Similar efficacies of selection shape mitochondrial and nuclear genes in Drosophila melanogaster and Homo sapiens

Similar efficacies of selection shape mitochondrial and nuclear genes in Drosophila melanogaster and Homo sapiens
Brandon S. Cooper, Chad Burrus, Chao Ji, Matthew W. Hahn, Kristi L. Montooth
doi: http://dx.doi.org/10.1101/010355

Deleterious mutations contribute to polymorphism even when selection effectively prevents their fixation. The efficacy of selection in removing deleterious mitochondrial mutations from populations depends on the effective population size (Ne) of the mtDNA, and the degree to which a lack of recombination magnifies the effects of linked selection. Using complete mitochondrial genomes from Drosophila melanogaster and nuclear data available from the same samples, we re-examine the hypothesis that non-recombining animal mtDNA harbor an excess of deleterious polymorphisms relative to the nuclear genome. We find no evidence of recombination in the mitochondrial genome, and the much-reduced level of mitochondrial synonymous polymorphism relative to nuclear genes is consistent with a reduction in Ne. Nevertheless, we find that the neutrality index (NI), a measure of the excess on nonsynonymous polymorphism relative to the neutral expectation, is not significantly different between mitochondrial and nuclear loci. Reanalysis of published data from Homo sapiens reveals the same lack of a difference between the two genomes, though small samples in previous studies had suggested a strong difference in both species. Thus, despite a smaller Ne, mitochondrial loci of both flies and humans appear to experience similar efficacies of selection as do loci in the recombining nuclear genome.

Recent evolution of the mutation rate and spectrum in Europeans

Recent evolution of the mutation rate and spectrum in Europeans
Kelley Harris
doi: http://dx.doi.org/10.1101/010314

As humans dispersed out of Africa, they adapted to new environmental challenges including changes in exposure to mutagenic solar radiation. This raises the possibility that different populations experienced different selective pressures affecting genome integrity. Prior work has uncovered divergent selection in tropical versus temperate latitudes on eQTLs that regulate the DNA damage response, as well as evidence that the human mutation rate per year has changed at least 2-fold since we shared a common ancestor with chimpanzees. Here, I present evidence that the rate of a particular mutation type has recently increased in the European lineage, rising in frequency by 50% during the 30,000–50,000 years since Europeans diverged from Asians. A comparison of single nucleotide polymorphisms (SNPs) private to Africa, Asia, and Europe in the 1000 Genomes data reveals that private European variation is enriched for the transition 5’-TCC-3’→5’-TTC-3’. Although it is not clear whether UV played a causal role in the changing the European mutational spectrum, 5’-TCC-3’→5’-TTC-3’ is known to be the most common somatic mutation present in melanoma skin cancers, as well as the mutation most frequently induced in vitro by UV. Regardless of its causality, this change indicates that DNA replication fidelity has not remained stable even since the origin of modern humans and might have changed numerous times during our recent evolutionary history.

Different tastes for different individuals

Different tastes for different individuals
Kohei Fujikura
doi: http://dx.doi.org/10.1101/009357

Individual taste differences were first reported in the first half of the 20th century, but the primary reasons for these differences have remained uncertain. Much of the taste variation among different mammalian species can be explained by pseudogenization of taste receptors. In this study, by analyzing 14 ethnically diverse populations, we investigated whether the most recent disruptions of taste receptor genes segregate with their intact forms. Our results revealed an unprecedented prevalence of segregating loss-of-function (LoF) taste receptor variants, identifying one of the most pronounced cases of functional population diversity in the human genome. LoF variant frequency was considerably higher than the overall mutation rate, and many humans harbored varying numbers of critical mutations. In particular, molecular evolutionary rates of sour and bitter receptors were far higher in humans than those of sweet, salty, and umami receptors compared with other carnivorous mammals although not all of the taste receptors genes were identified. Many LoF variants are population-specific, some of which arose even after the population differentiation, but not before divergence of the modern and archaic (Neanderthal and Denisovan) human. Based on these findings, we conclude that modern humans might have been losing their taste receptor genes because of high-frequency LoF taste receptor variants. Finally I actually demonstrated the genetic testing of taste receptors from personal exome sequence.

Changes in epistatic interactions in the long-term evolution of HIV-1 protease

Changes in epistatic interactions in the long-term evolution of HIV-1 protease

Aditi Gupta, Christoph Adami
(Submitted on 12 Aug 2014)

The human immuno-deficiency virus sub-type 1 (HIV-1) is evolving to keep up with a changing fitness landscape, due to the various drugs introduced to stop the virus’s replication. As the virus adapts, the information the virus encodes about its environment must change, and this change is reflected in the amino-acid composition of proteins, as well as changes in viral RNAs, binding sites, and splice sites. Information can also be encoded in the interaction between residues in a single protein as well as across proteins, leading to a change in the epistatic patterns that can affect how the virus can change in the future. Measuring epistasis usually requires fitness measurements that are difficult to obtain in high-throughput. Here we show that epistasis can be inferred from the pair-wise information between residues, and study how epistasis and information have changed over the long-term. Using HIV-1 protease sequence data from public databases covering the years 1998-2006 (from both treated and untreated subjects), we show that drug treatment has increased the protease’s per-site entropies on average. At the same time, the sum of mutual entropies across all pairs of residues within the protease shows a significant increase over the years, indicating an increase in epistasis in response to treatment, a trend not seen within sequences from untreated subjects. Our findings suggest that information theory can be an important tool to study long-term trends in the evolution of macromolecules.

V genes in primates from whole genome shotgun data

V genes in primates from whole genome shotgun data
David N Olivieri, Francisco Gambon-Deza

The adaptive immune system uses V genes for antigen recognition. The evolutionary diversification and selection processes within and across species and orders are poorly understood. Here, we studied the amino acid (AA) sequences obtained of translated in-frame V exons of immunoglobulins (IG) and T cell receptors (TR) from 16 primate species whose genomes have been sequenced. Multi-species comparative analysis supports the hypothesis that V genes in the IG loci undergo birth/death processes, thereby permitting rapid adaptability over evolutionary time. We also show that multiple cladistic groupings exist in the TRA (35 clades) and TRB (25 clades) V gene loci and that each primate species typically contributes at least one V gene to each of these clade. The results demonstrate that IG V genes and TR V genes have quite different evolutionary pathways; multiple duplications can explain the IG loci results, while co-evolutionary pressures can explain the phylogenetic results, as seen in genes of the TR loci. We describe how each of the 35 V genes clades of the TRA locus and 25 clades of the TRB locus must have specific and necessary roles for the viability of the species.

Author post: Predicting evolution from the shape of genealogical trees

This guest post by Richard Neher discusses his preprint Predicting evolution from the shape of genealogical trees. Richard A. Neher, Colin A. Russell, Boris I. Shraiman. arXived here. This is cross-posted from the Neher lab website.

In this preprint — a collaboration with Colin Russell and Boris Shraiman — we show that it is possible to predict which individual from a population is most closely related to future populations. To this end, we have developed a method that uses the branching pattern of genealogical trees to estimate which part of the tree contains the “fittest” sequences, where fit means rapidly multiplying. Those that multiply rapidly, are most likely to take over the population. We demonstrate the power of our method by predicting the evolution of seasonal influenza viruses.

How does it work?
Individuals adapt to a changing environment by accumulating beneficial mutations, while avoiding deleterious mutations. We model this process assuming that there are many such mutations which change fitness in small increments. Using this model, we calculate the probability that an individual that lived in the past at time t leaves n descendants in the present. This distributions depends critically on the fitness of the ancestral individual. We then extend this calculation to the probability of observing a certain branch in a genealogical tree reconstructed from a sample of sequences. A branch in a tree connects an individual A that lived at time tA and had fitness xA and with an individual B that lived at a later time tB with fitness xB as illustrated in the figure. B has descendants in the sample, otherwise the branch would not be part of the tree. Furthermore, all sampled descendants of A are also descendants of B, otherwise the connection between A and B would have branched between tA and tB. We call the mathematical object describing fitness evolution between A and B “branch propagator” and propagatordenote it by g(xB,tB|xA,tA). The joint probability distribution of fitness values of all nodes of the tree is given by a product of branch propagators. We then calculate the expected fitness of each node and use it to rank the sampled sequences. The top ranked sequence is our prediction for the sequence of the progenitor of the future population.

Why do we care?
flu_tree Being able to predict evolution could have immediate applications. The best example is the seasonal influenza vaccine, that needs to be updated frequently to keep up with the evolving virus. Vaccine strains are chosen among sampled virus strains, and the more closely this strain matches the future influenza virus population, the better the vaccine is going to be. Hence by predicting a likely progenitor of the future, our method could help to improve influenza vaccines. One of our predictions is shown in the figure, with the top ranked sequence marked by a black arrow. Influenza is not the only possible application. Since the algorithm only requires a reconstructed tree as input, it can be applied to other rapidly evolving pathogens or cancer cell populations. In addition, to being useful, the ability to predict also implies that the model captures an essential aspect of evolutionary dynamics: influenza evolution is to a substantial degree — enough to enable prediction — dependent on the accumulation of small effect mutations.

Comparison to other approaches
Given the importance of good influenza vaccines, there has been a number of previous efforts to anticipate influenza virus evolution, typically based on using patterns of molecular evolution from historical data. Along these lines, Luksza and Lässig have recently presented an explicit fitness model for influenza virus evolution that rewards mutations at positions known to convey antigenic novelty and penalizes likely deleterious mutations (+a few other things). By using molecular influenza specific signatures, this model is complementary to ours that uses only the tree reconstructed from nucleotide sequences. Interestingly, the two models do more or less equally well and combining different methods of prediction should result in more reliable results.

Sequence co-evolution gives 3D contacts and structures of protein complexes

Sequence co-evolution gives 3D contacts and structures of protein complexes
Thomas A. Hopf, Charlotta P.I. Schärfe, João P.G.L.M. Rodrigues, Anna G. Green, Chris Sander, Alexandre M.J.J. Bonvin, Debora S. Marks

High-throughput experiments in bacteria and eukaryotic cells have identified tens of thousands of interactions between proteins. This genome-wide view of the protein interaction universe is coarse-grained, whilst fine-grained detail of macro-molecular interactions critically depends on lower throughput, labor-intensive experiments. Computational approaches using measures of residue co-evolution across proteins show promise, but have been limited to specific interactions. Here we present a new generalized method showing that patterns of evolutionary sequence changes across proteins reflect residues that are close in space, with sufficient accuracy to determine the three-dimensional structure of the protein complexes. We demonstrate that the inferred evolutionary coupling scores accurately predict inter-protein residue interactions and can distinguish between interacting and non-interacting proteins. To illustrate the utility of the method, we predict co-evolved contacts between 50 E. coli complexes (of unknown structure), including the unknown 3D interactions between subunits of ATP synthase and find results consistent with detailed experimental data. We expect that the method can be generalized to genome-wide interaction predictions at residue resolution.