Unexpected correlations between gene expression and codon usage bias from microarray data for the whole Escherichia coli K-12 genome

Escherichia coli has long been regarded as a model organism in the study of codon usage bias (CUB). However, most studies in this organism regarding this topic have been computational or, when experimental, restricted to small datasets; particularly poor attention has been given to genes with low CUB. In this work, correspondence analysis on codon usage is used to classify E.coli genes into three groups, and the relationship between them and expression levels from microarray experiments is studied. These groups are: group 1, highly biased genes; group 2, moderately biased genes; and group 3, AT-rich genes with low CUB. It is shown that, surprisingly, there is a negative correlation between codon bias and expression levels for group 3 genes, i.e. genes with extremely low codon adaptation index (CAI) values are highly expressed, while group 2 show the lowest average expression levels and group 1 show the usual expected positive correlation between CAI and expression. This trend is maintained over all functional gene groups, seeming to contradict the E.coli–yeast paradigm on CUB. It is argued that these findings are still compatible with the mutation–selection balance hypothesis of codon usage and that E.coli genes form a dynamic system shaped by these factors

Solving the riddle of codon usage preferences: a test for translational selection

Translational selection is responsible for the unequal usage of synonymous codons in protein coding genes in a wide variety of organisms. It is one of the most subtle and pervasive forces of molecular evolution, yet, establishing the underlying causes for its idiosyncratic behaviour across living kingdoms has proven elusive to researchers over the past 20 years. In this study, a statistical model for measuring translational selection in any given genome is developed, and the test is applied to 126 fully sequenced genomes, ranging from archaea to eukaryotes. It is shown that tRNA gene redundancy and genome size are interacting forces that ultimately determine the action of translational selection, and that an optimal genome size exists for which this kind of selection is maximal. Accordingly, genome size also presents upper and lower boundaries beyond which selection on codon usage is not possible. We propose a model where the coevolution of genome size and tRNA genes explains the observed patterns in translational selection in all living organisms. This model finally unifies our understanding of codon usage across prokaryotes and eukaryotes. Helicobacter pylori, Saccharomyces cerevisiae and Homo sapiens are codon usage paradigms that can be better understood under the proposed model

Population genetics and substitution models of adaptive evolution

24 pages, 4 figures and 1 table. Manuscript written between January and April 201024 pages, 4 figures and 1 table. Manuscript written between January and April 201024 pages, 4 figures and 1 table. Manuscript written between January and April 2010The ratio of non-synonymous to synonymous substitutions $\omega(=d_{N}/d_{S})$ has been widely used as a measure of adaptive evolution in protein coding genes. Omega can be defined in terms of population genetics parameters as the fixation ratio of selected vs. neutral mutants. Here it is argued that approaches based on the infinite sites model are not appropriate to define $\omega$ for single codon locations. Simple models of amino acid substitution with reversible mutation and selection are analysed, and used to define $\omega$ under several evolutionary scenarios. In most practical cases $\omega1$ can be sometimes expected for single locations at equilibrium. An example with influenza data is discussed

The impact of ancestral population size and incomplete lineage sorting on Bayesian estimation of species divergence times

MdR was supported by Biotechnology and Biological Sciences Research Council (UK) grant BB/J009709/1 awarded to ZY

Pengaruh Kondisi Tanah Terhadap Kerusakan Jalan Menggunakan Metode (PCI) Tirto Rahhayu Landung Sari Desa Mulyoagung Kecamatan Dau Kabupaten Malang

Tanah adalah suatu himpunan mineral, bahan organik, dan endapan-endapan relatif lepas,salah satunya pada konstruksi jalan raya.tanah sebagai pondasi sangat berpengaruh terhadap kualitas pelayanan dan kondisi konstruksi jalan. Kondisi ini terjadi di Jalan Tirto Rahayu Landung Sari-Desa Mulyoagung Kecamatan Dau Kabupaten Malang yang merupakan obyek penelitian.Dari hasil penelitian yang dilakukan sepanjang 1000 m yang di bagi menjadi 200 m persegmen di Jalan Tirto Rahayu Landung Sari Desa Mulyoagung Kecamatan Dau Kabupaten Malang,kondisi jalan mengalami kerusakan.Hal ini dilihat dari kerusakan permukaan aspal yang terkelupas,retak, dan berlubang.Nilai rata-rata Pavement Condition Index (PCI) jalan Tirto Rahayu Landung Sari Desa Mulyoagung Kecanatan Dau Kabupaten Malang yaitu 44 Cukup (Fair),jenis tanah setelah di lakukan penelitian dan lolos ayakan 200 = 35% tanah berbutir sebagian besar lanau dan lempung.hasil analisa saringan lolos ayakan 200,20,dan 10 yaitu batu pecah,kerikil,dan pasir.hasil analisa kadar air rata-rata yaitu 54,05%,hasil rata-rata nilai plastisitas yaitu 1,1 % < 10 % sehingga rata-rata tingkat plastisitas segmen rendah dengan jenis tanah Lanau.hasil nilai rata-rata CBR dan DDT menggunakan alat DCP yaitu sebesar 2,43 % < 5 % dengan nilai DDT sebesar 3,36. jalan ini perlu dimasukan dalam program pemiliharaan secara berkala dan Pemilihan perkerasan dalam menggulangi kerusakan pada jalan ini yaitu menggunakan perkerasan lentu

A mutation-selection model of protein evolution underpersistent positive selection

We use first principles of population genetics to model the evolution of proteins under persistent positive selection (PPS). PPS may occur when organisms are subjected to persistent environmental change, during adaptive radiations, or in host-pathogen interactions. Our mutation-selection model indicates protein evolution under PPS is an irreversible Markov process, and thus proteins under PPS show a strongly asymmetrical distribution of selection coefficients among amino acid substitutions. Our model shows the criteria ω > 1 (where ω is the ratio of non-synonymous over synonymous codon substitution rates) to detect positive selection is conservative and indeed arbitrary, because in real proteins many mutations are highly deleterious and are removed by selection even at positively-selected sites. We use a penalized-likelihood implementation of the PPS model to successfully detect PPS in plant RuBisCO and influenza HA proteins. By directly estimating selection coefficients at protein sites, our inference procedure bypasses the need for using ω as a surrogate measure of selection and improves our ability to detect molecular adaptation in proteins

Organização da coleção entomológica da Embrapa Florestas.

Resumo

Gauge invariance of the background average effective action

Using the background field method for the functional renormalization group approach in the case of a generic gauge theory, we study the background field symmetry and gauge dependence of the background average effective action, when the regulator action depends on external fields. The final result is that the symmetry of the average effective action can be maintained for a wide class of regulator functions, but in all cases the dependence of the gauge fixing remains on-shell. The Yang-Mills theory is considered as the main particular example.Comment: Fits the version accepted in EPJ

The impact of the rate prior on Bayesian estimation of divergence times with multiple Loci.

Bayesian methods provide a powerful way to estimate species divergence times by combining information from molecular sequences with information from the fossil record. With the explosive increase of genomic data, divergence time estimation increasingly uses data of multiple loci (genes or site partitions). Widely used computer programs to estimate divergence times use independent and identically distributed (i.i.d.) priors on the substitution rates for different loci. The i.i.d. prior is problematic. As the number of loci (L) increases, the prior variance of the average rate across all loci goes to zero at the rate 1/L. As a consequence, the rate prior dominates posterior time estimates when many loci are analyzed, and if the rate prior is misspecified, the estimated divergence times will converge to wrong values with very narrow credibility intervals. Here we develop a new prior on the locus rates based on the Dirichlet distribution that corrects the problematic behavior of the i.i.d. prior. We use computer simulation and real data analysis to highlight the differences between the old and new priors. For a dataset for six primate species, we show that with the old i.i.d. prior, if the prior rate is too high (or too low), the estimated divergence times are too young (or too old), outside the bounds imposed by the fossil calibrations. In contrast, with the new Dirichlet prior, posterior time estimates are insensitive to the rate prior and are compatible with the fossil calibrations. We re-analyzed a phylogenomic data set of 36 mammal species and show that using many fossil calibrations can alleviate the adverse impact of a misspecified rate prior to some extent. We recommend the use of the new Dirichlet prior in Bayesian divergence time estimation. [Bayesian inference, divergence time, relaxed clock, rate prior, partition analysis.].This work was supported by Biotechnology and Biological Sciences Research Council (BBSRC), UK, grant BB/J009709/1. Z.Y. is a Royal Society Wolfson Merit award holder. T.Z. is supported by Natural Science Foundation of China (NSF) grants (31301093, 11301294 and 11201224)