Non-Darwinian evolution

Estimate of within population incremental selection through branch imbalance in lineage trees

Incremental selection within a population, defined as limited fitness changes following mutation, is an important aspect of many evolutionary processes. Strongly advantageous or deleterious mutations are detected using the synonymous to non-synonymous mutations ratio. However, there are currently no precise methods to estimate incremental selection. We here provide for the first time such a detailed method and show its precision in multiple cases of micro-evolution. The proposed method is a novel mixed lineage tree/sequence based method to detect within population selection as defined by the effect of mutations on the average number of offspring. Specifically, we propose to measure the log of the ratio between the number of leaves in lineage trees branches following synonymous and non-synonymous mutations. The method requires a high enough number of sequences, and a large enough number of independent mutations. It assumes that all mutations are independent events. It does not require of a baseline model and is practically not affected by sampling biases. We show the method's wide applicability by testing it on multiple cases of micro-evolution. We show that it can detect genes and inter-genic regions using the selection rate and detect selection pressures in viral proteins and in the immune response to pathogens.

Structure-Based Assignment of Ile, Leu, and Val Methyl Groups in the Active and Inactive Forms of the Mitogen-Activated Protein Kinase Extracellular Signal-Regulated Kinase 2

Resonance assignments are the first step in most NMR studies of protein structure, function, and dynamics. Standard protein assignment methods employ through-bond backbone experiments on uniformly (13)C/(15)N-labeled proteins. For larger proteins, this through-bond assignment procedure often breaks down due to rapid relaxation and spectral overlap. The challenges involved in studies of larger proteins led to efficient methods for (13)C labeling of side chain methyl groups, which have favorable relaxation properties and high signal-to-noise. These methyls are often still assigned by linking them to the previously assigned backbone, thus limiting the applications for larger proteins. Here, a structure-based procedure is described for assignment of (13)C(1)H3-labeled methyls by comparing distance information obtained from three-dimensional methyl-methyl nuclear Overhauser effect (NOE) spectroscopy with the X-ray structure. The Ile, Leu, or Val (ILV) methyl type is determined by through-bond experiments, and the methyl-methyl NOE data are analyzed in combination with the known structure. A hierarchical approach was employed that maps the largest observed "NOE-methyl cluster" onto the structure. The combination of identification of ILV methyl type with mapping of the NOE-methyl clusters greatly simplifies the assignment process. This method was applied to the inactive and active forms of the 42-kDa ILV (13)C(1)H3-methyl labeled extracellular signal-regulated kinase 2 (ERK2), leading to assignment of 60% of the methyls, including 90% of Ile residues. A series of ILV to Ala mutants were analyzed, which helped confirm the assignments. These assignments were used to probe the local and long-range effects of ligand binding to inactive and active ERK2.

Determinants of the rate of protein sequence evolution

The rate and mechanism of protein sequence evolution have been central questions in evolutionary biology since the 1960s. Although the rate of protein sequence evolution depends primarily on the level of functional constraint, exactly what determines functional constraint has remained unclear. The increasing availability of genomic data has enabled much needed empirical examinations on the nature of functional constraint. These studies found that the evolutionary rate of a protein is predominantly influenced by its expression level rather than functional importance. A combination of theoretical and empirical analyses has identified multiple mechanisms behind these observations and demonstrated a prominent role in protein evolution of selection against errors in molecular and cellular processes.

Neutral Models of Microbiome Evolution

There has been an explosion of research on host-associated microbial communities (i.e.,microbiomes). Much of this research has focused on surveys of microbial diversities across a variety of host species, including humans, with a view to understanding how these microbiomes are distributed across space and time, and how they correlate with host health, disease, phenotype, physiology and ecology. Fewer studies have focused on how these microbiomes may have evolved. In this paper, we develop an agent-based framework to study the dynamics of microbiome evolution. Our framework incorporates neutral models of how hosts acquire their microbiomes, and how the environmental microbial community that is available to the hosts is assembled. Most importantly, our framework also incorporates a Wright-Fisher genealogical model of hosts, so that the dynamics of microbiome evolution is studied on an evolutionary timescale. Our results indicate that the extent of parental contribution to microbial availability from one generation to the next significantly impacts the diversity of microbiomes: the greater the parental contribution, the less diverse the microbiomes. In contrast, even when there is only a very small contribution from a constant environmental pool, microbial communities can remain highly diverse. Finally, we show that our models may be used to construct hypotheses about the types of processes that operate to assemble microbiomes over evolutionary time.

Viewing protein fitness landscapes through a next-gen lens

High-throughput sequencing has enabled many powerful approaches in biological research. Here, we review sequencing approaches to measure frequency changes within engineered mutational libraries subject to selection. These analyses can provide direct estimates of biochemical and fitness effects for all individual mutations across entire genes (and likely compact genomes in the near future) in genetically tractable systems such as microbes, viruses, and mammalian cells. The effects of mutations on experimental fitness can be assessed using sequencing to monitor time-dependent changes in mutant frequency during bulk competitions. The impact of mutations on biochemical functions can be determined using reporters or other means of separating variants based on individual activities (e.g., binding affinity for a partner molecule can be interrogated using surface display of libraries of mutant proteins and isolation of bound and unbound populations). The comprehensive investigation of mutant effects on both biochemical function and experimental fitness provide promising new avenues to investigate the connections between biochemistry, cell physiology, and evolution. We summarize recent findings from systematic mutational analyses; describe how they relate to a field rich in both theory and experimentation; and highlight how they may contribute to ongoing and future research into protein structure-function relationships, systems-level descriptions of cell physiology, and population-genetic inferences on the relative contributions of selection and drift.

Estimating the mutation load in human genomes

Next-generation sequencing technology has facilitated the discovery of millions of genetic variants in human genomes. A sizeable fraction of these variants are predicted to be deleterious. Here, we review the pattern of deleterious alleles as ascertained in genome sequencing data sets and ask whether human populations differ in their predicted burden of deleterious alleles - a phenomenon known as mutation load. We discuss three demographic models that are predicted to affect mutation load and relate these models to the evidence (or the lack thereof) for variation in the efficacy of purifying selection in diverse human genomes. We also emphasize why accurate estimation of mutation load depends on assumptions regarding the distribution of dominance and selection coefficients - quantities that remain poorly characterized for current genomic data sets.

Early hemorrhage triggers metabolic responses that build up during prolonged shock

Metabolic staging after trauma/hemorrhagic shock is a key driver of acidosis and directly relates to hypothermia and coagulopathy. Metabolic responses to trauma/hemorrhagic shock have been assayed through classic biochemical approaches or NMR, thereby lacking a comprehensive overview of the dynamic metabolic changes occurring after shock. Sprague-Dawley rats underwent progressive hemorrhage and shock. Baseline and postshock blood was collected, and late hyperfibrinolysis was assessed (LY30 >3%) in all of the tested rats. Extreme and intermediate time points were collected to assay the dynamic changes of the plasma metabolome via ultra-high performance liquid chromatography-mass spectrometry. Sham controls were used to determine whether metabolic changes could be primarily attributable to anesthesia and supine positioning. Early hemorrhage-triggered metabolic changes that built up progressively and became significant during sustained hemorrhagic shock. Metabolic phenotypes either resulted in immediate hypercatabolism, or late hypercatabolism, preceded by metabolic deregulation during early hemorrhage in a subset of rats. Hemorrhagic shock consistently promoted hyperglycemia, glycolysis, Krebs cycle, fatty acid, amino acid, and nitrogen metabolism (urate and polyamines), and impaired redox homeostasis. Early dynamic changes of the plasma metabolome are triggered by hemorrhage in rats. Future studies will determine whether metabolic subphenotypes observed in rats might be consistently observed in humans and pave the way for tailored resuscitative strategies.

Potential role of glutathione in evolution of thiol-based redox signaling sites in proteins

Cysteine is susceptible to a variety of modifications by reactive oxygen and nitrogen oxide species, including glutathionylation; and when two cysteines are involved, disulfide formation. Glutathione-cysteine adducts may be removed from proteins by glutaredoxin, whereas disulfides may be reduced by thioredoxin. Glutaredoxin is homologous to the disulfide-reducing thioredoxin and shares similar binding modes of the protein substrate. The evolution of these systems is not well characterized. When a single Cys is present in a protein, conjugation of the redox buffer glutathione may induce conformational changes, resulting in a simple redox switch that effects a signaling cascade. If a second cysteine is introduced into the sequence, the potential for disulfide formation exists. In favorable protein contexts, a bistable redox switch may be formed. Because of glutaredoxin's similarities to thioredoxin, the mutated protein may be immediately exapted into the thioredoxin-dependent redox cycle upon addition of the second cysteine. Here we searched for examples of protein substrates where the number of redox-active cysteine residues has changed throughout evolution. We focused on cross-strand disulfides (CSDs), the most common type of forbidden disulfide. We searched for proteins where the CSD is present, absent and also found as a single cysteine in protein orthologs. Three different proteins were selected for detailed study-CD4, ERO1, and AKT. We created phylogenetic trees, examining when the CSD residues were mutated during protein evolution. We posit that the primordial cysteine is likely to be the cysteine of the CSD which undergoes nucleophilic attack by thioredoxin. Thus, a redox-active disulfide may be introduced into a protein structure by stepwise mutation of two residues in the native sequence to Cys. By extension, evolutionary acquisition of structural disulfides in proteins can potentially occur via transition through a redox-active disulfide state.

Evolutionary genetics of insect innate immunity

Patterns of evolution in immune defense genes help to understand the evolutionary dynamics between hosts and pathogens. Multiple insect genomes have been sequenced, with many of them having annotated immune genes, which paves the way for a comparative genomic analysis of insect immunity. In this review, I summarize the current state of comparative and evolutionary genomics of insect innate immune defense. The focus is on the conserved and divergent components of immunity with an emphasis on gene family evolution and evolution at the sequence level; both population genetics and molecular evolution frameworks are considered.

Asymmetric Context-Dependent Mutation Patterns Revealed through Mutation-Accumulation Experiments

Despite the general assumption that site-specific mutation rates are independent of the local sequence context, a growing body of evidence suggests otherwise. To further examine context-dependent patterns of mutation, we amassed 5,645 spontaneous mutations in wild- type (WT) and mismatch-repair deficient (MMR(-)) mutation-accumulation (MA) lines of the gram-positive model organism Bacillus subtilis. We then analyzed>7,500 spontaneous base-substitution mutations across B. subtilis, Escherichia coli, and Mesoplasma florum WT and MMR(-) MA lines, finding a context-dependent mutation pattern that is asymmetric around the origin of replication. Different neighboring nucleotides can alter site-specific mutation rates by as much as 75-fold, with sites neighboring G:C base pairs or dimers involving alternating pyrimidine-purine and purine-pyrimidine nucleotides having significantly elevated mutation rates. The influence of context-dependent mutation on genome architecture is strongest in M. florum, consistent with the reduced efficiency of selection in organisms with low effective population size. If not properly accounted for, the disparities arising from patterns of context-dependent mutation can significantly influence interpretations of positive and purifying selection.

LocSigDB: a database of protein localization signals

LocSigDB (http://genome.unmc.edu/LocSigDB/) is a manually curated database of experimental protein localization signals for eight distinct subcellular locations; primarily in a eukaryotic cell with brief coverage of bacterial proteins. Proteins must be localized at their appropriate subcellular compartment to perform their desired function. Mislocalization of proteins to unintended locations is a causative factor for many human diseases; therefore, collection of known sorting signals will help support many important areas of biomedical research. By performing an extensive literature study, we compiled a collection of 533 experimentally determined localization signals, along with the proteins that harbor such signals. Each signal in the LocSigDB is annotated with its localization, source, PubMed references and is linked to the proteins in UniProt database along with the organism information that contain the same amino acid pattern as the given signal. From LocSigDB webserver, users can download the whole database or browse/search for data using an intuitive query interface. To date, LocSigDB is the most comprehensive compendium of protein localization signals for eight distinct subcellular locations. Database URL: http://genome.unmc.edu/LocSigDB/

Non-coding RNA: what is functional and what is junk?

The genomes of large multicellular eukaryotes are mostly comprised of non-protein coding DNA. Although there has been much agreement that a small fraction of these genomes has important biological functions, there has been much debate as to whether the rest contributes to development and/or homeostasis. Much of the speculation has centered on the genomic regions that are transcribed into RNA at some low level. Unfortunately these RNAs have been arbitrarily assigned various names, such as “intergenic RNA,” “long non-coding RNAs” etc., which have led to some confusion in the field. Many researchers believe that these transcripts represent a vast, unchartered world of functional non-coding RNAs (ncRNAs), simply because they exist. However, there are reasons to question this Panglossian view because it ignores our current understanding of how evolution shapes eukaryotic genomes and how the gene expression machinery works in eukaryotic cells. Although there are undoubtedly many more functional ncRNAs yet to be discovered and characterized, it is also likely that many of these transcripts are simply junk. Here, we discuss how to determine whether any given ncRNA has a function. Importantly, we advocate that in the absence of any such data, the appropriate null hypothesis is that the RNA in question is junk.

Identification and computational analysis of gene regulatory elements

Over the last two decades, advances in experimental and computational technologies have greatly facilitated genomic research. Next-generation sequencing technologies have made de novo sequencing of large genomes affordable, and powerful computational approaches have enabled accurate annotations of genomic DNA sequences. Charting functional regions in genomes must account for not only the coding sequences, but also noncoding RNAs, repetitive elements, chromatin states, epigenetic modifications, and gene regulatory elements. A mix of comparative genomics, high-throughput biological experiments, and machine learning approaches has played a major role in this truly global effort. Here we describe some of these approaches and provide an account of our current understanding of the complex landscape of the human genome. We also present overviews of different publicly available, large-scale experimental data sets and computational tools, which we hope will prove beneficial for researchers working with large and complex genomes.

Empirically founded genotype-phenotype maps from mammalian cyclic nucleotide-gated ion channels

A major barrier between evolutionary and functional biology is the difficulty of determining appropriate genotype-phenotype-fitness maps, particularly in metazoans. Concrete perspectives towards unifying these approaches are offered by studies on the physiological systems that depend on ion channel dynamics. I focus on the cyclic nucleotide-gated (CNG) channels implicated in the photoreceptor's response to light. From an evolutionary standpoint, sensory systems offers interpretative advantages, as the relation between the sensory response and environment is relatively straightforward. For CNG and other ion channels, extensive data are available about the physiological consequences of scanning mutagenesis on sensitive protein domains, such as the conduction pore. Mutant ion channels can be easily studied in living cells, so that the relation between genotypes and phenotypes is less speculative than usual. By relying on relatively simple theoretical frameworks, I used these data to relate the sequence space with phenotypes at increasing hierarchical levels. These empirical genotype-phenotype and phenotype-phenotype landscapes became smoother at higher integration levels, especially in heterozygous condition. The epistatic interaction between sites was analyzed from double mutant constructs. Magnitude epistasis was common. Moreover, evidence of reciprocal sign epistasis and the presence of permissive mutations were also observed, which suggest how adaptive regions can be connected across maladaptive valleys. The approach I describe suggests a way to better relate the evolutionary dynamics with the underlying physiology.

Allelic richness following population founding events--a stochastic modeling framework incorporating gene flow and genetic drift

Allelic richness (number of alleles) is a measure of genetic diversity indicative of a population's long-term potential for adaptability and persistence. It is used less commonly than heterozygosity as a genetic diversity measure, partially because it is more mathematically difficult to take into account the stochastic process of genetic drift for allelic richness. This paper presents a stochastic model for the allelic richness of a newly founded population experiencing genetic drift and gene flow. The model follows the dynamics of alleles lost during the founder event and simulates the effect of gene flow on maintenance and recovery of allelic richness. The probability of an allele's presence in the population was identified as the relevant statistical property for a meaningful interpretation of allelic richness. A method is discussed that combines the probability of allele presence with a population's allele frequency spectrum to provide predictions for allele recovery. The model's analysis provides insights into the dynamics of allelic richness following a founder event, taking into account gene flow and the allele frequency spectrum. Furthermore, the model indicates that the “One Migrant per Generation” rule, a commonly used conservation guideline related to heterozygosity, may be inadequate for addressing preservation of diversity at the allelic level. This highlights the importance of distinguishing between heterozygosity and allelic richness as measures of genetic diversity, since focusing merely on the preservation of heterozygosity might not be enough to adequately preserve allelic richness, which is crucial for species persistence and evolution.

Sequence divergence and diversity suggests ongoing functional diversification of vertebrate NAD metabolism

NAD is not only an important cofactor in redox reactions but has also received attention in recent years because of its physiological importance in metabolic regulation, DNA repair and signaling. In contrast to the redox reactions, these regulatory processes involve degradation of NAD and therefore necessitate a constant replenishment of its cellular pool. NAD biosynthetic enzymes are common to almost all species in all clades, but the number of NAD degrading enzymes varies substantially across taxa. In particular, vertebrates, including humans, have a manifold of NAD degrading enzymes which require a high turnover of NAD. As there is currently a lack of a systematic study of how natural selection has shaped enzymes involved in NAD metabolism we conducted a comprehensive evolutionary analysis based on intraspecific variation and interspecific divergence. We compare NAD biosynthetic and degrading enzymes in four eukaryotic model species and subsequently focus on human NAD metabolic enzymes and their orthologs in other vertebrates. We find that the majority of enzymes involved in NAD metabolism are subject to varying levels of purifying selection. While NAD biosynthetic enzymes appear to experience a rather high level of evolutionary constraint, there is evidence for positive selection among enzymes mediating NAD-dependent signaling. This is particularly evident for members of the PARP family, a diverse protein family involved in DNA damage repair and programmed cell death. Based on haplotype information and substitution rate analysis we pinpoint sites that are potential targets of positive selection. We also link our findings to a three dimensional structure, which suggests that positive selection occurs in domains responsible for DNA binding and polymerization rather than the NAD catalytic domain. Taken together, our results indicate that vertebrate NAD metabolism is still undergoing functional diversification.

The evolution of pentameric ligand-gated ion-channels and the changing family of anthelmintic drug targets

SUMMARY Pentameric ligand-gated ion-channels rapidly transduce synaptic neurotransmitter signals to an electrical response in post-synaptic neuronal or muscle cells and control the neuromusculature of a majority of multicellular animals. A wide range of pharmaceuticals target these receptors including ethanol, nicotine, anti-depressants and other mood regulating drugs, compounds that control pain and mobility and are targeted by a majority of anthelmintic drugs used to control parasitic infection of humans and livestock. Major advances have been made in recent years to our understanding of the structure, function, activity and the profile of compounds that can activate specific receptors. It is becoming clear that these anthelmintic drug targets are not fixed, but differ in significant details from one nematode species to another. Here we review what is known about the evolution of the pentameric ligand-gated ion-channels, paying particular attention to the nematodes, how we can infer the origins of such receptors and understand the factors that determine how they change both over time and from one species to another. Using this knowledge provides a biological framework in which to understand these important drug targets and avenues to identify new receptors and aid the search for new anthelmintic drugs.

A single aromatic core mutation converts a designed "primitive" protein from halophile to mesophile folding

The halophile environment has a number of compelling aspects with regard to the origin of structured polypeptides (i.e., proteogenesis) and, instead of a curious niche that living systems adapted into, the halophile environment is emerging as a candidate "cradle" for proteogenesis. In this viewpoint, a subsequent halophile-to-mesophile transition was a key step in early evolution. Several lines of evidence indicate that aromatic amino acids were a late addition to the codon table and not part of the original "prebiotic" set comprising the earliest polypeptides. We test the hypothesis that the availability of aromatic amino acids could facilitate a halophile-to-mesophile transition by hydrophobic core-packing enhancement. The effects of aromatic amino acid substitutions were evaluated in the core of a "primitive" designed protein enriched for the 10 prebiotic amino acids (A,D,E,G,I,L,P,S,T,V)-having an exclusively prebiotic core and requiring halophilic conditions for folding. The results indicate that a single aromatic amino acid substitution is capable of eliminating the requirement of halophile conditions for folding of a "primitive" polypeptide. Thus, the availability of aromatic amino acids could have facilitated a critical halophile-to-mesophile protein folding adaptation-identifying a selective advantage for the incorporation of aromatic amino acids into the codon table.

Modeling evolution using the probability of fixation: history and implications

Many models of evolution calculate the rate of evolution by multiplying the rate at which new mutations originate within a population by a probability of fixation. Here we review the historical origins, contemporary applications, and evolutionary implications of these "origin-fixation" models, which are widely used in evolutionary genetics, molecular evolution, and phylogenetics. Origin-fixation models were first introduced in 1969, in association with an emerging view of "molecular" evolution. Early origin-fixation models were used to calculate an instantaneous rate of evolution across a large number of independently evolving loci; in the 1980s and 1990s, a second wave of origin-fixation models emerged to address a sequence of fixation events at a single locus. Although origin fixation models have been applied to a broad array of problems in contemporary evolutionary research, their rise in popularity has not been accompanied by an increased appreciation of their restrictive assumptions or their distinctive implications. We argue that origin-fixation models constitute a coherent theory of mutation-limited evolution that contrasts sharply with theories of evolution that rely on the presence of standing genetic variation. A major unsolved question in evolutionary biology is the degree to which these models provide an accurate approximation of evolution in natural populations.

General trends in selectively driven codon usage biases in the domain archaea

Since the advent of rapid techniques for sequencing DNA in the mid 70's, it became clear that all codons coding for the same amino acid are not used according to neutral expectations. In the last 30 years, several theories were proposed for explaining this fact. However, the most important concepts were the result of analyses carried out in Bacteria, and unicellular and multicellular eukaryotes like mammals (in other words, in two of the three Domains of life). In this communication, we study the main forces that shape codon usage in Archaeae under an evolutionary perspective. This is important because, as known, the orthologous genes related with the informational system in this Domain (replication, transcription and translation) are more similar to eukaryotes than to Bacteria. Our results show that the effect of selection acting at the level of translation is present in the Domain but mainly restricted to only a phylum (Euryarchaeota) and therefore is not as extended as in Bacteria. Besides, we describe the phylogenetic distribution of translational optimal codons and estimate the effect of selection acting at the level of accuracy. Finally, we discuss these results under some peculiarities that characterize this Domain.

Deleterious passengers in adapting populations

Most new mutations are deleterious and are eventually eliminated by natural selection. But in an adapting population, the rapid amplification of beneficial mutations can hinder the removal of deleterious variants in nearby regions of the genome, altering the patterns of sequence evolution. Here, we analyze the interactions between beneficial "driver" mutations and linked deleterious "passengers" during the course of adaptation. We derive analytical expressions for the substitution rate of a deleterious mutation as a function of its fitness cost, as well as the reduction in the beneficial substitution rate due to the genetic load of the passengers. We find that the fate of each deleterious mutation varies dramatically with the rate and spectrum of beneficial mutations and the deleterious substitution rate depends nonmonotonically on the population size and the rate of adaptation. By quantifying this dependence, our results allow us to estimate which deleterious mutations will be likely to fix and how many of these mutations must arise before the progress of adaptation is significantly reduced.

Extensive translation of small Open Reading Frames revealed by Poly-Ribo-Seq

Thousands of small Open Reading Frames (smORFs) with the potential to encode small peptides of fewer than 100 amino acids exist in our genomes. However, the number of smORFs actually translated, and their molecular and functional roles are still unclear. In this study, we present a genome-wide assessment of smORF translation by ribosomal profiling of polysomal fractions in Drosophila. We detect two types of smORFs bound by multiple ribosomes and thus undergoing productive translation. The ‘longer’ smORFs of around 80 amino acids resemble canonical proteins in translational metrics and conservation, and display a propensity to contain transmembrane motifs. The ‘dwarf’ smORFs are in general shorter (around 20 amino-acid long), are mostly found in 5′-UTRs and non-coding RNAs, are less well conserved, and have no bioinformatic indicators of peptide function. Our findings indicate that thousands of smORFs are translated in metazoan genomes, reinforcing the idea that smORFs are an abundant and fundamental genome component.

DOI:http://dx.doi.org/10.7554/eLife.03528.001

To produce a protein, a stretch of DNA must first be transcribed to produce a molecule of messenger RNA (mRNA). The genetic information copied from the DNA is then read three letters at a time, in groups called codons. Each codon either encodes a particular amino acid to be added into a protein or provides further instructions: ‘start codons’ mark the beginning of a protein; ‘stop codons’ mark its end. The DNA between these two points is called an open reading frame (or ORF)—however, not all ORFs produce proteins.

Most proteins are made of several hundred amino acids, but the genomes of animals contain thousands of ORFs that would generate much smaller proteins made of fewer than 100 amino acids, if they were translated. It is, however, unclear how many of these small ORFs are converted into mRNA molecules and functional proteins.

Ribosomes are large molecular machines that translate the code in mRNA molecules and join together the appropriate amino acids in the right order to make a protein. Ribosome profiling is a technique that identifies which mRNA molecules are translated into proteins by determining the sequences of all the mRNA molecules bound to ribosomes at a particular moment. The mRNA sequences can then be compared with the sequence of the whole genome to work out which ORFs they correspond to. Ribosome profiling has been used to detect translated small ORFs, but the method yields a relatively high false positive rate as some mRNAs can bind to ribosomes without being translated.

To better detect small protein-producing ORFs, Aspden et al. developed a technique based on ribosome profiling called Poly-Ribo-Seq. The method takes advantage of the fact that during active translation, clusters of multiple ribosomes, called polysomes, bind mRNAs. Poly-Ribo-Seq isolates these polysomes and determines the sequence bound by each of the ribosomes, thereby reducing the number of false positives.

Applying Poly-Ribo-Seq to cells from the fruit fly Drosophila allowed Aspden et al. to identify two types of short ORF. The first type codes for proteins that are around 80 amino acids long and are translated with the same efficiency as larger ORFs. The sequences of these ORFs are found in other species, match at least in part sequences of known functional ORFs, and the proteins produced are found in specific locations inside cells. These small proteins may contribute to membrane integrity or function. Together, these properties suggest that these mRNAs create functional small proteins.

The second pool consists of very small ORFs (‘dwarf smORFs’) that code for around 20 amino acids, which are not translated so often and do not show many similarities with other species.

As the findings of Aspden et al. suggest that a large fraction of Drosophila small ORFs are translated into proteins, the next challenge will be to determine the roles of these small proteins in cells.

DOI:http://dx.doi.org/10.7554/eLife.03528.002

Uncovering adaptive evolution in the human lineage

BACKGROUND

The recent increase in human polymorphism data, together with the availability of genome sequences from several primate species, provides an unprecedented opportunity to investigate how natural selection has shaped human evolution.

RESULTS

We compared human branch-specific substitutions with variation data in the current human population to measure the impact of adaptive evolution on human protein coding genes. The use of single nucleotide polymorphisms (SNPs) with high derived allele frequencies (DAFs) minimized the influence of segregating slightly deleterious mutations and improved the estimation of the number of adaptive sites. Using DAF ≥ 60% we showed that the proportion of adaptive substitutions is 0.2% in the complete gene set. However, the percentage rose to 40% when we focused on genes that are specifically accelerated in the human branch with respect to the chimpanzee branch, or on genes that show signatures of adaptive selection at the codon level by the maximum likelihood based branch-site test. In general, neural genes are enriched in positive selection signatures. Genes with multiple lines of evidence of positive selection include taxilin beta, which is involved in motor nerve regeneration and syntabulin, and is required for the formation of new presynaptic boutons.

CONCLUSIONS

We combined several methods to detect adaptive evolution in human coding sequences at a genome-wide level. The use of variation data, in addition to sequence divergence information, uncovered previously undetected positive selection signatures in neural genes.

Systematic exploration of ubiquitin sequence, E1 activation efficiency, and experimental fitness in yeast

The complexity of biological interaction networks poses a challenge to understanding the function of individual connections in the overall network. To address this challenge, we developed a high-throughput reverse engineering strategy to analyze how thousands of specific perturbations (encompassing all point mutations in a central gene) impact both a specific edge (interaction to a directly connected node) and an overall network function. We analyzed the effects of ubiquitin mutations on activation by the E1 enzyme and compared these to effects on yeast growth rate. Using this approach, we delineated ubiquitin mutations that selectively impacted the ubiquitin-E1 edge. We find that the elasticity function relating the efficiency of ubiquitin-E1 interaction to growth rate is non-linear and that a greater than 50-fold decrease in E1 activation efficiency is required to reduce growth rate by 2-fold. Despite the robustness of fitness to decreases in E1 activation efficiency, the effects of most ubiquitin mutations on E1 activation paralleled the effects on growth rate. Our observations indicate that most ubiquitin mutations that disrupt E1 activation also disrupt other functions. The structurally characterized ubiquitin-E1 interface encompasses the interfaces of ubiquitin with most other known binding partners, and we propose that this enables E1 in wild-type cells to selectively activate ubiquitin protein molecules capable of binding to other partners from the cytoplasmic pool of ubiquitin protein that will include molecules with chemical damage and/or errors from transcription and translation.

Epistatically interacting substitutions are enriched during adaptive protein evolution

Most experimental studies of epistasis in evolution have focused on adaptive changes—but adaptation accounts for only a portion of total evolutionary change. Are the patterns of epistasis during adaptation representative of evolution more broadly? We address this question by examining a pair of protein homologs, of which only one is subject to a well-defined pressure for adaptive change. Specifically, we compare the nucleoproteins from human and swine influenza. Human influenza is under continual selection to evade recognition by acquired immune memory, while swine influenza experiences less such selection due to the fact that pigs are less likely to be infected with influenza repeatedly in a lifetime. Mutations in some types of immune epitopes are therefore much more strongly adaptive to human than swine influenza—here we focus on epitopes targeted by human cytotoxic T lymphocytes. The nucleoproteins of human and swine influenza possess nearly identical numbers of such epitopes. However, mutations in these epitopes are fixed significantly more frequently in human than in swine influenza, presumably because these epitope mutations are adaptive only to human influenza. Experimentally, we find that epistatically constrained mutations are fixed only in the adaptively evolving human influenza lineage, where they occur at sites that are enriched in epitopes. Overall, our results demonstrate that epistatically interacting substitutions are enriched during adaptation, suggesting that the prevalence of epistasis is dependent on the underlying evolutionary forces at play.

Mutations can fix during evolution for two reasons: they can be beneficial and fix for adaptive reasons, or they can be neutral or deleterious and fix solely by chance. Most studies focus on adaptation, where the evolving population is increasing in fitness due to a new selection pressure. Such studies have found an important evolutionary role for epistasis, the phenomenon where the effect of one mutation depends on another mutation. But adaptation only accounts for a fraction of overall evolutionary change. Here we investigate whether epistasis is as common during non-adaptive as adaptive evolution. We do this by comparing the same protein from human and swine influenza. Human influenza is constantly adapting to escape from the immunity that people acquire from previous influenza infections. But swine influenza is under less pressure to escape from acquired immunity since pigs have shorter lifetimes and are less likely to be infected with influenza multiple times. We find that epistasis is less common during the evolution of the swine influenza protein than its human influenza counterpart. Overall, our results suggest that mutations that interact via epistasis are more likely to fix during adaptive evolution.

Neutral theory and the species abundance distribution: recent developments and prospects for unifying niche and neutral perspectives

Published in 2001, The Unified Neutral Theory of Biodiversity and Biogeography (UNTB) emphasizes the importance of stochastic processes in ecological community structure, and has challenged the traditional niche-based view of ecology. While neutral models have since been applied to a broad range of ecological and macroecological phenomena, the majority of research relating to neutral theory has focused exclusively on the species abundance distribution (SAD). Here, we synthesize the large body of work on neutral theory in the context of the species abundance distribution, with a particular focus on integrating ideas from neutral theory with traditional niche theory. First, we summarize the basic tenets of neutral theory; both in general and in the context of SADs. Second, we explore the issues associated with neutral theory and the SAD, such as complications with fitting and model comparison, the underlying assumptions of neutral models, and the difficultly of linking pattern to process. Third, we highlight the advances in understanding of SADs that have resulted from neutral theory and models. Finally, we focus consideration on recent developments aimed at unifying neutral- and niche-based approaches to ecology, with a particular emphasis on what this means for SAD theory, embracing, for instance, ideas of emergent neutrality and stochastic niche theory. We put forward the argument that the prospect of the unification of niche and neutral perspectives represents one of the most promising future avenues of neutral theory research.

The empirical codon mutation matrix as a communication channel

BACKGROUND

A number of evolutionary models have been widely used for sequence alignment, phylogenetic tree reconstruction, and database searches. These models focus on how sets of independent substitutions between amino acids or codons derive one protein sequence from its ancestral sequence during evolution. In this paper, we regard the Empirical Codon Mutation (ECM) Matrix as a communication channel and compute the corresponding channel capacity.

RESULTS

The channel capacity of 4.1875 bit, which is needed to preserve the information determined by the amino acid distribution, is obtained with an exponential factor of 0.26 applied to the ECM matrix. Additionally, we have obtained the optimum capacity achieving codon distribution. Compared to the biological distribution, there is an obvious difference, however, the distribution among synonymous codons is preserved. More importantly, the results show that the biological codon distribution allows for a "transmission" at a rate very close to the capacity.

CONCLUSION

We computed an exponential factor for the ECM matrix that would still allow for preserving the genetic information given the redundancy that is present in the codon-to-amino acid mapping. This gives an insight how such a mutation matrix relates to the preservation of a species in an information-theoretic sense.

Comparative population genomics: power and principles for the inference of functionality

The availability of sequenced genomes from multiple related organisms allows the detection and localization of functional genomic elements based on the idea that such elements evolve more slowly than neutral sequences. Although such comparative genomics methods have proven useful in discovering functional elements and ascertaining levels of functional constraint in the genome as a whole, here we outline limitations intrinsic to this approach that cannot be overcome by sequencing more species. We argue that it is essential to supplement comparative genomics with ultra-deep sampling of populations from closely related species to enable substantially more powerful genomic scans for functional elements. The convergence of sequencing technology and population genetics theory has made such projects feasible and has exciting implications for functional genomics.

Dynamic New World: Refining Our View of Protein Structure, Function and Evolution

Proteins are crucial to the functioning of all lifeforms. Traditional understanding posits that a single protein occupies a single structure ("fold"), which performs a single function. This view is radically challenged with the recognition that high structural dynamism-the capacity to be extra "floppy"-is more prevalent in functional proteins than previously assumed. As reviewed here, this dynamic take on proteins affects our understanding of protein "structure", function, and evolution, and even gives us a glimpse into protein origination. Specifically, this review will discuss historical developments concerning protein structure, and important new relationships between dynamism and aspects of protein sequence, structure, binding modes, binding promiscuity, evolvability, and origination. Along the way, suggestions will be provided for how key parts of textbook definitions-that so far have excluded membership to intrinsically disordered proteins (IDPs)-could be modified to accommodate our more dynamic understanding of proteins.

The synthesis paradigm in genetics

Experimental genetics with model organisms and mathematically explicit genetic theory are generally considered to be the major paradigms by which progress in genetics is achieved. Here I argue that this view is incomplete and that pivotal advances in genetics--and other fields of biology--are also made by synthesizing disparate threads of extant information rather than generating new information from experiments or formal theory. Because of the explosive expansion of information in numerous "-omics" data banks, and the fragmentation of genetics into numerous subdisciplines, the importance of the synthesis paradigm will likely expand with time.

Purification and partial characterization of vitellogenin from spotted wolffish (Anarhichas minor) and development of an enzyme-linked immunosorbent assay for the determination of gender and sexual maturity

Vitellogenin (VTG) from spotted wolffish, Anarhichas minor, a candidate species for cold-water marine aquaculture, was purified by MgCl₂/EDTA precipitation followed by a two-step chromatographic procedure. VTG had an apparent molecular mass of 470 kDa, as determined by gel filtration, and an amino acid composition similar to those of other teleosts. Sodium dodecyl sulfate polyacrylamide gel electrophoresis analysis of the purified VTG revealed a major band with a relative molecular weight of 166 kDa and some minor bands. Spotted wolffish VTG (sw-VTG) is relatively robust to in vitro degradation, as shown when samples of purified VTG and plasma from mature females subjected to various storage conditions or multiple freeze/thaw cycles were analyzed by Western blot. We developed an indirect competitive enzyme-linked immunosorbent assay (ELISA) using an antibody against Atlantic wolffish (Anarhichas lupus) VTG and purified sw-VTG. The ELISA had a detection limit of 6.7 ng/ml and a working range of 16.2-787.5 ng/ml, with intra- and inter-assay coefficients of variation ranging from 1.5 to 7.3 % and 7.1 to 14.3 %, respectively. The assay could distinguish males from immature females and discriminate maturing females at different stage of oocyte development. These results suggest that the sw-VTG ELISA would be useful in spotted wolffish aquaculture to determine sex and monitor female maturation.

Mendelian-mutationism: the forgotten evolutionary synthesis

According to a classical narrative, early geneticists, failing to see how Mendelism provides the missing pieces of Darwin's theory, rejected gradual changes and advocated an implausible yet briefly popular view of evolution-by-mutation; after decades of delay (in which synthesis was prevented by personal conflicts, disciplinary rivalries, and anti-Darwinian animus), Darwinism emerged on a new Mendelian basis. Based on the works of four influential early geneticists - Bateson, de Vries, Morgan and Punnett -, and drawing on recent scholarship, we offer an alternative that turns the classical view on its head. For early geneticists, embracing discrete inheritance and the mutation theory (for the origin of hereditary variation) did not entail rejection of selection, but rejection of Darwin's non-Mendelian views of heredity and variation, his doctrine of naturanon facitsaltum, and his conception of "natural selection" as a creative force that shapes features out of masses of infinitesimal differences. We find no evidence of a delay in synthesizing mutation, rules of discrete inheritance, and selection in a Mendelian-Mutationist Synthesis. Instead, before 1918, early geneticists had conceptualized allelic selection, the Hardy-Weinberg equilibrium, the evolution of a quantitative trait under selection, the probability of fixation of a new mutation, and other key innovations. Contemporary evolutionary thinking seems closer to their more ecumenical view than to the restrictive mid-twentieth-century consensus known as the Modern Synthesis.

Mutational effects on stability are largely conserved during protein evolution

Protein stability and folding are the result of cooperative interactions among many residues, yet phylogenetic approaches assume that sites are independent. This discrepancy has engendered concerns about large evolutionary shifts in mutational effects that might confound phylogenetic approaches. Here we experimentally investigate this issue by introducing the same mutations into a set of diverged homologs of the influenza nucleoprotein and measuring the effects on stability. We find that mutational effects on stability are largely conserved across the homologs. We reach qualitatively similar conclusions when we simulate protein evolution with molecular-mechanics force fields. Our results do not mean that proteins evolve without epistasis, which can still arise even when mutational stability effects are conserved. However, our findings indicate that large evolutionary shifts in mutational effects on stability are rare, at least among homologs with similar structures and functions. We suggest that properly describing the clearly observable and highly conserved amino acid preferences at individual sites is likely to be far more important for phylogenetic analyses than accounting for rare shifts in amino acid propensities due to site covariation.

Implications of HIV RNA structure for recombination, speciation, and the neutralism-selectionism controversy

The conflict between the needs to encode both a protein (impaired by non-synonymous mutation), and nucleic acid structure (impaired by synonymous or non-synonymous mutation), can sometimes be resolved in favour of the nucleic acid because its structure is critical for a selectively advantageous genome-wide activity--recombination. However, above a sequence difference threshold, recombination is impaired. It may then be advantageous for new species to arise. Building on the work of Grantham and others critical of the neutralist viewpoint, heuristic support for this hypothesis emerged from studies of the base composition and structure of retroviral genomes. The extreme enrichment in the purine A of the RNA of human immunodeficiency virus (HIV-1), parallels the mild purine-loading of the RNAs of most organisms, for which there is an adaptive explanation--immune evasion. However, human T cell leukaemia virus (HTLV-1), with the potential to invade the same host cell, shows extreme enrichment in the pyrimidine C. Assuming the low GC% HIV and the high GC% HTLV-1 to share a common ancestor, it was postulated that differences in GC% had arisen to prevent homologous recombination between these emerging lentiviral species. Sympatrically isolated by this intracellular reproductive barrier, prototypic HIV-1 seized the AU-rich (low GC%) high ground (thus committing to purine A rather than purine G). Prototypic HTLV-1 forwent this advantage and evolved an independent evolutionary strategy--similar to that of the GC%-rich Epstein-Barr virus--profound latency maintained by transcription of one purine-rich mRNA. The evidence supporting these interpretations is reviewed.

Direct measurements of human colon crypt stem cell niche genetic fidelity: the role of chance in non-darwinian mutation selection

Perfect human stem cell genetic fidelity would prevent aging and cancer. However, perfection would be difficult to achieve, and aging is universal and cancers common. A hypothesis is that because mutations are inevitable over a human lifetime, downstream mechanisms have evolved to manage the deleterious effects of beneficial and lethal mutations. In the colon, a crypt stem cell architecture reduces the number of mitotic cells at risk for mutation accumulation, and multiple niche stem cells ensure that a lethal mutation within any single stem cell does not lead to crypt death. In addition, the architecture of the colon crypt stem cell niche may harness probability or chance to randomly discard many beneficial mutations that might lead to cancer. An analysis of somatic chromosome copy number alterations (CNAs) reveals a lack of perfect fidelity in individual normal human crypts, with age-related increases and higher frequencies in ulcerative colitis, a proliferative, inflammatory disease. The age-related increase in somatic CNAs appears consistent with relatively normal replication error and cell division rates. Surprisingly, and similar to point mutations in cancer genomes, the types of crypt mutations were more consistent with random fixation rather than selection. In theory, a simple “non-Darwinian” way to nullify selection is to reduce the size of the reproducing population. Fates are more determined by chance rather than selection in very small populations, and therefore selection may be minimized within small crypt niches. The desired effect is that many beneficial mutations that might lead to cancer are randomly lost by drift rather than fixed by selection. The subdivision of the colon into multiple very small stem cell niches may trade Darwinian evolution for non-Darwinian somatic cell evolution, capitulating to aging but reducing cancer risks.

Amino acid composition of proteins reduces deleterious impact of mutations

The evolutionary origin of amino acid occurrence frequencies in proteins (composition) is not yet fully understood. We suggest that protein composition works alongside the genetic code to minimize impact of mutations on protein structure. First, we propose a novel method for estimating thermodynamic stability of proteins whose sequence is constrained to a fixed composition. Second, we quantify the average deleterious impact of substituting one amino acid with another. Natural proteome compositions are special in at least two ways: 1) Natural compositions do not generate more stable proteins than the average random composition, however, they result in proteins that are less susceptible to damage from mutations. 2) Natural proteome compositions that result in more stable proteins (i.e. those of thermophiles) are also tuned to have a higher tolerance for mutations. This is consistent with the observation that environmental factors selecting for more stable proteins also enhance the deleterious impact of mutations.

Pseudogenes and their composers: delving in the 'debris' of human genome

Pseudogenes, the nonfunctional homologs of functional genes and thus exemplified as 'genomic fossils' provide intriguing snapshots of the evolutionary history of human genome. These defunct copies generally arise by retrotransposition or duplication followed by various genetic disablements. In this study, focusing on human pseudogenes and their functional homologues we describe their characteristic features and relevance to protein sequence evolution. We recapitulate that pseudogenes harbor disease-causing degenerative sequence variations in conjunction with the immense disease gene association of their progenitors. Furthermore, we also discuss the issue of functional resurrection and the potentiality observed in some pseudogenes to regulate their functional counterparts.

Genome-wide patterns of codon bias are shaped by natural selection in the purple sea urchin, Strongylocentrotus purpuratus

Codon usage bias has been documented in a wide diversity of species, but the relative contributions of mutational bias and various forms of natural selection remain unclear. Here, we describe for the first time genome-wide patterns of codon bias at 4623 genes in the purple sea urchin, Strongylocentrotus purpuratus. Preferred codons were identified at 18 amino acids that exclusively used G or C at third positions, which contrasted with the strong AT bias of the genome (overall GC content is 36.9%). The GC content of third positions and coding regions exhibited significant correlations with the magnitude of codon bias. In contrast, the GC content of introns and flanking regions was indistinguishable from the genome-wide background, which suggested a limited contribution of mutational bias to synonymous codon usage. Five distinct clusters of genes were identified that had significantly different synonymous codon usage patterns. A significant correlation was observed between codon bias and mRNA expression supporting translational selection, but this relationship was driven by only one highly biased cluster that represented only 8.6% of all genes. In all five clusters preferred codons were evolutionarily conserved to a similar degree despite differences in their synonymous codon usage distributions and magnitude of codon bias. The third positions of preferred codons in two codon usage groups also paired significantly more often in stems than in loops of mRNA secondary structure predictions, which suggested that codon bias might also affect mRNA stability. Our results suggest that mutational bias has played a minor role in determining codon bias in S. purpuratus and that preferred codon usage may be heterogeneous across different genes and subject to different forms of natural selection.