Friday - PLoS Genetics, Pathogens, Computational Biology and ONE published today. As always, you should rate the articles, post notes and comments and send trackbacks when you blog about the papers. You can now also easily place articles on various social services (CiteULike, Mendeley, Connotea, Stumbleupon, Facebook and Digg) with just one click. Here are my own picks for the week - you go and look for your own favourites:
Circadian KaiC Phosphorylation: A Multi-Layer Network:
Circadian clocks are endogenous timing mechanisms that allow living organisms to coordinate their activities with daily environmental fluctuations. In cyanobacteria, almost all the genes are rhythmically expressed with the same ~24 h period yet exhibit a variety of phase relationships and waveforms. Remarkably, the core pacemaker ticks robustly via simple biochemical reactions carried out by three Kai proteins: KaiC undergoes circadian phosphorylation in the presence of KaiA, KaiB and ATP. In this work, we propose a reaction network modeling the Kai oscillator based on the differentiation of dual phosphorylation sites. We found a dynamic diversity in KaiC phosphorylation which may serve as a potential regulatory mechanism related to the diverse-phased genome-wide expressions in cyanobacteria. In addition, we deduce that each KaiC hexamer is a single oscillator in regulating its own phosphorylation and interactions with KaiA or/and KaiB. In complex organisms, a number of key clock components possess similar activities (e.g., phosphorylation) with multiple nonequivalent active sites, and they may also show some unusual dynamic features that are embedded in the proteins' own reaction networks. We hope our work could be helpful to study the correlations between gene expressions and circadian rhythm in prokaryotic cells, even in eukaryotic cells.
For many animals, including rats, accurate spatial memory over relatively large areas is important in order to find food and shelter. Just as unique points in time can be efficiently represented by combinations of repeating elements like hours, days, and months, points in space can be represented as combinations of elements that repeat at different spatial scales. Just such a code has been identified in the brains of rats and it shows an intriguing triangular spacing of encoded locations. Two different explanations have been developed as to what general mechanism in the brain might be able to generate this unusual code. However, to date there is not conclusive experimental evidence indicating whether either of the two explanations is correct. Here we show in detail that one of the explanations, called oscillatory interference, has specific requirements regarding the amount of variability in the system that implements it. We then report data experimentally examining candidate systems to evaluate their levels of noise. The large amount of noise that we find presents a challenge to the currently suggested biological implementations of oscillatory interference, but it does not provide support for the alternative explanation.
10 Reasons to be Tantalized by the B73 Maize Genome:
Why should you read about the maize genome? Now that so many eukaryotic genomes are available, it's easy to be blasé... just another few billion bases, grist for constructing gene trees. Why is this new information, so recently shared, worth considering? I am convinced, as I propose you will be too as you read on, that both geneticists and genome consumers will benefit from the first description of the B73 maize genome [1] and equally so from the companion papers compiled in this special collection (http://collections.plos.org/plosgeneticsâ/maize.php ).
On Theoretical Models of Gene Expression Evolution with Random Genetic Drift and Natural Selection:
The relative contributions of natural selection and random genetic drift are a major source of debate in the study of gene expression evolution, which is hypothesized to serve as a bridge from molecular to phenotypic evolution. It has been suggested that the conflict between views is caused by the lack of a definite model of the neutral hypothesis, which can describe the long-run behavior of evolutionary change in mRNA abundance. Therefore previous studies have used inadequate analogies with the neutral prediction of other phenomena, such as amino acid or nucleotide sequence evolution, as the null hypothesis of their statistical inference. In this study, we introduced two novel theoretical models, one based on neutral drift and the other assuming natural selection, by focusing on a common property of the distribution of mRNA abundance among a variety of eukaryotic cells, which reflects the result of long-term evolution. Our results demonstrated that (1) our models can reproduce two independently found phenomena simultaneously: the time development of gene expression divergence and Zipf's law of the transcriptome; (2) cytological constraints can be explicitly formulated to describe long-term evolution; (3) the model assuming that natural selection optimized relative mRNA abundance was more consistent with previously published observations than the model of optimized absolute mRNA abundances. The models introduced in this study give a formulation of evolutionary change in the mRNA abundance of each gene as a stochastic process, on the basis of previously published observations. This model provides a foundation for interpreting observed data in studies of gene expression evolution, including identifying an adequate time scale for discriminating the effect of natural selection from that of random genetic drift of selectively neutral variations.
Combination of Real-Value Smell and Metaphor Expression Aids Yeast Detection:
Smell provides important information about the quality of food and drink. Most well-known for their expertise in wine tasting, sommeliers sniff out the aroma of wine and describe them using beautiful metaphors. In contrast, electronic noses, devices that mimic our olfactory recognition system, also detect smells using their sensors but describe them using electronic signals. These devices have been used to judge the freshness of food or detect the presence of pathogenic microorganisms. However, unlike information from gas chromatography, it is difficult to compare odour information collected by these devices because they are made for smelling specific smells and their data are relative intensities. Here, we demonstrate the use of an absolute-value description method using known smell metaphors, and early detection of yeast using the method. This technique may help distinguishing microbial-contamination of food products earlier, or improvement of the food-product qualities.
Motor and Linguistic Linking of Space and Time in the Cerebellum:
Recent literature documented the presence of spatial-temporal interactions in the human brain. The aim of the present study was to verify whether representation of past and future is also mapped onto spatial representations and whether the cerebellum may be a neural substrate for linking space and time in the linguistic domain. We asked whether processing of the tense of a verb is influenced by the space where response takes place and by the semantics of the verb. Responses to past tense were facilitated in the left space while responses to future tense were facilitated in the right space. Repetitive transcranial magnetic stimulation (rTMS) of the right cerebellum selectively slowed down responses to future tense of action verbs; rTMS of both cerebellar hemispheres decreased accuracy of responses to past tense in the left space and to future tense in the right space for non-verbs, and to future tense in the right space for state verbs. The results suggest that representation of past and future is mapped onto spatial formats and that motor action could represent the link between spatial and temporal dimensions. Right cerebellar, left motor brain networks could be part of the prospective brain, whose primary function is to use past experiences to anticipate future events. Both cerebellar hemispheres could play a role in establishing the grammatical rules for verb conjugation.
Genetic differences both between individuals and populations are studied for their evolutionary relevance and for their potential medical applications. Most of the genetic differentiation among populations are caused by random drift that should affect all loci across the genome in a similar manner. When a locus shows extraordinary high or low levels of population differentiation, this may be interpreted as evidence for natural selection. The most used measure of population differentiation was devised by Wright and is known as fixation index, or FST. We performed a genome-wide estimation of FST on about 4 millions of SNPs from HapMap project data. We demonstrated a heterogeneous distribution of FST values between autosomes and heterochromosomes. When we compared the FST values obtained in this study with another evolutionary measure obtained by comparative interspecific approach, we found that genes under positive selection appeared to show low levels of population differentiation. We applied a gene set approach, widely used for microarray data analysis, to detect functional pathways under selection. We found that one pathway related to antigen processing and presentation showed low levels of FST, while several pathways related to cell signalling, growth and morphogenesis showed high FST values. Finally, we detected a signature of selection within genes associated with human complex diseases. These results can help to identify which process occurred during human evolution and adaptation to different environments. They also support the hypothesis that common diseases could have a genetic background shaped by human evolution.
Niche theory is central to understanding how species respond geographically to climate change. It defines a species' realized niche in a biological community, its fundamental niche as determined by physiology, and its potential niche--the fundamental niche in a given environment or geographic space. However, most predictions of the effects of climate change on species' distributions are limited to correlative models of the realized niche, which assume that species are in distributional equilibrium with respect to the variables or gradients included in the model. Here, I present a mechanistic niche model that measures species' responses to major seasonal temperature gradients that interact with the physiology of the organism. I then use lethal physiological temperatures to parameterize the model for bird species in North and South America and show that most focal bird species are not in direct physiological equilibrium with the gradients. Results also show that most focal bird species possess broad thermal tolerances encompassing novel climates that could become available with climate change. I conclude with discussion of how mechanistic niche models may be used to (i) gain insights into the processes that cause species to respond to climate change and (ii) build more accurate correlative distribution models in birds and other species.
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