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      cDNA and Gene Structure of MytiLec-1, A Bacteriostatic R-Type Lectin from the Mediterranean Mussel ( Mytilus galloprovincialis)

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          Abstract

          MytiLec is an α- d-galactose-binding lectin with a unique primary structure isolated from the Mediterranean mussel ( Mytilus galloprovincialis). The lectin adopts a β-trefoil fold that is also found in the B-sub-unit of ricin and other ricin-type (R-type) lectins. We are introducing MytiLec(-1) and its two variants (MytiLec-2 and -3), which both possess an additional pore-forming aerolysin-like domain, as members of a novel multi-genic “mytilectin family” in bivalve mollusks. Based on the full length mRNA sequence (911 bps), it was possible to elucidate the coding sequence of MytiLec-1, which displays an extended open reading frame (ORF) at the 5′ end of the sequence, confirmed both at the mRNA and at the genomic DNA sequence level. While this extension could potentially produce a polypeptide significantly longer than previously reported, this has not been confirmed yet at the protein level. MytiLec-1 was revealed to be encoded by a gene consisting of two exons and a single intron. The first exon comprised the 5′UTR and the initial ATG codon and it was possible to detect a putative promoter region immediately ahead of the transcription start site in the MytiLec-1 genomic locus. The remaining part of the MytiLec-1 coding sequence (including the three sub-domains, the 3′UTR and the poly-A signal) was included in the second exon. The bacteriostatic activity of MytiLec-1 was determined by the agglutination of both Gram-positive and Gram-negative bacteria, which was reversed by the co-presence of α-galactoside. Altogether, these data support the classification of MytiLec-1 as a member of the novel mytilectin family and suggest that this lectin may play an important role as a pattern recognition receptor in the innate immunity of mussels.

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          Improved splice site detection in Genie.

          We present an improved splice site predictor for the genefinding program Genie. Genie is based on a generalized Hidden Markov Model (GHMM) that describes the grammar of a legal parse of a multi-exon gene in a DNA sequence. In Genie, probabilities are estimated for gene features by using dynamic programming to combine information from multiple content and signal sensors, including sensors that integrate matches to homologous sequences from a database. One of the hardest problems in genefinding is to determine the complete gene structure correctly. The splice site sensors are the key signal sensors that address this problem. We replaced the existing splice site sensors in Genie with two novel neural networks based on dinucleotide frequencies. Using these novel sensors, Genie shows significant improvements in the sensitivity and specificity of gene structure identification. Experimental results in tests using a standard set of annotated genes showed that Genie identified 86% of coding nucleotides correctly with a specificity of 85%, versus 80% and 84% in the older system. In further splice site experiments, we also looked at correlations between splice site scores and intron and exon lengths, as well as at the effect of distance to the nearest splice site on false positive rates.
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            Application of a time-delay neural network to promoter annotation in the Drosophila melanogaster genome.

            Computational methods for automated genome annotation are critical to understanding and interpreting the bewildering mass of genomic sequence data presently being generated and released. A neural network model of the structural and compositional properties of a eukaryotic core promoter region has been developed and its application for analysis of the Drosophila melanogaster genome is presented. The model uses a time-delay architecture, a special case of a feed-forward neural network. The structure of this model allows for variable spacing between functional binding sites, which is known to play a key role in the transcription initiation process. Application of this model to a test set of core promoters not only gave better discrimination of potential promoter sites than previous statistical or neural network models, but also revealed indirectly subtle properties of the transcription initiation signal. When tested in the Adh region of 2.9 Mbases of the Drosophila genome, the neural network for promoter prediction (NNPP) program that incorporates the time-delay neural network model gives a recognition rate of 75% (69/92) with a false positive rate of 1/547 bases. The present work can be regarded as one of the first intensive studies that applies novel gene regulation technologies to the identification of the complex gene regulation sites in the genome of Drosophila melanogaster.
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              Comparative population genomics in animals uncovers the determinants of genetic diversity.

              Genetic diversity is the amount of variation observed between DNA sequences from distinct individuals of a given species. This pivotal concept of population genetics has implications for species health, domestication, management and conservation. Levels of genetic diversity seem to vary greatly in natural populations and species, but the determinants of this variation, and particularly the relative influences of species biology and ecology versus population history, are still largely mysterious. Here we show that the diversity of a species is predictable, and is determined in the first place by its ecological strategy. We investigated the genome-wide diversity of 76 non-model animal species by sequencing the transcriptome of two to ten individuals in each species. The distribution of genetic diversity between species revealed no detectable influence of geographic range or invasive status but was accurately predicted by key species traits related to parental investment: long-lived or low-fecundity species with brooding ability were genetically less diverse than short-lived or highly fecund ones. Our analysis demonstrates the influence of long-term life-history strategies on species response to short-term environmental perturbations, a result with immediate implications for conservation policies.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Mar Drugs
                Mar Drugs
                marinedrugs
                Marine Drugs
                MDPI
                1660-3397
                11 May 2016
                May 2016
                : 14
                : 5
                : 92
                Affiliations
                [1 ]Department of Life and Environmental System Science, Graduate School of NanoBio Sciences, Yokohama City University, 22-2 Seto, Kanazawa-ku, Yokohama 236-0027, Japan; hasanimtiaj@ 123456yahoo.co.uk (I.H.); rajia_bio@ 123456yahoo.com (S.R.); yasukoide04@ 123456yahoo.co.jp (Y.K.); r-ui@ 123456outlook.jp (D.Y.); akawsarabe@ 123456yahoo.com (S.M.A.K.)
                [2 ]Department of Biochemistry and Molecular Biology, Faculty of Science, University of Rajshahi, Rajshahi 6205, Bangladesh
                [3 ]Department of Life Sciences, University of Trieste, Via Licio Giorgieri 5, Trieste 34127, Italy; mgerdol@ 123456units.it
                [4 ]Department of Pharmacy, Faculty of Pharmaceutical Science, Nagasaki International University, 2825-7 Huis Ten Bosch, Sasebo, Nagasaki 859-3298, Japan; yfujii@ 123456niu.ac.jp
                [5 ]Department of Natural Science, Varendra University, Rajshahi 6204, Bangladesh
                [6 ]Department of Chemistry, Faculty of Sciences, University of Chittagong, Chittagong 4331, Bangladesh
                Author notes
                [* ]Correspondence: ozeki@ 123456yokohama-cu.ac.jp ; Tel.: +81-45-787-2221; Fax: +81-45-787-2413
                Article
                marinedrugs-14-00092
                10.3390/md14050092
                4882566
                27187419
                a1a11b97-4dd6-4ee0-9939-254692a2d44d
                © 2016 by the authors; licensee MDPI, Basel, Switzerland.

                This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 17 March 2016
                : 28 April 2016
                Categories
                Article

                Pharmacology & Pharmaceutical medicine
                bacteriostatic activity,cdna,gene,innate immunity,mytilectin family,mytilus galloprovincialis,mrna-sequence,mytilec-1,r-type lectin

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