Genotypic variation in phosphorus efficiency between wheat cultivars grown under greenhouse and field conditions

Phosphorus (P) efficiency (relative growth), which is described as the ratio of shoot dry matter or grain yield at deficient P supply to that obtained under adequate P supply, was compared in 25 winter wheat cultivars grown under greenhouse and field conditions with low and adequate P levels in a P-deficient calcareous soil. Adequate P supply resulted in significant increases in shoot dry weight and grain yield under both experimental conditions. In the greenhouse experiment, the increases in shoot dry weight under adequate P supply (80 mg kg(-1)) were from 0% (cv: C-1252) to 34% (cv: Dagdas). Under field conditions, the cultivars showed much greater variation in their response to adequate P supply (60 kg ha(-1)): the increases in shoot dry weight and grain yield with adequate P supply were between -2% (cv: Sivas-111/33) and 25% (cv: Kirac-66) for shoot dry matter production at the heading stage and between 0% (cv: Kirkpinar-79) and 76% (cv: Kate A-1) for grain yield at maturity. Almost all cultivars behaved totally different in their response to P deficiency under greenhouse and field conditions. Phosphorus efficiency ratios (relative growth) under greenhouse conditions did not correlate with the P efficiency ratios under field conditions. In general, durum wheat cultivars were found to be more P efficient compared with bread wheat cultivars. The results of this study indicated that there is wide variation in tolerance to P deficiency among wheat cultivars that can be exploited in breeding new wheat cultivars for high P deficiency tolerance. The results also demonstrated that P efficiency was expressed differently among the wheat cultivars when grown under greenhouse and field conditions and, therefore, special attention should be paid to growth conditions in screening wheat for P efficiency

The effects of low-impact mutations in digital organisms

<p>Abstract</p> <p>Background</p> <p>Avida is a computer program that performs evolution experiments with digital organisms. Previous work has used the program to study the evolutionary origin of complex features, namely logic operations, but has consistently used extremely large mutational fitness effects. The present study uses Avida to better understand the role of low-impact mutations in evolution.</p> <p>Results</p> <p>When mutational fitness effects were approximately 0.075 or less, no new logic operations evolved, and those that had previously evolved were lost. When fitness effects were approximately 0.2, only half of the operations evolved, reflecting a threshold for selection breakdown. In contrast, when Avida's default fitness effects were used, all operations routinely evolved to high frequencies and fitness increased by an average of 20 million in only 10,000 generations.</p> <p>Conclusions</p> <p>Avidian organisms evolve new logic operations only when mutations producing them are assigned high-impact fitness effects. Furthermore, purifying selection cannot protect operations with low-impact benefits from mutational deterioration. These results suggest that selection breaks down for low-impact mutations below a certain fitness effect, the <it>selection threshold</it>. Experiments using biologically relevant parameter settings show the tendency for increasing genetic load to lead to loss of biological functionality. An understanding of such genetic deterioration is relevant to human disease, and may be applicable to the control of pathogens by use of lethal mutagenesis.</p

UK science press officers, professional vision and the generation of expectations

Science press officers can play an integral role in helping promote expectations and hype about biomedical research. Using this as a starting point, this article draws on interviews with 10 UK-based science press officers, which explored how they view their role as science reporters and as generators of expectations. Using Goodwin’s notion of ‘professional vision’, we argue that science press officers have a specific professional vision that shapes how they produce biomedical press releases, engage in promotion of biomedical research and make sense of hype. We discuss how these insights can contribute to the sociology of expectations, as well as inform responsible science communication.This project was funded by the Wellcome Trust (Wellcome Trust Biomedical Strategic Award 086034)

EPGD: a comprehensive web resource for integrating and displaying eukaryotic paralog/paralogon information

Gene duplication is common in all three domains of life, especially in eukaryotic genomes. The duplicates provide new material for the action of evolutionary forces such as selection or genetic drift. Here we describe a sophisticated procedure to extract duplicated genes (paralogs) from 26 available eukaryotic genomes, to pre-calculate several evolutionary indexes (evolutionary rate, synonymous distance/clock, transition redundant exchange clock, etc.) based on the paralog family, and to identify block or segmental duplications (paralogons). We also constructed an internet-accessible Eukaryotic Paralog Group Database (EPGD; http://epgd.biosino.org/EPGD/). The database is gene-centered and organized by paralog family. It focuses on paralogs and evolutionary duplication events. The paralog families and paralogons can be searched by text or sequence, and are downloadable from the website as plain text files. The database will be very useful for both experimentalists and bioinformaticians interested in the study of duplication events or paralog families

The Random Nature of Genome Architecture: Predicting Open Reading Frame Distributions

Background: A better understanding of the size and abundance of open reading frames (ORFS) in whole genomes may shed light on the factors that control genome complexity. Here we examine the statistical distributions of open reading frames (i.e. distribution of start and stop codons) in the fully sequenced genomes of 297 prokaryotes, and 14 eukaryotes. Methodology/Principal Findings: By fitting mixture models to data from whole genome sequences we show that the size-frequency distributions for ORFS are strikingly similar across prokaryotic and eukaryotic genomes. Moreover, we show that i) a large fraction (60–80%) of ORF size-frequency distributions can be predicted a priori with a stochastic assembly model based on GC content, and that (ii) size-frequency distributions of the remaining “non-random” ORFs are well-fitted by log-normal or gamma distributions, and similar to the size distributions of annotated proteins. Conclusions/Significance: Our findings suggest stochastic processes have played a primary role in the evolution of genome complexity, and that common processes govern the conservation and loss of functional genomics units in both prokaryotes and eukaryotes.8 page(s