only 27% for tissue specific genes. Since most of the nonsynonymous mutations in constrained or broadly expressed genes are deleterious, fixation of these mutations is influenced by N_e. This results in a higher ω of these genes in primates compared to those from rodents. Conversely, the majority of nonsynonymous mutations in less-constrained or tissue-specific genes are neutral or nearly neutral and therefore fixation of them is largely independent of N_e, which leads to the similarity of ω in primates and rodents.     

Genetic Variability and Structuring of Arctic Charr (Salvelinus alpinus) Populations in Northern Fennoscandia

Variation in presumably neutral genetic markers can inform us about evolvability, historical effective population sizes and phylogeographic history of contemporary populations. We studied genetic variability in 15 microsatellite loci in six native landlocked Arctic charr (Salvelinus alpinus) populations in northern Fennoscandia, where this species is considered near threatened. We discovered that all populations were genetically highly (mean F _ST ≈ 0.26) differentiated and isolated from each other. Evidence was found for historical, but not for recent population size bottlenecks. Estimates of contemporary effective population size (N _e) ranged from seven to 228 and were significantly correlated with those of historical N _e but not with lake size. A census size (N _C) was estimated to be approximately 300 individuals in a pond (0.14 ha), which exhibited the smallest N _e (i.e. N _e/N _C = 0.02). Genetic variability in this pond and a connected lake is severely reduced, and both genetic and empirical estimates of migration rates indicate a lack of gene flow between them. Hence, albeit currently thriving, some northern Fennoscandian populations appear to be vulnerable to further loss of genetic variability and are likely to have limited capacity to adapt if selection pressures change.     

A century-long genetic record reveals that protist effective population sizes are comparable to those of macroscopic species

Effective population size (N_e) determines the rate of genetic drift and the relative influence of selection over random genetic changes. While free-living protist populations characteristically consist of huge numbers of cells (N), the absence of any estimates of contemporary N_e raises the question whether protist effective population sizes are comparably large. Using microsatellite genotype data of strains derived from revived cysts of the marine dinoflagellate Pentapharsodinium dalei from sections of a sediment record that spanned some 100 years, we present the first estimates of contemporary N_e for a local population in a free-living protist. The estimates of N_e are relatively small, of the order of a few 100 individuals, and thus are similar in magnitude to values of N_e reported for multicellular animals: the implications are that N_e of P. dalei is of many orders of magnitude lower than the number of cells present (N_e/N ∼ 10⁻¹²) and that stochastic genetic processes may be more prevalent in protist populations than previously anticipated.     

Translation Initiation Factors eIF3 and HCR1 Control Translation Termination and Stop Codon Read-Through in Yeast Cells

Translation is divided into initiation, elongation, termination and ribosome recycling. Earlier work implicated several eukaryotic initiation factors (eIFs) in ribosomal recycling in vitro. Here, we uncover roles for HCR1 and eIF3 in translation termination in vivo. A substantial proportion of eIF3, HCR1 and eukaryotic release factor 3 (eRF3) but not eIF5 (a well-defined “initiation-specific” binding partner of eIF3) specifically co-sediments with 80S couples isolated from RNase-treated heavy polysomes in an eRF1-dependent manner, indicating the presence of eIF3 and HCR1 on terminating ribosomes. eIF3 and HCR1 also occur in ribosome- and RNA-free complexes with both eRFs and the recycling factor ABCE1/RLI1. Several eIF3 mutations reduce rates of stop codon read-through and genetically interact with mutant eRFs. In contrast, a slow growing deletion of hcr1 increases read-through and accumulates eRF3 in heavy polysomes in a manner suppressible by overexpressed ABCE1/RLI1. Based on these and other findings we propose that upon stop codon recognition, HCR1 promotes eRF3·GDP ejection from the post-termination complexes to allow binding of its interacting partner ABCE1/RLI1. Furthermore, the fact that high dosage of ABCE1/RLI1 fully suppresses the slow growth phenotype of hcr1Δ as well as its termination but not initiation defects implies that the termination function of HCR1 is more critical for optimal proliferation than its function in translation initiation. Based on these and other observations we suggest that the assignment of HCR1 as a bona fide eIF3 subunit should be reconsidered. Together our work characterizes novel roles of eIF3 and HCR1 in stop codon recognition, defining a communication bridge between the initiation and termination/recycling phases of translation.     

Estimating Effective Population Size from Temporally Spaced Samples with a Novel,Efficient Maximum-Likelihood Algorithm

The effective population size N_e is a key parameter in population genetics and evolutionary biology, as it quantifies the expected distribution of changes in allele frequency due to genetic drift. Several methods of estimating N_e have been described, the most direct of which uses allele frequencies measured at two or more time points. A new likelihood-based estimator NB^ for contemporary effective population size using temporal data is developed in this article. The existing likelihood methods are computationally intensive and unable to handle the case when the underlying N_e is large. This article tries to work around this problem by using a hidden Markov algorithm and applying continuous approximations to allele frequencies and transition probabilities. Extensive simulations are run to evaluate the performance of the proposed estimator NB^, and the results show that it is more accurate and has lower variance than previous methods. The new estimator also reduces the computational time by at least 1000-fold and relaxes the upper bound of N_e to several million, hence allowing the estimation of larger N_e. Finally, we demonstrate how this algorithm can cope with nonconstant N_e scenarios and be used as a likelihood-ratio test to test for the equality of N_e throughout the sampling horizon. An R package “NB” is now available for download to implement the method described in this article.     

Temporal Stability of Genetic Variability and Differentiation in the Three-Spined Stickleback (Gasterosteus aculeatus)

Temporal variation in allele frequencies, whether caused by deterministic or stochastic forces, can inform us about interesting demographic and evolutionary phenomena occurring in wild populations. In spite of the continued surge of interest in the genetics of three-spined stickleback (Gasterosteus aculeatus) populations, little attention has been paid towards the temporal stability of allele frequency distributions, and whether there are consistent differences in effective size (N_e) of local populations. We investigated temporal stability of genetic variability and differentiation in 15 microsatellite loci within and among eight collection sites of varying habitat type, surveyed twice over a six-year time period. In addition, N_es were estimated with the expectation that they would be lowest in isolated ponds, intermediate in larger lakes and largest in open marine sites. In spite of the marked differences in genetic variability and differentiation among the study sites, the temporal differences in allele frequencies, as well as measures of genetic diversity and differentiation, were negligible. Accordingly, the N_e estimates were temporally stable, but tended to be lower in ponds than in lake or marine habitats. Hence, we conclude that allele frequencies in putatively neutral markers in three-spined sticklebacks seem to be temporally stable – at least over periods of few generations – across a wide range of habitat types differing markedly in levels of genetic variability, effective population size and gene flow.     

Repeatability of adaptation in experimental populations of different sizes

The degree to which evolutionary trajectories and outcomes are repeatable across independent populations depends on the relative contribution of selection, chance and history. Population size has been shown theoretically and empirically to affect the amount of variation that arises among independent populations adapting to the same environment. Here, we measure the contribution of selection, chance and history in different-sized experimental populations of the unicellular alga Chlamydomonas reinhardtii adapting to a high salt environment to determine which component of evolution is affected by population size. We find that adaptation to salt is repeatable at the fitness level in medium (N_e = 5 × 10⁴) and large (N_e = 4 × 10⁵) populations because of the large contribution of selection. Adaptation is not repeatable in small (N_e = 5 × 10³) populations because of large constraints from history. The threshold between stochastic and deterministic evolution in this case is therefore between effective population sizes of 10³ and 10⁴. Our results indicate that diversity across populations is more likely to be maintained if they are small. Experimental outcomes in large populations are likely to be robust and can inform our predictions about outcomes in similar situations.     

Coupling Demographic and Genetic Variability from Archived Collections of European Anchovy (Engraulis encrasicolus)

It is well known that temporal fluctuations in small populations deeply influence evolutionary potential. Less well known is whether fluctuations can influence the evolutionary potentials of species with large census sizes. Here, we estimated genetic population parameters from as survey of polymorphic microsatellite DNA loci in archived otoliths from Adriatic European anchovy (Engraulis encrasicolus), a fish with large census sizes that supports numerous local fisheries. Stocks have fluctuated greatly over the past few decades, and the Adriatic fishery collapsed in 1987. Our results show a significant reduction of mean genetic parameters as a consequence of the population collapse. In addition, estimates of effective population size (N_e) are much smaller than those expected in a fishes with large population census sizes (N_c). Estimates of N_e indicate low effective population sizes, even before the population collapse. The ratio N_e/N_e ranged between 10⁻⁶ and 10⁻⁸, indicating a large discrepancy between the anchovy gene pool and population census size. Therefore, anchovy populations may be more vulnerable to fishery effort and environmental change than previously thought.     

Simple life-history traits explain key effective population size ratios across diverse taxa

Effective population size (N_e) controls both the rate of random genetic drift and the effectiveness of selection and migration, but it is difficult to estimate in nature. In particular, for species with overlapping generations, it is easier to estimate the effective number of breeders in one reproductive cycle (N_b) than N_e per generation. We empirically evaluated the relationship between life history and ratios of N_e, N_b and adult census size (N) using a recently developed model (agene) and published vital rates for 63 iteroparous animals and plants. N_b/N_e varied a surprising sixfold across species and, contrary to expectations, N_b was larger than N_e in over half the species. Up to two-thirds of the variance in N_b/N_e and up to half the variance in N_e/N was explained by just two life-history traits (age at maturity and adult lifespan) that have long interested both ecologists and evolutionary biologists. These results provide novel insights into, and demonstrate a close general linkage between, demographic and evolutionary processes across diverse taxa. For the first time, our results also make it possible to interpret rapidly accumulating estimates of N_b in the context of the rich body of evolutionary theory based on N_e per generation.     

The Evolution of Selfing Is Accompanied by Reduced Efficacy of Selection and Purging of Deleterious Mutations

The transition from outcrossing to selfing is predicted to reduce the genome-wide efficacy of selection because of the lower effective population size (N_e) that accompanies this change in mating system. However, strongly recessive deleterious mutations exposed in the homozygous backgrounds of selfers should be under strong purifying selection. Here, we examine estimates of the distribution of fitness effects (DFE) and changes in the magnitude of effective selection coefficients (N_es) acting on mutations during the transition from outcrossing to selfing. Using forward simulations, we investigated the ability of a DFE inference approach to detect the joint influence of mating system and the dominance of deleterious mutations on selection efficacy. We investigated predictions from our simulations in the annual plant Eichhornia paniculata, in which selfing has evolved from outcrossing on multiple occasions. We used range-wide sampling to generate population genomic datasets and identified nonsynonymous and synonymous polymorphisms segregating in outcrossing and selfing populations. We found that the transition to selfing was accompanied by a change in the DFE, with a larger fraction of effectively neutral sites (N_es < 1), a result consistent with the effects of reduced N_e in selfers. Moreover, an increased proportion of sites in selfers were under strong purifying selection (N_es > 100), and simulations suggest that this is due to the exposure of recessive deleterious mutations. We conclude that the transition to selfing has been accompanied by the genome-wide influences of reduced N_e and strong purifying selection against deleterious recessive mutations, an example of purging at the molecular level.     

Local ecological divergence of two closely related stag beetles based on genetic,morphological, and environmental analyses

The process of phenotypic adaptation to the environments is widely recognized. However, comprehensive studies integrating phylogenetic, phenotypic, and ecological approaches to assess this process are scarce. Our study aims to assess whether local adaptation may explain intraspecific differentiation by quantifying multidimensional differences among populations in closely related lucanid species, Platycerus delicatulus and Platycerus kawadai, which are endemic saproxylic beetles in Japan. First, we determined intraspecific analysis units based on nuclear and mitochondrial gene analyses of Platycerus delicatulus and Platycerus kawadai under sympatric and allopatric conditions. Then, we compared differences in morphology and environmental niche between populations (analysis units) within species. We examined the relationship between morphology and environmental niche via geographic distance. P. kawadai was subdivided into the “No introgression” and “Introgression” populations based on mitochondrial COI gene – nuclear ITS region discordance. P. delicatulus was subdivided into “Allopatric” and “Sympatric” populations. Body length differed significantly among the populations of each species. For P. delicatulus, character displacement was suggested. For P. kawadai, the morphological difference was likely caused by geographic distance or genetic divergence rather than environmental differences. The finding showed that the observed mitochondrial–nuclear discordance is likely due to historical mitochondrial introgression following a range of expansion. Our results show that morphological variation among populations of P. delicatulus and P. kawadai reflects an ecological adaptation process based on interspecific interactions, geographic distance, or genetic divergence. Our results will deepen understanding of ecological specialization processes across the distribution and adaptation of species in natural systems.     

Effective population size in eusocial Hymenoptera with worker-produced males

In many eusocial Hymenoptera, a proportion of males are produced by workers. To assess the effect of male production by workers on the effective population size N_e, a general expression of N_e in Hymenoptera with worker-produced males is derived on the basis of the genetic drift in the frequency of a neutral allele. Stochastic simulation verifies that the obtained expression gives a good prediction of N_e under a wide range of conditions. Numerical computation with the expression indicates that worker reproduction generally reduces N_e. The reduction can be serious in populations with a unity or female-biased breeding sex ratio. Worker reproduction may increase N_e in populations with a male-biased breeding sex ratio, only if each laying worker produce a small number of males and the difference of male progeny number among workers is not large. Worker reproduction could be an important cause of the generally lower genetic variation found in Hymenoptera, through its effect on N_e.     

Stop codon read-through of mammalian MTCH2 leading to an unstable isoform regulates mitochondrial membrane potential

Stop codon read-through (SCR) is a process of continuation of translation beyond a stop codon. This phenomenon, which occurs only in certain mRNAs under specific conditions, leads to a longer isoform with properties different from that of the canonical isoform. MTCH2, which encodes a mitochondrial protein that regulates mitochondrial metabolism, was selected as a potential read-through candidate based on evolutionary conservation observed in the proximal region of its 3′ UTR. Here, we demonstrate translational read-through across two evolutionarily conserved, in-frame stop codons of MTCH2 using luminescence- and fluorescence-based assays, and by analyzing ribosome-profiling and mass spectrometry (MS) data. This phenomenon generates two isoforms, MTCH2x and MTCH2xx (single- and double-SCR products, respectively), in addition to the canonical isoform MTCH2, from the same mRNA. Our experiments revealed that a cis-acting 12-nucleotide sequence in the proximal 3′ UTR of MTCH2 is the necessary signal for SCR. Functional characterization showed that MTCH2 and MTCH2x were localized to mitochondria with a long t_1/2 (>36 h). However, MTCH2xx was found predominantly in the cytoplasm. This mislocalization and its unique C terminus led to increased degradation, as shown by greatly reduced t_1/2 (<1 h). MTCH2 read-through–deficient cells, generated using CRISPR-Cas9, showed increased MTCH2 expression and, consistent with this, decreased mitochondrial membrane potential. Thus, double-SCR of MTCH2 regulates its own expression levels contributing toward the maintenance of normal mitochondrial membrane potential.     

Molecular clock in neutral protein evolution

Background

A frequent observation in molecular evolution is that amino-acid substitution rates show an index of dispersion (that is, ratio of variance to mean) substantially larger than one. This observation has been termed the overdispersed molecular clock. On the basis of in silico protein-evolution experiments, Bastolla and coworkers recently proposed an explanation for this observation: Proteins drift in neutral space, and can temporarily get trapped in regions of substantially reduced neutrality. In these regions, substitution rates are suppressed, which results in an overall substitution process that is not Poissonian. However, the simulation method of Bastolla et al. is representative only for cases in which the product of mutation rate μ and population size N_e is small. How the substitution process behaves when μN_e is large is not known.

Results

Here, I study the behavior of the molecular clock in in silico protein evolution as a function of mutation rate and population size. I find that the index of dispersion decays with increasing μN_e, and approaches 1 for large μN_e . This observation can be explained with the selective pressure for mutational robustness, which is effective when μN_e is large. This pressure keeps the population out of low-neutrality traps, and thus steadies the ticking of the molecular clock.

Conclusions

The molecular clock in neutral protein evolution can fall into two distinct regimes, a strongly overdispersed one for small μN_e, and a mostly Poissonian one for large μN_e. The former is relevant for the majority of organisms in the plant and animal kingdom, and the latter may be relevant for RNA viruses.

     

TYPE I ERROR RATES FOR TESTING GENETIC DRIFT WITH PHENOTYPIC COVARIANCE MATRICES: A SIMULATION STUDY

Studies of evolutionary divergence using quantitative genetic methods are centered on the additive genetic variance–covariance matrix ( G ) of correlated traits. However, estimating G properly requires large samples and complicated experimental designs. Multivariate tests for neutral evolution commonly replace average G by the pooled phenotypic within‐group variance–covariance matrix ( W ) for evolutionary inferences, but this approach has been criticized due to the lack of exact proportionality between genetic and phenotypic matrices. In this study, we examined the consequence, in terms of type I error rates, of replacing average G by W in a test of neutral evolution that measures the regression slope between among‐population variances and within‐population eigenvalues (the Ackermann and Cheverud [AC] test) using a simulation approach to generate random observations under genetic drift. Our results indicate that the type I error rates for the genetic drift test are acceptable when using W instead of average G when the matrix correlation between the ancestral G and P is higher than 0.6, the average character heritability is above 0.7, and the matrices share principal components. For less‐similar G and P matrices, the type I error rates would still be acceptable if the ratio between the number of generations since divergence and the effective population size (t/N_e) is smaller than 0.01 (large populations that diverged recently). When G is not known in real data, a simulation approach to estimate expected slopes for the AC test under genetic drift is discussed.     

The major 5' determinant in stop codon read-through involves two adjacent adenines

The aim of this approach was to identify the major determinants, located at the 5′ end of the stop codon, that modulate translational read-through in Saccharomyces cerevisiae. We developed a library of oligonucleotides degenerate at the six positions immediately upstream of the termination codon, cloned in the ADE2 reporter gene. Variations at these positions modulated translational read-through efficiency ~16-fold. The major effect was imposed by the two nucleotides immediately upstream of the stop codon. We showed that this effect was neither mediated by the last amino acid residues present in the polypeptide chain nor by the tRNA present in the ribosomal P site. We propose that the mRNA structure, depending on the nucleotides in the P site, is the main 5′ determinant of read-through efficiency.