Coalescent-based genome analyses resolve the early branches of the euarchontoglires

Despite numerous large-scale phylogenomic studies, certain parts of the mammalian tree are extraordinarily difficult to resolve. We used the coding regions from 19 completely sequenced genomes to study the relationships within the super-clade Euarchontoglires (Primates, Rodentia, Lagomorpha, Dermoptera and Scandentia) because the placement of Scandentia within this clade is controversial. The difficulty in resolving this issue is due to the short time spans between the early divergences of Euarchontoglires, which may cause incongruent gene trees. The conflict in the data can be depicted by network analyses and the contentious relationships are best reconstructed by coalescent-based analyses. This method is expected to be superior to analyses of concatenated data in reconstructing a species tree from numerous gene trees. The total concatenated dataset used to study the relationships in this group comprises 5,875 protein-coding genes (9,799,170 nucleotides) from all orders except Dermoptera (flying lemurs). Reconstruction of the species tree from 1,006 gene trees using coalescent models placed Scandentia as sister group to the primates, which is in agreement with maximum likelihood analyses of concatenated nucleotide sequence data. Additionally, both analytical approaches favoured the Tarsier to be sister taxon to Anthropoidea, thus belonging to the Haplorrhine clade. When divergence times are short such as in radiations over periods of a few million years, even genome scale analyses struggle to resolve phylogenetic relationships. On these short branches processes such as incomplete lineage sorting and possibly hybridization occur and make it preferable to base phylogenomic analyses on coalescent methods

Wandering behaviour prevents inter and intra oceanic speciation in a coastal pelagic fish

Small pelagic fishes have the ability to disperse over long distances and may present complex evolutionary histories. Here, Old World Anchovies (OWA) were used as a model system to understand genetic patterns and connectivity of fish between the Atlantic and Pacific basins. We surveyed 16 locations worldwide using mtDNA and 8 microsatellite loci for genetic parameters, and mtDNA (cyt b; 16S) and nuclear (RAG1; RAG2) regions for dating major lineage-splitting events within Engraulidae family. The OWA genetic divergences (0-0.4%) are compatible with intra-specific divergence, showing evidence of both ancient and contemporary admixture between the Pacific and Atlantic populations, enhanced by high asymmetrical migration from the Pacific to the Atlantic. The estimated divergence between Atlantic and Pacific anchovies (0.67 [0.53-0.80] Ma) matches a severe drop of sea temperature during the Gunz glacial stage of the Pleistocene. Our results support an alternative evolutionary scenario for the OWA, suggesting a coastal migration along south Asia, Middle East and eastern Africa continental platforms, followed by the colonization of the Atlantic via the Cape of the Good Hope.Portuguese Foundation for Science & Technology (FCT) [SFRH/BD/36600/2007]; FCT [UID/MAR/04292/2013, SFRH/BPD/65830/2009]; FCT strategic plan [UID/Multi/04326/2013]info:eu-repo/semantics/publishedVersio

Coevolution of amino acid residues in the key photosynthetic enzyme Rubisco

<p>Abstract</p> <p>Background</p> <p>One of the key forces shaping proteins is coevolution of amino acid residues. Knowing which residues coevolve in a particular protein may facilitate our understanding of protein evolution, structure and function, and help to identify substitutions that may lead to desired changes in enzyme kinetics. Rubisco, the most abundant enzyme in biosphere, plays an essential role in the process of carbon fixation through photosynthesis, thus facilitating life on Earth. This makes Rubisco an important model system for studying the dynamics of protein fitness optimization on the evolutionary landscape. In this study we investigated the selective and coevolutionary forces acting on large subunit of land plants Rubisco using Markov models of codon substitution and clustering approaches applied to amino acid substitution histories.</p> <p>Results</p> <p>We found that both selection and coevolution shape Rubisco, and that positively selected and coevolving residues have their specifically favored amino acid composition and pairing preference. The mapping of these residues on the known Rubisco tertiary structures showed that the coevolving residues tend to be in closer proximity with each other compared to the background, while positively selected residues tend to be further away from each other. This study also reveals that the residues under positive selection or coevolutionary force are located within functionally important regions and that some residues are targets of both positive selection and coevolution at the same time.</p> <p>Conclusion</p> <p>Our results demonstrate that coevolution of residues is common in Rubisco of land plants and that there is an overlap between coevolving and positively selected residues. Knowledge of which Rubisco residues are coevolving and positively selected could be used for further work on structural modeling and identification of substitutions that may be changed in order to improve efficiency of this important enzyme in crops.</p

Selective Constraints on Amino Acids Estimated by a Mechanistic Codon Substitution Model with Multiple Nucleotide Changes

Empirical substitution matrices represent the average tendencies of substitutions over various protein families by sacrificing gene-level resolution. We develop a codon-based model, in which mutational tendencies of codon, a genetic code, and the strength of selective constraints against amino acid replacements can be tailored to a given gene. First, selective constraints averaged over proteins are estimated by maximizing the likelihood of each 1-PAM matrix of empirical amino acid (JTT, WAG, and LG) and codon (KHG) substitution matrices. Then, selective constraints specific to given proteins are approximated as a linear function of those estimated from the empirical substitution matrices. Akaike information criterion (AIC) values indicate that a model allowing multiple nucleotide changes fits the empirical substitution matrices significantly better. Also, the ML estimates of transition-transversion bias obtained from these empirical matrices are not so large as previously estimated. The selective constraints are characteristic of proteins rather than species. However, their relative strengths among amino acid pairs can be approximated not to depend very much on protein families but amino acid pairs, because the present model, in which selective constraints are approximated to be a linear function of those estimated from the JTT/WAG/LG/KHG matrices, can provide a good fit to other empirical substitution matrices including cpREV for chloroplast proteins and mtREV for vertebrate mitochondrial proteins. The present codon-based model with the ML estimates of selective constraints and with adjustable mutation rates of nucleotide would be useful as a simple substitution model in ML and Bayesian inferences of molecular phylogenetic trees, and enables us to obtain biologically meaningful information at both nucleotide and amino acid levels from codon and protein sequences.Comment: Table 9 in this article includes corrections for errata in the Table 9 published in 10.1371/journal.pone.0017244. Supporting information is attached at the end of the article, and a computer-readable dataset of the ML estimates of selective constraints is available from 10.1371/journal.pone.001724

Radiation Campaign of HPK Prototype LGAD sensors for the High-Granularity Timing Detector (HGTD)

We report on the results of a radiation campaign with neutrons and protons of Low Gain Avalanche Detectors (LGAD) produced by Hamamatsu (HPK) as prototypes for the High-Granularity Timing Detector (HGTD) in ATLAS. Sensors with an active thickness of 50~$\mu$m were irradiated in steps of roughly 2$\times$ up to a fluence of $3\times10^{15}~\mathrm{n_{eq}cm^{-2}}$. As a function of the fluence, the collected charge and time resolution of the irradiated sensors will be reported for operation at $-30^{\circ}$

Phylogeography of Japanese encephalitis virus:genotype is associated with climate

The circulation of vector-borne zoonotic viruses is largely determined by the overlap in the geographical distributions of virus-competent vectors and reservoir hosts. What is less clear are the factors influencing the distribution of virus-specific lineages. Japanese encephalitis virus (JEV) is the most important etiologic agent of epidemic encephalitis worldwide, and is primarily maintained between vertebrate reservoir hosts (avian and swine) and culicine mosquitoes. There are five genotypes of JEV: GI-V. In recent years, GI has displaced GIII as the dominant JEV genotype and GV has re-emerged after almost 60 years of undetected virus circulation. JEV is found throughout most of Asia, extending from maritime Siberia in the north to Australia in the south, and as far as Pakistan to the west and Saipan to the east. Transmission of JEV in temperate zones is epidemic with the majority of cases occurring in summer months, while transmission in tropical zones is endemic and occurs year-round at lower rates. To test the hypothesis that viruses circulating in these two geographical zones are genetically distinct, we applied Bayesian phylogeographic, categorical data analysis and phylogeny-trait association test techniques to the largest JEV dataset compiled to date, representing the envelope (E) gene of 487 isolates collected from 12 countries over 75 years. We demonstrated that GIII and the recently emerged GI-b are temperate genotypes likely maintained year-round in northern latitudes, while GI-a and GII are tropical genotypes likely maintained primarily through mosquito-avian and mosquito-swine transmission cycles. This study represents a new paradigm directly linking viral molecular evolution and climate

A comparison of common programming languages used in bioinformatics

<p>Abstract</p> <p>Background</p> <p>The performance of different programming languages has previously been benchmarked using abstract mathematical algorithms, but not using standard bioinformatics algorithms. We compared the memory usage and speed of execution for three standard bioinformatics methods, implemented in programs using one of six different programming languages. Programs for the Sellers algorithm, the Neighbor-Joining tree construction algorithm and an algorithm for parsing BLAST file outputs were implemented in C, C++, C#, Java, Perl and Python.</p> <p>Results</p> <p>Implementations in C and C++ were fastest and used the least memory. Programs in these languages generally contained more lines of code. Java and C# appeared to be a compromise between the flexibility of Perl and Python and the fast performance of C and C++. The relative performance of the tested languages did not change from Windows to Linux and no clear evidence of a faster operating system was found.</p> <p>Source code and additional information are available from <url>http://www.bioinformatics.org/benchmark/</url></p> <p>Conclusion</p> <p>This benchmark provides a comparison of six commonly used programming languages under two different operating systems. The overall comparison shows that a developer should choose an appropriate language carefully, taking into account the performance expected and the library availability for each language.</p

Lineage Divergence and Historical Gene Flow in the Chinese Horseshoe Bat (Rhinolophus sinicus)

PMCID: PMC3581519This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Destructive breakdown studies of irradiated LGADs at beam tests for the ATLAS HGTD

In the past years, it has been observed at several beam test campaigns that irradiated LGAD sensors break with a typical star shaped burn mark when operated at voltages much lower than those at which they were safely operated during laboratory tests. The study presented in this paper was designed to determine the safe operating voltage that these sensors can withstand. Many irradiated sensors from various producers were tested in two test beam facilities, DESY (Hamburg) and CERN-SPS (Geneva), as part of ATLAS High Granularity Timing Detector (HGTD) beam tests. The samples were placed in the beam and kept under bias over a long period of time in order to reach a high number of particles crossing each sensor. Both beam tests lead to a similar conclusion, that these destructive events begin to occur when the average electric field in the sensor becomes larger than 12 Volts per micrometre.Comment: Published versio