Predicting the Receptive Range of Olfactory Receptors

Although the family of genes encoding for olfactory receptors was identified more than 15 years ago, the difficulty of functionally expressing these receptors in an heterologous system has, with only some exceptions, rendered the receptive range of given olfactory receptors largely unknown. Furthermore, even when successfully expressed, the task of probing such a receptor with thousands of odors/ligands remains daunting. Here we provide proof of concept for a solution to this problem. Using computational methods, we tune an electronic nose to the receptive range of an olfactory receptor. We then use this electronic nose to predict the receptors' response to other odorants. Our method can be used to identify the receptive range of olfactory receptors, and can also be applied to other questions involving receptor–ligand interactions in non-olfactory settings

Patterns of intron gain and conservation in eukaryotic genes

<p>Abstract</p> <p>Background:</p> <p>The presence of introns in protein-coding genes is a universal feature of eukaryotic genome organization, and the genes of multicellular eukaryotes, typically, contain multiple introns, a substantial fraction of which share position in distant taxa, such as plants and animals. Depending on the methods and data sets used, researchers have reached opposite conclusions on the causes of the high fraction of shared introns in orthologous genes from distant eukaryotes. Some studies conclude that shared intron positions reflect, almost entirely, a remarkable evolutionary conservation, whereas others attribute it to parallel gain of introns. To resolve these contradictions, it is crucial to analyze the evolution of introns by using a model that minimally relies on arbitrary assumptions.</p> <p>Results:</p> <p>We developed a probabilistic model of evolution that allows for variability of intron gain and loss rates over branches of the phylogenetic tree, individual genes, and individual sites. Applying this model to an extended set of conserved eukaryotic genes, we find that parallel gain, on average, accounts for only ~8% of the shared intron positions. However, the distribution of parallel gains over the phylogenetic tree of eukaryotes is highly non-uniform. There are, practically, no parallel gains in closely related lineages, whereas for distant lineages, such as animals and plants, parallel gains appear to contribute up to 20% of the shared intron positions. In accord with these findings, we estimated that ancestral introns have a high probability to be retained in extant genomes, and conversely, that a substantial fraction of extant introns have retained their positions since the early stages of eukaryotic evolution. In addition, the density of sites that are available for intron insertion is estimated to be, approximately, one in seven basepairs.</p> <p>Conclusion:</p> <p>We obtained robust estimates of the contribution of parallel gain to the observed sharing of intron positions between eukaryotic species separated by different evolutionary distances. The results indicate that, although the contribution of parallel gains varies across the phylogenetic tree, the high level of intron position sharing is due, primarily, to evolutionary conservation. Accordingly, numerous introns appear to persist in the same position over hundreds of millions of years of evolution. This is compatible with recent observations of a negative correlation between the rate of intron gain and coding sequence evolution rate of a gene, suggesting that at least some of the introns are functionally relevant.</p

Homoplasy in genome-wide analysis of rare amino acid replacements: the molecular-evolutionary basis for Vavilov's law of homologous series

<p>Abstract</p> <p>Background</p> <p>Rare genomic changes (RGCs) that are thought to comprise derived shared characters of individual clades are becoming an increasingly important class of markers in genome-wide phylogenetic studies. Recently, we proposed a new type of RGCs designated RGC_CAMs (after Conserved Amino acids-Multiple substitutions) that were inferred using genome-wide identification of amino acid replacements that were: i) located in unambiguously aligned regions of orthologous genes, ii) shared by two or more taxa in positions that contain a different, conserved amino acid in a much broader range of taxa, and iii) require two or three nucleotide substitutions. When applied to animal phylogeny, the RGC_CAM approach supported the coelomate clade that unites deuterostomes with arthropods as opposed to the ecdysozoan (molting animals) clade. However, a non-negligible level of homoplasy was detected.</p> <p>Results</p> <p>We provide a direct estimate of the level of homoplasy caused by parallel changes and reversals among the RGC_CAMs using 462 alignments of orthologous genes from 19 eukaryotic species. It is shown that the impact of parallel changes and reversals on the results of phylogenetic inference using RGC_CAMs cannot explain the observed support for the Coelomata clade. In contrast, the evidence in support of the Ecdysozoa clade, in large part, can be attributed to parallel changes. It is demonstrated that parallel changes are significantly more common in internal branches of different subtrees that are separated from the respective common ancestor by relatively short times than in terminal branches separated by longer time intervals. A similar but much weaker trend was detected for reversals. The observed evolutionary trend of parallel changes is explained in terms of the covarion model of molecular evolution. As the overlap between the covarion sets in orthologous genes from different lineages decreases with time after divergence, the likelihood of parallel changes decreases as well.</p> <p>Conclusion</p> <p>The level of homoplasy observed here appears to be low enough to justify the utility of RGC_CAMs and other types of RGCs for resolution of hard problems in phylogeny. Parallel changes, one of the major classes of events leading to homoplasy, occur much more often in relatively recently diverged lineages than in those separated from their last common ancestor by longer time intervals of time. This pattern seems to provide the molecular-evolutionary underpinning of Vavilov's law of homologous series and is readily interpreted within the framework of the covarion model of molecular evolution.</p> <p>Reviewers</p> <p>This article was reviewed by Alex Kondrashov, Nicolas Galtier, and Maximilian Telford and Robert Lanfear (nominated by Laurence Hurst).</p

EREM: Parameter Estimation and Ancestral Reconstruction by Expectation-Maximization Algorithm for a Probabilistic Model of Genomic Binary Characters Evolution

Evolutionary binary characters are features of species or genes, indicating the absence (value zero) or presence (value one) of some property. Examples include eukaryotic gene architecture (the presence or absence of an intron in a particular locus), gene content, and morphological characters. In many studies, the acquisition of such binary characters is assumed to represent a rare evolutionary event, and consequently, their evolution is analyzed using various flavors of parsimony. However, when gain and loss of the character are not rare enough, a probabilistic analysis becomes essential. Here, we present a comprehensive probabilistic model to describe the evolution of binary characters on a bifurcating phylogenetic tree. A fast software tool, EREM, is provided, using maximum likelihood to estimate the parameters of the model and to reconstruct ancestral states (presence and absence in internal nodes) and events (gain and loss events along branches)

Lead in Archeological Human Bones Reflecting Historical Changes in Lead Production.

Forty years ago, in a seminal paper published in Science, Settle and Patterson used archeological and historical data to estimate the rates of worldwide lead production since the discovery of cupellation, approximately 5000 years ago. Here, we record actual lead exposure of a human population by direct measurements of the concentrations of lead in petrous bones of individuals representing approximately 12 000 years of inhabitation in Italy. This documentation of lead pollution throughout human history indicates that, remarkably, much of the estimated dynamics in lead production is replicated in human exposure. Thus, lead pollution in humans has closely followed anthropogenic lead production. This observation raises concerns that the forecasted increase in the production of lead and other metals might affect human health in the near future

System-wide Analysis of the T Cell Response

SummaryThe T cell receptor (TCR) controls the cellular adaptive immune response to antigens, but our understanding of TCR repertoire diversity and response to challenge is still incomplete. For example, TCR clones shared by different individuals with minimal alteration to germline gene sequences (public clones) are detectable in all vertebrates, but their significance is unknown. Although small in size, the zebrafish TCR repertoire is controlled by processes similar to those operating in mammals. Thus, we studied the zebrafish TCR repertoire and its response to stimulation with self and foreign antigens. We found that cross-reactive public TCRs dominate the T cell response, endowing a limited TCR repertoire with the ability to cope with diverse antigenic challenges. These features of vertebrate public TCRs might provide a mechanism for the rapid generation of protective T cell immunity, allowing a short temporal window for the development of more specific private T cell responses

Using Paleogenomics to Study the Evolution of Gene Families: Origin and Duplication History of the Relaxin Family Hormones and Their Receptors

Recent progress in the analysis of whole genome sequencing data has resulted in the emergence of paleogenomics, a field devoted to the reconstruction of ancestral genomes. Ancestral karyotype reconstructions have been used primarily to illustrate the dynamic nature of genome evolution. In this paper, we demonstrate how they can also be used to study individual gene families by examining the evolutionary history of relaxin hormones (RLN/INSL) and relaxin family peptide receptors (RXFP). Relaxin family hormones are members of the insulin superfamily, and are implicated in the regulation of a variety of primarily reproductive and neuroendocrine processes. Their receptors are G-protein coupled receptors (GPCR's) and include members of two distinct evolutionary groups, an unusual characteristic. Although several studies have tried to elucidate the origins of the relaxin peptide family, the evolutionary origin of their receptors and the mechanisms driving the diversification of the RLN/INSL-RXFP signaling systems in non-placental vertebrates has remained elusive. Here we show that the numerous vertebrate RLN/INSL and RXFP genes are products of an ancestral receptor-ligand system that originally consisted of three genes, two of which apparently trace their origins to invertebrates. Subsequently, diversification of the system was driven primarily by whole genome duplications (WGD, 2R and 3R) followed by almost complete retention of the ligand duplicates in most vertebrates but massive loss of receptor genes in tetrapods. Interestingly, the majority of 3R duplicates retained in teleosts are potentially involved in neuroendocrine regulation. Furthermore, we infer that the ancestral AncRxfp3/4 receptor may have been syntenically linked to the AncRln-like ligand in the pre-2R genome, and show that syntenic linkages among ligands and receptors have changed dynamically in different lineages. This study ultimately shows the broad utility, with some caveats, of incorporating paleogenomics data into understanding the evolution of gene families

On Predicting Responses to Mixtures in Quartz Microbalance

A fundamental question in studying odor patterns in electronic noses is how to estimate the response to a mixture, given the response curves of the pure chemicals. We study this question by proposing two mixture-predicting models, and verify them against real data collected using quartz microbalance sensors. We find that a simple additive law explains fairly well the measured response patterns of binary mixtures, but that a slightly more complicated mixing model is required in order to produce good estimations of the response patterns of mixtures that are comprised of more than two compounds

Visualization of Labeled Data Using Linear Transformations

We present a novel family of data-driven linear transformations, aimed at visualizing multivariate data in a low-dimensional space in a way that optimally preserves the structure of the data. The well-studied PCA and Fisher’s LDA are shown to be special members in this family of transformations, and we demonstrate how to generalize these two methods such as to enhance their performance. Furthermore, our technique is the only one, to the best of our knowledge, that reflects in the resulting embedding both the data coordinates and pairwise similarities and/or dissimilarities between the data elements. Even more so, when information on the clustering (labeling) decomposition of the data is known, this information can be integrated in the linear transformation, resulting in embeddings that clearly show the separation between the clusters, as well as their intra-structure. All this makes our technique very flexible and powerful, and lets us cope with kinds of data that other techniques fail to describe properly