Missed, not missing: Phylogenomic evidence for the existence of Avian FoxP3

The Forkhead box transcription factor FoxP3 is pivotal to the development and function of regulatory T cells (Tregs), which make a major contribution to peripheral tolerance. FoxP3 is believed to perform a regulatory role in all the vertebrate species in which it has been detected. The prevailing view is that FoxP3 is absent in birds and that avian Tregs rely on alternative developmental and suppressive pathways. Prompted by the automated annotation of foxp3 in the ground tit (Parus humilis) genome, we have questioned this assumption. Our analysis of all available avian genomes has revealed that the foxp3 locus is missing, incomplete or of poor quality in the relevant genomic assemblies for nearly all avian species. Nevertheless, in two species, the peregrine falcon (Falco peregrinus) and the saker falcon (F. cherrug), there is compelling evidence for the existence of exons showing synteny with foxp3 in the ground tit. A broader phylogenomic analysis has shown that FoxP3 sequences from these three species are similar to crocodilian sequences, the closest living relatives of birds. In both birds and crocodilians, we have also identified a highly proline-enriched region at the N terminus of FoxP3, a region previously identified only in mammals

A Study on Fish Classification Techniques using Convolutional Neural Networks on Highly Challenged Underwater Images

Underwater Fish Species Recognition (UFSR) has attained significance because of evolving research in underwater life. Manual techniques to distinguish fish can be tricky and tedious. They might require enormous inspecting endeavours, but they can be costly. It results in limited data and a lack of human resources, which may cause incorrect object identification. Automating the fish species detection and recognition utilizing technology would assist sea life science to evolve further. UFSR in wild natural habitats is difficult because the images open natural habitat, complex background, and low luminance. Species Visualization can assist us with deep knowledge of the movements of the species underwater. Automation systems can help to classify the fish accurately and consistently. Image classification has been emerging research with the advancement of deep learning systems. The reason is that the convolutional neural networks (CNNs) don't require explicit feature extraction methods. The vast majority of the current object detection and recognition mechanisms are based on images in the outdoor environment. This paper mainly reviews the strategies proposed in the past years for underwater fish detection and classification. Further, the paper also presents the classification of three different underwater datasets using CNN with evaluation metrics

Spot the match – wildlife photo-identification using information theory

BACKGROUND: Effective approaches for the management and conservation of wildlife populations require a sound knowledge of population demographics, and this is often only possible through mark-recapture studies. We applied an automated spot-recognition program (I(3)S) for matching natural markings of wildlife that is based on a novel information-theoretic approach to incorporate matching uncertainty. Using a photo-identification database of whale sharks (Rhincodon typus) as an example case, the information criterion (IC) algorithm we developed resulted in a parsimonious ranking of potential matches of individuals in an image library. Automated matches were compared to manual-matching results to test the performance of the software and algorithm. RESULTS: Validation of matched and non-matched images provided a threshold IC weight (approximately 0.2) below which match certainty was not assured. Most images tested were assigned correctly; however, scores for the by-eye comparison were lower than expected, possibly due to the low sample size. The effect of increasing horizontal angle of sharks in images reduced matching likelihood considerably. There was a negative linear relationship between the number of matching spot pairs and matching score, but this relationship disappeared when using the IC algorithm. CONCLUSION: The software and use of easily applied information-theoretic scores of match parsimony provide a reliable and freely available method for individual identification of wildlife, with wide applications and the potential to improve mark-recapture studies without resorting to invasive marking techniques

SynBlast: Assisting the analysis of conserved synteny information

<p>Abstract</p> <p>Motivation</p> <p>In the last years more than 20 vertebrate genomes have been sequenced, and the rate at which genomic DNA information becomes available is rapidly accelerating. Gene duplication and gene loss events inherently limit the accuracy of orthology detection based on sequence similarity alone. Fully automated methods for orthology annotation do exist but often fail to identify individual members in cases of large gene families, or to distinguish missing data from traceable gene losses. This situation can be improved in many cases by including conserved synteny information.</p> <p>Results</p> <p>Here we present the <monospace>SynBlast</monospace> pipeline that is designed to construct and evaluate local synteny information. <monospace>SynBlast</monospace> uses the genomic region around a focal reference gene to retrieve candidates for homologous regions from a collection of target genomes and ranks them in accord with the available evidence for homology. The pipeline is intended as a tool to aid high quality manual annotation in particular in those cases where automatic procedures fail. We demonstrate how <monospace>SynBlast</monospace> is applied to retrieving orthologous and paralogous clusters using the vertebrate <it>Hox </it>and <it>ParaHox </it>clusters as examples.</p> <p>Software</p> <p>The <monospace>SynBlast</monospace> package written in <monospace>Perl</monospace> is available under the GNU General Public License at <url>http://www.bioinf.uni-leipzig.de/Software/SynBlast/</url>.</p

Promiscuous Speciation with Gene Flow in Silverside Fish Genus Odontesthes (Atheriniformes, Atherinopsidae) from South Western Atlantic Ocean Basins

The present paper integrates phylogenetic and population genetics analyses based on mitochondrial and nuclear molecular markers in silversides, genus Odontesthes, from a non-sampled area in the SW Atlantic Ocean to address species discrimination and to define Managements Units for sustainable conservation. All phylogenetic analyses based on the COI mitochondrial gene were consistent to support the monophyly of the genus Odontesthes and to include O. argentinensis, O. perugiae-humensis and some O. bonariensis haplotypes in a basal polytomy conforming a major derivative clade. Microsatellites data revealed somewhat higher genetic variability values in the O. argentinensis-perugia populations than in O. bonariensis and O. perugia-humensis taxa. Contrasting population genetics structuring emerged from mitochondrial and microsatellites analyses in these taxa. Whereas mitochondrial data supported two major groups (O. argentinensis-perugia-humensis vs. O. bonariensis-perugiae-humensis populations), microsatellite data detected three major genetic entities represented by O. bonariensis, O. perugiae-humensis and an admixture of populations belonging to O. argentinensis-perugiae respectively. Therefore, the star COI polytomy in the tree topology involving these taxa could be interpreted by several hypothetic scenarios such as the existence of shared ancestral polymorphisms, incomplete lineage sorting in a radiating speciation process and/or reticulation events. Present findings support that promiscuous and recent contact between incipient species sharing asymmetric gene flow exchanges, blurs taxa boundaries yielding complicated taxonomy and Management Units delimitation in silverside genus Odontesthes from SW Atlantic Ocean basins.This research received financial support from the project Fondo María Viñas_2009_1_2793 (FMV_2009_1_2793_Project) granted by the Agencia Nacional de Investigación e Inovación (ANII) of UruguayS

SynBlast: Assisting the Analysis of Conserved Synteny Information

Motivation: In the last years more than 20 vertebrate genomes have been sequenced, and the rate at which genomic DNA information becomes available is rapidly accelerating. Gene duplication and gene loss events inherently limit the accuracy of orthology detection based on sequence similarity alone. Fully automated methods for orthology annotation do exist but often fail to identify individual members in cases of large gene families, or to distinguish missing data from traceable gene losses. This situation can be improved in many cases by including conserved synteny information. Results: Here we present the SynBlast pipeline that is designed to construct and evaluate local synteny information. SynBlast uses the genomic region around a focal reference gene to retrieve candidates for homologous regions from a collection of target genomes and ranks them in accord with the available evidence for homology. The pipeline is intended as a tool to aid high quality manual annotation in particular in those cases where automatic procedures fail. We demonstrate how SynBlast is applied to retrieving orthologous and paralogous clusters using the vertebrate Hox and ParaHox clusters as examples

The Borrelia afzelii outer membrane protein BAPKO_0422 binds human Factor-H and is predicted to form a membrane-spanning beta-barrel

The deep evolutionary history of the Spirochetes places their branch point early in the evolution of the diderms, before the divergence of the present day Proteobacteria. As a Spirochete, the morphology of the Borrelia cell envelope shares characteristics of both Gram-positive and Gram-negative bacteria. A thin layer of peptidoglycan, tightly associated with the cytoplasmic membrane is surrounded by a more labile outer membrane (OM). This OM is rich in lipoproteins but with few known integral membrane proteins. The OmpA domain is an eight-stranded membrane-spanning β-barrel, highly conserved among the Proteobacteria but so far unknown in the Spirochetes. In the present work we describe the identification of four novel OmpA-like β-barrels from Borrelia afzelii, the most common cause of erythema migrans rash in Europe. Structural characterisation of one these proteins (BAPKO_0422) by small angle X-ray scattering (SAXS) and circular dichroism indicate a compact globular structure rich in β-strand consistent with a monomeric β-barrel. Ab initio molecular envelopes calculated from the scattering profile are consistent with homology models and demonstrate that BAPKO_0422 adopts a peanut shape with dimensions 25 x 45 Å. Deviations from the standard C-terminal signature sequence are apparent; in particular the C-terminal Phe residue commonly found in Proteobacterial OM proteins is replaced by Ile/Leu or Asn. BAPKO_0422 is demonstrated to bind human factor-H and therefore may contribute to immune evasion by inhibition of the complement response. Encoded by chromosomal genes, these proteins are highly conserved between Borrelia subspecies and may be of diagnostic or therapeutic value

Spectrogram classification using dissimilarity space

In this work, we combine a Siamese neural network and different clustering techniques to generate a dissimilarity space that is then used to train an SVM for automated animal audio classification. The animal audio datasets used are (i) birds and (ii) cat sounds, which are freely available. We exploit different clustering methods to reduce the spectrograms in the dataset to a number of centroids that are used to generate the dissimilarity space through the Siamese network. Once computed, we use the dissimilarity space to generate a vector space representation of each pattern, which is then fed into an support vector machine (SVM) to classify a spectrogram by its dissimilarity vector. Our study shows that the proposed approach based on dissimilarity space performs well on both classification problems without ad-hoc optimization of the clustering methods. Moreover, results show that the fusion of CNN-based approaches applied to the animal audio classification problem works better than the stand-alone CNNs

NcDNAlign: Plausible multiple alignments of non-protein-coding genomic sequences

Genome-wide multiple sequence alignments (MSAs) are a necessary prerequisite for an increasingly diverse collection of comparative genomic approaches. Here we present a versatile method that generates high-quality MSAs for non-protein-coding sequences. The NcDNAlign pipeline combines pairwise BLAST alignments to create initial MSAs, which are then locally improved and trimmed. The program is optimized for speed and hence is particulary well-suited to pilot studies. We demonstrate the practical use of NcDNAlign in three case studies: the search for ncRNAs in gammaproteobacteria and the analysis of conserved noncoding DNA in nematodes and teleost fish, in the latter case focusing on the fate of duplicated ultra-conserved regions. Compared to the currently widely used genome-wide alignment program TBA, our program results in a 20- to 30-fold reduction of CPU time necessary to generate gammaproteobacterial alignments. A showcase application of bacterial ncRNA prediction based on alignments of both algorithms results in similar sensitivity, false discovery rates, and up to 100 putatively novel ncRNA structures. Similar findings hold for our application of NcDNAlign to the identification of ultra-conserved regions in nematodes and teleosts. Both approaches yield conserved sequences of unknown function, result in novel evolutionary insights into conservation patterns among these genomes, and manifest the benefits of an efficient and reliable genome-wide alignment package. The software is available under the GNU Public License at http://www.bioinf.uni-leipzig.de/Software/NcDNAlign/