ABSTRACT
The innate immunity of Drosophila melanogaster is based on cellular and humoral components. Drosophila Helical factor (Hf), is a molecule previously discovered using an in silico approach and whose expression is controlled by the immune deficiency (Imd) pathway. Here we present evidence demonstrating that Hf is an inducible protein constitutively produced by the S2 hemocyte-derived cell line. Hf expression is stimulated by bacterial extracts that specifically trigger the Imd pathway. In absence of any bacterial challenge, the recombinant form of Hf can influence the expression of the antimicrobial peptides (AMPs) defensin but not drosomycin. These data suggest that in vitro Hf is an inducible and immune-regulated factor, with functions comparable to those of secreted vertebrate cytokines.
Subject(s)
Cytokines/physiology , Drosophila Proteins/physiology , Animals , Base Sequence , Cell Line , DNA Primers , Drosophila Proteins/immunology , Drosophila melanogaster , Polymerase Chain ReactionABSTRACT
European sardine or pilchard is a planktonic small pelagic fish present from the North Sea in Europe to the coast of Senegal in the North of Africa, and across the Mediterranean sea to the Black Sea. Ecologically, sardines are an intermediary link in the trophic network, preying on plankton and being predated by larger fishes, marine mammals, and seabirds. This species is of great nutritional and economic value as a cheap but rich source of protein and fat. It is either consumed directly by humans or fed as fishmeal for aquaculture and farm animals. Despite its importance in the food basket, little is known about the molecular mechanisms involved in protein and lipid synthesis in this species. We collected nine tissues of Sardina pilchardus and reconstructed the transcriptome. In all, 198,597 transcripts were obtained, from which 68,031 are protein-coding. Quality assessment of the transcriptome was performed by back-mapping reads to the transcriptome and by searching for Single Copy Orthologs. Additionally, Gene Ontology and KEGG annotations were retrieved for most of the protein-coding genes. Finally, each library was quantified in terms of Transcripts per Million to disclose their expression patterns.
ABSTRACT
For population genetic studies in nonmodel organisms, it is important to use every single source of genomic information. This paper presents EXFI, a Python pipeline that predicts the splice graph and exon sequences using an assembled transcriptome and raw whole-genome sequencing reads. The main algorithm uses Bloom filters to remove reads that are not part of the transcriptome, to predict the intron-exon boundaries, to then proceed to call exons from the assembly, and to generate the underlying splice graph. The results are returned in GFA1 format, which encodes both the predicted exon sequences and how they are connected to form transcripts. EXFI is written in Python, tested on Linux platforms, and the source code is available under the MIT License at https://github.com/jlanga/exfi.
ABSTRACT
Tench (Tinca tinca L.) has great economic potential due to its high rate of fecundity and long-life span. Population genetic studies based on allozymes, microsatellites, PCR-RFLP and sequence analysis of genes and DNA fragments have revealed the presence of Eastern and Western phylogroups. However, the lack of genomic resources for this species has complicated the development of genetic markers. In this study, the tench transcriptome and genome were sequenced by high-throughput sequencing. A total of 60,414 putative SNPs were identified in the tench transcriptome using a computational pipeline. A set of 96 SNPs was selected for validation and a total of 92 SNPs was validated, resulting in the highest conversion and validation rate for a non-model species obtained to date (95.83%). The validated SNPs were used to genotype 140 individuals belonging to two tench breeds (Tabor and Hungarian), showing low (FST = 0.0450) but significant (<0.0001) genetic differentiation between the two tench breeds. This implies that set of validated SNPs array can be used to distinguish the tench breeds and that it might be useful for studying a range of associations between DNA sequence and traits of importance. These genomic resources created for the tench will provide insight into population genetics, conservation fish stock management, and aquaculture.
Subject(s)
Cyprinidae/genetics , Animals , Breeding , Cyprinidae/classification , Czech Republic , Female , Fisheries , Gene Ontology , Genetic Markers , Genetics, Population , Genome , Male , Phylogeny , Polymorphism, Single Nucleotide , Species Specificity , TranscriptomeABSTRACT
An empirical investigation of how local harmonic structures (e.g., chord progressions) contribute to the experience and enjoyment of uplifting trance (UT) music is presented. The connection between rhythmic and percussive elements and resulting trance-like states has been highlighted by musicologists, but no research, to our knowledge, has explored whether repeated harmonic elements influence affective responses in listeners of trance music. Two alternative hypotheses are discussed, the first highlighting the direct relationship between repetition/complexity and enjoyment, and the second based on the theoretical inverted-U relationship described by the Wundt curve. We investigate the connection between harmonic structure and subjective enjoyment through interdisciplinary behavioral and computational methods: First we discuss an experiment in which listeners provided enjoyment ratings for computer-generated UT anthems with varying levels of harmonic repetition and complexity. The anthems were generated using a statistical model trained on a corpus of 100 uplifting trance anthems created for this purpose, and harmonic structure was constrained by imposing particular repetition structures (semiotic patterns defining the order of chords in the sequence) on a professional UT music production template. Second, the relationship between harmonic structure and enjoyment is further explored using two computational approaches, one based on average Information Content, and another that measures average tonal tension between chords. The results of the listening experiment indicate that harmonic repetition does in fact contribute to the enjoyment of uplifting trance music. More compelling evidence was found for the second hypothesis discussed above, however some maximally repetitive structures were also preferred. Both computational models provide evidence for a Wundt-type relationship between complexity and enjoyment. By systematically manipulating the structure of chord progressions, we have discovered specific harmonic contexts in which repetitive or complex structure contribute to the enjoyment of uplifting trance music.
ABSTRACT
GnRH-II peptide hormone exhibits complete sequence conservation across vertebrate species, including man. Type-II GnRH receptor genes have been characterized recently in nonhuman primates, but the human receptor gene homolog contains a frameshift, a premature stop codon (UGA), and a 3' overlap of the RBM8A gene on chromosome 1q.12. A retrotransposed pseudogene, RBM8B, retains partial receptor sequence. In this study, bioinformatics show that the human receptor gene promoter overlaps the peroxisomal protein 11-beta gene promoter and the premature UGA is positionally conserved in chimpanzee. A CGA [arginine (Arg)] occurs in porcine DNA, but UGA is shifted one codon to the 5' direction in bovine DNA, suggesting independent evolution of premature stop codons. In contrast to marmoset tissue RNA, exon- and strand-specific probes are required to distinguish differently spliced human receptor gene transcripts in cell lines (HP75, IMR-32). RBM8B is not transcribed. Sequencing of cDNAs for spliced receptor mRNAs showed no evidence for alteration of the premature UGA by RNA editing, but alternative splicing circumvents the frameshift to encode a two-membrane-domain protein before this UGA. A stem-loop motif resembling a selenocysteine insertion sequence and a potential alternative translation initiation site might enable expression of further proteins involved in interactions within the GnRH system.
Subject(s)
Chromosomes, Human, Pair 1 , Evolution, Molecular , Receptors, LHRH/genetics , Transcriptional Activation/genetics , Adenoma , Alternative Splicing/genetics , Amino Acid Sequence , Animals , Blotting, Northern , Breast Neoplasms , Callithrix , Choriocarcinoma , DNA, Antisense , Endometrial Neoplasms , Female , Humans , Jurkat Cells , Male , Molecular Sequence Data , Neuroblastoma , Nucleic Acid Conformation , Open Reading Frames/genetics , Phylogeny , Pituitary Neoplasms , Promoter Regions, Genetic/genetics , Prostatic Neoplasms , Reverse Transcriptase Polymerase Chain Reaction , Selenocysteine/genetics , Sequence Homology, Nucleic AcidABSTRACT
Cytokines are an important class of proteins responsible for intercellular communication. The helical cytokines have a four-helix bundle fold, and they have remained largely intractable for sequence alignment methods due to their high evolutionary divergence. This paper presents a method that is specifically designed to recognize the helical cytokine fold in preprotein sequences such as full-length cDNA translations or transcripts predicted by gene finding methods. A protein fold is modeled by multiple sequence profiles, each representing a structurally conserved region. Nonstructural profiles are used to represent additional signals found in preprotein sequences. Profiles are connected by loop regions, each of a specified minimum and maximum length. A model for the helical cytokines is created by progressively improving a placement of four amphipathic helices onto training sequences. The sensitivity and specificity of the method are evaluated by a cross-validation procedure, demonstrating that cytokines with no intrafamily sequence similarity can be recognized. The method has been successfully used for the discovery of several new helical cytokines in the human genome.
Subject(s)
Computational Biology , Cytokines/chemistry , Amino Acid Motifs , Cytokines/genetics , Evolution, Molecular , Humans , Multigene Family , Protein Structure, TertiaryABSTRACT
Cytokines are important mediators of host defense and immunity, and were first identified for their role in immunity to infections. It was then found that some of them are pathogenic mediators in inflammatory diseases and much of the emphasis is now on pro-inflammatory cytokines, also in consideration of the fact that TNF inhibitors became effective drugs in chronic inflammatory diseases. The recent studies on the tissue-protective activities of erythropoietin (EPO) led to the term "tissue-protective cytokine." We discuss here how tissue-protective actions might be common to other cytokines, particularly those of the 4-alpha helical structural superfamily.
Subject(s)
Cytokines/metabolism , Animals , Cytokines/chemistry , Erythropoietin/metabolism , Invertebrates/metabolism , Models, BiologicalABSTRACT
Increased throughput in sequencing technologies has facilitated the acquisition of detailed genomic information in non-model species. The focus of this research was to discover and validate SNPs derived from the European anchovy (Engraulis encrasicolus) transcriptome, a species with no available reference genome, using next generation sequencing technologies. A cDNA library was constructed from four tissues of ten fish individuals corresponding to three populations of E. encrasicolus, and Roche 454 GS FLX Titanium sequencing yielded 19,367 contigs. Additionally, the European anchovy genome was sequenced for the same ten individuals using an Illumina HiSeq2000. Using a computational pipeline for combining transcriptome and genome information, a total of 18,994 SNPs met the necessary minor allele frequency and depth filters. A series of further stringent filters were applied to identify those SNPs likely to succeed in genotyping assays, and for filtering of those in potential duplicated genome regions. A novel method for detecting potential intron-exon boundaries in areas of putative SNPs has also been applied in silico to improve genotyping success. In all, 2,317 filtered putative transcriptome SNPs suitable for genotyping primer design were identified. From those, a subset of 530 were selected, with the genotyping results showing the highest reported conversion and validation rates (91.3% and 83.2%, respectively) reported to date for a non-model species. This study represents a promising strategy to discover genotypable SNPs in the exome of non-model organisms. The genomic resource generated for E. encrasicolus, both in terms of sequences and novel markers, will be informative for research into this species with applications including traceability studies, population genetic analyses and aquaculture.
Subject(s)
Fishes/genetics , Gene Expression Profiling , Genomics , High-Throughput Nucleotide Sequencing , Polymorphism, Single Nucleotide , Sequence Analysis, DNA , Sequence Analysis, RNA , Animals , Chromosome Mapping , Exons/genetics , Genetic Loci/genetics , Genetic Markers/genetics , Genotyping Techniques , Introns/genetics , Microsatellite Repeats/genetics , Molecular Sequence AnnotationABSTRACT
MOTIVATION: Gene finding remains an open problem well after the sequencing of the human genome. The low gene sensitivity of current methods is a problem for divergent protein families, because fairly accurate exon assemblies are required before sensitive fold recognition algorithms can be applied. This paper presents a new genomic threading algorithm which integrates the gene finding and fold recognition steps into a single process. The method is applicable to evolutionarily divergent protein families that have retained some trace of their common ancestry, number and phase of introns, sizes of exons and placement of structural elements on specific exons. Such conserved structural signals may be visible despite dramatic evolution of protein sequence. RESULTS: The method is evaluated on the family of helical cytokines by cross-validation sensitivity analysis. The method has also been applied to all intergenic regions of the human genome, and an expression and cloning approach has been coupled with the predictions of the method. Two genes discovered by this method are discussed. SUPPLEMENTARY INFORMATION: All data used and the results obtained in the cross-validation analysis are available at http://www.soi.city.ac.uk/~conklin/papers/GT/
Subject(s)
Algorithms , Chromosome Mapping/methods , Cytokines/chemistry , Cytokines/genetics , Exons/genetics , Genome, Human , Sequence Analysis, DNA/methods , Humans , Protein Conformation , Protein Folding , Structure-Activity RelationshipABSTRACT
MOTIVATION: Gene expression is dependent on two main types of signals; one involving transcription factors which initiates gene transcription, and another which regulates the translation of a nascent mRNA. These post-transcriptional events play an important yet incompletely understood role in regulating gene expression and cellular behavior. Many of the identified cis acting elements for translational regulation occur within the 3'untranslated region (3' UTR), and some have been observed to occur with surprising regularity within certain protein function classes. RESULTS: In this study, we present a new association rule mining method for discovering nucleotide sequence patterns that appear in more sequences than expected within protein function classes. The method is applied to a database of human 3' UTR sequences, and some significant associations between nucleotide patterns and protein function classes are discovered. Among previously identified patterns, the AU-Rich Element (ARE) is found here to occur within the 3' UTR of cytokines, providing statistical validation of an association often reported in the literature. The method has also identified some GC-rich patterns, found to occur within the 3' UTR of homeodomain transcription factors and nuclear proteins. The method should be applicable to many types of regulatory element discovery.
Subject(s)
3' Untranslated Regions , Algorithms , Base Composition , Cluster Analysis , Computational Biology , Cytokines/genetics , Databases, Nucleic Acid , Gene Expression Regulation , Humans , Pattern Recognition, AutomatedABSTRACT
MOTIVATION: Many of the most interesting functional and evolutionary relationships among proteins are so ancient that they cannot be reliably detected through sequence analysis and are apparent only through a comparison of the tertiary structures. The conserved features can often be described as structural motifs consisting of a few single residues or Secondary Structure (SS) elements. Confidence in such motifs is greatly boosted when they are found in more than a pair of proteins. RESULTS: We describe an algorithm for the automatic discovery of recurring patterns in protein structures. The patterns consist of individual residues having a defined order along the protein's backbone that come close together in the structure and whose spatial conformations are similar. The residues in a pattern need not be close in the protein's sequence. The work described in this paper builds on an earlier reported algorithm for motif discovery. This paper describes a significant improvement of the algorithm which makes it very efficient. The improved efficiency allows us to use it for doing unsupervised learning of patterns occurring in small subsets in a large set of structures, a non-redundant subset of the Protein Data Bank (PDB) database of all known protein structures.