Law of Genome Evolution Direction : Coding Information Quantity Grows

The problem of the directionality of genome evolution is studied. Based on the analysis of C-value paradox and the evolution of genome size we propose that the function-coding information quantity of a genome always grows in the course of evolution through sequence duplication, expansion of code, and gene transfer from outside. The function-coding information quantity of a genome consists of two parts, p-coding information quantity which encodes functional protein and n-coding information quantity which encodes other functional elements except amino acid sequence. The evidences on the evolutionary law about the function-coding information quantity are listed. The needs of function is the motive force for the expansion of coding information quantity and the information quantity expansion is the way to make functional innovation and extension for a species. So, the increase of coding information quantity of a genome is a measure of the acquired new function and it determines the directionality of genome evolution.Comment: 16 page

Innate Synchronous Oscillations in Freely-Organized Small Neuronal Circuits

BACKGROUND: Information processing in neuronal networks relies on the network's ability to generate temporal patterns of action potentials. Although the nature of neuronal network activity has been intensively investigated in the past several decades at the individual neuron level, the underlying principles of the collective network activity, such as the synchronization and coordination between neurons, are largely unknown. Here we focus on isolated neuronal clusters in culture and address the following simple, yet fundamental questions: What is the minimal number of cells needed to exhibit collective dynamics? What are the internal temporal characteristics of such dynamics and how do the temporal features of network activity alternate upon crossover from minimal networks to large networks? METHODOLOGY/PRINCIPAL FINDINGS: We used network engineering techniques to induce self-organization of cultured networks into neuronal clusters of different sizes. We found that small clusters made of as few as 40 cells already exhibit spontaneous collective events characterized by innate synchronous network oscillations in the range of 25 to 100 Hz. The oscillation frequency of each network appeared to be independent of cluster size. The duration and rate of the network events scale with cluster size but converge to that of large uniform networks. Finally, the investigation of two coupled clusters revealed clear activity propagation with master/slave asymmetry. CONCLUSIONS/SIGNIFICANCE: The nature of the activity patterns observed in small networks, namely the consistent emergence of similar activity across networks of different size and morphology, suggests that neuronal clusters self-regulate their activity to sustain network bursts with internal oscillatory features. We therefore suggest that clusters of as few as tens of cells can serve as a minimal but sufficient functional network, capable of sustaining oscillatory activity. Interestingly, the frequencies of these oscillations are similar those observed in vivo

A Distributed Chemosensory Circuit for Oxygen Preference in C. elegans

The nematode Caenorhabditis elegans has complex, naturally variable behavioral responses to environmental oxygen, food, and other animals. C. elegans detects oxygen through soluble guanylate cyclase homologs (sGCs) and responds to it differently depending on the activity of the neuropeptide receptor NPR-1: npr-1(lf) and naturally isolated npr-1(215F) animals avoid high oxygen and aggregate in the presence of food; npr-1(215V) animals do not. We show here that hyperoxia avoidance integrates food with npr-1 activity through neuromodulation of a distributed oxygen-sensing network. Hyperoxia avoidance is stimulated by sGC-expressing oxygen-sensing neurons, nociceptive neurons, and ADF sensory neurons. In npr-1(215V) animals, the switch from weak aerotaxis on food to strong aerotaxis in its absence requires close regulation of the neurotransmitter serotonin in the ADF neurons; high levels of ADF serotonin promote hyperoxia avoidance. In npr-1(lf) animals, food regulation is masked by increased activity of the oxygen-sensing neurons. Hyperoxia avoidance is also regulated by the neuronal TGF-β homolog DAF-7, a secreted mediator of crowding and stress responses. DAF-7 inhibits serotonin synthesis in ADF, suggesting that ADF serotonin is a convergence point for regulation of hyperoxia avoidance. Coalitions of neurons that promote and repress hyperoxia avoidance generate a subtle and flexible response to environmental oxygen

Metabolic labeling of RNA uncovers principles of RNA production and degradation dynamics in mammalian cells

available in PMC 2011 November 01.Cellular RNA levels are determined by the interplay of RNA production, processing and degradation. However, because most studies of RNA regulation do not distinguish the separate contributions of these processes, little is known about how they are temporally integrated. Here we combine metabolic labeling of RNA at high temporal resolution with advanced RNA quantification and computational modeling to estimate RNA transcription and degradation rates during the response of mouse dendritic cells to lipopolysaccharide. We find that changes in transcription rates determine the majority of temporal changes in RNA levels, but that changes in degradation rates are important for shaping sharp 'peaked' responses. We used sequencing of the newly transcribed RNA population to estimate temporally constant RNA processing and degradation rates genome wide. Degradation rates vary significantly between genes and contribute to the observed differences in the dynamic response. Certain transcripts, including those encoding cytokines and transcription factors, mature faster. Our study provides a quantitative approach to study the integrative process of RNA regulation.Human Frontier Science Program (Strasbourg, France)Howard Hughes Medical InstituteBurroughs Wellcome Fund (Career Award at the Scientific Interface

LOCAS – A Low Coverage Assembly Tool for Resequencing Projects

Motivation: Next Generation Sequencing (NGS) is a frequently applied approach to detect sequence variations between highly related genomes. Recent large-scale re-sequencing studies as the Human 1000 Genomes Project utilize NGS data of low coverage to afford sequencing of hundreds of individuals. Here, SNPs and micro-indels can be detected by applying an alignment-consensus approach. However, computational methods capable of discovering other variations such as novel insertions or highly diverged sequence from low coverage NGS data are still lacking. Results: We present LOCAS, a new NGS assembler particularly designed for low coverage assembly of eukaryotic genomes using a mismatch sensitive overlap-layout-consensus approach. LOCAS assembles homologous regions in a homologyguided manner while it performs de novo assemblies of insertions and highly polymorphic target regions subsequently to an alignment-consensus approach. LOCAS has been evaluated in homology-guided assembly scenarios with low sequence coverage of Arabidopsis thaliana strains sequenced as part of the Arabidopsis 1001 Genomes Project. While assembling the same amount of long insertions as state-of-the-art NGS assemblers, LOCAS showed best results regarding contig size, error rate and runtime. Conclusion: LOCAS produces excellent results for homology-guided assembly of eukaryotic genomes with short reads and low sequencing depth, and therefore appears to be the assembly tool of choice for the detection of novel sequenc

Distinctive expansion of potential virulence genes in the genome of the oomycete fish pathogen Saprolegnia parasitica.

Oomycetes in the class Saprolegniomycetidae of the Eukaryotic kingdom Stramenopila have evolved as severe pathogens of amphibians, crustaceans, fish and insects, resulting in major losses in aquaculture and damage to aquatic ecosystems. We have sequenced the 63 Mb genome of the fresh water fish pathogen, Saprolegnia parasitica. Approximately 1/3 of the assembled genome exhibits loss of heterozygosity, indicating an efficient mechanism for revealing new variation. Comparison of S. parasitica with plant pathogenic oomycetes suggests that during evolution the host cellular environment has driven distinct patterns of gene expansion and loss in the genomes of plant and animal pathogens. S. parasitica possesses one of the largest repertoires of proteases (270) among eukaryotes that are deployed in waves at different points during infection as determined from RNA-Seq data. In contrast, despite being capable of living saprotrophically, parasitism has led to loss of inorganic nitrogen and sulfur assimilation pathways, strikingly similar to losses in obligate plant pathogenic oomycetes and fungi. The large gene families that are hallmarks of plant pathogenic oomycetes such as Phytophthora appear to be lacking in S. parasitica, including those encoding RXLR effectors, Crinkler's, and Necrosis Inducing-Like Proteins (NLP). S. parasitica also has a very large kinome of 543 kinases, 10% of which is induced upon infection. Moreover, S. parasitica encodes several genes typical of animals or animal-pathogens and lacking from other oomycetes, including disintegrins and galactose-binding lectins, whose expression and evolutionary origins implicate horizontal gene transfer in the evolution of animal pathogenesis in S. parasitica

Methods for Minimizing the Confounding Effects of Word Length in the Analysis of Phonotactic Probability and Neighborhood Density

This is the author's accepted manuscript. The original is available at http://jslhr.pubs.asha.org/article.aspx?articleid=1781521&resultClick=3Recent research suggests that phonotactic probability (the likelihood of occurrence of a sound sequence) and neighborhood density (the number of words phonologically similar to a given word) influence spoken language processing and acquisition across the lifespan in both normal and clinical populations. The majority of research in this area has tended to focus on controlled laboratory studies rather than naturalistic data such as spontaneous speech samples or elicited probes. One difficulty in applying current measures of phonotactic probability and neighborhood density to more naturalistic samples is the significant correlation between these variables and word length. This study examines several alternative transformations of phonotactic probability and neighborhood density as a means of reducing or eliminating this correlation with word length. Computational analyses of the words in a large database and reanalysis of archival data supported the use of z scores for the analysis of phonotactic probability as a continuous variable and the use of median transformation scores for the analysis of phonotactic probability as a dichotomous variable. Neighborhood density results were less clear with the conclusion that analysis of neighborhood density as a continuous variable warrants further investigation to differentiate the utility of z scores in comparison to median transformation scores. Furthermore, balanced dichotomous coding of neighborhood density was difficult to achieve, suggesting that analysis of neighborhood density as a dichotomous variable should be approached with caution. Recommendations for future application and analyses are discussed

Genomic surveillance elucidates Ebola virus origin and transmission during the 2014 outbreak

In its largest outbreak, Ebola virus disease is spreading through Guinea, Liberia, Sierra Leone, and Nigeria. We sequenced 99 Ebola virus genomes from 78 patients in Sierra Leone to ~2000× coverage. We observed a rapid accumulation of interhost and intrahost genetic variation, allowing us to characterize patterns of viral transmission over the initial weeks of the epidemic. This West African variant likely diverged from central African lineages around 2004, crossed from Guinea to Sierra Leone in May 2014, and has exhibited sustained human-to-human transmission subsequently, with no evidence of additional zoonotic sources. Because many of the mutations alter protein sequences and other biologically meaningful targets, they should be monitored for impact on diagnostics, vaccines, and therapies critical to outbreak response.Organismic and Evolutionary Biolog