Conserved substitution patterns around nucleosome footprints in eukaryotes and Archaea derive from frequent nucleosome repositioning through evolution.

Nucleosomes, the basic repeat units of eukaryotic chromatin, have been suggested to influence the evolution of eukaryotic genomes, both by altering the propensity of DNA to mutate and by selection acting to maintain or exclude nucleosomes in particular locations. Contrary to the popular idea that nucleosomes are unique to eukaryotes, histone proteins have also been discovered in some archaeal genomes. Archaeal nucleosomes, however, are quite unlike their eukaryotic counterparts in many respects, including their assembly into tetramers (rather than octamers) from histone proteins that lack N- and C-terminal tails. Here, we show that despite these fundamental differences the association between nucleosome footprints and sequence evolution is strikingly conserved between humans and the model archaeon Haloferax volcanii. In light of this finding we examine whether selection or mutation can explain concordant substitution patterns in the two kingdoms. Unexpectedly, we find that neither the mutation nor the selection model are sufficient to explain the observed association between nucleosomes and sequence divergence. Instead, we demonstrate that nucleosome-associated substitution patterns are more consistent with a third model where sequence divergence results in frequent repositioning of nucleosomes during evolution. Indeed, we show that nucleosome repositioning is both necessary and largely sufficient to explain the association between current nucleosome positions and biased substitution patterns. This finding highlights the importance of considering the direction of causality between genetic and epigenetic change

Evaluation of Algorithm Performance in ChIP-Seq Peak Detection

Next-generation DNA sequencing coupled with chromatin immunoprecipitation (ChIP-seq) is revolutionizing our ability to interrogate whole genome protein-DNA interactions. Identification of protein binding sites from ChIP-seq data has required novel computational tools, distinct from those used for the analysis of ChIP-Chip experiments. The growing popularity of ChIP-seq spurred the development of many different analytical programs (at last count, we noted 31 open source methods), each with some purported advantage. Given that the literature is dense and empirical benchmarking challenging, selecting an appropriate method for ChIP-seq analysis has become a daunting task. Herein we compare the performance of eleven different peak calling programs on common empirical, transcription factor datasets and measure their sensitivity, accuracy and usability. Our analysis provides an unbiased critical assessment of available technologies, and should assist researchers in choosing a suitable tool for handling ChIP-seq data

Regulatory Multidimensionality of Gas Vesicle Biogenesis in Halobacterium salinarum NRC-1

It is becoming clear that the regulation of gas vesicle biogenesis in Halobacterium salinarum NRC-1 is multifaceted and appears to integrate environmental and metabolic cues at both the transcriptional and posttranscriptional levels. The mechanistic details underlying this process, however, remain unclear. In this manuscript, we quantify the contribution of light scattering made by both intracellular and released gas vesicles isolated from Halobacterium salinarum NRC-1, demonstrating that each form can lead to distinct features in growth curves determined by optical density measured at 600 nm (OD600). In the course of the study, we also demonstrate the sensitivity of gas vesicle accumulation in Halobacterium salinarum NRC-1 on small differences in growth conditions and reevaluate published works in the context of our results to present a hypothesis regarding the roles of the general transcription factor tbpD and the TCA cycle enzyme aconitase on the regulation of gas vesicle biogenesis

Indonesian Muslim Women and the Gender Equality Movement

Throughout the history of Indonesia, the concepts of gender and power-relations between men and women have been linked to a shifting and fluctuating idea of what constitutes good women, good men, and good gender relationships within the context of Indonesia and Islam. To analyse these changing attitudes to women\u27s issues in Indonesia, we need to pay attention to several points: the character of the women\u27s organizations, whether fully independent, semi autonomous, or subsidiaries of existing male organizations; the important issues rising within the movements, as well as the strategies to deal with them; and lastly the influential factor of government intervention in the women\u27s movement. This paper tries to explore the Muslim women\u27s movement and its strategy to accommodate or resist from the domination of Islam in terms of the nation state, the constitution and the dominant cultural norms in Indonesia

Draft genome of Haloarcula rubripromontorii strain SL3, a novel halophilic archaeon isolated from the solar salterns of Cabo Rojo, Puerto Rico.

The genus Haloarcula belongs to the family Halobacteriaceae which currently has 10 valid species. Here we report the draft genome sequence of strain SL3, a new species within this genus, isolated from the Solar Salterns of Cabo Rojo, Puerto Rico. Genome assembly performed using NGEN Assembler resulted in 18 contigs (N50 = 601,911 bp), the largest of which contains 1,023,775 bp. The genome consists of 3.97 MB and has a GC content of 61.97%. Like all species of Haloarcula, the genome encodes heterogeneous copies of the small subunit ribosomal RNA. In addition, the genome includes 6 rRNAs, 48 tRNAs, and 3797 protein coding sequences. Several carbohydrate-active enzymes genes were found, as well as enzymes involved in the dihydroxyacetone processing pathway which are not found in other Haloarcula species. The NCBI accession number for this genome is LIUF00000000 and the strain deposit number is CECT9001

A Monte Carlo-based framework enhances the discovery and interpretation of regulatory sequence motifs

Abstract Background Discovery of functionally significant short, statistically overrepresented subsequence patterns (motifs) in a set of sequences is a challenging problem in bioinformatics. Oftentimes, not all sequences in the set contain a motif. These non-motif-containing sequences complicate the algorithmic discovery of motifs. Filtering the non-motif-containing sequences from the larger set of sequences while simultaneously determining the identity of the motif is, therefore, desirable and a non-trivial problem in motif discovery research. Results We describe MotifCatcher, a framework that extends the sensitivity of existing motif-finding tools by employing random sampling to effectively remove non-motif-containing sequences from the motif search. We developed two implementations of our algorithm; each built around a commonly used motif-finding tool, and applied our algorithm to three diverse chromatin immunoprecipitation (ChIP) data sets. In each case, the motif finder with the MotifCatcher extension demonstrated improved sensitivity over the motif finder alone. Our approach organizes candidate functionally significant discovered motifs into a tree, which allowed us to make additional insights. In all cases, we were able to support our findings with experimental work from the literature. Conclusions Our framework demonstrates that additional processing at the sequence entry level can significantly improve the performance of existing motif-finding tools. For each biological data set tested, we were able to propose novel biological hypotheses supported by experimental work from the literature. Specifically, in Escherichia coli, we suggested binding site motifs for 6 non-traditional LexA protein binding sites; in Saccharomyces cerevisiae, we hypothesize 2 disparate mechanisms for novel binding sites of the Cse4p protein; and in Halobacterium sp. NRC-1, we discoverd subtle differences in a general transcription factor (GTF) binding site motif across several data sets. We suggest that small differences in our discovered motif could confer specificity for one or more homologous GTF proteins. We offer a free implementation of the MotifCatcher software package at http://www.bme.ucdavis.edu/facciotti/resources_data/software/ .http://deepblue.lib.umich.edu/bitstream/2027.42/112965/1/12859_2012_Article_5570.pd

The Inferelator: an algorithm for learning parsimonious regulatory networks from systems-biology data sets de novo

We present a method (the Inferelator) for deriving genome-wide transcriptional regulatory interactions, and apply the method to predict a large portion of the regulatory network of the archaeon Halobacterium NRC-1. The Inferelator uses regression and variable selection to identify transcriptional influences on genes based on the integration of genome annotation and expression data. The learned network successfully predicted Halobacterium's global expression under novel perturbations with predictive power similar to that seen over training data. Several specific regulatory predictions were experimentally tested and verified

Gene Gangs of the Chloroviruses: Conserved Clusters of Collinear Monocistronic Genes

Chloroviruses (family Phycodnaviridae) are dsDNA viruses found throughout the world’s inland waters. The open reading frames in the genomes of 41 sequenced chloroviruses (330 + 40 kbp each) representing three virus types were analyzed for evidence of evolutionarily conserved local genomic “contexts”, the organization of biological information into units of a scale larger than a gene. Despite a general loss of synteny between virus types, we informatically detected a highly conserved genomic context defined by groups of three or more genes that we have termed “gene gangs”. Unlike previously described local genomic contexts, the definition of gene gangs requires only that member genes be consistently co-localized and are not constrained by strand, regulatory sites, or intervening sequences (and therefore represent a new type of conserved structural genomic element). An analysis of functional annotations and transcriptomic data suggests that some of the gene gangs may organize genes involved in specific biochemical processes, but that this organization does not involve their coordinated expression