Comparative phylogeography of six herpetofauna species in Cyprus: late Miocene to Pleistocene colonization routes

The colonization patterns of oceanic islands are often interpreted through transmarine dispersal. However, in islands with intense human activities and unclear geological history, this inference may be inappropriate. Cyprus is such an island, whose geotectonic evolution has not been clarified yet to the desired level for biogeographical reconstructions, leaving the questions of ‘how the Cypriote biota arrived’ and ‘does the dispersal have the formative role in patterns of its diversification’ unanswered. Here, we address these issues through a reconstruction of the evolutionary history of six herptiles (Ablepharus budaki, Ophisops elegans, Acanthodactylus schreiberi, Telescopus fallax, Pelophylax cf. bedriagae, and Hyla savignyi) by means of mitochondrial DNA (cytochrome b and 16S rRNA), applying a Bayesian phylogenetic, biogeographical, and chronophylogenetic analyses. The phylogeographical analyses show that the colonization history of those species in Cyprus started in the late Miocene and extended into the Pliocene and Pleistocene, with geodispersal, transmarine dispersal, and human‐mediated dispersal having their share in shaping the diversification of Cypriote herptiles. The revealed patterns could be divided into three biogeographical categories: old colonizers that arrived in Cyprus during the late Miocene or early Pliocene either by a land bridge (geodispersal) which connected Cyprus with the mainland or by transmarine dispersal, younger colonizers that reached the island through transmarine dispersal from the Middle East, and new settlers that arrived through human‐induced (voluntary or not) introductions. This work advances our knowledge of the biogeography of Cyprus and highlights the need to consider both geo‐ and transmarine dispersal when dealing with islands whose associations do not have a straightforward interpretation. © 2013 The Linnean Society of London     

Cryptic diversity in flathead fishes (Scorpaeniformes: Platycephalidae) across the Indo‐West Pacific uncovered by DNA barcoding

Identification of taxonomical units underpins most biological endeavours ranging from accurate biodiversity estimates to the effective management of sustainably harvested, protected or endangered species. Successful species identification is now frequently based on a combination of approaches including morphometrics and DNA markers. Sequencing of the mitochondrial COI gene is an established methodology with an international campaign directed at barcoding all fishes. We employed COI sequencing alongside traditional taxonomic identification methods and uncovered instances of deep intraspecific genetic divergences among flathead species. Sixty‐five operational taxonomic units (OTUs) were observed across the Indo‐West Pacific from just 48 currently recognized species. The most comprehensively sampled taxon, Platycephalus indicus, exhibited the highest levels of genetic diversity with eight lineages separated by up to 16.37% genetic distance. Our results clearly indicate a thorough reappraisal of the current taxonomy of P. indicus (and its three junior synonyms) is warranted in conjunction with detailed taxonomic work on the other additional Platycephalidae OTUs detected by DNA barcoding.     

ProDeGe: a computational protocol for fully automated decontamination of genomes

Single amplified genomes and genomes assembled from metagenomes have enabled the exploration of uncultured microorganisms at an unprecedented scale. However, both these types of products are plagued by contamination. Since these genomes are now being generated in a high-throughput manner and sequences from them are propagating into public databases to drive novel scientific discoveries, rigorous quality controls and decontamination protocols are urgently needed. Here, we present ProDeGe (Protocol for fully automated Decontamination of Genomes), the first computational protocol for fully automated decontamination of draft genomes. ProDeGe classifies sequences into two classes—clean and contaminant—using a combination of homology and feature-based methodologies. On average, 84% of sequence from the non-target organism is removed from the data set (specificity) and 84% of the sequence from the target organism is retained (sensitivity). The procedure operates successfully at a rate of ~0.30 CPU core hours per megabase of sequence and can be applied to any type of genome sequence.Recent technological advancements have enabled the large-scale sampling of genomes from uncultured microbial taxa, through the high-throughput sequencing of single amplified genomes (SAGs; Rinke et al., 2013; Swan et al., 2013) and assembly and binning of genomes from metagenomes (GMGs; Cuvelier et al., 2010; Sharon and Banfield, 2013). The importance of these products in assessing community structure and function has been established beyond doubt (Kalisky and Quake, 2011). Multiple Displacement Amplification (MDA) and sequencing of single cells has been immensely successful in capturing rare and novel phyla, generating valuable references for phylogenetic anchoring. However, efforts to conduct MDA and sequencing in a high-throughput manner have been heavily impaired by contamination from DNA introduced by the environmental sample, as well as introduced during the MDA or sequencing process (Woyke et al., 2011; Engel et al., 2014; Field et al., 2014). Similarly, metagenome binning and assembly often carries various errors and artifacts depending on the methods used (Nielsen et al., 2014). Even cultured isolate genomes have been shown to lack immunity to contamination with other species (Parks et al., 2014; Mukherjee et al., 2015). As sequencing of these genome product types rapidly increases, contaminant sequences are finding their way into public databases as reference sequences. It is therefore extremely important to define standardized and automated protocols for quality control and decontamination, which would go a long way towards establishing quality standards for all microbial genome product types.Current procedures for decontamination and quality control of genome sequences in single cells and metagenome bins are heavily manual and can consume hours/megabase when performed by expert biologists. Supervised decontamination typically involves homology-based inspection of ribosomal RNA sequences and protein coding genes, as well as visual analysis of k-mer frequency plots and guanine–cytosine content (Clingenpeel, 2015). Manual decontamination is also possible through the software SmashCell (Harrington et al., 2010), which contains a tool for visual identification of contaminants from a self-organizing map and corresponding U-matrix. Another existing software tool, DeconSeq (Schmieder and Edwards, 2011), automatically removes contaminant sequences, however, the contaminant databases are required input. The former lacks automation, whereas the latter requires prior knowledge of contaminants, rendering both applications impractical for high-throughput decontamination.Here, we introduce ProDeGe, the first fully automated computational protocol for decontamination of genomes. ProDeGe uses a combination of homology-based and sequence composition-based approaches to separate contaminant sequences from the target genome draft. It has been pre-calibrated to discard at least 84% of the contaminant sequence, which results in retention of a median 84% of the target sequence. The standalone software is freely available at http://prodege.jgi-psf.org//downloads/src and can be run on any system that has Perl, R (R Core Team, 2014), Prodigal (Hyatt et al., 2010) and NCBI Blast (Camacho et al., 2009) installed. A graphical viewer allowing further exploration of data sets and exporting of contigs accompanies the web application for ProDeGe at http://prodege.jgi-psf.org, which is open to the wider scientific community as a decontamination service (Supplementary Figure S1).The assembly and corresponding NCBI taxonomy of the data set to be decontaminated are required inputs to ProDeGe (Figure 1a). Contigs are annotated with genes following which, eukaryotic contamination is removed based on homology of genes at the nucleotide level using the eukaryotic subset of NCBI''s Nucleotide database as the reference. For detecting prokaryotic contamination, a curated database of reference contigs from the set of high-quality genomes within the Integrated Microbial Genomes (IMG; Markowitz et al., 2014) system is used as the reference. This ensures that errors in public reference databases due to poor quality of sequencing, assembly and annotation do not negatively impact the decontamination process. Contigs determined as belonging to the target organism based on nucleotide level homology to sequences in the above database are defined as ‘Clean'', whereas those aligned to other organisms are defined as ‘Contaminant''. Contigs whose origin cannot be determined based on alignment are classified as ‘Undecided''. Classified clean and contaminated contigs are used to calibrate the separation in the subsequent 5-mer based binning module, which classifies undecided contigs as ‘Clean'' or ‘Contaminant'' using principal components analysis (PCA) of 5-mer frequencies. This parameter can also be specified by the user. When data sets do not have taxonomy deeper than phylum level, or a single confident taxonomic bin cannot be detected using sequence alignment, solely 9-mer based binning is used due to more accurate overall classification. In the absence of a user-defined cutoff, a pre-calibrated cutoff for 80% or more specificity separates the clean contigs from contaminated sequences in the resulting PCA of the 9-mer frequency matrix. Details on ProDeGe''s custom database, evaluation of the performance of the system and exploration of the parameter space to calibrate ProDeGe for a high accurate classification rate are provided in the Supplementary Material.Open in a separate windowFigure 1(a) Schematic overview of the ProDeGe engine. (b) Features of data sets used to validate ProDeGe: SAGs from the Arabidopsis endophyte sequencing project, MDM project, public data sets found in IMG but not sequenced at the JGI, as well as genomes from metagenomes. All the data and results can be found in Supplementary Table S3.The performance of ProDeGe was evaluated using 182 manually screened SAGs (Figure 1b,Supplementary Table S1) from two studies whose data sets are publicly available within the IMG system: genomes of 107 SAGs from an Arabidopsis endophyte sequencing project and 75 SAGs from the Microbial Dark Matter (MDM) project* (only 75/201 SAGs from the MDM project had 1:1 mapping between contigs in the unscreened and the manually screened versions, hence these were used; Rinke et al., 2013). Manual curation of these SAGs demonstrated that the use of ProDeGe prevented 5311 potentially contaminated contigs in these data sets from entering public databases. Figure 2a demonstrates the sensitivity vs specificity plot of ProDeGe results for the above data sets. Most of the data points in Figure 2a cluster in the top right of the box reflecting a median retention of 89% of the clean sequence (sensitivity) and a median rejection of 100% of the sequence of contaminant origin (specificity). In addition, on average, 84% of the bases of a data set are accurately classified. ProDeGe performs best when the target organism has sequenced homologs at the class level or deeper in its high-quality prokaryotic nucleotide reference database. If the target organism''s taxonomy is unknown or not deeper than domain level, or there are few contigs with taxonomic assignments, a target bin cannot be assessed and thus ProDeGe removes contaminant contigs using sequence composition only. The few samples in Figure 2a that demonstrate a higher rate of false positives (lower specificity) and/or reduced sensitivity typically occur when the data set contains few contaminant contigs or ProDeGe incorrectly assumes that the largest bin is the target bin. Some data sets contain a higher proportion of contamination than target sequence and ProDeGe''s performance can suffer under this condition. However, under all other conditions, ProDeGe demonstrates high speed, specificity and sensitivity (Figure 2). In addition, ProDeGe demonstrates better performance in overall classification when nucleotides are considered than when contigs are considered, illustrating that longer contigs are more accurately classified (Supplementary Table S1).Open in a separate windowFigure 2ProDeGe accuracy and performance scatterplots of 182 manually curated single amplified genomes (SAGs), where each symbol represents one SAG data set. (a) Accuracy shown by sensitivity (proportion of bases confirmed ‘Clean'') vs specificity (proportion of bases confirmed ‘Contaminant'') from the Endophyte and Microbial Dark Matter (MDM) data sets. Symbol size reflects input data set size in megabases. Most points cluster in the top right of the plot, showing ProDeGe''s high accuracy. Median and average overall results are shown in Supplementary Table S1. (b) ProDeGe completion time in central processing unit (CPU) core hours for the 182 SAGs. ProDeGe operates successfully at an average rate of 0.30 CPU core hours per megabase of sequence. Principal components analysis (PCA) of a 9-mer frequency matrix costs more computationally than PCA of a 5-mer frequency matrix used with blast-binning. The lack of known taxonomy for the MDM data sets prevents blast-binning, thus showing longer finishing times than the endophyte data sets, which have known taxonomy for use in blast-binning.All SAGs used in the evaluation of ProDeGe were assembled using SPAdes (Bankevich et al., 2012). In-house testing has shown that reads assembled with SPAdes from different strains or even slightly divergent species of the same genera may be combined into the same contig (Personal communications, KT and Robert Bowers). Ideally, the DNA in a well that gets sequenced belongs to a single cell. In the best case, contaminant sequences need to be at least from a different species to be recognized as such by the homology-based screening stage. In the absence of closely related sequenced organisms, contaminant sequences need to be at least from a different genus to be recognized as such by the composition-based screening stage (Supplementary Material). Thus, there is little risk of ProDeGe separating sequences from clonal populations or strains. We have found species- and genus-level contamination in MDA samples to be rare.To evaluate the quality of publicly available uncultured genomes, ProDeGe was used to screen 185 SAGs and 14 GMGs (Figure 1b). Compared with CheckM (Parks et al., 2014), a tool which calculates an estimate of genome sequence contamination using marker genes, ProDeGe generally marks a higher proportion of sequence as ‘Contaminant'' (Supplementary Table S2). This is because ProDeGe has been calibrated to perform at high specificity levels. The command line version of ProDeGe allows users to conduct their own calibration and specify a user-defined distance cutoff. Further, CheckM only outputs the proportion of contamination, but ProDeGe actually labels each contig as ‘Clean'' or ‘Contaminant'' during the process of automated removal.The web application for ProDeGe allows users to export clean and contaminant contigs, examine contig gene calls with their corresponding taxonomies, and discover contig clusters in the first three components of their k-dimensional space. Non-linear approaches for dimensionality reduction of k-mer vectors are gaining popularity (van der Maaten and Hinton, 2008), but we observed no systematic advantage of using t-Distributed Stochastic Neighbor Embedding over PCA (Supplementary Figure S2).ProDeGe is the first step towards establishing a standard for quality control of genomes from both cultured and uncultured microorganisms. It is valuable for preventing the dissemination of contaminated sequence data into public databases, avoiding resulting misleading analyses. The fully automated nature of the pipeline relieves scientists of hours of manual screening, producing reliably clean data sets and enabling the high-throughput screening of data sets for the first time. ProDeGe, therefore, represents a critical component in our toolkit during an era of next-generation DNA sequencing and cultivation-independent microbial genomics.     

Inter‐Fullerene Electronic Coupling Controls the Efficiency of Photoinduced Charge Generation in Organic Bulk Heterojunctions

Photoinduced charge generation (PCG) dynamics are notoriously difficult to correlate with specific molecular properties in device relevant polymer:fullerene organic photovoltaic blend films due to the highly complex nature of the solid state blend morphology. Here, this study uses six judiciously selected trifluoromethylfullerenes blended with the prototypical polymer poly(3‐hexylthiophene) and measure the PCG dynamics in 50 fs–500 ns time scales with time‐resolved microwave conductivity and femtosecond transient absorption spectroscopy. The isomeric purity and thorough chemical characterization of the fullerenes used in this study allow for a detailed correlation between molecular properties, driving force, local intermolecular electronic coupling and, ultimately, the efficiency of PCG yield. The findings show that the molecular design of the fullerene not only determines inter‐fullerene electronic coupling, but also influences the decay dynamics of free holes in the donor phase even when the polymer microstructure remains unchanged.     

A New Species of <Emphasis Type="Italic">Prolibytherium</Emphasis> (Ruminantia,Mammalia) from Pakistan,and the Functional Implications of an Atypical Atlanto-Occipital Morphology

We describe a new species of Prolibytherium, P. fusus, sp. nov., from the lower Miocene of Pakistan, thus extending the genus to Asia. Prolibytherium is otherwise known only from Libya. This species differs from Prolibytherium magnieri in several basioccipital and atlanto-occipital morphologies. Namely, the posterior basioccipital tuberosities are continuous at the midline and lack the elevated transverse ridge seen in P. magnieri, and the notch formed between the lateral occipital condyles and paraoccipital process is lower. Both species of Prolibytherium have a characteristic ventrally fused occipital condyle at the midline, with a notably fuller circumferential articular surface. Prolibytherium magnieri also has thickened dorsal and ventral arches of the atlas. These specimens also possess a longitudinal groove for the Eustachian tube extending from the alisphenoid canal to the bullae, and a second deep grove isolating the basisphenoid bone from the temporal bone. These, plus several other atlanto-occipital morphologies strengthen the cervical support of the head. This is especially important for Prolibytherium, as the taxon possesses massive aliform cranial appendages. We relate the approximation of the occipital condyles to a convergent state in two giraffids (Giraffokeryx punjabiensis and Schansitherium tafeli), each of which possesses multiple pairs of ossicones, presumably necessitating a strengthened atlanto-occipital joint.     

Enterobacter sp. AA26 gut symbiont as a protein source for Mediterranean fruit fly mass-rearing and sterile insect technique applications

Background

The interaction between gut bacterial symbionts and Tephritidae became the focus of several studies that showed that bacteria contributed to the nutritional status and the reproductive potential of its fruit fly hosts. Anastrepha fraterculus is an economically important fruit pest in South America. This pest is currently controlled by insecticides, which prompt the development of environmentally friendly methods such as the sterile insect technique (SIT). For SIT to be effective, a deep understanding of the biology and sexual behavior of the target species is needed. Although many studies have contributed in this direction, little is known about the composition and role of A. fraterculus symbiotic bacteria. In this study we tested the hypothesis that gut bacteria contribute to nutritional status and reproductive success of A. fraterculus males.

Results

AB affected the bacterial community of the digestive tract of A. fraterculus, in particular bacteria belonging to the Enterobacteriaceae family, which was the dominant bacterial group in the control flies (i.e., non-treated with AB). AB negatively affected parameters directly related to the mating success of laboratory males and their nutritional status. AB also affected males’ survival under starvation conditions. The effect of AB on the behaviour and nutritional status of the males depended on two additional factors: the origin of the males and the presence of a proteinaceous source in the diet.

Conclusions

Our results suggest that A. fraterculus males gut contain symbiotic organisms that are able to exert a positive contribution on A. fraterculus males’ fitness, although the physiological mechanisms still need further studies.

     

Micropropagation and molecular characterization of Thymus sibthorpii Benth. (Lamiaceae), an aromatic-medicinal thyme with ornamental value and conservation concern

Thymus sibthorpii Benth. (Lamiaceae), with accession number 01,1796-22, is a biotype of native Greek thyme with ascending stems and potential use as a new medicinal-aromatic crop and ornamental plant. An efficient and reliable protocol for in vitro clonal propagation of T. sibthorpii from nodes and meristem tip explants was developed. Shoot proliferation succeeded on a new basal medium (BB) without plant growth regulators, as prior experiments with 6-benzyladenine generated hyperhydricity. Eight different basal media were compared; on two formulations using the new BB 5.9 and 5.6 shoots per explant were produced. Regenerated single shoots were rooted in the BB medium, supplemented with 5 μM of indole-3-butyric acid, and produced 3.1 roots along with 2.5 adventitious shoots. Three types of acclimatization were assessed: in vitro, using two different systems (no significant differences); ex vitro, using eight soil substrates under greenhouse and outdoor nursery conditions (in two of them, 100% of plantlets survived); and in field cultivations, established at eight geographically distant areas of Greece (100% survival rate at all locations). Molecular characterization of T. sibthorpii was evaluated with one nuclear ribosomal DNA and seven chloroplast DNA markers, followed by DNA sequence comparisons with a total of 30 different Thymus species, subspecies, and varieties. The trnH/psbA, trnL/trnF, and matK genes were the most efficient markers for molecular characterization of T. sibthorpii. The molecular markers rpoC1 and petB/petD did not match to any Thymus species and therefore, these DNA sequences provide new sequence information for entire Thymus taxa.

     

Identification of Protein-Tyrosine Phosphatases in Archaea

Protein-tyrosine dephosphorylation is a major mechanism in cellular regulation. A large number of protein-tyrosine phosphatases is known from Eukarya, and more recently bacterial homologues have also been identified. By employing conserved sequence patterns from both eukaryotic and bacterial protein-tyrosine phosphatases, we have identified three homologous sequences in two of the four complete archaeal genomes. Two hypothetical open reading frames in the genome of Methanococcus jannaschii (MJ0215 and MJECL20) and one in the genome of Pyrococcus horikoshii (PH1732) clearly bear all the conserved residues of this family. No homologues were found in the genomes of Archaeoglobus fulgidus and Methanobacterium thermoautotrophicum. This is the first report of protein-tyrosine phosphatase sequences in Archaea. Received: 29 April 1998 / Accepted: 27 November 1998