A phylogenetic generalized hidden Markov model for predicting alternatively spliced exons

BACKGROUND: An important challenge in eukaryotic gene prediction is accurate identification of alternatively spliced exons. Functional transcripts can go undetected in gene expression studies when alternative splicing only occurs under specific biological conditions. Non-expression based computational methods support identification of rarely expressed transcripts. RESULTS: A non-expression based statistical method is presented to annotate alternatively spliced exons using a single genome sequence and evidence from cross-species sequence conservation. The computational method is implemented in the program ExAlt and an analysis of prediction accuracy is given for Drosophila melanogaster. CONCLUSION: ExAlt identifies the structure of most alternatively spliced exons in the test set and cross-species sequence conservation is shown to improve the precision of predictions. The software package is available to run on Drosophila genomes to search for new cases of alternative splicing

Unifying generative and discriminative learning principles

<p>Abstract</p> <p>Background</p> <p>The recognition of functional binding sites in genomic DNA remains one of the fundamental challenges of genome research. During the last decades, a plethora of different and well-adapted models has been developed, but only little attention has been payed to the development of different and similarly well-adapted learning principles. Only recently it was noticed that discriminative learning principles can be superior over generative ones in diverse bioinformatics applications, too.</p> <p>Results</p> <p>Here, we propose a generalization of generative and discriminative learning principles containing the maximum likelihood, maximum a posteriori, maximum conditional likelihood, maximum supervised posterior, generative-discriminative trade-off, and penalized generative-discriminative trade-off learning principles as special cases, and we illustrate its efficacy for the recognition of vertebrate transcription factor binding sites.</p> <p>Conclusions</p> <p>We find that the proposed learning principle helps to improve the recognition of transcription factor binding sites, enabling better computational approaches for extracting as much information as possible from valuable wet-lab data. We make all implementations available in the open-source library Jstacs so that this learning principle can be easily applied to other classification problems in the field of genome and epigenome analysis.</p

Apples and oranges: avoiding different priors in Bayesian DNA sequence analysis

<p>Abstract</p> <p>Background</p> <p>One of the challenges of bioinformatics remains the recognition of short signal sequences in genomic DNA such as donor or acceptor splice sites, splicing enhancers or silencers, translation initiation sites, transcription start sites, transcription factor binding sites, nucleosome binding sites, miRNA binding sites, or insulator binding sites. During the last decade, a wealth of algorithms for the recognition of such DNA sequences has been developed and compared with the goal of improving their performance and to deepen our understanding of the underlying cellular processes. Most of these algorithms are based on statistical models belonging to the family of Markov random fields such as position weight matrix models, weight array matrix models, Markov models of higher order, or moral Bayesian networks. While in many comparative studies different learning principles or different statistical models have been compared, the influence of choosing different prior distributions for the model parameters when using different learning principles has been overlooked, and possibly lead to questionable conclusions.</p> <p>Results</p> <p>With the goal of allowing direct comparisons of different learning principles for models from the family of Markov random fields based on the <it>same a-priori information</it>, we derive a generalization of the commonly-used product-Dirichlet prior. We find that the derived prior behaves like a Gaussian prior close to the maximum and like a Laplace prior in the far tails. In two case studies, we illustrate the utility of the derived prior for a direct comparison of different learning principles with different models for the recognition of binding sites of the transcription factor Sp1 and human donor splice sites.</p> <p>Conclusions</p> <p>We find that comparisons of different learning principles using the same a-priori information can lead to conclusions different from those of previous studies in which the effect resulting from different priors has been neglected. We implement the derived prior is implemented in the open-source library Jstacs to enable an easy application to comparative studies of different learning principles in the field of sequence analysis.</p

The Germ Cell Nuclear Proteins hnRNP G-T and RBMY Activate a Testis-Specific Exon

The human testis has almost as high a frequency of alternative splicing events as brain. While not as extensively studied as brain, a few candidate testis-specific splicing regulator proteins have been identified, including the nuclear RNA binding proteins RBMY and hnRNP G-T, which are germ cell-specific versions of the somatically expressed hnRNP G protein and are highly conserved in mammals. The splicing activator protein Tra2β is also highly expressed in the testis and physically interacts with these hnRNP G family proteins. In this study, we identified a novel testis-specific cassette exon TLE4-T within intron 6 of the human transducing-like enhancer of split 4 (TLE4) gene which makes a more transcriptionally repressive TLE4 protein isoform. TLE4-T splicing is normally repressed in somatic cells because of a weak 5′ splice site and surrounding splicing-repressive intronic regions. TLE4-T RNA pulls down Tra2β and hnRNP G proteins which activate its inclusion. The germ cell-specific RBMY and hnRNP G-T proteins were more efficient in stimulating TLE4-T incorporation than somatically expressed hnRNP G protein. Tra2b bound moderately to TLE4-T RNA, but more strongly to upstream sites to potently activate an alternative 3′ splice site normally weakly selected in the testis. Co-expression of Tra2β with either hnRNP G-T or RBMY re-established the normal testis physiological splicing pattern of this exon. Although they can directly bind pre-mRNA sequences around the TLE4-T exon, RBMY and hnRNP G-T function as efficient germ cell-specific splicing co-activators of TLE4-T. Our study indicates a delicate balance between the activity of positive and negative splicing regulators combinatorially controls physiological splicing inclusion of exon TLE4-T and leads to modulation of signalling pathways in the testis. In addition, we identified a high-affinity binding site for hnRNP G-T protein, showing it is also a sequence-specific RNA binding protein

Conscious uncoupling between FANCI and FANCD2 in DNA repair

The Fanconi anemia (FA)-BRCA pathway mediates repair of DNA interstrand crosslinks. The FA core complex, a multi-subunit ubiquitin ligase, participates in the detection of DNA lesions and monoubiquitinates two downstream FA proteins, FANCD2 and FANCI (or the ID complex). However, the regulation of the FA core complex itself is poorly understood. Here we show that the FA core complex proteins are recruited to sites of DNA damage and form nuclear foci in S and G2 phases of the cell cycle. ATR kinase activity, an intact FA core complex and FANCM-FAAP24 were crucial for this recruitment. Surprisingly, FANCI, but not its partner FANCD2, was needed for efficient FA core complex foci formation. Monoubiquitination or ATR-dependent phosphorylation of FANCI were not required for the FA core complex recruitment, but FANCI deubiquitination by USP1 was. Additionally, BRCA1 was required for efficient FA core complex foci formation. These findings indicate that FANCI functions upstream of FA core complex recruitment independently of FANCD2, and alter the current view of the FA-BRCA pathway

Primary Human mDC1, mDC2, and pDC Dendritic Cells Are Differentially Infected and Activated by Respiratory Syncytial Virus

Respiratory syncytial virus (RSV) causes recurrent infections throughout life. Vaccine development may depend upon understanding the molecular basis for induction of ineffective immunity. Because dendritic cells (DCs) are critically involved in early responses to infection, their interaction with RSV may determine the immunological outcome of RSV infection. Therefore, we investigated the ability of RSV to infect and activate primary mDCs and pDCs using recombinant RSV expressing green fluorescent protein (GFP). At a multiplicity of infection of 5, initial studies demonstrated ∼6.8% of mDC1 and ∼0.9% pDCs were infected. We extended these studies to include CD1c−CD141+ mDC2, finding mDC2 infected at similar frequencies as mDC1. Both infected and uninfected cells upregulated phenotypic markers of maturation. Divalent cations were required for infection and maturation, but maturation did not require viral replication. There is evidence that attachment and entry/replication processes exert distinct effects on DC activation. Cell-specific patterns of RSV-induced maturation and cytokine production were detected in mDC1, mDC2, and pDC. We also demonstrate for the first time that RSV induces significant TIMP-2 production in all DC subsets. Defining the influence of RSV on the function of selected DC subsets may improve the likelihood of achieving protective vaccine-induced immunity

Defining the Role of the MHC in Autoimmunity: A Review and Pooled Analysis

The major histocompatibility complex (MHC) is one of the most extensively studied regions in the human genome because of the association of variants at this locus with autoimmune, infectious, and inflammatory diseases. However, identification of causal variants within the MHC for the majority of these diseases has remained difficult due to the great variability and extensive linkage disequilibrium (LD) that exists among alleles throughout this locus, coupled with inadequate study design whereby only a limited subset of about 20 from a total of approximately 250 genes have been studied in small cohorts of predominantly European origin. We have performed a review and pooled analysis of the past 30 years of research on the role of the MHC in six genetically complex disease traits – multiple sclerosis (MS), type 1 diabetes (T1D), systemic lupus erythematosus (SLE), ulcerative colitis (UC), Crohn's disease (CD), and rheumatoid arthritis (RA) – in order to consolidate and evaluate the current literature regarding MHC genetics in these common autoimmune and inflammatory diseases. We corroborate established MHC disease associations and identify predisposing variants that previously have not been appreciated. Furthermore, we find a number of interesting commonalities and differences across diseases that implicate both general and disease-specific pathogenetic mechanisms in autoimmunity

Genomic view of the evolution of the complement system

The recent accumulation of genomic information of many representative animals has made it possible to trace the evolution of the complement system based on the presence or absence of each complement gene in the analyzed genomes. Genome information from a few mammals, chicken, clawed frog, a few bony fish, sea squirt, fruit fly, nematoda and sea anemone indicate that bony fish and higher vertebrates share practically the same set of complement genes. This suggests that most of the gene duplications that played an essential role in establishing the mammalian complement system had occurred by the time of the teleost/mammalian divergence around 500 million years ago (MYA). Members of most complement gene families are also present in ascidians, although they do not show a one-to-one correspondence to their counterparts in higher vertebrates, indicating that the gene duplications of each gene family occurred independently in vertebrates and ascidians. The C3 and factor B genes, but probably not the other complement genes, are present in the genome of the cnidaria and some protostomes, indicating that the origin of the central part of the complement system was established more than 1,000 MYA