Genetic Properties Influencing the Evolvability of Gene Expression

Functional and structural profiles of GST gene family from three Populus species reveal the sequence-function decoupling of orthologous genes

A common assumption in comparative genomics is that orthologous genes are functionally more similar than paralogous genes. However, the validity of this assumption needs to be assessed using robust experimental data. We conducted tissue-specific gene expression and protein function analyses of orthologous groups within the glutathione S-transferase (GST) gene family in three closely related Populus species: Populus trichocarpa, Populus euphratica and Populus yatungensis. This study identified 21 GST orthologous groups in the three Populus species. Although the sequences of the GST orthologous groups were highly conserved, the divergence in enzymatic functions was prevalent. Through site-directed mutagenesis of orthologous proteins, this study revealed that nonsynonymous substitutions at key amino acid sites played an important role in the divergence of enzymatic functions. In particular, a single amino acid mutation (Arg39→Trp39) contributed to P. euphratica PeGSTU30 possessing high enzymatic activity via increasing the hydrophobicity of the active cavity. This study provided experimental evidence showing that orthologues belonging to the gene family have functional divergences. The nonsynonymous substitutions at a few amino acid sites resulted in functional divergence of the orthologous genes. Our findings provide new insights into the evolution of orthologous genes in closely related species.

Old Trade, New Tricks: Insights into the Spontaneous Mutation Process from the Partnering of Classical Mutation Accumulation Experiments with High-Throughput Genomic Approaches

Mutations spawn genetic variation which, in turn, fuels evolution. Hence, experimental investigations into the rate and fitness effects of spontaneous mutations are central to the study of evolution. Mutation accumulation (MA) experiments have served as a cornerstone for furthering our understanding of spontaneous mutations for four decades. In the pregenomic era, phenotypic measurements of fitness-related traits in MA lines were used to indirectly estimate key mutational parameters, such as the genomic mutation rate, new mutational variance per generation, and the average fitness effect of mutations. Rapidly emerging next-generating sequencing technology has supplanted this phenotype-dependent approach, enabling direct empirical estimates of the mutation rate and a more nuanced understanding of the relative contributions of different classes of mutations to the standing genetic variation. Whole-genome sequencing of MA lines bears immense potential to provide a unified account of the evolutionary process at multiple levels-the genetic basis of variation, and the evolutionary dynamics of mutations under the forces of selection and drift. In this review, we have attempted to synthesize key insights into the spontaneous mutation process that are rapidly emerging from the partnering of classical MA experiments with high-throughput sequencing, with particular emphasis on the spontaneous rates and molecular properties of different mutational classes in nuclear and mitochondrial genomes of diverse taxa, the contribution of mutations to the evolution of gene expression, and the rate and stability of transgenerational epigenetic modifications. Future advances in sequencing technologies will enable greater species representation to further refine our understanding of mutational parameters and their functional consequences.

Induced mutations alter patterns of quantitative variation, phenotypic integration, and plasticity to elevated CO2 in Arabidopsis thaliana

A key step toward predicting responses to climate change is characterizing genetic variation in populations. While short-term responses will likely be shaped by currently available genetic variation, longer-term evolutionary responses will depend on the supply of novel variation by, ultimately, mutation. Studying mutational contributions to phenotypic variation can provide insights into the extent of potential variation on which selection may operate in future human-altered environments. Here we used the chemical mutagen ethyl methanesulfonate (EMS) to explore mutational contributions to phenotypic variation, integration, and plasticity to elevated carbon dioxide (eCO₂) in three accessions of Arabidopsis thaliana. We found that (1) mutagenesis increased broad-sense heritabilities and variation in plasticity to eCO₂ (genotype by environment interactions); (2) mutational effects varied among the three genetic backgrounds; (3) induced mutations had non-random (biased) effects on patterns of phenotypic integration. To our knowledge, this is the first study to address the effects of chemically induced mutations on phenotypic plasticity to eCO₂ in a model plant. We discuss our results in light of emerging insights from theoretical and empirical quantitative genetics, suggest potential avenues of research, and identify approaches that may help advance our understanding of climate-driven evolution in plants.

Hierarchical Assessment of Mutation Properties in Daphnia magna

Understanding the context-dependence of spontaneous mutations is crucial to predicting evolutionary trajectories. In this experiment, the impact of genetic background and trait-type on mutational susceptibility was investigated. Mutant and non-mutant lines of six unique genotypes from two populations of Daphnia magna were phenotypically assayed using a common-garden experiment. Morphological, life-history, and behavioral traits were measured and estimates of the mutation parameters were generated. The mutation parameters varied between the populations and among genotypes, suggesting differential susceptibility to mutation depending upon genomic background. Traits also varied in their susceptibility to mutation with behavioral traits evolving more rapidly than life-history and morphological traits. These results may reflect the unique selection histories of these populations.

Formation of dominant mode by evolution in biological systems

A reduction in high-dimensional phenotypic states to a few degrees of freedom is essential to understand biological systems. Here, we show evolutionary robustness causes such reduction which restricts possible phenotypic changes in response to a variety of environmental conditions. First, global protein expression changes in Escherichia coli after various environmental perturbations were shown to be proportional across components, across different types of environmental conditions. To examine if such dimension reduction is a result of evolution, we analyzed a cell model-with a huge number of components, that reproduces itself via a catalytic reaction network-and confirmed that common proportionality in the concentrations of all components is shaped through evolutionary processes. We found that the changes in concentration across all components in response to environmental and evolutionary changes are constrained to the changes along a one-dimensional major axis, within a huge-dimensional state space. On the basis of these observations, we propose a theory in which such constraints in phenotypic changes are achieved both by evolutionary robustness and plasticity and formulate this proposition in terms of dynamical systems. Accordingly, broad experimental and numerical results on phenotypic changes caused by evolution and adaptation are coherently explained.

Expression properties exhibit correlated patterns with the fate of duplicated genes, their divergence, and transcriptional plasticity in Saccharomycotina

Gene duplication is an important source of novelties and genome complexity. What genes are preserved as duplicated through long evolutionary times can shape the evolution of innovations. Identifying factors that influence gene duplicability is therefore an important aim in evolutionary biology. Here, we show that in the yeast Saccharomyces cerevisiae the levels of gene expression correlate with gene duplicability, its divergence, and transcriptional plasticity. Genes that were highly expressed before duplication are more likely to be preserved as duplicates for longer evolutionary times and wider phylogenetic ranges than genes that were lowly expressed. Duplicates with higher expression levels exhibit greater divergence between their gene copies. Duplicates that exhibit higher expression divergence are those enriched for TATA-containing promoters. These duplicates also show transcriptional plasticity, which seems to be involved in the origin of adaptations to environmental stresses in yeast. While the expression properties of genes strongly affect their duplicability, divergence and transcriptional plasticity are enhanced after gene duplication. We conclude that highly expressed genes are more likely to be preserved as duplicates due to their promoter architectures, their greater tolerance to expression noise, and their ability to reduce the noise-plasticity conflict.

Network Architecture and Mutational Sensitivity of the C. elegans Metabolome

A fundamental issue in evolutionary systems biology is understanding the relationship between the topological architecture of a biological network, such as a metabolic network, and the evolution of the network. The rate at which an element in a metabolic network accumulates genetic variation via new mutations depends on both the size of the mutational target it presents and its robustness to mutational perturbation. Quantifying the relationship between topological properties of network elements and the mutability of those elements will facilitate understanding the variation in and evolution of networks at the level of populations and higher taxa. We report an investigation into the relationship between two topological properties of 29 metabolites in the C. elegans metabolic network and the sensitivity of those metabolites to the cumulative effects of spontaneous mutation. The correlations between measures of network centrality and mutability are not statistically significant, but several trends point toward a weak positive association between network centrality and mutational sensitivity. There is a small but significant negative association between the mutational correlation of a pair of metabolites (r_M) and the shortest path length between those metabolites. Positive association between the centrality of a metabolite and its mutational heritability is consistent with centrally-positioned metabolites presenting a larger mutational target than peripheral ones, and is inconsistent with centrality conferring mutational robustness, at least in toto. The weakness of the correlation between r_M and the shortest path length between pairs of metabolites suggests that network locality is an important but not overwhelming factor governing mutational pleiotropy. These findings provide necessary background against which the effects of other evolutionary forces, most importantly natural selection, can be interpreted.

CpG island composition differences are a source of gene expression noise indicative of promoter responsiveness

BACKGROUND

Population phenotypic variation can arise from genetic differences between individuals, or from cellular heterogeneity in an isogenic group of cells or organisms. The emergence of gene expression differences between genetically identical cells is referred to as gene expression noise, the sources of which are not well understood.

RESULTS

In this work, by studying gene expression noise between multiple cell lineages and mammalian species, we find consistent evidence of a role for CpG islands as sources of gene expression noise. Variation in noise among CpG island promoters can be partially attributed to differences in island size, in which short islands have noisier gene expression. Building on these findings, we investigate the potential for short CpG islands to act as fast response elements to environmental stimuli. Specifically, we find that these islands are enriched amongst primary response genes in SWI/SNF-independent stimuli, suggesting that expression noise is an indicator of promoter responsiveness.

CONCLUSIONS

Thus, through the integration of single-cell RNA expression profiling, chromatin landscape and temporal gene expression dynamics, we have uncovered a role for short CpG island promoters as fast response elements.

Evaluation of functionality for serine and threonine phosphorylation with different evolutionary ages in human and mouse

BACKGROUND

Rapid evolution of phosphorylation sites could provide raw materials of natural selection to fit the environment by rewiring the regulation of signal pathways. However, a large part of phosphorylation sites was suggested to be non-functional. Although the new-arising phosphorylation sites with little functional implications prevailed in fungi, the evolutionary performance of vertebrate phosphorylation sites remained elusive.

RESULTS

In this study, we evaluated the functionality of human and mouse phosphorylation sites by dividing them into old, median and young age groups based on the phylogeny of vertebrates. We found the sites in the old group were more likely to be functional and involved in signaling pathways than those in the young group. A smaller proportion of sites in the young group originated from aspartate/glutamate, which could restore the ancestral functions. In addition, both the phosphorylation level and breadth was increased with the evolutionary age. Similar to cases in fungi, these results implied that the newly emerged phosphorylation sites in vertebrates were also more likely to be non-functional, especially for serine and threonine phosphorylation in disordered regions.

CONCLUSIONS

This study provided not only insights into the dynamics of phosphorylation evolution in vertebrates, but also new clues to identify the functional phosphorylation sites from massive noisy data.

Broad distribution spectrum from Gaussian to power law appears in stochastic variations in RNA-seq data

Gene expression levels exhibit stochastic variations among genetically identical organisms under the same environmental conditions. In many recent transcriptome analyses based on RNA sequencing (RNA-seq), variations in gene expression levels among replicates were assumed to follow a negative binomial distribution, although the physiological basis of this assumption remains unclear. In this study, RNA-seq data were obtained from Arabidopsis thaliana under eight conditions (21-27 replicates), and the characteristics of gene-dependent empirical probability density function (ePDF) profiles of gene expression levels were analyzed. For A. thaliana and Saccharomyces cerevisiae, various types of ePDF of gene expression levels were obtained that were classified as Gaussian, power law-like containing a long tail, or intermediate. These ePDF profiles were well fitted with a Gauss-power mixing distribution function derived from a simple model of a stochastic transcriptional network containing a feedback loop. The fitting function suggested that gene expression levels with long-tailed ePDFs would be strongly influenced by feedback regulation. Furthermore, the features of gene expression levels are correlated with their functions, with the levels of essential genes tending to follow a Gaussian-like ePDF while those of genes encoding nucleic acid-binding proteins and transcription factors exhibit long-tailed ePDF.

A study on the use of strain-specific and homologous promoters for heterologous expression in industrial Saccharomyces cerevisiae strains

Polymorphism is well known in Saccharomyces cerevisiae strains used for different industrial applications, however little is known about its effects on promoter efficiency. In order to test this, five different promoters derived from an industrial and a laboratory (S288c) strain were used to drive the expression of eGFP reporter gene in both cells. The ADH1 promoter (P_ADH1) in particular, which showed more polymorphism among the promoters analyzed, also exhibited the highest differences in intracellular fluorescence production. This was further confirmed by Northern blot analysis. The same behavior was also observed when the gene coding for secreted α-amylase from Cryptococcus flavus was placed under the control of either P_ADH1. These results underline the importance of the careful choice of the source of the promoter to be used in industrial yeast strains for heterologous expression.

Macroscopic Theory for Evolving Biological Systems Akin to Thermodynamics

We present a macroscopic theory to characterize the plasticity, robustness, and evolvability of biological responses and their fluctuations. First, linear approximation in intracellular reaction dynamics is used to demonstrate proportional changes in the expression of all cellular components in response to a given environmental stress, with the proportion coefficient determined by the change in growth rate as a consequence of the steady growth of cells. We further demonstrate that this relationship is supported through adaptation experiments of bacteria, perhaps too well as this proportionality is held even across cultures of different types of conditions. On the basis of simulations of cell models, we further show that this global proportionality is a consequence of evolution in which expression changes in response to environmental or genetic perturbations are constrained along a unique one-dimensional curve, which is a result of evolutionary robustness. It then follows that the expression changes induced by environmental changes are proportionally reduced across different components of a cell by evolution, which is akin to the Le Chatelier thermodynamics principle. Finally, with the aid of a fluctuation-response relationship, this proportionality is shown to hold between fluctuations caused by genetic changes and those caused by noise. Overall, these results and support from the theoretical and experimental literature suggest a formulation of cellular systems akin to thermodynamics, in which a macroscopic potential is given by the growth rate (or fitness) represented as a function of environmental and evolutionary changes.

Highly Expressed Genes Are Preferentially Co-Opted for C4 Photosynthesis

Novel adaptations are generally assembled by co-opting pre-existing genetic components, but the factors dictating the suitability of genes for new functions remain poorly known. In this work, we used comparative transcriptomics to determine the attributes that increased the likelihood of some genes being co-opted for C4 photosynthesis, a convergent complex trait that boosts productivity in tropical conditions. We show that independent lineages of grasses repeatedly co-opted the gene lineages that were the most highly expressed in non-C4 ancestors to produce their C4 pathway. Although ancestral abundance in leaves explains which genes were used for the emergence of a C4 pathway, the tissue specificity has surprisingly no effect. Our results suggest that levels of key genes were elevated during the early diversification of grasses and subsequently repeatedly used to trigger a weak C4 cycle via relatively few mutations. The abundance of C4-suitable transcripts therefore facilitated physiological innovation, but the transition to a strong C4 pathway still involved consequent changes in expression levels, leaf specificity, and coding sequences. The direction and amount of changes required for the strong C4 pathway depended on the identity of the genes co-opted, so that ancestral gene expression both facilitates adaptive transitions and constrains subsequent evolutionary trajectories.

Effects of mutation and selection on plasticity of a promoter activity in Saccharomyces cerevisiae

Phenotypic plasticity is an evolvable property of biological systems that can arise from environment-specific regulation of gene expression. To better understand the evolutionary and molecular mechanisms that give rise to plasticity in gene expression, we quantified the effects of 235 single-nucleotide mutations in the Saccharomyces cerevisiae TDH3 promoter (P_TDH3 ) on the activity of this promoter in media containing glucose, galactose, or glycerol as a carbon source. We found that the distributions of mutational effects differed among environments because many mutations altered the plastic response exhibited by the wild-type allele. Comparing the effects of these mutations with the effects of 30 P_TDH3 polymorphisms on expression plasticity in the same environments provided evidence of natural selection acting to prevent the plastic response in P_TDH3 activity between glucose and galactose from becoming larger. The largest changes in expression plasticity were observed between fermentable (glucose or galactose) and nonfermentable (glycerol) carbon sources and were caused by mutations located in the RAP1 and GCR1 transcription factor binding sites. Mutations altered expression plasticity most frequently between the two fermentable environments, with mutations causing significant changes in plasticity between glucose and galactose distributed throughout the promoter, suggesting they might affect chromatin structure. Taken together, these results provide insight into the molecular mechanisms underlying gene-by-environment interactions affecting gene expression as well as the evolutionary dynamics affecting natural variation in plasticity of gene expression.

High-resolution mapping of cis-regulatory variation in budding yeast

Genetic variants affecting gene-expression levels are a major source of phenotypic variation. The approximate locations of these variants can be mapped as expression quantitative trait loci (eQTLs); however, a major limitation of eQTLs is their low resolution, which precludes investigation of the causal variants and their molecular mechanisms. Here we report RNA-seq and full genome sequences for 85 diverse isolates of the yeast Saccharomyces cerevisiae-including wild, domesticated, and human clinical strains-which allowed us to perform eQTL mapping with 50-fold higher resolution than previously possible. In addition to variants in promoters, we uncovered an important role for variants in 3'UTRs, especially those affecting binding of the PUF family of RNA-binding proteins. The eQTLs are predominantly under negative selection, particularly those affecting essential genes and conserved genes. However, applying the sign test for lineage-specific selection revealed the polygenic up-regulation of dozens of biofilm suppressor genes in strains isolated from human patients, consistent with the key role of biofilms in fungal pathogenicity. In addition, a single variant in the promoter of a biofilm suppressor, NIT3, showed the strongest genome-wide association with clinical origin. Altogether, our results demonstrate the power of high-resolution eQTL mapping in understanding the molecular mechanisms of regulatory variation, as well as the natural selection acting on this variation that drives adaptation to environments, ranging from laboratories to vineyards to the human body.

Testing the neutral hypothesis of phenotypic evolution

Although evolution by natural selection is widely regarded as the most important principle of biology, it is unknown whether phenotypic variations within and between species are mostly adaptive or neutral due to the lack of relevant studies of large, unbiased samples of phenotypic traits. Here, we examine 210 yeast morphological traits chosen because of experimental feasibility irrespective of their potential adaptive values. Our analysis is based on the premise that, under neutrality, the rate of phenotypic evolution measured in the unit of mutational size declines as the trait becomes more important to fitness, analogous to the neutral paradigm that functional genes evolve more slowly than functionless pseudogenes. However, we find faster evolution of more important morphological traits within and between species, rejecting the neutral hypothesis. By contrast, an analysis of 3,466 gene expression traits fails to refute neutrality. Thus, at least in yeast, morphological evolution appears largely adaptive, but the same may not apply to other classes of phenotypes. Our neutrality test is applicable to other species, especially genetic model organisms, for which estimations of mutational size and trait importance are relatively straightforward.

Structure of the Transcriptional Regulatory Network Correlates with Regulatory Divergence in Drosophila

Transcriptional control of gene expression is regulated by biochemical interactions between cis-regulatory DNA sequences and trans-acting factors that form complex regulatory networks. Genetic changes affecting both cis- and trans-acting sequences in these networks have been shown to alter patterns of gene expression as well as higher-order organismal phenotypes. Here, we investigate how the structure of these regulatory networks relates to patterns of polymorphism and divergence in gene expression. To do this, we compared a transcriptional regulatory network inferred for Drosophila melanogaster to differences in gene regulation observed between two strains of D. melanogaster as well as between two pairs of closely related species: Drosophila sechellia and Drosophila simulans, and D. simulans and D. melanogaster. We found that the number of transcription factors predicted to directly regulate a gene ("in-degree") was negatively correlated with divergence in both gene expression (mRNA abundance) and cis-regulation. This observation suggests that the number of transcription factors directly regulating a gene's expression affects the conservation of cis-regulation and gene expression over evolutionary time. We also tested the hypothesis that transcription factors regulating more target genes (higher "out-degree") are less likely to evolve changes in their cis-regulation and expression (presumably due to increased pleiotropy), but found little support for this predicted relationship. Taken together, these data show how the architecture of regulatory networks can influence regulatory evolution.

Single nucleotide polymorphisms and microsatellites in the canine glutathione S-transferase pi 1 (GSTP1) gene promoter

BACKGROUND

Genetic polymorphisms within the glutathione S-transferase P1 (GSTP1) gene affect the elimination of toxic xenobiotics by the GSTP1 enzyme. In dogs, exposure to environmental chemicals that may be GSTP1 substrates is associated with cancer. The objectives of this study were to investigate the genetic variability in the GSTP1 promoter in a diverse population of 278 purebred dogs, compare the incidence of any variants found between breeds, and predict their effects on gene expression. To provide information on ancestral alleles, a number of wolves, coyotes, and foxes were also sequenced.

RESULTS

Fifteen single nucleotide polymorphisms (SNPs) and two microsatellites were discovered. Three of these loci were only polymorphic in dogs while three other SNPs were unique to wolves and coyotes. The major allele at c.-46 is T in dogs but is C in the wild canids. The c.-185 delT variant was unique to dogs. The microsatellite located in the 5' untranslated region (5'UTR) was a highly polymorphic GCC tandem repeat, consisting of simple and compound alleles that varied in size from 10 to 22-repeat units. The most common alleles consisted of 11, 16, and 17-repeats. The 11-repeat allele was found in 10% of dogs but not in the other canids. Unequal recombination and replication slippage between similar and distinct alleles may be the mechanism for the multiple microsatellites observed. Twenty-eight haplotypes were constructed in the dog, and an additional 8 were observed in wolves and coyotes. While the most common haplotype acrossbreeds was the wild-type *1A(17), other prevalent haplotypes included *3A(11) in Greyhounds, *6A(16) in Labrador Retrievers, *9A(16) in Golden Retrievers, and *8A(19) in Standard Poodles. Boxers and Siberian Huskies exhibited minimal haplotypic diversity. Compared to the simple 16*1 allele, the compound 16*2 allele (found in 12% of dogs) may interfere with transcription factor binding and/or the stability of the GSTP1 transcript.

CONCLUSIONS

Dogs and other canids exhibit extensive variation in the GSTP1 promoter. Genetic polymorphisms within distinct haplotypes prevalent in certain breeds can affect GSTP1 expression and carcinogen detoxification, and thus may be useful as genetic markers for cancer in dogs.

Evolutionary Dynamics of Regulatory Changes Underlying Gene Expression Divergence among Saccharomyces Species

Heritable changes in gene expression are important contributors to phenotypic differences within and between species and are caused by mutations in cis-regulatory elements and trans-regulatory factors. Although previous work has suggested that cis-regulatory differences preferentially accumulate with time, technical restrictions to closely related species and limited comparisons have made this observation difficult to test. To address this problem, we used allele-specific RNA-seq data from Saccharomyces species and hybrids to expand both the evolutionary timescale and number of species in which the evolution of regulatory divergence has been investigated. We find that as sequence divergence increases, cis-regulatory differences do indeed become the dominant type of regulatory difference between species, ultimately becoming a better predictor of expression divergence than trans-regulatory divergence. When both cis- and trans-regulatory differences accumulate for the same gene, they more often have effects in opposite directions than in the same direction, indicating widespread compensatory changes underlying the evolution of gene expression. The frequency of compensatory changes within and between species and the magnitude of effect for the underlying cis- and trans-regulatory differences suggests that compensatory changes accumulate primarily due to selection against divergence in gene expression as a result of weak stabilizing selection on gene expression levels. These results show that cis-regulatory differences and compensatory changes in regulation play increasingly important roles in the evolution of gene expression as time increases.

Inheritance of brewing-relevant phenotypes in constructed Saccharomyces cerevisiae × Saccharomyces eubayanus hybrids

BACKGROUND

Interspecific hybridization has proven to be a potentially valuable technique for generating de novo lager yeast strains that possess diverse and improved traits compared to their parent strains. To further enhance the value of hybridization for strain development, it would be desirable to combine phenotypic traits from more than two parent strains, as well as remove unwanted traits from hybrids. One such trait, that has limited the industrial use of de novo lager yeast hybrids, is their inherent tendency to produce phenolic off-flavours; an undesirable trait inherited from the Saccharomyces eubayanus parent. Trait removal and the addition of traits from a third strain could be achieved through sporulation and meiotic recombination or further mating. However, interspecies hybrids tend to be sterile, which impedes this opportunity.

RESULTS

Here we generated a set of five hybrids from three different parent strains, two of which contained DNA from all three parent strains. These hybrids were constructed with fertile allotetraploid intermediates, which were capable of efficient sporulation. We used these eight brewing strains to examine two brewing-relevant phenotypes: stress tolerance and phenolic off-flavour formation. Lipidomics and multivariate analysis revealed links between several lipid species and the ability to ferment in low temperatures and high ethanol concentrations. Unsaturated fatty acids, such as oleic acid, and ergosterol were shown to positively influence growth at high ethanol concentrations. The ability to produce phenolic off-flavours was also successfully removed from one of the hybrids, Hybrid T2, through meiotic segregation. The potential application of these strains in industrial fermentations was demonstrated in wort fermentations, which revealed that the meiotic segregant Hybrid T2 not only didn't produce any phenolic off-flavours, but also reached the highest ethanol concentration and consumed the most maltotriose.

CONCLUSIONS

Our study demonstrates the possibility of constructing complex yeast hybrids that possess traits that are relevant to industrial lager beer fermentation and that are derived from several parent strains. Yeast lipid composition was also shown to have a central role in determining ethanol and cold tolerance in brewing strains.

Uncovering SNP and indel variations of tetraploid cottons by SLAF-seq

Background

Cotton (Gossypium spp.), as the world’s most utilized textile fibre source, is an important, economically valuable crop worldwide. Understanding the genomic variation of tetraploid cotton species is important for exploitation of the excellent characteristics of wild cotton and for improving the diversity of cotton in breeding. However, the discovery of DNA polymorphisms in tetraploid cotton genomes has lagged behind other important crops.

Results

A total of 111,795,823 reads, 467,735 specific length amplified fragment (SLAF) tags and 139,176 high-quality DNA polymorphisms were identified using specific length amplified fragment sequencing (SLAF-seq), including 132,880 SNPs and 6,296 InDels between the reference genome (TM-1) and the five tetraploid cotton species. Intriguingly, gene ontology (GO) enrichment analysis revealed that a number of significant terms were related to reproduction in G. barbadense acc. 3–79. Based on the new data sets, we reconstructed phylogenetic trees that showed a high concordance to the phylogeny of diploid and polyploid cottons. A large amount of interspecific genetic variations were identified, and some of them were validated by the single-strand conformation polymorphism (SSCP) method, which will be applied in introgression genetics and breeding with G. hirsutum cv. Emian22 as the receptor and the other species as donors.

Conclusions

Using SLAF-seq, a large number of DNA polymorphisms were identified. The comprehensive analysis of DNA polymorphisms provided invaluable insights into the different tetraploid cotton species. More importantly, the identification of numerous interspecific genetic variations provides the basis and is very practical for future introgression breeding. The results presented herein provide a valuable genomic resource for new insights into the genetics and breeding of cotton.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3643-4) contains supplementary material, which is available to authorized users.

Network Centrality Analysis in Fungi Reveals Complex Regulation of Lost and Gained Genes

Gene gain and loss shape both proteomes and the networks they form. The increasing availability of closely related sequenced genomes and of genome-wide network data should enable a better understanding of the evolutionary forces driving gene gain, gene loss and evolutionary network rewiring. Using orthology mappings across 23 ascomycete fungi genomes, we identified proteins that were lost, gained or universally conserved across the tree, enabling us to compare genes across all stages of their life-cycle. Based on a collection of genome-wide network and gene expression datasets from baker's yeast, as well as a few from fission yeast, we found that gene loss is more strongly associated with network and expression features of closely related species than that of distant species, consistent with the evolutionary modulation of gene loss propensity through network rewiring. We also discovered that lost and gained genes, as compared to universally conserved "core" genes, have more regulators, more complex expression patterns and are much more likely to encode for transcription factors. Finally, we found that the relative rate of network integration of new genes into the different types of networks agrees with experimentally measured rates of network rewiring. This systems-level view of the life-cycle of eukaryotic genes suggests that the gain and loss of genes is tightly coupled to the gain and loss of network interactions, that lineage-specific adaptations drive regulatory complexity and that the relative rates of integration of new genes are consistent with network rewiring rates.

A genome wide dosage suppressor network reveals genomic robustness

Genomic robustness is the extent to which an organism has evolved to withstand the effects of deleterious mutations. We explored the extent of genomic robustness in budding yeast by genome wide dosage suppressor analysis of 53 conditional lethal mutations in cell division cycle and RNA synthesis related genes, revealing 660 suppressor interactions of which 642 are novel. This collection has several distinctive features, including high co-occurrence of mutant-suppressor pairs within protein modules, highly correlated functions between the pairs and higher diversity of functions among the co-suppressors than previously observed. Dosage suppression of essential genes encoding RNA polymerase subunits and chromosome cohesion complex suggests a surprising degree of functional plasticity of macromolecular complexes, and the existence of numerous degenerate pathways for circumventing the effects of potentially lethal mutations. These results imply that organisms and cancer are likely able to exploit the genomic robustness properties, due the persistence of cryptic gene and pathway functions, to generate variation and adapt to selective pressures.

Neurogenomics and the role of a large mutational target on rapid behavioral change

BACKGROUND

Behavior, while complex and dynamic, is among the most diverse, derived, and rapidly evolving traits in animals. The highly labile nature of heritable behavioral change is observed in such evolutionary phenomena as the emergence of converged behaviors in domesticated animals, the rapid evolution of preferences, and the routine development of ethological isolation between diverging populations and species. In fact, it is believed that nervous system development and its potential to evolve a seemingly infinite array of behavioral innovations played a major role in the successful diversification of metazoans, including our own human lineage. However, unlike other rapidly evolving functional systems such as sperm-egg interactions and immune defense, the genetic basis of rapid behavioral change remains elusive.

PRESENTATION OF THE HYPOTHESIS

Here we propose that the rapid divergence and widespread novelty of innate and adaptive behavior is primarily a function of its genomic architecture. Specifically, we hypothesize that the broad diversity of behavioral phenotypes present at micro- and macroevolutionary scales is promoted by a disproportionately large mutational target of neurogenic genes. We present evidence that these large neuro-behavioral targets are significant and ubiquitous in animal genomes and suggest that behavior's novelty and rapid emergence are driven by a number of factors including more selection on a larger pool of variants, a greater role of phenotypic plasticity, and/or unique molecular features present in large genes. We briefly discuss the origins of these large neurogenic genes, as they relate to the remarkable diversity of metazoan behaviors, and highlight key consequences on both behavioral traits and neurogenic disease across, respectively, evolutionary and ontogenetic time scales.

TESTING THE HYPOTHESIS

Current approaches to studying the genetic mechanisms underlying rapid phenotypic change primarily focus on identifying signatures of Darwinian selection in protein-coding regions. In contrast, the large mutational target hypothesis places genomic architecture and a larger allelic pool at the forefront of rapid evolutionary change, particularly in genetic systems that are polygenic and regulatory in nature. Genomic data from brain and neural tissues in mammals as well as a preliminary survey of neurogenic genes from comparative genomic data support this hypothesis while rejecting both positive and relaxed selection on proteins or higher mutation rates. In mammals and invertebrates, neurogenic genes harbor larger protein-coding regions and possess a richer regulatory repertoire of miRNA targets and transcription factor binding sites. Overall, neurogenic genes cover a disproportionately large genomic fraction, providing a sizeable substrate for evolutionary, genetic, and molecular mechanisms to act upon. Readily available comparative and functional genomic data provide unexplored opportunities to test whether a distinct neurogenomic architecture can promote rapid behavioral change via several mechanisms unique to large genes, and which components of this large footprint are uniquely metazoan.

IMPLICATIONS OF THE HYPOTHESIS

The large mutational target hypothesis highlights the eminent roles of mutation and functional genomic architecture in generating rapid developmental and evolutionary change. It has broad implications on our understanding of the genetics of complex adaptive traits such as behavior by focusing on the importance of mutational input, from SNPs to alternative transcripts to transposable elements, on driving evolutionary rates of functional systems. Such functional divergence has important implications in promoting behavioral isolation across short- and long-term timescales. Due to genome-scaled polygenic adaptation, the large target effect also contributes to our inability to identify adapted behavioral candidate genes. The presence of large neurogenic genes, particularly in the mammalian brain and other neural tissues, further offers emerging insight into the etiology of neurodevelopmental and neurodegenerative diseases. The well-known correlation between neurological spectrum disorders in children and paternal age may simply be a direct result of aging fathers accumulating mutations across these large neurodevelopmental genes. The large mutational target hypothesis can also explain the rapid evolution of other functional systems covering a large genomic fraction such as male fertility and its preferential association with hybrid male sterility among closely related taxa. Overall, a focus on mutational potential may increase our power in understanding the genetic basis of complex phenotypes such as behavior while filling a general gap in understanding their evolution.

The mutational structure of metabolism in Caenorhabditis elegans

A properly functioning organism must maintain metabolic homeostasis. Deleterious mutations degrade organismal function, presumably at least in part via effects on metabolic function. Here we present an initial investigation into the mutational structure of the Caenorhabditis elegans metabolome by means of a mutation accumulation experiment. We find that pool sizes of 29 metabolites vary greatly in their vulnerability to mutation, both in terms of the rate of accumulation of genetic variance (the mutational variance, VM) and the rate of change of the trait mean (the mutational bias, ΔM). Strikingly, some metabolites are much more vulnerable to mutation than any other trait previously studied in the same way. Although we cannot statistically assess the strength of mutational correlations between individual metabolites, principal component analysis provides strong evidence that some metabolite pools are genetically correlated, but also that there is substantial scope for independent evolution of different groups of metabolites. Averaged over mutation accumulation lines, PC3 is positively correlated with relative fitness, but a model in which metabolites are uncorrelated with fitness is nearly as good by Akaike's Information Criterion.

Transcriptional and Epigenetic Regulatory Mechanisms Affecting HTLV-1 Provirus

Human T-cell leukemia virus type 1 (HTLV-1) is a retrovirus associated with human diseases, such as adult T-cell leukemia (ATL) and HTLV-1-associated myelopathy/Tropic spastic paraparesis (HAM/TSP). As a retrovirus, its life cycle includes a step where HTLV-1 is integrated into the host genomic DNA and forms proviral DNA. In the chronic phase of the infection, HTLV‑1 is known to proliferate as a provirus via the mitotic division of the infected host cells. There are generally tens of thousands of infected clones within an infected individual. They exist not only in peripheral blood, but also in various lymphoid organs. Viral proteins encoded in HTLV-1 genome play a role in the proliferation and survival of the infected cells. As is the case with other chronic viral infections, HTLV-1 gene expression induces the activation of the host immunity against the virus. Thus, the transcription from HTLV-1 provirus needs to be controlled in order to evade the host immune surveillance. There should be a dynamic and complex regulation in vivo, where an equilibrium between viral antigen expression and host immune surveillance is achieved. The mechanisms regulating viral gene expression from the provirus are a key to understanding the persistent/latent infection with HTLV-1 and its pathogenesis. In this article, we would like to review our current understanding on this topic.

Hybrid sterility and evolution in Hawaiian Drosophila: differential gene and allele-specific expression analysis of backcross males

The Hawaiian Drosophila are an iconic example of sequential colonization, adaptive radiation and speciation on islands. Genetic and phenotypic analysis of closely related species pairs that exhibit incomplete reproductive isolation can provide insights into the mechanisms of speciation. Drosophila silvestris from Hawai'i Island and Drosophila planitibia from Maui are two closely related allopatric Hawaiian picture-winged Drosophila that produce sterile F1 males but fertile F1 females, a pattern consistent with Haldane's rule. Backcrossing F1 hybrid females between these two species to parental species gives rise to recombinant males with three distinct sperm phenotypes despite a similar genomic background: motile sperm, no sperm (sterile), and immotile sperm. We found that these three reproductive morphologies of backcross hybrid males produce divergent gene expression profiles in testes, as measured with RNA sequencing. There were a total of 71 genes significantly differentially expressed between backcross males with no sperm compared with those backcross males with motile sperm and immotile sperm, but no significant differential gene expression between backcross males with motile sperm and backcross males with immotile sperm. All of these genes were underexpressed in males with no sperm, including a number of genes with previously known activities in adult testis. An allele-specific expression analysis showed overwhelmingly more cis-divergent than trans-divergent genes, with no significant difference in the ratio of cis- and trans-divergent genes among the sperm phenotypes. Overall, the results indicate that the regulation of gene expression involved in sperm production likely diverged relatively rapidly between these two closely related species.

Spontaneous mutations and the origin and maintenance of quantitative genetic variation

Mutation and natural selection shape the genetic variation in natural populations. Here, we directly estimated the spontaneous mutation rate by sequencing new Drosophila mutation accumulation lines maintained with minimal natural selection. We inferred strong stabilizing natural selection on quantitative traits because genetic variation among wild-derived inbred lines was much lower than predicted from a neutral model and the mutational effects were much larger than allelic effects of standing polymorphisms. Stabilizing selection could act directly on the traits, or indirectly from pleiotropic effects on fitness. However, our data are not consistent with simple models of mutation-stabilizing selection balance; therefore, further empirical work is needed to assess the balance of evolutionary forces responsible for quantitative genetic variation.

DOI:http://dx.doi.org/10.7554/eLife.14625.001

A key challenge in evolutionary biology is to understand how genetic variation – differences in the DNA of individuals in a population – is generated and maintained to create the enormous diversity that exists in nature. Mutations to the DNA introduce new variation, but these are constantly removed from populations by two other evolutionary forces: natural selection and genetic drift.

Natural selection removes harmful genetic mutations that affect an organism’s fitness and reproduction, and genetic drift is the random increase in, or loss of, a genetic variant from a population over time. However, disentangling the effects of these evolutionary forces is challenging because the genetic variation we observe is often the final product of a long history of interaction between them.

Huang et al. have now investigated genetic variation by breeding fruit flies in the laboratory. Natural selection was minimized for these flies; genetic drift was therefore the main force that removed variation.

Huang et al. then sequenced the DNA of the flies to estimate the rate at which genetic mutations spontaneously occur. The sequences contained many more “high-impact” mutations (which directly affect how proteins in the fly’s cells work) than seen in sequences taken from a natural fly population.

Traits that are produced by the cumulative actions of many genes and the environment are known as quantitative traits. By examining how much variation genetic mutations introduced into the quantitative traits of each generation of the laboratory-grown flies, Huang et al. estimated how much variation should occur in a natural population whose quantitative traits evolved without natural selection. This estimate was much higher than the levels of genetic variation seen in nature, suggesting that natural selection acts to eliminate mutations that significantly affect quantitative traits.

Simple theoretical models cannot explain the relatively high spontaneous mutation rate and low genetic variation seen in the quantitative traits of natural populations. Therefore, further work is now required to understand more about the balance of evolutionary forces that maintain quantitative genetic variation.

DOI:http://dx.doi.org/10.7554/eLife.14625.002

Nonlinear Dynamics in Gene Regulation Promote Robustness and Evolvability of Gene Expression Levels

Cellular phenotypes underpinned by regulatory networks need to respond to evolutionary pressures to allow adaptation, but at the same time be robust to perturbations. This creates a conflict in which mutations affecting regulatory networks must both generate variance but also be tolerated at the phenotype level. Here, we perform mathematical analyses and simulations of regulatory networks to better understand the potential trade-off between robustness and evolvability. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics, through the creation of regions presenting sudden changes in phenotype with small changes in genotype. For genotypes embedding low levels of nonlinearity, robustness and evolvability correlate negatively and almost perfectly. By contrast, genotypes embedding nonlinear dynamics allow expression levels to be robust to small perturbations, while generating high diversity (evolvability) under larger perturbations. Thus, nonlinearity breaks the robustness-evolvability trade-off in gene expression levels by allowing disparate responses to different mutations. Using analytical derivations of robustness and system sensitivity, we show that these findings extend to a large class of gene regulatory network architectures and also hold for experimentally observed parameter regimes. Further, the effect of nonlinearity on the robustness-evolvability trade-off is ensured as long as key parameters of the system display specific relations irrespective of their absolute values. We find that within this parameter regime genotypes display low and noisy expression levels. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics. Our results provide a possible solution to the robustness-evolvability trade-off, suggest an explanation for the ubiquity of nonlinear dynamics in gene expression networks, and generate useful guidelines for the design of synthetic gene circuits.

Global relationships in fluctuation and response in adaptive evolution

Cells change their internal state to adapt to environmental changes, and evolve in response to the new conditions. The phenotype changes first via adaptation in response to environmental changes, and then through mutational changes in the genomic sequence, followed by selection in evolution. Here, we analysed simulated adaptive evolution using a simple cell model consisting of thousands of intracellular components, and found that the changes in their concentrations by adaptation are proportional to those by evolution across all the components, where the proportion coefficient between the two agreed well with the change in the growth rate of a cell. Furthermore, we demonstrate that the phenotypic variance in concentrations of cellular components due to (non-genetic) noise and to genomic alternations is proportional across all components. This implies that the specific phenotypes that are highly evolvable were already given by non-genetic fluctuations. These global relationships in cellular states were also supported by phenomenological theory based on steady reproduction and transcriptome analysis of laboratory evolution in Escherichia coli. These findings demonstrate that a possible evolutionary change in phenotypic state is highly restricted. Our results provide a basis for the development of a quantitative theory of plasticity and robustness in phenotypic evolution.

Genetic assimilation: a review of its potential proximate causes and evolutionary consequences

BACKGROUND

Most, if not all, organisms possess the ability to alter their phenotype in direct response to changes in their environment, a phenomenon known as phenotypic plasticity. Selection can break this environmental sensitivity, however, and cause a formerly environmentally induced trait to evolve to become fixed through a process called genetic assimilation. Essentially, genetic assimilation can be viewed as the evolution of environmental robustness in what was formerly an environmentally sensitive trait. Because genetic assimilation has long been suggested to play a key role in the origins of phenotypic novelty and possibly even new species, identifying and characterizing the proximate mechanisms that underlie genetic assimilation may advance our basic understanding of how novel traits and species evolve.

SCOPE

This review begins by discussing how the evolution of phenotypic plasticity, followed by genetic assimilation, might promote the origins of new traits and possibly fuel speciation and adaptive radiation. The evidence implicating genetic assimilation in evolutionary innovation and diversification is then briefly considered. Next, the potential causes of phenotypic plasticity generally and genetic assimilation specifically are examined at the genetic, molecular and physiological levels and approaches that can improve our understanding of these mechanisms are described. The review concludes by outlining major challenges for future work.

CONCLUSIONS

Identifying and characterizing the proximate mechanisms involved in phenotypic plasticity and genetic assimilation promises to help advance our basic understanding of evolutionary innovation and diversification.

Developmental mechanisms underlying variable, invariant and plastic phenotypes

BACKGROUND

Discussions of phenotypic robustness often consider scenarios where invariant phenotypes are optimal and assume that developmental mechanisms have evolved to buffer the phenotypes of specific traits against stochastic and environmental perturbations. However, plastic plant phenotypes that vary between environments or variable phenotypes that vary stochastically within an environment may also be advantageous in some scenarios.

SCOPE

Here the conditions under which invariant, plastic and variable phenotypes of specific traits may confer a selective advantage in plants are examined. Drawing on work from microbes and multicellular organisms, the mechanisms that may give rise to each type of phenotype are discussed.

CONCLUSION

In contrast to the view of robustness as being the ability of a genotype to produce a single, invariant phenotype, changes in a phenotype in response to the environment, or phenotypic variability within an environment, may also be delivered consistently (i.e. robustly). Thus, for some plant traits, mechanisms have probably evolved to produce plasticity or variability in a reliable manner.

Contrasting Frequencies and Effects of cis- and trans-Regulatory Mutations Affecting Gene Expression

Heritable differences in gene expression are caused by mutations in DNA sequences encoding cis-regulatory elements and trans-regulatory factors. These two classes of regulatory change differ in their relative contributions to expression differences in natural populations because of the combined effects of mutation and natural selection. Here, we investigate how new mutations create the regulatory variation upon which natural selection acts by quantifying the frequencies and effects of hundreds of new cis- and trans-acting mutations altering activity of the TDH3 promoter in the yeast Saccharomyces cerevisiae in the absence of natural selection. We find that cis-regulatory mutations have larger effects on expression than trans-regulatory mutations and that while trans-regulatory mutations are more common overall, cis- and trans-regulatory changes in expression are equally abundant when only the largest changes in expression are considered. In addition, we find that cis-regulatory mutations are skewed toward decreased expression while trans-regulatory mutations are skewed toward increased expression. We also measure the effects of cis- and trans-regulatory mutations on the variability in gene expression among genetically identical cells, a property of gene expression known as expression noise, finding that trans-regulatory mutations are much more likely to decrease expression noise than cis-regulatory mutations. Because new mutations are the raw material upon which natural selection acts, these differences in the frequencies and effects of cis- and trans-regulatory mutations should be considered in models of regulatory evolution.

Gene expression variability in clonal populations: Causes and consequences

During the last decade it has been shown that among cell variation in gene expression plays an important role within clonal populations. Here, we provide an overview of the different mechanisms contributing to gene expression variability in clonal populations. These are ranging from inherent variations in the biochemical process of gene expression itself, such as intrinsic noise, extrinsic noise and bistability to individual responses to variations in the local micro-environment, a phenomenon called phenotypic plasticity. Also genotypic variations caused by clonal evolution and phase variation can contribute to gene expression variability. Consequently, gene expression studies need to take these fluctuations in expression into account. However, frequently used techniques for expression quantification, such as microarrays, RNA sequencing, quantitative PCR and gene reporter fusions classically determine the population average of gene expression. Here, we discuss how these techniques can be adapted towards single cell analysis by integration with single cell isolation, RNA amplification and microscopy. Alternatively more qualitative selection-based techniques, such as mutant screenings, in vivo expression technology (IVET) and recombination-based IVET (RIVET) can be applied for detection of genes expressed only within a subpopulation. Finally, differential fluorescence induction (DFI), a protocol specially designed for single cell expression is discussed.

Functional redundancy of transcription factors explains why most binding targets of a transcription factor are not affected when the transcription factor is knocked out

Background

Biologists are puzzled by the extremely low percentage (3%) of the binding targets of a yeast transcription factor (TF) affected when the TF is knocked out, a phenomenon observed by comparing the TF binding dataset and TF knockout effect dataset.

Results

This study gives a plausible biological explanation of this counterintuitive phenomenon. Our analyses find that TFs with high functional redundancy show significantly lower percentage than do TFs with low functional redundancy. This suggests that functional redundancy may lead to one TF compensating for another, thus masking the TF knockout effect on the binding targets of the knocked-out TF. In addition, we show that seven classes of genes (lowly expressed genes, TATA box-less genes, genes containing a nucleosome-free region immediately upstream of the transcriptional start site (TSS), genes with low transcriptional plasticity, genes with a low number of bound TFs, genes with a low number of TFBSs, and genes with a short average distance of TFBSs to the TSS) are insensitive to the knockout of their promoter-binding TFs, providing clues for finding other biological explanations of the surprisingly low percentage of the binding targets of a TF affected when the TF is knocked out.

Conclusions

This study shows that one property of TFs (functional redundancy) and seven properties of genes (expression level, TATA box, nucleosome, transcriptional plasticity, the number of bound TFs, the number of TFBSs, and the average distance of TFBSs to the TSS) may be useful for explaining a counterintuitive phenomenon: most binding targets of a yeast transcription factor are not affected when the transcription factor is knocked out.

Population perspectives on functional genomic variation in yeast

Advances in high-throughput sequencing have facilitated large-scale surveys of genomic variation in the budding yeast,Saccharomyces cerevisiae These surveys have revealed extensive sequence variation between yeast strains. However, much less is known about how such variation influences the amount and nature of variation for functional genomic traits within and between yeast lineages. We review population-level studies of functional genomic variation, with a particular focus on how population functional genomic approaches can provide insights into both genome function and the evolutionary process. Although variation in functional genomics phenotypes is pervasive, our understanding of the consequences of this variation, either in physiological or evolutionary terms, is still rudimentary and thus motivates increased attention to appropriate null models. To date, much of the focus of population functional genomic studies has been on gene expression variation, but other functional genomic data types are just as likely to reveal important insights at the population level, suggesting a pressing need for more studies that go beyond transcription. Finally, we discuss how a population functional genomic perspective can be a powerful approach for developing a mechanistic understanding of the processes that link genomic variation to organismal phenotypes through gene networks.

Noise-plasticity correlations of gene expression in the multicellular organism Arabidopsis thaliana

Gene expression levels exhibit stochastic variations among genetically identical organisms under the same environmental conditions (called gene expression "noise" or phenotype "fluctuation"). In yeast and Escherichia coli, positive correlations have been found between such gene expression noise and "plasticity" with environmental variations. To determine the universality of such correlations in both unicellular and multicellular organisms, we focused on the relationships between gene expression "noise" and "plasticity" in Arabidopsis thaliana, a multicellular model organism. In recent studies on yeast and E. coli, only some gene groups with specific properties of promoter architecture, average expression levels, and functions exhibited strong noise-plasticity correlations. However, we found strong noise-plasticity correlations for most gene groups in Arabidopsis; additionally, promoter architecture, functional essentiality of genes, and circadian rhythm appeared to have only a weak influence on the correlation strength. The differences in the characteristics of noise-plasticity correlations may result from three-dimensional chromosomal structures and/or circadian rhythm.

Tandem repeat variation in human and great ape populations and its impact on gene expression divergence

Tandem repeats (TRs) are stretches of DNA that are highly variable in length and mutate rapidly. They are thus an important source of genetic variation. This variation is highly informative for population and conservation genetics. It has also been associated with several pathological conditions and with gene expression regulation. However, genome-wide surveys of TR variation in humans and closely related species have been scarce due to technical difficulties derived from short-read technology. Here we explored the genome-wide diversity of TRs in a panel of 83 human and nonhuman great ape genomes, in a total of six different species, and studied their impact on gene expression evolution. We found that population diversity patterns can be efficiently captured with short TRs (repeat unit length, 1–5 bp). We examined the potential evolutionary role of TRs in gene expression differences between humans and primates by using 30,275 larger TRs (repeat unit length, 2–50 bp). Genes that contained TRs in the promoters, in their 3′ untranslated region, in introns, and in exons had higher expression divergence than genes without repeats in the regions. Polymorphic small repeats (1–5 bp) had also higher expression divergence compared with genes with fixed or no TRs in the gene promoters. Our findings highlight the potential contribution of TRs to human evolution through gene regulation.

Variable Glutamine-Rich Repeats Modulate Transcription Factor Activity

Excessive expansions of glutamine (Q)-rich repeats in various human proteins are known to result in severe neurodegenerative disorders such as Huntington's disease and several ataxias. However, the physiological role of these repeats and the consequences of more moderate repeat variation remain unknown. Here, we demonstrate that Q-rich domains are highly enriched in eukaryotic transcription factors where they act as functional modulators. Incremental changes in the number of repeats in the yeast transcriptional regulator Ssn6 (Cyc8) result in systematic, repeat-length-dependent variation in expression of target genes that result in direct phenotypic changes. The function of Ssn6 increases with its repeat number until a certain threshold where further expansion leads to aggregation. Quantitative proteomic analysis reveals that the Ssn6 repeats affect its solubility and interactions with Tup1 and other regulators. Thus, Q-rich repeats are dynamic functional domains that modulate a regulator's innate function, with the inherent risk of pathogenic repeat expansions.

Gene Expression Evolves under a House-of-Cards Model of Stabilizing Selection

Divergence in gene regulation is hypothesized to underlie much of phenotypic evolution, but the role of natural selection in shaping the molecular phenotype of gene expression continues to be debated. To resolve the mode of gene expression, evolution requires accessible theoretical predictions for the effect of selection over long timescales. Evolutionary quantitative genetic models of phenotypic evolution can provide such predictions, yet those predictions depend on the underlying hypotheses about the distributions of mutational and selective effects that are notoriously difficult to disentangle. Here, we draw on diverse genomic data sets including expression profiles of natural genetic variation and mutation accumulation lines, empirical estimates of genomic mutation rates, and inferences of genetic architecture to differentiate contrasting hypotheses for the roles of stabilizing selection and mutation in shaping natural expression variation. Our analysis suggests that gene expression evolves in a domain of phenotype space well fit by the House-of-Cards (HC) model. Although the strength of selection inferred is sensitive to the number of loci controlling gene expression, the model is not. The consistency of these results across evolutionary time from budding yeast through fruit fly implies that this model is general and that mutational effects on gene expression are relatively large. Empirical estimates of the genetic architecture of gene expression traits imply that selection provides modest constraints on gene expression levels for most genes, but that the potential for regulatory evolution is high. Our prediction using data from laboratory environments should encourage the collection of additional data sets allowing for more nuanced parameterizations of HC models for gene expression.

The complex pattern of epigenomic variation between natural yeast strains at single-nucleosome resolution

BACKGROUND

Epigenomic studies on humans and model species have revealed substantial inter-individual variation in histone modification profiles. However, the pattern of this variation has not been precisely characterized, particularly regarding which genomic features are enriched for variability and whether distinct histone marks co-vary synergistically. Yeast allows us to investigate intra-species variation at high resolution while avoiding other sources of variation, such as cell type or subtype.

RESULTS

We profiled histone marks H3K4me3, H3K9ac, H3K14ac, H4K12ac and H3K4me1 in three unrelated wild strains of Saccharomyces cerevisiae at single-nucleosome resolution and analyzed inter-strain differences statistically. All five marks varied significantly at specific loci, but to different extents. The number of nucleosomes varying for a given mark between two strains ranged from 20 to several thousands; +1 nucleosomes were significantly less subject to variation. Genes with highly evolvable or responsive expression showed higher variability; however, the variation pattern could not be explained by known transcriptional differences between the strains. Synergistic variation of distinct marks was not systematic, with surprising differences between functionally related H3K9ac and H3K14ac. Interestingly, H3K14ac differences that persisted through transient hyperacetylation were supported by H3K4me3 differences, suggesting stabilization via cross talk.

CONCLUSIONS

Quantitative variation of histone marks among S. cerevisiae strains is abundant and complex. Its relation to functional characteristics is modular and seems modest, with partial association with gene expression divergences, differences between functionally related marks and partial co-variation between marks that may confer stability. Thus, the specific context of studies, such as which precise marks, individuals and genomic loci are investigated, is primordial in population epigenomics studies. The complexity found in this pilot survey in yeast suggests that high complexity can be anticipated among higher eukaryotes, including humans.

The frequent evolutionary birth and death of functional promoters in mouse and human

Promoters are central to the regulation of gene expression. Changes in gene regulation are thought to underlie much of the adaptive diversification between species and phenotypic variation within populations. In contrast to earlier work emphasizing the importance of enhancer evolution and subtle sequence changes at promoters, we show that dramatic changes such as the complete gain and loss (collectively, turnover) of functional promoters are common. Using quantitative measures of transcription initiation in both humans and mice across 52 matched tissues, we discriminate promoter sequence gains from losses and resolve the lineage of changes. We also identify expression divergence and functional turnover between orthologous promoters, finding only the latter is associated with local sequence changes. Promoter turnover has occurred at the majority (>56%) of protein-coding genes since humans and mice diverged. Tissue-restricted promoters are the most evolutionarily volatile where retrotransposition is an important, but not the sole, source of innovation. There is considerable heterogeneity of turnover rates between promoters in different tissues, but the consistency of these in both lineages suggests that the same biological systems are similarly inclined to transcriptional rewiring. The genes affected by promoter turnover show evidence of adaptive evolution. In mice, promoters are primarily lost through deletion of the promoter containing sequence, whereas in humans, many promoters appear to be gradually decaying with weak transcriptional output and relaxed selective constraint. Our results suggest that promoter gain and loss is an important process in the evolutionary rewiring of gene regulation and may be a significant source of phenotypic diversification.

Dosage compensation can buffer copy-number variation in wild yeast

Aneuploidy is linked to myriad diseases but also facilitates organismal evolution. It remains unclear how cells overcome the deleterious effects of aneuploidy until new phenotypes evolve. Although laboratory strains are extremely sensitive to aneuploidy, we show here that aneuploidy is common in wild yeast isolates, which show lower-than-expected expression at many amplified genes. We generated diploid strain panels in which cells carried two, three, or four copies of the affected chromosomes, to show that gene-dosage compensation functions at >30% of amplified genes. Genes subject to dosage compensation are under higher expression constraint in wild populations—but they show elevated rates of gene amplification, suggesting that copy-number variation is buffered at these genes. We find that aneuploidy provides a clear ecological advantage to oak strain YPS1009, by amplifying a causal gene that escapes dosage compensation. Our work presents a model in which dosage compensation buffers gene amplification through aneuploidy to provide a natural, but likely transient, route to rapid phenotypic evolution.

DOI:http://dx.doi.org/10.7554/eLife.05462.001

Evolution is driven by changes to the genes and other genetic information found in the DNA of an organism. These changes might, for example, alter the physical characteristics of the organism, or change how efficiently crucial tasks are carried out inside cells. Whatever the change, if it makes it easier for the organism to survive and reproduce, it is more likely to be passed on to future generations.

DNA is organized inside cells in structures called chromosomes. Most of the cells in animals, plants, and fungi contain two copies of each chromosome. However, sometimes mistakes happen during cell division and extra copies of a chromosome—and hence the genes contained within it—may end up in a cell. These extra copies of genes might help to speed up the rate at which a species evolves, as the ‘spare’ copies are free to adapt to new roles. However, having extra copies of genes can also often be harmful, and in humans can cause genetic disorders such as Down syndrome.

In the laboratory, chromosomes are commonly studied in a species of yeast called Saccharomyces cerevisiae. This species consists of several groups—or strains—that are genetically distinct from each other. Over the years, breeding the yeast for experiments has created laboratory strains that have lost some of the characteristics seen in wild strains. Earlier studies suggested that these cells fail to grow properly if they contain extra copies of chromosomes. Now, Hose et al. have studied nearly 50 wild strains of Saccharomyces cerevisiae. In these, extra copies of chromosomes are commonplace, and seemingly have no detrimental effect on growth. Instead, Hose et al. found that cells with too many copies of a gene use many of those genes less often than would be expected. This process is known as ‘dosage compensation’. This dosage compensation has not been observed in laboratory strains, in part because the extra gene copies make them sickly and hard to study.

Together, the results provide examples of how dosage compensation could help new traits to evolve in a species by reducing the negative effects of duplicated genes. This knowledge may have broad application, from suggesting methods to alleviate human disorders to implicating new ways to engineer useful traits in yeast and other microbes.

DOI:http://dx.doi.org/10.7554/eLife.05462.002

Modeling variation in early life mortality in the western lowland gorilla: Genetic, maternal and other effects

Uncovering sources of variation in gorilla infant mortality informs conservation and life history research efforts. The international studbook for the western lowland gorilla provides information on a sample of captive gorillas large enough for which to analyze genetic, maternal, and various other effects on early life mortality in this critically endangered species. We assess the importance of variables such as sex, maternal parity, paternal age, and hand rearing with regard to infant survival. We also quantify the proportions of variation in mortality influenced by heritable variation and maternal effects from these pedigree and survival data using variance component estimation. Markov chain Monte Carlo simulations of generalized linear mixed models produce variance component distributions in an animal model framework that employs all pedigree information. Two models, one with a maternal identity component and one with both additive genetic and maternal identity components, estimate variance components for different age classes during the first 2 years of life. This is informative of the extent to which mortality risk factors change over time during gorilla infancy. Our results indicate that gorilla mortality is moderately heritable with the strongest genetic influence just after birth. Maternal effects are most important during the first 6 months of life. Interestingly, hand-reared infants have lower mortality for the first 6 months of life. Aside from hand rearing, we found other predictors commonly used in studies of primate infant mortality to have little influence in these gorilla data.

The evolution and adaptive potential of transcriptional variation in sticklebacks--signatures of selection and widespread heritability

Evidence implicating differential gene expression as a significant driver of evolutionary novelty continues to accumulate, but our understanding of the underlying sources of variation in expression, both environmental and genetic, is wanting. Heritability in particular may be underestimated when inferred from genetic mapping studies, the predominant "genetical genomics" approach to the study of expression variation. Such uncertainty represents a fundamental limitation to testing for adaptive evolution at the transcriptomic level. By studying the inheritance of expression levels in 10,495 genes (10,527 splice variants) in a threespine stickleback pedigree consisting of 563 individuals, half of which were subjected to a thermal treatment, we show that 74-98% of transcripts exhibit significant additive genetic variance. Dominance variance is also prevalent (41-99% of transcripts), and genetic sources of variation seem to play a more significant role in expression variance in the liver than a key environmental variable, temperature. Among-population comparisons suggest that the majority of differential expression in the liver is likely due to neutral divergence; however, we also show that signatures of directional selection may be more prevalent than those of stabilizing selection. This predominantly aligns with the neutral model of evolution for gene expression but also suggests that natural selection may still act on transcriptional variation in the wild. As genetic variation both within- and among-populations ultimately defines adaptive potential, these results indicate that broad adaptive potential may be found within the transcriptome.