Liran Carmel

The ecoresponsive genome of Daphnia pulex

The Daphnia genome reveals a multitude of genes and shows adaptation through gene family expansions. We describe the draft genome of the microcrustacean Daphnia pulex, which is only 200 megabases and contains at least 30,907 genes. The high gene count is a consequence of an elevated rate of gene duplication resulting in tandem gene clusters. More than a third of Daphnia’s genes have no detectable homologs in any other available proteome, and the most amplified gene families are specific to the Daphnia lineage. The coexpansion of gene families interacting within metabolic pathways suggests that the maintenance of duplicated genes is not random, and the analysis of gene expression under different environmental conditions reveals that numerous paralogs acquire divergent expression patterns soon after duplication. Daphnia-specific genes, including many additional loci within sequenced regions that are otherwise devoid of annotations, are the most responsive genes to ecological challenges.

Genome-wide Analysis of Substrate Specificities of the Escherichia coli Haloacid Dehalogenase-like Phosphatase Family

Haloacid dehalogenase (HAD)-like hydrolases are a vast superfamily of largely uncharacterized enzymes, with a few members shown to possess phosphatase, β-phosphoglucomutase, phosphonatase, and dehalogenase activities. Using a representative set of 80 phosphorylated substrates, we characterized the substrate specificities of 23 soluble HADs encoded in the Escherichia coli genome. We identified small molecule phosphatase activity in 21 HADs and β-phosphoglucomutase activity in one protein. The E. coli HAD phosphatases show high catalytic efficiency and affinity to a wide range of phosphorylated metabolites that are intermediates of various metabolic reactions. Rather than following the classical “one enzyme-one substrate” model, most of the E. coli HADs show remarkably broad and overlapping substrate spectra. At least 12 reactions catalyzed by HADs currently have no EC numbers assigned in Enzyme Nomenclature. Surprisingly, most HADs hydrolyzed small phosphodonors (acetyl phosphate, carbamoyl phosphate, and phosphoramidate), which also serve as substrates for autophosphorylation of the receiver domains of the two-component signal transduction systems. The physiological relevance of the phosphatase activity with the preferred substrate was validated in vivo for one of the HADs, YniC. Many of the secondary activities of HADs might have no immediate physiological function but could comprise a reservoir for evolution of novel phosphatases.

Origin and evolution of spliceosomal introns

Evolution of exon-intron structure of eukaryotic genes has been a matter of long-standing, intensive debate. The introns-early concept, later rebranded ‘introns first’ held that protein-coding genes were interrupted by numerous introns even at the earliest stages of lifes evolution and that introns played a major role in the origin of proteins by facilitating recombination of sequences coding for small protein/peptide modules. The introns-late concept held that introns emerged only in eukaryotes and new introns have been accumulating continuously throughout eukaryotic evolution. Analysis of orthologous genes from completely sequenced eukaryotic genomes revealed numerous shared intron positions in orthologous genes from animals and plants and even between animals, plants and protists, suggesting that many ancestral introns have persisted since the last eukaryotic common ancestor (LECA). Reconstructions of intron gain and loss using the growing collection of genomes of diverse eukaryotes and increasingly advanced probabilistic models convincingly show that the LECA and the ancestors of each eukaryotic supergroup had intron-rich genes, with intron densities comparable to those in the most intron-rich modern genomes such as those of vertebrates. The subsequent evolution in most lineages of eukaryotes involved primarily loss of introns, with only a few episodes of substantial intron gain that might have accompanied major evolutionary innovations such as the origin of metazoa. The original invasion of self-splicing Group II introns, presumably originating from the mitochondrial endosymbiont, into the genome of the emerging eukaryote might have been a key factor of eukaryogenesis that in particular triggered the origin of endomembranes and the nucleus. Conversely, splicing errors gave rise to alternative splicing, a major contribution to the biological complexity of multicellular eukaryotes. There is no indication that any prokaryote has ever possessed a spliceosome or introns in protein-coding genes, other than relatively rare mobile self-splicing introns. Thus, the introns-first scenario is not supported by any evidence but exon-intron structure of protein-coding genes appears to have evolved concomitantly with the eukaryotic cell, and introns were a major factor of evolution throughout the history of eukaryotes. This article was reviewed by I. King Jordan, Manuel Irimia (nominated by Anthony Poole), Tobias Mourier (nominated by Anthony Poole), and Fyodor Kondrashov. For the complete reports, see the Reviewers’ Reports section.

The Function of Introns

The intron–exon architecture of many eukaryotic genes raises the intriguing question of whether this unique organization serves any function, or is it simply a result of the spread of functionless introns in eukaryotic genomes. In this review, we show that introns in contemporary species fulfill a broad spectrum of functions, and are involved in virtually every step of mRNA processing. We propose that this great diversity of intronic functions supports the notion that introns were indeed selfish elements in early eukaryotes, but then independently gained numerous functions in different eukaryotic lineages. We suggest a novel criterion of evolutionary conservation, dubbed intron positional conservation, which can identify functional introns.

Robust linear dimensionality reduction

We present a novel family of data-driven linear transformations, aimed at finding low-dimensional embeddings of multivariate data, in a way that optimally preserves the structure of the data. The well-studied PCA and Fishers 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 relationships between the data elements. Even more so, when information on the clustering (labeling) decomposition of the data is known, this information can also be integrated in the linear transformation, resulting in embeddings that clearly show the separation between the clusters, as well as their internal structure. All of this makes our technique very flexible and powerful, and lets us cope with kinds of data that other techniques fail to describe properly.

ACE: a fast multiscale eigenvectors computation for drawing huge graphs

We present an extremely fast graph drawing algorithm for very large graphs, which we term ACE (for Algebraic multigrid Computation of Eigenvectors). ACE exhibits an improvement of something like two orders of magnitude over the fastest algorithms we are aware of; it draws graphs of millions of nodes in less than a minute. ACE finds an optimal drawing by minimizing a quadratic energy function. The minimization problem is expressed as a generalized eigenvalue problem, which is rapidly solved using a novel algebraic multigrid technique. The same generalized eigenvalue problem seems to come up also in other fields, hence ACE appears to be applicable outside of graph drawing too.

Potency and Fate Specification in CNS Stem Cell Populations In Vitro

To realize the promise of stem cell biology, it is important to identify the precise time in the history of the cell when developmental potential is restricted. To achieve this goal, we developed a real-time imaging system that captures the transitions in fate, generating neurons, astrocytes, and oligodendrocytes from single CNS stem cells in vitro. In the presence of bFGF, tripotent cells normally produce specified progenitors through a bipotent intermediate cell type. Surprisingly, the tripotent state is reset at each passage. The cytokine CNTF is thought to instruct multipotent cells to an astrocytic fate. We demonstrate that CNTF both directs astrogliogenesis from tripotent cells, bypassing two of the three normal bipotent intermediates, and later promotes the expansion of specified astrocytic progenitors. These results show how discrete cell types emerge from a multipotent cell and provide a strong basis for future studies to determine the molecular basis of fate specification.

Reconstructing the DNA Methylation Maps of the Neandertal and the Denisovan

Methylating the Family Tree DNA sequences show a high level of similarities between humans and ancient hominids but the degree to which there are differences between methylated regions in their genomes that may explain phenotypic differences is unclear. Gokhman et al. (p. 523, published online 17 April) demonstrate that naturally degraded methylated cytosines in ancient DNA are converted to thymines and can be used to reconstruct ancient methylomes. The results suggest differences in methylation in bone tissues between modern humans and ancient hominids in a set of genes important for limb development. Estimates of differentially methylated nucleotides illuminate differences between modern human and ancient hominid bones. Ancient DNA sequencing has recently provided high-coverage archaic human genomes. However, the evolution of epigenetic regulation along the human lineage remains largely unexplored. We reconstructed the full DNA methylation maps of the Neandertal and the Denisovan by harnessing the natural degradation processes of methylated and unmethylated cytosines. Comparing these ancient methylation maps to those of present-day humans, we identified ~2000 differentially methylated regions (DMRs). Particularly, we found substantial methylation changes in the HOXD cluster that may explain anatomical differences between archaic and present-day humans. Additionally, we found that DMRs are significantly more likely to be associated with diseases. This study provides insight into the epigenetic landscape of our closest evolutionary relatives and opens a window to explore the epigenomes of extinct species.

Unifying measures of gene function and evolution

Recent genome analyses revealed intriguing correlations between variables characterizing the functioning of a gene, such as expression level (EL), connectivity of genetic and protein–protein interaction networks, and knockout effect, and variables describing gene evolution, such as sequence evolution rate (ER) and propensity for gene loss. Typically, variables within each of these classes are positively correlated, e.g. products of highly expressed genes also have a propensity to be involved in many protein–protein interactions, whereas variables between classes are negatively correlated, e.g. highly expressed genes, on average, evolve slower than weakly expressed genes. Here, we describe principal component (PC) analysis of seven genome-related variables and propose biological interpretations for the first three PCs. The first PC reflects a genes ‘importance’, or the ‘status’ of a gene in the genomic community, with positive contributions from knockout lethality, EL, number of protein–protein interaction partners and the number of paralogues, and negative contributions from sequence ER and gene loss propensity. The next two PCs define a plane that seems to reflect the functional and evolutionary plasticity of a gene. Specifically, PC2 can be interpreted as a genes ‘adaptability’ whereby genes with high adaptability readily duplicate, have many genetic interaction partners and tend to be non-essential. PC3 also might reflect the role of a gene in organismal adaptation albeit with a negative rather than a positive contribution of genetic interactions; we provisionally designate this PC ‘reactivity’. The interpretation of PC2 and PC3 as measures of a genes plasticity is compatible with the observation that genes with high values of these PCs tend to be expressed in a condition- or tissue-specific manner. Functional classes of genes substantially vary in status, adaptability and reactivity, with the highest status characteristic of the translation system and cytoskeletal proteins, highest adaptability seen in cellular processes and signalling genes, and top reactivity characteristic of metabolic enzymes.

A feature extraction method for chemical sensors in electronic noses

Abstract We propose a new feature extraction method for use with chemical sensors. It is based on fitting a parametric analytic model of the sensor’s response over time to the measured signal, and taking the set of best-fitting parameters as the features. The process of finding the features is fast and robust, and the resulting set of features is shown to significantly enhance the performance of subsequent classification algorithms. Moreover, the model that we have developed fits equally well to sensors of different technologies and embeddings, suggesting its applicability to a diverse repertoire of sensors and analytic devices.