Statistical mechanics of voting

Decision procedures aggregating the preferences of multiple agents can produce cycles and hence outcomes which have been described heuristically as `chaotic'. We make this description precise by constructing an explicit dynamical system from the agents' preferences and a voting rule. The dynamics form a one dimensional statistical mechanics model; this suggests the use of the topological entropy to quantify the complexity of the system. We formulate natural political/social questions about the expected complexity of a voting rule and degree of cohesion/diversity among agents in terms of random matrix models---ensembles of statistical mechanics models---and compute quantitative answers in some representative cases.Comment: 9 pages, plain TeX, 2 PostScript figures included with epsf.tex (ignore the under/overfull \vbox error messages

Population gene introgression and high genome plasticity for the zoonotic pathogen Streptococcus agalactiae

The influence that bacterial adaptation (or niche partitioning) within species has on gene spillover and transmission among bacteria populations occupying different niches is not well understood. Streptococcus agalactiae is an important bacterial pathogen that has a taxonomically diverse host range making it an excellent model system to study these processes. Here we analyze a global set of 901 genome sequences from nine diverse host species to advance our understanding of these processes. Bayesian clustering analysis delineated twelve major populations that closely aligned with niches. Comparative genomics revealed extensive gene gain/loss among populations and a large pan-genome of 9,527 genes, which remained open and was strongly partitioned among niches. As a result, the biochemical characteristics of eleven populations were highly distinctive (significantly enriched). Positive selection was detected and biochemical characteristics of the dispensable genes under selection were enriched in ten populations. Despite the strong gene partitioning, phylogenomics detected gene spillover. In particular, tetracycline resistance (which likely evolved in the human-associated population) from humans to bovine, canines, seals, and fish, demonstrating how a gene selected in one host can ultimately be transmitted into another, and biased transmission from humans to bovines was confirmed with a Bayesian migration analysis. Our findings show high bacterial genome plasticity acting in balance with selection pressure from distinct functional requirements of niches that is associated with an extensive and highly partitioned dispensable genome, likely facilitating continued and expansive adaptation

The Wide-field Infrared Survey Explorer (WISE): Mission Description and Initial On-orbit Performance

The all sky surveys done by the Palomar Observatory Schmidt, the European Southern Observatory Schmidt, and the United Kingdom Schmidt, the InfraRed Astronomical Satellite and the 2 Micron All Sky Survey have proven to be extremely useful tools for astronomy with value that lasts for decades. The Wide-field Infrared Survey Explorer is mapping the whole sky following its launch on 14 December 2009. WISE began surveying the sky on 14 Jan 2010 and completed its first full coverage of the sky on July 17. The survey will continue to cover the sky a second time until the cryogen is exhausted (anticipated in November 2010). WISE is achieving 5 sigma point source sensitivities better than 0.08, 0.11, 1 and 6 mJy in unconfused regions on the ecliptic in bands centered at wavelengths of 3.4, 4.6, 12 and 22 microns. Sensitivity improves toward the ecliptic poles due to denser coverage and lower zodiacal background. The angular resolution is 6.1, 6.4, 6.5 and 12.0 arc-seconds at 3.4, 4.6, 12 and 22 microns, and the astrometric precision for high SNR sources is better than 0.15 arc-seconds.Comment: 22 pages with 19 included figures. Updated to better match the accepted version in the A

Brains studying brains: look before you think in vision

Using our own brains to study our brains is extraordinary. For example, in vision this makes us naturally blind to our own blindness, since our impression of seeing our world clearly is consistent with our ignorance of what we do not see. Our brain employs its 'conscious' part to reason and make logical deductions using familiar rules and past experience. However, human vision employs many 'subconscious' brain parts that follow rules alien to our intuition. Our blindness to our unknown unknowns and our presumptive intuitions easily lead us astray in asking and formulating theoretical questions, as witnessed in many unexpected and counter-intuitive difficulties and failures encountered by generations of scientists. We should therefore pay a more than usual amount of attention and respect to experimental data when studying our brain. I show that this can be productive by reviewing two vision theories that have provided testable predictions and surprising insights

Gene content evolution in the arthropods

Arthropods comprise the largest and most diverse phylum on Earth and play vital roles in nearly every ecosystem. Their diversity stems in part from variations on a conserved body plan, resulting from and recorded in adaptive changes in the genome. Dissection of the genomic record of sequence change enables broad questions regarding genome evolution to be addressed, even across hyper-diverse taxa within arthropods. Using 76 whole genome sequences representing 21 orders spanning more than 500 million years of arthropod evolution, we document changes in gene and protein domain content and provide temporal and phylogenetic context for interpreting these innovations. We identify many novel gene families that arose early in the evolution of arthropods and during the diversification of insects into modern orders. We reveal unexpected variation in patterns of DNA methylation across arthropods and examples of gene family and protein domain evolution coincident with the appearance of notable phenotypic and physiological adaptations such as flight, metamorphosis, sociality, and chemoperception. These analyses demonstrate how large-scale comparative genomics can provide broad new insights into the genotype to phenotype map and generate testable hypotheses about the evolution of animal diversity

Evolutionary History of Chemosensory-Related Gene Families across the Arthropoda

Chemosensory-related gene (CRG) families have been studied extensively in insects, but their evolutionary history across the Arthropoda had remained relatively unexplored. Here, we address current hypotheses and prior conclusions on CRG family evolution using a more comprehensive data set. In particular, odorant receptors were hypothesized to have proliferated during terrestrial colonization by insects (hexapods), but their association with other pancrustacean clades and with independent terrestrial colonizations in other arthropod subphyla have been unclear. We also examine hypotheses on which arthropod CRG family is most ancient. Thus, we reconstructed phylogenies of CRGs, including those from new arthropod genomes and transcriptomes, and mapped CRG gains and losses across arthropod lineages. Our analysis was strengthened by including crustaceans, especially copepods, which reside outside the hexapod/branchiopod clade within the subphylum Pancrustacea. We generated the first high-resolution genome sequence of the copepod Eurytemora affinis and annotated its CRGs. We found odorant receptors and odorant binding proteins present only in hexapods (insects) and absent from all other arthropod lineages, indicating that they are not universal adaptations to land. Gustatory receptors likely represent the oldest chemosensory receptors among CRGs, dating back to the Placozoa. We also clarified and confirmed the evolutionary history of antennal ionotropic receptors across the Arthropoda. All antennal ionotropic receptors in E. affinis were expressed more highly in males than in females, suggestive of an association with male mate-recognition behavior. This study is the most comprehensive comparative analysis to date of CRG family evolution across the largest and most speciose metazoan phylum Arthropoda

Atlas of Transcription Factor Binding Sites from ENCODE DNase Hypersensitivity Data across 27 Tissue Types.

Characterizing the tissue-specific binding sites of transcription factors (TFs) is essential to reconstruct gene regulatory networks and predict functions for non-coding genetic variation. DNase-seq footprinting enables the prediction of genome-wide binding sites for hundreds of TFs simultaneously. Despite the public availability of high-quality DNase-seq data from hundreds of samples, a comprehensive, up-to-date resource for the locations of genomic footprints is lacking. Here, we develop a scalable footprinting workflow using two state-of-the-art algorithms: Wellington and HINT. We apply our workflow to detect footprints in 192 ENCODE DNase-seq experiments and predict the genomic occupancy of 1,515 human TFs in 27 human tissues. We validate that these footprints overlap true-positive TF binding sites from ChIP-seq. We demonstrate that the locations, depth, and tissue specificity of footprints predict effects of genetic variants on gene expression and capture a substantial proportion of genetic risk for complex traits

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types