Cultural Evolutionary Tipping Points in the Storage and Transmission of Information

Human culture has evolved through a series of major tipping points in information storage and communication. The first was the appearance of language, which enabled communication between brains and allowed humans to specialize in what they do and to participate in complex mating games. The second was information storage outside the brain, most obviously expressed in the Upper Paleolithic Revolution - the sudden proliferation of cave art, personal adornment, and ritual in Europe some 35,000-45,000 years ago. More recently, this storage has taken the form of writing, mass media, and now the Internet, which is arguably overwhelming humans\u27 ability to discern relevant information. The third tipping point was the appearance of technology capable of accumulating and manipulating vast amounts of information outside humans, thus removing them as bottlenecks to a seemingly self-perpetuating process of knowledge explosion. Important components of any discussion of cultural evolutionary tipping points are tempo and mode, given that the rate of change, as well as the kind of change, in information storage and transmission has not been constant over the previous million years

Excited States in Isobaric Multiplets—Experimental Advances and the Shell-Model Approach

A review of recent advances in the study of the energy splitting between excited isobaric analogue states is presented. Some of the experimental developments, and new approaches, associated with spectroscopy of the most proton-rich members of isobaric multiplets, are discussed. The review focuses on the immense impact of the shell-model in the analysis of energy differences and their interpretation in terms of nuclear structure phenomena

Factors Affecting Annual Deer Harvest in Arkansas

An understanding of general forces affecting annual harvest is essential to the management of white-tailed deer (Odocoileus virginianus). A predictive model based on such factors would be valuable to managers. The relationship between 27 different variables and annual, legal deer harvest in Arkansas was evaluated for 1957-1986. Variables most affecting harvest were soybean acreage, hay acreage, number of days in the deer season, rain during the deer season, and total state timber production, total state pulpwood production, and deer harvest 2 years prior. Because significant autocorrelation and heteroscedasticity were present in the variables, log-linear, first differencing and non-linear quasi-Newton regression methods were used in addition to ordinary least squares. First differencing removed autocorrelation and heteroscedasticity, but fit was not acceptable (R2 = 0.710). Non-linear estimation of first differenced log transformed variables provided an acceptably high R2 (0.896) with high significance of the individual parameter estimators. Factors associated with habitat quality 2 years prior most affected present-year deer harvest

Estimating a Path through a Map of Decision Making

Studies of the evolution of collective behavior consider the payoffs of individual versus social learning. We have previously proposed that the relative magnitude of social versus individual learning could be compared against the transparency of payoff, also known as the “transparency” of the decision, through a heuristic, two-dimensional map. Moving from west to east, the estimated strength of social influence increases. As the decision maker proceeds from south to north, transparency of choice increases, and it becomes easier to identify the best choice itself and/or the best social role model from whom to learn (depending on position on east–west axis). Here we show how to parameterize the functions that underlie the map, how to estimate these functions, and thus how to describe estimated paths through the map. We develop estimation methods on artificial data sets and discuss real-world applications such as modeling changes in health decisions

Second Generation International Space Station (ISS) Total Organic Carbon Analyzer (TOCA) Verification Testing and On-Orbit Performance Results

The Total Organic Carbon Analyzer (TOGA) is designed to autonomously determine recovered water quality as a function of TOC. The current TOGA has been on the International Space Station since November 2008. Functional checkout and operations revealed complex operating considerations. Specifically, failure of the hydrogen catalyst resulted in the development of an innovative oxidation analysis method. This method reduces the activation time and limits the hydrogen produced during analysis, while retaining the ability to indicate TOC concentrations within 25% accuracy. Subsequent testing and comparison to archived samples returned from the Station and tested on the ground yield high confidence in this method, and in the quality of the recovered water

Validation of Reference Genes for Robust qRT-PCR Gene Expression Analysis in the Rice Blast Fungus \u3ci\u3eMagnaporthe oryzae\u3c/i\u3e

The rice blast fungus causes significant annual harvest losses. It also serves as a genetically- tractable model to study fungal ingress. Whilst pathogenicity determinants have been unmasked and changes in global gene expression described, we know little about Magnaporthe oryzae cell wall remodelling. Our interests, in wall remodelling genes expressed during infection, vegetative growth and under exogenous wall stress, demand robust choice of reference genes for quantitative Real Time-PCR (qRT-PCR) data normalisation. We describe the expression stability of nine candidate reference genes profiled by qRT-PCR with cDNAs derived during asexual germling development, from sexual stage perithecia and from vegetative mycelium grown under various exogenous stressors. Our Minimum Information for Publication of qRT-PCR Experiments (MIQE) compliant analysis reveals a set of robust reference genes used to track changes in the expression of the cell wall remodelling gene MGG_Crh2 (MGG_00592). We ranked nine candidate reference genes by their expression stability (M) and report the best gene combination needed for reliable gene expression normalisation, when assayed in three tissue groups (Infective, Vegetative, and Global) frequently used in M. oryzae expression studies. We found that MGG_Actin (MGG_03982) and the 40S 27a ribosomal subunit MGG_40s (MGG_02872) proved to be robust reference genes for the Infection group and MGG_40s and MGG_Ef1 (Elongation Factor1-α) for both Vegetative and Global groups. Using the above validated reference genes, M. oryzae MGG_Crh2 expression was found to be significantly (p\u3c0.05) elevated three-fold during vegetative growth as compared with dormant spores and two fold higher under cell wall stress (Congo Red) compared to growth under optimal conditions. We recommend the combinatorial use of two reference genes, belonging to the cytoskeleton and ribosomal synthesis functional groups, MGG_Actin, MGG_40s, MGG_S8 (Ribosomal subunit 40S S8) or MGG_Ef1, which demonstrated low M values across heterogeneous tissues. By contrast, metabolic pathway genes MGG_Fad (FAD binding domain-containing protein) and MGG_Gapdh (Glyceraldehyde-3-phosphate dehydrogenase) performed poorly, due to their lack of expression stability across samples

Multi-trait ensemble genomic prediction and simulations of recurrent selection highlight importance of complex trait genetic architecture for long-term genetic gains in wheat

Cereal crop breeders have achieved considerable genetic gain in genetically complex traits, such as grain yield, while maintaining genetic diversity. However, focus on selection for yield has negatively impacted other important traits. To better understand multi-trait selection within a breeding context, and how it might be optimized, we analysed genotypic and phenotypic data from a genetically diverse, 16-founder wheat multi-parent advanced generation inter-cross population. Compared to single-trait models, multi-trait ensemble genomic prediction models increased prediction accuracy for almost 90 % of traits, improving grain yield prediction accuracy by 3–52 %. For complex traits, non-parametric models (Random Forest) also outperformed simplified, additive models (LASSO), increasing grain yield prediction accuracy by 10–36 %. Simulations of recurrent genomic selection then showed that sustained greater forward prediction accuracy optimized long-term genetic gains. Simulations of selection on grain yield found indirect responses in related traits, involving optimized antagonistic trait relationships. We found multi-trait selection indices could effectively optimize undesirable relationships, such as the trade-off between grain yield and protein content, or combine traits of interest, such as yield and weed competitive ability. Simulations of phenotypic selection found that including Random Forest rather than LASSO genetic models, and multi-trait rather than single-trait models as the true genetic model accelerated and extended long-term genetic gain whilst maintaining genetic diversity. These results (i) suggest important roles of pleiotropy and epistasis in the wider context of wheat breeding programmes, and (ii) provide insights into mechanisms for continued genetic gain in a limited genepool and optimization of multiple traits for crop improvement

A truncation allele in vascular endothelial growth factor c reveals distinct modes of signaling during lymphatic and vascular development

Vascular endothelial growth factor C (Vegfc) is a secreted protein that guides lymphatic development in vertebrate embryos. However, its role during developmental angiogenesis is not well characterized. Here, we identify a mutation in zebrafish vegfc that severely affects lymphatic development and leads to angiogenesis defects on sensitized genetic backgrounds. The um18 mutation prematurely truncated Vegfc, blocking its secretion and paracrine activity but not its ability to activate its receptor Flt4. When expressed in endothelial cells, vegfc(um18) could not rescue lymphatic defects in mutant embryos, but induced ectopic blood vessel branching. Furthermore, vegfc-deficient endothelial cells did not efficiently contribute to tip cell positions in developing sprouts. Computational modeling together with assessment of endothelial cell dynamics by time-lapse analysis suggested that an autocrine Vegfc/Flt4 loop plays an important role in migratory persistence and filopodia stability during sprouting. Our results suggest that Vegfc acts in two distinct modes during development: as a paracrine factor secreted from arteries to guide closely associated lymphatic vasculature and as an autocrine factor to drive migratory persistence during angiogenesis

Genome-level analyses of Mycobacterium bovis lineages reveal the role of SNPs and antisense transcription in differential gene expression

BACKGROUND: Bovine tuberculosis (bTB) is a disease with major implications for animal welfare and productivity, as well as having the potential for zoonotic transmission. In Great Britain (GB) alone, controlling bTB costs in the region of £100 million annually, with the current control scheme seemingly unable to stop the inexorable spread of infection. One aspect that may be driving the epidemic is evolution of the causative pathogen, Mycobacterium bovis. To understand the underlying genetic changes that may be responsible for this evolution, we performed a comprehensive genome-level analyses of 4 M. bovis strains that encompass the main molecular types of the pathogen circulating in GB. RESULTS: We have used a combination of genome sequencing, transcriptome analyses, and recombinant DNA technology to define genetic differences across the major M. bovis lineages circulating in GB that may give rise to phenotypic differences of practical importance. The genomes of three M. bovis field isolates were sequenced using Illumina sequencing technology and strain specific differences in gene expression were measured during in vitro growth and in ex vivo bovine alveolar macrophages using a whole genome amplicon microarray and a whole genome tiled oligonucleotide microarray. SNP/small base pair insertion and deletions and gene expression data were overlaid onto the genomic sequence of the fully sequenced strain of M. bovis 2122/97 to link observed strain specific genomic differences with differences in RNA expression. CONCLUSIONS: We show that while these strains show extensive similarities in their genetic make-up and gene expression profiles, they exhibit distinct expression of a subset of genes. We provide genomic, transcriptomic and functional data to show that synonymous point mutations (sSNPs) on the coding strand can lead to the expression of antisense transcripts on the opposing strand, a finding with implications for how we define a 'silent’ nucleotide change. Furthermore, we show that transcriptomic data based solely on amplicon arrays can generate spurious results in terms of gene expression profiles due to hybridisation of antisense transcripts. Overall our data suggest that subtle genetic differences, such as sSNPS, may have important consequences for gene expression and subsequent phenotype